System Reliability Analysis And Optimal Design Based On Survival Signature Theory

System reliability is an important part of reliability theory.The overall reliability can be obtained by studying the structural relationship between units and the whole system and also between each units.To analyze and optimize the reliability of complex systems more accurately and efficiently is one of the most important issues in the field of reliability.In this paper,a new tool for system reliability analysis,survival signature,is discussed.Reliability analysis,simulation and optimization are studied by this method.The specific work is as follows:Using survival signature to analyze and simulate the reliability of the actual system:As example of traction drive system of CRH3 high speed train:The corresponding life distribution types and distribution parameters are fitted through the failure data of the existing system components.According to survival signature,the reliability of the system is expressed by full probability formula,and the reliability curve based on the running distance is obtained.Monte Carlo simulation of reliability of complex power supply and distribution system based on survival signature:Fewer samples are used to simulate the failure state of each component in the system in a certain period of time.The survive signature in each period is used to represent the reliability of the system under this condition.The time-based break-line graph of reliability is obtained.After repeated tests,the smooth reliability curve is obtained.A high efficiency reliability sensitivity simulation method based on survival signature is presented.By using the mathematical characteristics of survival signature,the importance of each component is obtained in the equivalent system,and the structural analysis process of the complex system is simplified.The reliability sensitivity is then expressed in the form of component reliability through the Jacobian partial derivative matrix of the component life distribution function.In the Monte Carlo simulation of component reliability,the subset simulation method is adopted to reduce sampling times and further improve the computational efficiency.Applying the presented method to a complex bridge system,the ideal result is obtained,which verifies the efficiency and accuracy of the method.Using survival signature to solve reliability redundancy allocation problems:Halton sequence is introduced into artificial bee colony algorithm to improve the uniformity of initial population;The arithmetic crossover operation is added in the iteration process to further improve the population quality.The survival signature is used to simplify the optimization model,reduce the dimension of variables,and greatly improve the calculation efficiency.At the same time,the target redundancy is optimized two times to further improve the reliability of the system.The improved artificial bee colony algorithm and random fractal search are used to verify the numerical examples.Introducing components' swapping in system reliability analysis:The substitution system structure is introduced through the effective description of survival signature,and the optimal substitution strategy is introduced to the optimized redundant system,so that the system achieves the original reliability and reduces the existing redundancy at the same time.By establishing the cost function of component swapping,the reliability allocation model with component swapping is constructed.The reliability of components and the mode of component replacement with the highest reliability of the system are calculated by optimization algorithm.Compared with the direct reliability redundancy allocation,the performance-price ratio is higher.