TY - JOUR
T1 - A New Evidential Reasoning-Based Method for Online Safety Assessment of Complex Systems
AU - Zhao, Fu Jun
AU - Zhou, Zhi Jie
AU - Hu, Chang Hua
AU - Chang, Lei Lei
AU - Zhou, Zhi Guo
AU - Li, Gai Ling
N1 - Funding Information:
Manuscript received April 6, 2016; accepted November 4, 2016. Date of publication December 7, 2016; date of current version May 15, 2018.The work of Z.-J. Zhou was supported in part by the National Natural Science Foundation of China (NSFC) under Grant 61370031 and Grant 61374138 and in part by the China Post-Doctoral Science Foundation under Grant 2015M570847 and Grant 2016T90938. The work of C.-H. Hu was supported by the NSFC under Grant 61573365. The work of L.-L. Chang was supported in part by the NSFC under Grant 71601180, Grant 71671186, Grant 71401167, and Grant 61403404 and in part by the Open Funding Program of Joint Laboratory of Flight Vehicle Ocean-based Measurement and Control under Grant FOM2015OF017. This paper was recommended by Associate Editor B.-F. Wu. (Corresponding author: Zhi-Jie Zhou.) F.-J. Zhao, C.-H. Hu, and L.-L. Chang are with the High-Tech Institute of Xi’an, Xi’an 710025, China (e-mail: fujunzhao@hotmail.com; hch6603@263.net; leileichang@hotmail.com).
Publisher Copyright:
© 2013 IEEE.
PY - 2018/6
Y1 - 2018/6
N2 - It is vital to online assess the safety of a complex dynamic system by taking into account the current state, degradation trend, and historical records together. This paper proposes a new safety assessment model with an online algorithm based on the evidential reasoning (ER) approach. It does not only take into account the relative importance of each safety indicator, but also consider the reliability of each indicator. To obtain the integrated safety level, multiple safety indicators are fused at first and the 'history,' 'current,' and 'future' safety states are then integrated. First, a forecasting model based on the third-order Volterra filter is proposed to predict the safety indicators' information online. Second, an adaptive weighting model is developed to automatically adjust to various conditions and track the characteristics of the dynamic system, and the reliability of each indicator is considered to diminish the influence of inherent disturbance and/or noise. Finally, a safety assessment aggregation scheme based on the ER approach is presented to fuse the history, current, and future safety indicators to obtain the corresponding safety state, and the safety states are then fused synthetically to obtain a comprehensive safety assessment result of the complex dynamic system. A numerical study is examined to demonstrate the implementation and effectiveness. Moreover, a practical example of the inertial navigation system is studied to show the potential applications of the proposed ER-based safety assessment method.
AB - It is vital to online assess the safety of a complex dynamic system by taking into account the current state, degradation trend, and historical records together. This paper proposes a new safety assessment model with an online algorithm based on the evidential reasoning (ER) approach. It does not only take into account the relative importance of each safety indicator, but also consider the reliability of each indicator. To obtain the integrated safety level, multiple safety indicators are fused at first and the 'history,' 'current,' and 'future' safety states are then integrated. First, a forecasting model based on the third-order Volterra filter is proposed to predict the safety indicators' information online. Second, an adaptive weighting model is developed to automatically adjust to various conditions and track the characteristics of the dynamic system, and the reliability of each indicator is considered to diminish the influence of inherent disturbance and/or noise. Finally, a safety assessment aggregation scheme based on the ER approach is presented to fuse the history, current, and future safety indicators to obtain the corresponding safety state, and the safety states are then fused synthetically to obtain a comprehensive safety assessment result of the complex dynamic system. A numerical study is examined to demonstrate the implementation and effectiveness. Moreover, a practical example of the inertial navigation system is studied to show the potential applications of the proposed ER-based safety assessment method.
KW - Evidential reasoning (ER)
KW - information fusion
KW - online safety assessment
KW - reliability
KW - volterra filter
KW - weight
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U2 - 10.1109/TSMC.2016.2630800
DO - 10.1109/TSMC.2016.2630800
M3 - Article
AN - SCOPUS:85044920480
SN - 2168-2216
VL - 48
SP - 954
EP - 966
JO - IEEE Transactions on Systems, Man, and Cybernetics: Systems
JF - IEEE Transactions on Systems, Man, and Cybernetics: Systems
IS - 6
ER -