Performance Assessment and Prediction for Superheterodyne Receivers Based on Mahalanobis Distance and Time Sequence Analysis
The superheterodyne receiver is a typical device widely used in electronics and information systems. Thus effective performance assessment and prediction for superheterodyne receiver are necessary for its preventative maintenance. A scheme of performance assessment and prediction based on Mahalanobi...
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| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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Wiley
2017-01-01
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| Series: | International Journal of Antennas and Propagation |
| Online Access: | http://dx.doi.org/10.1155/2017/6458954 |
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| _version_ | 1850176021896101888 |
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| author | Jinwen Sun Chen Lu Manxi Wang Hang Yuan Le Qi |
| author_facet | Jinwen Sun Chen Lu Manxi Wang Hang Yuan Le Qi |
| author_sort | Jinwen Sun |
| collection | DOAJ |
| description | The superheterodyne receiver is a typical device widely used in electronics and information systems. Thus effective performance assessment and prediction for superheterodyne receiver are necessary for its preventative maintenance. A scheme of performance assessment and prediction based on Mahalanobis distance and time sequence analysis is proposed in this paper. First, a state observer based on radial basis function (RBF) neural network is designed to monitor the superheterodyne receiver and generate the estimated output. The residual error can be calculated by the actual and estimated output. Second, time-domain features of the residual error are then extracted; after that, the Mahalanobis distance measurement is utilized to obtain the health confidence value which represents the performance assessment result of the most recent state. Furthermore, an Elman neural network based time sequence analysis approach is adopted to forecast the future performance of the superheterodyne receiver system. The results of simulation experiments demonstrate the robustness and effectiveness of the proposed performance assessment and prediction method. |
| format | Article |
| id | doaj-art-b76cc136f6a54632884f2edafb51fef2 |
| institution | OA Journals |
| issn | 1687-5869 1687-5877 |
| language | English |
| publishDate | 2017-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | International Journal of Antennas and Propagation |
| spelling | doaj-art-b76cc136f6a54632884f2edafb51fef22025-08-20T02:19:19ZengWileyInternational Journal of Antennas and Propagation1687-58691687-58772017-01-01201710.1155/2017/64589546458954Performance Assessment and Prediction for Superheterodyne Receivers Based on Mahalanobis Distance and Time Sequence AnalysisJinwen Sun0Chen Lu1Manxi Wang2Hang Yuan3Le Qi4State Key Laboratory of Complex Electromagnetic Environment Effects on Electronics and Information System, No. 33, 085 Mailbox, Luoyang, Henan, ChinaSchool of Reliability and Systems Engineering, Beihang University, Beijing, ChinaState Key Laboratory of Complex Electromagnetic Environment Effects on Electronics and Information System, No. 33, 085 Mailbox, Luoyang, Henan, ChinaSchool of Reliability and Systems Engineering, Beihang University, Beijing, ChinaSchool of Reliability and Systems Engineering, Beihang University, Beijing, ChinaThe superheterodyne receiver is a typical device widely used in electronics and information systems. Thus effective performance assessment and prediction for superheterodyne receiver are necessary for its preventative maintenance. A scheme of performance assessment and prediction based on Mahalanobis distance and time sequence analysis is proposed in this paper. First, a state observer based on radial basis function (RBF) neural network is designed to monitor the superheterodyne receiver and generate the estimated output. The residual error can be calculated by the actual and estimated output. Second, time-domain features of the residual error are then extracted; after that, the Mahalanobis distance measurement is utilized to obtain the health confidence value which represents the performance assessment result of the most recent state. Furthermore, an Elman neural network based time sequence analysis approach is adopted to forecast the future performance of the superheterodyne receiver system. The results of simulation experiments demonstrate the robustness and effectiveness of the proposed performance assessment and prediction method.http://dx.doi.org/10.1155/2017/6458954 |
| spellingShingle | Jinwen Sun Chen Lu Manxi Wang Hang Yuan Le Qi Performance Assessment and Prediction for Superheterodyne Receivers Based on Mahalanobis Distance and Time Sequence Analysis International Journal of Antennas and Propagation |
| title | Performance Assessment and Prediction for Superheterodyne Receivers Based on Mahalanobis Distance and Time Sequence Analysis |
| title_full | Performance Assessment and Prediction for Superheterodyne Receivers Based on Mahalanobis Distance and Time Sequence Analysis |
| title_fullStr | Performance Assessment and Prediction for Superheterodyne Receivers Based on Mahalanobis Distance and Time Sequence Analysis |
| title_full_unstemmed | Performance Assessment and Prediction for Superheterodyne Receivers Based on Mahalanobis Distance and Time Sequence Analysis |
| title_short | Performance Assessment and Prediction for Superheterodyne Receivers Based on Mahalanobis Distance and Time Sequence Analysis |
| title_sort | performance assessment and prediction for superheterodyne receivers based on mahalanobis distance and time sequence analysis |
| url | http://dx.doi.org/10.1155/2017/6458954 |
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