New approach of wavelet fractal analysis to mechanical fault diagnosis

Zhengjia He; Yanyang Zi; Peng Chen; Toshio Toyota

New approach of wavelet fractal analysis to mechanical fault diagnosis

Zhengjia He
, Yanyang Zi
, Peng Chen
, Toshio Toyota

机械工程学院

Xi'an Jiaotong University
Kyushu Institute of Technology

科研成果: 会议稿件 › 论文 › 同行评审

1 引用（Scopus）

摘要

Wavelet transform decomposes signals in both time and frequency domains. According to the principle of multi-resolution, irregularities or complexities of decomposed signals in various frequency bands are different, which can indicate mechanical fault. Fractal dimension of decomposed signal is an excellent factor to express the irregularity or complexity. It can make features of mechanical faults remarkable. Based on wavelet fractal dimension, successful diagnosis of looseness fault of bearing bridge for 50MW turbo-generator was obtained.

源语言	英语
页	2905-2909
页数	5
出版状态	已出版 - 2001
活动	18th Biennial Conference on Mechanical Vibration and Noise - Pittsburgh, PA, 美国期限: 9 9月 2001 → 12 9月 2001

会议

会议	18th Biennial Conference on Mechanical Vibration and Noise
国家/地区	美国
市	Pittsburgh, PA
时期	9/09/01 → 12/09/01

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引用此

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title = "New approach of wavelet fractal analysis to mechanical fault diagnosis",

abstract = "Wavelet transform decomposes signals in both time and frequency domains. According to the principle of multi-resolution, irregularities or complexities of decomposed signals in various frequency bands are different, which can indicate mechanical fault. Fractal dimension of decomposed signal is an excellent factor to express the irregularity or complexity. It can make features of mechanical faults remarkable. Based on wavelet fractal dimension, successful diagnosis of looseness fault of bearing bridge for 50MW turbo-generator was obtained.",

keywords = "Diagnosis, Fractal analysis, Mechanical fault, Wavelet packets",

author = "Zhengjia He and Yanyang Zi and Peng Chen and Toshio Toyota",

year = "2001",

language = "英语",

pages = "2905--2909",

note = "18th Biennial Conference on Mechanical Vibration and Noise ; Conference date: 09-09-2001 Through 12-09-2001",

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TY - CONF

T1 - New approach of wavelet fractal analysis to mechanical fault diagnosis

AU - He, Zhengjia

AU - Zi, Yanyang

AU - Chen, Peng

AU - Toyota, Toshio

PY - 2001

Y1 - 2001

N2 - Wavelet transform decomposes signals in both time and frequency domains. According to the principle of multi-resolution, irregularities or complexities of decomposed signals in various frequency bands are different, which can indicate mechanical fault. Fractal dimension of decomposed signal is an excellent factor to express the irregularity or complexity. It can make features of mechanical faults remarkable. Based on wavelet fractal dimension, successful diagnosis of looseness fault of bearing bridge for 50MW turbo-generator was obtained.

AB - Wavelet transform decomposes signals in both time and frequency domains. According to the principle of multi-resolution, irregularities or complexities of decomposed signals in various frequency bands are different, which can indicate mechanical fault. Fractal dimension of decomposed signal is an excellent factor to express the irregularity or complexity. It can make features of mechanical faults remarkable. Based on wavelet fractal dimension, successful diagnosis of looseness fault of bearing bridge for 50MW turbo-generator was obtained.

KW - Diagnosis

KW - Fractal analysis

KW - Mechanical fault

KW - Wavelet packets

UR - https://www.scopus.com/pages/publications/0035791261

M3 - 论文

AN - SCOPUS:0035791261

SP - 2905

EP - 2909

T2 - 18th Biennial Conference on Mechanical Vibration and Noise

Y2 - 9 September 2001 through 12 September 2001

ER -

New approach of wavelet fractal analysis to mechanical fault diagnosis

摘要

会议

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