掉齿对带锯条横向振动最大Lyapunov指数的影响
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摘要
以MJ3210A型木工跑车带锯机为研究对象,使用信号采集分析仪采集不同工况下带锯条横向振动位移,计算、分析带锯条横向振动最大Lyapunov指数,找出带锯条掉齿与最大Lyapunov指数关系.由正交试验结果可知:负载下影响MJ3210A型跑车带锯机带锯条横向振动位移的显著因素依次为锯轮主轴转速、进料速度、锯条张紧力.在最优工作条件下,由锯轮转速、带锯条张紧力、跑车进料速度、锯路高度对带锯条横向振动的Lyapunov指数影响结果看,空载下完好带锯条、空载下有掉齿缺陷带锯条、负载下有掉齿缺陷带锯条3种工况下的最大Lyapunov指数分布范围界限非常明显,因此可以根据最大Lyapunov指数范围判定带锯条工作负载状况和产生掉齿缺陷故障状况;掉齿数量对带锯条横向振动最大Lyapunov指数影响十分明显.随着掉齿数量的增加,带锯条横向振动最大Lyapunov指数急剧增加;随着木材硬度的提高,有掉齿缺陷带锯条最大Lyapunov指数也随之增加,由此也可以根据最大Lyapunov指数和加工原料树种判断负载状况及掉齿缺陷产生及发展状况;在最优工作条件下,本试验将带锯机工作59.2 h作为判断掉齿故障阈值时间.在判断带锯条故障种类及发展程度上,带锯条横向振动最大Lyapunov指数法要好于横向振动位移法和横向振动主频率法.
Taking the MJ3210 A woodworking sports car band saw as the research object,the signal acquisition analyzer is used to collect and analyze the lateral vibration displacement of the band saw blade under different working conditions,and calculate the maximum Lyapunov exponent of the band saw blade lateral vibration to find the band saw blade and the largest Lyapunov exponent. From the orthogonal test results,it can be seen that the factors affecting the lateral vibration displacement of the band saw blade of the MJ3210 A sports car band sawmachine under load are the spindle wheel speed,feed speed and saw blade tension. Under the optimal working conditions,the effect of the saw wheel speed,band saw blade tension,sports car feed speed,and sawing height on the Lyapunov exponent of the lateral vibration of the band saw blade shows that the band saw blade is intact under no load and there is no load under no load. The maximum Lyapunov exponential distribution range of the sawtooth defect band saw blade and the sawtooth loss defect band saw blade under load is very obvious.Therefore,the band saw blade workload condition and the sawtooth defect condition can be determined according to the maximum Lyapunov exponent value range. The number of missing teeth has a significant influence on the maximum Lyapunov exponent value of the lateral vibration of the band saw blade. With the increase of the number of teeth,the maximum Lyapunov exponent value of the band saw blade increases sharply. With the increase of the hardness of the wood,the band saw blade with the sawtooth loss is the largest. The Lyapunov exponent value also increases so that the load condition and the occurrence and development of the sawtooth loss can be judged according to the maximum Lyapunov exponent value and the processing of the raw material species. Under the optimal working conditions,this test will use the band saw machine working time of 59. 2 h as the judgment time threshold of the sawtooth loss. In determining the type and development degree of band saw blade failure,the maximum lateral vibration of the band saw blade Lyapunov exponent method is better than the lateral vibration displacement method of the band saw blade and the lateral vibration main frequency method of the band saw blade.
Taking the MJ3210 A woodworking sports car band saw as the research object,the signal acquisition analyzer is used to collect and analyze the lateral vibration displacement of the band saw blade under different working conditions,and calculate the maximum Lyapunov exponent of the band saw blade lateral vibration to find the band saw blade and the largest Lyapunov exponent. From the orthogonal test results,it can be seen that the factors affecting the lateral vibration displacement of the band saw blade of the MJ3210 A sports car band sawmachine under load are the spindle wheel speed,feed speed and saw blade tension. Under the optimal working conditions,the effect of the saw wheel speed,band saw blade tension,sports car feed speed,and sawing height on the Lyapunov exponent of the lateral vibration of the band saw blade shows that the band saw blade is intact under no load and there is no load under no load. The maximum Lyapunov exponential distribution range of the sawtooth defect band saw blade and the sawtooth loss defect band saw blade under load is very obvious.Therefore,the band saw blade workload condition and the sawtooth defect condition can be determined according to the maximum Lyapunov exponent value range. The number of missing teeth has a significant influence on the maximum Lyapunov exponent value of the lateral vibration of the band saw blade. With the increase of the number of teeth,the maximum Lyapunov exponent value of the band saw blade increases sharply. With the increase of the hardness of the wood,the band saw blade with the sawtooth loss is the largest. The Lyapunov exponent value also increases so that the load condition and the occurrence and development of the sawtooth loss can be judged according to the maximum Lyapunov exponent value and the processing of the raw material species. Under the optimal working conditions,this test will use the band saw machine working time of 59. 2 h as the judgment time threshold of the sawtooth loss. In determining the type and development degree of band saw blade failure,the maximum lateral vibration of the band saw blade Lyapunov exponent method is better than the lateral vibration displacement method of the band saw blade and the lateral vibration main frequency method of the band saw blade.
引文
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[19]陈淑燕,王炜.基于Lyapunov指数的交通量混沌预测方法[J].土木工程学报,2004,37(9):96-99.
[20]赵赏鑫,张来斌,王朝晖,等.基于最大李雅普诺夫指数的滚动轴承故障诊断研究[J].石油大学学报(自然科学版),2005,29(4):80-83.
[21]李国辉,周世平,徐得名.时间序列最大Lyapunov指数的计算[J].应用科学学报,2003,21(2):127-131.
[22]中国林业科学研究院木材工业研究所.中国主要树种的木材物理力学性质[M].北京:中国林业出版社,1982.
[2]虞和济,韩庆大,李沈,等.设备故障诊断工程[M].北京:冶金工业出版社,2001:13.
[3]关新平,范正平,陈彩莲,等.混沌控制及其在保密通信中的应用[M].北京:国防工业出版社,2002:1.
[4]L Karimova1,N Makarenko.Diagnosis of stochastic fields by the mathematical morphology and computational topology methods[J].Nuclear Instruments and Methods in Physics Research A,2003,502:802-804.
[5]Keith Warren,Raymond C Hawkins,Julien C Sprott.Substance abuse as a dynamical disease:evidence and clinical implications of nonlinearity in a time series of daily alcohol consumption[J].Addictive Behaviors,2003,28:369-374.
[6]王树禾.微分方程模型与混沌[M].合肥:中国科学技术大学出版社,1999:42.
[7]高金贵,张健,李辉,等.带锯条掉齿前后横向振动位移及主频率变化规律[J].北华大学学报(自然科学版),2016,17(4):549-554.
[8]高金贵,赵洪刚,齐华春,等.不同张紧装置对带锯条横向振动及裂纹扩展的影响[J].北华大学学报(自然科学版),2018,19(1):118-122.
[9]高金贵,赵洪刚,姜兆方,等.木工带锯机主参数对裂纹产生前后带锯条AE计值的影响[J].木材加工机械,2017,28(6):1-6,26.
[10]高金贵,姜兆方,张健,等.裂纹木工带锯条横向振动位移的扩展分析与预测[J].北华大学学报(自然科学版),2017,18(3):401-407.
[11]姜万录.基于混沌性质和多分辨分析的故障诊断理论及实验研究[D].秦皇岛:燕山大学,2001:140-148.
[12]姜万录,王益群,孔祥东.齿轮故障的混沌诊断识别方法[J].机械工程学报,1999,35(6):44-47.
[13]Jiang Wanlu,Wang Yiqun,Zhang Shuqing.Chaostheory method for fault diagnosis of hydraulic pump[C]//Harbin:Proceedings of the 3rd International Symposium on Fluid Power Transmission and Control,1999:215-220.
[14]Chu F,Zhang Z.Bifurcation and chaos in a rub-impact Jeffcott rotor systems[J].Journal of Sound and Vibration,1998,210(1):1-18.
[15]David Logan,Joseph Mathew.Using the correlation dimension for vibration fault diagnosis of rolling element bearing-1[J].Basic Concepts Mechanical Systems and Signal Processing,1996,10(3):241-250.
[16]张雨.关联维分形与模糊聚类在柴油机工作状态监测中的应用[J].内燃机学报,1998,16(2):208-213.
[17]夏勇,张振仁,商斌梁,等.多重分形维数谱及其在内燃机故障诊断中的应用[J].机械,2000,27(增刊):37-41,43.
[18]侯荣涛,褚祥志,任立义.基于Lyapunov指数-相轨迹的发电机组故障诊断[J].东北大学学报(自然科学版),2004,25(5):478-481.
[19]陈淑燕,王炜.基于Lyapunov指数的交通量混沌预测方法[J].土木工程学报,2004,37(9):96-99.
[20]赵赏鑫,张来斌,王朝晖,等.基于最大李雅普诺夫指数的滚动轴承故障诊断研究[J].石油大学学报(自然科学版),2005,29(4):80-83.
[21]李国辉,周世平,徐得名.时间序列最大Lyapunov指数的计算[J].应用科学学报,2003,21(2):127-131.
[22]中国林业科学研究院木材工业研究所.中国主要树种的木材物理力学性质[M].北京:中国林业出版社,1982.