利用声发射信号时频特征在线监测慢走丝线切割加工表面粗糙度
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摘要
针对慢走丝线切割加工(WEDM-LS)时因温度高、切缝窄等因素造成的加工过程难以监测的问题,利用声发射检测技术对占空比可调脉冲的慢走丝线切割加工过程进行在线监测。首先利用小波包能谱算法将AE信号分解到8个独立的频段上:分别为W1~W8,且频率依次降低;然后提取各频段上的能量特征,研究其与加工工件表面粗糙度值之间的相关性。试验结果表明:W8频段的能量与表面粗糙度值之间具有较高的相关性,该频段的能量与脉冲放电能量均随着脉冲信号占空比的增大而增大,且加工表面粗糙度值也随之逐渐增大。最后通过回归分析得到了反应材料表面粗糙度值与W8频段能量占比关系的数学预测模型,该模型的预测结果与实际测得的表面粗糙度值误差仅为3.51%。说明该模型具有较高的预测精度,可用于加工表面粗糙度的在线监测。
Aiming at the problem that monitoring of Wire Electrical Discharging Machining-Low Speed(WEDM-LS)process is difficult because of high temperature,narrow kerf and other factors,Acoustic Emission(AE)was adopted to implement on-line monitoring of WEDM-LS process with adjustable duty ratio pulse.Firstly,AE signal was decomposed into eight independent frequency bands by energy spectrum algorithm of wavelet packet,respectively being W1~ W8 and frequency reduces in sequence;then energy characteristic of all frequency bands was extracted to research the relativity between it and surface roughness value of machining work-piece.Experimental results show that energy of W8 frequency band is highly related to surface roughness value and energy of this frequency band and pulse discharge energy increase with increase of pulse duty ratio,and roughness value of machining surface increases with it gradually.Finally,a mathematical prediction model between the surface roughness value and the energy in W8 frequency band was established via regression analysis,and error was only 3.51% between prediction result and surface roughness actually measured.It can be illustrated that this model has high prediction precision for online monitoring of machining surface roughness.
Aiming at the problem that monitoring of Wire Electrical Discharging Machining-Low Speed(WEDM-LS)process is difficult because of high temperature,narrow kerf and other factors,Acoustic Emission(AE)was adopted to implement on-line monitoring of WEDM-LS process with adjustable duty ratio pulse.Firstly,AE signal was decomposed into eight independent frequency bands by energy spectrum algorithm of wavelet packet,respectively being W1~ W8 and frequency reduces in sequence;then energy characteristic of all frequency bands was extracted to research the relativity between it and surface roughness value of machining work-piece.Experimental results show that energy of W8 frequency band is highly related to surface roughness value and energy of this frequency band and pulse discharge energy increase with increase of pulse duty ratio,and roughness value of machining surface increases with it gradually.Finally,a mathematical prediction model between the surface roughness value and the energy in W8 frequency band was established via regression analysis,and error was only 3.51% between prediction result and surface roughness actually measured.It can be illustrated that this model has high prediction precision for online monitoring of machining surface roughness.
引文
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[12]贺银芝,沈松,应怀樵,等.小波包分解及其能量谱在发动机连杆轴承故障诊断中的应用[J].振动工程学报,2001,14(1):72-75.HE Y ZH,SHEN S,YING H Q,et al..Application of wavelet packet decomposition and its energy spectrum on the fault diagnosis of reciprocation machinery[J].Journal of Vibration Engineering,2001,14(1):72-75.(in Chinese)
[13]邓扬,丁幼亮,李爱群.基于小波包分析的拉索损伤声发射信号特征提取[J].振动与冲击,2010,29(6):154-158+242.DENG Y,DING Y L,LI A Q.Feature extraction of acoustic emission signals for cable damage based on wavelet packet analysis[J].Journal of Vibration and Shock,2010,29(6):155-158+242.(in Chinese)
[2]DAHMENE S,YAACOUBI M,MOUNTASSIR M,et al..On the modal acoustic emission testing of composite structure[J].Journal Metrics,2016(7):446-452.
[3]姜晨,李郝林.基于声发射信号的精密外圆切入磨削时间评估算法及试验研究[J].机械工程学报,2014,50(5):194-200.JIANG CH,LI H L.Algorithm and experiment of estimation of time of precision cylindrical plunge grinding based on acoustic emission signal[J].Journal of Mechanical Engineering,2014,50(5):194-200.(in Chinese)
[4]毕果,郭昕乾,孙郅佶,等.利用状态信号特征识别BK7玻璃的去除性能[J].光学精密工程,2016,24(10):394-399.BI G,GUO X Q,SUN ZH J,et al..Recognition of removal performance of BK7glass by taking advantages of status signal features[J].Opt.Precision Eng.,2016,24(10):394-399.(in Chinese)
[5]居志兰,朱永伟,王建彬,等.抛光介质对固结磨料化学机械抛光水晶的影响[J].光学精密工程,2013,21(4):955-962.JU ZH L,ZHU Y W,WANG J B,et al..Effect of slurries on chemical mechanical polishing of decorative glasses by fixed-abrasive pad[J].Opt.Precision Eng.,2013,21(4):955-962.(in Chinese)
[6]YOSHIAKI A,KAZURO K.Effect of gap region medium on acoustic emission wave by single pulse discharge[J].Optical Society of America,2006,10(4):23-27.
[7]MUTO K,SHIOTA Y,FUTAMURA S.Study on observation of EDM processing and monitoring of discharging point with acoustic emission[C].Proceedings of the ICEM,1989:301-304.
[8]王艳,杨林,丁成才,等.基于圆台形热传导模型的慢走丝线切割加工仿真与试验[J].中国机械工程,2015,26(5):598-605+619.WANG Y,YANG L,DING CH C,et al..Simulation and experiments of WEDM-LS based on turncated cone-shaped thermal conduction model[J].China Mechanical Engineering,2015,26(5):598-605+619.(in Chinese)
[9]赵亚利.慢走丝线切割机床脉冲基准信号发生器的研究与设计[D].南昌:南昌大学,2009.ZHAO Y L.The study and design on pulse standard signal generator for LSWEDM[D].Nanchang:Nanchang University,2009.(in Chinese)
[10]杨晓冬,滕庆.移动热源作用下电火花线切割加工电极丝三维温度场模拟[J].电加工与模具,2011(6):7-11.YANG X D,TENG Q.3Dtemperature field simulation of wire electrode in WEDM under the moving heat source[J].Electromachining&Mould,2011(6):7-11.(in Chinese)
[11]喻俊馨,王计生,黄惟公.小波包分析在刀具声发射信号特征提取中的应用[J].数据采集与处理,2005,20(3):346-350.YU J X,WANG J SH,HUANG W G.Wavelet package analysis to picking-up characteristics of AE signal of tools[J].Journal of Data Acquisition and Processing,2005,20(3):346-350.(in Chinese)
[12]贺银芝,沈松,应怀樵,等.小波包分解及其能量谱在发动机连杆轴承故障诊断中的应用[J].振动工程学报,2001,14(1):72-75.HE Y ZH,SHEN S,YING H Q,et al..Application of wavelet packet decomposition and its energy spectrum on the fault diagnosis of reciprocation machinery[J].Journal of Vibration Engineering,2001,14(1):72-75.(in Chinese)
[13]邓扬,丁幼亮,李爱群.基于小波包分析的拉索损伤声发射信号特征提取[J].振动与冲击,2010,29(6):154-158+242.DENG Y,DING Y L,LI A Q.Feature extraction of acoustic emission signals for cable damage based on wavelet packet analysis[J].Journal of Vibration and Shock,2010,29(6):155-158+242.(in Chinese)
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