Whole-process self-adaptive coal flow control method under mine ecological environment

By collecting multi-source sensing data in the Kuanghong ecosystem, the coal flow status is calculated in real time and virtual coal flow data is generated, which solves the system instability problem caused by visual perception failure, realizes the adaptive and efficient operation of coal flow control, and ensures the continuous reliability of the system and the safety of the equipment.

CN122131831APending Publication Date: 2026-06-02JINING MINING GRP HAINA TECH ELECTROMECHANICAL CO
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Patent Information

Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
JINING MINING GRP HAINA TECH ELECTROMECHANICAL CO
Filing Date
2026-03-24
Publication Date
2026-06-02

AI Technical Summary

Technical Problem

Under the Kuanghong ecosystem, existing technologies have failed to effectively solve the problem of continuous and reliable system operation when the main sensing source fails due to strong interference, and have failed to achieve global collaborative control logic, especially lacking multi-source data arbitration and reverse dynamic optimization capabilities in coal flow control.

Method used

By synchronously collecting visual, physical signals, and equipment status perception data, the coal flow status is calculated in real time, consistency verification and correlation analysis are performed, and multi-source data arbitration is initiated after triggering visual anomaly flags to generate virtual coal flow data. Based on this, adaptive control commands are generated to adjust the operating parameters of the coal flow transmission equipment.

Benefits of technology

When visual perception fails, the system automatically switches to vibration, audio, and motor current arbitration mode to generate reliable virtual coal flow data, avoid production accidents, achieve continuous and stable control of coal flow, reduce energy consumption, and extend equipment life.

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Abstract

This invention relates to the field of intelligent control technology for coal transportation, specifically disclosing a whole-process adaptive coal flow control method under the Kuanghong ecosystem. This method simultaneously collects three types of sensing data: visual, physical signals, and equipment status. Based on equipment status and historical trends, it calculates predicted coal flow status values ​​in real time. By verifying the consistency between visual data and predicted values ​​and performing correlation analysis with physical signals, it dynamically evaluates the reliability of visual data and triggers an anomaly flag when visual distortion occurs. Subsequently, a multi-source data arbitration mode is initiated, generating virtual coal flow data based on the fusion of vibration and motor current characteristics to replace failure sensing. Combining downstream equipment status and storage requirements, it reverse-calculates coordinated speed control commands for all equipment along the entire line and issues them for execution through the Kuanghong system. This invention achieves robust fault tolerance and predictive adaptive control of coal flow sensing under interference from dust, water mist, etc., and improves system reliability, energy efficiency, and equipment lifespan.
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