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Overview： This product is a new type of mold copper plate surface detection equipment. The equipment adopts a high-precision and high-sensitivity laser ranging sensor, which scans the copper plate of the mould by scanning a laser line with a fixed width, and returns the measurement data in real time. After modeling and analyzing the data, the upper computer gives the wear data of the mold copper plate, as well as the data of surface cracks and surface flatness. The host computer software intuitively reflects the surface profile of the detected mold and thickness deviation and other data to the user in the form of data sheet, data curves and mold 3D model diagrams, providing a true and reliable theory for on-site operators to maintain the mold. The mold surface detection equipment is a high-precision instrument, which includes high-precision laser ranging sensors, two digital servomotors, encoders, horizontal sliding screws, vertical sliding screws, and calibration consoles, controllers and other components. The equipment has many advantages such as high accuracy, strong stability, convenient installation and strong observability. It is suitable for mold surface detection, surface flatness analysis, surface flaw detection, taper measurement, etc. It is also suitable for round billets, square billets, slabs, special-shaped billets, etc., widely used and powerful. The composition of the system： 1. The mold surface detection equipment is equipped with: data processing and display unit, horizontal motion mechanical power output unit, vertical mechanical power output unit, instrument motion control unit, laser measurement sensor, and instrument bracket. 2. Data processing and display unit: used for data acquisition and storage, system equipment control, parameter configuration, height display of the descent, start and stop control, etc. 3. Horizontal motion mechanical power output unit: the digital servo motor in the horizontal direction controls the sensor to move in the horizontal direction, so that the sensor can scan the horizontal inner cavity wall of the mold copper plate to detect data. 4. Vertical mechanical power output unit: the digital servo motor in the vertical direction controls the sensor to move in the vertical direction, so that the sensor can scan the vertical cavity wall of the mold copper plate to detect data. 5. Instrument motion control unit: It is used to control the motion scanning of the motor, and the running speed, running track, and control mode of the motor can be configured through parameter settings. 6. Laser measurement sensor: The laser displacement sensor adopts the principle of laser triangulation. The laser transmitter shoots the visible infrared laser to the surface of the measured object through the lens, and the laser reflected by the object passes through the receiver lens and is received by the internal line array image processing sensor. According to different distances, the corresponding positions of the light spots received on the line array sensor are also different. According to the angle of this reflection, the distance between the actual objects can be calculated by calculating the distance of the sensor spot. 7. Instrument bracket: The mold surface detection equipment need to be placed directly above the mold when it is in use, and it is required to be fixed firmly without displacement vibration during the measurement process to ensure the measurement accuracy. The parameters： Detection instrument service life: ≥5 years; Detection instrument reliability: more than 98%; Detection range: 60~1000mm (customizable) Detection accuracy: 0.01mm Spot diameter: 1.0x1.5mm (spot scan), 1.0x20mm (line scan) Falling pace: 1~20mm/step Single measurement time: less than 2min Power supply: DC24V Operating temperature: -20~80℃ Equipment warm-up time: 3~5min Shock resistance: 50G (X, Y, Z axis) Vibration resistance: 10Hz~5Hz (amplitude 1.5mm, each 2 hours in X, Y, Z axis)

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Overview： Mold powder is mainly used in the continuous casting and steelmaking process, evenly sprinkled on the molten steel surface in the mold to lubricate, keep warm, prevent oxidation and absorb non-metallic inclusions. Mold powder is an indispensable auxiliary production material in the production process. In the process of evenly distributing the mold powder to the molten steel surface of the mold, the amount of mold powder should be controlled, and the thickness of the mold powder should be within a certain range. If the coverage thickness of the mold flux is too thin, it will cause no heat preservation, oxidation of molten steel, inclusions, cracks, large drawing resistance, steel leakage, etc. At the same time, the coverage thickness of mold flux should not be too thick, they can’t melt in time with too much mold powder, if the molten steel is churning, it is easy to get the mold powder into molten steel at this time, resulting in mold leakage. Therefore, the amount of mold powder must be controlled within a reasonable range. The detection and control of mold flux thickness is very important, especially for the steel plants which are strict with the steelmaking production process. The detection principle： The mold flux detection system developed by Wuhan CenterRise M&C Engineering CO., Ltd. uses the laser triangular sensor fixedly installed above the mold to obtain the height h1 by scanning the upper surface layer of mold flux with high-precision laser triangulation. When the laser measuring head is placed each time, the height h3 of the upper nozzle of the mold will be marked, and the system through the PLC system which is connected to the continuous casting machine through the network to introduce the height h1 of the mold liquid level. Through the calculation of three heights, we can get the thickness of mold powder H = 900-h1-(h3-h2)mm (900mm is the depth of mold). The features： The system adopts a high-precision laser triangulation distance meter, which can measure the thickness of the mold flux with high speed and high precision, and the accuracy can reach 1mm. The equipment is easy to install and use. When we are using, the laser rangefinding sensor can be placed directly above the mold without affecting production. The system can be interlocked with the automatic mold powder feeding system to automatically adjust the amount of mold powder, so as to automatically control the amount of mold powder within a reasonable range and realize intelligent automatic mold powder feeding. Non-contact measurement, the system only needs ventilation protection, simple and stable to use. The parameters： Measurement range：0-50mm Temperature measurement range: -20℃-700℃ Equipment installation distance：750mm System measurement accuracy：1mm Laser measurement accuracy: 0.1mm Frequency: 700-2000Hz Cooling method: air-cooled purging Installation method: rail sliding installation, can be slid out during maintenance Storage period: data can be stored for more than 2 years Communication method: Industrial Ethernet or Profibus-DP

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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