Condition monitoring approaches for the detection of railway wheel defects

Alemi, Alireza; Corman, Francesco; Lodewijks, Gabriël

doi:10.1177/0954409716656218

Cited by 107 publications

(69 citation statements)

References 65 publications

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“…In recent years, researchers have proposed many different methods for in-service measuring of wheel defects, which have, generally, been divided into two types, on-board and wayside measurements [9]. Most on-board techniques are based on vibration, acoustic, image detection, and ultrasonic technologies.…”

Section: Introductionmentioning

confidence: 99%

Railway Wheel Flat Recognition and Precise Positioning Method Based on Multisensor Arrays

et al. 2020

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Featured Application: Wheel flats are one of the most threatening defects during the service lifespan of railway vehicle wheels. This study proposes a new long-term monitoring method for wheel flats based on multisensor arrays. The dynamic strain responses of rails are captured by sensor arrays mounted on the rail web, ensuring that all the wheels are assessed during the train passage. Through data fusion among multiple sensors, the method locates the specific position of wheel defects. This study provides potential guidance for the maintenance of vehicles soon after the occurrences of defects.Abstract: Wheel flats have become a major problem affecting the long-term service of railway systems. Wheels with flats create intermittent impact loads to trains and rails. This not only accelerates the deterioration of vehicle and track components but also leads to abnormal wheel-rail contact conditions. An effective method for detecting wheel conditions is urgently needed to ensure the operation of the railway and provide guidance for the repair of wheels. However, most previous researches have used qualitative detection methods, and hence have been unable to achieve accurate positioning of the wheel flats. In addition, the theoretical basis for the layout scheme for wheel flat detection sensors is lacking, making it impossible to meet the needs of field applications. In this study, we simulated the spatial distribution characteristics of rail strain, under different wheel flat conditions, and based on this, a layout scheme of multisensor arrays was proposed which more effectively captured the responses of the wheel flats. A wheel flat recognition and precise positioning method based on multisensor fusion was designed. The algorithm was validated through the combination of experimental and simulation methods. The result shows that the algorithm can ideally detect and locate the wheel flats under complex conditions.

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Section: Introductionmentioning

confidence: 99%

Railway Wheel Flat Recognition and Precise Positioning Method Based on Multisensor Arrays

et al. 2020

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“…The main benefit of using accelerometers over strain gauges for detecting wheel defects is their ability to detect impact across the entire length of the rail between two sleepers, thus providing a more effective condition monitoring for the entire circumference of the wheel [71]. Nevertheless, a limited performance regarding repeatability for detecting damage has been identified for some conventional accelerometer-based systems [70]. However, the advantage of these systems over strain based systems is that the magnitude of the response depends in part on the wheel/rail associated with the unsprung mass [68].…”

Section: Accelerometermentioning

confidence: 99%

“…However, the advantage of these systems over strain based systems is that the magnitude of the response depends in part on the wheel/rail associated with the unsprung mass [68]. Therefore, the response is independent of the vehicle mass [70].…”

Section: Accelerometermentioning

confidence: 99%

“…In railway applications, the vibration monitored by the accelerometer in the track can be converted into force, and then be used for detecting wheel defects or counting the number of axles (in this case a supplementary method is needed) [68,69]. Field testing has been extensively executed for validating the ability of accelerometer based condition monitoring systems to capture several train features for different passing speeds from the track vibration [70].…”

Section: Accelerometermentioning

confidence: 99%

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State-of-the-Art Review of Railway Track Resilience Monitoring

2018

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Abstract:In recent years, railway systems have played a significant role in transportation systems due to the demand increase in conveying both cargo and passengers. Due to the harsh environments and severe loading conditions, caused by the traffic growth, heavier axles and vehicles and increase in speed, railway tracks are at risk of degradation and failure. Condition monitoring has been widely used to support the health assessment of civil engineering structures and infrastructures. In this context, it was adopted as a powerful tool for an objective assessment of the railway track behaviour by enabling real-time data collection, inspection and detection of structural degradation. According to relevant literature, a number of sensors can be used to monitor track behaviour during the train passing under harsh environments. This paper presents a review of sensors used for structural monitoring of railway track infrastructure, as well as their application to sense the performance of different track components during extreme events. The insight into track monitoring for railways serving traffic with extreme features will not only improve the track inspection and damage detection but also enable a predictive track maintenance regime in order to assist the decision-making process towards more cost-effective management in the railway industry.

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“…Many condition monitoring methods have been studied by different researchers, which are commented in general review works of [1][2][3][4]. Based on these reviews, the condition monitoring methods can be divided into two main groups, on-board and track-side techniques.…”

Section: Introductionmentioning

confidence: 99%