Influence and prediction of hobbing process parameters and vibration on tooth profile deviation
With the concept of green manufacturing being strongly advocated,new energy vehicles are listed as one of the top ten key development areas in China,and high-speed gears are the core basic components of the drive system of new energy vehicles.How to improve the machining accuracy and efficiency of high-speed gears and reduce the energy consumption has become one of the problems that plague the manufacturing industry.High-speed dry cutting hobbing is widely used because it does not need cutting fluid,has higher machining efficiency and is more friendly to the environment.Currently,the selection of hobbing cutting parameters in most manufacturing enterprises primarily depends on experience and process manuals.Inefficient and unreasonable selection of cutting parameters will often cause strong vibration of machine tools,which will lead to lower machining accuracy of workpieces and worse gear transmission performance.At present,there has been extensive research on how to optimize hobbing process parameters and predict machining accuracy at home and abroad,but there are still the following obvious defects.First,for the optimization of cutting parameters,the existing research often ignores the influence of vibration,and fails to consider the specific influence mechanism of machine tool vibration on gear machining accuracy while optimizing cutting parameters.Therefore,it is necessary to consider the vibration characteristics of machine tools and its influence mechanism on machining accuracy under different cutting parameters.In addition,for the prediction of gear machining accuracy,most of the existing studies only predict gear machining accuracy through process parameters,which fails to consider the constraints of vibration and other factors during machining,or only takes vibration signals as the input of the prediction model,and fails to comprehensively analyze the vibration influence mechanism under the comprehensive action of multiple parameters.These factors will restrict the accuracy of the prediction results.Aiming to improve the reliability of hobbing process parameters selection and reduce the prediction error of gear machining accuracy,this paper establishes a hobbing profile deviation prediction model with gear cutting parameters and vibration signals as inputs.First,a hobbing experiment platform was built,and the spindle speed and feed rate were taken as the main factors of this cutting experiment,and a two-factor and five-level orthogonal experiment scheme was designed,and the vibration signal of the machine tool spindle in the Z-axis direction was collected through three acceleration sensors and Donghua dynamic signal testing system.The wavelet threshold method is applied to remove the high-frequency noise components of the original vibration signal,which provides a more reliable data set for the subsequent vibration analysis.Second,the orthogonal experiments of hobbing under different cutting parameters are completed,and the tooth profile deviation of the machined gear is measured.By the analysis of range and variance,the significant order of the influencing factors of tooth profile deviation and vibration signal is determined.Then,the influence law of process parameters and root mean square of machine tool vibration signal on tooth profile deviation is analyzed,and the good correlation between root mean square of vibration signal and tooth profile deviation is determined by data fitting method.Finally,based on the previous article,a prediction model with process parameters and vibration signal as input and gear hobbing tooth profile deviation as output is established based on GA-Elman neural network.The results show that the prediction error is less than 4%,and the correlation of the model is about 0.85,which effectively guides gear hobbing process.
hobbing processprocessing parametervibratetooth profile deviationprediction model
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