Auto-Fördertyp Nadel-Detektor NC-D

FEATURE 1. Accurate locating technology for metal impurities, rich customer functionality, be easy to operate. 2. The core system and part of digital signal processing are based on high speed 32bit RISC CPU. 3. Use LCD touch screen technology and based on multi language operation system. 4. Cycled magnetic sensor, excellent anti-disturb performance. 5. Individual sensibility adjusting for every channel, fit for more product detecting. 6. Smart report system( data printing system), provide kinds of report. 7. The control systems are based on RS-485 bus technology. 8. Installed machine state indicator and operator guider which are based on matrix LED display technology. 9. Optional conveying mode after alarm, and optional automatic restart. 10. Reliability mechanical frame design, Hi stable during detection. 11. Designed for universal AC power supply, switch power supply. PURPOSE 1.Detecting broken needles and magnetic metal impurities in sewing products, such as: garments, fabric, knit underwear, shoes, hats, toys, crafts, down products, bedding products, carpets etc. 2.Detecting magnetic metal impurities in foods, pharmaceutical products. 3.Detecting magnetic metal impurities in chemical raw materials, rubber, paper etc. 4.Detecting magnetic metal impurities in pure Copper, Aluminum, Stainless Steel. SPECIFICATIONS 1.Type NC-D(100) 2. Detection Method Magnetic induction 3.Detection adjustment Max.100 steps/channel 4.Detection sensitivity Fe¢0.8mm 5. Detection widtd 650mm 6. Alarm method Buzzer,Lamp 7.Belt speed 32m/min(50HZ),40m/min(60HZ) 8.Power source AC200-240V 50-60HZ 9.Rated output Appr140W 10.Weight Appr220Kg 11.Dimension 1650mm(L)*1100mm(W)*900mm(H) SERIES Detection HeightDetection SensitivityRemark100mm¢0.8mm steelstandard120mm¢1.0mm steeloption150mm¢1.2mm steeloption200mm¢1.5mm steeloption250mm¢2.0mm steeloptionAbove specification is under standard test condition. As different working condition, different environment, different products shape will effect above standard data.