Condition monitoring of pitting evolution using multiple sensing
Condition monitoring of pitting evolution using multiple sensing
Pitting on surfaces is a type of rolling contact fatigue (RCF) occurs in rolling-sliding contacts operating under mixed or boundary lubrication conditions. The early detection of pitting is of great importance due to its potential detrimental effects on the performance and reliability of machinery components, such as rolling element bearings and gears. This research aims to investigate the responses of multiple sensors to the progression of pitting and achieve early detection of pitting initiation. Experiments were conducted on a TE74 twin-disc tribometer to investigate the behaviour of bearing steel discs. Mild wear and pitting fatigue were obtained with specimens of different roughness combinations. During testing, vibration, acoustic emission (AE) and
electrostatic (ES) data were recorded, and post-test signal analysis was conducted in both the time domain and frequency domain. After testing, the worn surfaces were examined to determine the mechanisms responsible for specific features seen in the sensor data. The presence of pitting in the near-surface region was observed, and its development was effectively monitored using the employed sensing techniques. The stages of running-in, pitting initiation, and pitting formation were identified through the analysis of time domain parameters and frequency spectrums. Vibration signal analysis exhibited a more prominent indication of pitting formation, whereas AE and ES methods demonstrated an
ability to detect the onset of pitting at an earlier stage.
Tian, Zaihao
5e2ef015-09d7-4b13-b8f5-3878de761eb4
Wang, Shuncai
8a390e2d-6552-4c7c-a88f-25bf9d6986a6
Merk, Daniel
2fedf927-8b2c-41cb-b6e0-40329a3ca193
Wood, Robert
d9523d31-41a8-459a-8831-70e29ffe8a73
September 2023
Tian, Zaihao
5e2ef015-09d7-4b13-b8f5-3878de761eb4
Wang, Shuncai
8a390e2d-6552-4c7c-a88f-25bf9d6986a6
Merk, Daniel
2fedf927-8b2c-41cb-b6e0-40329a3ca193
Wood, Robert
d9523d31-41a8-459a-8831-70e29ffe8a73
Tian, Zaihao, Wang, Shuncai, Merk, Daniel and Wood, Robert
(2023)
Condition monitoring of pitting evolution using multiple sensing.
The Nineteenth International Conference on Condition Monitoring and Asset Management, , Northampton, United Kingdom.
12 - 14 Sep 2023.
12 pp
.
Record type:
Conference or Workshop Item
(Paper)
Abstract
Pitting on surfaces is a type of rolling contact fatigue (RCF) occurs in rolling-sliding contacts operating under mixed or boundary lubrication conditions. The early detection of pitting is of great importance due to its potential detrimental effects on the performance and reliability of machinery components, such as rolling element bearings and gears. This research aims to investigate the responses of multiple sensors to the progression of pitting and achieve early detection of pitting initiation. Experiments were conducted on a TE74 twin-disc tribometer to investigate the behaviour of bearing steel discs. Mild wear and pitting fatigue were obtained with specimens of different roughness combinations. During testing, vibration, acoustic emission (AE) and
electrostatic (ES) data were recorded, and post-test signal analysis was conducted in both the time domain and frequency domain. After testing, the worn surfaces were examined to determine the mechanisms responsible for specific features seen in the sensor data. The presence of pitting in the near-surface region was observed, and its development was effectively monitored using the employed sensing techniques. The stages of running-in, pitting initiation, and pitting formation were identified through the analysis of time domain parameters and frequency spectrums. Vibration signal analysis exhibited a more prominent indication of pitting formation, whereas AE and ES methods demonstrated an
ability to detect the onset of pitting at an earlier stage.
Text
1D3-FULL.Tian.Zaihio
- Accepted Manuscript
More information
Accepted/In Press date: 3 July 2023
Published date: September 2023
Venue - Dates:
The Nineteenth International Conference on Condition Monitoring and Asset Management, , Northampton, United Kingdom, 2023-09-12 - 2023-09-14
Identifiers
Local EPrints ID: 483950
URI: http://eprints.soton.ac.uk/id/eprint/483950
PURE UUID: 862af808-98a2-49fd-b556-0505bdf6c877
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Date deposited: 07 Nov 2023 18:47
Last modified: 14 Apr 2024 01:56
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Contributors
Author:
Zaihao Tian
Author:
Daniel Merk
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