Fastener identification and assembly verification via machine vision

Rusli, Leonard P.; Luscher, Anthony F.

doi:10.1108/aa-08-2016-093

Cited by 10 publications

(8 citation statements)

References 14 publications

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“…Statistical pattern recognition methods can be applied to predict assembly errors when the geometric trajectory of a mated part and the relational position of a base part are out of the allowable tolerance in a robotic assembly system [139]. Vision-based identification algorithms can also be applied to recognize unique features around fasteners so that the assemble results of fasteners are able to be verified [140]. This kind of CV application can also be found in automotive factory assembly lines such as identification of human errors involved in the bolt securing process [141].…”

Section: E Assemblymentioning

confidence: 99%

Computer Vision Techniques in Manufacturing

Zhou¹,

Zhang²,

Konz³

2022

Preprint

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Computer vision techniques have played an important role in promoting the informatization, digitization and intelligence of industrial manufacturing systems. Considering the rapid development of computer vision techniques, we present a comprehensive review of the state-of-the-art of these techniques and their applications in manufacturing industries. We survey the most common methods, including feature detection, recognition, segmentation and 3D modeling. A system framework of computer vision in the manufacturing environment is proposed, consisting of a lighting module, a manufacturing system, a sensing module, computer vision algorithms, a decision-making module, and an actuator. Applications of computer vision to different stages of the entire product life cycle are then explored, including product design, modeling and simulation, planning and scheduling, the production process, inspection and quality control, assembly, transportation, and disassembly. Challenges include algorithm implementation, data pre-processing, data labeling, and benchmarks. Future directions include building benchmarks, developing methods for non-annotated data processing, developing effective data pre-processing mechanisms, customizing computer vision models, and opportunities aroused by 5G.

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Section: E Assemblymentioning

confidence: 99%

Computer Vision Techniques in Manufacturing

Zhou¹,

Zhang²,

Konz³

2022

Preprint

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“…Rusli and Luscher evaluated the ability of machine vision cameras and software to identify fasteners for assembly verification. This will enable current assembly verification systems to correlate torque verification to specific fasteners [ 14 ].…”

Section: Related Workmentioning

confidence: 99%

The Influence of Artificial Intelligence on Visual Elements of Web Page Design under Machine Vision

Wang

2022

Computational Intelligence and Neuroscience

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As the presentation form of the web, web pages contain a lot of important information in web design. As many information carriers, such as sound, graphics, and text, web pages have been integrated and have played a good role in visual transmission. It inherits many features of traditional graphic design, it can be said that it extends graphic design, and web design is richer in visual performance. At present, the research on web design in China is mainly background research. There is little research on the front-end aspects of web pages, especially in the aspect of plane vision. The lack of research in this area limits the development of web design. This paper introduces the relevant situation of web design and then analyzes the relevant elements in web design, such as visual elements, and their innovative applications. In addition, it focuses on the presentation form of visual elements in web design and summarizes the development trend of visual elements in contemporary web interface design. It proposes the strategy of innovation and application of visual elements in web design. The author hopes that, through the research of this paper, it will lay a theoretical foundation for the development of web design in the future. At the same time, this paper uses the NCMF algorithm in artificial intelligence to identify the visual elements of web pages, thereby improving the efficiency of web page design. Experiments show that the Chaos accuracy rate of the NCMF algorithm in the CETD dataset is 73.3482%.

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“…Arjun et al recognized and assembled the parts by matching the template shape and the geometric features of the parts [11]. Rusli et al recognized and assembled automotive fasteners via a template matching method [12]. The featuredescriptors-based methods achieve parts recognition and positioning via extracting and matching the feature descriptors in the part images and template images.…”

Section: Introductionmentioning

confidence: 99%

A Coaxial Alignment Method for Large Flange Parts Assembly Using Multiple Local Images

Sun

Zhang

2021

IEEE Access

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The large flange parts in aero-engines are usually manually assembled. Collision damage caused by assembly alignment error often occurs in the assembly process, which affects the assembly accuracy and product reliability. The machine vision-based alignment methods usually achieve the highprecision measurement of the parts by obtaining the high-resolution images of the whole parts with a combination of laser distance sensors. Hence, existing methods are high costly and inefficient. In this paper, a new alignment method based on the principle of coaxial alignment for large flange parts is proposed. The proposed method first obtains multiple high-precision image pairs from the local field of views at the fitting surfaces of flanges. The clearance and bolt holes in each image pair are then extracted via edge recognition and Hough Transformation. Two optimization models are built to calculate the translation adjustment and rotation adjustment. The optimization model 1 is built with the translation adjustments of the flange as the variables and the consistency of the clearances as the objective function. The algorithm to solve the model based on the gradient-descent method is proposed. The positions of the bolt holes in the images are subsequently adjusted based on the translation adjustment, and the rotation adjustment is calculated by solving the built optimization model 2. The experiments show that the proposed method can be applied to the assembly process of large flange parts, and the visual servo control model based on this method also has good stability.

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Fastener identification and assembly verification via machine vision

Cited by 10 publications

References 14 publications

Computer Vision Techniques in Manufacturing

Computer Vision Techniques in Manufacturing

The Influence of Artificial Intelligence on Visual Elements of Web Page Design under Machine Vision

A Coaxial Alignment Method for Large Flange Parts Assembly Using Multiple Local Images

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