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Switching algorithm for maglev train double-modular redundant positioning sensors.

He N, Long Z, Xue S - Sensors (Basel) (2012)

Bottom Line: The prediction errors are used to trigger sensor switching.The time delay characteristics of the method are analyzed to guide the algorithm simplification.Finally, the effectiveness of the simplified switching algorithm is verified through experiments.

View Article: PubMed Central - PubMed

Affiliation: College of Mechatronics Engineering and Automation, National University of Defense Technology, Changsha 410073, China. hening0606@126.com

ABSTRACT
High-resolution positioning for maglev trains is implemented by detecting the tooth-slot structure of the long stator installed along the rail, but there are large joint gaps between long stator sections. When a positioning sensor is below a large joint gap, its positioning signal is invalidated, thus double-modular redundant positioning sensors are introduced into the system. This paper studies switching algorithms for these redundant positioning sensors. At first, adaptive prediction is applied to the sensor signals. The prediction errors are used to trigger sensor switching. In order to enhance the reliability of the switching algorithm, wavelet analysis is introduced to suppress measuring disturbances without weakening the signal characteristics reflecting the stator joint gap based on the correlation between the wavelet coefficients of adjacent scales. The time delay characteristics of the method are analyzed to guide the algorithm simplification. Finally, the effectiveness of the simplified switching algorithm is verified through experiments.

No MeSH data available.


The reconstituted signal and predicted signal.
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f9-sensors-12-11294: The reconstituted signal and predicted signal.

Mentions: Choose a threshold T = 10, and update the wavelet coefficients by setting dj(k) and dj(k′) to zero when dj(k) &middot; dj(k′) < T. Then a reconstructed signal can be gotten by applying Equation (11) to the scale coefficients and the updated wavelet coefficients shown in Figure 9.


Switching algorithm for maglev train double-modular redundant positioning sensors.

He N, Long Z, Xue S - Sensors (Basel) (2012)

The reconstituted signal and predicted signal.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC3472885&req=5

f9-sensors-12-11294: The reconstituted signal and predicted signal.
Mentions: Choose a threshold T = 10, and update the wavelet coefficients by setting dj(k) and dj(k′) to zero when dj(k) &middot; dj(k′) < T. Then a reconstructed signal can be gotten by applying Equation (11) to the scale coefficients and the updated wavelet coefficients shown in Figure 9.

Bottom Line: The prediction errors are used to trigger sensor switching.The time delay characteristics of the method are analyzed to guide the algorithm simplification.Finally, the effectiveness of the simplified switching algorithm is verified through experiments.

View Article: PubMed Central - PubMed

Affiliation: College of Mechatronics Engineering and Automation, National University of Defense Technology, Changsha 410073, China. hening0606@126.com

ABSTRACT
High-resolution positioning for maglev trains is implemented by detecting the tooth-slot structure of the long stator installed along the rail, but there are large joint gaps between long stator sections. When a positioning sensor is below a large joint gap, its positioning signal is invalidated, thus double-modular redundant positioning sensors are introduced into the system. This paper studies switching algorithms for these redundant positioning sensors. At first, adaptive prediction is applied to the sensor signals. The prediction errors are used to trigger sensor switching. In order to enhance the reliability of the switching algorithm, wavelet analysis is introduced to suppress measuring disturbances without weakening the signal characteristics reflecting the stator joint gap based on the correlation between the wavelet coefficients of adjacent scales. The time delay characteristics of the method are analyzed to guide the algorithm simplification. Finally, the effectiveness of the simplified switching algorithm is verified through experiments.

No MeSH data available.