The application of the fuzzy neural network-wavelet singularity detection in mechanical fault diagnosis of high voltage breakers

Laijun Sun; Xiaoguang Hu; Yanchao Ji; Chao Lv

The application of the fuzzy neural network-wavelet singularity detection in mechanical fault diagnosis of high voltage breakers

Laijun Sun^*
, Xiaoguang Hu
, Yanchao Ji
, Chao Lv

^*Corresponding author for this work

School of Automation Science and Electrical Engineering

Harbin Institute of Technology

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

4 Scopus citations

Abstract

In this paper, a new method that the wavelet singularity detecting and NN of fuzzy combined to process the mechanism libration signal of the HV breaker is introduced, which is called the NN of fuzzy singularity. This is a new method that the wavelet singularity exponent of fuzzification combined with the multilayer feedforward NN is imported to the mechanism fault diagnosis of the HV breaker. The experimental results show that this method can achieve better effect than the wavelet singularity detecting and improves the accuracy and precision of diagnosis.

Original language	English
Title of host publication	IMTC'05 - Proceedings of the IEEE Instrumentation and Measurement Technology Conference
Pages	2164-2167
Number of pages	4
State	Published - 2005
Event	IMTC'05 - Proceedings of the IEEE Instrumentation and Measurement Technology Conference - Ottawa, ON, Canada Duration: 16 May 2005 → 19 May 2005

Publication series

Name	Conference Record - IEEE Instrumentation and Measurement Technology Conference
Volume	3
ISSN (Print)	1091-5281

Conference

Conference	IMTC'05 - Proceedings of the IEEE Instrumentation and Measurement Technology Conference
Country/Territory	Canada
City	Ottawa, ON
Period	16/05/05 → 19/05/05

Keywords

Fault diagnosis
Fuzzy neural network
HV breaker
Neural network
Wavelet singularity

Cite this

Sun, L., Hu, X., Ji, Y., & Lv, C. (2005). The application of the fuzzy neural network-wavelet singularity detection in mechanical fault diagnosis of high voltage breakers. In IMTC'05 - Proceedings of the IEEE Instrumentation and Measurement Technology Conference (pp. 2164-2167). Article 1604558 (Conference Record - IEEE Instrumentation and Measurement Technology Conference; Vol. 3).

Sun, Laijun ; Hu, Xiaoguang ; Ji, Yanchao et al. / The application of the fuzzy neural network-wavelet singularity detection in mechanical fault diagnosis of high voltage breakers. IMTC'05 - Proceedings of the IEEE Instrumentation and Measurement Technology Conference. 2005. pp. 2164-2167 (Conference Record - IEEE Instrumentation and Measurement Technology Conference).

@inproceedings{722c66cec04143ef96d579ac652479e7,

title = "The application of the fuzzy neural network-wavelet singularity detection in mechanical fault diagnosis of high voltage breakers",

abstract = "In this paper, a new method that the wavelet singularity detecting and NN of fuzzy combined to process the mechanism libration signal of the HV breaker is introduced, which is called the NN of fuzzy singularity. This is a new method that the wavelet singularity exponent of fuzzification combined with the multilayer feedforward NN is imported to the mechanism fault diagnosis of the HV breaker. The experimental results show that this method can achieve better effect than the wavelet singularity detecting and improves the accuracy and precision of diagnosis.",

keywords = "Fault diagnosis, Fuzzy neural network, HV breaker, Neural network, Wavelet singularity",

author = "Laijun Sun and Xiaoguang Hu and Yanchao Ji and Chao Lv",

year = "2005",

language = "英语",

isbn = "0780388798",

series = "Conference Record - IEEE Instrumentation and Measurement Technology Conference",

pages = "2164--2167",

booktitle = "IMTC'05 - Proceedings of the IEEE Instrumentation and Measurement Technology Conference",

note = "IMTC'05 - Proceedings of the IEEE Instrumentation and Measurement Technology Conference ; Conference date: 16-05-2005 Through 19-05-2005",

}

Sun, L, Hu, X, Ji, Y & Lv, C 2005, The application of the fuzzy neural network-wavelet singularity detection in mechanical fault diagnosis of high voltage breakers. in IMTC'05 - Proceedings of the IEEE Instrumentation and Measurement Technology Conference., 1604558, Conference Record - IEEE Instrumentation and Measurement Technology Conference, vol. 3, pp. 2164-2167, IMTC'05 - Proceedings of the IEEE Instrumentation and Measurement Technology Conference, Ottawa, ON, Canada, 16/05/05.

The application of the fuzzy neural network-wavelet singularity detection in mechanical fault diagnosis of high voltage breakers. / Sun, Laijun; Hu, Xiaoguang; Ji, Yanchao et al.
IMTC'05 - Proceedings of the IEEE Instrumentation and Measurement Technology Conference. 2005. p. 2164-2167 1604558 (Conference Record - IEEE Instrumentation and Measurement Technology Conference; Vol. 3).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - The application of the fuzzy neural network-wavelet singularity detection in mechanical fault diagnosis of high voltage breakers

AU - Sun, Laijun

AU - Hu, Xiaoguang

AU - Ji, Yanchao

AU - Lv, Chao

PY - 2005

Y1 - 2005

N2 - In this paper, a new method that the wavelet singularity detecting and NN of fuzzy combined to process the mechanism libration signal of the HV breaker is introduced, which is called the NN of fuzzy singularity. This is a new method that the wavelet singularity exponent of fuzzification combined with the multilayer feedforward NN is imported to the mechanism fault diagnosis of the HV breaker. The experimental results show that this method can achieve better effect than the wavelet singularity detecting and improves the accuracy and precision of diagnosis.

AB - In this paper, a new method that the wavelet singularity detecting and NN of fuzzy combined to process the mechanism libration signal of the HV breaker is introduced, which is called the NN of fuzzy singularity. This is a new method that the wavelet singularity exponent of fuzzification combined with the multilayer feedforward NN is imported to the mechanism fault diagnosis of the HV breaker. The experimental results show that this method can achieve better effect than the wavelet singularity detecting and improves the accuracy and precision of diagnosis.

KW - Fault diagnosis

KW - Fuzzy neural network

KW - HV breaker

KW - Neural network

KW - Wavelet singularity

UR - https://www.scopus.com/pages/publications/33847138620

M3 - 会议稿件

AN - SCOPUS:33847138620

SN - 0780388798

SN - 9780780388796

T3 - Conference Record - IEEE Instrumentation and Measurement Technology Conference

SP - 2164

EP - 2167

BT - IMTC'05 - Proceedings of the IEEE Instrumentation and Measurement Technology Conference

T2 - IMTC'05 - Proceedings of the IEEE Instrumentation and Measurement Technology Conference

Y2 - 16 May 2005 through 19 May 2005

ER -

The application of the fuzzy neural network-wavelet singularity detection in mechanical fault diagnosis of high voltage breakers

Abstract

Publication series

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Keywords

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