Model-based and data-driven prognosis of automotive and electronic systems

Recent advances in sensor technology, remote communication and computational capabilities, and standardized hardware/software interfaces are creating a dramatic shift in the way the health of vehicles is monitored and managed. Concomitantly, there is an increased trend towards the forecasting of sys...

Full description

Saved in:
Bibliographic Details
Published in2009 IEEE International Conference on Automation Science and Engineering pp. 96 - 101
Main Authors Sankavaram, C., Pattipati, B., Kodali, A., Pattipati, K., Azam, M., Kumar, S., Pecht, M.
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.08.2009
Subjects
Automotive engineering
Availability
Communications technology
Computer interfaces
Degradation
Demand forecasting
Hardware
Remote monitoring
Technology management
Vehicles
Online AccessGet full text
ISBN1424445787
9781424445783
ISSN2161-8070
DOI10.1109/COASE.2009.5234108

Cover

More Information
Summary:Recent advances in sensor technology, remote communication and computational capabilities, and standardized hardware/software interfaces are creating a dramatic shift in the way the health of vehicles is monitored and managed. Concomitantly, there is an increased trend towards the forecasting of system degradation through a prognostic process to fulfill the needs of customers demanding high vehicle availability. Prognosis is viewed as an add-on capability to diagnosis that assesses the current health of a system and predicts its remaining life based on sensed features that capture the gradual degradation in the operation of the vehicle. This paper discusses a hybrid model-based, data-driven and knowledge-based integrated diagnosis and prognosis framework, and applies it to automotive (suspension and battery systems) and on-board electronic systems.
ISBN:1424445787
9781424445783
ISSN:2161-8070
DOI:10.1109/COASE.2009.5234108