Abstract: A process monitoring method based on independent component analysis(ICA) and wavelet transform was presented. which used ICA to calculate independent component and wavelet decomposition to construct average energy as the process feature respectively. Then the process monitoring can be conducted by comparing similarity degree that was considered as a monitoring perofrmance index. ICA is more accurate than principle component analysis(PCA) in extraction of non-Gaussian distribution signal, and it can get second power of signal features that are more compact and suitable for post-end treatment from original input. Since these features can represent essential information in the input data, ICA method is better than the feature extraction mehods only by considering variance information.

Key words: automatic control technology, signal treatment technology, independent component analysis (ICA), process monitoring, wavelet transform, principal-component analysis