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Dynamic Reliability Model for Airborne Systems Based on Stochastic Petri Net
- Source :
- Xibei Gongye Daxue Xuebao, Vol 38, Iss 4, Pp 846-854 (2020)
- Publication Year :
- 2020
- Publisher :
- EDP Sciences, 2020.
-
Abstract
- The reliability of the airborne systems have a significant influence on the safety of aircraft. The modern airborne systems have a high degree of automation and integration, which lead to obvious dynamic failure characteristics. Namely, system failure is not only dependent on the combination of units' failures but also related to their sequence. A dynamic reliability method for modeling airborne systems is proposed based on the stochastic Petri nets. Stochastic Petri nets are applied in reliability modeling for typical dynamic structures including warm standby, cold standby and load sharing, which are widely used in airborne systems. In this way, the dynamic (time-dependent) failure behaviors of the airborne system can be represented. In terms of the stochastic Petri net based reliability model, a reliability analysis method based on Monte Carlo simulation is proposed by generating system life samples for system reliability parameter calculation. Finally, an electrical power system is used as a case to illustrate the application and effectiveness of the present approaches. The results show that the difference by using the present method and the analytical method is below 2×10-7, which can be neglected in practice.
- Subjects :
- 0209 industrial biotechnology
stochastic petri nets
dynamic reliability modeling
Computer science
Monte Carlo method
ComputerApplications_COMPUTERSINOTHERSYSTEMS
System safety
02 engineering and technology
Dynamic reliability
020901 industrial engineering & automation
0203 mechanical engineering
Reliability (statistics)
Motor vehicles. Aeronautics. Astronautics
020301 aerospace & aeronautics
Sequence
business.industry
General Engineering
monte carlo simulation
TL1-4050
Automation
Reliability engineering
airborne systems
Stochastic Petri net
system safety
Electric power
business
Subjects
Details
- ISSN :
- 26097125 and 10002758
- Volume :
- 38
- Database :
- OpenAIRE
- Journal :
- Xibei Gongye Daxue Xuebao/Journal of Northwestern Polytechnical University
- Accession number :
- edsair.doi.dedup.....f67fe727f960ace6d650b088158023de
- Full Text :
- https://doi.org/10.1051/jnwpu/20203840846