Intro
Intelligent Pick Wear Monitoring and Spontaneous Combustion Risk Mitigation Using Thermal Vision
Modern underground coal mining faces a constant balance between productivity, asset protection and safety. Nowhere is this more evident than on continuous miners, where worn cutting picks not only reduce cutting efficiency but also introduce serious ignition and spontaneous combustion risks.
JMB Automation has developed an advanced continuous miner pick wear and temperature monitoring platform using FLIR thermal imaging technology, real-time analytics and PLC integration to provide early warning of abnormal pick behaviour, overheating and spark events.
The result is a production-ready monitoring system that improves cutting performance, reduces unplanned downtime and assists in the mitigation of spontaneous combustion (Spont Com) risk.
The Challenge: Pick Wear, Heat and Ignition Risk
Continuous miner picks operate in one of the harshest environments in mining. As picks wear, cutting efficiency drops, friction increases and temperatures rise. This creates multiple operational risks:
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Reduced cutting rates and higher power consumption
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Increased mechanical stress on cutting drums
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Accelerated pick and holder damage
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Elevated ignition risk from overheated steel
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Increased probability of spark generation
In coal seams with known spontaneous combustion risk, unmanaged heat sources and ignition events can have serious consequences.
Historically, pick condition has been managed through:
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Visual inspections
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Fixed maintenance schedules
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Operator feedback
All of which are reactive and subjective.
What has been missing is continuous, objective, real-time condition monitoring.
The Solution: Thermal Vision-Based Pick Intelligence
JMB Automation’s pick wear platform uses FLIR thermal cameras mounted on the continuous miner to continuously monitor cutting drum temperature profiles during operation.
Thermal vision allows the system to see what standard cameras cannot:
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Individual pick temperature
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Abnormal heat signatures
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Hot spots on cutting drums
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Friction-related temperature rise
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Ignition and spark events
This data is processed in real time using JMB’s edge analytics platform and integrated directly into the machine control system.
How the System Works
1. Real-Time Thermal Monitoring
FLIR thermal cameras capture continuous thermal imagery of the cutting drums and pick assemblies during operation.
Each pick generates a distinct thermal signature. As wear increases, friction rises — and temperature follows.
2. Pick Wear Analytics
JMB’s analytics engine tracks:
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Absolute pick temperature
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Temperature rise rate
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Thermal variance across the drum
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Hot spot persistence
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Abnormal thermal patterns
Over time, this builds a thermal wear profile for every pick position on the drum.
This allows the system to identify:
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Rapidly wearing picks
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Broken or missing picks
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Failing holders
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Abnormal friction zones
Before they become a mechanical or safety issue.
3. Spark Detection and Ignition Events
Thermal and visible spectrum data is also used to detect:
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Spark events
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Friction ignition
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Abnormal flash events
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Hot debris ejection
These events are automatically logged with:
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Time
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Machine location
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Cutting conditions
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Thermal context
This provides both real-time alarming and long-term risk analysis.
4. Spontaneous Combustion Risk Mitigation
By tracking thermal energy at the cutting face and detecting ignition events, the system provides a new layer of protection against spontaneous combustion.
The platform can:
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Alert operators to abnormal heat generation
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Flag elevated ignition risk zones
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Provide early warning of unsafe cutting conditions
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Feed directly into site TARP frameworks
This transforms Spont Com management from reactive investigation to proactive control.
Integration with Machine Control Systems
The platform is fully integrated into the continuous miner control system via PLC and industrial networking.
This allows:
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Real-time alarms in the operator cab
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Automatic event logging
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Trending and reporting in SCADA
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Integration into maintenance systems
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Site-wide visibility through dashboards
The system operates entirely on-site with deterministic performance — no cloud dependency required.
Turning Data Into Decisions
Over time, the system builds a complete digital history of:
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Pick wear rates
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Drum thermal behaviour
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Cutting conditions
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Spark frequency
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Ignition events
This enables:
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Predictive pick replacement
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Optimised cutting parameters
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Reduced unplanned downtime
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Lower maintenance costs
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Improved safety compliance
Maintenance becomes condition-based, not calendar-based.
Built for Underground Production
Like all JMB Automation platforms, the pick wear monitoring system is engineered for underground mining:
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Industrial-grade hardware
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Vibration and dust tolerant
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Low-light and zero-light capable
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Deterministic real-time processing
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Fully supportable on site
This is not a lab prototype — it is a production system.
The Future of Intelligent Cutting
As mining moves toward higher levels of automation, condition monitoring and digital twins, systems like intelligent pick wear monitoring become foundational.
They provide:
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Machine-level intelligence
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Risk-based decision making
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Data-driven maintenance
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Real-time hazard detection
And most importantly — a safer cutting environment.
Driving Safer, Smarter Mining
JMB Automation continues to develop intelligent automation platforms that combine traditional PLC control with machine vision, AI and real-time analytics.
Our continuous miner pick wear system is another example of how smart automation is reshaping underground mining — improving safety, productivity and operational certainty.
