{"title":"从桥梁结构响应估计车辆数量","authors":"Tom Strain, S. Gunner, E. Wilson","doi":"10.1680/ICSIC.64669.751","DOIUrl":null,"url":null,"abstract":"In this paper an offline method for counting vehicles travelling across a bridge through its structural response under loading is developed. Readings from a single vertically oriented accelerometer fixed to the bridge are normalised and then summarised by instantaneous amplitude envelopes. The envelopes for a single vehicle have a profile that is log-normal in appearance. Least squares fitting is used in conjunction with the Akaike information criterion to fit the envelope time series as the superposition of 𝑛𝑛 log-normal functions (other functional forms are also considered). It is hypothesised that this fit describes 𝑛𝑛 vehicles travelling across the bridge. This method is applied to data from a previous study on rapid deployment of structural health monitoring systems undertaken on the Clifton Suspension Bridge (CSB) in Bristol. The data from a single strain gauge-based accelerometer installed as part of a wireless sensor network (WSN) on the bridge is used and demonstrates the value added by this method to pre-existing asset monitoring systems. A prediction accuracy of 74% is achieved on a labelled test set.","PeriodicalId":205150,"journal":{"name":"International Conference on Smart Infrastructure and Construction 2019 (ICSIC)","volume":"18 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Estimation of Vehicle Counts from the Structural Response of a Bridge\",\"authors\":\"Tom Strain, S. Gunner, E. Wilson\",\"doi\":\"10.1680/ICSIC.64669.751\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper an offline method for counting vehicles travelling across a bridge through its structural response under loading is developed. Readings from a single vertically oriented accelerometer fixed to the bridge are normalised and then summarised by instantaneous amplitude envelopes. The envelopes for a single vehicle have a profile that is log-normal in appearance. Least squares fitting is used in conjunction with the Akaike information criterion to fit the envelope time series as the superposition of 𝑛𝑛 log-normal functions (other functional forms are also considered). It is hypothesised that this fit describes 𝑛𝑛 vehicles travelling across the bridge. This method is applied to data from a previous study on rapid deployment of structural health monitoring systems undertaken on the Clifton Suspension Bridge (CSB) in Bristol. The data from a single strain gauge-based accelerometer installed as part of a wireless sensor network (WSN) on the bridge is used and demonstrates the value added by this method to pre-existing asset monitoring systems. A prediction accuracy of 74% is achieved on a labelled test set.\",\"PeriodicalId\":205150,\"journal\":{\"name\":\"International Conference on Smart Infrastructure and Construction 2019 (ICSIC)\",\"volume\":\"18 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Conference on Smart Infrastructure and Construction 2019 (ICSIC)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1680/ICSIC.64669.751\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Conference on Smart Infrastructure and Construction 2019 (ICSIC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1680/ICSIC.64669.751","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Estimation of Vehicle Counts from the Structural Response of a Bridge
In this paper an offline method for counting vehicles travelling across a bridge through its structural response under loading is developed. Readings from a single vertically oriented accelerometer fixed to the bridge are normalised and then summarised by instantaneous amplitude envelopes. The envelopes for a single vehicle have a profile that is log-normal in appearance. Least squares fitting is used in conjunction with the Akaike information criterion to fit the envelope time series as the superposition of 𝑛𝑛 log-normal functions (other functional forms are also considered). It is hypothesised that this fit describes 𝑛𝑛 vehicles travelling across the bridge. This method is applied to data from a previous study on rapid deployment of structural health monitoring systems undertaken on the Clifton Suspension Bridge (CSB) in Bristol. The data from a single strain gauge-based accelerometer installed as part of a wireless sensor network (WSN) on the bridge is used and demonstrates the value added by this method to pre-existing asset monitoring systems. A prediction accuracy of 74% is achieved on a labelled test set.