Abstract
Following the current trend of the automotive context, also in the motorcycle applications the employment of sensors for improving vehicle performance and passenger’s safety are becoming even more widespread. Among the most recent examples of this trend we can find the systems designed to electronically control and to on-line adapt the suspension subsystems. Of course, the correct operating of such systems is strictly related to the reliability of the information provided by the sensors involved in the related measurement and control chain. In this framework, the paper proposes an Instrument Fault Detection and Isolation (IFDI) Scheme for a motorcycle semi-active suspension system equipping a real prototype motorcycle. In particular, the proposed scheme is based on the analytical redundancy existing among the quantities measured by the involved sensors. As for the residuals generation, suitable soft sensors based on artificial neural networks are proposed to allow the fault detection and isolation.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
