The Identification of Shaft Current Induced Defects on Rolling Bearings in Wind Turbine Generators

Long Li; Guangbin Wang; Wenhui Deng; Xiaoli Tang; Fengshou Gu; Andrew Ball

doi:10.23919/IConAC.2017.8081991

The Identification of Shaft Current Induced Defects on Rolling Bearings in Wind Turbine Generators

Long Li, Guangbin Wang, Wenhui Deng, Xiaoli Tang, Fengshou Gu, Andrew Ball

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

1 Citation (Scopus)

Abstract

Rolling bearings are an important part of wind turbine systems. Shaft current induced damages are one of the main causes for bearing failures, which lead to considerable operation loss of wind turbine plants. In this paper, the characteristics of shaft current damages and their induced vibration responses are studied analytically. Then it suggests to use an emerging Modulation Signal Bispectrum (MSB) to detect and diagnose the incipient defects as MSB can suppress various noise and provide a sparse result that integrates particularly the fault modulator and the structural resonance carrier to highlight the fault effect. Finally, the detection and diagnosis results based on both simulated signals and experimental signals show the outstanding performance of MSB analysis in detecting common bearing faults. Especially, it can achieve a straightforward differentiation between the fatigue pitting defects and shaft current damages, whereas conventional envelope analysis cannot provide a separation between these two types.

Original language	English
Title of host publication	Proceedings of the 23rd International Conference on Automation and Computing (University of Huddersfield, 7-8 September 2017)
Publisher	Institute of Electrical and Electronics Engineers Inc.
Number of pages	6
ISBN (Electronic)	9780701702601
ISBN (Print)	9781509050406
DOIs	https://doi.org/10.23919/IConAC.2017.8081991
Publication status	Published - 26 Oct 2017
Event	23rd International Conference on Automation and Computing: Addressing Global Challenges through Automation and Computing - University of Huddersfield, Huddersfield, United Kingdom Duration: 7 Sep 2017 → 8 Sep 2017 Conference number: 23 https://www.ieee.org/conferences_events/conferences/conferencedetails/index.html?Conf_ID=41042 (Link to Conference Website)

Conference

Conference	23rd International Conference on Automation and Computing
Abbreviated title	ICAC 2017
Country/Territory	United Kingdom
City	Huddersfield
Period	7/09/17 → 8/09/17
Other	The scope of the conference covers a broad spectrum of areas with multi-disciplinary interests in the fields of automation, control engineering, computing and information systems, ranging from fundamental research to real-world applications.
Internet address	https://www.ieee.org/conferences_events/conferences/conferencedetails/index.html?Conf_ID=41042 (Link to Conference Website)

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

Access to Document

10.23919/IConAC.2017.8081991Licence: Unspecified

http://eprints.hud.ac.uk/id/eprint/33632Licence: Unspecified

Cite this

Li, L., Wang, G., Deng, W., Tang, X., Gu, F., & Ball, A. (2017). The Identification of Shaft Current Induced Defects on Rolling Bearings in Wind Turbine Generators. In Proceedings of the 23rd International Conference on Automation and Computing (University of Huddersfield, 7-8 September 2017) Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.23919/IConAC.2017.8081991

@inproceedings{055bc36892b047859d90d1e2b046d6f7,

title = "The Identification of Shaft Current Induced Defects on Rolling Bearings in Wind Turbine Generators",

abstract = "Rolling bearings are an important part of wind turbine systems. Shaft current induced damages are one of the main causes for bearing failures, which lead to considerable operation loss of wind turbine plants. In this paper, the characteristics of shaft current damages and their induced vibration responses are studied analytically. Then it suggests to use an emerging Modulation Signal Bispectrum (MSB) to detect and diagnose the incipient defects as MSB can suppress various noise and provide a sparse result that integrates particularly the fault modulator and the structural resonance carrier to highlight the fault effect. Finally, the detection and diagnosis results based on both simulated signals and experimental signals show the outstanding performance of MSB analysis in detecting common bearing faults. Especially, it can achieve a straightforward differentiation between the fatigue pitting defects and shaft current damages, whereas conventional envelope analysis cannot provide a separation between these two types.",

keywords = "Shaft current, Bearing fault diagnosis, Envelope spectrum, MSB",

author = "Long Li and Guangbin Wang and Wenhui Deng and Xiaoli Tang and Fengshou Gu and Andrew Ball",

year = "2017",

month = oct,

day = "26",

doi = "10.23919/IConAC.2017.8081991",

language = "English",

isbn = "9781509050406",

booktitle = "Proceedings of the 23rd International Conference on Automation and Computing (University of Huddersfield, 7-8 September 2017)",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

address = "United States",

note = "23rd International Conference on Automation and Computing : Addressing Global Challenges through Automation and Computing, ICAC 2017 ; Conference date: 07-09-2017 Through 08-09-2017",

url = "https://www.ieee.org/conferences_events/conferences/conferencedetails/index.html?Conf_ID=41042",

}

Li, L, Wang, G, Deng, W, Tang, X, Gu, F & Ball, A 2017, The Identification of Shaft Current Induced Defects on Rolling Bearings in Wind Turbine Generators. in Proceedings of the 23rd International Conference on Automation and Computing (University of Huddersfield, 7-8 September 2017). Institute of Electrical and Electronics Engineers Inc., 23rd International Conference on Automation and Computing, Huddersfield, United Kingdom, 7/09/17. https://doi.org/10.23919/IConAC.2017.8081991

The Identification of Shaft Current Induced Defects on Rolling Bearings in Wind Turbine Generators. / Li, Long; Wang, Guangbin; Deng, Wenhui et al.

Proceedings of the 23rd International Conference on Automation and Computing (University of Huddersfield, 7-8 September 2017). Institute of Electrical and Electronics Engineers Inc., 2017.

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

TY - GEN

T1 - The Identification of Shaft Current Induced Defects on Rolling Bearings in Wind Turbine Generators

AU - Li, Long

AU - Wang, Guangbin

AU - Deng, Wenhui

AU - Tang, Xiaoli

AU - Gu, Fengshou

AU - Ball, Andrew

N1 - Conference code: 23

PY - 2017/10/26

Y1 - 2017/10/26

N2 - Rolling bearings are an important part of wind turbine systems. Shaft current induced damages are one of the main causes for bearing failures, which lead to considerable operation loss of wind turbine plants. In this paper, the characteristics of shaft current damages and their induced vibration responses are studied analytically. Then it suggests to use an emerging Modulation Signal Bispectrum (MSB) to detect and diagnose the incipient defects as MSB can suppress various noise and provide a sparse result that integrates particularly the fault modulator and the structural resonance carrier to highlight the fault effect. Finally, the detection and diagnosis results based on both simulated signals and experimental signals show the outstanding performance of MSB analysis in detecting common bearing faults. Especially, it can achieve a straightforward differentiation between the fatigue pitting defects and shaft current damages, whereas conventional envelope analysis cannot provide a separation between these two types.

AB - Rolling bearings are an important part of wind turbine systems. Shaft current induced damages are one of the main causes for bearing failures, which lead to considerable operation loss of wind turbine plants. In this paper, the characteristics of shaft current damages and their induced vibration responses are studied analytically. Then it suggests to use an emerging Modulation Signal Bispectrum (MSB) to detect and diagnose the incipient defects as MSB can suppress various noise and provide a sparse result that integrates particularly the fault modulator and the structural resonance carrier to highlight the fault effect. Finally, the detection and diagnosis results based on both simulated signals and experimental signals show the outstanding performance of MSB analysis in detecting common bearing faults. Especially, it can achieve a straightforward differentiation between the fatigue pitting defects and shaft current damages, whereas conventional envelope analysis cannot provide a separation between these two types.

KW - Shaft current

KW - Bearing fault diagnosis

KW - Envelope spectrum

KW - MSB

UR - http://ieeexplore.ieee.org/xpl/conhome.jsp?punumber=1800563

U2 - 10.23919/IConAC.2017.8081991

DO - 10.23919/IConAC.2017.8081991

M3 - Conference contribution

SN - 9781509050406

BT - Proceedings of the 23rd International Conference on Automation and Computing (University of Huddersfield, 7-8 September 2017)

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 23rd International Conference on Automation and Computing

Y2 - 7 September 2017 through 8 September 2017

ER -

The Identification of Shaft Current Induced Defects on Rolling Bearings in Wind Turbine Generators

Abstract

Conference

UN SDGs

Access to Document

Other files and links

Fingerprint

Cite this