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Overview The mold is a device that shapes the cast product in continuous steel casting, and it is also the core equipment and key technology of continuous casting machine. The main function of the mould oscillation deflection detection instrument is to detect the the mould oscillation table’s oscillation frequency, amplitude, deflection rate, phase, oscillation trajectory curve, etc. Through the detection and adjustment of the detection instrument, the mold moves along the outer arc of the continuous casting machine according to the set amplitude, frequency and waveform deflection characteristics. The actual oscillation parameters of the mold oscillation table during the production process and the process parameters of the cast products cannot be effectively known without the data detection of the mold deflection detection instrument, so that the operator cannot adjust the mould’s production process parameters in real time according to the real-time situation of the on-site production. The continuous casting mold deflection detection instrument independently developed by our company is suitable for various molds such as slab, square billet, round billet and shaped billet. The system obtains the process parameters such as actual oscillation holographic parameters and negative slip amount of the oscillation table by effectively detecting the movement of the mold. The technicians can formulate the control strategy of the mould according to these actual parameters, and improve the output and quality of the product within a safe and reliable range. The structure of the instrument Continuous casting mold oscillation and deflection detection instrument is mainly composed of sensor system, sensor signal conditioning circuit, power supply circuit, synchronous data acquisition module, communication cable, and software data analysis system. There are three axial acceleration sensors installed in the mold oscillation and deflection detection instrument, one of which is to detect the vertical oscillation signal (Y axis), and the other two are to detect the horizontal oscillation signal (X and Z axis). The signal obtained by the sensor is processed by the preprocessor and the preprocessing module. The oscillation signal and sensor status signal will be filtered and normalized, sent to the synchronous data collector for digitization and feature extraction, and the data is analyzed and processed by the master computer software to obtain various oscillation parameters and process parameters required by users. The functions of the system 1. Adopting mould oscillation X/Y/Z three-dimensional data acquisition, using high-precision sensor system and high-sensitivity axial accelerometer, comprehensive detection of equipment oscillation state, including: 1) Detect the oscillation frequency of the mold oscillation table 2) Detect the amplitude of the mold oscillation table 3) Detect the deflection rate of oscillation 4) Detect the lateral deflection, longitudinal deflection, phase, and phase difference of the mold oscillation table 5) Three-dimensional display of the oscillation trajectory, and the oscillation table trajectory can be viewed from 6 sides of the oscillation table (X-Y, X-Z, Z-Y) 2. The software system adopts the design of man-machine interactive graphic interface, which can display the mold oscillation state in real time. The software functions include: 1) Real-time data curve display: oscillation waveform, oscillation frequency, signal superposition analysis 2) Single-axis curve display, multi-axis curve display, amplitude, acceleration, three-dimensional graph 3) View historical curve 4) Generate test report 5) Give a warning prompt 6) Spectrum analysis function 7) Long-term storage of data 3. Portable measurement method, which can provide handheld detection equipment with wireless remote transmission, and the operation is simple. 4. Provide an overview of inspection parameters under the full screen, displaying all data including oscillation parameters and process parameters. At the same time, the calculation and display of the oscillation spectrum is completed in real time, which is used to evaluate the frame loss of the waveform , and to determine whether there is a problem with the installation of the oscillation device. 5. Alarm management. Record each alarm data under real-time alarm conditions to analyze the cause of the alarm and evaluate the impact of the alarm on production. 6. Parameter setting. Users can set the ideal oscillation value and normal working range of various steels online. We also can set the alarm limit, and the storage time of the database etc. 7. After charging the device once, it can work continuously for more than four hours. 8. Integrate embedded processing equipment to realize data collection, display, analysis, reporting and other functions. 9. According to the mold characteristics and user requirements, it can be flexibly configured, wich is suitable for all types of molds such as square billets, slabs, round billets and other mold oscillation tables. 10. Support wired and wireless data transmission functions, easy to use. 11. Use the laptop to receive the collected data, can be used for the operation test on site, and can analyze and process the data conveniently. The features of the system 1. The actual oscillation state replaces the ideal oscillation state. The actual oscillation state of the table is used to formulate a control strategy, so that the oscillation table can be used to produce products with more accurate oscillation. 2. Convenient detection method. The equipment can be used for on-site inspection at any time, and the production site can grasp the operating status of the on-site equipment in time, so that we can make production adjustments to the equipment at any time. 3. Efficient working methods and processing platforms. The high-integration equipment developed by embedded technology can work in high temperature and harsh environment. This system can comprehensively detect XYZ three-axis data, and realize real-time data analysis and processing with high-speed data operation and processing platform. 4. Powerful database function. The database adopts the mode of computer automatic management and operator's manual assistance management, and there are tables for recording historical data and alarm data and working parameter setting table of monitoring system inside the database. By adjusting the output range, the best output effect can be obtained.

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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%

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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.

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

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