基于压缩感知的弹药自动装填系统数据采集方法

摘要

嵌入式火炮弹药自动装填系统的故障诊断机对装填系统进行实时监控,利用传感器采集弹药自动装填系统运行时的数据并进行分析处理,检测、隔离故障或预测该系统未来的健康状况。为解决传统嵌入式故障诊断机在恶劣环境下采集和存储数据量减少带来的问题,该文提出一种基于压缩感知的嵌入式火炮弹药自动装填系统故障诊断机数据采集方法。使用降采样方式对弹药自动装填协调动作角速度数据进行采样,利用压缩感知理论,通过正交匹配追踪( Orthogonal matching pursuit,OMP)算法对数据进行重构。结果表明,OMP算法能较准确地恢复原数据,提高故障诊断机的精确度,保证其诊断和预测的正确性。%The embedded fault diagnosis machine for the automatic ammunition loading system monitors the system realtimely, collects the data by using sensors, analyzes the data, detects and isolates faults,and predicts the health of the system in the future. In order to solve the problem that the data acquisition and storage of the traditional embedded fault diagnosis machine are reducted under the severe environment,a data acquisition method based on the compressive sensing theory is proposed. The data of the coordinated action angular velocity is sampled by the down-sample mode. By using the compressive sensing theory,the data is reconstructed by the orthogonal matching pursuit ( OMP) algorithm. The result shows that the OMP algorithm can recover the original data accurately, improve the accuracy,and guarantee the correctness of diagnosis and prognosis of the fault diagnosis machine.