Abstract
To diagnose a slight and incipient fault in a power plant thermal system correctly and timely, a new fault recognition approach is put forward by using fault symptom zoom technology(SZT) and fuzzy pattern recognition method. By studying the rules of the faults pertinent to energy and mass balance in a power plant thermal system, a new fault symptom preprocessing method, which is called “fault symptom zoom technology”, is put forward to preprocess the fault characteristic parameters. The complexity of the thermal system fault knowledge library can be effectively reduced and the slight fault recognition ability can be greatly enhanced with SZT. The fault fuzzy pattern recognition method is introduced. A new general-purpose fuzzy recognition function is given, which can fit for various kinds of fault symptoms and is with favorable fault classifying ability. Some examples for incipient and slight fault diagnosis for a power plant thermal system are given to verify the effectiveness of the method.
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© 2006 Springer-Verlag Berlin Heidelberg
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Ma, L., Ma, J., Ma, Y., Wang, B. (2006). To Diagnose a Slight and Incipient Fault in a Power Plant Thermal System Based on Symptom Zoom Technology and Fuzzy Pattern Recognition Method. In: Yeung, D.S., Liu, ZQ., Wang, XZ., Yan, H. (eds) Advances in Machine Learning and Cybernetics. Lecture Notes in Computer Science(), vol 3930. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11739685_100
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DOI: https://doi.org/10.1007/11739685_100
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-33584-9
Online ISBN: 978-3-540-33585-6
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