Centrifugal Pumps Fault Diagnosis Using Multivariate Multiscale Symbolic Dynamic Entropy and Logistic Regression

Yongbo Li; Xianzhi Wang; Shubin Si

doi:10.1109/PHM-Chongqing.2018.00078

Centrifugal Pumps Fault Diagnosis Using Multivariate Multiscale Symbolic Dynamic Entropy and Logistic Regression

Yongbo Li, Xianzhi Wang, Shubin Si

Northwestern Polytechnical University Xian

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

6 Scopus citations

Abstract

The fault diagnosis of centrifugal pumps is crucial to ensure its safety operation and reduce the maintenance costs. In this paper, a novel framework is established for fault diagnosis of centrifugal pumps. First, the multivariate multiscale symbolic dynamic entropy (MvMSDE) is proposed to extract the fault features from the measured synchronous multi-channel vibration signals. Then, the fault features are taken as the input of logistic regression (LR) to classify different fault types of a centrifugal pump. The effectiveness of the proposed method is validated using the experimental data. Meanwhile, a comparison is conducted between MSDE and MvMSDE. Results show that the proposed method has better performance to recognize different bearing and impeller faults of centrifugal pumps.

Original language	English
Title of host publication	Proceedings - 2018 Prognostics and System Health Management Conference, PHM-Chongqing 2018
Editors	Ping Ding, Chuan Li, Shuai Yang, Ping Ding, Rene-Vinicio Sanchez
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	422-426
Number of pages	5
ISBN (Electronic)	9781538653791
DOIs	https://doi.org/10.1109/PHM-Chongqing.2018.00078
State	Published - 4 Jan 2019
Event	2018 Prognostics and System Health Management Conference, PHM-Chongqing 2018 - Chongqing, China Duration: 26 Oct 2018 → 28 Oct 2018

Publication series

Name	Proceedings - 2018 Prognostics and System Health Management Conference, PHM-Chongqing 2018

Conference

Conference	2018 Prognostics and System Health Management Conference, PHM-Chongqing 2018
Country/Territory	China
City	Chongqing
Period	26/10/18 → 28/10/18

Keywords

Centrifugal pumps
Fault feature extraction
Multivariate multiscale symbolic dynamic entropy (MvMSDE)

Access to Document

10.1109/PHM-Chongqing.2018.00078

Cite this

Li, Y., Wang, X., & Si, S. (2019). Centrifugal Pumps Fault Diagnosis Using Multivariate Multiscale Symbolic Dynamic Entropy and Logistic Regression. In P. Ding, C. Li, S. Yang, P. Ding, & R.-V. Sanchez (Eds.), Proceedings - 2018 Prognostics and System Health Management Conference, PHM-Chongqing 2018 (pp. 422-426). Article 8603386 (Proceedings - 2018 Prognostics and System Health Management Conference, PHM-Chongqing 2018). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/PHM-Chongqing.2018.00078

Li, Yongbo ; Wang, Xianzhi ; Si, Shubin. / Centrifugal Pumps Fault Diagnosis Using Multivariate Multiscale Symbolic Dynamic Entropy and Logistic Regression. Proceedings - 2018 Prognostics and System Health Management Conference, PHM-Chongqing 2018. editor / Ping Ding ; Chuan Li ; Shuai Yang ; Ping Ding ; Rene-Vinicio Sanchez. Institute of Electrical and Electronics Engineers Inc., 2019. pp. 422-426 (Proceedings - 2018 Prognostics and System Health Management Conference, PHM-Chongqing 2018).

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title = "Centrifugal Pumps Fault Diagnosis Using Multivariate Multiscale Symbolic Dynamic Entropy and Logistic Regression",

abstract = "The fault diagnosis of centrifugal pumps is crucial to ensure its safety operation and reduce the maintenance costs. In this paper, a novel framework is established for fault diagnosis of centrifugal pumps. First, the multivariate multiscale symbolic dynamic entropy (MvMSDE) is proposed to extract the fault features from the measured synchronous multi-channel vibration signals. Then, the fault features are taken as the input of logistic regression (LR) to classify different fault types of a centrifugal pump. The effectiveness of the proposed method is validated using the experimental data. Meanwhile, a comparison is conducted between MSDE and MvMSDE. Results show that the proposed method has better performance to recognize different bearing and impeller faults of centrifugal pumps.",

keywords = "Centrifugal pumps, Fault feature extraction, Multivariate multiscale symbolic dynamic entropy (MvMSDE)",

author = "Yongbo Li and Xianzhi Wang and Shubin Si",

note = "Publisher Copyright: {\textcopyright} 2018 IEEE.; 2018 Prognostics and System Health Management Conference, PHM-Chongqing 2018 ; Conference date: 26-10-2018 Through 28-10-2018",

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Li, Y, Wang, X & Si, S 2019, Centrifugal Pumps Fault Diagnosis Using Multivariate Multiscale Symbolic Dynamic Entropy and Logistic Regression. in P Ding, C Li, S Yang, P Ding & R-V Sanchez (eds), Proceedings - 2018 Prognostics and System Health Management Conference, PHM-Chongqing 2018., 8603386, Proceedings - 2018 Prognostics and System Health Management Conference, PHM-Chongqing 2018, Institute of Electrical and Electronics Engineers Inc., pp. 422-426, 2018 Prognostics and System Health Management Conference, PHM-Chongqing 2018, Chongqing, China, 26/10/18. https://doi.org/10.1109/PHM-Chongqing.2018.00078

Centrifugal Pumps Fault Diagnosis Using Multivariate Multiscale Symbolic Dynamic Entropy and Logistic Regression. / Li, Yongbo; Wang, Xianzhi; Si, Shubin.
Proceedings - 2018 Prognostics and System Health Management Conference, PHM-Chongqing 2018. ed. / Ping Ding; Chuan Li; Shuai Yang; Ping Ding; Rene-Vinicio Sanchez. Institute of Electrical and Electronics Engineers Inc., 2019. p. 422-426 8603386 (Proceedings - 2018 Prognostics and System Health Management Conference, PHM-Chongqing 2018).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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T1 - Centrifugal Pumps Fault Diagnosis Using Multivariate Multiscale Symbolic Dynamic Entropy and Logistic Regression

AU - Li, Yongbo

AU - Wang, Xianzhi

AU - Si, Shubin

PY - 2019/1/4

Y1 - 2019/1/4

N2 - The fault diagnosis of centrifugal pumps is crucial to ensure its safety operation and reduce the maintenance costs. In this paper, a novel framework is established for fault diagnosis of centrifugal pumps. First, the multivariate multiscale symbolic dynamic entropy (MvMSDE) is proposed to extract the fault features from the measured synchronous multi-channel vibration signals. Then, the fault features are taken as the input of logistic regression (LR) to classify different fault types of a centrifugal pump. The effectiveness of the proposed method is validated using the experimental data. Meanwhile, a comparison is conducted between MSDE and MvMSDE. Results show that the proposed method has better performance to recognize different bearing and impeller faults of centrifugal pumps.

AB - The fault diagnosis of centrifugal pumps is crucial to ensure its safety operation and reduce the maintenance costs. In this paper, a novel framework is established for fault diagnosis of centrifugal pumps. First, the multivariate multiscale symbolic dynamic entropy (MvMSDE) is proposed to extract the fault features from the measured synchronous multi-channel vibration signals. Then, the fault features are taken as the input of logistic regression (LR) to classify different fault types of a centrifugal pump. The effectiveness of the proposed method is validated using the experimental data. Meanwhile, a comparison is conducted between MSDE and MvMSDE. Results show that the proposed method has better performance to recognize different bearing and impeller faults of centrifugal pumps.

KW - Centrifugal pumps

KW - Fault feature extraction

KW - Multivariate multiscale symbolic dynamic entropy (MvMSDE)

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A2 - Ding, Ping

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PB - Institute of Electrical and Electronics Engineers Inc.

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Y2 - 26 October 2018 through 28 October 2018

ER -

Li Y, Wang X, Si S. Centrifugal Pumps Fault Diagnosis Using Multivariate Multiscale Symbolic Dynamic Entropy and Logistic Regression. In Ding P, Li C, Yang S, Ding P, Sanchez RV, editors, Proceedings - 2018 Prognostics and System Health Management Conference, PHM-Chongqing 2018. Institute of Electrical and Electronics Engineers Inc. 2019. p. 422-426. 8603386. (Proceedings - 2018 Prognostics and System Health Management Conference, PHM-Chongqing 2018). doi: 10.1109/PHM-Chongqing.2018.00078

Centrifugal Pumps Fault Diagnosis Using Multivariate Multiscale Symbolic Dynamic Entropy and Logistic Regression

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