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Overview The infrared converter slag detection system uses a far-infrared thermal imager to monitor the situation of converter tapping in real time, and is connected to the main control computer in the electrical room through the conversion and transmission of video signals. The radiation intensity in the infrared wavelength range of 7-14um is different to distinguish molten steel and slag. In the later stage of the converter tapping, the molten steel gradually decreases, and the steelmaking slag is involved in the molten steel and flows out of the tapping hole. After the thermal imager recognizes the steelmaking slag in the imaging temperature measurement, it will give an alarm according to the slag content ratio threshold set by the software. The thermal imager will start the slide plate to close the tapping hole, so as to realize the control of the slag in the converter tapping, and ensure the maximum yield of molten steel and the minimum control of the steelmaking slag content. The effect of slag detection in converter tapping is of great significance to the control effect of the slag amount. The converter slag detection and control system developed by our company conducts non-contact monitoring of the tapping steel flow through the far-infrared detector thermal imager. It can detect the slag condition in real time and output an alarm signal and control system, which can replace manual visual inspection and provide accurate, efficient and stable slag detection effect. When the system finds the slag, the intelligent control unit quickly makes a judgment of lifting the furnace and blocking the slag and outputs an alarm signal. As shown in Figure 1, the system includes thermal imager, front purge protection box, front electrical box, power distribution cabinet, main control monitor, monitor of rocking furnace chamber, sound and light alarm, infrared converter slag monitoring software system, etc. The features of thermal imager 1. The temperature measurement range is 200°C ~ 2000°C, high temperature measurement accuracy, and multiple temperature measurement intervals can be set. 2. High-resolution thermal imaging system, the imaging picture is clear, and the imaging color can be freely marked according to the set temperature. 3. With hot zone alarm function, the alarm zone and temperature range can be set arbitrarily. 4. With hot zone tracking function 5. Equipped with special 7~14um infrared filter lens The technical parameters 1. Temperature measurement range: 200°C ~ 2000°C 2. Temperature measurement accuracy: 2% 3. Detection accuracy and alarm accuracy: ≥98% 4. Resolution: ≥ 0.5℃ 5. Pixels: 640x240PT 6. Band: 7~14um 7. Field of view: 7.5°×5.5° 8. Frame rate: ≥ 25 frames/sec 9. Equipment service life: ≥5 years 10. The normal operation rate of the automatic control system: ≥99%

The composition of the system The photoelectric strip automatic center position control system is mainly composed of sensors, amplifiers, PLC controllers, hydraulic control and other parts. System composition block diagram The main technical parameters 1. Detection width: 300-2800mm 2. Detection light source: 220VAC. (100VAC) 30W. High frequency white light works continuously 3. Photodetector: precision die-casting components, time constant 20ms 4. Maximum working voltage: 50VDC 5. Distance from receiver to emitter: 300-1000mm 6. Operating temperature: 0℃-60℃ 7. Resolution: 0.5mm 8. Linearity: ±1%F.S (after linearization) 9. Repeatability error: △R1%, F.S 10. Servo-valve working signal: ±10V 11. Rated pressure (oil pressure): 4.5Mpa 12. Rated flow: 30L/min 13. Symmetry: 10%

Overview: The BPS-K600 continuous casting mould breakout prediction system is developed by Wuhan CenterRise M&C Measuring Co., Ltd. It adopts artificial neural network and combines with traditional artificial intelligence and information processing technology to overcome the defects of traditional logic-based prediction models. It has the functions of self-adaptation, self-organization and real-time learning. The breakout prediction system has an optimized industrial network structure. According to the distribution and change rules of the temperature field of the mold, it can track and respond to the breakout process in real time. It can learn and judge by itself, and provide early warning information for on-site operations. It can effectively prevent the occurrence of breakout accidents, greatly reducing the cost and improving the safety factor of continuous casting. The system is suitable for all kinds of continuous casting machines such as square billet, round billet, rectangular billet and slab. Block Diagram of Breakout Prediction System The composition of the system Thermocouple: according to the on-site conditions of the mold, water tank, bolts and mold frame to desgin Front-end acquisition system: Multi-module acquisition chain, industrial Ethernet interface, high-speed embedded processing module Working platform: Real-time display of mold temperature field status, online analysis and prediction of mold breakout Server: Data exchange and storage management, reporting and printing system, with data analysis and self-learning functions The Main technical parameters Data sampling: the sampling frequency of K-type/T-type thermocouple can up to 10HZ Accuracy of temperature measurement: ±0.25℃ Support communication protocol: Industrial Ethernet (TCP/IP)，PROFIBUS-DP，CANopen Executive standard: DE0411 Standard Class III/1EC584/IEC1515 Transmission speed: 100M/bps The composition of the software Online monitoring software for breakout prediction Offline query software for breakout prediction Data recovery and self-learning software packages Data acquisition and monitoring software The software package of mold thermal status display The functions of the system Real-time data acquisition, data analysis and judgment Automatic selection of steel grade’s alarm parameters Real-time dynamic picture monitoring Prediction alarm and information display of breakout signs Automatic deceleration after alarm Historical data storage and historical trend graph display Automatic report generation and printing Alarm prediction and pattern recognition of unknown steel grades by neural network Dynamic real-time temperature profile prediction Mould heat flow field display FIG 1：Typical process of mold breakout prediction The features of the system 1. Reasonable design of temperature measurement point and professional protection front-end acquisition system, and complete installation and calibration tool components. 2. The system has strong adaptability and can meet the transformation of various structural continuous casting machines. 3. High-speed data communication, using industrial network to form an independent local area network for each workstation and server. It can realize high-speed data transmission of alarm files, alarm parameters, and other databases. 4. The combination of artificial neural network and intelligent forecasting model improves the alarm accuracy of breakout forecasting. 5. Historical data storage and historical trend graph display, historical reports, historical alarm legend printing, real-time alarm data printing. 6. Provide a local area network interface, which can realize the storage and forwarding of alarm files, and the input and output of offline alarm data. 7. Remote Web browsing can be achieved according to customer needs. 8. Can be seamlessly connected with MES-C220 mould expert system.

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