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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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Overview: In the steelmaking production process, the ladle is the key equipment for holding molten steel, secondary refining, and continuous pouring. In a modern steelmaking plant, refractory materials are required for converters, refining, and ladles. In the steelmaking process, ladle is the main equipment for using and consuming refractory materials. Improving the service life of ladles and reducing refractory consumption is the key technology for steelmaking plants to save costs and reduce energy consumption for green production. In order to ensure the orderly operation of the ladle, save the consumption of refractory materials, prolong the service life of the ladle, and ensure the safe operation of the ladle, Wuhan CenterRise M&C Engineering CO. developed and launched the LDT-N200 integrated management system for the ladle. Introduction: LDT-N200 ladle integrated management system integrates LDT-L200 ladle lining thickness gauge, TBP-S300 ladle, tundish baking temperature and leakage monitoring system, RFD -C100 metallurgical electronic positioning system, and also integrates SQL Server database and NeuralWare (American computer software company) neural network software NeuralWorks to realize intelligent and optimized management of ladles. LDT-L200 ladle lining thickness gauge uses a laser area array scanning sensor to accurately measure the real-time thickness of the ladle lining, calculate the lining loss, and predict the service life of the ladle. TBP-S300 ladle, tundish baking temperature and leakage monitoring system uses infrared thermal imaging camera and embedded armor wire system to comprehensively monitor and prevent ladle leakage. RFD-C100 metallurgical electronic positioning system installs RFID electronic tags on all ladles to realize full-time and full-space ladle positioning and tracking. LDT-S200 ladle optimization control and analysis software, based on SQL Server database, B/S network structure, realizes online management of ladles, and adopts BP neural network system to realize intelligent optimization control of ladles. LDT-N200 ladle integrated management system can realize ladle age management based on ladle lining data and neural network algorithm, safety process control of ladle turnover and use, full-time tracking management of steelmaking production and full-space tracking management of ladle use and provide optimal control and management of steelmaking production and ladle maintenance. Comprehensive ladle measurement and monitoring, ladle positioning and management, and data management and optimization enable the LDT-N200 ladle integrated management system to fully realize ladle entire process management, optimize the service life of ladles, and comprehensively reduce the cost of refractory materials. The features: Using a lining thickness gauge to measure the thickness of the ladle lining Using infrared thermal imaging camera/embedded armor wire to realize ladle leakage detection Using RFID/number plate recognition to realize the location management of ladles Ladle age management system based on overall tracking Overall (full-time full-space) ladle management system based on database Provide overall production scheduling data Using neural network to predict ladle service life based on big data Ladle Optimal Scheduling System based on database and ladle service life Increase the service life of ladle by 12%-20% Reduce the use of refractory materials more than 15% Realize orderly management of ladle baking Realize full space and full time domain control Reduce the costs of ladle management and maintenance Improve the efficiency of ladle turnover operation

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.

Overview The surface quality inspection of high temperature cast product is of great significance to the repair of cast product’s defects and the hot delivery of hot cast product. The ZSQ-T series of online surface quality inspection equipment for casting billets developed by Wuhan CenterRise M&C Engineering Co., Ltd can detect the defects such as scratches, cracks, holes, pits, edge cracks, edge defects on the surface of the cast products, and meet the customer's requirements for the quality inspection of the surface of the cast product. The principle of the system The ZSQ-T200 online surface quality inspection system for continuously cast products adopts the principle of optical imaging and uses a CCD image sensor to input the surface image of the cast products to be detected into the computer, and then the obtained image is processed by special image processing software to find out whether there is any defect in the image. After the defects in the image are obtained, the obtained defects are classified through a special self-learning system, and finally the requirements of the computer to automatically identify the surface defects of the cast products are achieved. The composition of the system 1. Optical part: The optical part is composed of multiple fixed-focus lenses and linear CCD, which mainly realizes scanning and imaging of the surface of the cast products. 2. Lighting part: The lighting part is composed of a high-brightness LED array and a cylindrical lens, which realizes high-brightness and high-uniformity lighting on the surface of the cast products. 3. Mechanical structure part: The mechanical structure part mainly realizes the adjustment, installation and fixing of the optical part and the lighting part, and consists of the imaging head (optical part), light box (lighting part), bracket and control cabinet. The structure is required to be stable and reliable. 4. Real-time processing: The real-time processing part is completed by the multi-CCD data real-time sampling processing unit (high-speed DSP) independently developed by Wuhan CenterRise M&C Engineering Co., Ltd. 5. Hardware part: The hardware part consists of high-speed storage controller and storage hard disk array, Gigabit InternetMAC controller, Gigabit Ethernet PHY. Rj45, and multiple high-speed workstations. 6. Detection software: The detection software mainly realizes the functions of collection, storage, transmission, processing of CCD scanning images, extraction of defects, analysis of defect characteristics, calculation of defect size and position, storage of defect images, generation of cast product’s surface quality analysis reports. etc.