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The thesis, in order to solve the fault diagnosis problem of oil Parameter, adaptive neural network-based fuzzy inference system (ANFIS) was applied to build a fault diagnosis model of automobile engine, with the construction of ANFIS, by using gradient descent genetic algorithm and optimization of system parameters of neutral network learning algorithm, inputs the fusion data into ANFIS, and introduces...
Using the concepts of typical gas's concentration and cumulative frequency in analysis of the reliability data for dealing with the pretreatment of data of DGA, two new normalized methods which named characteristic normalization and mix normalization are presented in this paper. The Fisher rule to evaluate the results of the two pretreatment methods is also introduced. The evaluation of the results...
This paper aims at the BP neural network model, to against the problems of the weakness of capability of knowledge acquisition and low stability of learning and memory. The paper put forward a new fast error back propagation algorithm, and give an example to make a comparison between BP algorithm and FBP algorithm on fault diagnosis, The diagnosis results indicate the reliability of this method.
A fault diagnosis method for analog circuits based on Support Vector Machine (SVM) and AdaBoost algorithm is developed in this paper. Firstly, output voltage signals from the test nodes are obtained from analog circuits test points and the fault feature vectors are extracted from Haar wavelet packet transform coefficients. Then, after training the AdaBoost SVM by faulty feature vectors, the SVM ensemble...
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