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Specification Used Electric Motor Scrap sealed units purity: 99.97% with connection box consist of aluminum case, with full copper content inside voltage220/440 voltage 50 or 60 hz. Size : 100 -500 cm3 power 2 Hp to 40 Hp Three phase Compressor weight: 6Kg, 8Kg, 10Kg, 12Kg 14kg 20kg -22 kg 40kg material : oil drained, comes copper Inside bulk quantity available for more details inbox me or contact us via email at baicuscrapmetalltd@gmail.com or add us on whatsapp +447918 245841

We have the Outboard Boat Engine OXE. Yamaha We are specialized in the sales of full metal scrap/ recycling material such as ac/fridge compressor , Ceramic Cpu Gold Processor Scraps , H.M.S 1&2, Copper wire scrap,Drained Battery Lead scrap in the UK (LONDON).We have all our product fully ready for sales in good quantity and quality also to be shipped out for our buyers.For Booking : https://wa.link/og0sgp Whatsapp: +15806151130

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Overview: LGK-S107 analog heat source instrument (heating tool) is independently developed and designed by Wuhan CenterRise M&C CO., Ltd. This instrument is a heating and testing equipment used to test the performance of the thermocouples installed in the mold in continuous casting machine. After the installation of the mold breakout prediction thermocouples completed, the analog heat source instrument is used to test these thermocouples before they go online. After the thermocouple is connected to the mold thermocouple detector, the current temperature of each thermocouple point will be displayed. By using our heating device to heat the copper plate point of each thermocouple at a fixed point, the thermocouple will have a synchronous temperature rise and then we can observe the temperature rise curve of the same column of temperature points to see whether the temperature measurement consistency of the column of thermocouples is consistent, so as to judge the overall status of thermocouples installed in the mold. If an abnormal point occurs, it needs to be repaired and replaced, so as to ensure the stable operation of the mold breakout prediction system. The working principle: The heating tool generates high heat by 220v alternating current and the electric heating element. The heat is transmitted to the copper plate of the mold through the copper head to simulate the heat source of molten steel, so that the thermocouples of the mold can sense the temperature change to achieve the purpose of calibrating the temperature measurement system. The composition: Walking trolley mechanism Preloader Pure copper heating contacts PID thermostat High power heating tube high power driver The parameters: Power supply: AC220V 50Hz Total power: 2200W Single point power: 300W Temperature control accuracy: 1°C Temperature control range: 0°C-500°C Common temperature range: 25°C-300°C Heating points: 3 (points can be customized) Heating method: heating tube heating Heating contact material: copper

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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