PQ3000数据导出后用Python二次分析

PQ3000导出格式CSV时间戳各通道电压/电流/功率/谐波、COMTRADE录波文件、PQAnalyzer原生格式。环境搭建pip install pandas numpy matplotlib scipy数据读取pythonimport pandas as pdimport numpy as npfrom scipy import fftdf pd.read_csv(pq3000_data.csv, parse_dates[Time])df df.fillna(methodffill)df.set_index(Time, inplaceTrue)谐波分析pythonu_a df[U_A].valuesN len(u_a)T 1.0 / 51200yf fft.fft(u_a)xf np.fft.fftfreq(N, T)[:N//2]harmonics {}for i in range(1, 51):idx np.argmin(np.abs(xf - i * 50))harmonics[i] 2.0/N * np.abs(yf[idx])fundamental harmonics[1]h_sum np.sqrt(sum([h**2 for h in harmonics.values() if h ! fundamental]))thd h_sum / fundamental * 100print(fTHD {thd:.2f}%)电压暂降检测pythonu_rms df[U_A_RMS]threshold 0.9 * u_rms.mean()dips u_rms thresholdfrom scipy import ndimagelabeled, num_features ndimage.label(dips)print(f共检测到 {num_features} 次电压暂降)PQ3000的开放数据格式Python生态让电能质量分析从封闭到开放。