Application of Vibration Signal Processing Methods to Detect and Diagnose Wheel Flats in Railway Vehicles
This paper studied two useful vibration signal processing methods for detection and diagnosis of wheel flats. First, the cepstrum analysis method combined with order analysis was applied to the vibration signal to detect periodic responses in the spectrum for a rotating body such as a wheel. In the...
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| Format: | Article |
| Language: | English |
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MDPI AG
2021-02-01
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| Series: | Applied Sciences |
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| Online Access: | https://www.mdpi.com/2076-3417/11/5/2151 |
| _version_ | 1797416962518679552 |
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| author | JaeSeok Shim GeoYoung Kim ByungJin Cho JeongSeo Koo |
| author_facet | JaeSeok Shim GeoYoung Kim ByungJin Cho JeongSeo Koo |
| author_sort | JaeSeok Shim |
| collection | DOAJ |
| description | This paper studied two useful vibration signal processing methods for detection and diagnosis of wheel flats. First, the cepstrum analysis method combined with order analysis was applied to the vibration signal to detect periodic responses in the spectrum for a rotating body such as a wheel. In the case of railway vehicles, changes in speed occur while driving. Thus, it is difficult to effectively evaluate the flat signal of the wheel because the time cycle of the flat signal changes frequently. Thus, the order analysis was combined with the existing cepstrum analysis method to consider the changes in train speed. The order analysis changes the domain of the vibration signal from time domain to rotating angular domain to consider the train speed change in the cepstrum analysis. Second, the cross correlation analysis method combined with the order analysis was applied to evaluate the flat signal from the vibration signal well containing the severe field noise produced by the vibrations of the rail irregularities and bogie components. Unlike the cepstrum analysis method, it can find out the wheel flat size because the flat signal linearly increases to the wheel flat. Thus, it is more effective when checking the size of the wheel flat. Finally, the data tested in the Korea Railroad Research Institute were used to confirm that the cepstrum analysis and cross correlation analysis methods are appropriate for not only simulation but also test data. |
| first_indexed | 2024-03-09T06:11:57Z |
| format | Article |
| id | doaj.art-cd38636ff8324dda8c2b0cbce37caa27 |
| institution | Directory Open Access Journal |
| issn | 2076-3417 |
| language | English |
| last_indexed | 2024-03-09T06:11:57Z |
| publishDate | 2021-02-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Applied Sciences |
| spelling | doaj.art-cd38636ff8324dda8c2b0cbce37caa272023-12-03T11:57:44ZengMDPI AGApplied Sciences2076-34172021-02-01115215110.3390/app11052151Application of Vibration Signal Processing Methods to Detect and Diagnose Wheel Flats in Railway VehiclesJaeSeok Shim0GeoYoung Kim1ByungJin Cho2JeongSeo Koo3Department of Railway Safety Engineering, Seoul National University of Science and Technology, Seoul 01811, KoreaDepartment of Rolling Stock System Engineering, Seoul National University of Science and Technology, Seoul 01811, KoreaDepartment of Rolling Stock System Engineering, Seoul National University of Science and Technology, Seoul 01811, KoreaDepartment of Railway Safety Engineering, Seoul National University of Science and Technology, Seoul 01811, KoreaThis paper studied two useful vibration signal processing methods for detection and diagnosis of wheel flats. First, the cepstrum analysis method combined with order analysis was applied to the vibration signal to detect periodic responses in the spectrum for a rotating body such as a wheel. In the case of railway vehicles, changes in speed occur while driving. Thus, it is difficult to effectively evaluate the flat signal of the wheel because the time cycle of the flat signal changes frequently. Thus, the order analysis was combined with the existing cepstrum analysis method to consider the changes in train speed. The order analysis changes the domain of the vibration signal from time domain to rotating angular domain to consider the train speed change in the cepstrum analysis. Second, the cross correlation analysis method combined with the order analysis was applied to evaluate the flat signal from the vibration signal well containing the severe field noise produced by the vibrations of the rail irregularities and bogie components. Unlike the cepstrum analysis method, it can find out the wheel flat size because the flat signal linearly increases to the wheel flat. Thus, it is more effective when checking the size of the wheel flat. Finally, the data tested in the Korea Railroad Research Institute were used to confirm that the cepstrum analysis and cross correlation analysis methods are appropriate for not only simulation but also test data.https://www.mdpi.com/2076-3417/11/5/2151fault detection and diagnosisvibration signal processing techniquewheel flatcepstrum analysiscross correlation analysis |
| spellingShingle | JaeSeok Shim GeoYoung Kim ByungJin Cho JeongSeo Koo Application of Vibration Signal Processing Methods to Detect and Diagnose Wheel Flats in Railway Vehicles Applied Sciences fault detection and diagnosis vibration signal processing technique wheel flat cepstrum analysis cross correlation analysis |
| title | Application of Vibration Signal Processing Methods to Detect and Diagnose Wheel Flats in Railway Vehicles |
| title_full | Application of Vibration Signal Processing Methods to Detect and Diagnose Wheel Flats in Railway Vehicles |
| title_fullStr | Application of Vibration Signal Processing Methods to Detect and Diagnose Wheel Flats in Railway Vehicles |
| title_full_unstemmed | Application of Vibration Signal Processing Methods to Detect and Diagnose Wheel Flats in Railway Vehicles |
| title_short | Application of Vibration Signal Processing Methods to Detect and Diagnose Wheel Flats in Railway Vehicles |
| title_sort | application of vibration signal processing methods to detect and diagnose wheel flats in railway vehicles |
| topic | fault detection and diagnosis vibration signal processing technique wheel flat cepstrum analysis cross correlation analysis |
| url | https://www.mdpi.com/2076-3417/11/5/2151 |
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