摘要
针对装备故障预测,采用卡尔曼滤波器进行应用研究。在实际应用中,考虑到噪声和扰动对测量结果的影响,在对实测的噪声进行分析同时利用卡尔曼滤波器可实现对一组含有实测噪声的数据进行预测;卡尔曼滤波器易于电脑程序设计,可对现场数据进行即时更新和处理,便于实现和结合其他算法运用。通过卡尔曼滤波关键方法的论述及实例分析结果表明,卡尔曼滤波在装备故障预测中具有良好应用前景。
Kalman filter is applied to equipment fault prediction.In practical application,considering the influence of noise and disturbance on the measurement results,the Kalman filter can be used to predict a group of data containing measured noise while analyzing the measured noise;the Kalman filter is easy to design computer program,can update and process the field data in real time,and is easy to implement and combine with other algorithms.Through the discussion of the key methods of Kalman filtering and the analysis of examples,the results show that Kalman filtering has a good application prospect in equipment fault prediction.
作者
赵建印
雷瑶
李振宇
Zhao Jianyin;Lei Yao;Li Zhenyu(Naval Aviation University,Yantai 264001,China)
出处
《兵工自动化》
北大核心
2024年第9期16-20,共5页
Ordnance Industry Automation
关键词
卡尔曼滤波
故障预测
实测数据
噪声处理
Kalman filtering
fault prediction
measured data
noise processing