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Cluster system preventive maintenance method based on deep reinforcement learning

A swarm system and reinforcement learning technology, applied in neural learning methods, instruments, biological neural network models, etc., can solve the problems of non-deterministic polynomial difficulties, insufficient consideration of large-scale swarm characteristics and degenerate state characteristics of swarm systems, etc.

Pending Publication Date: 2021-11-19
BEIHANG UNIV
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Problems solved by technology

[0005] The purpose of the present invention is to provide a new type of preventive maintenance method for the cluster system in the long-term operation process, aiming to solve the problem that the traditional preventive maintenance method does not fully consider the large-scale cluster characteristics and degradation state characteristics of each component unit of the cluster system, and the nondeterministic polynomial-hard character of the problem as a whole

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  • Cluster system preventive maintenance method based on deep reinforcement learning
  • Cluster system preventive maintenance method based on deep reinforcement learning
  • Cluster system preventive maintenance method based on deep reinforcement learning

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[0029] In order to gain a clearer understanding of the technical solutions, features and advantages of the present invention, a detailed description will be given below in conjunction with the accompanying drawings.

[0030] The invention provides a novel preventive maintenance method, which can be used to solve the "single system-unit" cluster preventive maintenance problem of the cluster system during long-term operation, and solves the problem of large-scale maintenance without fully considering the components of the cluster system Cluster and degenerate state features, and nondeterministic polynomially hard features for the problem as a whole.

[0031] Overall structure of the present invention, see figure 1 shown. Its specific implementation steps are:

[0032] Step 1: Description of the degradation state of the cluster system.

[0033] The preventive maintenance strategy of the cluster system is regarded as a multi-unit cluster maintenance decision-making problem. Fi...

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Abstract

The invention discloses a cluster system preventive maintenance method based on deep reinforcement learning, and solves the preventive maintenance problem of a cluster system in a long-term operation process. The method comprises the following steps: 1, establishing a residual life state matrix of a single system-unit cluster of a cluster system according to a degradation state; 2, evaluating the reliability level of the cluster system based on the residual life state matrix of the single system-unit cluster of the cluster system; 3, designing a neural network to predict the prior maintenance probability and the prior maintenance strategy value of the single system-unit cluster of the cluster system; 4, constructing a preventive maintenance strategy solution algorithm architecture, traversing a preventive maintenance strategy solution space, and selecting a series of optimal maintenance actions; 5, calculating the reliability of the cluster system based on the change of the residual life state of the cluster, and then checking the recovery degree of the cluster system; 6, generating a complete preventive strategy by the optimal maintenance actions stored in the preventive maintenance strategy solving process.

Description

[0001] Technical field [0002] The present invention provides a cluster system preventive maintenance method based on deep reinforcement learning, and in particular relates to a multi-unit cluster maintenance that considers the degradation characteristics of each component unit of the cluster system and realizes solving the cluster system preventive maintenance problem based on a deep reinforcement learning algorithm. The decision-making method belongs to the field of maintainability engineering. Background technique [0003] Preventive maintenance refers to taking maintenance measures in advance to prevent failures in consideration of the degradation state of the product. At present, condition-based preventive maintenance is gradually replacing time-based preventive maintenance. The cluster system is composed of multiple single systems and has high fault tolerance. It is widely used in military and civilian fields. In recent years, more attention has been paid to the preven...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06Q10/00G06N3/04G06N3/08
CPCG06Q10/20G06N3/08G06N3/045
Inventor 冯强吴其隆任羿王自力孙博杨德真
Owner BEIHANG UNIV
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