Notice of Retraction Application of principal component analysis and BP neural network in gear noise prediction

This paper presents an experimental investigation on gear noise for identifying the influence of gear tooth geometrical errors caused by machining on the radiated sound. The prediction model for the gear noise was established based on the principal component analysis (PCA) and BP neural network method. Using the principal components of original variables as the input of network can cut down the dimensions of input, and at the same time eliminate the relativity between variables. Back-propagation neural networks were introduced to describe the relationships between gear tooth geometrical errors and sound pressure level. The results indicate that the model has better predictive capability.