Research on speed measurement technology for maglev trains based on multi-source information fusion
The speed and distance measurement is deemed core functions of the automatic protection system for maglev trains. The key requirement is to provide accurate, real-time, safe, and reliable speed information for overspeeding and overrunning protections. Traditional speed measurement techniques for mag...
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| Format: | Article |
| Language: | zho |
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Editorial Department of Electric Drive for Locomotives
2024-11-01
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| Series: | 机车电传动 |
| Subjects: | |
| Online Access: | http://edl.csrzic.com/thesisDetails#10.13890/j.issn.1000-128X.2024.06.021 |
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| _version_ | 1850142507199889408 |
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| author | LUO Yongsheng FAN Liang LIU Ze WANG Yeliu |
| author_facet | LUO Yongsheng FAN Liang LIU Ze WANG Yeliu |
| author_sort | LUO Yongsheng |
| collection | DOAJ |
| description | The speed and distance measurement is deemed core functions of the automatic protection system for maglev trains. The key requirement is to provide accurate, real-time, safe, and reliable speed information for overspeeding and overrunning protections. Traditional speed measurement techniques for maglev trains mostly include sleeper eddy-current speed measurement, high-precision sensor speed measurement, and satellite differential speed measurement and positioning. However, deficiencies such as single source of speed measurement information, measurement performance limitations, and common cause failures result in low speed measurement accuracy and significant speed update delays for trains running at low speeds, thereby influencing the safety of train operation. This research was conducted relying on the Grobers algorithm and the fuzzy closeness algorithm. Through multi-scenario weighted fusion modeling of train operation, a technical solution for train speed measurement was devised based on multi-source information fusion, and a main control unit for fusion speed measurement was developed. Simulation and testing results indicate that, compared with traditional train speed measurement solutions, the speed measurement solution employing multi-source information fusion enhances speed measurement accuracy to 0.1 km/h during low-speed train operation and shortens response time by 1 second. The proposed solution overcomes industry challenges such as oscillating speed curves during the operation of maglev trains and a precise parking probability of no less than 99.999%, achieving precise control and safety improvement of maglev trains. |
| format | Article |
| id | doaj-art-ee8de5b9d29f4654a1194e5f32761af9 |
| institution | OA Journals |
| issn | 1000-128X |
| language | zho |
| publishDate | 2024-11-01 |
| publisher | Editorial Department of Electric Drive for Locomotives |
| record_format | Article |
| series | 机车电传动 |
| spelling | doaj-art-ee8de5b9d29f4654a1194e5f32761af92025-08-20T02:29:03ZzhoEditorial Department of Electric Drive for Locomotives机车电传动1000-128X2024-11-0115516282049615Research on speed measurement technology for maglev trains based on multi-source information fusionLUO YongshengFAN LiangLIU ZeWANG YeliuThe speed and distance measurement is deemed core functions of the automatic protection system for maglev trains. The key requirement is to provide accurate, real-time, safe, and reliable speed information for overspeeding and overrunning protections. Traditional speed measurement techniques for maglev trains mostly include sleeper eddy-current speed measurement, high-precision sensor speed measurement, and satellite differential speed measurement and positioning. However, deficiencies such as single source of speed measurement information, measurement performance limitations, and common cause failures result in low speed measurement accuracy and significant speed update delays for trains running at low speeds, thereby influencing the safety of train operation. This research was conducted relying on the Grobers algorithm and the fuzzy closeness algorithm. Through multi-scenario weighted fusion modeling of train operation, a technical solution for train speed measurement was devised based on multi-source information fusion, and a main control unit for fusion speed measurement was developed. Simulation and testing results indicate that, compared with traditional train speed measurement solutions, the speed measurement solution employing multi-source information fusion enhances speed measurement accuracy to 0.1 km/h during low-speed train operation and shortens response time by 1 second. The proposed solution overcomes industry challenges such as oscillating speed curves during the operation of maglev trains and a precise parking probability of no less than 99.999%, achieving precise control and safety improvement of maglev trains.http://edl.csrzic.com/thesisDetails#10.13890/j.issn.1000-128X.2024.06.021maglev transportationtrain speed measurementGrobers algorithmclosenessinformation fusionmgalev train |
| spellingShingle | LUO Yongsheng FAN Liang LIU Ze WANG Yeliu Research on speed measurement technology for maglev trains based on multi-source information fusion 机车电传动 maglev transportation train speed measurement Grobers algorithm closeness information fusion mgalev train |
| title | Research on speed measurement technology for maglev trains based on multi-source information fusion |
| title_full | Research on speed measurement technology for maglev trains based on multi-source information fusion |
| title_fullStr | Research on speed measurement technology for maglev trains based on multi-source information fusion |
| title_full_unstemmed | Research on speed measurement technology for maglev trains based on multi-source information fusion |
| title_short | Research on speed measurement technology for maglev trains based on multi-source information fusion |
| title_sort | research on speed measurement technology for maglev trains based on multi source information fusion |
| topic | maglev transportation train speed measurement Grobers algorithm closeness information fusion mgalev train |
| url | http://edl.csrzic.com/thesisDetails#10.13890/j.issn.1000-128X.2024.06.021 |
| work_keys_str_mv | AT luoyongsheng researchonspeedmeasurementtechnologyformaglevtrainsbasedonmultisourceinformationfusion AT fanliang researchonspeedmeasurementtechnologyformaglevtrainsbasedonmultisourceinformationfusion AT liuze researchonspeedmeasurementtechnologyformaglevtrainsbasedonmultisourceinformationfusion AT wangyeliu researchonspeedmeasurementtechnologyformaglevtrainsbasedonmultisourceinformationfusion |