车轮电磁超声探伤技术及自适应滤波算法研究  

Research on EMAT Used in Wheel Flaw Detecting and Adaptive Filtering Algorithm

作　　者：戴立新[1] 韩激扬 王泽勇[1] 王黎[1] 高晓蓉[1] 

机构地区：[1]西南交通大学理学院,四川成都610031 [2]武汉铁路局武汉动车基地建设指挥部,湖北武汉430071

出　　处：《铁道学报》2010年第4期114-118,共5页Journal of the China Railway Society

基　　金：铁道部科技研究开发计划(2002J040)

摘　　要：对电磁超声技术(EMAT)及车轮踏面探伤原理进行介绍,并给出回波定位及缺陷判断的方法。针对检测过程中所产生的噪声信号,提出采用变步长、归一化的最小均方自适应滤波(NLMS)算法来解决。通过将输入信号进行适当延迟获得参考信号,将其与输入信号叠加,进而用于过滤探伤中产生的噪声信号。从处理结果来看,该方法应用前景良好。Use of the electro-magnetic acoustic transducer（EMAT） represents a new trend of development of nondestructive testing,and recently EMAT has been widely adopted by railway departments in our country.The principles of EMA technology and flaw detecting of wheel treads and the methods of flaw identification and echo positioning are introduced.In view of generation of noise signals in the detecting process,the normalized least mean-square algorithm（NLMS） with a changing step size is adopted to appropriately delay input signals to obtain reference signals and to superimpose the reference signals on input signals to further filter out the generated noise signals.It can be seen that the proposed method has good prospects in application.

关 键 词：电磁超声技术 表面波 铁路车轮 归一化最小均方自适应滤波 

分 类 号：U270.7[机械工程—车辆工程]