A fast PCB hole detection method based on geometric features

Zhu, Weilin; Gu, Hong; Su, Weimin

doi:10.1088/1361-6501/ab8b21

Cited by 12 publications

(5 citation statements)

References 26 publications

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“…Object detection is widely applied in industry applications, such as defect detection of electrical components or printed circuit boards (PCBs) [2]. As demands in PCB process design and quality assurance escalate, the diversity of defects found on PCB surfaces, including spurs, mouse bites, short circuits, and open circuits, continues to expand.…”

Section: Previous Workmentioning

confidence: 99%

Measurement of Si pixel sensor alignment for the ALICE ITS detector

Satya Wicaksana,

Prakasa,

Di Mauro

et al. 2024

Meas. Sci. Technol.

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The ALICE experiment is one of the four experiments at the Large Hadron Collider (LHC) designed to investigate the status of matter under very high energy densities produced during heavy-ion collisions. The ALICE Inner Tracking System (ITS) consists of seven concentric cylindrical layers of monolithic silicon pixel sensors known as ALICE Pixel Detector (ALPIDE). The sensors are used to reconstruct the paths of charged particles generated in the collisions. The sensor alignment of the detector must be adjusted to a high precision standard. The adjustment objective is to obtain a detector that can undertake high-resolution measurements. This paper introduces a method for measuring the reference markers utilized in sensor alignment determination. Markers engraved at the chip corners have been detected using the Hough transform, Canny edge detection, and template matching techniques. The distances between two markers are measured to determine the accuracy of the pixel sensor alignment before and after assembly. The proposed methods exhibit an accuracy exceeding 99% and demonstrate high speed analysis. The average processing times for detecting the circle and cross markers are 105.9 ms/image and 113.8 ms/image, respectively. The sensor alignment of the detector must be adjusted to a high precision standard. However, recent studies have shown deviations of up to 5um above the desired value in the measured sensor position. Such deviations do not represent a major issue, nevertheless it is important to measure them in order to speed-up and make more accurate the recursive track-based alignment procedure used to reconstruct the position of each pixel sensor in the tracking detector. The proposed method offers a promising solution to deliver precise and rapid measurements for a large number of examined objects.

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Section: Previous Workmentioning

confidence: 99%

Measurement of Si pixel sensor alignment for the ALICE ITS detector

Satya Wicaksana,

Prakasa,

Di Mauro

et al. 2024

Meas. Sci. Technol.

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“…Methods such as blob detection, canny edge detection and Hough transformation are used to detect drilled holes in wood-based materials [ 19 ]. A canny edge detector based algorithm is also used to detect holes on printed circuit boards [ 20 ]. Belonging to other domains, these approaches can be transferred to the detection of codes.…”

Section: Related Workmentioning

confidence: 99%

Reading Direct-Part Marking Data Matrix Code in the Context of Polymer-Based Additive Manufacturing

Matuszczyk

Weichert

2023

Sensors

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A novel approach to detect and decode direct-part-marked, low-contrast data matrix codes on polymer-based selective laser sintering manufactured parts, which is able to work on lightweight devices, is presented. Direct-part marking is a concept for labeling parts directly, which can be carried out during the additive manufacturing’s design process. Because of low contrast in polymer-based selective laser sintering manufactured parts, it is a challenging task to detect and read codes on unicolored parts. To achieve this, at first, codes are located using a deep-learning-based approach. Afterwards, the calculated regions of interest are passed into an image encoding network in order to compute readable standard data matrix codes. To enhance the training process, rendered images, improved with a generative adversarial network, are used. This process fulfills the traceability task in assembly line production and is suitable for running on mobile devices such as smartphones or cheap sensors placed in the assembly line. The results show that codes can be localized with 97.38% mean average precision, and a readability of 89.36% is achieved.

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“…In the context of detecting small holes in industrial components, Jiang et al partitioned the image into blocks, and during the assessment of candidate circles, restricted the edge point selection of a few local image segments, thereby enhancing the detection efficiency [ 24 ]. According to the symmetry characteristic of circular hole contours, Zhu et al proposed a fast hole detection method using the Euclidean distance transformation of a binary image, aimed at determining the precise localization of a large number of holes [ 25 ]. Mei et al proposed a hole measurement method with high accuracy, combining a vote-based ellipse-fitting algorithm with an optimization approach utilizing the snakes model [ 26 ].…”

Section: Introductionmentioning

confidence: 99%

A Visual Measurement Method for Deep Holes in Composite Material Aerospace Components

Meng,

Yang,

Yang

et al. 2024

Sensors

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The visual measurement of deep holes in composite material workpieces constitutes a critical step in the robotic assembly of aerospace components. The positioning accuracy of assembly holes significantly impacts the assembly quality of components. However, the complex texture of the composite material surface and mutual interference between the imaging of the inlet and outlet edges of deep holes significantly challenge hole detection. A visual measurement method for deep holes in composite materials based on the radial penalty Laplacian operator is proposed to address the issues by suppressing visual noise and enhancing the features of hole edges. Coupled with a novel inflection-point-removal algorithm, this approach enables the accurate detection of holes with a diameter of 10 mm and a depth of 50 mm in composite material components, achieving a measurement precision of 0.03 mm.

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A fast PCB hole detection method based on geometric features

Cited by 12 publications

References 26 publications

Measurement of Si pixel sensor alignment for the ALICE ITS detector

Measurement of Si pixel sensor alignment for the ALICE ITS detector

Reading Direct-Part Marking Data Matrix Code in the Context of Polymer-Based Additive Manufacturing

A Visual Measurement Method for Deep Holes in Composite Material Aerospace Components

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