Bimodal line

During the movement of the gloves, the high-speed camera completes the shooting, and the collected images are uploaded to the host computer for image preprocessing and then sent to the Deep Learning model for inference. The results of the model inference are sent to the system to classify the gloves into qualified or defective categories. . The equipment does not take any measures for qualified gloves and releases them to the counting machine for packaging; for defective gloves, the control system automatically controls the rejecting machine and counting machine to remove the defective gloves.

High detection efficiency

High detection efficiency,Gloves do not need to be flipped to complete front and back detection

Diversified detection

Gloves can be detected on both sides without flipping, and can be quickly switched between different glove models. One device can meet the requirements for detecting multiple types of gloves, solving the problem that one device can only detect one type of glove in similar products

Customization of self-developed testing software and equipment

It can meet various testing needs of customers.

Defective workpiece diagram
Piston Pin
Valve seat insert
Valve guide
Technical Indicators

Testing items

Appearance defects such as scratches, abrasions, chipping, end face damage, misalignment, cracks, bumps, crushing, missed processing, mixing, etc

Detection range

Ø 5~100mm,

Testing requirements

The surface of the workpiece is clean and free of oil stains.

Optical resolution


Mean time between failures


Detection speed

5000-20000 pieces per hour



Supply Voltage



1.0m*1.0m*1.8m / 250kg

Equipment air source


System working environment

Temperature: 5 ℃~30 ℃;Relative humidity:<70%RH

Other characteristics

1、Real time display of detection status and NG product quantity alarm;

2、The device software has remote technical support function.

Related solutions
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