Yang Deng, Weihao Zhai, Chongyang Fu, Qizheng Li, Yanqiang Li, Huaisong Zhao, Xiaoxiong Wang
{"title":"基于定向静电纺丝的水下情境低频振动传感器。","authors":"Yang Deng, Weihao Zhai, Chongyang Fu, Qizheng Li, Yanqiang Li, Huaisong Zhao, Xiaoxiong Wang","doi":"10.1088/1361-6528/ade5fb","DOIUrl":null,"url":null,"abstract":"<p><p>With the increasing importance of low-frequency signals in underwater monitoring, earthquake early warning, environmental noise analysis, and biomedical imaging, traditional sensor technologies face challenges such as limited flexibility, slow response time, and poor adaptability. Although existing sensors, such as electromagnetic, piezoelectric, and capacitive sensors, have made progress in certain areas, their applications are often restricted by complex environments. This paper innovatively proposes an<i>in-situ</i>vibration monitoring method, designing a low-frequency<i>in-situ</i>detection system based on triboelectric nanogenerator technology. The system not only enables efficient low-frequency signal detection in complex underwater environments but also, by incorporating machine learning algorithms, identifies different signal sources, achieving accurate distinction of intrinsic signals. The application of this technology realizes the concept of<i>in-situ</i>detection, breaking through the limitations of traditional sensor systems and providing a new solution for real-time monitoring of low-frequency signals.</p>","PeriodicalId":19035,"journal":{"name":"Nanotechnology","volume":"36 30","pages":""},"PeriodicalIF":2.8000,"publicationDate":"2025-07-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Underwater<i>in-situ</i>low-frequency vibration sensor based on oriented electrospinning.\",\"authors\":\"Yang Deng, Weihao Zhai, Chongyang Fu, Qizheng Li, Yanqiang Li, Huaisong Zhao, Xiaoxiong Wang\",\"doi\":\"10.1088/1361-6528/ade5fb\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>With the increasing importance of low-frequency signals in underwater monitoring, earthquake early warning, environmental noise analysis, and biomedical imaging, traditional sensor technologies face challenges such as limited flexibility, slow response time, and poor adaptability. Although existing sensors, such as electromagnetic, piezoelectric, and capacitive sensors, have made progress in certain areas, their applications are often restricted by complex environments. This paper innovatively proposes an<i>in-situ</i>vibration monitoring method, designing a low-frequency<i>in-situ</i>detection system based on triboelectric nanogenerator technology. The system not only enables efficient low-frequency signal detection in complex underwater environments but also, by incorporating machine learning algorithms, identifies different signal sources, achieving accurate distinction of intrinsic signals. The application of this technology realizes the concept of<i>in-situ</i>detection, breaking through the limitations of traditional sensor systems and providing a new solution for real-time monitoring of low-frequency signals.</p>\",\"PeriodicalId\":19035,\"journal\":{\"name\":\"Nanotechnology\",\"volume\":\"36 30\",\"pages\":\"\"},\"PeriodicalIF\":2.8000,\"publicationDate\":\"2025-07-24\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Nanotechnology\",\"FirstCategoryId\":\"88\",\"ListUrlMain\":\"https://doi.org/10.1088/1361-6528/ade5fb\",\"RegionNum\":4,\"RegionCategory\":\"材料科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"MATERIALS SCIENCE, MULTIDISCIPLINARY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Nanotechnology","FirstCategoryId":"88","ListUrlMain":"https://doi.org/10.1088/1361-6528/ade5fb","RegionNum":4,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"MATERIALS SCIENCE, MULTIDISCIPLINARY","Score":null,"Total":0}
Underwaterin-situlow-frequency vibration sensor based on oriented electrospinning.
With the increasing importance of low-frequency signals in underwater monitoring, earthquake early warning, environmental noise analysis, and biomedical imaging, traditional sensor technologies face challenges such as limited flexibility, slow response time, and poor adaptability. Although existing sensors, such as electromagnetic, piezoelectric, and capacitive sensors, have made progress in certain areas, their applications are often restricted by complex environments. This paper innovatively proposes anin-situvibration monitoring method, designing a low-frequencyin-situdetection system based on triboelectric nanogenerator technology. The system not only enables efficient low-frequency signal detection in complex underwater environments but also, by incorporating machine learning algorithms, identifies different signal sources, achieving accurate distinction of intrinsic signals. The application of this technology realizes the concept ofin-situdetection, breaking through the limitations of traditional sensor systems and providing a new solution for real-time monitoring of low-frequency signals.
期刊介绍:
The journal aims to publish papers at the forefront of nanoscale science and technology and especially those of an interdisciplinary nature. Here, nanotechnology is taken to include the ability to individually address, control, and modify structures, materials and devices with nanometre precision, and the synthesis of such structures into systems of micro- and macroscopic dimensions such as MEMS based devices. It encompasses the understanding of the fundamental physics, chemistry, biology and technology of nanometre-scale objects and how such objects can be used in the areas of computation, sensors, nanostructured materials and nano-biotechnology.