Abstract
This paper (Part 2) presents the practical application of componential coding, the principles of which were described in the accompanying Part 1 paper. Four major issues are addressed, including optimization of the neural network, assessment of the anomaly detection results, development of diagnostic approaches (based on the reconstruction error) and also benchmarking of componential coding with other techniques (including waveform measures. Fourier-based signal reconstruction and principal component analysis). This is achieved by applying componential coding to the data monitored from both a conventional induction motor and from a novel transverse flux motor. The results reveal that machine condition monitoring using componential coding is not only capable of detecting and then diagnosing anomalies but it also outperforms other conventional techniques in that it is able to separate very small and localized anomalies.
| Language | English |
|---|---|
| Pages | 901-915 |
| Number of pages | 15 |
| Journal | Proceedings of the Institution of Mechanical Engineers, Part C: Journal of Mechanical Engineering Science |
| Volume | 217 |
| Issue number | 8 |
| DOIs | |
| Publication status | Published - 1 Aug 2003 |
| Externally published | Yes |
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Componential coding in the condition monitoring of electrical machines : Part 2: Application to a conventional machine and a novel machine. / Payne, B. S.; Gu, F.; Webber, C. J.S.; Ball, A. D.
In: Proceedings of the Institution of Mechanical Engineers, Part C: Journal of Mechanical Engineering Science, Vol. 217, No. 8, 01.08.2003, p. 901-915.Research output: Contribution to journal › Article
TY - JOUR
T1 - Componential coding in the condition monitoring of electrical machines
T2 - Proceedings of the Institution of Mechanical Engineers, Part C: Journal of Mechanical Engineering Science
AU - Payne, B. S.
AU - Gu, F.
AU - Webber, C. J.S.
AU - Ball, A. D.
PY - 2003/8/1
Y1 - 2003/8/1
N2 - This paper (Part 2) presents the practical application of componential coding, the principles of which were described in the accompanying Part 1 paper. Four major issues are addressed, including optimization of the neural network, assessment of the anomaly detection results, development of diagnostic approaches (based on the reconstruction error) and also benchmarking of componential coding with other techniques (including waveform measures. Fourier-based signal reconstruction and principal component analysis). This is achieved by applying componential coding to the data monitored from both a conventional induction motor and from a novel transverse flux motor. The results reveal that machine condition monitoring using componential coding is not only capable of detecting and then diagnosing anomalies but it also outperforms other conventional techniques in that it is able to separate very small and localized anomalies.
AB - This paper (Part 2) presents the practical application of componential coding, the principles of which were described in the accompanying Part 1 paper. Four major issues are addressed, including optimization of the neural network, assessment of the anomaly detection results, development of diagnostic approaches (based on the reconstruction error) and also benchmarking of componential coding with other techniques (including waveform measures. Fourier-based signal reconstruction and principal component analysis). This is achieved by applying componential coding to the data monitored from both a conventional induction motor and from a novel transverse flux motor. The results reveal that machine condition monitoring using componential coding is not only capable of detecting and then diagnosing anomalies but it also outperforms other conventional techniques in that it is able to separate very small and localized anomalies.
KW - Auto-encoder
KW - Componential coding
KW - Condition monitoring
KW - Fault detection
KW - Fault diagnosis
KW - Induction motor
KW - Neural network
KW - Transverse flux motor
UR - http://www.scopus.com/inward/record.url?scp=0141522905&partnerID=8YFLogxK
U2 - 10.1243/095440603322310440
DO - 10.1243/095440603322310440
M3 - Article
VL - 217
SP - 901
EP - 915
JO - Proceedings of the Institution of Mechanical Engineers, Part C: Journal of Mechanical Engineering Science
JF - Proceedings of the Institution of Mechanical Engineers, Part C: Journal of Mechanical Engineering Science
SN - 0954-4062
IS - 8
ER -