Research on Gauge-Ultra-High Dual-Parameter Fusion Measurement Method under ARM Architecture

This study innovatively proposes a synchronized gauge-overheight dual-parameter measurement method based on ARM architecture, aiming at solving the problems of low efficiency, high cost, and insufficient accuracy in traditional railroad track inspection. The method realizes efficient and accurate measurement of track geometric parameters by integrating a high-precision magnetotropic displacement sensor and LCF-100 inclinometer sensor. The system adopts a modularized design, uses an ARM processor as the core, and combines Bluetooth wireless transmission technology to construct a low-cost and high-reliability track inspection system. The application of the Bluetooth module not only simplifies the system wiring but also significantly improves the data transmission rate, which makes real-time uploading and processing of measurement data possible and further improves the system's response speed and work efficiency. In the experimental validation phase, the research team verified the measurement accuracy and stability of the method through multiple sets of comparison experiments. The experimental data show that the repeatability accuracy of the data measurement meets the experimental standards. In addition, the system has good environmental adaptability and anti-interference ability and can operate stably under complex working conditions. Through the in-depth analysis and processing of the experimental data by MATLAB software, the research team further optimized the algorithm, reduced the measurement error, and improved the system's overall performance. Compared with traditional track detection methods, this technology has significant advantages. The research results have important theoretical significance and practical application value in the field of railroad safety monitoring, laying a solid foundation for the development of a real-time track condition monitoring system, and also providing a valuable reference for precision measurement in other engineering fields.

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Publication Details

Journal
Academic Journal of Science and Technology
Published
2025-03-26
DOI
https://doi.org/10.54097/pgh7ma07
Primary Topic
Advanced Measurement and Detection Methods
Type
article
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article

Research on Gauge-Ultra-High Dual-Parameter Fusion Measurement Method under ARM Architecture

Zhi‐Hua Hu, Yiran You, Jinlong Lv
Academic Journal of Science and Technology
Advanced Measurement and Detection Methods
article

Research on Gauge-Ultra-High Dual-Parameter Fusion Measurement Method under ARM Architecture

Zhi‐Hua Hu, Yiran You, Jinlong Lv
article en

Abstract

This study innovatively proposes a synchronized gauge-overheight dual-parameter measurement method based on ARM architecture, aiming at solving the problems of low efficiency, high cost, and insufficient accuracy in traditional railroad track inspection. The method realizes efficient and accurate measurement of track geometric parameters by integrating a high-precision magnetotropic displacement sensor and LCF-100 inclinometer sensor. The system adopts a modularized design, uses an ARM processor as the core, and combines Bluetooth wireless transmission technology to construct a low-cost and high-reliability track inspection system. The application of the Bluetooth module not only simplifies the system wiring but also significantly improves the data transmission rate, which makes real-time uploading and processing of measurement data possible and further improves the system's response speed and work efficiency. In the experimental validation phase, the research team verified the measurement accuracy and stability of the method through multiple sets of comparison experiments. The experimental data show that the repeatability accuracy of the data measurement meets the experimental standards. In addition, the system has good environmental adaptability and anti-interference ability and can operate stably under complex working conditions. Through the in-depth analysis and processing of the experimental data by MATLAB software, the research team further optimized the algorithm, reduced the measurement error, and improved the system's overall performance. Compared with traditional track detection methods, this technology has significant advantages. The research results have important theoretical significance and practical application value in the field of railroad safety monitoring, laying a solid foundation for the development of a real-time track condition monitoring system, and also providing a valuable reference for precision measurement in other engineering fields.

Academic Journal of Science and TechnologyVol. 14(3)
Openalex Percentile: Top 95%
Advanced Measurement and Detection Methods
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