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Technical University of Crete
Technical University of Crete
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| URI: | http://purl.tuc.gr/dl/dias/B201147F-C976-45E2-8512-7B964034C8A0 | ||
| Year | 2001 | ||
| Type of Item | Peer-Reviewed Journal Publication | ||
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| Bibliographic Citation | S. Goumas, M. Zervakis, A. Pouliezos, G.S. Stavrakakis," Intelligent on-line quality control of washing machines using discrete wavelet analysis features and likelihood classification," Engin. Applications of Art.Intelligence,vol. 14,no. 5,pp. 655-666,2001.doi:10.1016/S0952-1976(01)00028-8 https://doi.org/10.1016/S0952-1976(01)00028-8 | ||
| Appears in Collections |
This paper presents a method for extracting features in the wavelet domain from the vibration velocity signals of washing machines, focusing on the transient (non-stationary) part of the signal. These features are then used for classification of the state (acceptable-faulty) of the machine. The performance of this feature set is compared to features obtained through standard Fourier analysis of the steady-state (stationary) part of the vibration signal. Minimum distance Bayes classifiers are used for classification purposes. Measurements from a variety of defective/non-defective washing machines taken in the laboratory as well as from the production line are used to illustrate the applicability of the proposed method.
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