Study on Vibration Characteristics Analysis and Characterization of Multiple Failure Modes of High-speed Train Axle Bearing

CAI YI; JIANHUI LIN; LU LIU; KWOK-LEUNG TSUI

Study on Vibration Characteristics Analysis and Characterization of Multiple Failure Modes of High-speed Train Axle Bearing

CAI YI
, JIANHUI LIN
, LU LIU
, KWOK-LEUNG TSUI

Research output: Chapters, Conference Papers, Creative and Literary Works › RGC 32 - Refereed conference paper (with host publication) › peer-review

Abstract

This paper focuses on analysing vibration signals from the axle bearings of highspeed trains to quantitatively characterize the bearings' operating conditions. A novel characterization method for analyzing the axle-box vibration signature based on the EEMD shape function is presented. A wheel-set running test bench is used to obtain the different vibration signals of an axle bearing with multiple fault statuses. The main IMF of measured signals is selected to establish the shape function. The resulting steadiness index contains well-defined dividing value intervals with no overlap between multiple axle bearing states. Based on the results obtained, the proposed method provides an effective and reliable condition monitoring procedure and a reference threshold for axle bearing online monitoring strategies and alarm mechanisms in real-world applications.

Original language	English
Title of host publication	Structural Health Monitoring 2017
Subtitle of host publication	Real-Time Material State Awareness and Data-Driven Safety Assurance - Proceedings of the 11th International Workshop on Structural Health Monitoring, September 12–14, 2017
Editors	Fu-Kuo Chang, Fotis Kopsaftopoulos
Publisher	DEStech Publications, Inc.
Pages	2935-2942
Volume	2
ISBN (Print)	9781605953304
Publication status	Published - Sept 2017
Event	The 11th International Workshop on Structural Health Monitoring : Real-Time Material State Awareness and Data-Driven Safety Assurance - Stanford University, Stanford, United States Duration: 12 Sept 2017 → 14 Sept 2017 http://web.stanford.edu/group/sacl/workshop/IWSHM2017/index.html https://web.stanford.edu/group/sacl/workshop/IWSHM2017/nposter.html

Conference

Conference	The 11th International Workshop on Structural Health Monitoring : Real-Time Material State Awareness and Data-Driven Safety Assurance
Abbreviated title	IWSHM 2017
Place	United States
City	Stanford
Period	12/09/17 → 14/09/17
Internet address	http://web.stanford.edu/group/sacl/workshop/IWSHM2017/index.html https://web.stanford.edu/group/sacl/workshop/IWSHM2017/nposter.html

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Full text of this publication does not contain sufficient affiliation information. With consent from the author(s) concerned, the Research Unit(s) information for this record is based on the existing academic department affiliation of the author(s).

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YI, CAI., LIN, JIANHUI., LIU, LU., & TSUI, KWOK.-LEUNG. (2017). Study on Vibration Characteristics Analysis and Characterization of Multiple Failure Modes of High-speed Train Axle Bearing. In F.-K. Chang, & F. Kopsaftopoulos (Eds.), Structural Health Monitoring 2017: Real-Time Material State Awareness and Data-Driven Safety Assurance - Proceedings of the 11th International Workshop on Structural Health Monitoring, September 12–14, 2017 (Vol. 2, pp. 2935-2942). DEStech Publications, Inc..

YI, CAI ; LIN, JIANHUI ; LIU, LU et al. / Study on Vibration Characteristics Analysis and Characterization of Multiple Failure Modes of High-speed Train Axle Bearing. Structural Health Monitoring 2017: Real-Time Material State Awareness and Data-Driven Safety Assurance - Proceedings of the 11th International Workshop on Structural Health Monitoring, September 12–14, 2017. editor / Fu-Kuo Chang ; Fotis Kopsaftopoulos. Vol. 2 DEStech Publications, Inc., 2017. pp. 2935-2942

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title = "Study on Vibration Characteristics Analysis and Characterization of Multiple Failure Modes of High-speed Train Axle Bearing",

abstract = "This paper focuses on analysing vibration signals from the axle bearings of highspeed trains to quantitatively characterize the bearings' operating conditions. A novel characterization method for analyzing the axle-box vibration signature based on the EEMD shape function is presented. A wheel-set running test bench is used to obtain the different vibration signals of an axle bearing with multiple fault statuses. The main IMF of measured signals is selected to establish the shape function. The resulting steadiness index contains well-defined dividing value intervals with no overlap between multiple axle bearing states. Based on the results obtained, the proposed method provides an effective and reliable condition monitoring procedure and a reference threshold for axle bearing online monitoring strategies and alarm mechanisms in real-world applications.",

author = "CAI YI and JIANHUI LIN and LU LIU and KWOK-LEUNG TSUI",

note = "Full text of this publication does not contain sufficient affiliation information. With consent from the author(s) concerned, the Research Unit(s) information for this record is based on the existing academic department affiliation of the author(s).; The 11th International Workshop on Structural Health Monitoring : Real-Time Material State Awareness and Data-Driven Safety Assurance, IWSHM 2017 ; Conference date: 12-09-2017 Through 14-09-2017",

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language = "English",

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editor = "Fu-Kuo Chang and Fotis Kopsaftopoulos",

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YI, CAI, LIN, JIANHUI, LIU, LU & TSUI, KWOK-LEUNG 2017, Study on Vibration Characteristics Analysis and Characterization of Multiple Failure Modes of High-speed Train Axle Bearing. in F-K Chang & F Kopsaftopoulos (eds), Structural Health Monitoring 2017: Real-Time Material State Awareness and Data-Driven Safety Assurance - Proceedings of the 11th International Workshop on Structural Health Monitoring, September 12–14, 2017. vol. 2, DEStech Publications, Inc., pp. 2935-2942, The 11th International Workshop on Structural Health Monitoring : Real-Time Material State Awareness and Data-Driven Safety Assurance, Stanford, California, United States, 12/09/17.

Study on Vibration Characteristics Analysis and Characterization of Multiple Failure Modes of High-speed Train Axle Bearing. / YI, CAI; LIN, JIANHUI; LIU, LU et al.
Structural Health Monitoring 2017: Real-Time Material State Awareness and Data-Driven Safety Assurance - Proceedings of the 11th International Workshop on Structural Health Monitoring, September 12–14, 2017. ed. / Fu-Kuo Chang; Fotis Kopsaftopoulos. Vol. 2 DEStech Publications, Inc., 2017. p. 2935-2942.

Research output: Chapters, Conference Papers, Creative and Literary Works › RGC 32 - Refereed conference paper (with host publication) › peer-review

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AU - YI, CAI

AU - LIN, JIANHUI

AU - LIU, LU

AU - TSUI, KWOK-LEUNG

N1 - Full text of this publication does not contain sufficient affiliation information. With consent from the author(s) concerned, the Research Unit(s) information for this record is based on the existing academic department affiliation of the author(s).

PY - 2017/9

Y1 - 2017/9

N2 - This paper focuses on analysing vibration signals from the axle bearings of highspeed trains to quantitatively characterize the bearings' operating conditions. A novel characterization method for analyzing the axle-box vibration signature based on the EEMD shape function is presented. A wheel-set running test bench is used to obtain the different vibration signals of an axle bearing with multiple fault statuses. The main IMF of measured signals is selected to establish the shape function. The resulting steadiness index contains well-defined dividing value intervals with no overlap between multiple axle bearing states. Based on the results obtained, the proposed method provides an effective and reliable condition monitoring procedure and a reference threshold for axle bearing online monitoring strategies and alarm mechanisms in real-world applications.

AB - This paper focuses on analysing vibration signals from the axle bearings of highspeed trains to quantitatively characterize the bearings' operating conditions. A novel characterization method for analyzing the axle-box vibration signature based on the EEMD shape function is presented. A wheel-set running test bench is used to obtain the different vibration signals of an axle bearing with multiple fault statuses. The main IMF of measured signals is selected to establish the shape function. The resulting steadiness index contains well-defined dividing value intervals with no overlap between multiple axle bearing states. Based on the results obtained, the proposed method provides an effective and reliable condition monitoring procedure and a reference threshold for axle bearing online monitoring strategies and alarm mechanisms in real-world applications.

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BT - Structural Health Monitoring 2017

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A2 - Kopsaftopoulos, Fotis

PB - DEStech Publications, Inc.

T2 - The 11th International Workshop on Structural Health Monitoring : Real-Time Material State Awareness and Data-Driven Safety Assurance

Y2 - 12 September 2017 through 14 September 2017

ER -

YI CAI, LIN JIANHUI, LIU LU, TSUI KWOKLEUNG. Study on Vibration Characteristics Analysis and Characterization of Multiple Failure Modes of High-speed Train Axle Bearing. In Chang FK, Kopsaftopoulos F, editors, Structural Health Monitoring 2017: Real-Time Material State Awareness and Data-Driven Safety Assurance - Proceedings of the 11th International Workshop on Structural Health Monitoring, September 12–14, 2017. Vol. 2. DEStech Publications, Inc. 2017. p. 2935-2942

Study on Vibration Characteristics Analysis and Characterization of Multiple Failure Modes of High-speed Train Axle Bearing

Abstract

Conference

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