{"title":"利用有限数量的传感器估计大型结构的固有频率","authors":"S. Turrisi, E. Zappa, A. Cigada, T. Hötzer","doi":"10.1109/I2MTC43012.2020.9129009","DOIUrl":null,"url":null,"abstract":"Security and safety issues are of major concern when considering large civil structures hosting many people. In recent years, this led to a growing interest towards monitoring solutions able to automatically evaluate the dynamic behaviour of the structure. Numerous studies confirm the possibility to correlate structural health with the evolution of its modal parameters, meaning that a change may indicate a modification of structure properties and a possible ongoing damage. This work is part of a long-lasting project which involves Politecnico di Milano in the continuous development of a complete Structural Health Monitoring (SHM) system for the G. Meazza stadium in Milan. The paper proposes a robust approach to estimate the main natural frequencies of a structure using the vibration data of a limited number of sensors. This comes from the necessity that, in case of complex buildings like a stadium, a balance between costs and system performance must be found. Environmental conditions can strongly modify the dynamic behaviour of a structure, sometimes masking variations due to other \"abnormal\" changes, i.e. a stiffness reduction due to structure degradation. Thus, the relationship between temperature and the estimated frequencies is investigated here using regression models, aiming at compensating for the temperature effects.","PeriodicalId":227967,"journal":{"name":"2020 IEEE International Instrumentation and Measurement Technology Conference (I2MTC)","volume":"24 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"Large structures natural frequencies estimation using a limited number of sensors\",\"authors\":\"S. Turrisi, E. Zappa, A. Cigada, T. Hötzer\",\"doi\":\"10.1109/I2MTC43012.2020.9129009\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Security and safety issues are of major concern when considering large civil structures hosting many people. In recent years, this led to a growing interest towards monitoring solutions able to automatically evaluate the dynamic behaviour of the structure. Numerous studies confirm the possibility to correlate structural health with the evolution of its modal parameters, meaning that a change may indicate a modification of structure properties and a possible ongoing damage. This work is part of a long-lasting project which involves Politecnico di Milano in the continuous development of a complete Structural Health Monitoring (SHM) system for the G. Meazza stadium in Milan. The paper proposes a robust approach to estimate the main natural frequencies of a structure using the vibration data of a limited number of sensors. This comes from the necessity that, in case of complex buildings like a stadium, a balance between costs and system performance must be found. Environmental conditions can strongly modify the dynamic behaviour of a structure, sometimes masking variations due to other \\\"abnormal\\\" changes, i.e. a stiffness reduction due to structure degradation. Thus, the relationship between temperature and the estimated frequencies is investigated here using regression models, aiming at compensating for the temperature effects.\",\"PeriodicalId\":227967,\"journal\":{\"name\":\"2020 IEEE International Instrumentation and Measurement Technology Conference (I2MTC)\",\"volume\":\"24 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-05-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2020 IEEE International Instrumentation and Measurement Technology Conference (I2MTC)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/I2MTC43012.2020.9129009\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 IEEE International Instrumentation and Measurement Technology Conference (I2MTC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/I2MTC43012.2020.9129009","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Large structures natural frequencies estimation using a limited number of sensors
Security and safety issues are of major concern when considering large civil structures hosting many people. In recent years, this led to a growing interest towards monitoring solutions able to automatically evaluate the dynamic behaviour of the structure. Numerous studies confirm the possibility to correlate structural health with the evolution of its modal parameters, meaning that a change may indicate a modification of structure properties and a possible ongoing damage. This work is part of a long-lasting project which involves Politecnico di Milano in the continuous development of a complete Structural Health Monitoring (SHM) system for the G. Meazza stadium in Milan. The paper proposes a robust approach to estimate the main natural frequencies of a structure using the vibration data of a limited number of sensors. This comes from the necessity that, in case of complex buildings like a stadium, a balance between costs and system performance must be found. Environmental conditions can strongly modify the dynamic behaviour of a structure, sometimes masking variations due to other "abnormal" changes, i.e. a stiffness reduction due to structure degradation. Thus, the relationship between temperature and the estimated frequencies is investigated here using regression models, aiming at compensating for the temperature effects.