Ship electric propulsion system fault diagnosis method based on ABC-SVM expert system

Abstract

The invention aims to provide a ship electric propulsion system fault diagnosis method based on an ABC-SVM expert system, knowledge and experience of experts are stored in a knowledge base, a supportvector machine optimized by using an artificial bee colony is used in an inference machine, the knowledge in the knowledge base is preprocessed and then is used for performing classification trainingon the inference machine and storing a trained model. real-time data collected from the ship electric propulsion system is stored in a dynamic database, feature value extraction is conducted, the datais input into a trained inference engine, whether the ship electric propulsion system breaks down or not is judged, which device breaks down is judged, and the reason why the fault occurs is explained. Practicability and real-time performance of an expert system are greatly improved, the problem of a local optimal solution of the support vector machine is solved to a great extent, and the accuracy of fault diagnosis is improved.

Description

technical field [0001] The invention relates to a fault diagnosis method, in particular to a ship fault diagnosis method. Background technique [0002] At present, the ship structure is becoming more and more complex, the tonnage of the ship is also increasing, and the power to be provided is also increasing. As the main provider of ship power, the ship electric propulsion system has a very important position. In practical applications, the ship electric propulsion system is affected by various factors and its own aging, and the probability of failure of the ship electric propulsion system is increasing day by day. The failure of the current ship electric propulsion system will bring adverse effects on the normal operation and navigation of the ship, and the relationship between the various components of the ship electric propulsion system is very complicated, which makes the fault diagnosis of the ship electric propulsion system face a huge challenge. [0003] In fault dia...

AI Technical Summary

Problems solved by technology

Therefore, the expert system based on the neural network has relatively poor stability in the fault diagnosis results of the ship electric propulsion system, and sometimes there will be a fault diagnosis phenomenon with a high error rate.

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