加速度计加速退化数据统计分析方法
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摘要
加速退化试验广泛应用于加速度计的可靠性评估或寿命预测,然而加速退化数据统计分析方法的研究不足制约了可靠性评估或寿命预测的准确性。提出了一种基于Wiener退化模型的加速退化数据统计分析方法,利用加速因子不变原则推导退化模型各参数的变化规律,在此基础上建立加速退化模型,从而克服依赖假定进行加速退化建模容易造成较大误差的不足。针对传统的极大似然估计方法适用性不强的问题,提出了利用fminsearch函数结合最小二乘法求解极大似然估计值的方法。针对寿命预测时无法得到可靠寿命解析式的问题,提出了利用fzero函数求取可靠寿命的方法。仿真试验证明了加速因子不变原则推导结论的正确性,案例应用验证了所提方法的有效性。研究工作在加速退化建模、参数估计、寿命预测三个方面提出了有效的方法,具有一定的工程应用价值。
The accelerated degradation testing is extensively applied in the reliability evaluation and lifetime prediction of the accelerometer. To improve the accuracies of evaluation and prediction, a statistical analysis method for accelerated degradation data is proposed based on Wiener degradation model, which utilizes the acceleration factor constant principle to deduce the change rules of model parameters. Based on this, an accelerated degradation model is set up, which overcomes the drawbacks of the traditional assumption-based modeling method. In order to overcome the insufficient applicability problem of the traditional maximum likelihood method, an estimation method using fminsearch function and the least square method is proposed. Since the mathematical expression of the reliability lifetime cannot be obtained, a resolving method using fzero function is given. Simulation test validates the conclusion deduced from the acceleration factor constant principle, and the case study demonstrates the effectiveness of the proposed method. The research works provide effective methods for the accelerated degradation modeling, parameters estimation and lifetime prediction, which can be applied in the engineering application.
The accelerated degradation testing is extensively applied in the reliability evaluation and lifetime prediction of the accelerometer. To improve the accuracies of evaluation and prediction, a statistical analysis method for accelerated degradation data is proposed based on Wiener degradation model, which utilizes the acceleration factor constant principle to deduce the change rules of model parameters. Based on this, an accelerated degradation model is set up, which overcomes the drawbacks of the traditional assumption-based modeling method. In order to overcome the insufficient applicability problem of the traditional maximum likelihood method, an estimation method using fminsearch function and the least square method is proposed. Since the mathematical expression of the reliability lifetime cannot be obtained, a resolving method using fzero function is given. Simulation test validates the conclusion deduced from the acceleration factor constant principle, and the case study demonstrates the effectiveness of the proposed method. The research works provide effective methods for the accelerated degradation modeling, parameters estimation and lifetime prediction, which can be applied in the engineering application.
引文
[1]牛跃听,穆希辉,姜志保,等.自然贮存环境下某型加速度计贮存寿命评估[J].中国惯性技术学报,2014,22(4):552-556.Niu Yue-ting,Mu Xi-hui,Jiang Zhi-bao,et al.Storage life assessment of an accelerometer under natural storage environment[J].Journal of Chinese Inertial Technology,2014,22(4):552-556.
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[8]Wang H,Wang G J,Duan F J.Planning of step-stress accelerated degradation test based on the inverse Gaussian process[J].Reliability Engineering and System Safety,2016,154:97-105.
[9]Wang H W,Xi W J.Acceleration factor constant principle and the application under ADT[J].Quality and Reliability Engineering International,2016,32(7):2591-2600.
[10]王浩伟,徐廷学,赵建忠.融合加速退化和现场实测退化数据的剩余寿命预测方法[J].航空学报,2014,35(12):3350-3357.Wang Hao-wei,Xu Ting-xue,Zhao Jian-zhong.Residual life prediction method fusing accelerated degradation and field degradation data[J].Acta Aeronautica et Astronautica Sinica,2014,35(12):3350-3357.
[11]Wang H W,Teng K N.Residual life prediction for highly reliable products with prior accelerated degradation data[J].Eksploatacja i Niezawodnosc–Maintenance and Reliability,2016,18(3):379-389.
[12]Ye Z S,Chen L P,Tang L C,et al.Accelerated degradation test planning using the Inverse Gaussian process[J].IEEE Transactions on Reliability,2014,63:750-763.
[13]Park C,Padgett W J.Stochastic degradation models with several accelerating variables[J].IEEE Transactions on Reliability,2006,55:379-390.
[14]Ye Z S,Chen N,Shen Y.A new class of Wiener process model for degradation analysis[J].Reliability Engineering and System Safety,2015,139:58-67.
[15]Wang H W,Xu T X,Mi Q L.Lifetime prediction based on Gamma processes from accelerated degradation data[J].Chinese Journal of Aeronautics,2015,28(1):172-179.
[2]许丹,廖寻,陈云霞,等.加速度计贮存稳定期分析[J].北京航空航天大学学报,2013,39(2):173-177.Xu Dan,Liao Xun,Chen Yun-xia,et al.Analysis of storage stability of accelerometers[J].Journal of Beijing University of Aeronautics and Astronautics,2013,39(2):173-177.
[3]王前程,陈云霞,康锐.加速度计加速退化机理模型建模方法[J].北京航空航天大学学报,2012,38(10):1405-1409.Wang Qian-cheng,Chen Yun-xia,Kang Rui.Accelerated degradation mechanism modeling method for accelerometers[J].Journal of Beijing University of Aeronautics and Astronautics,2012,38(10):1405-1409.
[4]Wang H W,Xu T X,Wang W Y.Remaining life predicttion based on Wiener processes with ADT prior information[J].Quality and Reliability Engineering International,2016,32(2):753-765.
[5]Si X S,Wang W B,Hu C H,et al.A Wiener-processbased degradation model with a recursive filter algorithm for remaining useful life estimation[J].Mechanical Systems and Signal Processing,2013,35(2):219-237.
[6]袁宏杰,李楼德,段刚,等.加速度计贮存寿命与可靠性的步进加速退化试验评估方法[J].中国惯性技术学报,2012,20(1):113-116.Yuan Hong-jie,Li Lou-de,Duan Gang,et al.Storage life and reliability evaluation of accelerometer by step stress accelerated degradation testing[J].Journal of Chinese Inertial Technology,2012,20(1):113-116.
[7]李瑞,汪立新,刘刚,等.基于加速退化模型的加速度计非线性特征分析及贮存寿命预测[J].中国惯性技术学报,2014,22(1):125-130.Li Rui,Wang Li-xin,Liu Gang,et al.Nonlinear characteristic analysis and storage life forecast for accelerometer based on accelerate degradation model[J].Journal of Chinese Inertial Technology,2014,22(1):125-130.
[8]Wang H,Wang G J,Duan F J.Planning of step-stress accelerated degradation test based on the inverse Gaussian process[J].Reliability Engineering and System Safety,2016,154:97-105.
[9]Wang H W,Xi W J.Acceleration factor constant principle and the application under ADT[J].Quality and Reliability Engineering International,2016,32(7):2591-2600.
[10]王浩伟,徐廷学,赵建忠.融合加速退化和现场实测退化数据的剩余寿命预测方法[J].航空学报,2014,35(12):3350-3357.Wang Hao-wei,Xu Ting-xue,Zhao Jian-zhong.Residual life prediction method fusing accelerated degradation and field degradation data[J].Acta Aeronautica et Astronautica Sinica,2014,35(12):3350-3357.
[11]Wang H W,Teng K N.Residual life prediction for highly reliable products with prior accelerated degradation data[J].Eksploatacja i Niezawodnosc–Maintenance and Reliability,2016,18(3):379-389.
[12]Ye Z S,Chen L P,Tang L C,et al.Accelerated degradation test planning using the Inverse Gaussian process[J].IEEE Transactions on Reliability,2014,63:750-763.
[13]Park C,Padgett W J.Stochastic degradation models with several accelerating variables[J].IEEE Transactions on Reliability,2006,55:379-390.
[14]Ye Z S,Chen N,Shen Y.A new class of Wiener process model for degradation analysis[J].Reliability Engineering and System Safety,2015,139:58-67.
[15]Wang H W,Xu T X,Mi Q L.Lifetime prediction based on Gamma processes from accelerated degradation data[J].Chinese Journal of Aeronautics,2015,28(1):172-179.