Maglev Train Signal Processing Architecture Based on Nonlinear Discrete Tracking Differentiator
In a maglev train levitation system, signal processing plays an important role for the reason that some sensor signals are prone to be corrupted by noise due to the harsh installation and operation environment of sensors and some signals cannot be acquired directly via sensors. Based on these concer...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2018-05-01
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| Series: | Sensors |
| Subjects: | |
| Online Access: | http://www.mdpi.com/1424-8220/18/6/1697 |
| _version_ | 1798039731512016896 |
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| author | Zhiqiang Wang Xiaolong Li Yunde Xie Zhiqiang Long |
| author_facet | Zhiqiang Wang Xiaolong Li Yunde Xie Zhiqiang Long |
| author_sort | Zhiqiang Wang |
| collection | DOAJ |
| description | In a maglev train levitation system, signal processing plays an important role for the reason that some sensor signals are prone to be corrupted by noise due to the harsh installation and operation environment of sensors and some signals cannot be acquired directly via sensors. Based on these concerns, an architecture based on a new type of nonlinear second-order discrete tracking differentiator is proposed. The function of this signal processing architecture includes filtering signal noise and acquiring needed signals for levitation purposes. The proposed tracking differentiator possesses the advantages of quick convergence, no fluttering, and simple calculation. Tracking differentiator’s frequency characteristics at different parameter values are studied in this paper. The performance of this new type of tracking differentiator is tested in a MATLAB simulation and this tracking-differentiator is implemented in Very-High-Speed Integrated Circuit Hardware Description Language (VHDL). In the end, experiments are conducted separately on a test board and a maglev train model. Simulation and experiment results show that the performance of this novel signal processing architecture can fulfill the real system requirement. |
| first_indexed | 2024-04-11T21:57:47Z |
| format | Article |
| id | doaj.art-aa11dc8947854a84867a8e38d0b5201d |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-04-11T21:57:47Z |
| publishDate | 2018-05-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-aa11dc8947854a84867a8e38d0b5201d2022-12-22T04:01:02ZengMDPI AGSensors1424-82202018-05-01186169710.3390/s18061697s18061697Maglev Train Signal Processing Architecture Based on Nonlinear Discrete Tracking DifferentiatorZhiqiang Wang0Xiaolong Li1Yunde Xie2Zhiqiang Long3Maglev Engineering Research Center, National University of Defense Technology, Changsha 410073, ChinaMaglev Engineering Research Center, National University of Defense Technology, Changsha 410073, ChinaBeijing Enterprises Holdings Maglev Technology Development Co. Ltd., Beijing 100124, ChinaMaglev Engineering Research Center, National University of Defense Technology, Changsha 410073, ChinaIn a maglev train levitation system, signal processing plays an important role for the reason that some sensor signals are prone to be corrupted by noise due to the harsh installation and operation environment of sensors and some signals cannot be acquired directly via sensors. Based on these concerns, an architecture based on a new type of nonlinear second-order discrete tracking differentiator is proposed. The function of this signal processing architecture includes filtering signal noise and acquiring needed signals for levitation purposes. The proposed tracking differentiator possesses the advantages of quick convergence, no fluttering, and simple calculation. Tracking differentiator’s frequency characteristics at different parameter values are studied in this paper. The performance of this new type of tracking differentiator is tested in a MATLAB simulation and this tracking-differentiator is implemented in Very-High-Speed Integrated Circuit Hardware Description Language (VHDL). In the end, experiments are conducted separately on a test board and a maglev train model. Simulation and experiment results show that the performance of this novel signal processing architecture can fulfill the real system requirement.http://www.mdpi.com/1424-8220/18/6/1697maglev trainsignal processing architecturetracking differentiator (TD)FPGA |
| spellingShingle | Zhiqiang Wang Xiaolong Li Yunde Xie Zhiqiang Long Maglev Train Signal Processing Architecture Based on Nonlinear Discrete Tracking Differentiator Sensors maglev train signal processing architecture tracking differentiator (TD) FPGA |
| title | Maglev Train Signal Processing Architecture Based on Nonlinear Discrete Tracking Differentiator |
| title_full | Maglev Train Signal Processing Architecture Based on Nonlinear Discrete Tracking Differentiator |
| title_fullStr | Maglev Train Signal Processing Architecture Based on Nonlinear Discrete Tracking Differentiator |
| title_full_unstemmed | Maglev Train Signal Processing Architecture Based on Nonlinear Discrete Tracking Differentiator |
| title_short | Maglev Train Signal Processing Architecture Based on Nonlinear Discrete Tracking Differentiator |
| title_sort | maglev train signal processing architecture based on nonlinear discrete tracking differentiator |
| topic | maglev train signal processing architecture tracking differentiator (TD) FPGA |
| url | http://www.mdpi.com/1424-8220/18/6/1697 |
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