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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 LDT-I200 is a new generation of converter lining thickness gauge launched by our company. The system equipment emits a pulsed laser beam to the lining surface of the converter, and receives the returned laser light to measure its flight time. Then the system equipment calculates the distance between the equipment and the target point according to the transmission speed of the laser. During measurement, the user pushes the equipment to a certain position on the platform in front of the converter, and the equipment can start to scan and measure the target area of the converter after the equipment performs rapid self-positioning. The Measuring principle The measurement speed of LDT-I200 can reach up to 2,000,000 points per second, and each scan can obtain distance data of more than 1.5 million points. The actual surface curve of the entire converter lining can be obtained by combining the measurement data of different positions and angles. During the measurement, the laser head of the equipment rotates at a certain step angle to rapidly change the angle of the pulsed laser beam. Within 4 minutes, the three-dimensional surface contour of the converter lining can be formed, and the thickness information of the furnace lining can be obtained through coordinate conversion calculation. The measurement accuracy up to ±2mm. In order to convert the distance from the internal point of the converter to the thickness gauge into the thickness of the furnace lining at each point, we must know the coordinate relationship between the trolley and the converter. We use the second laser head to position the trolley. When the trolley is pushed to the measurement site, the positioning laser head rotates at high speed to scan the three reflective strips opposite the converter. Through triangulation measurement and calculation, we can calculate the relative position of the trolley to the reflective strips. The coordinates of the reflective strip and the converter are known through mapping, so that the coordinates of the trolley relative to the converter can be accurately obtained. The main components 1. Laser measuring head 2. Wireless communication 3. Battery pack 4. Mobile laser thickness gauge host 5. Converter inclination measurement system 6. Cooling circulation system 7. Positioning auxiliary reflector 8. Laser positioning system The technical indexes Laser reproducibility: ±2mm Laser accuracy: ±2mm Local fastest measurement time: 15s Positioning time: 30s Full image measurement time: 4min The highest measurable lining temperature: 1850℃ Measuring distance: 0.5-25m Actual points are measured per frame: 1500000 points Continuous working time after fully charged: ≥3h Eye-safe laser: Class 1 laser product (doesn't hurt the eyes) The parameters of laser measuring head Measurement principle: According to the flight time and speed of the laser to calculate the distance Laser reproducibility: ±2mm Laser accuracy: ±2mm Scan rate: 2000000 points/second Measuring angle: vertical ±40°, horizontal 360° Maximum measurement temperature: 2200℃ Working temperature: -20℃-80℃ Cooling method: Integrated liquid cooling system, IP64 grade protection Laser wavelength: 1550nm (near infrared)

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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 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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