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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)

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 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.

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