{"title":"大面积腐蚀坑作用下高强度钢丝纵导波衰减","authors":"Sipeng Wan;Haijun Zhou;Yiqing Zou","doi":"10.1109/JSEN.2025.3573102","DOIUrl":null,"url":null,"abstract":"When guided waves encounter defects, they generate echoes, enabling the determination of defect location and severity. However, detecting and characterizing large-area corrosion pits poses challenges as they often fails to produce distinct echoes. To address this issue, guided waves attenuation has been proposed as a potential solution, prompting the need to investigate the attenuation behavior of guided waves in the context of large-area corrosion pits. Corroded high-strength steel wire samples were obtained by accelerating corrosion using a neutral salt spray. Surface corrosion morphology was captured using a 3-D optical scanner, and the guided waves attenuation was measured across varying degrees of corrosion. An algorithm was developed to automate the identification of corrosion pits, followed by statistical analysis of pit parameters. The findings revealed four representative morphologies on corroded steel wires, with pit parameters and guided waves attenuation evolving in accordance with the mass loss ratio. The contributions of pit parameters to scattering attenuation are ranked in the order of pit volume, pit area, pit sharpness, and pit depth. Guided wave scattering attenuation is more sensitive to larger values of pit parameters, with only pit sharpness and pit depth exhibiting a critical threshold effect. Furthermore, statistical models were formulated to predict the probabilistic characteristics of corrosion morphology based on detection outcomes.","PeriodicalId":447,"journal":{"name":"IEEE Sensors Journal","volume":"25 13","pages":"23913-23925"},"PeriodicalIF":4.3000,"publicationDate":"2025-06-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Longitudinal Guided Waves Attenuation in High-Strength Steel Wires Subject to Large-Area Corrosion Pits\",\"authors\":\"Sipeng Wan;Haijun Zhou;Yiqing Zou\",\"doi\":\"10.1109/JSEN.2025.3573102\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"When guided waves encounter defects, they generate echoes, enabling the determination of defect location and severity. However, detecting and characterizing large-area corrosion pits poses challenges as they often fails to produce distinct echoes. To address this issue, guided waves attenuation has been proposed as a potential solution, prompting the need to investigate the attenuation behavior of guided waves in the context of large-area corrosion pits. Corroded high-strength steel wire samples were obtained by accelerating corrosion using a neutral salt spray. Surface corrosion morphology was captured using a 3-D optical scanner, and the guided waves attenuation was measured across varying degrees of corrosion. An algorithm was developed to automate the identification of corrosion pits, followed by statistical analysis of pit parameters. The findings revealed four representative morphologies on corroded steel wires, with pit parameters and guided waves attenuation evolving in accordance with the mass loss ratio. The contributions of pit parameters to scattering attenuation are ranked in the order of pit volume, pit area, pit sharpness, and pit depth. Guided wave scattering attenuation is more sensitive to larger values of pit parameters, with only pit sharpness and pit depth exhibiting a critical threshold effect. Furthermore, statistical models were formulated to predict the probabilistic characteristics of corrosion morphology based on detection outcomes.\",\"PeriodicalId\":447,\"journal\":{\"name\":\"IEEE Sensors Journal\",\"volume\":\"25 13\",\"pages\":\"23913-23925\"},\"PeriodicalIF\":4.3000,\"publicationDate\":\"2025-06-02\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"IEEE Sensors Journal\",\"FirstCategoryId\":\"103\",\"ListUrlMain\":\"https://ieeexplore.ieee.org/document/11018850/\",\"RegionNum\":2,\"RegionCategory\":\"综合性期刊\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"ENGINEERING, ELECTRICAL & ELECTRONIC\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Sensors Journal","FirstCategoryId":"103","ListUrlMain":"https://ieeexplore.ieee.org/document/11018850/","RegionNum":2,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENGINEERING, ELECTRICAL & ELECTRONIC","Score":null,"Total":0}
Longitudinal Guided Waves Attenuation in High-Strength Steel Wires Subject to Large-Area Corrosion Pits
When guided waves encounter defects, they generate echoes, enabling the determination of defect location and severity. However, detecting and characterizing large-area corrosion pits poses challenges as they often fails to produce distinct echoes. To address this issue, guided waves attenuation has been proposed as a potential solution, prompting the need to investigate the attenuation behavior of guided waves in the context of large-area corrosion pits. Corroded high-strength steel wire samples were obtained by accelerating corrosion using a neutral salt spray. Surface corrosion morphology was captured using a 3-D optical scanner, and the guided waves attenuation was measured across varying degrees of corrosion. An algorithm was developed to automate the identification of corrosion pits, followed by statistical analysis of pit parameters. The findings revealed four representative morphologies on corroded steel wires, with pit parameters and guided waves attenuation evolving in accordance with the mass loss ratio. The contributions of pit parameters to scattering attenuation are ranked in the order of pit volume, pit area, pit sharpness, and pit depth. Guided wave scattering attenuation is more sensitive to larger values of pit parameters, with only pit sharpness and pit depth exhibiting a critical threshold effect. Furthermore, statistical models were formulated to predict the probabilistic characteristics of corrosion morphology based on detection outcomes.
期刊介绍:
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