| The maintenance work of coal mine electrical and mechanical equipment isclosely related with the field staff’s life safety. The mechanical and electricalequipment once break down will give enterprise caused heavy losses andcasualties, facing these problems we urgently need to adopt scientific technicalmeans to strengthen the quality of mechanical and electrical equipmentmaintenance work.In order to solve the above problems, this paper designed a set of electricaland mechanical equipment maintenance wireless detection system, and analysedthe detail design and implementation of each function, selected Lu’an Wuyangcoal mine Nanfeng partition as the testing location of this research. This subjectdeveloped equipment maintenance wireless detection software platform, dataacquisition, Web server, handheld mobile terminal and database support,wireless base stations to solve the supervision problems of equipmentmaintenance work quality. It collected samples evaluated by the technicalexperts in industrial field for training the neural network, validated evaluationmodel, then through the use of validated models to achieve quality unmannedevaluation. The structure of this paper include Summary, hardware, softwareand algorithm arrangement, six major aspects of the work of the entire researchprocess.(1) Analysis on electrical and mechanical equipment maintenance andequipment working state testing field; (2) Research and analysis of wireless detection system and the theory ofelectrical and mechanical equipment maintenance, according to the detectiontask requirements and comparative analysis to determined using RBF neuralnetwork;(3) The overall structure of the system, according to the functionalrequirements of the hardware,Analysis the MIMO wireless networkcommunication technology and RFID technology, the technology of thecorresponding hardware equipment selection;(4) Analyze the system software requirement, design the whole structureand function design of the main modules, and the realization of the main classesof the software.;(5) The simulation of the hardware and software system and the verificationof the algorithm.(6) Summary of the prospect of this research that it developing towards thedirection of the field of big data and cloud platform.The innovation of this research is in real-time detection of handheldterminal uploads the event log. It will accord to the event log time supervise theequipment maintenance work, and use the mobile terminal feedback data as theinput vectors of neural network for quantitative detection of the working state ofequipment, as a reference to adjust the arrangement of equipment maintenancework and supervise the whole process. Through the feedback of technicalexperts in test location we can see that the system significantly improves theequipment maintenance work quality and efficiency, has played a positive rolein ensuring the coal mine safety production. |
