A detection method for biological electric shock based on improved sample entropy

Biological electric shock detection is the key to safeguarding of persons in grids. However, present methods cannot make protectors trip correctly by extracting the characteristics of living things. To improve the situation, this paper presents an innovation by which the protectors can be adaptive to trip correctly when the biological electric shock happens. The basic principle of proposed method is extracting biological electric shock characteristics (BESC) from measured current based on the sample entropy (SampEn). It can distinguish whether the electric shock is caused by mammals or not. Besides, for practical need, a fast BESC calculation method is proposed in order to reduce redundant computation. Moreover, an execution module for electric shock protection based on DSP is developed. And electric shock experiments have been carried out to validate the effectiveness of proposed method. The results show that accuracy of biological electric shock detection is improved and proposed method is practical even in strong noise environment.