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Abstract: A
novel multi-layer neural networks is proposed, which is based on
independent component analysis (ICA) for feature extraction of different
modes (for example normal and bearing fault etc.), followed by a
multi-layer perceptron (MLP) which implements the final classification.
By the use of ICA, invariable features embedded in multi-channel
vibration measurements can be captured. Thus, stable MLP classifier is
constructed. The successful results achieved by the selected experiments
indicated great potential of the new method in health condition
monitoring of rotating machines.
Key words: Independent component analysis Mutual information Principal
component analysis Multi-layer perceptron
CLC No: TN912.3
国家自然科学基金(50205025)和浙江省自然科学基金(5001004)资助项目. Received 20030324, received
in revised form 20030923
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