{"title":"基于MEMS加速度计的地震传感器零基线自动校正电路","authors":"P. Ioakim, I. Triantis","doi":"10.1109/ISISS.2018.8358160","DOIUrl":null,"url":null,"abstract":"Data from seismic instruments utilizing MEMS accelerometric inertial sensors require two numerical integrations in order for ground motion over time trends to be derived. The noise, offsets and drifts in the interfacing electronics and within the MEMS sensor, manifest themselves as considerable cumulative errors on the post-integration derived displacement data. Currently, these errors are tackled by pre-event data averaging and digital correction algorithms on the accelerometric digitized data, requiring careful interpretation and manual manipulation, inevitably leading to undetermined displacement trends. The work presented herein practically demonstrates an instrument based circuit solution, facilitating baseline error correction at the source, and thus greatly reducing the otherwise prominent cumulative errors in the derived displacement trends.","PeriodicalId":237642,"journal":{"name":"2018 IEEE International Symposium on Inertial Sensors and Systems (INERTIAL)","volume":"79 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Auto-zero baseline correction circuit for MEMS accelerometer based seismic sensor\",\"authors\":\"P. Ioakim, I. Triantis\",\"doi\":\"10.1109/ISISS.2018.8358160\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Data from seismic instruments utilizing MEMS accelerometric inertial sensors require two numerical integrations in order for ground motion over time trends to be derived. The noise, offsets and drifts in the interfacing electronics and within the MEMS sensor, manifest themselves as considerable cumulative errors on the post-integration derived displacement data. Currently, these errors are tackled by pre-event data averaging and digital correction algorithms on the accelerometric digitized data, requiring careful interpretation and manual manipulation, inevitably leading to undetermined displacement trends. The work presented herein practically demonstrates an instrument based circuit solution, facilitating baseline error correction at the source, and thus greatly reducing the otherwise prominent cumulative errors in the derived displacement trends.\",\"PeriodicalId\":237642,\"journal\":{\"name\":\"2018 IEEE International Symposium on Inertial Sensors and Systems (INERTIAL)\",\"volume\":\"79 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-03-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2018 IEEE International Symposium on Inertial Sensors and Systems (INERTIAL)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ISISS.2018.8358160\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 IEEE International Symposium on Inertial Sensors and Systems (INERTIAL)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISISS.2018.8358160","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Auto-zero baseline correction circuit for MEMS accelerometer based seismic sensor
Data from seismic instruments utilizing MEMS accelerometric inertial sensors require two numerical integrations in order for ground motion over time trends to be derived. The noise, offsets and drifts in the interfacing electronics and within the MEMS sensor, manifest themselves as considerable cumulative errors on the post-integration derived displacement data. Currently, these errors are tackled by pre-event data averaging and digital correction algorithms on the accelerometric digitized data, requiring careful interpretation and manual manipulation, inevitably leading to undetermined displacement trends. The work presented herein practically demonstrates an instrument based circuit solution, facilitating baseline error correction at the source, and thus greatly reducing the otherwise prominent cumulative errors in the derived displacement trends.