Fault Diagnosis of Tank Fire Control System Based on NRS and WOA-SVM

Abstract

In order to save the high cost of tank maintenance, reduce the redundant input of manpower and material resources for tank maintenance, and improve the reliability of tank performance, a fault diagnosis method based on NRS and WOA-SVM is proposed. Taking the fire control computer and sensor subsystem of a certain type of tank fire control system as the research object, the NRS algorithm is used to reduce the properties of the performance parameters of the fire control computer, and the most important performance index is selected. Then, a novel meta-heuristic algorithm, WOA, is used to optimize the parameters of the SVM, and the fault data classification model is constructed according to the global best fitness function value. Finally, the attribute-reduced dataset is input into the WOA-SVM fault classification model to realize the fault diagnosis of the system. The experimental results show that the method can effectively evaluate the health status and fault diagnosis of the fire control system, achieve the purpose of precise maintenance, repair and replacement, and improve the reliability of the equipment.