RESEARCH ON SHIP ENGINE ROOM MONITORING AND FAULT DIAGNOSIS SYSTEM BASED ON LABVIEW

Abstract

The structure of marine engine room system is complex, with many fault sources and abundant symptom parameters. There is no simple correspondence between faults and symptoms, but they are interrelated and intricate. The existing fault diagnosis of ship engine room is mostly based on expert system, but the bottleneck of knowledge acquisition, lack of learning ability and the complexity and efficiency of the expert system are restricting its further development. In order to overcome the above shortcomings of expert system, the support vector machine (SVM) is introduced into the expert system, and the support vector machine (SVM) is used to solve the problem of small sample self-learning ability and high-dimensional space self-adaptation ability. The expert system is used to achieve the automatic knowledge acquisition and rapid logical reasoning. Knowledge base management and maintenance, symbolic reasoning and related explanations, and give full play to the advantages of both SVM and expert system. Finally, the fault diagnosis of marine diesel engine booster system is introduced as an example. The MATLAB Script is used to call the MATLAB SVM analysis toolkit, and the combination of SVM and expert system is used to diagnose the fault.