Design of a Dual-Chain Synchronization Monitoring System for Scraper Conveyors Based on Magnetic Sensing

Chain breakage in dual-chain scraper conveyors poses significant risks to the safe and efficient operation of coal mines. To address the challenges of harsh underground environments and the lack of effective synchronization monitoring, this paper presents the design and implementation of an intelligent monitoring system for conveyor integrity. The system integrates non-contact Hall-effect sensors with a custom-designed intrinsically safe data acquisition unit. A systematic algorithmic framework is designed, comprising an adaptive threshold and plateau seeking (ATPS) module and an adaptive clustering-based identification (ACCI) module, to enable high-accuracy automatic identification of chain elements. Furthermore, a novel synchronization evaluation design based on event correlation and statistical features is introduced to quantify inter-chain timing deviations. This leads to the construction of a Chain Synchronization Index (CSI) for desynchronization anomaly detection. Field experiments conducted under representative operating conditions, including normal operation and controlled single-chain disconnection scenarios, demonstrate that the proposed design achieves a chain element recognition accuracy of 98.2%. Under normal conditions, the CSI remains consistently high, while breakage faults are sensitively detected. The proposed system provides a practical engineering solution for synchronization-aware condition monitoring and anomaly warning of scraper conveyor chains in underground coal mines.

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Publication Details

Journal
Designs
Published
2026-02-09
DOI
https://doi.org/10.3390/designs10010018
Primary Topic
Belt Conveyor Systems Engineering
Type
article
Field-Weighted Citation Impact
0.00
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article

Design of a Dual-Chain Synchronization Monitoring System for Scraper Conveyors Based on Magnetic Sensing

Haoting Liu, Xishuo Zhu, Junsheng Zhang, Han Tian et al.
Designs
Belt Conveyor Systems Engineering
article

Design of a Dual-Chain Synchronization Monitoring System for Scraper Conveyors Based on Magnetic Sensing

Haoting Liu, Xishuo Zhu, Junsheng Zhang, Han Tian, Junyuan Li, Jiacheng Li, Hao Li
article en

Abstract

Chain breakage in dual-chain scraper conveyors poses significant risks to the safe and efficient operation of coal mines. To address the challenges of harsh underground environments and the lack of effective synchronization monitoring, this paper presents the design and implementation of an intelligent monitoring system for conveyor integrity. The system integrates non-contact Hall-effect sensors with a custom-designed intrinsically safe data acquisition unit. A systematic algorithmic framework is designed, comprising an adaptive threshold and plateau seeking (ATPS) module and an adaptive clustering-based identification (ACCI) module, to enable high-accuracy automatic identification of chain elements. Furthermore, a novel synchronization evaluation design based on event correlation and statistical features is introduced to quantify inter-chain timing deviations. This leads to the construction of a Chain Synchronization Index (CSI) for desynchronization anomaly detection. Field experiments conducted under representative operating conditions, including normal operation and controlled single-chain disconnection scenarios, demonstrate that the proposed design achieves a chain element recognition accuracy of 98.2%. Under normal conditions, the CSI remains consistently high, while breakage faults are sensitively detected. The proposed system provides a practical engineering solution for synchronization-aware condition monitoring and anomaly warning of scraper conveyor chains in underground coal mines.

DesignsVol. 10(1)
Tiandi Science & Technology (China) (CN), China Coal Research Institute (China) (CN), University of Science and Technology Beijing (CN)
Openalex Percentile: Top 63%
Belt Conveyor Systems Engineering
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Design of a Dual-Chain Synchronization Monitoring System for Scraper Conveyors Based on Magnetic Sensing — Haoting Liu, Xishuo Zhu, et al. · Designs (2026) | TGRS Research Map | TGRS