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- """
- @Time : 2024-03-04
- @Author : Wei
- @FileName: DiagnosisLib.py
- @Software: 故障诊断函数库
- """
- import numpy as np
- import matplotlib.pyplot as plt
- from math import pi
- from scipy import signal
- from scipy import interpolate
- import math
- class DiagnosisLib:
-
- def __init__(self):
- pass
- ###############################################################################
- ###############################################################################
- # 半带滤波器系数
- def halfbandcoefficient(self):
- halfbandcoefficient = np.array([0.00000063557331607068,0,-0.00000627255234261115,0,0.00002474955105003003,0,\
- -0.00007140981582044673,0,0.00017237915446870680,0,-0.00036863887543283979,0,\
- 0.00072039609678193576,0,-0.00131147951710543810,0,0.00225360507770744260,0,\
- -0.00369069002024503300,0,0.00580407535380912750,0,-0.00882079299392407940,0,\
- 0.01302944110367636400,0,-0.01881320502983020000,0,0.02672090662754737100,0,\
- -0.03762627155576255700,0,0.05311294860790129200,0,-0.07653440360979835200,0,\
- 0.11663131038150232000,0,-0.20562506738991029000,0,0.63439761518650584000,1,\
- 0.63439761518650584000,0,-0.20562506738991029000,0,0.11663131038150232000,0,\
- -0.07653440360979835200,0,0.05311294860790129200,0,-0.03762627155576255700,0,\
- 0.02672090662754737100,0,-0.01881320502983020000,0,0.01302944110367636400,0,\
- -0.00882079299392407940,0,0.00580407535380912750,0,-0.00369069002024503300,0,\
- 0.00225360507770744260,0,-0.00131147951710543810,0,0.00072039609678193576,0,\
- -0.00036863887543283979,0,0.00017237915446870680,0,-0.00007140981582044673,0,\
- 0.00002474955105003003,0,-0.00000627255234261115,0,0.00000063557331607068])
- return halfbandcoefficient
- ###############################################################################
- ###############################################################################
- # 计算时域波形均值
- def Average(self,xTimeWave):
- return sum(xTimeWave) / len(xTimeWave)
- ###############################################################################
- ###############################################################################
- # 计算时域波形xTimeWave的频谱
- # fs是时域波形的采样频率,单位是Hz
- # 调用代码须保证输入时域波形xTimeWave的数据点数为2的N幂
- # 频谱计算默认采用汉宁窗
- # 输出为频谱的x轴freq即频率,单位是Hz, 和频谱的y轴,单位是时域波形的幅值单位
- # x轴和y轴的数据点数为输入时域波形xTimeWave数据点数的1/2.56倍+1,即1024点时域波形
- # 输出频谱的x轴和y轴分别有401点数据,2048点时域波形时,输出频谱的x轴和y轴分别有801点数据。
-
- def Spectrum(self,xTimeWave,fs):
- DataLen = len(xTimeWave)
- xSpec = abs(np.fft.fft((xTimeWave*np.hanning(DataLen))))/DataLen*4
- freq = np.arange(0, fs / 2.56 + fs / DataLen, fs / DataLen)
-
- return [freq, xSpec[0:int(DataLen/2.56)+1]]
-
- ###############################################################################
- ###############################################################################
- # 计算时域波形xTimeWave的幅值谱倒频谱
- # fs是时域波形的采样频率,单位是Hz
- # 调用代码须保证输入时域波形xTimeWave的数据点数为2的N幂
- # 输出为倒谱的x轴quefrency,单位是秒,倒谱的幅值单位是dB
- def Cepstrum(self,xTimeWave,fs):
- # cepstrum = np.abs(np.fft.ifft(np.log(np.absolute(np.fft.fft(xTimeWave)))))
- cepstrum = 20*np.log((np.abs(np.fft.ifft(np.log(np.abs(np.fft.fft(xTimeWave))))))/0.1)
- quefrency = np.array(range(len(xTimeWave)))/fs
-
- return [quefrency,cepstrum]
-
- ###############################################################################
- ###############################################################################
- # 计算频谱xSpec的固定频率特征值,xSpec是频谱的y轴数组,其数据点数为101,201,401,801,1601,3201,6401,12801
- # fMax是频谱的分析频宽,单位为Hz
- # fTarget是特征频率的目标值,单位为Hz。比如轴的转频,齿轮啮合频率,水泵叶片通过频率等等
- # fRange是特征频率的搜索范围,其输入值根据fRangeMode的不同值而不一样,
- # fRangeMode可以赋值0或1,默认值是0。当fRangeMode = 0时,fRange的值是xx%, 比如 2%(实际输入为0.02) ,
- # 此时搜索范围是 fTarge +/- fTarge*fRange/2。
- # 当fRangeMode = 1时,fRange的值是频率值,比如2Hz,
- # 此时的搜索范围就是 fTarge +/- fRange/2
- # Detection是特征值的峰值(此时输入0),有效值(输入1),峰峰值(输入2)
- # numHarmonics为谐波数,0代表不需要考虑谐波即只有特征频率的基频,1代表包括基频和2倍频,2代表包括基频和2、3倍频
- def FixedFreqFeature(self,xSpec, fMax, fTarget, fRange, fRangeMode, Detection, numHarmonics):
- if fRangeMode == '百分比':
- fRange = fRange*fTarget
- if fRangeMode == '数值':
- fRange = fRange
-
- # print(fRange)
- SpecResolution = fMax/(len(xSpec)-1)
- index_SearchRangeMax = int(math.ceil((fTarget + fRange/2)/SpecResolution))
- index_SearchRangeMin = int(math.floor((fTarget - fRange/2)/SpecResolution))
-
- if index_SearchRangeMin < 3:
- index_SearchRangeMin = 3
-
- index_SearchRange = index_SearchRangeMax - index_SearchRangeMin
-
- xArray = xSpec[index_SearchRangeMin:(index_SearchRangeMax+1)]
- while((int(np.argmax(xArray))==0) or (int(np.argmax(xArray))==len(xArray)-1)):
- index_SearchRangeMin = index_SearchRangeMin -1
- index_SearchRange = index_SearchRange + 1
- xArray = xSpec[int(index_SearchRangeMin-math.floor(index_SearchRange/2)):int(index_SearchRangeMin+math.ceil(index_SearchRange/2+1))]
- ActualTargetFreq = self.FundamentalFreqActualValue(xArray, SpecResolution,index_SearchRangeMin)
- # print(ActualTargetFreq)
-
- featureValue = self.FreqFeatureValue(xSpec, SpecResolution, ActualTargetFreq, index_SearchRange, Detection, numHarmonics)
-
- return featureValue
-
- ###############################################################################
- ###############################################################################
- # 该函数只用于内部调用,其调用函数为 FixedFreqFeature
- def FundamentalFreqActualValue(self,xArray, SpecResolution, index_SearchRangeMin):
- indexPeak = int(self.PeakFinderInArray(xArray))
- indexCenter = int(indexPeak + index_SearchRangeMin)
- ActualFundamentalFreq = self.FrequencyCompensation(indexCenter,xArray[indexPeak],xArray[indexPeak-1],xArray[indexPeak+1],SpecResolution)
-
- return ActualFundamentalFreq
- ###############################################################################
- ###############################################################################
- # 该函数只用于内部调用,其调用函数为 FundamentalFreqActualValue
- def PeakFinderInArray(self,xArray):
- NoElements = len(xArray)
- index_peak = int(np.argmin(xArray)) # initialize the peak index with the minimal value's index
- peak = xArray[index_peak] # initialize the peak value with the minimal value
-
- for i in range(0, NoElements-2):
- if (xArray[i+1] > xArray[i]) and (xArray[i+1] > xArray[i+2]) and (xArray[i+1] > peak):
- index_peak = i+1
- peak = xArray[i+1]
- return index_peak
-
- ###############################################################################
- ###############################################################################
- # 该函数只用于内部调用,其调用函数为 FundamentalFreqActualValue
- def FrequencyCompensation(self,indexCenter, AmpCenter, AmpLeft, AmpRight, xSpecResolution):
- if AmpRight >= AmpLeft:
- delta_k = (2*AmpRight-AmpCenter)/(AmpRight+AmpCenter)
- else:
- delta_k = (AmpCenter-2*AmpLeft)/(AmpLeft+AmpCenter)
-
- ActualFrequency = (indexCenter + delta_k)*xSpecResolution
- return ActualFrequency
-
- ###############################################################################
- ###############################################################################
- # 该函数只用于内部调用,其调用函数为 FixedFreqFeature
- def FreqFeatureValue(self,xSpec, SpecResolution, ActualTargetFreq, index_SearchRange, Detection, numHarmonics = 0):
- sumation = 0
- # print(ActualTargetFreq)
- featureValue = []
- featureValue = [0 for i in range(numHarmonics+1)]
- for i in range(0,numHarmonics+1):
- index_i = int(round((i+1)*ActualTargetFreq/SpecResolution))
- a = xSpec[int(index_i-math.floor(index_SearchRange/2)):int(index_i+math.ceil(index_SearchRange/2+1))]
- while((int(np.argmax(a))==0) or (int(np.argmax(a))==len(a)-1)):
- index_SearchRange = index_SearchRange + 2
- a = xSpec[int(index_i-math.floor(index_SearchRange/2)):int(index_i+math.ceil(index_SearchRange/2+1))]
- indexPeak = int(self.PeakFinderInArray(a) + index_i-math.floor(index_SearchRange/2))
- # print(int(index_i-math.floor(index_SearchRange/2)),indexPeak,int(index_i+math.ceil(index_SearchRange/2)))
- for j in range(indexPeak-2,indexPeak+2+1):
- sumation = sumation + xSpec[j]*xSpec[j]
-
- featureValue[i] = np.sqrt(sumation/1.5)
- sumation = 0
- # print(featureValue[i])
-
- if Detection == '峰值':
- pass
- if Detection == '有效值':
- featureValue = [x/math.sqrt(2) for x in featureValue]
- if Detection == '峰峰值':
- featureValue = [x*2 for x in featureValue]
-
- return featureValue
- ###############################################################################
- ###############################################################################
- # 计算频域积分
- # xSpecOrig需要对其计算积分的频谱数组,其长度为:101,201,401,801,1601,3201,6401,12801
- # fMax为频谱的分析频宽,单位为Hz
- # fCut为计算积分的低频截止频率,单位为Hz
- def FreqIntegration(self,xSpecOrig, fMax, fCut):
- nLine = len(xSpecOrig) - 1
- lineResolution = fMax / nLine
- iStarting = int(math.floor(fCut / lineResolution))
- if iStarting == 0:
- iStarting = 1
- xSpecOut = np.zeros(len(xSpecOrig))
- for i in range(iStarting, len(xSpecOrig)):
- xSpecOut[i] = xSpecOrig[i]/(2*pi*lineResolution*i)
- return xSpecOut
-
- ###############################################################################
- ###############################################################################
- # 巴特沃斯高通滤波
- # xTimeWave是时域波形数组, fs是采样频率,单位为Hz
- # fco 为高通截止频率,单位为Hz
- # Order为滤波器阶数,通常为偶数,2,4,6,8一般不超过8
- def HighPassButter(self,xTimeWave, fs, fco, Order):
- sos = signal.butter(Order, fco/(fs/2), 'hp', output='sos')
- filtered = signal.sosfilt(sos, xTimeWave)
- return filtered
- ###############################################################################
- ###############################################################################
- # 巴特沃斯低通滤波
- # xTimeWave是时域波形数组, fs是采样频率,单位为Hz
- # fco 为低通截止频率,单位为Hz
- # Order为滤波器阶数,通常为偶数,2,4,6,8一般不超过8
- def LowPassButter(self,xTimeWave, fs, fco, Order):
- sos = signal.butter(Order, fco/(fs/2), 'lp', output='sos')
- filtered = signal.sosfilt(sos, xTimeWave)
- return filtered
- ###############################################################################
- ###############################################################################
- # 计算包络
- # xTimeWave是时域波形数组
- # DownSampleRate是降采样率,调用函数需提供此数值,其计算公式为
- # 原始波形xTimeWave的分析频宽/包络后时域波形的分析频宽,比如原始波形分析频宽是10000Hz(采样频率是25600Hz),包络后时域
- # 波形的分析频宽是1000Hz,那 DownSampleRate = 10000/1000 = 10
- # Method是SKF的包络方法,还是PeakHold包络方法
- def EnvLopInTime(self,xTimeWave, DownSampleRate, Method = "SKF"):
- xOut = np.zeros(math.floor(len(xTimeWave)/DownSampleRate))
- if Method == "SKF":
- scale = 2.2
- xTimeWave = np.absolute(scale*xTimeWave)
- w = 1/(1.28*DownSampleRate)
- Order = 4
- sos = signal.butter(Order, w, 'lp', output='sos')
- xTimeWave = signal.sosfilt(sos, xTimeWave)
- xOut =xTimeWave[::DownSampleRate]
- if Method == "PeakHold":
- for i in range(0, len(xOut)):
- xOut[i] = np.amax(np.absolute(xTimeWave[i*DownSampleRate:((i+1)*DownSampleRate-1)]))
- return xOut - np.mean(xOut)
- ###############################################################################
- ###############################################################################
- # 内部调用函数
- def DownSampleBy2(self,xTimeWave):
- xTimeWave = signal.resample_poly(xTimeWave, 1, 2)
- return xTimeWave
- def DownSampleBy4(self,xTimeWave):
- xTimeWave = signal.resample_poly(xTimeWave,1,4)
- return xTimeWave
-
- def DownSampleBy5(self,xTimeWave):
- xTimeWave = signal.resample_poly(xTimeWave,1,5)
- return xTimeWave
-
- def DownSampleBy8(self,xTimeWave):
- xTimeWave = signal.resample_poly(xTimeWave,1,8)
- return xTimeWave
-
- def DownSampleBy10(self,xTimeWave):
- xTimeWave = signal.resample_poly(xTimeWave,1,10)
- return xTimeWave
-
- def DownSampleBy20(self,xTimeWave):
- xTimeWave = signal.resample_poly(xTimeWave,1,10)
- xTimeWave = signal.resample_poly(xTimeWave,1,2)
- return xTimeWave
-
- def DownSampleBy40(self,xTimeWave):
- xTimeWave = signal.resample_poly(xTimeWave,1,10)
- xTimeWave = signal.resample_poly(xTimeWave,1,4)
- return xTimeWave
-
- def DownSampleBy50(self,xTimeWave):
- xTimeWave = signal.resample_poly(xTimeWave,1,10)
- xTimeWave = signal.resample_poly(xTimeWave,1,5)
- return xTimeWave
- def DownSampleBy80(self,xTimeWave):
- xTimeWave = signal.resample_poly(xTimeWave,1,10)
- xTimeWave = signal.resample_poly(xTimeWave,1,8)
- return xTimeWave
- def DownSampleBy100(self,xTimeWave):
- xTimeWave = signal.resample_poly(xTimeWave,1,10)
- xTimeWave = signal.resample_poly(xTimeWave,1,10)
- return xTimeWave
- def DownSampleBy200(self,xTimeWave):
- xTimeWave = signal.resample_poly(xTimeWave,1,10)
- xTimeWave = signal.resample_poly(xTimeWave,1,10)
- xTimeWave = signal.resample_poly(xTimeWave,1,2)
- return xTimeWave
-
- def DownSampleBy400(self,xTimeWave):
- xTimeWave = signal.resample_poly(xTimeWave,1,10)
- xTimeWave = signal.resample_poly(xTimeWave,1,10)
- xTimeWave = signal.resample_poly(xTimeWave,1,4)
- return xTimeWave
-
- def DownSampleBy500(self,xTimeWave):
- xTimeWave = signal.resample_poly(xTimeWave,1,10)
- xTimeWave = signal.resample_poly(xTimeWave,1,10)
- xTimeWave = signal.resample_poly(xTimeWave,1,5)
- return xTimeWave
- def DownSampleBy800(self,xTimeWave):
- xTimeWave = signal.resample_poly(xTimeWave,1,10)
- xTimeWave = signal.resample_poly(xTimeWave,1,10)
- xTimeWave = signal.resample_poly(xTimeWave,1,8)
- return xTimeWave
-
- def DownSampleBy1000(self,xTimeWave):
- xTimeWave = signal.resample_poly(xTimeWave,1,10)
- xTimeWave = signal.resample_poly(xTimeWave,1,10)
- xTimeWave = signal.resample_poly(xTimeWave,1,10)
- return xTimeWave
-
- def DownSampleBy2000(self,xTimeWave):
- xTimeWave = signal.resample_poly(xTimeWave,1,10)
- xTimeWave = signal.resample_poly(xTimeWave,1,10)
- xTimeWave = signal.resample_poly(xTimeWave,1,10)
- xTimeWave = signal.resample_poly(xTimeWave,1,2)
- return xTimeWave
-
- def DownSampleBy4000(self,xTimeWave):
- xTimeWave = signal.resample_poly(xTimeWave,1,10)
- xTimeWave = signal.resample_poly(xTimeWave,1,10)
- xTimeWave = signal.resample_poly(xTimeWave,1,10)
- xTimeWave = signal.resample_poly(xTimeWave,1,4)
- return xTimeWave
-
-
- def DownSample(self, xTimeWave, fsIn, fsOut, nPointIn, nPointOut):
- #输入: xTimeWave: 时域波形数据
- # Fs: xTimeWave波形数据的采样频率(Hz)
- # fs: 降采样后时域波形数据的采样频率(Hz)
- # nPointIn: 输入波形的数据点数
- # nPointOut: 返回的波形的数据点数
- #
- #返回: 返回一个长度为nPointOut的时域波形数组
-
- DownSampleRate = int(fsIn/fsOut)
-
- if int(nPointIn/nPointOut) < DownSampleRate:
- print('Input data length is not enough')
- return -1
-
- if DownSampleRate == 2:
- return self.DownSampleBy2(xTimeWave[0:int(nPointOut*2)])
-
- if DownSampleRate == 4:
- return self.DownSampleBy4(xTimeWave[0:int(nPointOut*4)])
-
- if DownSampleRate == 5:
- return self.DownSampleBy5(xTimeWave[0:int(nPointOut*5)])
-
- if DownSampleRate == 8:
- return self.DownSampleBy8(xTimeWave[0:int(nPointOut*8)])
-
- if DownSampleRate == 10:
- return self.DownSampleBy10(xTimeWave[0:int(nPointOut*10)])
-
- if DownSampleRate == 20:
- return self.DownSampleBy20(xTimeWave[0:int(nPointOut*20)])
-
- if DownSampleRate == 40:
- return self.DownSampleBy40(xTimeWave[0:int(nPointOut*40)])
-
- if DownSampleRate == 50:
- return self.DownSampleBy50(xTimeWave[0:int(nPointOut*50)])
-
- if DownSampleRate == 100:
- return self.DownSampleBy100(xTimeWave[0:int(nPointOut*100)])
-
- if DownSampleRate == 200:
- return self.DownSampleBy200(xTimeWave[0:int(nPointOut*200)])
-
- if DownSampleRate == 400:
- return self.DownSampleBy400(xTimeWave[0:int(nPointOut*400)])
-
- if DownSampleRate == 500:
- return self.DownSampleBy500(xTimeWave[0:int(nPointOut*500)])
-
- if DownSampleRate == 1000:
- return self.DownSampleBy1000(xTimeWave[0:int(nPointOut*1000)])
-
- if DownSampleRate == 2000:
- return self.DownSampleBy2000(xTimeWave[0:int(nPointOut*2000)])
-
- if DownSampleRate == 4000:
- return self.DownSampleBy4000(xTimeWave[0:int(nPointOut*4000)])
-
- ###############################################################################
- ###############################################################################
- def OrderAnalysis(self, xTimeWave, Fs, xTimeSpeedPulse, nPulsePerRev, nRev, nLine, TransLevel, TransLevelPara):
- #输入: xTimeWave: 时域波形数据
- # Fs: xTimeWave波形数据的采样频率(Hz)
- # xTimeSpeedPulse: 相邻转速脉冲信号的时间间隔(s)
- # nPulsePerRev: 每周的脉冲个数
- # nRev: 阶次分析整周数(整周数必须是2的N次幂,比如:4、8、16、32、64、128、256、512等等)
- # nLine: 阶次频谱的谱线数(谱线数可选项为:100、200、400、800、1600、3200、6400)
- # TransLevel: 阶次分析轴与转速测量轴的转速等级关系,
- # 0:表示阶次分析轴与转速分析轴是同一根轴
- # 1:表示阶次分析轴与转速分析轴不在同一根轴上,有1次转速比变化
- # 2:表示阶次分析轴与转速分析轴不在同一根轴上,有2次转速比变化
- # 3:表示阶次分析轴与转速分析轴不在同一根轴上,有3次转速比变化, 以此类推
- # TransLevelPara: 齿轮齿数数组,
- # 当 TransLevel == 0 时,这个数组只有1个元素,可以是[0]
- # 当 TransLevel == 1 时,有一对齿轮啮合,2根轴。这个数组有2个元素,第一个元素是转速测量轴(1轴)上的齿轮齿数,
- # 第二个元素是与转速测量轴啮合(2轴)的齿轮的齿数,
- # 当 TransLevel == 2 时,有二对齿轮啮合,3根轴。这个数组有4个元素,第一个元素是转速测量轴(2轴)上的齿轮齿数,
- # 第二个元素是与转速测量轴啮合(2轴)的齿轮的齿数,第三个元素是2轴与下一级(3轴)啮合的齿轮的齿数,
- # 第四个元素是3轴与2轴啮合的齿轮的齿数。
- #返回: 等角度采样的角度轴坐标,等角度采样的波形,阶次谱的阶次轴坐标,阶次谱的幅值
- nRevSpeedSensorShaft = int(len(xTimeSpeedPulse)/nPulsePerRev) # 计算转速测量轴的转速测量信号有多少个整周数
- xTimeSpeedPulse = xTimeSpeedPulse[0:0+int(nRevSpeedSensorShaft*nPulsePerRev)] # 整周数以外多余的脉冲信号去掉
- xTimeSpeedPerRevSpeedSensorShaft = np.sum(np.reshape(xTimeSpeedPulse,(nRevSpeedSensorShaft,nPulsePerRev)),axis = 1) # 计算转速测量轴每转一周的时间
-
- if TransLevel == 0:
- xTimeSpeedPerRevCurrentShaft = xTimeSpeedPerRevSpeedSensorShaft
- xTimeSpeedPerRevCurrentShaft_ave = np.average(xTimeSpeedPerRevCurrentShaft) # 当转速测量轴就是阶次分析的轴时,转速脉冲可以直接使用
- fMax_MAX = 1/xTimeSpeedPerRevCurrentShaft_ave*nLine/nRev
- else:
- xTemp = np.cumsum(xTimeSpeedPerRevSpeedSensorShaft) # 转速脉冲时间累积
- xTemp = np.append(0,xTemp) # 添加起始点 # 当转速测量轴不是阶次分析轴时,传输脉冲信号必须转换到阶次分析轴上
- for i in range (TransLevel):
- up = TransLevelPara[i] # 转速测量轴齿轮齿数
- down = TransLevelPara[i+1] # 啮合轴齿轮齿数
- dataLength = int(len(xTemp)*up) # 转速测量轴增采样后的数据长度
- flipelements = int(len(xTemp)*0.5) # 转速信号加长50%防止长度不够
- extention = np.zeros(flipelements)
- for j in range(flipelements): # 转速信号加长算法,以最后一点为对称中心
- extention[j] = xTemp[-1]-(xTemp[-1-j-1]-xTemp[-1])
- xTemp1 = np.append(xTemp,extention) # 转速信号加长后的转速脉冲时间累积
- xTemp2 = np.zeros(xTemp1.size*(up),xTemp1.dtype)
- xTemp2[::up] = xTemp1 # 脉冲时间累积信号增采样,增采样率为转速测量轴齿轮的齿数
- # plt.figure(30)
- # plt.plot(xTemp2)
- #==============================================================
- delta1 = 0.00000001
- delta2 = 0.0000001
- freq1 = 0.39/up
- freq2 = 0.61/up
- AA = np.matrix([[-4.278e-1,-4.761e-1,0],[-5.941e-1,7.114e-2,0],[-2.66e-3,5.309e-03,0]])
- d1 = np.log10(delta1)
- d2 = np.log10(delta2)
- D = np.array([1,d1,d1*d1])*AA*np.array([[1],[d2],[d2*d2]])
- bb = np.array([11.01217,0.51244])
- fK = np.dot(np.array([1.0,(d1-d2)]),bb)
- df = np.abs(freq2-freq1)
- N = int(D[0]/df-fK*df+1)
- if np.remainder(N,2) == 0:
- N = N+1
- upSampleFilterCoefficients = signal.remez(N, [0,0.39,0.61,up/2], [1,0],Hz = up,maxiter = 500)
- # [freq, response] = signal.freqz(upSampleFilterCoefficients)
- # ampl = np.abs(response)
- # plt.figure(31)
- # plt.plot(freq,ampl)
- #==============================================================
- groupDelay = int((len(upSampleFilterCoefficients)+1)/2)
- xTemp3 = signal.convolve(xTemp2,upSampleFilterCoefficients)
- xTemp4 = (xTemp3[groupDelay-1:groupDelay-1+dataLength])*up
- plt.figure(30)
- plt.plot(xTemp4)
- xTemp5 = xTemp4[0::down]
-
-
- xTimeSpeedPerRevCurrentShaft = np.diff(xTemp5)
- xTimeSpeedPerRevCurrentShaft_ave = np.average(xTimeSpeedPerRevCurrentShaft) # 当转速测量轴就是阶次分析的轴时,转速脉冲可以直接使用
- fMax_MAX = 1/xTimeSpeedPerRevCurrentShaft_ave*nLine/nRev
- xTimeSpeedPerRevCurrentShaft_min = np.min(xTimeSpeedPerRevCurrentShaft) # 计算轴转得最快的一周的时间
- fMax_MAX = 1/xTimeSpeedPerRevCurrentShaft_min*nLine/nRev # 根据最快的一周的时间得出阶次频谱最高分析频宽的频率
- Order = 6
- if fMax_MAX <= Fs/2.56:
- xTimeWave = self.LowPassButter(xTimeWave, Fs, fMax_MAX, Order) # 低通滤波消除大于fMax_MAX的信号,然后才能做阶次分析
-
- xTimeSpeedCurrentShaftCumulative = np.cumsum(xTimeSpeedPerRevCurrentShaft) # 计算轴每转一周所用时间的累积值
- nVibDataPoint = nLine*2.56 # 计算时域波形点数
- up = nVibDataPoint/nRev # 计算每周等角度采样点数
- # down = 1
- halfbandWeight = self.halfbandcoefficient()
-
- groupDelay = int((len(halfbandWeight)+1)/2)
- numIteration = int(np.log10(up)/np.log10(2))
- temp = np.append(0,xTimeSpeedCurrentShaftCumulative)
- flipelements = int(len(temp)*0.5)
- extention = np.zeros(flipelements)
- for i in range(numIteration):
- dataLength = int(len(temp)*2)
- for j in range(flipelements):
- extention[j] = temp[-1]-(temp[-1-j-1]-temp[-1])
- temp1 = np.append(temp,extention)
- temp2 = np.insert(temp1,np.arange(1,len(temp1),1),0)
- temp3 = np.append(temp2,0)
- temp4 = signal.convolve(temp3,halfbandWeight)
- temp = temp4[groupDelay-1:groupDelay-1+dataLength]
-
- xTimeNewSamplePoint = temp
-
- flipelements = int(len(xTimeWave)*0.25)
- extention = np.zeros(flipelements)
- for j in range(flipelements):
- extention[j] = xTimeWave[-1]-(xTimeWave[-1-j-1]-xTimeWave[-1])
- xTimeWave = np.append(xTimeWave,extention)
- xTimeSamplePoint = np.arange(0,len(xTimeWave)/Fs,1/Fs) # 计算输入波形的采样时间点
- # spl = UnivariateSpline(xTimeSamplePoint,xTimeWave)
- # Waveform = spl(xTimeNewSamplePoint)
- fx = interpolate.interp1d(xTimeSamplePoint,xTimeWave,kind= 'cubic')
- Waveform = fx(xTimeNewSamplePoint)
- OrderWaveform = Waveform[0:int(nLine*2.56)]
- ct = 360/(nLine*2.56/nRev)
- orderTimeLine = np.arange(0,nLine*2.56*ct,ct)
- fOT = nLine*2.56/nRev
- fMax = fOT/2.56
- fCut = 10*fMax/nLine
- WinType = 0
- AverageType = 0
- OverLapType = 0
- [f, xSpectrum, xSpectrumPhase] = self.Spectrum(OrderWaveform,nLine,fMax,fCut,WinType, AverageType ,OverLapType) # 计算插值函数
- len(OrderWaveform)
- return [orderTimeLine, OrderWaveform, f, xSpectrum]
- ###############################################################################
- ###############################################################################
- # 内部函数
- def halfBandDesign (self, filterLength, transitionBand ):
-
- invalidInput = False
-
- # check if integer
- if (np.abs(filterLength - int(filterLength)) > 1e-10):
- print('halfBandDesign.py: filterLength must be an integer')
- invalidInput = True
-
- # check if too small
- if (filterLength < 7):
- print('halfBandDesign.py: filterLength must be larger than 6')
- invalidInput = True
-
- # check if proper length
- if (np.mod(filterLength+1,4) != 0):
- print('halfBandDesign.py: filterLength+1 must be divisble by 4')
- invalidInput = True
-
- # check range for transition band
- if (transitionBand <= 0 or transitionBand >= 0.5):
- print('halfBandDesign.py: transitionBand must be greater than 0 and less than 0.5')
- invalidInput = True
-
- if (invalidInput):
- return []
-
- else:
-
- # design a half band filter with remez
- cutoff = 0.25
- fPass = cutoff - (transitionBand/2)
- fStop = cutoff + (transitionBand/2)
- fVec = [0, fPass, fStop, 0.5]
- aVec = [1, 0]
-
- weights = signal.remez(filterLength,fVec,aVec)
-
- # force zero weights
- zeroWeightIndicesHalf = np.arange(2,(filterLength-1)/2,2,dtype=int)
- zeroWeightIndicesNegative = np.concatenate((-zeroWeightIndicesHalf[::-1],zeroWeightIndicesHalf))
- zeroWeightIndices = zeroWeightIndicesNegative - zeroWeightIndicesNegative[0] + 1
-
- weights[zeroWeightIndices] = 0
-
- return weights
- ###############################################################################
- ###############################################################################
-
- # def Pk_Search_BW(self):
- # BW = 0.03
- # return BW
-
- ###############################################################################
- ###############################################################################
- # @staticmethod
- def gE_Bearing_Defect_HM_Threshhold(self,alert, danger, defectType):
- gE_Bearing_Defect_HM_alert = np.zeros(5)
- gE_Bearing_Defect_HM_danger = np.zeros(5)
- if defectType == 'BPFO' :
- gE_Bearing_Defect_HM_alert[0] = alert*0.167
- gE_Bearing_Defect_HM_alert[1] = alert*0.131
- gE_Bearing_Defect_HM_alert[2] = alert*0.098
- gE_Bearing_Defect_HM_alert[3] = alert*0.089
- gE_Bearing_Defect_HM_alert[4] = alert*0.082
-
- gE_Bearing_Defect_HM_danger[0] = danger*0.167
- gE_Bearing_Defect_HM_danger[1] = danger*0.131
- gE_Bearing_Defect_HM_danger[2] = danger*0.098
- gE_Bearing_Defect_HM_danger[3] = danger*0.089
- gE_Bearing_Defect_HM_danger[4] = danger*0.082
-
- return gE_Bearing_Defect_HM_alert, gE_Bearing_Defect_HM_danger
-
- if defectType == 'BPFI':
- gE_Bearing_Defect_HM_alert[0] = alert*0.088
- gE_Bearing_Defect_HM_alert[1] = alert*0.064
- gE_Bearing_Defect_HM_alert[2] = alert*0.056
- gE_Bearing_Defect_HM_alert[3] = alert*0.035
- gE_Bearing_Defect_HM_alert[4] = alert*0.024
-
- gE_Bearing_Defect_HM_danger[0] = danger*0.088
- gE_Bearing_Defect_HM_danger[1] = danger*0.064
- gE_Bearing_Defect_HM_danger[2] = danger*0.056
- gE_Bearing_Defect_HM_danger[3] = danger*0.035
- gE_Bearing_Defect_HM_danger[4] = danger*0.024
-
- return gE_Bearing_Defect_HM_alert, gE_Bearing_Defect_HM_danger
-
- if defectType == 'BSF':
- gE_Bearing_Defect_HM_alert[0] = alert*0.088
- gE_Bearing_Defect_HM_alert[1] = alert*0.064
- gE_Bearing_Defect_HM_alert[2] = alert*0.056
- gE_Bearing_Defect_HM_alert[3] = alert*0.035
- gE_Bearing_Defect_HM_alert[4] = alert*0.024
-
- gE_Bearing_Defect_HM_danger[0] = danger*0.088
- gE_Bearing_Defect_HM_danger[1] = danger*0.064
- gE_Bearing_Defect_HM_danger[2] = danger*0.056
- gE_Bearing_Defect_HM_danger[3] = danger*0.035
- gE_Bearing_Defect_HM_danger[4] = danger*0.024
-
-
- return gE_Bearing_Defect_HM_alert, gE_Bearing_Defect_HM_danger
- if defectType == 'FTF':
- gE_Bearing_Defect_HM_alert[0] = alert*0.088
- gE_Bearing_Defect_HM_alert[1] = alert*0.064
- gE_Bearing_Defect_HM_alert[2] = alert*0.056
- gE_Bearing_Defect_HM_alert[3] = alert*0.035
- gE_Bearing_Defect_HM_alert[4] = alert*0.024
-
- gE_Bearing_Defect_HM_danger[0] = danger*0.088
- gE_Bearing_Defect_HM_danger[1] = danger*0.064
- gE_Bearing_Defect_HM_danger[2] = danger*0.056
- gE_Bearing_Defect_HM_danger[3] = danger*0.035
- gE_Bearing_Defect_HM_danger[4] = danger*0.024
-
- return gE_Bearing_Defect_HM_alert, gE_Bearing_Defect_HM_danger
- ###############################################################################
- ###############################################################################
- # @staticmethod
- def Vel_Bearing_Defect_HM_Threshhold(self,alert, danger, defectType):
- Vel_Bearing_Defect_HM_alert = np.zeros(5)
- Vel_Bearing_Defect_HM_danger = np.zeros(5)
- if defectType == 'BPFO':
- Vel_Bearing_Defect_HM_alert[0] = alert*1.0
- Vel_Bearing_Defect_HM_alert[1] = alert*1.0
- Vel_Bearing_Defect_HM_alert[2] = alert*1.0
- Vel_Bearing_Defect_HM_alert[3] = alert*1.0
-
- Vel_Bearing_Defect_HM_danger[0] = danger*1.0
- Vel_Bearing_Defect_HM_danger[1] = danger*1.0
- Vel_Bearing_Defect_HM_danger[2] = danger*1.0
- Vel_Bearing_Defect_HM_danger[3] = danger*1.0
-
- return Vel_Bearing_Defect_HM_alert, Vel_Bearing_Defect_HM_danger
-
- if defectType == 'BPFI':
- Vel_Bearing_Defect_HM_alert[0] = alert*1.0
- Vel_Bearing_Defect_HM_alert[1] = alert*1.0
- Vel_Bearing_Defect_HM_alert[2] = alert*1.0
- Vel_Bearing_Defect_HM_alert[3] = alert*1.0
-
- Vel_Bearing_Defect_HM_danger[0] = danger*1.0
- Vel_Bearing_Defect_HM_danger[1] = danger*1.0
- Vel_Bearing_Defect_HM_danger[2] = danger*1.0
- Vel_Bearing_Defect_HM_danger[3] = danger*1.0
-
- return Vel_Bearing_Defect_HM_alert, Vel_Bearing_Defect_HM_danger
-
- if defectType == 'BSF':
- Vel_Bearing_Defect_HM_alert[0] = alert*1.0
- Vel_Bearing_Defect_HM_alert[1] = alert*0.5
- Vel_Bearing_Defect_HM_alert[2] = alert*0.5
- Vel_Bearing_Defect_HM_alert[3] = alert*0.5
-
- Vel_Bearing_Defect_HM_danger[0] = danger*1.0
- Vel_Bearing_Defect_HM_danger[1] = danger*0.5
- Vel_Bearing_Defect_HM_danger[2] = danger*0.5
- Vel_Bearing_Defect_HM_danger[3] = danger*0.5
-
- return Vel_Bearing_Defect_HM_alert, Vel_Bearing_Defect_HM_danger
-
-
- ###############################################################################
- ###############################################################################
- # @staticmethod
- def Vel_Bearing_RunningSpd_HM_Threshhold(self,alert, danger, defectType):
- Vel_Bearing_RunningSpd_HM_alert = np.zeros(5)
- Vel_Bearing_RunningSpd_HM_danger = np.zeros(5)
- if defectType == 'BSF':
- Vel_Bearing_RunningSpd_HM_alert[0] = alert*1.0
- Vel_Bearing_RunningSpd_HM_alert[1] = alert*0.5
- Vel_Bearing_RunningSpd_HM_alert[2] = alert*0.5
- Vel_Bearing_RunningSpd_HM_alert[3] = alert*0.5
- Vel_Bearing_RunningSpd_HM_alert[4] = alert*0.5
-
- Vel_Bearing_RunningSpd_HM_danger[0] = danger*1.0
- Vel_Bearing_RunningSpd_HM_danger[1] = danger*0.5
- Vel_Bearing_RunningSpd_HM_danger[2] = danger*0.5
- Vel_Bearing_RunningSpd_HM_danger[3] = danger*0.5
- Vel_Bearing_RunningSpd_HM_danger[4] = danger*0.5
- return Vel_Bearing_RunningSpd_HM_alert, Vel_Bearing_RunningSpd_HM_danger
- ###############################################################################
- ###############################################################################
- # @staticmethod
- def Vel_Unbalance_HM_Threshold(self,alert, danger):
- Vel_Unbalance_HM_alert = np.zeros(5)
- Vel_Unbalance_HM_danger = np.zeros(5)
- Vel_Unbalance_HM_alert[0] = alert*1.0
- Vel_Unbalance_HM_alert[1] = alert*0.5
- Vel_Unbalance_HM_alert[2] = alert*0.5
- Vel_Unbalance_HM_alert[3] = alert*0.5
- Vel_Unbalance_HM_alert[4] = alert*0.5
-
- Vel_Unbalance_HM_danger[0] = danger*1.0
- Vel_Unbalance_HM_danger[1] = danger*0.5
- Vel_Unbalance_HM_danger[2] = danger*0.5
- Vel_Unbalance_HM_danger[3] = danger*0.5
- Vel_Unbalance_HM_danger[4] = danger*0.5
-
- return Vel_Unbalance_HM_alert, Vel_Unbalance_HM_danger
- ###############################################################################
- ###############################################################################
- # @staticmethod
- def Vel_Misalignment_HM_Threshold(self,alert, danger):
- Vel_Misalignment_HM_alert = np.zeros(5)
- Vel_Misalignment_HM_danger = np.zeros(5)
-
- Vel_Misalignment_HM_alert[0] = alert*1.0
- Vel_Misalignment_HM_alert[1] = alert*0.5
- Vel_Misalignment_HM_alert[2] = alert*0.5
- Vel_Misalignment_HM_alert[3] = alert*0.5
- Vel_Misalignment_HM_alert[4] = alert*0.5
-
- Vel_Misalignment_HM_danger[0] = danger*1.0
- Vel_Misalignment_HM_danger[1] = danger*0.5
- Vel_Misalignment_HM_danger[2] = danger*0.5
- Vel_Misalignment_HM_danger[3] = danger*0.5
- Vel_Misalignment_HM_danger[4] = danger*0.5
-
- return Vel_Misalignment_HM_alert, Vel_Misalignment_HM_danger
- ###############################################################################
- ###############################################################################
- # @staticmethod
- def Vel_Looseness_HM_Threshold(self,alert, danger):
- Vel_Looseness_HM_alert = np.zeros(5)
- Vel_Looseness_HM_danger = np.zeros(5)
-
- Vel_Looseness_HM_alert[0] = alert*1.0
- Vel_Looseness_HM_alert[1] = alert*0.5
- Vel_Looseness_HM_alert[2] = alert*0.5
- Vel_Looseness_HM_alert[3] = alert*0.5
- Vel_Looseness_HM_alert[4] = alert*0.5
-
- Vel_Looseness_HM_danger[0] = danger*1.0
- Vel_Looseness_HM_danger[1] = danger*0.5
- Vel_Looseness_HM_danger[2] = danger*0.5
- Vel_Looseness_HM_danger[3] = danger*0.5
- Vel_Looseness_HM_danger[4] = danger*0.5
-
- return Vel_Looseness_HM_alert, Vel_Looseness_HM_danger
-
- ###############################################################################
- ###############################################################################
- # @staticmethod
- def gE_2XLF_HM_Threshhold(self,alert, danger):
- gE_2XLF_HM_alert = np.zeros(5)
- gE_2XLF_HM_danger = np.zeros(5)
- gE_2XLF_HM_alert[0] = alert*0.167
- gE_2XLF_HM_alert[1] = alert*0.131
- gE_2XLF_HM_alert[2] = alert*0.098
- gE_2XLF_HM_alert[3] = alert*0.089
- gE_2XLF_HM_alert[4] = alert*0.082
-
- gE_2XLF_HM_danger[0] = danger*0.167
- gE_2XLF_HM_danger[1] = danger*0.131
- gE_2XLF_HM_danger[2] = danger*0.098
- gE_2XLF_HM_danger[3] = danger*0.089
- gE_2XLF_HM_danger[4] = danger*0.082
- return gE_2XLF_HM_alert, gE_2XLF_HM_danger
- ###############################################################################
- ###############################################################################
- # @staticmethod
- def Vel_2XLF_HM_Threshhold(self,alert, danger):
- Vel_2XLF_HM_alert = np.zeros(1)
- Vel_2XLF_HM_danger = np.zeros(1)
- Vel_2XLF_HM_alert[0] = alert*1.0
- Vel_2XLF_HM_danger[0] = danger*1.0
- return Vel_2XLF_HM_alert, Vel_2XLF_HM_danger
- ###############################################################################
- ###############################################################################
- # @staticmethod
- def Acc_GMF_HM_Threshhold(self,alert, danger):
- Acc_GMF_HM_alert = np.zeros(3)
- Acc_GMF_HM_danger = np.zeros(3)
-
- Acc_GMF_HM_alert[0] = alert*1.0
- Acc_GMF_HM_alert[1] = alert*1.0
- Acc_GMF_HM_alert[2] = alert*1.0
-
- Acc_GMF_HM_danger[0] = danger*1.0
- Acc_GMF_HM_danger[1] = danger*1.0
- Acc_GMF_HM_danger[2] = danger*1.0
-
- return Acc_GMF_HM_alert, Acc_GMF_HM_danger
-
- ###############################################################################
- ###############################################################################
- # @staticmethod
- def Vel_GMF_HM_Threshhold(self,alert, danger):
- Vel_GMF_HM_alert = np.zeros(3)
- Vel_GMF_HM_danger = np.zeros(3)
-
- Vel_GMF_HM_alert[0] = alert*1.0
- Vel_GMF_HM_alert[1] = alert*1.0
- Vel_GMF_HM_alert[2] = alert*1.0
-
- Vel_GMF_HM_danger[0] = danger*1.0
- Vel_GMF_HM_danger[1] = danger*1.0
- Vel_GMF_HM_danger[2] = danger*1.0
-
- return Vel_GMF_HM_alert, Vel_GMF_HM_danger
-
- ###############################################################################
- ###############################################################################
- # @staticmethod
- def gE_GMF_HM_Threshhold(self,alert, danger):
- gE_GMF_HM_alert = np.zeros(3)
- gE_GMF_HM_danger = np.zeros(3)
-
- gE_GMF_HM_alert[0] = alert*0.167
- gE_GMF_HM_alert[1] = alert*0.131
- gE_GMF_HM_alert[2] = alert*0.098
-
- gE_GMF_HM_danger[0] = danger*0.167
- gE_GMF_HM_danger[1] = danger*0.131
- gE_GMF_HM_danger[2] = danger*0.098
-
- return gE_GMF_HM_alert, gE_GMF_HM_danger
-
- ###############################################################################
- ###############################################################################
- # @staticmethod
- def gE_GTIF_HM_Threshhold(self,alert, danger):
- gE_GTIF_HM_alert = np.zeros(5)
- gE_GTIF_HM_danger = np.zeros(5)
-
- gE_GTIF_HM_alert[0] = alert*0.167
- gE_GTIF_HM_alert[1] = alert*0.131
- gE_GTIF_HM_alert[2] = alert*0.098
- gE_GTIF_HM_alert[3] = alert*0.089
- gE_GTIF_HM_alert[4] = alert*0.082
-
- gE_GTIF_HM_danger[0] = danger*0.167
- gE_GTIF_HM_danger[1] = danger*0.131
- gE_GTIF_HM_danger[2] = danger*0.098
- gE_GTIF_HM_danger[3] = danger*0.089
- gE_GTIF_HM_danger[4] = danger*0.082
-
- return gE_GTIF_HM_alert, gE_GTIF_HM_danger
-
- ###############################################################################
- ###############################################################################
- # @staticmethod
- def Vel_VPF_HM_Threshhold(self,alert, danger):
- Vel_VPF_HM_alert = np.zeros(2)
- Vel_VPF_HM_danger = np.zeros(2)
-
- Vel_VPF_HM_alert[0] = alert*1.0
- Vel_VPF_HM_alert[1] = alert*1.0
-
- Vel_VPF_HM_danger[0] = danger*1.0
- Vel_VPF_HM_danger[1] = danger*1.0
-
- return Vel_VPF_HM_alert, Vel_VPF_HM_danger
- ###############################################################################
- ###############################################################################
- # @staticmethod
- def Vel_BTF_HM_Threshhold(self,alert, danger):
- Vel_BTF_HM_alert = np.zeros(2)
- Vel_BTF_HM_danger = np.zeros(2)
-
- Vel_BTF_HM_alert[0] = alert*1.0
- Vel_BTF_HM_alert[1] = alert*1.0
-
- Vel_BTF_HM_danger[0] = danger*1.0
- Vel_BTF_HM_danger[1] = danger*1.0
-
- return Vel_BTF_HM_alert, Vel_BTF_HM_danger
-
- ###############################################################################
- ###############################################################################
- # @staticmethod
- def Vel_SHF_HM_Threshhold(self,alert, danger):
- Vel_SHF_HM_alert = np.zeros(1)
- Vel_SHF_HM_danger = np.zeros(1)
-
- Vel_SHF_HM_alert[0] = alert*1.0
-
- Vel_SHF_HM_danger[0] = danger*1.0
-
- return Vel_SHF_HM_alert, Vel_SHF_HM_danger
- ###############################################################################
- ###############################################################################
- # @staticmethod
- def Vel_RBPF_HM_Threshhold(self,alert, danger):
- Vel_RBPF_HM_alert = np.zeros(1)
- Vel_RBPF_HM_danger = np.zeros(1)
-
- Vel_RBPF_HM_alert[0] = alert*1.0
-
- Vel_RBPF_HM_danger[0] = danger*1.0
-
- return Vel_RBPF_HM_alert, Vel_RBPF_HM_danger
-
- ###############################################################################
- ###############################################################################
- # @staticmethod
- def Acc_RBPF_HM_Threshhold(self,alert, danger):
- Acc_RBPF_HM_alert = np.zeros(1)
- Acc_RBPF_HM_danger = np.zeros(1)
-
- Acc_RBPF_HM_alert[0] = alert*1.0
-
- Acc_RBPF_HM_danger[0] = danger*1.0
-
- return Acc_RBPF_HM_alert, Acc_RBPF_HM_danger
- ###############################################################################
- ###############################################################################
- # @staticmethod
- def Bearing_Fault_Diag(self,gE_Bearing_Defect_HM, Vel_Bearing_Defect_HM, Vel_RunningSpd_HM, gE_alert, gE_danger, Vel_alert, Vel_danger, defectType):
- BrDefDetection = False
- BrDefSev = 0
- gE_Bearing_Defect_HM_alert = np.zeros(5)
- gE_Bearing_Defect_HM_danger = np.zeros(5)
- Vel_Bearing_Defect_HM_alert = np.zeros(5)
- Vel_Bearing_Defect_HM_danger = np.zeros(5)
- Vel_Bearing_RunningSpd_HM_alert = np.zeros(5)
- Vel_Bearing_RunningSpd_HM_danger = np.zeros(5)
- ###############################################################################
- # Check bearing outer race and inner race defect
-
- if (defectType == 'BPFO') or (defectType == 'BPFI'):
- [gE_Bearing_Defect_HM_alert, gE_Bearing_Defect_HM_danger] = self.gE_Bearing_Defect_HM_Threshhold(gE_alert, gE_danger, defectType)
- # [Vel_Bearing_RunningSpd_HM_alert, Vel_Bearing_RunningSpd_HM_danger] = self.Vel_Bearing_RunningSpd_HM_Threshhold(Vel_alert, Vel_danger, defectType)
- [Vel_Bearing_Defect_HM_alert, Vel_Bearing_Defect_HM_danger] = self.Vel_Bearing_Defect_HM_Threshhold(Vel_alert, Vel_danger, defectType)
- # Bearing outer race frequency, severe, confirmed by velocity spectrum, CF = 8, Severity = 10
- # AND
- # OR
- # ge_BPFO_1 >= Alert
- # ge_BPFO_2 >= Alert
- # OR
- # Vel_BPFO_1 >= Alert
- # Vel_BPFO_2 >= Alert
- #
- # above logics apply to BPFI as well
-
- if (gE_Bearing_Defect_HM[0] >= gE_Bearing_Defect_HM_alert[0] or gE_Bearing_Defect_HM[1] >= gE_Bearing_Defect_HM_alert[1]) and \
- (Vel_Bearing_Defect_HM[0] >= Vel_Bearing_Defect_HM_alert[0] or Vel_Bearing_Defect_HM[1] >= Vel_Bearing_Defect_HM_alert[1]):
- BrDefDetection = True
- BrDefSev = 8
-
- return BrDefDetection, BrDefSev
-
- # Bearing outer race frequency, severe, no confirming by velocity spectrum, CF = 6, Severity = 10
- # AND
- # OR
- # AND
- # ge_BPFO_1 >= Danger
- # ge_BPFO_2 >= Alert
- # AND
- # gE_BPFO_1 >= Danger
- # gE_BPFO_3 >= Alert
- # AND
- # gE_BPFO_1 >= Danger
- # gE_BPFO_4 >= Alert
- # NOR
- # Vel_BPFO_1 >= Alert
- # Vel_BPFO_2 >= Alert
- #
- # above logics apply to BPFI as well
-
- else:
- if ((gE_Bearing_Defect_HM[0] >= gE_Bearing_Defect_HM_danger[0] and gE_Bearing_Defect_HM[1] >= gE_Bearing_Defect_HM_alert[1]) or \
- (gE_Bearing_Defect_HM[0] >= gE_Bearing_Defect_HM_danger[0] and gE_Bearing_Defect_HM[2] >= gE_Bearing_Defect_HM_alert[2]) or \
- (gE_Bearing_Defect_HM[0] >= gE_Bearing_Defect_HM_danger[0] and gE_Bearing_Defect_HM[3] >= gE_Bearing_Defect_HM_alert[3])) and \
- (not(Vel_Bearing_Defect_HM[0] >= Vel_Bearing_Defect_HM_alert[0] or Vel_Bearing_Defect_HM[1] >= Vel_Bearing_Defect_HM_alert[1])):
- BrDefDetection = True
- BrDefSev = 6
- return BrDefDetection, BrDefSev
-
- # Bearing outer race frequency, severe, not confirmed by gE spectrum, CF = 6, Severity = 10
- # OR
- # Vel_BPFO_1 >= Alert
- # Vel_BPFO_2 >= Alert
- #
- # above logics apply to BPFI as well
-
- else:
- if (Vel_Bearing_Defect_HM[0] >= Vel_Bearing_Defect_HM_alert[0] or Vel_Bearing_Defect_HM[1] >= Vel_Bearing_Defect_HM_alert[1]):
- BrDefDetection = True
- BrDefSev = 6
-
- return BrDefDetection, BrDefSev
- # Bearing outer race frequency, moderate, several defect peaks, no confirming by velocity spectrum, CF = 5, Severity = 5
- # AND
- # OR
- # AND
- # ge_BPFO_1 >= Alert
- # ge_BPFO_2 >= Alert
- # AND
- # gE_BPFO_1 >= Alert
- # gE_BPFO_3 >= Alert
- # AND
- # gE_BPFO_1 >= Alert
- # gE_BPFO_4 >= Alert
- # NOR
- # Vel_BPFO_1 >= Alert
- # Vel_BPFO_2 >= Alert
- #
- # above logics apply to BPFI as well
-
- else:
- if ((gE_Bearing_Defect_HM[0] >= gE_Bearing_Defect_HM_alert[0] and gE_Bearing_Defect_HM[1] >= gE_Bearing_Defect_HM_alert[1]) or \
- (gE_Bearing_Defect_HM[0] >= gE_Bearing_Defect_HM_alert[0] and gE_Bearing_Defect_HM[2] >= gE_Bearing_Defect_HM_alert[2]) or \
- (gE_Bearing_Defect_HM[0] >= gE_Bearing_Defect_HM_alert[0] and gE_Bearing_Defect_HM[3] >= gE_Bearing_Defect_HM_alert[3])) and \
- (not(Vel_Bearing_Defect_HM[0] >= Vel_Bearing_Defect_HM_alert[0] or Vel_Bearing_Defect_HM[1] >= Vel_Bearing_Defect_HM_alert[1])):
- BrDefDetection = True
- BrDefSev = 3
- return BrDefDetection, BrDefSev
-
- # Bearing outer race frequency, suspect, only 1x defect peak evaluated, CF = 3, Severity = 5
- # ge_BPFO_1 >= Alert
- #
- # above logics apply to BPFI as well
-
- else:
- if (gE_Bearing_Defect_HM[0] >= gE_Bearing_Defect_HM_alert[0]):
- BrDefDetection = True
- BrDefSev = 1
- return BrDefDetection, BrDefSev
-
- return BrDefDetection, BrDefSev
- ###############################################################################
- # Check bearing rolling element defect
-
- if defectType == 'BSF':
- [gE_Bearing_Defect_HM_alert, gE_Bearing_Defect_HM_danger] = self.gE_Bearing_Defect_HM_Threshhold(gE_alert, gE_danger, defectType)
- [Vel_Bearing_RunningSpd_HM_alert, Vel_Bearing_RunningSpd_HM_danger] = self.Vel_Bearing_RunningSpd_HM_Threshhold(Vel_alert, Vel_danger, defectType)
- [Vel_Bearing_Defect_HM_alert, Vel_Bearing_Defect_HM_danger] = self.Vel_Bearing_Defect_HM_Threshhold(Vel_alert, Vel_danger, defectType)
- # print(Vel_Bearing_RunningSpd_HM_alert, Vel_Bearing_RunningSpd_HM_danger)
- # Bearing rolling element frequency, severe, CF = 9, Severity = 10
- # AND
- # AND
- # Vel_BSF_2 >= Alert
- # Vel_BSF_4 >= Alert
- # NOR
- # Vel_RS_2 >= Alert
- # Vel_RS_3 >= Alert
- # Vel_RS_4 >= Alert
- # Vel_RS_5 >= Alert
-
- if (Vel_Bearing_Defect_HM[1] >= Vel_Bearing_Defect_HM_alert[1] and Vel_Bearing_Defect_HM[3] >= Vel_Bearing_Defect_HM_alert[3]) and \
- (not(Vel_RunningSpd_HM[1] >= Vel_Bearing_RunningSpd_HM_alert[1] or Vel_RunningSpd_HM[2] >= Vel_Bearing_RunningSpd_HM_alert[2] or \
- Vel_RunningSpd_HM[3] >= Vel_Bearing_RunningSpd_HM_alert[3] or Vel_RunningSpd_HM[4] >= Vel_Bearing_RunningSpd_HM_alert[4])):
- BrDefDetection = True
- BrDefSev = 9
- return BrDefDetection, BrDefSev
-
- # Bearing rolling element frequency, moderate, CF = 9, Severity = 5
- # AND
- # AND
- # gE_BSF_1 >= Alert
- # NOR
- # Vel_BSF_2 >= Alert
- # Vel_BSF_4 >= Alert
- # Vel_RS_2 >= Alert
- # Vel_RS_3 >= Alert
- # Vel_RS_4 >= Alert
- # Vel_RS_5 >= Alert
-
- else:
- if gE_Bearing_Defect_HM[0] >= gE_Bearing_Defect_HM_alert[0] and \
- (not(Vel_Bearing_Defect_HM[1] >= Vel_Bearing_Defect_HM_alert[1] or Vel_Bearing_Defect_HM[3] >= Vel_Bearing_Defect_HM_alert[3] or \
- Vel_RunningSpd_HM[1] >= Vel_Bearing_RunningSpd_HM_alert[1] or Vel_RunningSpd_HM[2] >= Vel_Bearing_RunningSpd_HM_alert[2] or \
- Vel_RunningSpd_HM[3] >= Vel_Bearing_RunningSpd_HM_alert[3] or Vel_RunningSpd_HM[4] >= Vel_Bearing_RunningSpd_HM_alert[4])):
- BrDefDetection = True
- BrDefSev = 5
- return BrDefDetection, BrDefSev
- # Bearing rolling element frequency, suspect, CF = 3, Severity = 5
- # AND
- # OR
- # gE_BSF_1 = Alert
- # gE_BSF_2 = Alert
- # gE_BSF_4 = Alert
- # NOR
- # gE_BSF_1 = Danger
- # gE_BSF_2 = Danger
- # gE_BSF_4 = Danger
- # Vel_BSF_2 >= Alert
- # Vel_BSF_4 >= Alert
- # Vel_RS_2 >= Alert
- # Vel_RS_3 >= Alert
- # Vel_RS_4 >= Alert
- # Vel_RS_5 >= Alert
-
- else:
- if ((gE_Bearing_Defect_HM[0] >= gE_Bearing_Defect_HM_alert[0] and gE_Bearing_Defect_HM[0] < gE_Bearing_Defect_HM_danger[0]) or \
- (gE_Bearing_Defect_HM[1] >= gE_Bearing_Defect_HM_alert[1] and gE_Bearing_Defect_HM[1] < gE_Bearing_Defect_HM_danger[1]) or \
- (gE_Bearing_Defect_HM[3] >= gE_Bearing_Defect_HM_alert[3] and gE_Bearing_Defect_HM[3] < gE_Bearing_Defect_HM_danger[3] )) and \
- (not(gE_Bearing_Defect_HM[0] >= gE_Bearing_Defect_HM_danger[0] or gE_Bearing_Defect_HM[1] >= gE_Bearing_Defect_HM_danger[1] or gE_Bearing_Defect_HM[3] >= gE_Bearing_Defect_HM_danger[3] or \
- Vel_Bearing_Defect_HM[0] >= Vel_Bearing_Defect_HM_alert[0] or Vel_Bearing_Defect_HM[1] >= Vel_Bearing_Defect_HM_alert[1] or \
- Vel_RunningSpd_HM[1] >= Vel_Bearing_RunningSpd_HM_alert[1] or Vel_RunningSpd_HM[2] >= Vel_Bearing_RunningSpd_HM_alert[2] or \
- Vel_RunningSpd_HM[3] >= Vel_Bearing_RunningSpd_HM_alert[3] or Vel_RunningSpd_HM[4] >= Vel_Bearing_RunningSpd_HM_alert[4])):
- BrDefDetection = True
- BrDefSev = 1
-
- return BrDefDetection, BrDefSev
-
- return BrDefDetection, BrDefSev
- ###############################################################################
- # Check bearing cage defect
- if defectType == 'FTF':
- [gE_Bearing_Defect_HM_alert, gE_Bearing_Defect_HM_danger] = self.gE_Bearing_Defect_HM_Threshhold(gE_alert, gE_danger, defectType)
- # Bearing cage frequency, severe, CF = 6, Severity = 10
- # OR
- # gE_CG_1 >= Danger
- # gE_CG_2 >= Danger
-
- if gE_Bearing_Defect_HM[0] >= gE_Bearing_Defect_HM_danger[0] or gE_Bearing_Defect_HM[1] >= gE_Bearing_Defect_HM_danger[1]:
- BrDefDetection = True
- BrDefSev = 6
-
- return BrDefDetection, BrDefSev
- # Bearing cage frequency, moderate, CF = 5, Severity = 5
- # AND
- # OR
- # gE_CG_1 >= Alert
- # gE_CG_2 >= Alert
- # NOR
- # gE_CG_1 = Danger
- # gE_CG_2 = Danger
-
- else:
- if (gE_Bearing_Defect_HM[0] >= gE_Bearing_Defect_HM_alert[0] or gE_Bearing_Defect_HM[1] >= gE_Bearing_Defect_HM_alert[1]) and \
- (not(gE_Bearing_Defect_HM[0] >= gE_Bearing_Defect_HM_danger[0] or gE_Bearing_Defect_HM[1] >= gE_Bearing_Defect_HM_danger[1])):
- BrDefDetection = True
- BrDefSev = 3
-
- return BrDefDetection, BrDefSev
-
- return BrDefDetection, BrDefSev
-
- ###############################################################################
- ###############################################################################
- # @staticmethod
- def RunningSpd_Symptom_Rule(self,Vel_RunningSpd_HM, Vel_RunningSpd_HM_alert, Vel_RunningSpd_HM_danger):
- RPM1_MOD = False
- RPM1_SEV = False
- RPM2_MOD = False
- RPM2_SEV = False
- RPM345_MOD = False
- RPM345_SEV = False
- # 1x RPM, Moderate, CF=8, Severity = 5
- # AND
- # Vel_RS_1 = Alert
-
- if Vel_RunningSpd_HM[0] >= Vel_RunningSpd_HM_alert[0] and Vel_RunningSpd_HM[0] < Vel_RunningSpd_HM_danger[0]:
- RPM1_MOD = True
- # 1x RPM, Severe, CF=8, Severity = 10
- # AND
- # Vel_RS_1 = Danger
-
- if Vel_RunningSpd_HM[0] >= Vel_RunningSpd_HM_danger[0]:
- RPM1_SEV = True
-
- # 2x RPM, Moderate, CF=8, Severity = 5
- # AND
- # Vel_RS_2 = Alert
-
- if Vel_RunningSpd_HM[1] >= Vel_RunningSpd_HM_alert[1] and Vel_RunningSpd_HM[1] < Vel_RunningSpd_HM_danger[1]:
- RPM2_MOD = True
- # 2x RPM, Severe, CF=8, Severity = 10
- # AND
- # Vel_RS_2 = Danger
-
- if Vel_RunningSpd_HM[1] >= Vel_RunningSpd_HM_danger[1]:
- RPM2_SEV = True
- # 3x, 4x, 5x RPM, moderate, CF=8, Severity = 5
- # AND
- # OR
- # Vel_RS_3 = Alert
- # Vel_RS_4 = Alert
- # Vel_RS_5 = Alert
- # NOR
- # Vel_RS_3 = Danger
- # Vel_RS_4 = Danger
- # Vel_RS_5 = Danger
-
- if (Vel_RunningSpd_HM[2] >= Vel_RunningSpd_HM_alert[2] and Vel_RunningSpd_HM[2] < Vel_RunningSpd_HM_danger[2] or \
- Vel_RunningSpd_HM[3] >= Vel_RunningSpd_HM_alert[3] and Vel_RunningSpd_HM[3] < Vel_RunningSpd_HM_danger[3] or \
- Vel_RunningSpd_HM[4] >= Vel_RunningSpd_HM_alert[4] and Vel_RunningSpd_HM[4] < Vel_RunningSpd_HM_danger[4]) and \
- (not(Vel_RunningSpd_HM[2] >= Vel_RunningSpd_HM_danger[2] or Vel_RunningSpd_HM[3] >= Vel_RunningSpd_HM_danger[3] or \
- Vel_RunningSpd_HM[4] >= Vel_RunningSpd_HM_danger[4])):
- RPM345_MOD = True
-
- # 3x, 4x, 5x RPM, Sever, CF=8, Severity = 10
- # OR
- # Vel_RS_3 = Danger
- # Vel_RS_4 = Danger
- # Vel_RS_5 = Danger
- if Vel_RunningSpd_HM[2] >= Vel_RunningSpd_HM_danger[2] or Vel_RunningSpd_HM[3] >= Vel_RunningSpd_HM_danger[3] or \
- Vel_RunningSpd_HM[4] >= Vel_RunningSpd_HM_danger[4]:
- RPM345_SEV = True
-
- return RPM1_MOD, RPM1_SEV, RPM2_MOD, RPM2_SEV, RPM345_MOD, RPM345_SEV
- ###############################################################################
- ###############################################################################
- # @staticmethod
- # Note: The alert and danger threshold values (in mm/s RMS) are set according to ISO vibration standard for flexible mounting in group 3
-
- def RunningSpd_Fault_Diag(self,Vel_RunningSpd_HM, Vel_alert = 7.1, Vel_danger = 11, defectType = 'Unbalance'):
- RPM1_MOD = False
- RPM1_SEV = False
- RPM2_MOD = False
- RPM2_SEV = False
- RPM345_MOD = False
- RPM345_SEV = False
-
- UnbalanceDetection = False
- UnbalanceSev = 0
- MisalignmentDetction = False
- MisalignmentSev = 0
- LoosenessDetection = False
- LoosenessSev = 0
-
- Vel_Unbalance_HM_alert = np.zeros(5)
- Vel_Unbalance_HM_danger = np.zeros(5)
- Vel_Misalignment_HM_alert = np.zeros(5)
- Vel_Misalignment_HM_danger = np.zeros(5)
- Vel_Looseness_HM_alert = np.zeros(5)
- Vel_Looseness_HM_danger = np.zeros(5)
-
- ###############################################################################
- # Check Unbalance
- if defectType == 'Unbalance':
- [Vel_Unbalance_HM_alert, Vel_Unbalance_HM_danger] = self.Vel_Unbalance_HM_Threshold(Vel_alert, Vel_danger)
- [RPM1_MOD, RPM1_SEV, RPM2_MOD, RPM2_SEV, RPM345_MOD, RPM345_SEV] = self.RunningSpd_Symptom_Rule(Vel_RunningSpd_HM, Vel_Unbalance_HM_alert, Vel_Unbalance_HM_danger)
- # print('RPM1_MOD,RPM1_SEV, RPM2_MOD, RPM2_SEV, RPM345_MOD, RPM345_SEV',' ',RPM1_MOD,' ', RPM1_SEV,' ', RPM2_MOD, ' ',RPM2_SEV, ' ',RPM345_MOD, ' ',RPM345_SEV)
- # Unbalance, severe, rather confident, 1x RPM peak dominates, CF=8, Severity = 10
- # AND
- # RPM1_SEV == True
- # NOR
- # RPM2_MOD == True
- # RPM2_SEV == True
- # RPM345_MOD == True
- # RPM345_SEV == True
-
- if RPM1_SEV == True and (not (RPM2_MOD == True or RPM2_SEV == True or RPM345_MOD == True or RPM345_SEV == True )):
- UnbalanceDetection = True
- UnbalanceSev = 8
- else:
- # Unbalance, severe, somewhat confident 1x RPM peak dominates but low level of 2xRPM is possible, CF=6, Severity = 10
- # AND
- # RPM1_SEV == True
- # NOR
- # RPM2_SEV == True
- # RPM345_MOD == True
- # RPM345_SEV == True
-
- if RPM1_SEV == True and (not(RPM2_SEV == True or RPM345_MOD == True or RPM345_SEV == True )):
- UnbalanceDetection = True
- UnbalanceSev = 6
- else:
- # Unbalance, moderate, rather confident since 1x RPM peak dominates, CF=8, Severity = 5
- # AND
- # RPM1_MOD == True
- # NOR
- # RPM2_MOD == True
- # RPM2_SEV == True
- # RPM345_MOD == True
- # RPM345_SEV == True
-
- if RPM1_MOD == True and (not(RPM2_MOD == True or RPM2_SEV == True or RPM345_MOD == True or RPM345_SEV == True )):
- UnbalanceDetection = True
- UnbalanceSev = 5
- return UnbalanceDetection, UnbalanceSev
- ###############################################################################
- # Check Misalignment
- if defectType == 'Misalignment':
- [Vel_Misalignment_HM_alert, Vel_Misalignment_HM_danger] = self.Vel_Misalignment_HM_Threshold(Vel_alert, Vel_danger)
- [RPM1_MOD, RPM1_SEV, RPM2_MOD, RPM2_SEV, RPM345_MOD, RPM345_SEV] = self.RunningSpd_Symptom_Rule(Vel_RunningSpd_HM, Vel_Misalignment_HM_alert, Vel_Misalignment_HM_danger)
- # Misalignment, moderate CF = 8, Severity = 10
- # AND
- # RPM2_SEV == True
- # OR
- # RPM1_MOD == True
- # RPM1_SEV == True
- # RPM345_MOD == True
- # NOR
- # RPM345_SEV == True
-
- if RPM2_SEV == True and (RPM1_MOD == True or RPM1_SEV == True or RPM345_MOD == True) and (not(RPM1_SEV == True)):
- MisalignmentDetction = True
- MisalignmentSev = 8
- # Misalignment, moderate CF = 6, Severity 10
- # AND
- # RPM2_SEV == True
- # NOR
- # RPM1_MOD == True
- # RPM1_SEV == True
- # RPM345_MOD == True
- # RPM345_SEV == True
- else:
- if RPM2_SEV == True and (not(RPM1_MOD == True or RPM1_SEV == True or RPM345_MOD == True or RPM345_SEV == True)):
- MisalignmentDetction = True
- MisalignmentSev = 6
- # Misalignment, moderate CF = 8, Severity = 5
- # AND
- # RPM2_MOD == True
- # OR
- # RPM1_MOD == True
- # RPM345_MOD == True
- # NOR
- # RPM1_SEV == True
- # RPM345_SEV == True
- else:
- if RPM2_MOD == True and (RPM1_MOD == True or RPM345_MOD == True) and (not(RPM1_SEV == True or RPM345_SEV == True)):
- MisalignmentDetction = True
- MisalignmentSev = 5
- # Misalignment, moderate CF = 6, Severity = 5
- # AND
- # RPM2_MOD == True
- # NOR
- # RPM1_MOD == True
- # RPM1_SEV == True
- # RPM345_MOD == True
- # RPM345_SEV == True
-
- else:
- if RPM2_MOD == True and (not (RPM1_MOD == True or RPM1_SEV == True or RPM345_MOD == True or RPM345_SEV == True)):
- MisalignmentDetction = True
- MisalignmentSev = 4
-
- return MisalignmentDetction, MisalignmentSev
- ###############################################################################
- # Check Looseness
- if defectType == 'Looseness':
- [Vel_Looseness_HM_alert, Vel_Looseness_HM_danger] = self.Vel_Looseness_HM_Threshold(Vel_alert, Vel_danger)
- [RPM1_MOD, RPM1_SEV, RPM2_MOD, RPM2_SEV, RPM345_MOD, RPM345_SEV] = self.RunningSpd_Symptom_Rule(Vel_RunningSpd_HM, Vel_Looseness_HM_alert, Vel_Looseness_HM_danger)
- # Mechanical looseness, sever CF = 8, Severity = 10
- # OR
- # AND
- # RPM1_SEV == True
- # OR
- # RPM345_MOD == True
- # RPM345_SEV == True
- # AND
- # RPM2_SEV == True
- # OR
- # RPM345_MOD == True
- # RPM345_SEV == True
- # AND
- # RPM345_SEV == True
- # OR
- # RPM1_MOD == True
- # RPM1_SEV == True
- # AND
- # RPM345_SEV == True
- # OR
- # RPM2_MOD == True
- # RPM2_SEV == True
-
- if (RPM1_SEV == True and (RPM345_MOD == True or RPM345_SEV == True )) or (RPM2_SEV == True and (RPM345_MOD == True or RPM345_SEV == True )) or \
- (RPM345_SEV == True and (RPM1_MOD == True or RPM1_SEV == True )) or (RPM345_SEV == True and (RPM2_MOD == True or RPM2_SEV == True )):
- LoosenessDetection = True
- LoosenessSev = 8
- # Mechanical looseness, sever CF = 6, Severity = 10
- # AND
- # RPM345_SEV == True
- # NOR
- # RPM1_MOD == True
- # RPM1_SEV == True
- # RPM2_MOD == True
- # RPM2_SEV == True
-
- else:
- if RPM345_SEV == True and (not( RPM1_MOD == True or RPM1_SEV == True or RPM2_MOD == True or RPM2_SEV == True )):
- LoosenessDetection = True
- LoosenessSev = 6
- # Mechanical looseness, moderate CF = 8, Severity = 5
- # AND
- # OR
- # AND
- # RPM1_MOD == True
- # RPM345_MOD == True
- # AND
- # RPM2_MOD == True
- # RPM345_MOD == True
- # NOR
- # RPM1_SEV == True
- # RPM2_SEV == True
- # RPM345_SEV == True
- else:
- if ((RPM1_MOD == True and RPM345_MOD == True )or(RPM2_MOD == True and RPM345_MOD == True))and\
- (not(RPM1_SEV == True or RPM2_SEV == True or RPM345_SEV == True)):
- LoosenessDetection = True
- LoosenessSev = 5
-
- # Mechanical looseness, moderate CF = 6, Severity = 5
- # AND
- # RPM345_MOD == True
- # NOR
- # RPM1_MOD == True
- # RPM1_SEV == True
- # RPM2_MOD == True
- # RPM2_SEV == True
-
- else:
- if RPM345_MOD == True and (not( RPM1_MOD == True or RPM1_SEV == True or RPM2_MOD == True or \
- RPM2_SEV == True )):
- LoosenessDetection = True
- LoosenessSev = 4
-
- return LoosenessDetection, LoosenessSev
-
- ###############################################################################
- ###############################################################################
- # @staticmethod
- def GMF_GTIF_Symptom_Rule(self,Vel_GMF_HM, Acc_GMF_HM, gE_GMF_HM, gE_GTIF_HM, Vel_GMF_HM_alert, Vel_GMF_HM_danger, \
- Acc_GMF_HM_alert, Acc_GMF_HM_danger, gE_GMF_HM_alert, gE_GMF_HM_danger, gE_GTIF_HM_alert, \
- gE_GTIF_HM_danger):
- GMF_MOD = False
- GMF_SEV = False
- GTIF = False
-
- # Gear mesh frequency and harmonics, moderate, CF=8, Severity = 5
- # AND
- # OR
- # Vel_GMF_1 = Alert
- # Vel_GMF_2 = Alert
- # Vel_GMF_3 = Alert
- # Acc_GMF_1 = Alert
- # Acc_GMF_2 = Alert
- # Acc_GMF_3 = Alert
- # gE_GMF_1 = Alert
- # gE_GMF_2 = Alert
- # gE_GMF_3 = Alert
- # NOR
- # Vel_GMF_1 = Danger
- # Vel_GMF_2 = Danger
- # Vel_GMF_3 = Danger
- # Acc_GMF_1 = Danger
- # Acc_GMF_2 = Danger
- # Acc_GMF_3 = Danger
- # gE_GMF_1 = Danger
- # gE_GMF_2 = Danger
- # gE_GMF_3 = Danger
-
- if (Vel_GMF_HM[0] >= Vel_GMF_HM_alert[0] and Vel_GMF_HM[0] < Vel_GMF_HM_danger[0] or \
- Vel_GMF_HM[1] >= Vel_GMF_HM_alert[1] and Vel_GMF_HM[1] < Vel_GMF_HM_danger[1] or \
- Vel_GMF_HM[2] >= Vel_GMF_HM_alert[2] and Vel_GMF_HM[2] < Vel_GMF_HM_danger[2] or \
- Acc_GMF_HM[0] >= Acc_GMF_HM_alert[0] and Acc_GMF_HM[0] < Acc_GMF_HM_danger[0] or \
- Acc_GMF_HM[1] >= Acc_GMF_HM_alert[1] and Acc_GMF_HM[1] < Acc_GMF_HM_danger[1] or \
- Acc_GMF_HM[2] >= Acc_GMF_HM_alert[2] and Acc_GMF_HM[2] < Acc_GMF_HM_danger[2] or \
- gE_GMF_HM[0] >= gE_GMF_HM_alert[0] and gE_GMF_HM[0] < gE_GMF_HM_danger[0] or \
- gE_GMF_HM[1] >= gE_GMF_HM_alert[1] and gE_GMF_HM[1] < gE_GMF_HM_danger[1] or \
- gE_GMF_HM[2] >= gE_GMF_HM_alert[2] and gE_GMF_HM[2] < gE_GMF_HM_danger[2]) \
- and \
- (not(Vel_GMF_HM[0] >= Vel_GMF_HM_danger[0] or \
- Vel_GMF_HM[1] >= Vel_GMF_HM_danger[1] or \
- Vel_GMF_HM[2] >= Vel_GMF_HM_danger[2] or \
- Acc_GMF_HM[0] >= Acc_GMF_HM_danger[0] or \
- Acc_GMF_HM[1] >= Acc_GMF_HM_danger[1] or \
- Acc_GMF_HM[2] >= Acc_GMF_HM_danger[2] or \
- gE_GMF_HM[0] >= gE_GMF_HM_danger[0] or \
- gE_GMF_HM[1] >= gE_GMF_HM_danger[1] or \
- gE_GMF_HM[2] >= gE_GMF_HM_danger[2])):
-
- GMF_MOD = True
- # Gear mesh frequency and harmonics, sever, CF=8, Severity = 10
- # OR
- # Vel_GMF_1 = Danger
- # Vel_GMF_2 = Danger
- # Vel_GMF_3 = Danger
- # Acc_GMF_1 = Danger
- # Acc_GMF_2 = Danger
- # Acc_GMF_3 = Danger
- # gE_GMF_1 = Danger
- # gE_GMF_2 = Danger
- # gE_GMF_3 = Danger
-
- if (Vel_GMF_HM[0] >= Vel_GMF_HM_danger[0] or \
- Vel_GMF_HM[1] >= Vel_GMF_HM_danger[1] or \
- Vel_GMF_HM[2] >= Vel_GMF_HM_danger[2] or \
- Acc_GMF_HM[0] >= Acc_GMF_HM_danger[0] or \
- Acc_GMF_HM[1] >= Acc_GMF_HM_danger[1] or \
- Acc_GMF_HM[2] >= Acc_GMF_HM_danger[2] or \
- gE_GMF_HM[0] >= gE_GMF_HM_danger[0] or \
- gE_GMF_HM[1] >= gE_GMF_HM_danger[1] or \
- gE_GMF_HM[2] >= gE_GMF_HM_danger[2]):
-
- GMF_SEV = True
-
- # Gear tooth impact frequency and harmonics, CF=8, Severity = 10
- # OR
- # gE_GTIF_1 >= Alert
- # gE_GTIF_2 >= Alert
- # gE_GTIF_3 >= Alert
- # gE_GTIF_4 >= Alert
- # gE_GTIF_5 >= Alert
-
- if (gE_GTIF_HM[0] >= gE_GTIF_HM_alert[0] or \
- gE_GTIF_HM[1] >= gE_GTIF_HM_alert[1] or \
- gE_GTIF_HM[2] >= gE_GTIF_HM_alert[2] or \
- gE_GTIF_HM[3] >= gE_GTIF_HM_alert[3] or \
- gE_GTIF_HM[4] >= gE_GTIF_HM_alert[4]):
-
- GTIF = True
-
-
- return GMF_MOD, GMF_SEV, GTIF
- ###############################################################################
- ###############################################################################
- # @staticmethod
- def Gear_Fault_Diag(self,Acc_GMF_HM, Vel_GMF_HM, gE_GMF_HM, gE_GTIF_HM, Acc_GMF_alert_gPk = 0.299, Acc_GMF_danger_gPk = 0.344, \
- Vel_GMF_alert_mmsRMS = 4.0, Vel_GMF_danger_mmsRMS = 8.0, gE_GMF_alert_gE = 3.0, \
- gE_GMF_danger_gE = 6.0, gE_GTIF_alert_gE = 3.0, gE_GTIF_danger_gE = 6.0):
-
- GMF_MOD = False
- GMF_SEV = False
- GTIF = False
-
- Acc_GMF_HM_alert =[]
- Acc_GMF_HM_danger = []
- Vel_GMF_HM_alert =[]
- Vel_GMF_HM_danger = []
- gE_GMF_HM_alert = []
- gE_GMF_HM_danger = []
- gE_GTIF_HM_alert = []
- gE_GTIF_HM_danger = []
-
- GearToothWearDetection = False
- GearToothWearSev = 0
-
- GearToothCrackBrokenDetection = False
- GearToothCrackBrokenSev = 0
-
- [Acc_GMF_HM_alert, Acc_GMF_HM_danger] = self.Acc_GMF_HM_Threshhold(Acc_GMF_alert_gPk, Acc_GMF_danger_gPk)
- [Vel_GMF_HM_alert, Vel_GMF_HM_danger] = self.Vel_GMF_HM_Threshhold(Vel_GMF_alert_mmsRMS, Vel_GMF_danger_mmsRMS)
- [gE_GMF_HM_alert, gE_GMF_HM_danger] = self.gE_GMF_HM_Threshhold(gE_GMF_alert_gE, gE_GMF_danger_gE)
- [gE_GTIF_HM_alert, gE_GTIF_HM_danger] = self.gE_GTIF_HM_Threshhold(gE_GTIF_alert_gE, gE_GTIF_danger_gE)
-
- [GMF_MOD, GMF_SEV, GTIF] = self.GMF_GTIF_Symptom_Rule(Vel_GMF_HM, Acc_GMF_HM, gE_GMF_HM, gE_GTIF_HM, Vel_GMF_HM_alert, \
- Vel_GMF_HM_danger, Acc_GMF_HM_alert, Acc_GMF_HM_danger, \
- gE_GMF_HM_alert, gE_GMF_HM_danger, gE_GTIF_HM_alert, gE_GTIF_HM_danger)
- # Gear wear, misalignment, or eccentricity, sever, CF = 8, severity = 10
- # AND
- # GMF_SEV = True
-
- if GMF_SEV == True:
- GearToothWearDetection = True
- GearToothWearSev = 10
-
- # Gear wear, misalignment, or eccentricity, moderate, CF = 8, severity = 5
- # AND
- # GMF_MOD = True
-
- else:
- if GMF_MOD == True:
- GearToothWearDetection = True
- GearToothWearSev = 5
- # Gear tooth broken or cracked, CF = 8, severity = 5
- # AND
- # GTIF = True
- # NOR
- # GMF_MOD = True
- # GMF_SEV = True
-
- if GTIF == True and (not(GMF_MOD == True or GMF_SEV == True)):
- GearToothCrackBrokenDetection = True
- GearToothCrackBrokenSev = 5
-
- return GearToothWearDetection, GearToothWearSev, GearToothCrackBrokenDetection, GearToothCrackBrokenSev
-
- ###############################################################################
- ###############################################################################
- # @staticmethod
- # Note: the default alert and danger threshold values (in mm/s RMS for velocity and g peak for acceleration) are set according a DSS AC motor model, it can be adjusted if necessary
- def RBPF_Symptom_Rule(self,Vel_RBPF_HM, Acc_RBPF_HM, Vel_RBPF_HM_alert, Vel_RBPF_HM_danger, Acc_RBPF_HM_alert, \
- Acc_RBPF_HM_danger):
- RBPF_MOD = False
- RBPF_SEV = False
-
- # Rotorbar pass frequency, sever, CF=8, severity = 10
- # OR
- # Vel_RBPF_1 == Danger
- # Acc_RBPF_1 == Danger
-
- if (Vel_RBPF_HM[0] >= Vel_RBPF_HM_danger[0] or Acc_RBPF_HM[0] >= Acc_RBPF_HM_danger[0]):
- RBPF_SEV = True
- # Rotorbar pass frequency, moderate, CF=8, severity = 5
- # OR
- # Vel_RBPF_1 == Alert
- # Acc_RBPF_1 == Alert
-
- else:
- if (Vel_RBPF_HM[0] >= Vel_RBPF_HM_alert[0] or Acc_RBPF_HM[0] >= Acc_RBPF_HM_alert[0]) and Vel_RBPF_HM[0] < Vel_RBPF_HM_danger[0] and Acc_RBPF_HM[0] < Acc_RBPF_HM_danger[0]:
- RBPF_MOD = True
-
- return RBPF_MOD, RBPF_SEV
-
- ###############################################################################
- ###############################################################################
- # @staticmethod
- # Note: the default alert and danger threshold values (in mm/s RMS for velocity and g peak for acceleration) are set according a DSS AC motor model, it can be adjusted if necessary
- def Cracked_Rotorbar_Diag(self,Vel_RBPF_HM, Acc_RBPF_HM, Vel_RBPF_alert_mmsRMS = 0.064*25.4, \
- Vel_RBPF_danger_mmsRMS = 0.127*25.4, Acc_RBPF_alert_gPk = 2.5, Acc_RBPF_danger_gPk = 3.75):
- RBPF_MOD = False
- RBPF_SEV = False
- Vel_RBPF_HM_alert = []
- Vel_RBPF_HM_danger = []
- Acc_RBPF_HM_alert = []
- Acc_RBPF_HM_danger = []
-
- CrackedRotorbarDetection = False
- CrackedRotorbarSev = 0
- [Acc_RBPF_HM_alert, Acc_RBPF_HM_danger] = self.Acc_RBPF_HM_Threshhold(Acc_RBPF_alert_gPk, Acc_RBPF_danger_gPk)
- [Vel_RBPF_HM_alert,Vel_RBPF_HM_danger] = self.Vel_RBPF_HM_Threshhold(Vel_RBPF_alert_mmsRMS, Vel_RBPF_danger_mmsRMS)
-
- [RBPF_MOD, RBPF_SEV] = self.RBPF_Symptom_Rule(Vel_RBPF_HM, Acc_RBPF_HM, Vel_RBPF_HM_alert, Vel_RBPF_HM_danger, Acc_RBPF_HM_alert, Acc_RBPF_HM_danger)
- # Cracked rotorbar, sever CF = 8, severity = 10
- # AND
- # RBPF_SEV = True
- if RBPF_SEV == True:
- CrackedRotorbarDetection = True
- CrackedRotorbarSev = 8
- # Cracked rotorbar, moderate CF = 8, severity = 5
- # AND
- # RBPF_MOD = True
- # NOR
- # RBPF_SEV = True
- if RBPF_MOD == True and (not(RBPF_SEV == True)):
- CrackedRotorbarDetection = True
- CrackedRotorbarSev = 5
- return CrackedRotorbarDetection, CrackedRotorbarSev
-
- ###############################################################################
- ###############################################################################
- # @staticmethod
- # Note: the default velocity alert and danger threshold (in mm/s RMS for velocity) is set according a DSS AC motor model, it can be adjusted if necessary
- def LF2X_Symptom_Rule(self,Vel_2XLF_HM, gE_2XLF_HM, Vel_2XLF_HM_alert, Vel_2XLF_HM_danger, gE_2XLF_HM_alert, gE_2XLF_HM_danger):
- LF2X_MOD = False
- LF2X_SEV = False
- # 2X line frequency, moderate, CF=8, severity = 5
- # AND
- # Vel_2XLF_1 = alert
-
- if Vel_2XLF_HM[0] >= Vel_2XLF_HM_alert[0] and Vel_2XLF_HM[0] < Vel_2XLF_HM_danger[0]:
- LF2X_MOD = True
- # 2X line frequency, moderate, several defect peaks, no confirming velocity, CF=8, severity = 5
- # AND
- # OR
- # AND
- # gE_2XLF_1 = alert
- # gE_2XLF_2 = alert
- # AND
- # gE_2XLF_1 = alert
- # gE_2XLF_3 = alert
- # AND
- # gE_2XLF_1 = alert
- # gE_2XLF_4 = alert
- # AND
- # gE_2XLF_1 = alert
- # gE_2XLF_5 = alert
- # NOR
- # Vel_2XLF_1 >= alert
- else:
- if (((gE_2XLF_HM[0] >= gE_2XLF_HM_alert[0] and gE_2XLF_HM[0] < gE_2XLF_HM_danger[0]) and (gE_2XLF_HM[1] >= gE_2XLF_HM_alert[1] and gE_2XLF_HM[1] < gE_2XLF_HM_danger[1])) or \
- ((gE_2XLF_HM[0] >= gE_2XLF_HM_alert[0] and gE_2XLF_HM[0] < gE_2XLF_HM_danger[0]) and (gE_2XLF_HM[2] >= gE_2XLF_HM_alert[2] and gE_2XLF_HM[2] < gE_2XLF_HM_danger[2])) or \
- ((gE_2XLF_HM[0] >= gE_2XLF_HM_alert[0] and gE_2XLF_HM[0] < gE_2XLF_HM_danger[0]) and (gE_2XLF_HM[3] >= gE_2XLF_HM_alert[3] and gE_2XLF_HM[3] < gE_2XLF_HM_danger[3])) or \
- ((gE_2XLF_HM[0] >= gE_2XLF_HM_alert[0] and gE_2XLF_HM[0] < gE_2XLF_HM_danger[0]) and (gE_2XLF_HM[4] >= gE_2XLF_HM_alert[4] and gE_2XLF_HM[4] < gE_2XLF_HM_danger[4]))) and \
- (not(Vel_2XLF_HM[0] >= Vel_2XLF_HM_alert[0])):
- LF2X_MOD = True
- # 2X line frequency, severe, CF=8, severity = 10
- # AND
- # Vel_2XLF_1 = Danger
-
- if Vel_2XLF_HM[0] >= Vel_2XLF_HM_danger[0]:
- LF2X_SEV = True
- # 2X line frequency, severe, several defect peaks, no confirming velocity, CF=8, severity = 10
- # AND
- # OR
- # AND
- # gE_2XLF_1 >= danger
- # gE_2XLF_2 >= alert
- # AND
- # gE_2XLF_1 >= danger
- # gE_2XLF_3 >= alert
- # AND
- # gE_2XLF_1 >= danger
- # gE_2XLF_4 >= alert
- # AND
- # gE_2XLF_1 >= danger
- # gE_2XLF_5 >= alert
- # NOR
- # Vel_2XLF_1 >= alert
-
- else:
- if (((gE_2XLF_HM[0] >= gE_2XLF_HM_danger[0]) and (gE_2XLF_HM[1] >= gE_2XLF_HM_alert[1])) or \
- ((gE_2XLF_HM[0] >= gE_2XLF_HM_danger[0]) and (gE_2XLF_HM[2] >= gE_2XLF_HM_alert[2])) or \
- ((gE_2XLF_HM[0] >= gE_2XLF_HM_danger[0]) and (gE_2XLF_HM[3] >= gE_2XLF_HM_alert[3])) or \
- ((gE_2XLF_HM[0] >= gE_2XLF_HM_danger[0]) and (gE_2XLF_HM[4] >= gE_2XLF_HM_alert[4]))) and \
- (not(Vel_2XLF_HM[0] < Vel_2XLF_HM_alert[0])):
- LF2X_SEV = True
- # 2X line frequency, severe, confirmed by velocity spectrum, CF=8, severity = 10
- # AND
- # OR
- # gE_2XLF_1 >= Alert
- # gE_2XLF_2 >= Alert
- # OR
- # Vel_2XLF_1 >= Alert
-
-
- else:
- if (gE_2XLF_HM[0] >= gE_2XLF_HM_alert[0] or gE_2XLF_HM[1] >= gE_2XLF_HM_alert[1]) and \
- Vel_2XLF_HM[0] >= Vel_2XLF_HM_alert[0]:
- LF2X_SEV = True
-
- return LF2X_MOD, LF2X_SEV
-
- ###############################################################################
- ###############################################################################
- # @staticmethod
- def Variable_AirGap_Diag(self,Vel_2XLF_HM, gE_2XLF_HM, Vel_2XLF_alert = 0.064*25.4, Vel_2XLF_danger = 0.127*25.4, gE_2XLF_alert = 3, gE_2XLF_danger = 10):
- LF2X_MOD = False
- LF2X_SEV = False
- gE_2XLF_HM_alert = []
- gE_2XLF_HM_danger = []
- Vel_2XLF_HM_alert = []
- Vel_2XLF_HM_danger = []
-
- VariableAirgapDetection = False
- VariableAirgapSev = 0
-
- [gE_2XLF_HM_alert,gE_2XLF_HM_danger] = self.gE_2XLF_HM_Threshhold(gE_2XLF_alert, gE_2XLF_danger)
- [Vel_2XLF_HM_alert,Vel_2XLF_HM_danger] = self.Vel_2XLF_HM_Threshhold(Vel_2XLF_alert, Vel_2XLF_danger)
- [LF2X_MOD, LF2X_SEV] = self.LF2X_Symptom_Rule(Vel_2XLF_HM, gE_2XLF_HM, Vel_2XLF_HM_alert, Vel_2XLF_HM_danger,gE_2XLF_HM_alert, gE_2XLF_HM_danger)
- # Variable air gap, sever CF = 8, severity = 10
- # AND
- # LF2X_SEV = True
- if LF2X_SEV == True:
- VariableAirgapDetection = True
- VariableAirgapSev = 8
- # Variable air gap, moderate CF = 8, severity = 5
- # AND
- # LF2X_MOD = True
- # NOR
- # LF2X_SEV = True
- else:
- if LF2X_MOD == True and LF2X_SEV == False:
- VariableAirgapDetection = True
- VariableAirgapSev = 5
-
- return VariableAirgapDetection, VariableAirgapSev
- ###############################################################################
- ###############################################################################
-
- def VPF_Symptom_Rule(self,Vel_VPF_HM, Vel_VPF_HM_alert, Vel_VPF_HM_danger):
- VAN_VPFH_MOD = False
- VAN_VPFH_SEV = False
- # Vane pass frequency and harmonics (VPFH), sever, CF=8, Severity = 10
- # OR
- # Vel_VPF_1 = Danger
- # Vel_VPF_2 = Danger
-
- if Vel_VPF_HM[0] >= Vel_VPF_HM_danger[0] or Vel_VPF_HM[1] >= Vel_VPF_HM_danger[1] :
- VAN_VPFH_SEV = True
-
- # Vane pass frequency and harmonics (VPFH), moderate, CF=8, Severity = 5
- # AND
- # OR
- # Vel_VPF_1 = Alert
- # Vel_VPF_2 = Alert
- # NOR
- # Vel_VPF_1 = Danger
- # Vel_VPF_2 = Danger
-
-
- if (Vel_VPF_HM[0] >= Vel_VPF_HM_alert[0] and Vel_VPF_HM[0] < Vel_VPF_HM_danger[0] or\
- Vel_VPF_HM[1] >= Vel_VPF_HM_alert[1] and Vel_VPF_HM[1] < Vel_VPF_HM_danger[1]) and\
- (not(Vel_VPF_HM[0] >= Vel_VPF_HM_danger[0] or Vel_VPF_HM[1] >= Vel_VPF_HM_danger[1])):
- VAN_VPFH_MOD = True
- return VAN_VPFH_MOD, VAN_VPFH_SEV
-
- ###############################################################################
- ###############################################################################
- # @staticmethod
- def Vane_WearDamage_Diag(self,Vel_VPF_HM, Vel_VPF_alert_mmsRMS = 0.159*25.4, \
- Vel_VPF_danger_mmsRMS = 0.318*25.4):
- VAN_VPFH_MOD = False
- VAN_VPFH_SEV = False
- Vel_VPF_HM_alert = []
- Vel_VPF_HM_danger = []
-
- VaneWearDamageDetection = False
- VaneWearDamageSev = 0
-
- [Vel_VPF_HM_alert,Vel_VPF_HM_danger] = self.Vel_VPF_HM_Threshhold(Vel_VPF_alert_mmsRMS, Vel_VPF_danger_mmsRMS)
- [VAN_VPFH_MOD, VAN_VPFH_SEV] = self.VPF_Symptom_Rule(Vel_VPF_HM, Vel_VPF_HM_alert, Vel_VPF_HM_danger)
- # Vane wear or damage, severe CF = 8, severity = 10
- # OR
- # VAN_VPFH_SEV= True
-
- if VAN_VPFH_SEV == True:
- VaneWearDamageDetection = True
- VaneWearDamageSev = 10
- # Vane wear or damage, moderate CF = 6, severity = 5
- # OR
- # VAN_VPFH_MOD= True
-
- else:
- if VAN_VPFH_MOD == True:
- VaneWearDamageDetection = True
- VaneWearDamageSev = 5
-
- return VaneWearDamageDetection, VaneWearDamageSev
- ###############################################################################
- ###############################################################################
- # 巴特沃斯带通滤波
- # xTimeWave是时域波形数组, fs是采样频率,单位为Hz
- # lowcut 为低截止频率,单位为Hz
- # highcut 为高截止频率,单位为Hz
- # Order为滤波器阶数,通常为偶数,2,4,6,8一般不超过8
- def BandPassButter(self,xTimeWave, lowcut, highcut, fs, order):
- low = lowcut * 2 / fs
- high = highcut * 2 / fs
- sos = signal.butter(order, [low, high], 'bandpass', output='sos')
- filtered = signal.sosfilt(sos, xTimeWave)
- return filtered
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