Fault Diagnosis of Roller Bearings Based on a Wavelet Neural Network and Manifold Learning

In order to improve the accuracy of the fault diagnosis of roller bearings, this paper proposes a kind of fault diagnosis algorithm based on manifold learning combined with a wavelet neural network. First, a high-dimensional feature signal set is obtained using a conventional feature extraction algo...

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Main Authors:	Lifeng Wu, Beibei Yao, Zhen Peng, Yong Guan
Format:	Article
Language:	English
Published:	MDPI AG 2017-02-01
Series:	Applied Sciences
Subjects:	roller bearing manifold learning wavelet neural network fault diagnosis
Online Access:	http://www.mdpi.com/2076-3417/7/2/158

id	doaj-fda1ca6ffbb5474fa41abcb1fc75311c
record_format	Article
spelling	doaj-fda1ca6ffbb5474fa41abcb1fc75311c2020-11-24T22:01:46ZengMDPI AGApplied Sciences2076-34172017-02-017215810.3390/app7020158app7020158Fault Diagnosis of Roller Bearings Based on a Wavelet Neural Network and Manifold LearningLifeng Wu0Beibei Yao1Zhen Peng2Yong Guan3College of Information Engineering, Capital Normal University, Beijing 100048, ChinaCollege of Information Engineering, Capital Normal University, Beijing 100048, ChinaInformation Management Department, Beijing Institute of Petrochemical Technology, Beijing 102617, Beijing, ChinaCollege of Information Engineering, Capital Normal University, Beijing 100048, ChinaIn order to improve the accuracy of the fault diagnosis of roller bearings, this paper proposes a kind of fault diagnosis algorithm based on manifold learning combined with a wavelet neural network. First, a high-dimensional feature signal set is obtained using a conventional feature extraction algorithm; second, an improved Laplacian characteristic mapping algorithm is proposed to reduce the dimensions of the characteristics and obtain an effective characteristic signal. Finally, the processed characteristic signal is inputted into the constructed wavelet neural network whose output is the types of fault. In the actual experiment of recognizing data sets on roller bearing failures, the validity and accuracy of the method for diagnosing faults was verified.http://www.mdpi.com/2076-3417/7/2/158roller bearingmanifold learningwavelet neural networkfault diagnosis
collection	DOAJ
language	English
format	Article
sources	DOAJ
author	Lifeng Wu Beibei Yao Zhen Peng Yong Guan
spellingShingle	Lifeng Wu Beibei Yao Zhen Peng Yong Guan Fault Diagnosis of Roller Bearings Based on a Wavelet Neural Network and Manifold Learning Applied Sciences roller bearing manifold learning wavelet neural network fault diagnosis
author_facet	Lifeng Wu Beibei Yao Zhen Peng Yong Guan
author_sort	Lifeng Wu
title	Fault Diagnosis of Roller Bearings Based on a Wavelet Neural Network and Manifold Learning
title_short	Fault Diagnosis of Roller Bearings Based on a Wavelet Neural Network and Manifold Learning
title_full	Fault Diagnosis of Roller Bearings Based on a Wavelet Neural Network and Manifold Learning
title_fullStr	Fault Diagnosis of Roller Bearings Based on a Wavelet Neural Network and Manifold Learning
title_full_unstemmed	Fault Diagnosis of Roller Bearings Based on a Wavelet Neural Network and Manifold Learning
title_sort	fault diagnosis of roller bearings based on a wavelet neural network and manifold learning
publisher	MDPI AG
series	Applied Sciences
issn	2076-3417
publishDate	2017-02-01
description	In order to improve the accuracy of the fault diagnosis of roller bearings, this paper proposes a kind of fault diagnosis algorithm based on manifold learning combined with a wavelet neural network. First, a high-dimensional feature signal set is obtained using a conventional feature extraction algorithm; second, an improved Laplacian characteristic mapping algorithm is proposed to reduce the dimensions of the characteristics and obtain an effective characteristic signal. Finally, the processed characteristic signal is inputted into the constructed wavelet neural network whose output is the types of fault. In the actual experiment of recognizing data sets on roller bearing failures, the validity and accuracy of the method for diagnosing faults was verified.
topic	roller bearing manifold learning wavelet neural network fault diagnosis
url	http://www.mdpi.com/2076-3417/7/2/158
work_keys_str_mv	AT lifengwu faultdiagnosisofrollerbearingsbasedonawaveletneuralnetworkandmanifoldlearning AT beibeiyao faultdiagnosisofrollerbearingsbasedonawaveletneuralnetworkandmanifoldlearning AT zhenpeng faultdiagnosisofrollerbearingsbasedonawaveletneuralnetworkandmanifoldlearning AT yongguan faultdiagnosisofrollerbearingsbasedonawaveletneuralnetworkandmanifoldlearning
_version_	1725838649289867264

Fault Diagnosis of Roller Bearings Based on a Wavelet Neural Network and Manifold Learning

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