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Group maintenance decision-making method based on system-level life information

A decision-making method, a system-level technology, used in data processing applications, forecasting, instrumentation, etc.

Active Publication Date: 2022-04-19
BEIHANG UNIV
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

In addition, for long-life and high-reliability products, their failures are due to degradation failures such as aging and wear, while traditional maintenance models are often based on failure rate functions.

Method used

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  • Group maintenance decision-making method based on system-level life information
  • Group maintenance decision-making method based on system-level life information
  • Group maintenance decision-making method based on system-level life information

Examples

Experimental program
Comparison scheme
Effect test

Embodiment example

[0053] (1) Overview of simulation examples

[0054] Suppose a product G has image 3 The functional structures shown are related, in which subsystems C and F are connected in parallel, and are respectively composed of A, B, D, and E in series. The product has two mission downtimes at 552h and 840h, that is, two maintenance opportunities, and is decommissioned after the working time reaches 1100h. The failure modes and associated costs of components A, B, E, and D are shown in the table below.

[0055] Table 1 Failure modes and related costs of each component

[0056]

[0057] (2) Model construction

[0058] According to the system reliability block diagram, the relationship between components can be established. It can be known that components A, B, D, and E are root nodes, subsystem CF is an intermediate node, and system G is a leaf node. Based on the series-parallel relationship between components and expert experience, the BN model can be established as Figure 4 sh...

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Abstract

The invention discloses a group maintenance decision-making method based on system-level life information, in order to solve the problem of ignoring system-level reliability when using component-level information for group maintenance decision-making. First, use the degradation data of each component to perform component-level life prediction and system-level life prediction to obtain the system reliability evaluation function; secondly, use the component-level life prediction information to calculate the preventive maintenance time of each component; then, use the system task profile and component The optimal preventive maintenance time is grouped, and the related costs are calculated; finally, the optimal group maintenance strategy at the system level is obtained by using the multi-attribute value theory in multi-objective optimization, with cost and system reliability as the goals. In the present invention, while considering the group maintenance cost, the life prediction information at the system level can be considered in combination, so as to ensure the high reliability and task success of the system. The invention is suitable for group maintenance decision-making of products with complex structures and high reliability requirements.

Description

technical field [0001] The invention relates to a grouped maintenance decision-making method based on life prediction model, maintenance grouping and multi-objective planning for degradation data of multi-level systems with complex structures, and belongs to the technical field of maintenance decision-making. Background technique [0002] In order to ensure that the system completes a series of tasks within the specified time, certain maintenance and repair work is required to ensure system safety and task success, and reduce losses caused by failures. Therefore, it is a research hotspot in recent years to carry out an appropriate maintenance strategy to ensure that the system has high performance and low cost during its lifetime. For system-level maintenance strategies, most studies tend to tend to opportunity maintenance and group maintenance. Many techniques, such as stochastic processes, optimization algorithms, model theory, etc., are widely used and discussed in the s...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06Q10/04G06Q10/00
CPCG06Q10/04G06Q10/20
Inventor 王晓红王立志张源孙玉胜郭洪洲
Owner BEIHANG UNIV