Dynamic Reliability Evaluation Approach for Electromechanical Systems Based on Probabilistic Model Checking

被引：0

作者：

Hou Y. ^{[1
]}

Yang P. ^{[1
]}

Xu K. ^{[1
]}

Liu Q. ^{[2
]}

Fan J. ^{[2
]}

机构：

[1] School of Mechanical Engineering, Xi'an Jiaotong University, Xi'an

[2] No.1 Center of Measuring and Physical-chemical Performance Testing, Northwestern Industrial Group Co., Xi'an

来源：

Zhongguo Jixie Gongcheng/China Mechanical Engineering | 2019年 / 30卷 / 05期

关键词：

Dynamic reliability; Electromechanical system; Probabilistic model checking; Reliability evaluation;

D O I：

10.3969/j.issn.1004-132X.2019.05.007

中图分类号：

学科分类号：

摘要：

To overcome the shortcomings of the traditional dynamic reliability analysis methods, a dynamic reliability evaluation approach for electromechanical systems was proposed based on probabilistic model checking. The concept of probabilistic model checking and a probabilistic model checker PRISM were introduced. State transitions of system components were represented using formal modeling language provided by the model checker, from which the formal model of electromechanical systems was built. Reliability indices were described by means of continuous stochastic logic formulas to establish the formal specifications of the reliability indices. Based on the formal model and formal specifications, reliability indices were computed automatically with the probabilistic model checker, and therefore dynamic reliability evaluation was achieved based on probabilistic model checking. The approach presented herein simplifies the modeling processes and improves the efficiency of dynamic reliability analysis for electromechanical systems. © 2019, China Mechanical Engineering Magazine Office. All right reserved.

引用

页码：549 / 553

页数：4

共 15 条

[1] Distefano S., Puliafito A., Reliability and Availability Analysis of Dependent-dynamic Systems with DRBDs, Reliability Engineering & System Safety, 94, 9, pp. 1381-1393, (2009)
[2] Tao J., Wang Y., Chen X., A Survey of the Complex Large System Dynamic Reliability and Dynamic Probabilistic Risk Assessment, Acta Armanentarii, 30, 11, pp. 1533-1539, (2009)
[3] Zhang Z., Guo Q., Huang L., Et al., Analysis of Weapon Systems Subject to Correlative Cause Failures Based on Markov Process, Fire Control & Command Control, 37, 7, pp. 117-119, (2012)
[4] Bouissou M., Bon J.L., A New Formalism that Combines Advantages of Fault-trees and Markov Models: Boolean Logic Driven Markov Processes, Reliability Engineering & System Safety, 82, 2, pp. 149-163, (2003)
[5] Chiacchio F., Compagno L., D'Urso D., Et al., An Open-source Application to Model and Solve Dynamic Fault Tree of Real Industrial Systems, IEEE International Conference on Software, pp. 1-8, (2012)
[6] Montani S., Portinale L., Bobbio A., Et al., A Tool for Automatically Translating Dynamic Fault Trees into Dynamic Bayesian Networks, IEEE Reliability & Maintainability Symposium, pp. 434-441, (2006)
[7] Shi J., Wang S., Wang K., GSPN-based Reliability Model of Aircraft Hydraulic Actuator System, Acta Aeronautica et Astronautica Sinica, 32, 5, pp. 920-933, (2011)
[8] Clarke E.M., Grumberg O., Peled D.A., Model Checking, 2000
[9] Lin H., Zhang W., Model Checking: Theories, Techniques and Applications, Acta Electronica Sinica, 30, 12, pp. 1907-1912, (2002)
[10] Jia Y., Li Z., Xing J., Et al., Advances in the Component Verification Technology Based on Model Checking, Journal of Computer Research and Development, 48, 6, pp. 913-922, (2011)

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