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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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Overview The system realizes the fixed-length measurement of the width, thickness and length of the continuously cast product through machine vision and laser rangefinding system. The measured data is transmitted to the host system through the optical fiber. The host system calculates the weight of each billet according to different steel grades and specific gravity, so that we can realize the fixed length measurement and fixed weight control of the cast products and the precise control of the steelmaking process in the production process. After cutting the billets by fixed weight and length, the fixed weight cut-to-length system is checked by the online weighing measurement system, so as to give feedback to the fixed length model of control system. The slab number (automatic checking) can also be automatically identified online by using machine vision, and the weight and slab number can be automatically stored in the local database for use in the production and management system. The measuring principle of the system On the upper surface of the billet, a set of linear CCD cameras and a laser rangefinding instrument are respectively installed. Through machine vision and laser correction, we can achieve precise measurement of the cast products’ shape. Through accurate cast products’ shape monitoring, the billet thermal expansion coefficient of cast products and cast products’ density at the current temperature, we can obtain the quality of the billet. At the same time, we can achieve high-precision quality cut-to-length , namely, fixed-weight and fixed-length. The system can be matched with the weight detection and calibration system. The system adopts the online barrier-free hidden integral roller table weighing method for continuous casting products, and connects its weighing data into the intelligent control model. The model and steel billet weighing system, and the fixed weight cut-to-length system realize the closed-loop control of the system model, and optimize the fixed weight accuracy through automatic signal collection. The features of the equipment The cutting control technology for fixed-length and fixed-weight of cast products is a concrete manifestation of the lean production management of steel products. In the era of high-quality competition of steel products, only high-end intelligent technology and management can reduce costs, improve quality and market competitiveness. 1. Data management can be carried out according to shifts, pouring times, days, weeks, months, etc., as well as data management according to specifications, production capacity, quality, etc. 2. Each stream can send out signals such as pre-clamping, clamping, cutting, roll-up, roll-down and return of the cutting car according to the user's requirements. 3. The detection and cutting precision is high, the controllable length sizing accuracy is ±1mm, and the quality sizing accuracy is more than 1.5‰. 4. It is not sensitive to other high-intensity light interference, and overcomes the influence of light sources such as sunlight and arc welding. 5. The monitor displays the running status of the current hot billet in real time and displays the corresponding parameters. 6. Laser rangefinding and CCD machine vision are used to calculate the weight of the cast products and optimize the cutting to length. 7. Historical cutting data is automatically stored, and the system can set rules for historical data. 8. Support the free transformation of fixed length, and a variety of operation modes are available for the operator to choose. 9. Adopt advanced high temperature laser measurement and high pixel linear CCD technology. 10. The system provides abundant interfaces, which can communicate with the PLC control. 11. Applicable to all kinds of continuous casting machine flame cutting system. 12. Provide automatic, upper and manual cutting control. The main technical requirements 1. Width range of the inspected cast product: 120~2000 mm 2. Length range of the inspected cast product: 1000~20000 mm 3. Thickness range of the inspected cast product: 35~400 mm 4. Steel billet moving speed: 3.5 m/s 5. Billet running speed: 6.5m/min 6. Temperature of the measured steel billet: 0~850 °C 7. Measurement accuracy: width ±0.2mm thickness ±0.2mm length ±0.2mm 8. Fixed weight accuracy: 0.8‰ (temperature model verification) 9. Quality inspection check: 1‰

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