触电事故特征改进近似熵检测方法

Electrical shock feature detection method based on improved approximate entropy

为了有效减少人身触电事故的发生,针对低压系统,给出一种基于近似熵的触电特征快速检测方法。利用滑动时间窗计算单通道测量所得总剩余电流的近似熵值。根据近似熵变化规律识别触电事故特征。并针对近似熵算法存在的计算冗余问题,提出一种改进近似熵算法,以此减少触电特征检测时间。对IEC人体电阻抗模型、实验用兔和小树枝进行低压实验,并利用数据验证该方法。结果证明,触电特征近似熵检测方法具有噪声鲁棒性、不受总剩余电流幅值和触电方式影响的特点,采用改进近似熵算法缩短了触电特征检测时间,能满足工程应用需要。

Aiming at reducing the frequency of the electrical shock faults in low voltage power system, approximate entropy （ApEn） based electrical shock feature method is proposed. Firstly, it samples a total residual current from a single-channel and slides a time window continuously to calculate the ApEn in every target period. Then, it determines whether the electrical shock fault happens by identifying the varying tendency of ApEn. Considering the redundant operation in the present algorithm, it proposes an improved algorithm to reduce the time consumption of electrical shock feature detection. Finally, physical experiment about IEC body impedance model, experimental rabbits and sprays is made and verified by using the data. The result shows that the method is of noise robustness, and also independent of amplitude of the total residual current and the way of electric shock. Moreover, the proposed algorithm shortens the detection time of electric shock feature, meeting the need of engineering application.