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Status Self-Validation of Sensor Arrays Using Gray Forecasting Model and Bootstrap Method.

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Title: Status Self-Validation of Sensor Arrays Using Gray Forecasting Model and Bootstrap Method.
Authors: Chen, Yinsheng1, Yang, Jingli1, Xu, Yonghui1, Jiang, Shouda1, Liu, Xiaodong1, Wang, Qi1
Source: IEEE Transactions on Instrumentation & Measurement. 7/1/2016, Vol. 65 Issue 7, p1626-1640. 15p.
Subjects: Statistical bootstrapping, Statistical sampling software, Uncertainty, Gray forecasting model, Mathematical models of decision making, Sensor arrays
Abstract: The reliability monitoring of sensor arrays is a challenging and critical issue that directly influences the performance of a measurement and control system. In this paper, a novel strategy based on gray forecasting model GM(1,1) coupled with the bootstrap method is proposed for status self-validation of sensor arrays. The proposed strategy focuses on fault detection, isolation, and recovery (FDIR), data validation and dynamic measurement uncertainty estimation of the sensor arrays. The FDIR scheme can effectively detect and isolate sensor abrupt faults and simultaneously accomplish fault recovery with high accuracy and good timeliness. Furthermore, the proposed FDIR scheme has the advantage of discriminating between fault-free signals with sudden changes and undoubted abrupt faults through the trust mechanism. The model GM(1,1) is updated continuously by a metabolism method to improve the adaptivity of the strategy for reliability monitoring. After signal reconstruction, the data validation and dynamic measurement uncertainty can be evaluated by the bootstrap method without any prior information about measurands. A real metal-oxide gas sensor array experimental system is designed to verify the excellent performance of the proposed strategy. The experimental results demonstrate that the proposed approach is capable of conducting the status self-validation of sensor arrays effectively and improving the reliability of sensor arrays in engineering applications. [ABSTRACT FROM PUBLISHER]
Copyright of IEEE Transactions on Instrumentation & Measurement is the property of IEEE and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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DbLabel: Engineering Source
An: 116115917
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  Data: Status Self-Validation of Sensor Arrays Using Gray Forecasting Model and Bootstrap Method.
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  Data: <searchLink fieldCode="AR" term="%22Chen%2C+Yinsheng%22">Chen, Yinsheng</searchLink><relatesTo>1</relatesTo><br /><searchLink fieldCode="AR" term="%22Yang%2C+Jingli%22">Yang, Jingli</searchLink><relatesTo>1</relatesTo><br /><searchLink fieldCode="AR" term="%22Xu%2C+Yonghui%22">Xu, Yonghui</searchLink><relatesTo>1</relatesTo><br /><searchLink fieldCode="AR" term="%22Jiang%2C+Shouda%22">Jiang, Shouda</searchLink><relatesTo>1</relatesTo><br /><searchLink fieldCode="AR" term="%22Liu%2C+Xiaodong%22">Liu, Xiaodong</searchLink><relatesTo>1</relatesTo><br /><searchLink fieldCode="AR" term="%22Wang%2C+Qi%22">Wang, Qi</searchLink><relatesTo>1</relatesTo>
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  Data: <searchLink fieldCode="DE" term="%22Statistical+bootstrapping%22">Statistical bootstrapping</searchLink><br /><searchLink fieldCode="DE" term="%22Statistical+sampling+software%22">Statistical sampling software</searchLink><br /><searchLink fieldCode="DE" term="%22Uncertainty%22">Uncertainty</searchLink><br /><searchLink fieldCode="DE" term="%22Gray+forecasting+model%22">Gray forecasting model</searchLink><br /><searchLink fieldCode="DE" term="%22Mathematical+models+of+decision+making%22">Mathematical models of decision making</searchLink><br /><searchLink fieldCode="DE" term="%22Sensor+arrays%22">Sensor arrays</searchLink>
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  Data: The reliability monitoring of sensor arrays is a challenging and critical issue that directly influences the performance of a measurement and control system. In this paper, a novel strategy based on gray forecasting model GM(1,1) coupled with the bootstrap method is proposed for status self-validation of sensor arrays. The proposed strategy focuses on fault detection, isolation, and recovery (FDIR), data validation and dynamic measurement uncertainty estimation of the sensor arrays. The FDIR scheme can effectively detect and isolate sensor abrupt faults and simultaneously accomplish fault recovery with high accuracy and good timeliness. Furthermore, the proposed FDIR scheme has the advantage of discriminating between fault-free signals with sudden changes and undoubted abrupt faults through the trust mechanism. The model GM(1,1) is updated continuously by a metabolism method to improve the adaptivity of the strategy for reliability monitoring. After signal reconstruction, the data validation and dynamic measurement uncertainty can be evaluated by the bootstrap method without any prior information about measurands. A real metal-oxide gas sensor array experimental system is designed to verify the excellent performance of the proposed strategy. The experimental results demonstrate that the proposed approach is capable of conducting the status self-validation of sensor arrays effectively and improving the reliability of sensor arrays in engineering applications. [ABSTRACT FROM PUBLISHER]
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  Label:
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  Data: <i>Copyright of IEEE Transactions on Instrumentation & Measurement is the property of IEEE and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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        Value: 10.1109/TIM.2016.2540942
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        Text: English
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      – SubjectFull: Uncertainty
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      – SubjectFull: Mathematical models of decision making
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      – SubjectFull: Sensor arrays
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      – TitleFull: Status Self-Validation of Sensor Arrays Using Gray Forecasting Model and Bootstrap Method.
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              Text: 7/1/2016
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