Application of Frequency-Domain Blind Deconvolution in Mechanical Fault Detection

被引：2

作者：

Pan, Nan ^{[1
]}

Wu, Xing ^{[1
]}

Chi, Yilin ^{[1
]}

Liu, Chang ^{[1
]}

Liu, Xiaoqin ^{[1
]}

机构：

[1] Kunming Univ Sci & Technol, Fac Mech & Elect Engn, Kunming 650093, Peoples R China

来源：

MECHANICAL AND ELECTRONICS ENGINEERING III, PTS 1-5 | 2012年 / 130-134卷

关键词：

Frequency-Domain Blind Deconvolution; Fault Detection; Complex-Domain FastICA; Vibration Signal Processing;

D O I：

10.4028/www.scientific.net/AMM.130-134.2128

中图分类号：

TH [机械、仪表工业];

学科分类号：

0802 ;

摘要：

On the basis of summing up the Frequency-Domain Blind Deconvolution (FDBD), a method combine Complex-Domain FastICA algorithm and amplitude correlation was proposed to extract the typical defect signals from mechanical equipment. The application in combined failure rolling bearing acceleration signals demonstrate that, comparing with the existing Time-Domain Blind Signal Processing methods, FDBD has more advantages and better prospects in mechanical fault detection.

引用

页码：2128 / 2132

页数：5

共 50 条

[31] ON INITIAL FAULT-DETECTION OF A TAPERED ROLLER BEARING - FREQUENCY-DOMAIN ANALYSIS
SU, YT
LIN, SJ
[J]. JOURNAL OF SOUND AND VIBRATION, 1992, 155 (01) : 75 - 84
[32] Equivalence between frequency-domain blind source separation and frequency-domain adaptive beamforming for convolutive mixtures
Araki, S
Makino, S
Hinamoto, Y
Mukai, R
Nishikawa, T
Saruwatari, H
[J]. EURASIP JOURNAL ON APPLIED SIGNAL PROCESSING, 2003, 2003 (11) : 1157 - 1166
[33] Equivalence between Frequency-Domain Blind Source Separation and Frequency-Domain Adaptive Beamforming for Convolutive Mixtures
[J]. Araki, S. (shoko@cslab.ked.ntt.co.jp), 1600, Hindawi Publishing Corporation (2003):
[34] Equivalence between Frequency-Domain Blind Source Separation and Frequency-Domain Adaptive Beamforming for Convolutive Mixtures
Shoko Araki
Shoji Makino
Yoichi Hinamoto
Ryo Mukai
Tsuyoki Nishikawa
Hiroshi Saruwatari
[J]. EURASIP Journal on Advances in Signal Processing, 2003
[35] Noise separation based on blind deconvolution in frequency domain
National Die and Mould CAD Engineering Research Center, Shanghai Jiaotong University, Shanghai 200030, China
[J]. J Vib Shock, 2006, 6 (100-103+107):
[36] A review on the application of blind deconvolution in machinery fault diagnosis
Miao, Yonghao
Zhang, Boyao
Lin, Jing
Zhao, Ming
Liu, Hanyang
Liu, Zongyang
Li, Hao
[J]. MECHANICAL SYSTEMS AND SIGNAL PROCESSING, 2022, 163
[37] Frequency-Domain Detection for Molecular Communications
Civas, Meltem
Abdali, Ali
Kuscu, Murat
Akan, Ozgur B.
[J]. ICC 2023-IEEE INTERNATIONAL CONFERENCE ON COMMUNICATIONS, 2023, : 4488 - 4494
[38] Isotropy frequency-domain extension imaging and its application in detection of nanostructures
Bai, Jinxi
Ren, Huan
Shi, Zhendong
Ma, Hua
Liu, Lijia
Ma, Ke
Chai, Liqun
Zhang, Lin
[J]. FRONTIERS IN PHYSICS, 2022, 10
[39] OBJECTIVE RESPONSE DETECTION IN THE FREQUENCY-DOMAIN
DOBIE, RA
WILSON, MJ
[J]. ELECTROENCEPHALOGRAPHY AND CLINICAL NEUROPHYSIOLOGY, 1993, 88 (06): : 516 - 524
[40] RESIDUAL GENERATOR FOR SENSOR AND ACTUATOR FAULT-DETECTION AND ISOLATION - A FREQUENCY-DOMAIN APPROACH
KINNAERT, M
PENG, Y
[J]. INTERNATIONAL JOURNAL OF CONTROL, 1995, 61 (06) : 1423 - 1435

← 1 2 3 4 5 →