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One is 7 months old (not sexed); freely flying, like to be out of cage all day, freely flying around. Other one is 5 months old (breeder told male, but not sexed) has already started training; steps on a perch now on demand, wing feathers growing back, likes to be outside cage on his stand.

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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 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.