Fault Diagnosis Algorithms Based on GEP

Based on the existing intelligent algorithms such as particle swarm optimization (PSO) and gene expression programming (GEP), this paper proposes a hybrid intelligent algorithm to diagnose the faults of a certain type of equipment combination and floor quickly. At the same time, the quantum theory is introduced, and the adaptive quantum particle swarm optimization algorithm and the quantum neural network are constructed to extract fault features and fault diagnosis algorithm. A hybrid intelligent diagnosis core algorithm library based on Genetic Wavelet particle swarm optimization neural network is established and verified by simulation.