Condition monitoring of track geometry from sensors mounted on an in-service vehicle offers continual monitoring of track geometry that can aid track maintenance strategies. Mounting and maintaining a full track geometry recording system on an in-service vehicle is an expensive proposition as the commonly used optical sensors are difficult to keep working in the dirty railway environment. A simpler and more cost-effective alternative is to estimate track geometry using a small number of robust sensors such as accelerometers and rate gyroscopes, from which a worthwhile proportion of geometric quality measures and specific irregularities can be identified. This paper describes the theory and practical results of using a bogie-mounted pitchrate gyro to obtain mean vertical alignment, conditional on the secondary vertical damper geometry. Left and right axlebox-mounted accelerometers can be added to provide short wavelength irregularity, if required. Results from trials on Tyne and Wear Metro vehicles and on a Class 175 mainline vehicle demonstrate effective vertical irregularity monitoring, in particular the ability to monitor vertical irregularity over a wide range of vehicle speeds down to about 1 ms-1, where vertically sensing accelerometers combined with displacement transducers are unable to function correctly.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
customersupport@researchsolutions.com
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.