电光与控制, 2016, 23 (6): 96, 网络出版: 2021-01-28  

火箭发动机故障检测的自适应相关算法的改进

Improvement of Adaptive Correlation Algorithm for Rocket Engine Fault Detection
作者单位
1 北京宇航系统工程研究所,北京 100076
2 北京航空航天大学自动化科学与电气工程学院,北京 100191
摘要
针对自适应相关算法(ACA)采用单一理论阈值,且马氏(Mahalanobis)距离的修正方法不太合理的问题,在已有的自适应相关方法基础上,提出了改进的火箭发动机实时故障检测的自适应相关算法。改进之处有:1) 利用理论阈值和发动机历史数据统计得到的经验阈值共同作为判断依据;2) 提出了修正Mahalanobis距离的计算方法,去除偏离数据均值最大的1~3个参数对Mahalanobis距离的贡献。在给定的5%误检率下,通过发动机的仿真数据验证了改进的算法能对发动机稳态工作过程中的故障及时准确地检测,并能有效解决野值存在时的误报警情况。
Abstract
Aiming at the problems that the Adaptive Correlation Algorithm (ACA) uses single theoretical threshold and the Mahalanobis distance correction method is unreasonable, we proprose an improved adaptive correlation algorithm for real-time rocket engine fault detection on the basis of existing research. The improvements are: 1) The empirical threshold obtained from the historical data of the engine is used together with the theoretical threshold as judgment criterion; and 2) Mahalanobis distance is corrected by removing 1 to 3 parameters that contribute the largest deviation to data mean. Under the given false detecting rate of 5%, simulation data demonstrate that the improved algorithm can give timely and accurate fault detection result, and can effectively solve false alarm problem when outliers exist.
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张利彬, 李璨, 张翔, 安雪岩, 李文, 任章. 火箭发动机故障检测的自适应相关算法的改进[J]. 电光与控制, 2016, 23(6): 96. ZHANG Li-bin, LI Can, ZHANG Xiang, AN Xue-yan, LI Wen, REN Zhang. Improvement of Adaptive Correlation Algorithm for Rocket Engine Fault Detection[J]. Electronics Optics & Control, 2016, 23(6): 96.

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