电缆次周期扰动电压特征提取方法

A feature extraction method of cable sub-cycle disturbance voltage

电缆发生绝缘缺陷时会引发次周期扰动电压现象,提取扰动电压特征对及时检测绝缘缺陷、保障电缆安全运行具有重要意义。对此,提出了一种电缆次周期扰动电压特征提取方法。首先,通过试验获取电缆次周期扰动电压波形并定义扰动波形的时间和幅值两个特征参数。然后,通过STKF(强跟踪卡尔曼滤波)快速跟踪电压幅值变化,设置自适应参数抑制GMM(高斯混合模型)的参数波动,结合STKF与GMM提取扰动电压特征参数。最后,通过试验获取的扰动电压数据进行算法测试,并分析高斯混合模型中自适应参数、采样频率、检测算法的死区对特征参数提取的影响。MATLAB仿真结果表明,电压采样频率在2.25 kHz及以上时计算结果相对稳定,验证了所提方法能够提取电缆次周期扰动电压特征参数。

When insulation defects arise in cables,they trigger the occurrence of sub-cycle disturbance voltage,making it imperative to extract the disturbance voltage features for timely defect detection and ensuring safe opera⁃tion.To address this need,a method for extracting cable sub-cycle disturbance voltage features is introduced.Firstly,the cable’s sub-cycle disturbance voltage waveform is obtained through testing,and two characteristic pa⁃rameters,namely time and amplitude,are defined for the disturbance waveform.Subsequently,voltage amplitude changes are rapidly tracked using the strong tracking Kalman filter(STKF).Adaptive parameters are established to suppress fluctuations in the parameters of the Gaussian mixture model(GMM),facilitating the extraction of distur⁃bance voltage characteristic parameters through the combined use of STKF and GMM.The algorithm is then tested using disturbance voltage data obtained from experiments,and the effects of adaptive parameters,sampling fre⁃quency,and the detection algorithm’s dead zone within the Gaussian mixture model on the extraction of characteris⁃tic parameters are analyzed.MATLAB simulation results demonstrate that the computational outcomes remain rela⁃tively stable when the voltage sampling frequency is set at 2.25 kHz and above.This validation underscores the method’s capability to extract characteristic parameters related to cable sub-cycle disturbance voltage.