Coal Mining
Coal Mining
Intelligent Monitoring Solution for Mining and Washing Mills

Mining and washing mills are critical to ore crushing, grinding and cleaning in mining and building materials, directly affecting efficiency, quality and costs. Current practice relies on manual inspection and reactive repair, with delayed monitoring, weak fault identification, imprecise energy management, high O&M costs and safety risks. Undetected gearbox or bearing abnormalities can cause shutdowns. Designed for heavy dust, vibration and loads, this solution addresses poor environmental compatibility, delayed detection, inefficient O&M, difficult oil management and data silos, enabling predictive maintenance and providing lifecycle support for stable, efficient and safe production.

Monitoring Challenges

Poor Operating-Condition Adaptability
Poor Operating-Condition Adaptability
Heavy dust, strong vibration and high humidity exceed ordinary devices' protection capabilities, causing sensor clogging, distorted data and damage and preventing long-term stability.
Delayed Monitoring Response
Delayed Monitoring Response
Infrequent manual inspections and offline sampling provide limited coverage. Small faults develop into major problems, causing unplanned downtime and disrupting production.
Inefficient O&M
Inefficient O&M
Hidden critical components are difficult and time-consuming to inspect, and site conditions are hazardous. Fragmented data without a unified platform hinders root-cause analysis and informed decisions, resulting in excessive or insufficient maintenance.
Weak O&M Warning Capability
Weak O&M Warning Capability
Without predictive maintenance, repairs rely on experience, with both over- and under-maintenance. Fixed thresholds cannot learn or adapt to changing conditions, causing frequent false and missed alarms.

Product Advantages

Safe and Convenient

 

Remote real-time monitoring substantially reduces personnel exposure to dusty, noisy and slippery areas, improving inspection safety.

Intelligent Early Warning and Diagnosis

 

Self-learning alarms adapt to baselines and distinguish normal fluctuations from faults, substantially reducing false alarms. Real-time analysis supports warning, localization and deterioration assessment to enable predictive maintenance.

Data Visualization and Traceability

Trend curves, historical queries, alarm records and O&M reports with long-term storage support root-cause analysis, management assessment and production optimization.
Simple, Convenient On-Site Deployment

Industrial wireless/wired transmission requires no major equipment modifications, enabling fast installation and rapid commissioning.

Project Case

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