RSL Prediction Approach for Systems with Operation State Switches

Xiao-Sheng Si (), Zheng-Xin Zhang and Chang-Hua Hu
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Xiao-Sheng Si: Xi’an Institute of High-Technology
Zheng-Xin Zhang: Xi’an Institute of High-Technology
Chang-Hua Hu: Xi’an Institute of High-Technology

Chapter Chapter 12 in Data-Driven Remaining Useful Life Prognosis Techniques, 2017, pp 337-360 from Springer

Abstract: Abstract Predicting the residual life is of significant importance in proactive maintenance, and prognostics and health management of systems (Pecht, Prognostics and health management of electronics, 2008, [1], Ye et al., Eur J Oper Res 221(2):360–367, 2012, [2], Lall et al., IEEE Trans Ind Electron 59(11):4301–4314, 2012, [3]). Many highly critical systems in military and aerospace fields, like missiles, rockets, and their associated systems, are required of long-term storage before used (Mclain and Warren, Automated reliability life data analysis of missiles in storage and flight, (1990), [4], Zhao et al., Qual Reliab Eng Int 11(1):123–127, 1995, [5], Luo et al., Research on storage life prediction method for strap-down inertial navigation system, 2012, [6]). For such systems, storage is an essential part of their lifecycles and the operating time of such systems is usually very short compared with the time in storage. Therefore, the investigation of the residual storage life (RSL) prediction is of significant importance in that it can help to plan efficient monitoring policy to extend the system’s life.

Date: 2017
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DOI: 10.1007/978-3-662-54030-5_12

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