Diesel generator sensor fault diagnosis model based on LMD-SVM algorithm

For the fault diagnosis of a diesel generator sensor system, a fault diagnosis model of diesel generator sensor based on the coupling of LMD and SVM algorithm is proposed, firstly, the fault signal is collected and the fault features are extracted by using LMD demarcation, then it is combined with SVM model, and the SVM classifier parameters are optimized by using the modified particle swarm algorithm (MPSO) to further improve the accuracy of fault diagnosis. The experimental results show that the accuracy of fault diagnosis of diesel generator sensor system (vibration sensor, temperature sensor, voltage sensor, and current sensor) using LMD-SVM model can reach 96.9%, 95.3%, 95.8%, and 94.8%, which has better diagnosis effect.