基于多重分形谱和灰色模型GM(1,1)的齿轮接触疲劳寿命预测
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摘要
开展齿轮接触疲劳寿命预测对齿轮传动系统维护和使用具有重要意义。基于渐开线直齿轮接触疲劳台架运转试验采集的振动信号,应用多重分形去趋势分析对振动信号进行了分析,得到了多重分形谱,并构建了多重分形谱宽度指标用来表征齿轮接触疲劳退化;在此基础上,应用灰色模型GM(1,1),建立了齿轮接触疲劳寿命预测模型;结合试验数据对寿命预测结果进行了验证。结果表明,提出的寿命预测方法具有较高的预测精度,预测结果可作为齿轮寿命估计的参考。
The implement of gear contact fatigue life prediction( CFLP) is critically important for maintenance and operation of gear transmission system. A novel method for gear CFLP based on vibration data collected from the run-to-failure test of involute spur gear is proposed. The multifractal detrended fluctuation analysis( MF-DFA) is used to analyzed vibration data. As a result,the multifractal spectrum( MFS) are obtained and the indicator for assessing gear contact condition deterioration is designed based on the width of MFS. Subsequently,the gear CFLP model is developed based on the proposed indicator and GM( 1,1) model. The efficiency of this model is demonstrated by using experimental results. The results show that the proposed method delivers satisfactory performances with high precision and the prediction results can be used as a reference to gear life estimation.
The implement of gear contact fatigue life prediction( CFLP) is critically important for maintenance and operation of gear transmission system. A novel method for gear CFLP based on vibration data collected from the run-to-failure test of involute spur gear is proposed. The multifractal detrended fluctuation analysis( MF-DFA) is used to analyzed vibration data. As a result,the multifractal spectrum( MFS) are obtained and the indicator for assessing gear contact condition deterioration is designed based on the width of MFS. Subsequently,the gear CFLP model is developed based on the proposed indicator and GM( 1,1) model. The efficiency of this model is demonstrated by using experimental results. The results show that the proposed method delivers satisfactory performances with high precision and the prediction results can be used as a reference to gear life estimation.
引文
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[19]林国语,贾云献,孙磊,等.基于EKF-SSM的齿轮箱剩余寿命预测[J].机械强度,2014,36(4):614-619.
[20]孙磊,汤心刚,张星辉,等.基于随机滤波模型的齿轮箱剩余寿命预测研究[J].机械传动,2011,35(10):56-60.
[21]段明德,位宝磊,游延伟.基于无偏灰色马尔可夫组合模型的齿轮寿命预测[J].机械传动,2015,39(2):16-18.
[22]颜天晓,张瑞亮,王铁,等.基于EEMD和Hilbert包络分析的轴承复合故障诊断研究[J].机械传动,2016,40(6):132-135.
[23]魏冰阳,石佩斐.锥齿轮疲劳寿命预测的灰色GM(1,1)模型[J].机械传动,2013,37(11):24-26.
[2]唐东红,崔玉莲,张炳喜,等.装甲车辆侧减速器齿轮接触疲劳寿命预测研究[J].中国机械工程,2011(22):2762-2765.
[3]张景柱,崔清斌,徐诚.基于协同仿真的传动箱齿轮疲劳寿命预测方法[J].兵工学报,2007,28(12):1424-1427.
[4]王炎,马吉胜,蒙刚,等.齿轮系统刚柔耦合动力学建模与仿真研究[J].机械传动,2009,33(4):32-35+135.
[5]林腾蛟,钟声,沈亮.圆柱齿轮齿根三维裂纹扩展分析及寿命预测[J].重庆大学学报,2012,35(11):1-7.
[6]王良模,刘飞,夏汉关,等.某汽车差速器齿轮的强度分析及疲劳寿命预测[J].重庆理工大学学报(自然科学版),2012,26(11):1-4.
[7]潘冬,赵阳,李娜,等.齿轮磨损寿命预测方法[J].哈尔滨工业大学学报,2012,44(9):29-33.
[8]俞必强,李威,薛建华,等.基于动载荷谱的齿轮弯曲疲劳寿命预测[J].北京科技大学学报,2013,35(06):813-817.
[9]王延忠,田志敏,侯良威,等.航空重载面齿轮三维裂纹分析与疲劳寿命预测[J].北京航空航天大学学报,2014,40(2):148-153.
[10]BIGERELLE M,NAJJAR D,FOURNIER B,et al.Application of Lambda Distributions and Bootstrapanalysis to the prediction of fatigue lifetime andconfidence intervals[J].International Journal of Fatigue,2006,28(3):223-236.
[11]SAKIN R,AY I.Statistical analysis of bending fatigue life data using Weibull distributionin glass-fiber reinforced polyester composites[J].Materials and Design,2008,29(6):1170-1181.
[12]安艳秋,陈举华,张洪才.基于进化神经网络的齿轮可靠性预测[J].山东大学学报(工学版),2002,32(3):227-231.
[13]曾宇露,祝志芳.基于RBF网络的后桥齿轮残余寿命预测研究[J].汽车技术,2012(1):44-47.
[14]MOURA E P,VIEIRA A P,SIRMAO M A,et al.Applications of detrended-fluctuation analysis to gearbox fault diagnosis[J].Mechanical Systems and Signal Processing,2009,23(3):682-689.
[15]李兵,张培林,米双山,等.齿轮故障信号多重分形维数的形态学计算方法[J].振动、测试与诊断,2011,31(4):450-453.
[16]林近山,陈前.基于多重分形去趋势波动分析的齿轮箱故障特征提取方法[J].振动与冲击,2013,32(2):97-101.
[17]李莎,潘宏侠,张君东,等.基于多重分形和PSO-SVM的齿轮箱故障诊断[J].机械传动,2015,39(2):132-136.
[18]黄国龙.基于阶比跟踪和AR模型的旋转机械故障诊断与状态预测技术研究[D].天津:天津大学,2008:54-56.
[19]林国语,贾云献,孙磊,等.基于EKF-SSM的齿轮箱剩余寿命预测[J].机械强度,2014,36(4):614-619.
[20]孙磊,汤心刚,张星辉,等.基于随机滤波模型的齿轮箱剩余寿命预测研究[J].机械传动,2011,35(10):56-60.
[21]段明德,位宝磊,游延伟.基于无偏灰色马尔可夫组合模型的齿轮寿命预测[J].机械传动,2015,39(2):16-18.
[22]颜天晓,张瑞亮,王铁,等.基于EEMD和Hilbert包络分析的轴承复合故障诊断研究[J].机械传动,2016,40(6):132-135.
[23]魏冰阳,石佩斐.锥齿轮疲劳寿命预测的灰色GM(1,1)模型[J].机械传动,2013,37(11):24-26.