DocumentCode :
2322294
Title :
Application of wavelet package and neural network in ventilators fault warning
Author :
Quan Zhu ; Sheng Fu ; Jing Li
Author_Institution :
Coll. of Mech. Eng. & Appl. Electron. Technol., Beijing Univ. of Technol., Beijing
fYear :
2008
fDate :
21-24 April 2008
Firstpage :
1362
Lastpage :
1364
Abstract :
ldquoEnergy-faultrdquo method is introduced for faults warning of ventilators, which is based on wavelet package analysis and BP neural network. Character vectors which reflect different faults state of ventilators are extracted from different frequency segments with the technology of wavelet package analysis, and taking them into BP neural network model which is trained with character vectors of typical faults sample. The faults states of ventilators are identified with the BP neural network model. The results of research show that this kind of faults diagnosis technology is an effective way to implement faults warning.
Keywords :
backpropagation; neural nets; power system faults; ventilation; wavelet transforms; BP neural network; energy-fault method; faults diagnosis; ventilators fault warning; wavelet package analysis; Cables; Costs; Crystalline materials; Current transformers; Frequency response; Neural networks; Packaging; Partial discharges; Permeability; Transformer cores; fault diagnosis; neural network; ventilator; warning; wavelet package;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Condition Monitoring and Diagnosis, 2008. CMD 2008. International Conference on
Conference_Location :
Beijing
Print_ISBN :
978-1-4244-1621-9
Electronic_ISBN :
978-1-4244-1622-6
Type :
conf
DOI :
10.1109/CMD.2008.4580522
Filename :
4580522
Link To Document :
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