Guoping Liu, Zhaoshu Yang, Zhongbo He, Kai Tao, Jingtao Zhou, Sen Li, Wei Hu, Minzheng Sun
{"title":"一种基于驻极体的自感知微振减振器及基于支持向量回归算法的建模","authors":"Guoping Liu, Zhaoshu Yang, Zhongbo He, Kai Tao, Jingtao Zhou, Sen Li, Wei Hu, Minzheng Sun","doi":"10.1007/s12217-023-10069-6","DOIUrl":null,"url":null,"abstract":"<div><p>In this paper, we developed a lightweight, self-sensing electret-based dynamic vibration absorber (ESDVA) for micro-vibration suppressions. We modeled the electromechanical coupling procedure of the ESDVA based on the first principles and proposed a sensing model based on support vector regression machine (SVR). The SVR algorithm helps to linearize the original voltage generated by the electret for precise vibration sensing. A prototype of the ESDVA is fabricated, and the theoretical model and SVR algorithms are verified by experiments. According to experimental results, the ESDVA successfully reduced primary structure vibration amplitudes by up to 50% with a mass burden of 1.4% of the primary structure. The proposed sensing model achieve an accuracy rate of over 93.5% for vibration sensing and the robustness of the model was also assessed. Moreover, the advantages of the proposed electret-based sensing method over classical methods are discussed.</p></div>","PeriodicalId":707,"journal":{"name":"Microgravity Science and Technology","volume":null,"pages":null},"PeriodicalIF":1.3000,"publicationDate":"2023-08-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"An Electret-Based Self-Sensing Micro-Vibration Absorber and the Modeling Based on Support Vector Regression Algorithm\",\"authors\":\"Guoping Liu, Zhaoshu Yang, Zhongbo He, Kai Tao, Jingtao Zhou, Sen Li, Wei Hu, Minzheng Sun\",\"doi\":\"10.1007/s12217-023-10069-6\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>In this paper, we developed a lightweight, self-sensing electret-based dynamic vibration absorber (ESDVA) for micro-vibration suppressions. We modeled the electromechanical coupling procedure of the ESDVA based on the first principles and proposed a sensing model based on support vector regression machine (SVR). The SVR algorithm helps to linearize the original voltage generated by the electret for precise vibration sensing. A prototype of the ESDVA is fabricated, and the theoretical model and SVR algorithms are verified by experiments. According to experimental results, the ESDVA successfully reduced primary structure vibration amplitudes by up to 50% with a mass burden of 1.4% of the primary structure. The proposed sensing model achieve an accuracy rate of over 93.5% for vibration sensing and the robustness of the model was also assessed. Moreover, the advantages of the proposed electret-based sensing method over classical methods are discussed.</p></div>\",\"PeriodicalId\":707,\"journal\":{\"name\":\"Microgravity Science and Technology\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":1.3000,\"publicationDate\":\"2023-08-18\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Microgravity Science and Technology\",\"FirstCategoryId\":\"5\",\"ListUrlMain\":\"https://link.springer.com/article/10.1007/s12217-023-10069-6\",\"RegionNum\":4,\"RegionCategory\":\"工程技术\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"ENGINEERING, AEROSPACE\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Microgravity Science and Technology","FirstCategoryId":"5","ListUrlMain":"https://link.springer.com/article/10.1007/s12217-023-10069-6","RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"ENGINEERING, AEROSPACE","Score":null,"Total":0}
An Electret-Based Self-Sensing Micro-Vibration Absorber and the Modeling Based on Support Vector Regression Algorithm
In this paper, we developed a lightweight, self-sensing electret-based dynamic vibration absorber (ESDVA) for micro-vibration suppressions. We modeled the electromechanical coupling procedure of the ESDVA based on the first principles and proposed a sensing model based on support vector regression machine (SVR). The SVR algorithm helps to linearize the original voltage generated by the electret for precise vibration sensing. A prototype of the ESDVA is fabricated, and the theoretical model and SVR algorithms are verified by experiments. According to experimental results, the ESDVA successfully reduced primary structure vibration amplitudes by up to 50% with a mass burden of 1.4% of the primary structure. The proposed sensing model achieve an accuracy rate of over 93.5% for vibration sensing and the robustness of the model was also assessed. Moreover, the advantages of the proposed electret-based sensing method over classical methods are discussed.
期刊介绍:
Microgravity Science and Technology – An International Journal for Microgravity and Space Exploration Related Research is a is a peer-reviewed scientific journal concerned with all topics, experimental as well as theoretical, related to research carried out under conditions of altered gravity.
Microgravity Science and Technology publishes papers dealing with studies performed on and prepared for platforms that provide real microgravity conditions (such as drop towers, parabolic flights, sounding rockets, reentry capsules and orbiting platforms), and on ground-based facilities aiming to simulate microgravity conditions on earth (such as levitrons, clinostats, random positioning machines, bed rest facilities, and micro-scale or neutral buoyancy facilities) or providing artificial gravity conditions (such as centrifuges).
Data from preparatory tests, hardware and instrumentation developments, lessons learnt as well as theoretical gravity-related considerations are welcome. Included science disciplines with gravity-related topics are:
− materials science
− fluid mechanics
− process engineering
− physics
− chemistry
− heat and mass transfer
− gravitational biology
− radiation biology
− exobiology and astrobiology
− human physiology