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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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Manufacturer's Warranty. Tecno Industries (Reg) اَلحَمْدُ لِله Manufacturers of: SERVO MOTOR controlled, Automatic Voltage Stabilizers & Regulators. (pure copper) Since 1986 Tecno Lazer Pakistan. 0300-9433728 Ring Road, Band Road, Lahore Pakistan. A Servo Stabilizer That Decreases 30 Volts (back-from 250 to 220 & Increases 70 Volts from 150 to 220) (±) 1% {CAN STEP-UP from even low (on-demand)} اَلحَمْدُ لِله Runs your Equipment Even in Low Main Voltage. INFORMATION: 1: ( An Old Transformer / Relay carrying Stabilizer steps down or up after losing or gaining 20-25 Volts While A Servo Stabilizer steps down or up after losing or gaining 1 Volt. (±) 1%) 2: (on-demand) Buck-Boost Transformer Technology add-in 2kVA and above Models. Basically they work on DC Servo Motor Control system. Their efficiency is much better and its output voltage of either 110 or 220 AC or any required voltage, more-over TECNO 3Phase models up-to 500kVA ratings are manufactured against a confirmed order. 1 year warranty with parts. 100% genuine copper winding (GUARANTEED) Specs for (intelligent Voltage Stabilizer): SERVO MOTOR controlled, Automatic Voltage Stabilizers & Regulators. Input Voltage : 150 To 250 AC Output Voltage : 110v & 220v AC (±) 1% Frequency : 45 or 60 Hz Wave Form : Non-distorted Sine-wave Response Time : 25ms / V Efficiency : 95 % Power Factor : 0.95 Relative Humidity : 30% to 80% (without condensation) Temperature Rise : Less Then 50c Control System : DC. Servo Motor Insulation Resistance : More then 3M?? at 500V DC Tested : 1500 V We Manufacture Servo Motor Controlled Automatic Voltage Stabilizer, using Japanese technology, for UPS, Solar, AC Air-Conditioner, Split-Type, Window Type, (LCD/LED TV) Washing Machine, Treadmill, Photocopier Machine. Television, Music System, Refrigerators, Ultra sound Machines, Embroidery Machines, All Sensitive Equipment, Signalling Devices, CNC Machines, Air Conditioning Plants, Telecommunication Networks, Motor Loads, Data Processing Equipment, Bio Medical Equipment, Drives, PLC’s, Induction Heating, Hotels, Defence Application, Industrial Units, Lighting Loads, Residential/ Offices, Farm Houses, R & D Institutions, Mainline Stabilizers, Sophisticated Laboratory Equipment etc. Runs your Appliances Even in Low Main Voltage. وولٹیج سٹیبلائزر Standard Power Ratings Available in Single-Phase & 3-Phase: 500VA, 1kVA, 2kVA, 3kVA, 5kVA, 10kVA, 30kVA. Up-to 500kVA Punjab NWFP, KPK, & All Pakistan Cargo, Feel Free to Call: Rana Naeem Hammad. M.D. Tecno Industries (Pvt) Ltd Lahore. +923009433728

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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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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

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