2018/12/06 by Na Qu, Jianhui Wang, Jinhai Liu · 2 citations
Decision Sciences · Engineering · Mathematics · #Algorithm #Amplitude #Arc (geometry) #Arc-fault circuit interrupter #Artificial intelligence #Circuit breaker #Computer science #Current (fluid) #Electrical Fault Detection and Protection #Electrical engineering #Engineering #Fault (geology) #Fault detection and isolation #Integrated Circuits and Semiconductor Failure Analysis #Mathematics #Physics #Representation (politics) #Residual #Risk and Safety Analysis #Short circuit #Sparse approximation #Voltage
paper · doi:10.1109/tim.2018.2880939
openalex publication_date 2018/12/06 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/29
When a series arc fault occurs, the current value of circuit is often less than the threshold of the circuit breaker. But the temperature of the arc combustion can be as high as thousands of degrees, which can lead to electrical fire. The current data of the normal work and arc fault are collected by using arc fault experiment. The arc fault is detected based on the current amplitude spectrum and the sparse representation algorithm. In traditional sparse representation algorithm based on Lpnorm, the regular order p selects the fixed value, and p is usually 1 or 1/2. According to the previous studies on the characteristics of L1, L3/4, L1/2, and L1/4 norm, it is found that the accuracy and sparsity of classification can be improved by adopting different norms for different data. Then, the online adjustment method of regular order p has been proposed. The regular order p is adjusted by calculating the minimum value of residual, which can make p be the optimal value for any test data.