The work presented in this paper aims at investigating the ability of acoustic noise correlation technique for railway infrastructure health monitoring. The principle of this technique is based on impulse responses re...The work presented in this paper aims at investigating the ability of acoustic noise correlation technique for railway infrastructure health monitoring. The principle of this technique is based on impulse responses reconstruction by correlation of random noise propagated in the medium. Since wheel-rail interaction constitutes a source of such noise, correlation technique could be convenient for detection of rail defects using only passive sensors. Experiments have been carried out on a 2 m-long rail sample. Acoustic noise is generated in the sample at several positions. Direct comparison between an active emission-reception response and the estimated noise correlation function has confirmed the validity of the equivalence relation between them. The quality of the reconstruction is shown to be strongly related to the spatial distribution of the noise sources. High sensitivity of the noise-correlation functions to a local defect on the rail is also demonstrated. However, interpretation of the defect signature is more ambiguous than when using classical active responses. Application of a spatiotemporal Fourier transform on data recorded with variable sensor-defect distances has allowed overcoming this ambiguity.展开更多
WSNs （wireless sensor networks） can be used for railway infrastructure inspection and vehicle health monitoring. SHM （structural health monitoring） systems have a great potential to improve regular operation, secu...WSNs （wireless sensor networks） can be used for railway infrastructure inspection and vehicle health monitoring. SHM （structural health monitoring） systems have a great potential to improve regular operation, security and maintenance routine of structures with estimating the state of its health and detecting the changes that affect its performance. This is vital for the development, upgrading, and expansion of railway networks. The work presented in this paper aims at the possible use of acoustic sensors coupled with ZigBee modules for health monitoring of rails. The detection principle is based on acoustic noise correlation techniques. Experiments have been performed in a rail sample to confirm the validity of acoustic noise correlation techniques in the rail. A wireless communication platform prototype based on the ZigBee/IEEE 802.15.4 technology has been implemented and deployed on a rail sample. Once the signals from the structure are collected, sensor data are transmitted through a ZigBee solution to the processing unit.展开更多
Rail defects can pose significant safety risks in railway operations, raising the need for effective detection methods. Acoustic Emission (AE) technology has shown promise for identifying and monitoring these defects,...Rail defects can pose significant safety risks in railway operations, raising the need for effective detection methods. Acoustic Emission (AE) technology has shown promise for identifying and monitoring these defects, and this study evaluates an advanced on-vehicle AE detection approach using bone-conduct sensors—a solution to improve upon previous AE methods of using on-rail sensor installations, which required extensive, costly on-rail sensor networks with limited effectiveness. In response to these challenges, the study specifically explored bone-conduct sensors mounted directly on the vehicle rather than rails by evaluating AE signals generated by the interaction between rails and the train’s wheels while in motion. In this research, a prototype detection system was developed and tested through initial trials at the Nevada Railroad Museum using a track with pre-damaged welding defects. Further testing was conducted at the Transportation Technology Center Inc. (rebranded as MxV Rail) in Colorado, where the system’s performance was evaluated across various defect types and train speeds. The results indicated that bone-conduct sensors were insufficient for detecting AE signals when mounted on moving vehicles. These findings highlight the limitations of contact-based methods in real-world applications and indicate the need for exploring improved, non-contact approaches.展开更多
文摘The work presented in this paper aims at investigating the ability of acoustic noise correlation technique for railway infrastructure health monitoring. The principle of this technique is based on impulse responses reconstruction by correlation of random noise propagated in the medium. Since wheel-rail interaction constitutes a source of such noise, correlation technique could be convenient for detection of rail defects using only passive sensors. Experiments have been carried out on a 2 m-long rail sample. Acoustic noise is generated in the sample at several positions. Direct comparison between an active emission-reception response and the estimated noise correlation function has confirmed the validity of the equivalence relation between them. The quality of the reconstruction is shown to be strongly related to the spatial distribution of the noise sources. High sensitivity of the noise-correlation functions to a local defect on the rail is also demonstrated. However, interpretation of the defect signature is more ambiguous than when using classical active responses. Application of a spatiotemporal Fourier transform on data recorded with variable sensor-defect distances has allowed overcoming this ambiguity.
文摘WSNs （wireless sensor networks） can be used for railway infrastructure inspection and vehicle health monitoring. SHM （structural health monitoring） systems have a great potential to improve regular operation, security and maintenance routine of structures with estimating the state of its health and detecting the changes that affect its performance. This is vital for the development, upgrading, and expansion of railway networks. The work presented in this paper aims at the possible use of acoustic sensors coupled with ZigBee modules for health monitoring of rails. The detection principle is based on acoustic noise correlation techniques. Experiments have been performed in a rail sample to confirm the validity of acoustic noise correlation techniques in the rail. A wireless communication platform prototype based on the ZigBee/IEEE 802.15.4 technology has been implemented and deployed on a rail sample. Once the signals from the structure are collected, sensor data are transmitted through a ZigBee solution to the processing unit.
文摘Rail defects can pose significant safety risks in railway operations, raising the need for effective detection methods. Acoustic Emission (AE) technology has shown promise for identifying and monitoring these defects, and this study evaluates an advanced on-vehicle AE detection approach using bone-conduct sensors—a solution to improve upon previous AE methods of using on-rail sensor installations, which required extensive, costly on-rail sensor networks with limited effectiveness. In response to these challenges, the study specifically explored bone-conduct sensors mounted directly on the vehicle rather than rails by evaluating AE signals generated by the interaction between rails and the train’s wheels while in motion. In this research, a prototype detection system was developed and tested through initial trials at the Nevada Railroad Museum using a track with pre-damaged welding defects. Further testing was conducted at the Transportation Technology Center Inc. (rebranded as MxV Rail) in Colorado, where the system’s performance was evaluated across various defect types and train speeds. The results indicated that bone-conduct sensors were insufficient for detecting AE signals when mounted on moving vehicles. These findings highlight the limitations of contact-based methods in real-world applications and indicate the need for exploring improved, non-contact approaches.
