In the Plant Production Environment Furnace, maintaining consistent temperatures is critical for efficient operation and preventing damage. The furnace uses burners to maintain the required heat, and any internal issues, such as fallen bricks, can cause localised temperature spikes, which may signal a problem. Monitoring these temperature fluctuations is essential to avoid furnace damage and operational downtime.
Key Features
01
System Configuration
• Thermal Cameras: A series of thermal cameras are positioned at the circumference of the cylindrical furnace, approximately 1 to 2 metres from the surface. These cameras are arranged to provide a full view of each burner and the surrounding walls, ensuring complete coverage of the furnace. Each camera captures both the burner and adjacent left and right sections of the furnace wall.
• AI-Based Temperature Monitoring: The thermal cameras continuously capture Images and send them to an AI server via optical cables. The system processes these thermal images to detect any temperature anomalies.
02
Temperature Monitoring and Alerts
The system records the furnace's temperature every 15 minutes and raises alerts under the following conditions:Monitor a live view of the inspection process.
1. Rising Temperature Trend: If a gradual increase in temperature is detected over time, indicating potential issues such as brick displacement.
2. Sudden Temperature Spike: A sharp rise in temperature is flagged as an urgent issue, potentially indicating immediate damage or malfunction.
3. Exceeding Configured Temperature Threshold: If the temperature surpasses a user-defined limit, an alarm is triggered.
When any of these conditions are met, an alert is raised, a hooter sounds, and the system records the event with a timestamp in the database for further analysis.
03
Predictive Incident Detection
The system includes a prediction algorithm that analyses historical temperature data to forecast potential incidents. By identifying patterns in the data, the algorithm can detect conditions that may lead to future incidents, allowing operators to address issues before they escalate.
Conclusion
The Plant Production Environment Furnace Temperature Monitoring System provides real-time monitoring and predictive analysis to ensure the smooth operation of the furnace. By integrating thermal cameras, AI-based detection, and a predictive algorithm, the system helps detect and prevent issues like brick displacement and temperature spikes. The user interface gives operators live insights, trend analysis, and detailed defect logs, improving both furnace safety and operational efficiency.