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+# -*- coding: utf-8 -*-
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+"""
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+Spyder 编辑器
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+
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+这是一个临时脚本文件。
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+"""
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+import copy
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+import datetime
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+import multiprocessing
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+import os
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+
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+import pandas as pd
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+import numpy as np
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+
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+dianjian_str = """
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+wind_turbine_number
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+time_stamp 时间
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+active_power 有功功率 kW
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+rotor_speed 风轮转速 rpm
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+generator_speed 发电机转速 rpm
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+wind_velocity 风速 m/s
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+pitch_angle_blade_1 叶片1角度 °
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+pitch_angle_blade_2 叶片2角度 °
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+pitch_angle_blade_3 叶片3角度 °
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+cabin_position 机舱位置 °
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+true_wind_direction
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+yaw_error1 风向 °
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+twisted_cable_angle
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+main_bearing_temperature 主轴温度 ℃
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+gearbox_oil_temperature 齿轮箱温度 ℃
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+gearbox_low_speed_shaft_bearing_temperature 齿轮箱轴承温度 ℃
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+gearboxmedium_speed_shaftbearing_temperature
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+gearbox_high_speed_shaft_bearing_temperature 齿轮箱轴承温度2 ℃
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+generatordrive_end_bearing_temperature 发电机驱动侧轴承温度 ℃
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+generatornon_drive_end_bearing_temperature 发电机非驱动侧轴承温度 ℃
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+cabin_temperature 机舱温度 ℃
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+outside_cabin_temperature 舱外温度 ℃
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+generator_winding1_temperature
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+generator_winding2_temperature
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+generator_winding3_temperature
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+front_back_vibration_of_the_cabin
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+side_to_side_vibration_of_the_cabin
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+required_gearbox_speed
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+inverter_speed_master_control
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+actual_torque
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+given_torque
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+clockwise_yaw_count
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+counterclockwise_yaw_count
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+unusable
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+power_curve_available
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+set_value_of_active_power 有功功率设定 kW
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+wind_turbine_status
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+wind_turbine_status2
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+turbulence_intensity
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+"""
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+
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+datas = [i for i in dianjian_str.split("\n") if i]
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+
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+dianjian_dict = dict()
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+
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+for data in datas:
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+ ds = data.split("\t")
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+
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+ if len(ds) == 3:
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+ dianjian_dict[ds[0]] = ds[2]
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+ else:
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+ dianjian_dict[ds[0]] = ''
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+
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+
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+def read_df(file_path):
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+ df = pd.read_csv(file_path, header=[0, 1])
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+
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+ col_nams_map = dict()
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+ pre_col = ""
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+ for tuple_col in df.columns:
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+ col1 = tuple_col[0]
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+ col2 = tuple_col[1]
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+ if str(col1).startswith("Unnamed"):
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+ if pre_col:
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+ col1 = pre_col
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+ pre_col = ''
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+ else:
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+ col1 = ''
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+ else:
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+ pre_col = col1
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+
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+ if str(col2).startswith("Unnamed"):
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+ col2 = ''
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+
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+ col_nams_map[str(tuple_col)] = ''.join([col1, col2])
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+
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+ for k, v in col_nams_map.items():
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+ if str(v).endswith('均值'):
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+ col_nams_map[k] = str(v)[:-2]
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+
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+ df.columns = [str(col) for col in df.columns]
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+ df.rename(columns=col_nams_map, inplace=True)
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+
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+ for col, name in dianjian_dict.items():
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+ if name in df.columns:
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+ df.rename(columns={name: col}, inplace=True)
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+
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+ for col in df.columns:
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+ if col not in dianjian_dict.keys():
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+ del df[col]
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+
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+ return df
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+
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+
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+def get_wind_name_files(path):
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+ files = os.listdir(path)
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+
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+ wind_files_map = dict()
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+ for file in files:
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+ full_file = os.path.join(path, file)
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+ file_datas = str(file).split("@")
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+ key = file_datas[0].replace("HD", "HD2")
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+ if key in wind_files_map.keys():
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+ wind_files_map[key].append(full_file)
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+ else:
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+ wind_files_map[key] = [full_file]
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+
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+ return wind_files_map
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+
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+
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+def combine_df(save_path, wind_name, files):
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+ begin = datetime.datetime.now()
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+ df = pd.DataFrame()
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+ for file in files:
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+ query_df = read_df(file)
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+ print("读取", file, query_df.shape)
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+ query_df['time_stamp'] = pd.to_datetime(query_df['time_stamp'])
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+ query_df.set_index(keys='time_stamp', inplace=True)
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+ query_df = query_df[~query_df.index.duplicated(keep='first')]
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+ if df.empty:
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+ df = copy.deepcopy(query_df)
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+ else:
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+ df = pd.concat([df, query_df], axis=1, join='inner')
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+ df.reset_index(inplace=True)
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+ df['wind_turbine_number'] = wind_name
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+ for col, name in dianjian_dict.items():
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+ if col not in df.columns:
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+ df[col] = np.nan
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+
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+ df = df[dianjian_dict.keys()]
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+ df.to_csv(os.path.join(save_path, wind_name + ".csv"), encoding='utf-8', index=False)
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+
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+ print(wind_name, '整理完成', '耗时:', (datetime.datetime.now() - begin).seconds)
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+
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+
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+if __name__ == '__main__':
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+ read_path = r'/data/download/collection_data/1进行中/诺木洪风电场-甘肃-华电/收资数据/sec'
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+ save_path = r'/data/download/collection_data/1进行中/诺木洪风电场-甘肃-华电/清理数据/sec'
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+
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+ # read_path = r'D:\trans_data\诺木洪\收资数据\min'
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+ # save_path = r'D:\trans_data\诺木洪\清理数据\min'
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+ if not os.path.exists(save_path):
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+ os.makedirs(save_path, exist_ok=True)
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+ wind_files_map = get_wind_name_files(read_path)
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+
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+ with multiprocessing.Pool(6) as pool:
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+ pool.starmap(combine_df, [(save_path, wind_name, files) for wind_name, files in wind_files_map.items()])
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