Intelligent Soft Sensors
This Special Issue deals with the field of intelligent soft sensors that enable the online estimation of nonmeasurable process variables. Soft sensors or virtual sensors are common names for software algorithms in which multiple measurements are processed together. Typically, soft sensors are based...
محفوظ في:
| التنسيق: | Online |
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| اللغة: | الإنجليزية |
| منشور في: |
MDPI - Multidisciplinary Digital Publishing Institute
2023
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| الموضوعات: | |
| الوصول للمادة أونلاين: | ONIX_20230911_9783036585222_54 |
| الوسوم: |
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| _version_ | 1869527227359559680 |
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| collection | Directory of Open Access Books |
| description | This Special Issue deals with the field of intelligent soft sensors that enable the online estimation of nonmeasurable process variables. Soft sensors or virtual sensors are common names for software algorithms in which multiple measurements are processed together. Typically, soft sensors are based on control theory and are also referred to as state observers. There may be dozens or even hundreds of measurements from hard sensors (big data). The interaction of signals can be used to compute new quantities that cannot be measured directly online or are difficult and expensive to measure. Soft sensors are particularly useful in data fusion, combining measurements of different characteristics and dynamics. They can be used for fault diagnosis (self-analysis, self-calibration, and self-maintenance) as well as for control applications. Well-known software algorithms that can be seen as soft sensors include, for example, Kalman filters. More recent implementations of soft sensors use neural networks, fuzzy logic, models based on evolving clustering, partial least squares, etc. In the digitized factories of the future, intelligent sensors represent one of the core building blocks for automating and optimizing production, as they make production more efficient in every respect. |
| format | Online |
| id | doab-20.500.12854ir-113921 |
| institution | Directory of Open Access Books |
| language | eng |
| publishDate | 2023 |
| publishDateRange | 2023 |
| publishDateSort | 2023 |
| publisher | MDPI - Multidisciplinary Digital Publishing Institute |
| publisherStr | MDPI - Multidisciplinary Digital Publishing Institute |
| record_format | ojs |
| spelling | doab-20.500.12854ir-1139212024-04-11T15:11:04Z Intelligent Soft Sensors Tomažič, Simon extended Kalman filter state estimation sensor selection observability non-linear models prognostic and health management extreme learning machine soft sensors computerized adaptive testing (CAT) soft-sensor based diagnosis executive functions neurodevelopmental disorders robust observer bioprocess monitoring nonlinear systems general anesthesia total intravenous anesthesia target-controlled infusion propofol BIS index depth of hypnosis improved mathematical model population-data-based model residual model early fire warning hybrid feature fusion intelligent building system D-S evidence theory affective computing EDA stress detection physiological signals frequency analysis shape memory coil joule heating effect self-sensing actuation variable stiffness actuation electrical resistance support vector machine regression model nonlinear regression model multi-source data fusion sintering quality prediction image feature extraction keyframe extraction soft sensor improved particle swarm algorithm least squares support vector machine transfer learning Pichia pastoris spectroscopy Raman modelling variable selection outliers simulator kinetic model n/a thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues::TBX History of engineering and technology This Special Issue deals with the field of intelligent soft sensors that enable the online estimation of nonmeasurable process variables. Soft sensors or virtual sensors are common names for software algorithms in which multiple measurements are processed together. Typically, soft sensors are based on control theory and are also referred to as state observers. There may be dozens or even hundreds of measurements from hard sensors (big data). The interaction of signals can be used to compute new quantities that cannot be measured directly online or are difficult and expensive to measure. Soft sensors are particularly useful in data fusion, combining measurements of different characteristics and dynamics. They can be used for fault diagnosis (self-analysis, self-calibration, and self-maintenance) as well as for control applications. Well-known software algorithms that can be seen as soft sensors include, for example, Kalman filters. More recent implementations of soft sensors use neural networks, fuzzy logic, models based on evolving clustering, partial least squares, etc. In the digitized factories of the future, intelligent sensors represent one of the core building blocks for automating and optimizing production, as they make production more efficient in every respect. 2023-09-11T12:01:21Z 2023-09-11T12:01:21Z 2023 book ONIX_20230911_9783036585222_54 9783036585222 9783036585239 https://directory.doabooks.org/handle/20.500.12854/113921 eng application/octet-stream Attribution 4.0 International https://mdpi.com/books/pdfview/book/7764 https://mdpi.com/books/pdfview/book/7764 MDPI - Multidisciplinary Digital Publishing Institute 10.3390/books978-3-0365-8523-9 10.3390/books978-3-0365-8523-9 46cabcaa-dd94-4bfe-87b4-55023c1b36d0 9783036585222 9783036585239 230 open access |
| spellingShingle | extended Kalman filter state estimation sensor selection observability non-linear models prognostic and health management extreme learning machine soft sensors computerized adaptive testing (CAT) soft-sensor based diagnosis executive functions neurodevelopmental disorders robust observer bioprocess monitoring nonlinear systems general anesthesia total intravenous anesthesia target-controlled infusion propofol BIS index depth of hypnosis improved mathematical model population-data-based model residual model early fire warning hybrid feature fusion intelligent building system D-S evidence theory affective computing EDA stress detection physiological signals frequency analysis shape memory coil joule heating effect self-sensing actuation variable stiffness actuation electrical resistance support vector machine regression model nonlinear regression model multi-source data fusion sintering quality prediction image feature extraction keyframe extraction soft sensor improved particle swarm algorithm least squares support vector machine transfer learning Pichia pastoris spectroscopy Raman modelling variable selection outliers simulator kinetic model n/a thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues::TBX History of engineering and technology Intelligent Soft Sensors |
| title | Intelligent Soft Sensors |
| title_full | Intelligent Soft Sensors |
| title_fullStr | Intelligent Soft Sensors |
| title_full_unstemmed | Intelligent Soft Sensors |
| title_short | Intelligent Soft Sensors |
| title_sort | intelligent soft sensors |
| topic | extended Kalman filter state estimation sensor selection observability non-linear models prognostic and health management extreme learning machine soft sensors computerized adaptive testing (CAT) soft-sensor based diagnosis executive functions neurodevelopmental disorders robust observer bioprocess monitoring nonlinear systems general anesthesia total intravenous anesthesia target-controlled infusion propofol BIS index depth of hypnosis improved mathematical model population-data-based model residual model early fire warning hybrid feature fusion intelligent building system D-S evidence theory affective computing EDA stress detection physiological signals frequency analysis shape memory coil joule heating effect self-sensing actuation variable stiffness actuation electrical resistance support vector machine regression model nonlinear regression model multi-source data fusion sintering quality prediction image feature extraction keyframe extraction soft sensor improved particle swarm algorithm least squares support vector machine transfer learning Pichia pastoris spectroscopy Raman modelling variable selection outliers simulator kinetic model n/a thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues::TBX History of engineering and technology |
| topic_facet | extended Kalman filter state estimation sensor selection observability non-linear models prognostic and health management extreme learning machine soft sensors computerized adaptive testing (CAT) soft-sensor based diagnosis executive functions neurodevelopmental disorders robust observer bioprocess monitoring nonlinear systems general anesthesia total intravenous anesthesia target-controlled infusion propofol BIS index depth of hypnosis improved mathematical model population-data-based model residual model early fire warning hybrid feature fusion intelligent building system D-S evidence theory affective computing EDA stress detection physiological signals frequency analysis shape memory coil joule heating effect self-sensing actuation variable stiffness actuation electrical resistance support vector machine regression model nonlinear regression model multi-source data fusion sintering quality prediction image feature extraction keyframe extraction soft sensor improved particle swarm algorithm least squares support vector machine transfer learning Pichia pastoris spectroscopy Raman modelling variable selection outliers simulator kinetic model n/a thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues::TBX History of engineering and technology |
| url | ONIX_20230911_9783036585222_54 |