基于状态空间模型的可靠性评估方法

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摘要基于设备性能退化特征的可靠性分析是可靠性技术研究重要方向之一，但当前许多研究是基于多样本进行分析，但针对单个设备的可靠性预测问题非常有限，为此本文提出基于状态空间模型的可靠性方法进行小样本预测。首先通过在线监测技术获得反映设备状态的信号，运用小波分析方法提取监测信号的小波包能量，选取趋势明显符合设备状态变化的相关频带能量作为设备退化指标。然后对这些特征指标进行滑动平均滤波处理，提高了退化特征的信噪比，将其作为状态空间模型的输入对模型参数进行估计，从而建立退化指标的状态空间预测模型，最后预测退化指标的概率分布并计算可靠度。结合滚动轴承试验数据和铣刀磨损数据验证方法的准确性和有效性，本文为小样本事件的可靠性预测提供一个有效方法。

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	李宏坤1
	2
	何德鲁1
	张志新1
	任远杰1
	2
	丛明1
	2

关键词 ：可靠性预测, 状态空间模型, 特征提取, 小波分析, 滑动平均

Abstract：Reliability analysis based on equipment's performance degradation characteristics is one of the important research directions for reliability technology. As many researchers work on multi-sample analysis, it is limit for single equipment reliability prediction. So, the method of reliability prediction based on state space model is proposed for single sample analysis. First, signals about machine working conditions are determined based on-line monitoring technology for equipment. Secondly, wavelet packet energy is used for characteristic extraction for the monitored signals. Frequency band energy is determined to be as characteristic parameter. Then, the degradation characteristics of signal to noise ratio is improved by moving average filtering processing. Finally, state space model was established to predict degradation characteristics of probability density distribution, and the degree of reliability is calculated. Two real testing example of bearing and milling cutter are used to demonstrate the rationality and effectiveness of this method. It’s a useful method for single sample reliability prediction.

Key words： Reliability prediction state space model feature extraction wavelet analysis moving average

收稿日期: 2014-08-20 出版日期: 2015-12-25

引用本文:

李宏坤1,2，何德鲁1，张志新1，任远杰1,2，丛明1,2. 基于状态空间模型的可靠性评估方法[J]. 振动与冲击, 2016, 35(1): 118-124.
LI Hongkun1,2, HE Delu1, ZHANG Zhixin1, Ren Yuanjie1,2, Cong Ming1,2. Reliability Prediction Method Based on State Space Model. JOURNAL OF VIBRATION AND SHOCK, 2016, 35(1): 118-124.

链接本文:

http://jvs.sjtu.edu.cn/CN/ 或 http://jvs.sjtu.edu.cn/CN/Y2016/V35/I1/118

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