Reliability model for failure cause analysis of a system with component load-sharing redundancy between uniform modulus

Stefanovych T., Shcherbovskykh S.
The mathematical reliability model for a system with load-sharing redundancy of the components between uniform modules is developed. The model is intended for the quantitative analysis of system failure cause. Considered system is composed of the two modules, as well as the connecting component between the modules. Each module contains the generator and the consumer. The connecting component is used for diagnostic purposes and for ensuring redundancy. If both modules are operating the connecting component is unloaded. There is the task to increase the reliability of the main module by means capacity of temporarily turn of the neighboring module generator instead the main module generator. In this state the neighboring module generator ensures both module operating and its load is doubled. Component life to failure is distributed by Weibull. Reliability of the system is mathematically formalized by dynamic fault tree. This tree defines the logical conditions of system failure and logical conditions of component load-sharing. Logical conditions of load-sharing are determined how load of the neighboring module generator and the connecting component are changed depending on the state of the main module generator. For reliability analysis state transition diagram is formed. It contains eight states and ten transitions. Non-operating states of the system are grouped into three set according to the common failure cause. Probabilistic characteristics of the system are determined by homogeneous Markov model, which is formed based on tensor analysis for splitting state space. Based on the model it is analyzed how load-sharing of the neighboring module generator after the main module generator failure is affected on system failure causes. It is shown quantitatively that with load increasing the system failure cause due to both generators failure became primary failure cause.
Friday, February 17, 2017
Friday, February 17, 2017