Remote Status Monitoring And Intelligent Fault Diagnosis System For Mine Hoist

Mine hoist is one of the most important key mechanical and electrical equipments, which often referred to as the "throat of the mine". It’s safe and reliable operation not only affects the entire production capacity of the mine, but also related to the life and safety of the underground staff. In recent years, many mining enterprises occurrence many major accidents are mostly caused by the mine hoist fault, so this paper studies the mine hoist condition monitoring and intelligent fault diagnosis system has important practical significance.This paper analyzed the research trends for the status monitoring and fault diagnosis home and abroad, then studied the monitoring and intelligent fault diagnosis system based the GPRS wireless communication technology for mine hoisting machine,which is put forward on the basis of the common faults of the mine hoist,while using the bayesian network to carried out the simulation of the fault diagnosis and maintenance decision-making for mine hoisting, proving the validity and rationality of the bayesian network theory for the undeterministic fault diagnosis in the mine hoist equipment. This paper mainly about:(1)By analyzing current remote monitoring technique and fault diagnosis for mine hoist home and abroad, compared to the wireless communication technology with the actual applications, then proposed mine hoist remote status monitoring and intelligent fault diagnosis system based on GPRS technology.(2)This paper described the system components and working principle of the haulage inclined shaft for the mine hoist, then based the common faults of mine determine the monitoring content and monitoring method, and the necessary hardware and software of the monitoring system selected and designed, then build hardware and software platform of monitoring system.(3)The monitoring and diagnoses software with two levels which are real-time monitoring diagnoses on-site and remote monitoring diagnoses in monitoring center. Respectively the GPRS program of the programmable logic controllers, the IPC software configuration and signal processing software design on-site, software configuration and diagnoses software design in remote monitoring center are introduced, and finally summarized system run testing.(4)Finally, the Bayesian network theory, its foundation of probabilistic inference and Bayesian network inference and construction method are introduced, mine hoist fault diagnosis and maintenance decision network model was simulated by the GeNIe development platform.The innovation lies of this subject is not only to fulfill the real-time requirement but also to achieve remote monitoring and fault diagnosis of the mine hoist; Bayesian network for fault diagnosis and maintenance decisions reasoning can be very effective to solve the problem of uncertainty fault and fault cascade. Fault diagnosis is conducive to launch the emerged but subtle fault by monitoring software to do early prevention; from the fault derive the reasons for the fault to find the first point of fault, then to do the purpose maintenance decisions. Appling of remote condition monitoring and intelligent fault diagnosis system on mine hoist can achieve the mine hoist modern management, and effectively improve the safe and reliable operation level of the mine hoist system.