Feature extraction methods for quality attributes prediction in injection moulding

摘要

A method to extract essential features from time domain process signals of injection moulding machines based on discrete wavelet transform is presented and compared to existing methods. The performance of the new method is assessed by comparing the goodness of fit of linear regression models to estimate final part quality. The results of the experiments show that the wavelet-based feature extraction method performs best regarding model performance and size.