# -*- coding: utf-8 -*- """ Spyder 编辑器 这是一个临时脚本文件。 """ import os import pandas as pd pd.set_option('chained_assignment', None) select_cols = ['遥测ID号', '风场', '风场几期', '风机号', '测点', '标准化中文', '转发顺序号', 'en_name'] origin_col_map = { 'wind_turbine_number': '风机编号', 'wind_turbine_name': '风机原始名称', 'time_stamp': '时间戳', 'active_power': '有功功率', 'rotor_speed': '风轮转速', 'generator_speed': '发电机转速', 'wind_velocity': '风速', 'pitch_angle_blade_1': '桨距角1', 'pitch_angle_blade_2': '桨距角2', 'pitch_angle_blade_3': '桨距角3', 'cabin_position': '机舱位置', 'true_wind_direction': '绝对风向', 'yaw_error1': '对风角度', 'set_value_of_active_power': '有功功率设定值', 'gearbox_oil_temperature': '齿轮箱油温', 'generatordrive_end_bearing_temperature': '发电机驱动端轴承温度', 'generatornon_drive_end_bearing_temperature': '发电机非驱动端轴承温度', 'cabin_temperature': '机舱内温度', 'twisted_cable_angle': '扭缆角度', 'front_back_vibration_of_the_cabin': '机舱前后振动', 'side_to_side_vibration_of_the_cabin': '机舱左右振动', 'actual_torque': '实际力矩', 'given_torque': '给定力矩', 'clockwise_yaw_count': '顺时针偏航次数', 'counterclockwise_yaw_count': '逆时针偏航次数', 'unusable': '不可利用', 'power_curve_available': '功率曲线可用', 'required_gearbox_speed': '齿轮箱转速', 'inverter_speed_master_control': '变频器转速(主控)', 'outside_cabin_temperature': '环境温度', 'main_bearing_temperature': '主轴承轴承温度', 'gearbox_high_speed_shaft_bearing_temperature': '齿轮箱高速轴轴承温度', 'gearboxmedium_speed_shaftbearing_temperature': '齿轮箱中速轴轴承温度', 'gearbox_low_speed_shaft_bearing_temperature': '齿轮箱低速轴轴承温度', 'generator_winding1_temperature': '发电机绕组1温度', 'generator_winding2_temperature': '发电机绕组2温度', 'generator_winding3_temperature': '发电机绕组3温度', 'wind_turbine_status': '风机状态1', 'wind_turbine_status2': '风机状态2', 'turbulence_intensity': '湍流强度' } def youyu_measurepoint(df, name): df['风场几期'] = df['遥测ID号'].apply(lambda x: x.split(' ')[1].split('_')[1].split('-')[0][0:4]) df['风场'] = df['风场几期'].apply(lambda x: x[0:len(name)]) df['风机号'] = df['遥测ID号'].apply(lambda x: x.split(' ')[1].split('_')[1].split('-')[1][0:3]) df['测点'] = df['遥测ID号'].apply( lambda x: ''.join(x.replace('遥测值', '').strip().split(' ')[1:]).split('_')[1].split('-')[1][3:]) show_measurepoint(df, name + '测点') col_mapping = { "3#桨叶片角度": "pitch_angle_blade_3", "机舱侧向振动(已滤波)": "side_to_side_vibration_of_the_cabin", "机舱轴向振动(已滤波)": "front_back_vibration_of_the_cabin", "机舱角度": "cabin_position", "扭缆角度": "twisted_cable_angle", "发电机有功功率": "active_power", "发电机驱动端轴承温度": "generatordrive_end_bearing_temperature", "发电机非驱动端轴承温度": "generatornon_drive_end_bearing_temperature", "发电机定子U相线圈温度": "generator_winding1_temperature", "发电机定子V相线圈温度": "generator_winding2_temperature", "发电机定子W相线圈温度": "generator_winding3_temperature", "绕组温度1": "generator_winding1_temperature", "绕组温度2": "generator_winding2_temperature", "绕组温度3": "generator_winding3_temperature", "舱内温度": "cabin_temperature", "舱外温度": "outside_cabin_temperature", "风向": "true_wind_direction", "风速": "wind_velocity", "机舱中轴线与风向夹角": "yaw_error1", "1#桨叶片角度": "pitch_angle_blade_1", "2#桨叶片角度": "pitch_angle_blade_2", "发电机转速": "generator_speed", "主轴转速": "rotor_speed", "齿轮箱高速轴非驱动端轴承温度": "gearbox_high_speed_shaft_bearing_temperature", "齿轮箱油池温度": "gearbox_oil_temperature", "齿轮箱中速轴非驱动端轴承温度": "gearboxmedium_speed_shaftbearing_temperature", "主轴承外圈温度": "main_bearing_temperature", } df['en_name'] = df['测点'].map(col_mapping) print(df.groupby('en_name').count()) df.sort_values(by='转发顺序号', inplace=True) save_df(df, name + '测点') return df def pinglu_measurepoint(df, name): df['风场几期'] = df['遥测ID号'].apply(lambda x: x.split(' ')[1].split('_')[1].split('-')[0]) df['风场'] = df['风场几期'].apply(lambda x: x[0:len(name)]) df['风机号'] = df['遥测ID号'].apply(lambda x: x.split(' ')[2].split('-')[1][0:2]) df['测点'] = df['遥测ID号'].apply( lambda x: ''.join(x.replace('遥测值', '').strip().split(' ')[1:]).split('_')[1].split('-')[1][2:]) show_measurepoint(df, name + '测点') col_mapping = { "发电机非驱动端轴承温度": "generatornon_drive_end_bearing_temperature", "发电机定子U相线圈温度": "generator_winding1_temperature", "发电机定子V相线圈温度": "generator_winding2_temperature", "发电机转速": "generator_speed", "发电机驱动端轴承温度": "generatordrive_end_bearing_temperature", "2#桨叶片角度": "pitch_angle_blade_2", "主轴承外圈温度": "main_bearing_temperature", "发电机定子W相线圈温度": "generator_winding3_temperature", "发电机有功功率": "active_power", "主轴转速": "rotor_speed", "齿轮箱高速轴非驱动端轴承温度": "gearbox_high_speed_shaft_bearing_temperature", "1#桨叶片角度": "pitch_angle_blade_1", "舱外温度": "outside_cabin_temperature", "舱内温度": "cabin_temperature", "风向": "true_wind_direction", "机舱中轴线与风向夹角": "yaw_error1", "机舱角度": "cabin_position", "扭缆角度": "twisted_cable_angle", "3#桨叶片角度": "pitch_angle_blade_3", "机舱轴向振动(已滤波)": "front_back_vibration_of_the_cabin", "风速": "wind_velocity", "机舱侧向振动(已滤波)": "side_to_side_vibration_of_the_cabin", "齿轮箱高速轴费非驱动端轴承温度": "gearbox_high_speed_shaft_bearing_temperature", # 与“齿轮箱高速轴非驱动端轴承温度”相同 "机舱角度（位置）": "cabin_position", "机舱侧向振动值(已滤波)": "side_to_side_vibration_of_the_cabin", "机舱轴向振动值(已滤波)": "front_back_vibration_of_the_cabin", "机舱与风向夹角": "yaw_error1", "1#桨叶片角度(桨距角)": "pitch_angle_blade_1", "2#桨叶片角度(桨距角)": "pitch_angle_blade_2", "3#桨叶片角度(桨距角)": "pitch_angle_blade_3", "齿轮箱高速轴驱动端轴承温度": "gearbox_high_speed_shaft_bearing_temperature", # 根据规则，齿轮箱高速轴不区分驱动端和非驱动端 "齿轮箱中间轴非驱动端轴承温度": "gearboxmedium_speed_shaftbearing_temperature", } df['en_name'] = df['测点'].map(col_mapping) print(df.groupby('en_name').count()) df.sort_values(by='转发顺序号', inplace=True) save_df(df, name + '测点') return df def ruicheng_measurepoint(df, name): # 根据芮城数据格式调整字段提取逻辑 df['风场几期'] = df['遥测ID号'].apply(lambda x: x.split(' ')[1].split('_')[1][0:4]) df['风场'] = df['风场几期'].apply(lambda x: x[0:len(name)]) # 假设风机号在第三个分割段中 df['风机号'] = df['遥测ID号'].apply(lambda x: x.split(' ')[1].split('_')[1][6:9]) # 测点提取可能需要调整切片位置 df['测点'] = df['遥测ID号'].apply( lambda x: ''.join(x.replace('遥测值', '').strip().split(' ')[1:]).split('_')[1].split('-')[1][3:]) show_measurepoint(df, name + '测点') col_mapping = { "1#桨叶片角度": "pitch_angle_blade_1", "2#桨叶片角度": "pitch_angle_blade_2", "3#桨叶片角度": "pitch_angle_blade_3", "舱内温度": "cabin_temperature", "舱外温度": "outside_cabin_temperature", "齿轮箱高速轴非驱动端轴承温度": "gearbox_high_speed_shaft_bearing_temperature", "齿轮箱油池温度": "gearbox_oil_temperature", "发电机定子U相线圈温度": "generator_winding1_temperature", "发电机定子V相线圈温度": "generator_winding2_temperature", "发电机定子W相线圈温度": "generator_winding3_temperature", "发电机非驱动端轴承温度": "generatornon_drive_end_bearing_temperature", "发电机驱动端轴承温度": "generatordrive_end_bearing_temperature", "发电机有功功率": "active_power", "发电机转速": "generator_speed", "风速": "wind_velocity", "风向": "true_wind_direction", "机舱侧向振动(已滤波)": "side_to_side_vibration_of_the_cabin", "机舱角度": "cabin_position", "机舱中轴线与风向夹角": "yaw_error1", "机舱轴向振动(已滤波)": "front_back_vibration_of_the_cabin", "扭缆角度": "twisted_cable_angle", "主轴承外圈温度": "main_bearing_temperature", "主轴转速": "rotor_speed", "机舱与风向夹角": "yaw_error1", "机舱角度（位置）": "cabin_position", "1#桨叶片角度(桨距角)": "pitch_angle_blade_1", "2#桨叶片角度(桨距角)": "pitch_angle_blade_2", "3#桨叶片角度(桨距角)": "pitch_angle_blade_3", } df['en_name'] = df['测点'].map(col_mapping) print(df.groupby('en_name').count()) df.sort_values(by='转发顺序号', inplace=True) save_df(df, name + '测点') return df def yuxian_measurepoint(df, name): # 根据孟县数据格式调整字段提取逻辑 df['风场几期'] = df['遥测ID号'].apply(lambda x: x.split(' ')[1].split('_')[1].split('-')[0][0:4]) df['风场'] = df['风场几期'].apply(lambda x: x[0:len(name)]) # 假设风机号在第三个分割段中 df['风机号'] = df['遥测ID号'].apply(lambda x: x.split(' ')[1].split('-')[1][0:3]) # 测点提取可能需要调整切片位置 df['测点'] = df['遥测ID号'].apply( lambda x: ''.join(x.replace('遥测值', '').strip().split(' ')[1:]).split('-')[1][3:]) show_measurepoint(df, name + '测点') col_mapping = { "发电机定子W相线圈温度": "generator_winding3_temperature", "发电机非驱动端轴承温度": "generatornon_drive_end_bearing_temperature", "机舱侧向振动(已滤波)": "side_to_side_vibration_of_the_cabin", "风速": "wind_velocity", "机舱中轴线与风向夹角": "yaw_error1", "1#桨叶片角度": "pitch_angle_blade_1", "2#桨叶片角度": "pitch_angle_blade_2", "发电机有功功率": "active_power", "发电机转速": "generator_speed", "风向": "true_wind_direction", "发电机驱动端轴承温度": "generatordrive_end_bearing_temperature", "机舱轴向振动(已滤波)": "front_back_vibration_of_the_cabin", "机舱角度": "cabin_position", "扭揽角度": "twisted_cable_angle", "发电机定子U相线圈温度": "generator_winding1_temperature", "发电机定子V相线圈温度": "generator_winding2_temperature", "主轴转速": "rotor_speed", "齿轮箱中速轴非驱动端轴承温度": "gearboxmedium_speed_shaftbearing_temperature", "齿轮箱高速轴非驱动端轴承温度": "gearbox_high_speed_shaft_bearing_temperature", "齿轮箱油池温度": "gearbox_oil_temperature", "主轴承外圈温度": "main_bearing_temperature", "舱内温度": "cabin_temperature", "舱外温度": "outside_cabin_temperature", "3#桨叶片角度": "pitch_angle_blade_3", "扭缆角度": "twisted_cable_angle", "齿轮箱中间轴非驱动端轴承温度": "gearbox_high_speed_shaft_bearing_temperature", # 与“齿轮箱中速轴非驱动端轴承温度”相同 "主轴(风轮)转速": "rotor_speed", "1#桨叶片角度(桨距角)": "pitch_angle_blade_1", "2#桨叶片角度(桨距角)": "pitch_angle_blade_2", "3#桨叶片角度(桨距角)": "pitch_angle_blade_3", "机舱角度（位置）": "cabin_position", "机舱侧向振动值(已滤波)": "side_to_side_vibration_of_the_cabin", "机舱轴向振动值(已滤波)": "front_back_vibration_of_the_cabin", } df['en_name'] = df['测点'].map(col_mapping) print(df.groupby('en_name').count()) df.sort_values(by='转发顺序号', inplace=True) save_df(df, name + '测点') return df def gujiao_measurepoint(df, name): # 古交数据格式处理 df['风场几期'] = df['遥测ID号'].apply(lambda x: x.split(' ')[1].split('_')[1].split('-')[0][0:4]) df['风场'] = df['风场几期'].apply(lambda x: x[0:len(name)]) # 假设风机号在第三个分割段中 df['风机号'] = df['遥测ID号'].apply(lambda x: x.split(' ')[1].split('-')[1][0:3]) # 测点提取可能需要调整切片位置 df['测点'] = df['遥测ID号'].apply( lambda x: ''.join(x.replace('遥测值', '').strip().split(' ')[1:]).split('-')[1][3:]) show_measurepoint(df, name + '测点') col_mapping = { "机舱与风向夹角": "yaw_error1", "1#桨叶片角度(桨距角)": "pitch_angle_blade_1", "2#桨叶片角度(桨距角)": "pitch_angle_blade_2", "3#桨叶片角度(桨距角)": "pitch_angle_blade_3", "主轴转速": "rotor_speed", "齿轮箱高速轴非驱动端轴承温度": "gearbox_high_speed_shaft_bearing_temperature", "齿轮箱油池温度": "gearbox_oil_temperature", "主轴承外圈温度": "main_bearing_temperature", "发电机转速": "generator_speed", "发电机驱动端轴承温度": "generatordrive_end_bearing_temperature", "发电机非驱动端轴承温度": "generatornon_drive_end_bearing_temperature", "发电机定子U相线圈温度": "generator_winding1_temperature", "发电机定子V相线圈温度": "generator_winding2_temperature", "发电机定子W相线圈温度": "generator_winding3_temperature", "舱内温度": "cabin_temperature", "舱外温度": "outside_cabin_temperature", "风向": "true_wind_direction", "机舱角度（位置）": "cabin_position", "偏航角度(扭缆角度）": "twisted_cable_angle", # "桨叶片角度(桨距角)": ["pitch_angle_blade_1", "pitch_angle_blade_2", "pitch_angle_blade_3"], # 根据具体桨叶选择 "机舱侧向振动值(已滤波)": "side_to_side_vibration_of_the_cabin", "机舱轴向振动值(已滤波)": "front_back_vibration_of_the_cabin", "风速": "wind_velocity", "发电机有功功率": "active_power", } df['en_name'] = df['测点'].map(col_mapping) print(df.groupby('en_name').count()) df.sort_values(by='转发顺序号', inplace=True) save_df(df, name + '测点') return df def shilou_measurepoint(df, name): # 石楼数据格式处理 df['风场几期'] = df['遥测ID号'].apply(lambda x: x.split(' ')[1].split('_')[1].split('-')[0][0:4]) df['风场'] = df['风场几期'].apply(lambda x: x[0:len(name)]) # 假设风机号在第三个分割段中 df['风机号'] = df['遥测ID号'].apply(lambda x: x.split(' ')[1].split('-')[1][0:3]) # 测点提取可能需要调整切片位置 df['测点'] = df['遥测ID号'].apply( lambda x: ''.join(x.replace('遥测值', '').strip().split(' ')[1:]).split('-')[1][3:]) show_measurepoint(df, name + '测点') col_mapping = { "舱内温度": "cabin_temperature", "舱外温度": "outside_cabin_temperature", "偏航角度(扭缆角度）": "twisted_cable_angle", "风向": "true_wind_direction", "风速": "wind_velocity", "机舱中轴线与风向夹角": "yaw_error1", "1#桨叶片角度": "pitch_angle_blade_1", "2#桨叶片角度": "pitch_angle_blade_2", "3#桨叶片角度": "pitch_angle_blade_3", "主轴转速": "rotor_speed", "机舱轴向振动(已滤波)": "front_back_vibration_of_the_cabin", "发电机有功功率": "active_power", "发电机转速": "generator_speed", "机舱与风向夹角": "yaw_error1", "1#桨叶片角度(桨距角)": "pitch_angle_blade_1", "2#桨叶片角度(桨距角)": "pitch_angle_blade_2", "3#桨叶片角度(桨距角)": "pitch_angle_blade_3", "齿轮箱油池温度": "gearbox_oil_temperature", "主轴后轴承温度": "main_bearing_temperature", # 根据规则，主轴后轴承温度对应 main_bearing_temperature "发电机驱动端轴承温度": "generatordrive_end_bearing_temperature", "发电机非驱动端轴承温度": "generatornon_drive_end_bearing_temperature", "齿轮箱高速轴非驱动端轴承温度": "gearbox_high_speed_shaft_bearing_temperature", "发电机定子U相线圈温度": "generator_winding1_temperature", "发电机定子V相线圈温度": "generator_winding2_temperature", "发电机定子W相线圈温度": "generator_winding3_temperature", "机舱侧向振动值(已滤波)": "side_to_side_vibration_of_the_cabin", "机舱轴向振动值(已滤波)": "front_back_vibration_of_the_cabin", "齿轮箱中速轴非驱动端轴承温度": "gearboxmedium_speed_shaftbearing_temperature", "机舱角度（位置）": "cabin_position", } df['en_name'] = df['测点'].map(col_mapping) print(df.groupby('en_name').count()) df.sort_values(by='转发顺序号', inplace=True) save_df(df, name + '测点') return df def show_measurepoint(df, name): print(f'--------{name}-----------') for cn_name in df['测点'].unique(): print(f"{cn_name}:'',") print('-------------------') def save_df(df, name): df['遥测ID号'] = df['遥测ID号'].apply(lambda x: x.replace('遥测定义表 ', '').replace('遥测值', '').strip()) df['标准化中文'] = df['en_name'].map(origin_col_map) df.to_csv(r'C:\Users\wzl\Desktop\中广核104测点\2404' + os.sep + str(name) + '.csv', columns=select_cols, index=False, encoding='utf8') if __name__ == '__main__': df = pd.read_csv(r"D:\data\tmp\2404ZF.csv", encoding='gbk') # 添加右玉处理 youyu_df = youyu_measurepoint(df[df['遥测ID号'].str.contains('右玉')], '右玉') # 添加平陆处理 pinglu_df = pinglu_measurepoint(df[df['遥测ID号'].str.contains('平陆')], '平陆') # 添加芮城处理 ruicheng_df = ruicheng_measurepoint(df[df['遥测ID号'].str.contains('芮城')], '芮城') # 添加盂县处理 yuxian_df = yuxian_measurepoint(df[df['遥测ID号'].str.contains('盂县')], '盂县') # 添加古交处理 gujiao_df = gujiao_measurepoint(df[df['遥测ID号'].str.contains('古交')], '古交') # 添加石楼处理 shilou_df = shilou_measurepoint(df[df['遥测ID号'].str.contains('石楼')], '石楼') result_df = pd.concat([youyu_df, pinglu_df, ruicheng_df, yuxian_df, gujiao_df, shilou_df]) save_df(result_df, '2404测点')