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ALUMINIUM USED BEVERAGE CANS SCRAP LOOSE BALED OF UK ORIGIN. Available quantity 500mt Minimum Order acceptable 25MT Will be loaded in a 40ft high cube container Weight per container will be approx 25 mt. Origin: United Kingdom Details Item Aluminium scrap UBC Attechment : 3% Purity: 97.9% Minimum Density : 14 Pounds Per Cubic ft (225 kg/m3) Smooth Surface Tight Tolerances aluminum scrap Easy control and operation Fast melting Discontinuous melting with scrap High efficiency Stable working structure Packaging & Delivery Packaging Detail: it comes in bales, or according to the customer demand. Delivery Detail : Within 21-25 working days after order confirmed A maximum of 3% of impurities to be considered.this is just an outer limited Specification: Aluminium UBC Beverage Cans Chemical Composition: Si: 0.2 – 0.6%, Fe: 0.35%, Cu: 0.1%, Mn: 0.1%, Mg: 0.45 – 0.9%, Cr: 0.1%, Zn: 0.1% Standard Conforming to: (C11000 (ETP) Content 99.90%) Origin: United Kingdom/ Europe Packing: In Bundles Quantity: 25MTS and up to 300 MT per month Shipment: 40FT Container for more details contact us via email at baicuscrapmetalltd@gmail.com or whatsapp +447918 245841

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Overview The automatic control for the molten steel level of the mold is one of the key technologies of continuous casting production. It is very important to reduce the labor intensity of workers, improve production efficiency, improve the quality and output of casting billet, reduce overflow and breakout of steel and improve the management level of steelmaking and continuous casting. The molten steel is poured into the mold. In order to prevent overflow, the molten steel level must be kept stable. Otherwise, during the casting process, if the level will fluctuate too much, and slag will be involved, forming surface slag inclusion on the surface of the casting billet, affecting the quality of the billet. The test points out that the relationship between the level fluctuation and the depth of casting billet surface slag inclusion is as follows: The experience has shown that surface slag inclusions can be eliminated when the level fluctuation is within ±10mm. At the same time, if the level fluctuation is more than 10mm, the rate of longitudinal cracks on the casting billet surface is 30%. It means that the level fluctuation directly affects the surface quality of the casting billet. The principle of the system The eddy current type molten steel level gauge is the key to the system. The system operates reliably and has excellent performance: high temperature resistance, strong anti-interference ability, fast dynamic response (lag time 0.10s), high detection accuracy (±05mm), and large measurement range (0-150mm). The selected electromagnetic field frequency ensures that the level detection probe only detects the level change of the mold and does not detect the mold flux or steel slag layer. The system has the advantages of simple operation and no radiation protection problems. The system is insensitive to argon blowing, and its sensors can be mounted on the tundish car or on the platform. The sensor is cooled by compressed air during use. The principle is shown in the figure A high-frequency exciting winding is installed above the molten steel surface of the mold. The high-frequency magnetic field generated by the high-frequency exciting winding induces eddy currents on the molten steel surface to form a magnetic field. The magnetic field generated by the induced eddy current is in the opposite direction to the magnetic field generated by the high-frequency exciting winding, which changes the impedance of the high-frequency exciting winding. Under the condition that the winding material and structure, steel grade, temperature remain unchanged, the coil impedance change only has a single-value function relationship with the height of the molten steel level. As long as the impedance change of the high-frequency winding is detected, the change of the molten steel level in the mold can be converted. The components of the system Continuous casting mold level automatic control system is composed of eddy current tyoe molten steel level gauge, controller and digital actuator for adjusting the opening of tundish stopper. The detection end of the mold level automatic control system is ① eddy current displacement sensor, which uses the eddy current mutual inductance effect between the energized coil and the metal conductor to detect the distance. The effective signal of the eddy current sensor is amplified and linearized by the circuit of ② mold level gauge, which converts the 0-150mm change in the molten steel level of the mold into a standard signal of 4-20mA.DC, and then transmits it to the ③ control computer to complete data processing and system control functions. We can also control the actuator manually and automatically through the ④on-site operation display control panel, and the opening of the stopper is controlled by the ⑤ actuator to realize the automatic control of the molten steel level. 1 Eddy current sensor; 2 mold level gauge; 3 control computer; 4 On-site operation display control panel; 5 digital actuator; The control principle of the system The system can be set to four control modes: automatic, semi-automatic, manual and motor clutch. The automatic mode is the closed-loop control system of the molten steel level, and control the opening of the stopper by the digital actuator; the semi-automatic mode uses opening degree setter and digital actuator to set the opening of the stopper manually; the manual mode is to open and close the button directly to control the opening of the stopper; the motor clutch mode is quickly changed from any of the above control methods to manual stopper operation. The functions of the system also include: display and record of molten steel level, nozzle opening and casting speed; setting of molten steel level and nozzle opening; alarm of molten steel level at limit value etc. In addition to taking the detection of molten steel level as the main feedback signal of the control system, the control system also considers various interference factors that have an impact on the level control. These interference factors include: 1. The influence of the change of the flow characteristics on the control system after the melt loss of the stopper 2. The influence of the weight change of molten steel in the tundish on the control system 3. The influence of the change of the casting speed of the continuous casting machine on the control system 4. The influence of the mold width change (the mold width is adjustable) on the control system 5. The influence of the vibration frequency and amplitude of the mold on the molten steel level gauge The function and software implementation In order to overcome these disturbances, the mold level control strategy adopts PID control. And on the basis of PID control, self-adaptive correction and feedforward control are introduced to form an advanced control system. The level control is the main loop, and there is a proportional gain of the main loop controller. According to the self-adaptive correction of the mold width change and feedforward compensation of casting speed, so as to further reduce and eliminate liquid level fluctuations caused by mold width adjustment and casting speed changes. In order to reduce the frequent action of the stopper, the system adopts the intergarting time change of the controller, and automatically selects a longer intergarting time when the molten steel level fluctuates lightly. And the system will choose a shorter intergrating time when molten steel level fluctuates greatly. Thereby, the fluctuation of the controlled object caused by the frequent action of the stopper rod is suppressed. In the signal processing of molten steel level gauge, an appropriate filtering link is added and the vibration frequency synchronous filter is used for filtering processing, which can overcome the interference of mold vibration frequency and amplitude variation.

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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.

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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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