Design And Research On Fault Diagnosis Platform For Deep Well Hoisting System

Deep well hoisting system is a key equipment for safe production in deep coal mines.It is a large-scale complex system integrating mechanical,electrical and hydraulic integration.Its safe and reliable operation is related to the economical efficiency and reliability of the entire coal mine production,and it is even more related to the safety of miners.Therefore,the whole-state monitoring and fault diagnosis of the deep well hoisting system is an important task to ensure the safe production of coal mines.Expert system is a tool that enables users to master the overall operation characteristics of the system through man-machine interface.Therefore,it is of great significance to design and study the deep well hoisting system fault diagnosis platform which is based on expert system.The aim of this paper is a multi-rope friction hoist system fault diagnosis platform,which is based on the overall deep well hoisting system and each subsystem are designed as the research objects,the fault tree analysis method is used to analyze several important subsystems of the deep well hoisting system and a corresponding fault tree is established.The advantages and disadvantages of the fault tree analysis method are analyzed and the practical applicationrequirements are studied,a fault tree sub-node analysis method is proposed.The original overall fault tree is simplified by the idea of layer-by-layer simplification and reduced to multiple sub-fault trees.The qualitative analysis of the fault tree is avoided and the quantity of quantitative analysis is reduced.The hoisting wire rope fault tree is taken as an example,by comparing the traditional fault tree analysis method,this paper illustrates the practicability of the fault tree sub-node analysis method when dealing with complex fault trees,and lays a theoretical foundation for the establishment of expert system knowledge base.This paper is based on the principle of fault tree analysis and Microsoft SQL Server 2008 database software is used to establish the expert system knowledge base.An adaptive rule reasoning method based on CBR and RBR is proposed,the relationship model is used to quickly retrieve all the fault information which are related to the fault events.It is beneficial to improve the efficiency and precision of the known fault and reduce the diagnosis range of the unknown fault.In this paper,LabVIEW 2017 software is used to design fault diagnosis platform for the deep well hoisting expert system.The user interface,monitoring platform and fault diagnosis platform are included.The monitoring platform part mainly completes the design of hoist braking system module.LabSQL database access toolkit is used to connect fault diagnosis platform and knowledge base.Based on LabVIEW and MatLab hybrid programming technology,the fault tree sub-node analysis method is used as the basic principle to realize thedevelopment of expert system diagnostic program.The LabVIEW Report Generation Toolkit sub-VI is used to complete the generation of diagnostic reports.This can be used for storage and remote release of diagnostic results.The system debugging has been completed through simple experiments and typical failures and prove that the system support on-line real-time monitoring and diagnosis.