A friction noise prediction method based on a BP neural network

Abstract

The invention provides a friction noise prediction method based on a BP (Back Propagation) neural network, which is used for predicting the frequency of friction noise generated in the braking processof a brake on a vehicle and comprises the following steps: step 1, acquiring the friction noise and a data sample p1i associated with the friction noise; Step 2, performing normalization processing on the data samples p1i to obtain corresponding normalized data samples p2i respectively, and dividing the data samples p2i into two groups, namely a first normalized data sample and a second normalized data sample; Step 3, establishing a friction noise prediction model by using a function newff specially establishing a BP neural network in MATLAB; 4, inputting the first normalized data sample intoa friction noise prediction model to obtain an updated network weight and an updated network threshold; And 5, inputting the second normalized data sample into the friction noise prediction model until the training error is 0.01, and determining a final network weight and a final network threshold to obtain a qualified friction noise prediction model.

Description

technical field [0001] The invention relates to a friction noise prediction method, in particular to a friction noise prediction method based on a BP neural network. Background technique [0002] Noise is often generated during the friction process. The noise generated by friction has a wide frequency range, high noise intensity, and complex causes and changes. The prediction of friction noise has always been a hot issue in the field of tribology. For the prediction method of friction noise, there are finite element-based brake squeal modeling and analysis methods, which include the frequency domain complex eigenvalue method and the time domain transient dynamics analysis method. The frequency domain complex eigenvalue method cannot clearly point out The mechanism of brake squeal, and the assumption of linearization lacks consideration of time-varying loads and material properties and other unsteady characteristics, often resulting in "over-prediction" and "under-prediction...

AI Technical Summary

Problems solved by technology

For the prediction method of friction noise, there are finite element-based brake squeal modeling and analysis methods, which include the frequency domain complex eigenvalue method and the time domain transient dynamics analysis method. The frequency domain complex eigenvalue method cannot clearly point out The mechanism of brake squeal, and the assumption of linearization lacks consideration of time-varying loads and material properties and other unsteady characteristics, often resulting in "over-prediction" and "under-prediction" of unstable frequencies, which limits its Prediction accuracy and reliability, and the disadvantage of time domain transient analysis method is that it takes too long to calculate and takes up a lot of disk space, and the data is difficult to be directly applied to the design

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