基于多尺度小波变换和时频图的微波源故障检测  

Fault detection of microwave source based on multi-scale wavelet transform and time-frequency diagram

作　　者：朱娜 母其海 刘志邦 邓卓 杨彪[1] Zhu Na;Mu Qihai;Liu Zhibang;Deng Zhuo;Yang Biao(School of Information Engineering and Automation,Kunming University of Science and Technology,Kunming 650500,China)

机构地区：[1]昆明理工大学信息工程与自动化学院,昆明650500

出　　处：《电子测量技术》2021年第13期48-53,共6页Electronic Measurement Technology

摘　　要：针对目前大功率微波加热系统的微波源队列只有工作与否的二值检测,为了提高其队列运行的经济性和可靠性,在线实时检测微波源队列的运行状态及变化非常必要。提出一种基于多尺度小波变换和时频图的微波源故障检测方法。首先,根据电场强度的变化情况判断微波源队列是否发生故障。其次计算出残差信号,并根据残差在多尺度下的变化情况完成检测。最后,绘制残差信号的小波时频图,对检测结果进行可视化分析。对微波源的3种故障状态分别进行实例仿真,检测出t=80、90、100 s分别发生3种故障。仿真结果表明,利用连续小波变换的分析方法对微波源队列进行故障检测,可以准确的在线检测出微波源队列中故障微波源的位置以及发生故障的时刻。The microwave source queue of high-power microwave heating system have only binary detection of whether there are running or not. Online real-time detection of the working status and changes of the microwave source queue is necessary in order to improve the economy and reliability of its queue. A microwave source fault detection method based on multi-scale wavelet transform and time-frequency diagram is proposed. Firstly, the fault of microwave source queue is judged according to the change of electric field intensity. Secondly, calculate the residual signal, and the detection is completed according to the change of the residual signal at multiple scales. Finally, the wavelet time-frequency spectrum of the residual signal is drawn to obtain the perform visual analysis of the detection results. Three fault states of microwave source are simulated respectively. Three types of faults were detected at t=80、90、100 s respectively. Simulation results show the continuous wavelet transform analysis method is used to detect the fault of the microwave source queue, which can accurately detect the fault location and time of microwave source queue online.

关 键 词：多尺度小波变换 小波时频图 大功率微波加热系统 微波源队列 故障检测 

分 类 号：TN123[电子电信—物理电子学] TP206.3[自动化与计算机技术—检测技术与自动化装置]