Fault diagnosis method and system for heading machine hydraulic system

A hydraulic system and fault diagnosis technology, which is applied in neural learning methods, testing of mechanical components, testing of machine/structural components, etc., can solve problems such as inconvenient human-computer interaction, low accuracy of fault diagnosis, and imperfect knowledge base, etc., to achieve Easy to expand, good human-computer interaction interface, and the effect of improving accuracy

Inactive Publication Date: 2015-07-01
CHANGSHU RES INSTITUE OF NANJING UNIV OF SCI & TECH
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  • Abstract
  • Description
  • Claims
  • Application Information

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Problems solved by technology

[0007] The present invention solves the deficiencies of the prior art, overcomes the shortcomings of low fault diagnosis accuracy, inconvenient h

Method used

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  • Fault diagnosis method and system for heading machine hydraulic system
  • Fault diagnosis method and system for heading machine hydraulic system
  • Fault diagnosis method and system for heading machine hydraulic system

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Experimental program
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Embodiment 1

[0027] There are many physical parameters caused by a certain fault. To diagnose the fault of the hydraulic system, the parameters reflecting the state of the hydraulic system must be extracted first. When the hydraulic system fails, these parameters will change directly or indirectly. Therefore, by analyzing the By analyzing the changes of these parameters, we can diagnose the failure of the system. If the characteristic parameters are not selected properly, it will increase the difficulty of diagnosis. Too many choices may generate redundant information and increase the cost of collection. Too few will reduce the accuracy of diagnosis and may even cause misjudgment. The diagnosis of faults plays a vital role.

[0028] A fault diagnosis method for a hydraulic system of a roadheader includes the following steps:

[0029] Step (1), firstly extract the parameters that reflect the state of the hydraulic system. The extracted parameters of the state of the hydraulic system includ...

Embodiment 2

[0035] Such as figure 1 , is the basic structure of the knowledge base management system of the roadheader hydraulic fault diagnosis system of the present invention. The overall structure of the designed fault diagnosis KBMS is divided into three layers. Among them, the surface layer functions of the knowledge base are directly oriented to the database to implement operations such as adding, querying, modifying, and deleting knowledge in the database. The inspection management of the knowledge base layer acts as a link between the functions of the two layers; the knowledge base management layer is application-oriented and directly calls the functions of the knowledge base layer for various operations of the knowledge base management. In practical applications, the knowledge base is divided into three layers of call forms, that is, the functions of each layer are set to complete different functions

[0036] Such as figure 2 , is the fuzzy neural network fault diagnosis mode...

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Abstract

The invention discloses a fault diagnosis method and system for a heading machine hydraulic system. The method includes: building a fault diagnosis system framework through a fuzzy neural network method, building subsystems such as a parameter monitoring module, a fault knowledge base management maintenance module and an intelligent diagnosis reasoning module, taking a knowledge base of the heading machine hydraulic system as the basis and combining each module into a whole organically; building the overall structure of the knowledge base which comprises a fault type base, a fault knowledge base and a fault rule base according to the expert system design principle, introducing a relational data base into a knowledge base system, using the ACCESS as the database platform, building corresponding data sheets, realizing the functions of the expert system and managing and maintaining the knowledge base through fully utilization of the database technology; and building a fuzzy neural network fault diagnosis mode, reducing the network instability through the adaptive learning rate method and the additional momentum method, and training and simulating the fuzzy neural network model through actual data. Therefore, the fault diagnosis method and system for the heading machine hydraulic system can accurately reflect the faults of the heading machine hydraulic system.

Description

technical field [0001] The invention relates to the field of equipment fault diagnosis, in particular to a fault diagnosis method system for a hydraulic system of a roadheader. Background technique [0002] The roadheader is mainly used to dig dangerous roads, and is widely used in road engineering, urban underground transportation, mine excavation and other construction operations. Compared with the drilling and blasting method, it has the advantages of reducing work intensity, improving construction efficiency, and providing better excavation. effect, increase construction safety and other characteristics. The hydraulic system is widely used in metallurgical industry, engineering equipment, mechanical machine tools, aviation, etc. Aerospace, weaponry, transportation and other equipment have become an indispensable part of these equipment. With the development of equipment in the direction of high power and high precision, the hydraulic system is required to develop along...

Claims

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Application Information

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IPC IPC(8): G06F17/30G06N3/08G01M13/00
Inventor 孙瑜张洪瑾滕诣迪
Owner CHANGSHU RES INSTITUE OF NANJING UNIV OF SCI & TECH
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