Monitoring Vertical Accelerations of Railway Wagon using Machine Leaning Technique
MetadataShow full item record
Wireless communications and modern machine learning techniques have jointly been applied in the recent development of vehicle health monitoring (VHM) systems. The performance of rail vehicles running on railway tracks is governed by the dynamic behaviors of railway bogies especially in the cases of lateral instability and track irregularities. In this study we have proposed a system to monitor the vertical displacements of railway wagons attached to a moving locomotive. The system uses a classical linear regression machine learning technique with real wagon body acceleration data to predict vertical displacements of vehicle body motion. The system is then able to generate precautionary signals and system status which can be used by the locomotive driver for necessary actions. This VHM system provides forward-looking decisions on track maintenance that can reduce maintenance costs and inspection requirements of railway systems
ISBN # for Set: 1-60132-072-8 (sponsors: http://www.world-academy-of-science.org/ )
Showing items related by title, author, creator and subject.
Shafiullah, G.; Thompson, Adam; Wolfs, Peter; Ali, S. (2008)Wireless sensor networking (WSN) and modern machine learning techniques have encouraged interest in the development of vehicle monitoring systems that ensure safe and secure operations of the rail vehicle. To make an ...
Shafiullah, G.; Gyasi-Agyei, A.; Wolfs, Peter (2007)Advances in information and communications technology have enabled the adoption of wireless communication techniques in all sectors for the transmission of information in all forms between any two points. Wireless ...
Rao, Arjun (2009)With security and surveillance gaining paramount importance in recent years, it has become important to reliably automate some surveillance tasks for monitoring crowded areas. The need to automate this process also supports ...