Jose Ricardo Silva Scarpari, C. S. Deolindo, Maria Adelia Albano Aratanha, M. W. Ribeiro, Anderson de Souza, E. Kozasa, Daisy Hirata, J. E. Matieli, R. G. Annes da Silva, C. Forster
{"title":"耦合加速度计数据同步记录仪的方法","authors":"Jose Ricardo Silva Scarpari, C. S. Deolindo, Maria Adelia Albano Aratanha, M. W. Ribeiro, Anderson de Souza, E. Kozasa, Daisy Hirata, J. E. Matieli, R. G. Annes da Silva, C. Forster","doi":"10.1109/INERTIAL51137.2021.9430459","DOIUrl":null,"url":null,"abstract":"This paper presents a method to synchronize data acquisition devices that are mechanically coupled, having attached an accelerometer to each device. A common time base for the accelerometer signals are obtained through the identification of pairing salient peaks and applying line-fitting through the potential matches. Aligning data recorded from different sources is important to precisely provide an observation of the state of a system in time (sensor fusion), to estimate the correlation between its variables and to correlate variables to time-based events. A data link between devices is not always possible or convenient. If the acquisition devices are mechanically coupled, such as being in the same body or vehicle, we propose to synchronize the data recorded from both by using the accelerometers signals to bridge. The provided solution is an automated process to find the temporal reference between accelerometer signals. Several signal processing steps are taken after data collection and storage: inconsistency removal and filtering, detection of maxima and minima, selection of saliencies, description through a characteristic pair of numbers: the interval lengths between it and its successor and its predecessor, listing possible matches between salient points, selection of the topmost relevant matches and line fitting with consensus. We discuss qualitative similarities of related work. Quantitative results are also presented by using the multidisciplinary study that motivated this work, with simultaneous data from the instrumentation of a helicopter and pilot physiological data. To conclude, we discuss the limitations of the presented approach and future work.","PeriodicalId":424028,"journal":{"name":"2021 IEEE International Symposium on Inertial Sensors and Systems (INERTIAL)","volume":"253 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-03-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Method for the Synchronization of Data Recorders by Coupling Accelerometer Data\",\"authors\":\"Jose Ricardo Silva Scarpari, C. S. Deolindo, Maria Adelia Albano Aratanha, M. W. Ribeiro, Anderson de Souza, E. Kozasa, Daisy Hirata, J. E. Matieli, R. G. Annes da Silva, C. Forster\",\"doi\":\"10.1109/INERTIAL51137.2021.9430459\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper presents a method to synchronize data acquisition devices that are mechanically coupled, having attached an accelerometer to each device. A common time base for the accelerometer signals are obtained through the identification of pairing salient peaks and applying line-fitting through the potential matches. Aligning data recorded from different sources is important to precisely provide an observation of the state of a system in time (sensor fusion), to estimate the correlation between its variables and to correlate variables to time-based events. A data link between devices is not always possible or convenient. If the acquisition devices are mechanically coupled, such as being in the same body or vehicle, we propose to synchronize the data recorded from both by using the accelerometers signals to bridge. The provided solution is an automated process to find the temporal reference between accelerometer signals. Several signal processing steps are taken after data collection and storage: inconsistency removal and filtering, detection of maxima and minima, selection of saliencies, description through a characteristic pair of numbers: the interval lengths between it and its successor and its predecessor, listing possible matches between salient points, selection of the topmost relevant matches and line fitting with consensus. We discuss qualitative similarities of related work. Quantitative results are also presented by using the multidisciplinary study that motivated this work, with simultaneous data from the instrumentation of a helicopter and pilot physiological data. To conclude, we discuss the limitations of the presented approach and future work.\",\"PeriodicalId\":424028,\"journal\":{\"name\":\"2021 IEEE International Symposium on Inertial Sensors and Systems (INERTIAL)\",\"volume\":\"253 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-03-22\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2021 IEEE International Symposium on Inertial Sensors and Systems (INERTIAL)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/INERTIAL51137.2021.9430459\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 IEEE International Symposium on Inertial Sensors and Systems (INERTIAL)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/INERTIAL51137.2021.9430459","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Method for the Synchronization of Data Recorders by Coupling Accelerometer Data
This paper presents a method to synchronize data acquisition devices that are mechanically coupled, having attached an accelerometer to each device. A common time base for the accelerometer signals are obtained through the identification of pairing salient peaks and applying line-fitting through the potential matches. Aligning data recorded from different sources is important to precisely provide an observation of the state of a system in time (sensor fusion), to estimate the correlation between its variables and to correlate variables to time-based events. A data link between devices is not always possible or convenient. If the acquisition devices are mechanically coupled, such as being in the same body or vehicle, we propose to synchronize the data recorded from both by using the accelerometers signals to bridge. The provided solution is an automated process to find the temporal reference between accelerometer signals. Several signal processing steps are taken after data collection and storage: inconsistency removal and filtering, detection of maxima and minima, selection of saliencies, description through a characteristic pair of numbers: the interval lengths between it and its successor and its predecessor, listing possible matches between salient points, selection of the topmost relevant matches and line fitting with consensus. We discuss qualitative similarities of related work. Quantitative results are also presented by using the multidisciplinary study that motivated this work, with simultaneous data from the instrumentation of a helicopter and pilot physiological data. To conclude, we discuss the limitations of the presented approach and future work.