Trend Forecast of Mine Hoist Fault with Wavelet Neural Network

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作者单位: College of Information and Engineering，Taishan Medical University，Tai'an 271016，China；School of Information Science and Technology，Qingdao University of Science and Technology，Qingdao

摘要: The wavelet neural network is used to predict the time series of key characteristic parameters about the abrad-ability of steel wire rope, time of idle motion, life of pad wear away, clearance of brake shoe, remnant oil pressure and deflection degree of brake disk for the mine hoist Then the trend of hoist fault can be forecasted from these predicted characteristic parameters. Simulations and experiments indicate that the forecasting precision can satisfy the practical requirement It is very sig...更多; The wavelet neural network is used to predict the time series of key characteristic parameters about the abrad-ability of steel wire rope, time of idle motion, life of pad wear away, clearance of brake shoe, remnant oil pressure and deflection degree of brake disk for the mine hoist Then the trend of hoist fault can be forecasted from these predicted characteristic parameters. Simulations and experiments indicate that the forecasting precision can satisfy the practical requirement It is very significant to ensure the secure and efficient run of mine hoist.收起

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