Abstract
Considering the issues that the relationship between the fault of screw oil pump existent and fault information is a complicated and nonlinear system, and it is very difficult to found the process model to describe it. The support vector machine (SVM) has the ability of strong nonlinear function approach and the ability of strong generalization and also has the feature of global optimization. In this paper, a fault diagnosis system with self-repair function for screw oil pump based on SVM is presented. Moreover, the genetic algorithm (GA) was used to optimize SVM parameters. With the ability of strong self-learning and well generalization of SVM, the diagnosis system can truly diagnose the fault of screw oil pump by learning the fault information. The real diagnosis results show that this system is feasible and effective.
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