Wd-01 Wall Scanner Detector Multifunction Stud Find Wood Block / Metals / Cable

Features * Don’t worry about punching holes three detection modes: switch the detection mode arbitrarily according to different working conditions metal mode cable detection wooden block detection *Deep detection up to 120mm detectable: covering conventional drilling depth (30~60mm) various drilling scenarios are easy * Hole position marking one-stop precise drilling: center positioning hole design directly mark the punching position after detection to achieve one-stop precise drilling * Wide range of applications easy to deal with multiple scenarios: whether it is indoor or outdoor industrial or household it can be easily dealt with * Accurate and sensitive high-performance detection module: high-performance anti-jamming chip reducing false positives more accurate detection depth faster positioning *Multiple warnings safe drilling: screen status display indicator light status display buzzer sound reminder multiple detection status prompts only when you have a bottom in mind can you get started safely *Save money and worry recyclable lithium battery: built-in rechargeable lithium battery no need to buy extra battery configuration Type-C charging hole charge and use * Quick to get started simple interface and buttons: two buttons with a simple UI you will use it when you get it Specification Maximum Detection Depth Ferrous metal: 120mm Non-ferrous metal (copper): 100mm AC: 50mm Single strand copper wire (≥4mm2): 40mm Wooden stop: precision mode: 20mm; depth mode: 38mm Automatic shutdown: after 5 minutes of no operation Power supply mode: rechargeable lithium battery; Type-C charging Product size: 138*68*22mm Product weight: 122g Packing size: 203*98*45.5mm Packing list 1*Wall detector 1*Type-C cable 1*storage bag 1*User Manual Note: 1. The real color of the item may be slightly different from the pictures shown on website caused by many factors such as brightness of your monitor and light brightness. 2. Please allow slight manual measurement deviation for the data.