Real time implementation of fiber Bragg grating sensor in monitoring flat wheel detection for railways. (August 2022)
- Record Type:
- Journal Article
- Title:
- Real time implementation of fiber Bragg grating sensor in monitoring flat wheel detection for railways. (August 2022)
- Main Title:
- Real time implementation of fiber Bragg grating sensor in monitoring flat wheel detection for railways
- Authors:
- Mishra, Suchandana
Sharan, Preeta
Saara, K. - Abstract:
- Graphical abstract: Highlights: Rail-wheel analysis of the train. Real time monitoring and detection of the train wheel passage using optical sensor fiber Bragg grating sensor. Positions of grating sensors installed on the rail. Time domain and frequency spectrum analysis for the strain data induced on the rail when train passes by, to detect wheel flats. Reflection spectrum analysis for good wheel and bad wheel of a passenger train. Abstract: Wheel flats are a key source of issues in railway systems, as they generate significant wear on both the infrastructure and the train carriages. Flat zones on the wheel tread are created by the wheel sliding unintentionally on the rail. They can cause serious damage to the train and accidents, so identifying worn wheels is critical for human safety and rail transit. The purpose of this study is to present the real-time implementation of fiber Bragg grating sensors on rail tracks and to investigate the train's flat wheel status. By considering passenger train running at speed 70kmph, it has been monitored for 35 sec in the interrogator. Real time analysis of strain induced in the rail was calculated and it has been found from the sensor reading there is peak value of strain of the order of 303.4 µɛ which implies that wheel flatness is present whereas for normal wheel strain value is minimal up to 173.23 µɛ. By collecting experimental strain data simulation has been done and shift in peak wavelength at 1550.804 nm and reflectivityGraphical abstract: Highlights: Rail-wheel analysis of the train. Real time monitoring and detection of the train wheel passage using optical sensor fiber Bragg grating sensor. Positions of grating sensors installed on the rail. Time domain and frequency spectrum analysis for the strain data induced on the rail when train passes by, to detect wheel flats. Reflection spectrum analysis for good wheel and bad wheel of a passenger train. Abstract: Wheel flats are a key source of issues in railway systems, as they generate significant wear on both the infrastructure and the train carriages. Flat zones on the wheel tread are created by the wheel sliding unintentionally on the rail. They can cause serious damage to the train and accidents, so identifying worn wheels is critical for human safety and rail transit. The purpose of this study is to present the real-time implementation of fiber Bragg grating sensors on rail tracks and to investigate the train's flat wheel status. By considering passenger train running at speed 70kmph, it has been monitored for 35 sec in the interrogator. Real time analysis of strain induced in the rail was calculated and it has been found from the sensor reading there is peak value of strain of the order of 303.4 µɛ which implies that wheel flatness is present whereas for normal wheel strain value is minimal up to 173.23 µɛ. By collecting experimental strain data simulation has been done and shift in peak wavelength at 1550.804 nm and reflectivity obtained was 89.3% for flat wheel. Simulation result shows that there is a remarkable wavelength shift for the flat wheel and normal wheel from the Bragg center wavelength. … (more)
- Is Part Of:
- Engineering failure analysis. Volume 138(2022)
- Journal:
- Engineering failure analysis
- Issue:
- Volume 138(2022)
- Issue Display:
- Volume 138, Issue 2022 (2022)
- Year:
- 2022
- Volume:
- 138
- Issue:
- 2022
- Issue Sort Value:
- 2022-0138-2022-0000
- Page Start:
- Page End:
- Publication Date:
- 2022-08
- Subjects:
- Wheel flat detection -- Fiber Bragg grating -- Optical sensor -- Rail wheel analysis -- Healthy wheel -- Worn wheel -- Signal processing
System failures (Engineering) -- Periodicals
Fracture mechanics -- Periodicals
Reliability (Engineering) -- Periodicals
Pannes -- Périodiques
Rupture, Mécanique de la -- Périodiques
Fiabilité -- Périodiques
Fracture mechanics
Reliability (Engineering)
System failures (Engineering)
Periodicals
Electronic journals
620.112 - Journal URLs:
- http://www.sciencedirect.com/science/journal/13506307 ↗
http://www.elsevier.com/journals ↗ - DOI:
- 10.1016/j.engfailanal.2022.106376 ↗
- Languages:
- English
- ISSNs:
- 1350-6307
- Deposit Type:
- Legaldeposit
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- British Library DSC - 3760.991000
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