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Intelligent Camera for Surface Defect Inspection
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作者 CHENG Wan-sheng ZHAO Jie WANG Ke-cheng 《Semiconductor Photonics and Technology》 CAS 2007年第1期33-38,共6页
An intelligent camera for surface defect inspection is presented which can pre-process the surface image of a rolled strip and pick defective areas out at a spead of 1 600 meters per minute. The camera is made up of a... An intelligent camera for surface defect inspection is presented which can pre-process the surface image of a rolled strip and pick defective areas out at a spead of 1 600 meters per minute. The camera is made up of a high speed line CCD, a 60 Mb/s CCD digitizer with correlated double sampling function, and a field programmable gate array(FPGA), which can quickly distinguish defective areas using a perceptron embedded in FPGA thus the data to be further processed would dramatically be reduced. Some experiments show that the camera can meet high producing speed, and reduce cost and complexity of automation surface inspection systems. 展开更多
关键词 intelligent camera surface defect inspection FPGA PERCEPTRON
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Steel Ball Defect Detection System Using Automatic Vertical Rotating Mechanism and Convolutional Neural Network
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作者 Yi-Ze Wu Yi-Cheng Huang 《Computers, Materials & Continua》 2025年第4期97-114,共18页
Precision steel balls are critical components in precision bearings.Surface defects on the steel balls will significantly reduce their useful life and cause linear or rotational transmission errors.Human visual inspec... Precision steel balls are critical components in precision bearings.Surface defects on the steel balls will significantly reduce their useful life and cause linear or rotational transmission errors.Human visual inspection of precision steel balls demands significant labor work.Besides,human inspection cannot maintain consistent quality assurance.To address these limitations and reduce inspection time,a convolutional neural network(CNN)based optical inspection system has been developed that automatically detects steel ball defects using a novel designated vertical mechanism.During image detection processing,two key challenges were addressed and resolved.They are the reflection caused by the coaxial light onto the ball center and the image deformation appearing at the edge of the steel balls.The special vertical rotating mechanism utilizing a spinning rod along with a spiral track was developed to enable successful and reliable full steel ball surface inspection during the rod rotation.The combination of the spinning rod and the spiral rotating component effectively rotates the steel ball to facilitate capturing complete surface images.Geometric calculations demonstrate that the steel balls can be completely inspected through specific rotation degrees,with the surface fully captured in 12 photo shots.These images are then analyzed by a CNN to determine surface quality defects.This study presents a new inspection method that enables the entire examination of steel ball surfaces.The successful development of this innovative automated optical inspection system with CNN represents a significant advancement in inspection quality control for precision steel balls. 展开更多
关键词 Steel ball surface defect inspection automated optical inspection convolutional neural network
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