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Breakdown maintenance and fault analysis method for complicated equipment

A fault analysis method and technology of fault analysis, applied in the direction of neural learning methods, instruments, biological neural network models, etc., can solve problems such as greater influence on the accuracy of fault trees, fault knowledge expression, and complex fault relationships

Inactive Publication Date: 2012-06-13
HUAZHONG UNIV OF SCI & TECH
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Problems solved by technology

[0003] Few people have studied the fault diagnosis technology in post-event maintenance occasions. Fault tree analysis (FTA) and failure mode and effect analysis (FEMA) are the classic analysis methods. However, major equipment is generally a highly complex equipment that integrates mechanics, electricity, and hydraulics. , its faults are affected by its own design, assembly, environment and operation, etc., and the relationship between faults is intricate. FTA or FMEA can no longer fully express its fault knowledge. In terms of fault analysis, FMEA focuses on fault modes and their hazards The description of degree etc. is difficult to be used for diagnostic reasoning, while FTA focuses on weak link research and is greatly affected by the accuracy of fault tree when used for diagnosis

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  • Breakdown maintenance and fault analysis method for complicated equipment

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Embodiment Construction

[0037] The present invention will be described in further detail below in conjunction with the accompanying drawings.

[0038] as attached Figure 1 Shown, the present invention comprises the following steps:

[0039] Step 1, fault classification.

[0040] According to the different fault objects, the faults are divided into: (a) structural faults, which have obvious fault objects, and must be eradicated by self-replacement or maintenance; (b) functional faults, which can be eliminated by repairing or adjusting other objects. Troubleshooting; (c) external faults, including process, environment, human operation and other fault states that do not meet the equipment requirements.

[0041] According to the degree of visibility, faults are divided into: (a) symptomatic faults, also known as fault symptoms or fault phenomena, that is, faults that can be detected by facial features or conventional measuring instruments, which are the appearance of faults deteriorating to a certain ...

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Abstract

The invention discloses a breakdown maintenance and fault analysis method for complicated equipment. The method specifically comprises the following steps: (1) classifying faults into different types according to objects or visual degree; (2) building a knowledge base including a specification base and a history base; (3) configuring the analysis method according to the fault phenomenon; (4) generating 'fault links' and 'fault diagrams'; (5) utilizing fault analysis algorithm to conduct fault analysis according to the divided diagnosis objects; (6) and fusing the causes of various fault analysis algorithms. The fault analysis method provided by the invention is suitable for different fault cases, the 'fault links' are built from the specification base according to the fault phenomenon andthe configuration condition, and a plurality of fault links can form the 'fault diagram' of composite faults; and different fault phenomenon sets are respectively diagnosed and analyzed by adopting different analysis methods according to the configuration condition, so as to obtain the corresponding fault causes and the probability of faults and provide a solution for breakdown diagnosis of important equipment.

Description

technical field [0001] The invention belongs to the field of equipment fault diagnosis and maintenance, and specifically relates to a fault analysis method for complex equipment after-the-fact maintenance occasions, which can organize complex fault knowledge, analyze fault causes, and provide decision-making for on-site maintenance. Background technique [0002] Major and complex equipment has played an increasingly important role, and its downtime will seriously affect the production efficiency of the enterprise and bring huge losses to the enterprise. Therefore, related technologies such as condition monitoring, fault diagnosis, reliability analysis, life prediction, and preventive maintenance have become research hotspots for complex equipment. However, due to many contradictions between high acquisition accuracy requirements and harsh working environment, intensive data integration requirements and low informatization, high cost and low effectiveness, these intelligent d...

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Application Information

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IPC IPC(8): G06K9/62G06N3/08
Inventor 王远航吴军邵新宇邓超熊尧
Owner HUAZHONG UNIV OF SCI & TECH
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