A Novel Improved Local Binary Pattern and Its Application to the Fault Diagnosis of Diesel Engine
Joint Authors
Cai, Yanping
Xu, Guanghua
Li, Aihua
Wang, Xu
Source
Issue
Vol. 2020, Issue 2020 (31 Dec. 2020), pp.1-15, 15 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2020-02-21
Country of Publication
Egypt
No. of Pages
15
Main Subjects
Abstract EN
Aiming at the feature extraction difficulty of vibration signals, an improved local binary pattern- (ILBP-) based diesel engine fault diagnosis approach is proposed.
To effectively make use of the component spatial information in time-frequency images, local binary pattern (LBP) algorithm is applied.
Also, in view of the problems that traditional LBP coding is easily interfered by singular pixel points and the relative spatial information is not prominent, an improved coding rule of the LBP operator is put forward in this paper.
Compared with some typical LBP algorithms, computational complexity of the proposed ILBP algorithm is greatly reduced, and the coding sparsity is greatly improved.
The ILBP operator is applied to fault diagnosis of BF4L1011F diesel engine with eight different valve conditions.
For comparison, six kinds of time-frequency distribution are used to convert raw vibration signals into time-frequency images, and then circular LBP, rotation-invariant LBP, uniform LBP, and ILBP operator are applied for texture coding.
Finally, nearest neighbor classifier (NNC) and support vector machine (SVM) are used for fault identification.
The classification results show that the ILBP operator proposed in this paper can better describe the texture feature information in vibration time-frequency images of the diesel engine, and a good diagnostic effect can be achieved by combining wavelet packet (WP) distribution and ILBP.
American Psychological Association (APA)
Cai, Yanping& Xu, Guanghua& Li, Aihua& Wang, Xu. 2020. A Novel Improved Local Binary Pattern and Its Application to the Fault Diagnosis of Diesel Engine. Shock and Vibration،Vol. 2020, no. 2020, pp.1-15.
https://search.emarefa.net/detail/BIM-1213719
Modern Language Association (MLA)
Cai, Yanping…[et al.]. A Novel Improved Local Binary Pattern and Its Application to the Fault Diagnosis of Diesel Engine. Shock and Vibration No. 2020 (2020), pp.1-15.
https://search.emarefa.net/detail/BIM-1213719
American Medical Association (AMA)
Cai, Yanping& Xu, Guanghua& Li, Aihua& Wang, Xu. A Novel Improved Local Binary Pattern and Its Application to the Fault Diagnosis of Diesel Engine. Shock and Vibration. 2020. Vol. 2020, no. 2020, pp.1-15.
https://search.emarefa.net/detail/BIM-1213719
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1213719