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Sintering Machine Tail Monitoring
Applications
Aug 04,2026
System introduction
The HIRDA-S series is a specialized device designed for high-temperature environments, enabling real-time monitoring of the sinter cake cross-section temperature at the sintering machine tail. The system consists of an infrared thermal imaging core, a high-temperature-resistant infrared thermal imaging lens, an automatic retraction protection device, a kiln wall mounting kit, an air filtration system, a field equipment box, an algorithm server, and intelligent temperature measurement software. Currently, the following issues are encountered in sintering machine tail detection: traditional lenses are prone to damage and contamination in high-temperature, high-dust environments. Cooling anomalies risk equipment burnout and massive losses. Manual cross-section judgment is subjective, compromising sinter quality stability. The use of our advanced infrared thermal imaging camera can effectively address these problems.
Product features
1. Infrared image acquisition of the sinter cake cross-section and temperature distribution display.
2. Analysis of sintering machine tail cross-section related information.
3. Establishment of a trend model for FeO content variation in sinter.
4. Endoscopic high-temperature-resistant stainless steel protective housing, capable of extending deep into the tail hood for data acquisition.
5. Retraction length is customizable according to wall thickness.
6. Spiral air curtain design prevents dust accumulation on the lens.
7. Automatic retraction protection device with fault indication when retracted.
8. Automatic retraction in case of overtemperature, undervoltage, or power failure.
Application
This equipment is mainly used for infrared thermography temperature detection and analysis of a sintering machine tail in high-temperature environments.
Equipment value
1. Transforming experience-based judgment into precise quantification to enable scientific prediction of the sintering endpoint: Converting manual observation of the machine tail cross-section into infrared image feature data, combined with the FeO prediction model, to scientifically adjust trolley speed, bed depth, and fuel ratio, which are important factors affecting the quality of sintered ore.
2. Moving process control forward, upgrading from "post-production inspection" to "in-process intervention": Continuously capturing cross-section images with real-time analysis to predict product trends and intervene in abnormal conditions before sintering is completed, while effectively reducing solid fuel consumption through optimized ignition and fuel ratio, directly addressing the pressure of high raw material prices.
3. Building a data closed-loop to empower intelligent production management: Accumulating cross-section images and quality data to support process optimization, quality traceability, and model iteration, driving sintering production from experience-driven to data-driven intelligent decision-making.
Case
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