This paper introduces a new model-free diagnostic methodology to detect and identify machine failures and product defects. The basic module of the methodology is a novel multi-dimensional wavelet neural network construct used as the failure mode classifier. Validated sensor data are preprocessed and a vector of appropriate features is extracted. The feature vector becomes the input to the wavelet neural network which is trained off-line to map features to failure causes. An example is employed to illustrate the robustness and effectiveness of the proposed scheme.
|Number of pages||6|
|State||Published - 2001|
|Event||Proceedings of the 2001 IEEE International Symposium on Intelligent Control ISIC '01 - Mexico City, Mexico|
Duration: 5 Sep 2001 → 7 Sep 2001
|Conference||Proceedings of the 2001 IEEE International Symposium on Intelligent Control ISIC '01|
|Period||5/09/01 → 7/09/01|