Equipment Performance Deterioration Prediction Method Based On Functional Approximation And Its Applications

In order to reduce the operation cost of large and complex equipment on thepromise of safe operation, condition based maintenance and predictivemaintenance based on condition monitoring has been applied more and more.Thekey to condition based maintenance and predictive maintenance is predictingperformance deterioration of equipment.Predicting performance deterioration isto predict the changing of data which can reflect the performance, consideringperformance deterioration of large equipment is mainly influenced by timecumulation effect, two process prediction methods: process regression analysisand process neural network based on convolution, based on functionalapproximation are given in this article and are applied in the practice, achieving agood result.A new process regression analysis is proposed based on traditionalregression analysis, do not like the traditional regression analysis, it is abecause of having a operator which represent time cumulation effect. Simulationexperiment indicates that the predicting accuracy of process regression analysisis higher than the predicting accuracy of traditional regression analysis.Though process neural network is a functional approximation tool, adisadvantage that makes information incomplete when expanding the inputfunction and weight function with orthogonal basis function is found, so a newprocess neural network based on convolution which can keep informationcomplete is given. In the calculation of process neural network based onconvolution, a kind of fast convolution is used to make the computation speedfaster. The experiment shows that the prediction accuracy of new process neuralnetwork is higher than the traditional one’s.Process regression analysis and process neural network based onconvolution proposed in this article are applied to the prediction of performancedeterioration of aero engine and get a good result.