Adaptive noise cancelling and time-frequency techniques for rail surface defect detection
- Submitting institution
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The University of Huddersfield
- Unit of assessment
- 12 - Engineering
- Output identifier
- 24
- Type
- D - Journal article
- DOI
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10.1016/j.ymssp.2014.06.012
- Title of journal
- Mechanical Systems and Signal Processing
- Article number
- -
- First page
- 41
- Volume
- 54-55
- Issue
- -
- ISSN
- 0888-3270
- Open access status
- Out of scope for open access requirements
- Month of publication
- September
- Year of publication
- 2014
- URL
-
-
- Supplementary information
-
-
- Request cross-referral to
- -
- Output has been delayed by COVID-19
- No
- COVID-19 affected output statement
- -
- Forensic science
- No
- Criminology
- No
- Interdisciplinary
- No
- Number of additional authors
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3
- Research group(s)
-
-
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- This was an investigation of adaptive noise cancellation (ANC) for railway vehicle fault diagnosis. ANC is a technique which is very effective to remove additive noises from the contaminated signals. However, it was seldom used for the surveillance and diagnosis of mechanical systems before late of 1990s. An ANC and time-frequency application for railway wheel flat and rail surface defect detection has been carried out. The experimental results show that this approach can significantly reduce unwanted interferences noise and extract the weak signals from strong background noises. The paper attracted interest from companies for its potential application in railway industry.
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -