Songbai Xu, Chaoyong Peng, Jianqiang Guo, Jianping Peng, Ling Luo
{"title":"轨底焊缝相控阵超声全聚焦图像去噪研究","authors":"Songbai Xu, Chaoyong Peng, Jianqiang Guo, Jianping Peng, Ling Luo","doi":"10.1109/FENDT54151.2021.9749663","DOIUrl":null,"url":null,"abstract":"The rail bottom weld area is prone to cracks, which can cause rail break. When using the ultrasonic total focus method(TFM) to detect rail bottom welds, there are a lot of background noise in the image due to the material impurities in the weld area, resulting in unobvious defect characterization. In this paper, the band-pass filtering method is used to filter and denoise the data collected in the full matrix capture(FMC) mode. Then, according to the phase distribution characteristics of the ultrasonic detection signal, the phase coherence factor is used to weight the image on the basis of the filtering to further improve the image signal-to-noise ratio. A 64-element probe is used to image the B-type phased array test block. The results show that this algorithm can effectively improve the image signal-to-noise ratio without weaking the defect signals. Under the same test conditions, the vertical groove defects on the bottom surface of the rail weld were detected and imaged. The results show that this method has a good suppression effect on the background noise in welds, the signal-to-noise ratio has been greatly improved, and can eliminate the artifacts of crack defects.","PeriodicalId":425658,"journal":{"name":"2021 IEEE Far East NDT New Technology & Application Forum (FENDT)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-12-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Denoising of phased array ultrasonic total focus image on rail bottom welds\",\"authors\":\"Songbai Xu, Chaoyong Peng, Jianqiang Guo, Jianping Peng, Ling Luo\",\"doi\":\"10.1109/FENDT54151.2021.9749663\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The rail bottom weld area is prone to cracks, which can cause rail break. When using the ultrasonic total focus method(TFM) to detect rail bottom welds, there are a lot of background noise in the image due to the material impurities in the weld area, resulting in unobvious defect characterization. In this paper, the band-pass filtering method is used to filter and denoise the data collected in the full matrix capture(FMC) mode. Then, according to the phase distribution characteristics of the ultrasonic detection signal, the phase coherence factor is used to weight the image on the basis of the filtering to further improve the image signal-to-noise ratio. A 64-element probe is used to image the B-type phased array test block. The results show that this algorithm can effectively improve the image signal-to-noise ratio without weaking the defect signals. Under the same test conditions, the vertical groove defects on the bottom surface of the rail weld were detected and imaged. The results show that this method has a good suppression effect on the background noise in welds, the signal-to-noise ratio has been greatly improved, and can eliminate the artifacts of crack defects.\",\"PeriodicalId\":425658,\"journal\":{\"name\":\"2021 IEEE Far East NDT New Technology & Application Forum (FENDT)\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-12-14\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2021 IEEE Far East NDT New Technology & Application Forum (FENDT)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/FENDT54151.2021.9749663\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 IEEE Far East NDT New Technology & Application Forum (FENDT)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/FENDT54151.2021.9749663","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Denoising of phased array ultrasonic total focus image on rail bottom welds
The rail bottom weld area is prone to cracks, which can cause rail break. When using the ultrasonic total focus method(TFM) to detect rail bottom welds, there are a lot of background noise in the image due to the material impurities in the weld area, resulting in unobvious defect characterization. In this paper, the band-pass filtering method is used to filter and denoise the data collected in the full matrix capture(FMC) mode. Then, according to the phase distribution characteristics of the ultrasonic detection signal, the phase coherence factor is used to weight the image on the basis of the filtering to further improve the image signal-to-noise ratio. A 64-element probe is used to image the B-type phased array test block. The results show that this algorithm can effectively improve the image signal-to-noise ratio without weaking the defect signals. Under the same test conditions, the vertical groove defects on the bottom surface of the rail weld were detected and imaged. The results show that this method has a good suppression effect on the background noise in welds, the signal-to-noise ratio has been greatly improved, and can eliminate the artifacts of crack defects.