Abstract: In the drilling process, the power spectrum of a drilling force is closely related to the drill wear. This relationship is widely applied in the monitoring of drill wear. But the problem of how to extract and identify the features of power spectrum have not been completely sloved. This paper achieves this through the multilayer decomposition of the power spectrum by using the wavelet transform and the extract of the low frequency decomposition coefficient as the envelope information of the power spectrum. Intelligent identification of the state of drill wear is achieved in the drilling process through fusing the wavelet decomposition coefficients of the power spectrum by using BP neural network. The experimental results show that the features of power spectrum can be extracted efficiently through this method, and the trained neural networks have high identification precision and the ability of extension.

Key words: drill wear, power spectrum, wavelet analysis, neural network