Wang Li
1. College of Electrical and Information Engineering，Anhui University of Science and Technology，Huainan 232001，China; 3. Institute of Environmentally Friendly Materials and Occupational Health (Wuhu)，Anhui University of Science and Technology，Wuhu 241003，ChinaLi Zhenbi
1. College of Electrical and Information Engineering，Anhui University of Science and Technology，Huainan 232001，China; 2. Department of Electronic and Information Engineering，Bozhou University，Bozhou 236800，ChinaJiang Yuanyuan
1. College of Electrical and Information Engineering，Anhui University of Science and Technology，Huainan 232001，China; 3. Institute of Environmentally Friendly Materials and Occupational Health (Wuhu)，Anhui University of Science and Technology，Wuhu 241003，China1. College of Electrical and Information Engineering，Anhui University of Science and Technology，Huainan 232001，China; 2. Department of Electronic and Information Engineering，Bozhou University，Bozhou 236800，China; 3. Institute of Environmentally Friendly Materials and Occupational Health (Wuhu)，Anhui University of Science and Technology，Wuhu 241003，China
U226.8+1
To address the problems of difficult feature extraction and low classification accuracy in soft fault diagnosis of DC-DC circuits, a fault diagnosis method based on multi-strategy improved Harris optimization algorithm-back propagation (MHHO-BP) neural network is proposed. The method processes the fault signal by VMD, extracts its time-domain and frequency-domain features as the fault vector, and uses the MHHO algorithm to optimize the weights and thresholds of the BP neural network to establish a VMD-MHHO-BP soft fault diagnosis model of DC-DC circuits. The experimental results show that for soft faults of DC-DC circuits, the method has good diagnostic effect and high accuracy compared with the Whale Optimization Algorithm (WOA) and Butterfly Optimization Algorithm (BOA) optimized BP neural network.
