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作 者:刘洪政 石瑞 普承恩 胡洲 梁国用 黄松 LIU Hongzheng;SHI Rui;PU Chengen;HU Zhou;LIANG Gouyong;HUANG Song(Sichuan Institute of Aerospace Systems Engineering,Chengdu 611130,China)
出 处:《兵器装备工程学报》2024年第4期176-183,共8页Journal of Ordnance Equipment Engineering
摘 要:针对电动舵机大动作测试数据人工关联判读工作量大、效率低、故障诊断难的问题,提出一种基于离散小波变换和多约束特征点提取的关联判读方法。根据测试数据量大、类型多的特点,分别采用离散小波变换以及多约束特征提取算法对不同类型的测试数据进行特征提取,剔除异常值,准确定位各个数据的大动作时刻,提取出特征值;使用时间关联判读方法对提取的特征点进行判读,给出了判读异常情况下的故障诊断结果并自动生成判读报表。为验证关联判读方法的有效性,进行了自动判读算法的实验测试验证。结果表明:该方法可在45 s内完成舵机测试数据的关联自动判读和故障诊断,而依赖专业技术人员的人工判读方法至少需要335 s,每个大动作点的数据判读效率提高了6倍以上。Aiming at the problems of high workload,low efficiency,and difficulty in fault diagnosis of manual correlation and interpretation of test data for fast rotating electrical actuators,a correlation interpretation method based on discrete wavelet transform(DWT)and multi constraint feature point extraction is proposed.According to the characteristics of large amount and many types of test data,discrete wavelet transform and multi constraint feature extraction algorithm are used to extract features from test data,eliminate abnormal data,and accurately locate the fasting rotating time of each data;The time correlation interpretation method is used to interpret the extracted feature points,and the fault diagnosis results under abnormal interpretation conditions are provided and interpretation reports are generated automatically.In order to verify the validity of the correlation interpretation method,the test data verification is carried out by experiment.The results show that the method can complete the automatic interpretation and fault diagnosis of the servo test data within 45 s,while the manual interpretation method relying on professional and technical personnel takes at least 335 s,and the data interpretation efficiency of each large action point is increased by 6 times.
分 类 号:TJ414[兵器科学与技术—火炮、自动武器与弹药工程]
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