Based On The Improved Second Generation Wavelets Mine Ventilator Fault Diagnosis

As we all know, as the important task of coal mine production safety, mine ventilation and mine lungs "said. For underground transportation of fresh air to dilute and exhaust gases such as CO, H2S, NH3, Downhole face the required amount of wind, humidity and temperature adjustment, improve the production conditions of the underground working place to ensure the safe production of underground improve production efficiency. Therefore, the normal safe operation of the coal mine ventilator obviously coal mine ventilator fault diagnosis naturally become the focus of attention of the coal technology management. Completed the following major tasks in this article:First, the article describes the the mine fan structure, characteristics, classification, and common failure. The typical fault its characteristics according to the fan leads to the principle of fault diagnosis. Describes the future development trend of fault diagnosis of mine ventilator fault diagnosis. A vibration signal of the ventilator as a parameter analysis, briefly the overall design of the monitoring system of ventilation and the corresponding part of the function. In addition, the introduction of virtual instrument technology development and its virtual instrument characteristics on the basis of the composition principle leads to the LabVIEW software development platform.Secondly, the paper elaborated the traditional wavelet transform, the second generation wavelet transform redundant fundamentals of the structure of the second generation of the second generation wavelet transform and adaptive redundant transform its decomposition and reconstruction process. Several different wavelet noise reduction methods, given some of the more intuitive icons and algorithmic formulas. Redundant second generation wavelet construction based on a prior forecast updated second generation wavelet transform method, and this method redundant predictor, redundant updates combine adaptive redundancy The second generation wavelet transform. Through the analysis and comparison of the simulation of the actual engineering data and multiple signal denoising final draw:adaptive redundant second generation wavelet transform noise reduction effect compared to several other methods, optimal. Which makes fault diagnosis before removing interference noise signal, in order to obtain more accurate fault diagnosis results.Finally, the narrative of the wavelet neural network, elaborated adaptive redundant second generation wavelet implemented in Lab VIEW. The powerful Lab VIEW software and wavelet neural network combination design coal mine ventilator fault diagnosis system. Given part of the functional modules of the system and its development process, Function description draw a corresponding picture of the experimental data and conclusions. Learned through trial and good vibration fault diagnosis system based on Lab VIEW software platform developed ventilator ventilator fault diagnosis. fan test field, the use of advanced virtual instrument test technology is able to meet the needs of the vibration signal testing and diagnosis, and provides a theoretical and practical basis for further ventilator fault diagnosis. Figure [47] table [8] reference [68]...