Mario Escarcega, Meghan Cephus, Skyler Hughes, Nakii Tsosie, Kimberly Kelso, Raechelle Sandoval, A. Ebrahimkhanlou
{"title":"基于声发射的未来月球管道结构健康监测","authors":"Mario Escarcega, Meghan Cephus, Skyler Hughes, Nakii Tsosie, Kimberly Kelso, Raechelle Sandoval, A. Ebrahimkhanlou","doi":"10.1115/imece2021-71429","DOIUrl":null,"url":null,"abstract":"\n This paper explores the use of acoustic-based structural health monitoring (SHM) in lunar habitats to detect damage and failure in pipelines used for resource transportation. Acoustic-based SHM on Earth is a well-studied field of research. Various studies validate the effectiveness of acoustic-based SHM to detect, locate, and characterize damage in pipelines. Relevant literature shows that little to no research has been conducted on SHM regarding simulated lunar pipelines. In this paper, acoustic emission (AE) waveforms were collected and analyzed for aluminum pipe sections that were damaged from three separately simulated lunar conditions. Experiments simulating lunar regolith abrasion, internal galvanic corrosion, and irradiation were conducted on aluminum pipes. Pipes on the lunar surface will be constantly exposed to radiation, abrasion, and corrosion. As such, it is important to detect, localize, and predict damage resulting from these lunar hazards. The waveform data were clustered based on hit-driven properties. These clusters showed distinct differences between the datasets, which allowed for comparison and characterization of the data. It was found that variations in cluster shape and placement in peak, centroid, and average frequency could reliably distinguish between corrosive and abrasive processes. Understanding the differences in the data that contribute to distinctions between event types, and those that do not, will enable AE monitoring systems to better identify, characterize, and predict lunar pipeline failure.","PeriodicalId":23648,"journal":{"name":"Volume 1: Acoustics, Vibration, and Phononics","volume":"88 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2021-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Acoustic Emission-Based Structural Health Monitoring for Future Lunar Pipelines\",\"authors\":\"Mario Escarcega, Meghan Cephus, Skyler Hughes, Nakii Tsosie, Kimberly Kelso, Raechelle Sandoval, A. Ebrahimkhanlou\",\"doi\":\"10.1115/imece2021-71429\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"\\n This paper explores the use of acoustic-based structural health monitoring (SHM) in lunar habitats to detect damage and failure in pipelines used for resource transportation. Acoustic-based SHM on Earth is a well-studied field of research. Various studies validate the effectiveness of acoustic-based SHM to detect, locate, and characterize damage in pipelines. Relevant literature shows that little to no research has been conducted on SHM regarding simulated lunar pipelines. In this paper, acoustic emission (AE) waveforms were collected and analyzed for aluminum pipe sections that were damaged from three separately simulated lunar conditions. Experiments simulating lunar regolith abrasion, internal galvanic corrosion, and irradiation were conducted on aluminum pipes. Pipes on the lunar surface will be constantly exposed to radiation, abrasion, and corrosion. As such, it is important to detect, localize, and predict damage resulting from these lunar hazards. The waveform data were clustered based on hit-driven properties. These clusters showed distinct differences between the datasets, which allowed for comparison and characterization of the data. It was found that variations in cluster shape and placement in peak, centroid, and average frequency could reliably distinguish between corrosive and abrasive processes. Understanding the differences in the data that contribute to distinctions between event types, and those that do not, will enable AE monitoring systems to better identify, characterize, and predict lunar pipeline failure.\",\"PeriodicalId\":23648,\"journal\":{\"name\":\"Volume 1: Acoustics, Vibration, and Phononics\",\"volume\":\"88 1\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-11-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Volume 1: Acoustics, Vibration, and Phononics\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1115/imece2021-71429\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Volume 1: Acoustics, Vibration, and Phononics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1115/imece2021-71429","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Acoustic Emission-Based Structural Health Monitoring for Future Lunar Pipelines
This paper explores the use of acoustic-based structural health monitoring (SHM) in lunar habitats to detect damage and failure in pipelines used for resource transportation. Acoustic-based SHM on Earth is a well-studied field of research. Various studies validate the effectiveness of acoustic-based SHM to detect, locate, and characterize damage in pipelines. Relevant literature shows that little to no research has been conducted on SHM regarding simulated lunar pipelines. In this paper, acoustic emission (AE) waveforms were collected and analyzed for aluminum pipe sections that were damaged from three separately simulated lunar conditions. Experiments simulating lunar regolith abrasion, internal galvanic corrosion, and irradiation were conducted on aluminum pipes. Pipes on the lunar surface will be constantly exposed to radiation, abrasion, and corrosion. As such, it is important to detect, localize, and predict damage resulting from these lunar hazards. The waveform data were clustered based on hit-driven properties. These clusters showed distinct differences between the datasets, which allowed for comparison and characterization of the data. It was found that variations in cluster shape and placement in peak, centroid, and average frequency could reliably distinguish between corrosive and abrasive processes. Understanding the differences in the data that contribute to distinctions between event types, and those that do not, will enable AE monitoring systems to better identify, characterize, and predict lunar pipeline failure.