Optimal selective maintenance optimization method and device for multi-stage task multi-state system

Abstract

The invention discloses an optimal selective maintenance optimization method and device for a multi-stage task multi-state system. The method comprises the steps that a component layer performance set, a state transition rate matrix of each component and a multi-stage task sequence in the system are given; according to the state transition rate matrix of each component, probability distribution of the component layer performance set is calculated; according to the component layer performance set and the probability distribution of the component layer performance set, a system layer performance set and probability distribution of the system layer performance set are calculated; according to the performance state of each component, the system layer performance set, the probability distribution of the system layer performance set and the multi-stage task sequence, system reliability is calculated; according to the residual number of replacement components, a maintenance action feasible set is calculated; the system task reliability is taken as an indicator function, and the maintenance action feasible set is taken as constraint conditions; according to the multi-stage task sequence, the performance state of each component and the residual number of the replacement components, a maintenance optimization model is built, and an optimal strategy table is solved.

Description

technical field [0001] The invention relates to the field of equipment maintenance optimization management, and more specifically, the invention relates to a method and device for optimal selective maintenance optimization of a multi-stage task and multi-state system. Background technique [0002] When the degradation degree of the system during use is reflected in its performance level (such as output power, power generation, etc.), it often exhibits multi-state characteristics. Lisnianski and Levitin called this system a multi-state system. In recent years, research on selective maintenance optimization methods for multi-state systems has gradually attracted attention, which mainly solves the problem of which components to select for maintenance when maintenance resources such as spare parts are limited. [0003] Maintenance is to restore the performance of the system so that it can meet the subsequent mission requirements. However, due to the limitations of task requirem...

AI Technical Summary

Problems solved by technology

However, due to the limitations of task requirements and work locations, maintenance activities can usually only be carried out at specific times. For example, the generator sets of a power station are only inspected every Sunday morning.

Recently, Liu and Huang considered the selective maintenance strategy of selecting some components for maintenance when maintenance resources are limited, but only considered single-stage tasks

However, tasks are often multi-stage, and problems in any one stage will lead to the failure of the entire mission, such as spacecraft launch, ocean-going ships, hospital power supply, machining, etc.

In the case of multi-stage tasks, the optimization method under a single-stage task can only obtain a local optimum, which may cause excessive use of resources and affect the operation of subsequent multiple task stages

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