The Software Development Of Condition Monitoring And Mechanical Fault Diagnosis Warning For The Main Ventilator Motor

The content of this paper is an important part of " Mine ventilation and power system security condition monitoring and fault diagnosis of early warning systems" (No:2007BAK29B05). It is based on the current situation that the continuously happened fault in the mine main ventilator motor mechanical fault, poor monitoring reliability and the imperfect diagnostic function.The mine main ventilator, forcing stable air circulation through the mechanical power, reducing the aggregation of gas and dust, is one of key equipments for ensuring the production safety of mine. Because of its long running, complex working condition and bad running environment, the main ventilator fault continuously happen. Mine must be installed with two ventilators, in consideration of its important position, to ensure the safety. One of them is used as a reserve, and use periodical maintenance. This greatly reduces the failure rate of main ventilator, but at the same time, increases the mine production investment, causes the equipment excess maintenance, and impacts the production efficiency and safety. Therefore, the mechanical state monitoring and evaluation for main ventilator core component-motor, can greatly reduce maintenance costs, prevent sudden fault, eliminate threat from hidden trouble, and have important practical significance for production safety of mine.This paper throughly learn signal analysis and intelligent diagnosis technology through analyzing mine main ventilator motor common mechanical fault and fault mechanism, and summarize fault characteristic data through a large number fault simulation experiment, aimed at developing a set of system which has perfect monitoring function, accurate fault diagnosis ability and high reliability to provide effective condition maintenance guidance for main ventilator reliable operation. The main research contents are as follows:Combining on-site maintenance experience and related literature, this paper studies main ventilator motor common mechanical fault mechanism, establishes fault space, determines target parameters which can reflect overall main ventilator motor mechanical condition and confirms condition monitoring and fault diagnosis warning system overall framework.This paper configures hardware collection circuit of every parameter for monitoring system, selects suitable sensors, and finishes field experiment, including voltage and current collection equipment, vibration collection equipment and rotational speed and torque collection equipment.Through the study of signal processing technology and intelligent diagnosis technology, combining with this system's diagnosis warning requirements, This paper determines main ventilator motor mechanical fault diagnosis warning scheme:main ventilator motor mechanical fault diagnosis warning is implemented through using frequency domain analysis and wavelet packet analysis technology, extracting fault characteristic parameters of stator current signal and key parts vibration signal, applying BP neural network as fault diagnosis classifier and adopting pattern recognition method.According to the overall requirements of diagnosis warning system, combining with hardware characteristics, this paper determines software and technical scheme overall structure:using LabVIEW as software development platform, this paper designs state parameters collection programs, signals pretreatment programs, spectra analysis programs, signal storage database programs, man-machine interface programs, wavelet packet analysis programs, fault diagnosis warning programs which combines frequency domain analysis and BP neural network, etc.Based on motor fault reasons, combining with process technology, this paper manufactures related mechanical fault motor, puts up motor fault experimental platform, installs corresponding sensor and collection equipment, collects target parameters, analyses experimental data, summarizes characteristic quantities of various kinds mechanical fault.This paper constructs a network platform in the laboratory, does debugging and experiment for motor condition monitoring system hardware and software, and system joint adjusting; installs complete set of equipment in site, does industrial test, debugs hardware and software of the whole system, optimizes upper computer software. The field tests suggest that this system parameter monitoring is accurate real-time, diagnosis warning result is reliable; the whole system has stable operation and achieves all the design targets.