Identification algorithm for live working violations based on critical values and similarity

In order to improve the accuracy of identifying violations in live working, this paper proposes a live working violation recognition algorithm based on critical values and similarity. Firstly, by setting a reasonable critical value, it is possible to determine whether the operator's operation behavior exceeds the safety range. When the operation behavior approaches or exceeds the critical value, the system can issue a warning or alarm signal to remind the operators to correct the error in a timely manner. Then, key behavioral features are extracted, and based on Fourier descriptors, similarity recognition is performed on the characteristics of live working behavior to identify and judge violations. Finally, live working behaviors with lower similarity to standard regulations are judged as violations, achieving recognition of live working violations. The experimental results show that the algorithm can accurately identify various violations of live work regulations, with high recognition accuracy and efficiency, providing strong support for safety management in power operation sites.