Mechanical Fault Diagnosis Using Color Image Recognition of Vibration Spectrogram Based on Quaternion Invariable Moment
Joint Authors
Hua, Liang
Zhang, Xinsong
Qiang, Yujian
Gu, Juping
Chen, Ling
Zhu, Hairong
Source
Mathematical Problems in Engineering
Issue
Vol. 2015, Issue 2015 (31 Dec. 2015), pp.1-11, 11 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2015-09-16
Country of Publication
Egypt
No. of Pages
11
Main Subjects
Abstract EN
Automatic extraction of time-frequency spectral image of mechanical faults can be achieved and faults can be identified consequently when rotating machinery spectral image processing technology is applied to fault diagnosis, which is an advantage.
Acquired mechanical vibration signals can be converted into color time-frequency spectrum images by the processing of pseudo Wigner-Ville distribution.
Then a feature extraction method based on quaternion invariant moment was proposed, combining image processing technology and multiweight neural network technology.
The paper adopted quaternion invariant moment feature extraction method and gray level-gradient cooccurrence matrix feature extraction method and combined them with geometric learning algorithm and probabilistic neural network algorithm, respectively, and compared the recognition rates of rolling bearing faults.
The experimental results show that the recognition rates of quaternion invariant moment are higher than gray level-gradient cooccurrence matrix in the same recognition method.
The recognition rates of geometric learning algorithm are higher than probabilistic neural network algorithm in the same feature extraction method.
So the method based on quaternion invariant moment geometric learning and multiweight neural network is superior.
What is more, this algorithm has preferable generalization performance under the condition of fewer samples, and it has practical value and acceptation on the field of fault diagnosis for rotating machinery as well.
American Psychological Association (APA)
Hua, Liang& Qiang, Yujian& Gu, Juping& Chen, Ling& Zhang, Xinsong& Zhu, Hairong. 2015. Mechanical Fault Diagnosis Using Color Image Recognition of Vibration Spectrogram Based on Quaternion Invariable Moment. Mathematical Problems in Engineering،Vol. 2015, no. 2015, pp.1-11.
https://search.emarefa.net/detail/BIM-1074514
Modern Language Association (MLA)
Hua, Liang…[et al.]. Mechanical Fault Diagnosis Using Color Image Recognition of Vibration Spectrogram Based on Quaternion Invariable Moment. Mathematical Problems in Engineering No. 2015 (2015), pp.1-11.
https://search.emarefa.net/detail/BIM-1074514
American Medical Association (AMA)
Hua, Liang& Qiang, Yujian& Gu, Juping& Chen, Ling& Zhang, Xinsong& Zhu, Hairong. Mechanical Fault Diagnosis Using Color Image Recognition of Vibration Spectrogram Based on Quaternion Invariable Moment. Mathematical Problems in Engineering. 2015. Vol. 2015, no. 2015, pp.1-11.
https://search.emarefa.net/detail/BIM-1074514
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1074514