摘要
针对高可靠性产品服役期间数据有限、数据信息利用不充分等问题,融合性能退化实测数据分布参数与预测分布参数,提出了基于改进的Sage-Husa自适应无迹卡尔曼滤波的可靠性评估方法。该方法确定了性能退化数据统计模型得到了分布参数,并构建了基于分布参数最优估值的退化失效模型。利用最小二乘支持向量机(LS-SVM)预测得到了分布参数的预测数据以表征数据趋势信息,并以预测数据为状态变量、实测数据为观测变量,基于非线性Wiener过程建立了无迹卡尔曼滤波模型的状态方程与观测方程,得到了分布参数的最优估值;同时为了降低传统无迹卡尔曼滤波中测量噪声协方差矩阵对滤波精度影响,引入改进的Sage-Husa算法对其进行优化以提高最优估值结果的准确性和稳定性。示例结果表明,该方法增大了可靠性评估可利用数据的信息量,且得到的可靠性评估结果与工程实际结果基本一致,验证了本方法的合理性和有效性。
To solve the problems of limited data and insufficient data utilization during the service period of high-reliability equipment,a reliability assessment method based on an improved Sage-Husa adaptive unscented Kalman filter(UKF)is proposed.This method integrates the distribution parameters of the measured data reflecting performance degradation with predicted distribution parameters.A statistical model is established for performance degradation data,and a degradation failure model is constructed based on the optimal estimates of the distribution parameters.The least squares support vector machine(LS-SVM)is utilized to predict the distribution parameters,serving to characterize the data trend information.The predicted data is set as the state variable and the measured distribution parameters as observation variables.Based on the nonlinear Wiener process,the state and observation equations of the UKF model are established to obtain the optimal estimates of the distribution parameters.To reduce the impact of the measurement noise covariance matrix on the filtering accuracy,the improved Sage-Husa algorithm is introduced to optimize these matrices,enhancing the accuracy and stability of the optimal estimates.Exemplary results demonstrate that the proposed method increases the information content of the data available for reliability assessment.The reliability evaluation results obtained for the equipment are in good agreement with the actual engineering results,validating the rationality and effectiveness of the method.
作者
赵建印
姜经纬
魏顺涛
ZHAO Jianyin;JIANG Jingwei;WEI Shuntao(Naval Aviation University,Yantai 264001,China;PLA 71770 Troops)
出处
《现代防御技术》
北大核心
2025年第4期129-139,共11页
Modern Defence Technology
