Vision based in-process inspection for countersink in automated drilling and riveting

Yu, Long; Bi, Qinsheng; Ji, Yulei; Yun-fei, Fan; Huang, Nuodi; Wang, Yuhan

doi:10.1016/j.precisioneng.2019.05.002

Cited by 26 publications

(17 citation statements)

References 22 publications

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“…Fig. 12 The topological structure of the control system of the HDMDRM of visual measurement control system and motion control system, as shown in Fig. 12.…”

Section: Methodsmentioning

confidence: 99%

“…Generally, measuring systems in digital drilling and riveting equipment consist of four laser displacement sensors (LDSs) and camera vision which are used for normal adjusting and positioning, respectively. Although almost all aircraft panels are curved, it is generally considered that a curved surface is an approximate plane [12] for a slight curvature near the reference hole. There are three standard methods to measure the normal direction of the reference hole, which are eddy current, mechanical contact, and laser non-contact.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

A novel accurate positioning method of reference hole for complex surface in aircraft assembly

Zhang

Liu

Zheng

et al. 2021

Int J Adv Manuf Technol

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In the digital drilling and riveting process of complex surfaces such as aircraft panels, the reference hole is pre-drilled on the skin surface. Generally, four laser displacement sensors (LDSs) are used as a group for normal adjustment. The camera vision is used to determine the position of the reference hole to obtain the accurate positioning of the drilling position. However, while dealing with large curvature complex panel surface and panel edge, four LDSs have the problem of reflection laser disappearance or matching failure. Applying two LDSs for normal adjustment on one side, the projection of the reference hole on the camera focal plane is an ellipse which means a further normal adjustment is desired in the direction of the ellipse's minor axis. Therefore, this paper proposes a 3-dimensional pose estimation method (TDPEM) combining multi-sensor fusion and space geometry to realize the normal adjustment and position measurement of reference holes with a monocular camera and two LDSs. Firstly, two LDSs are used to adjust the reference hole's horizontal (or vertical) direction. And then, an ellipse contour extraction algorithm is proposed to determine the ellipse parameters. Finally, the pose of the reference hole on the panel is determined by a spatial circle reverse algorithm. The experiment proves that the position error and angle error between this algorithm and the traditional four-LDS-based measurement method are within 0.03 mm and 0.2°, respectively, which verifies the feasibility and reliability of this algorithm.

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“…Fig. 12 The topological structure of the control system of the HDMDRM of visual measurement control system and motion control system, as shown in Fig. 12.…”

Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

A novel accurate positioning method of reference hole for complex surface in aircraft assembly

Zhang

Liu

Zheng

et al. 2021

Int J Adv Manuf Technol

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“…Drilled hole contours can be separated, and the color/texture of boards is always constant. Another drilling inspection approach was described by Yu et al [ 10 ]. Researchers have used multiple image preprocessing techniques and Canny edge [ 11 ] to extract holes and a flush for rivets in aircraft panels.…”

Section: Related Workmentioning

confidence: 99%

Segmentation of Drilled Holes in Texture Wooden Furniture Panels Using Deep Neural Network

Augustauskas

Lipnickas

Surgailis³

2021

Sensors

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Drilling operations are an essential part of furniture from MDF laminated boards required for product assembly. Faults in the process might introduce adverse effects to the furniture. Inspection of the drilling quality can be challenging due to a big variety of board surface textures, dust, or woodchips in the manufacturing process, milling cutouts, and other kinds of defects. Intelligent computer vision methods can be engaged for global contextual analysis with local information attention for automated object detection and segmentation. In this paper, we propose blind and through drilled holes segmentation on textured wooden furniture panel images using the UNet encoder-decoder modifications enhanced with residual connections, atrous spatial pyramid pooling, squeeze and excitation module, and CoordConv layers for better segmentation performance. We show that even a lightweight architecture is capable to perform on a range of complex textures and is able to distinguish the holes drilling operations’ semantical information from the rest of the furniture board and conveyor context. The proposed model configurations yield better results in more complex cases with a not significant or small bump in processing time. Experimental results demonstrate that our best-proposed solution achieves a Dice score of up to 97.89% compared to the baseline U-Net model’s Dice score of 94.50%. Statistical, visual, and computational properties of each convolutional neural network architecture are addressed.

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“…Feature matching algorithm can be divided into point-based matching algorithm (Kleppe et al , 2017; Yu et al , 2019), line-based matching algorithm (Miraldo et al , 2015; Lopez et al , 2015) and edge-based matching algorithm (Cai et al , 2016). The feature points are easy to extract by using point feature operator.…”

Section: Literature Reviewmentioning

confidence: 99%

A contour-guided pose alignment method based on Gaussian mixture model for precision assembly

Guo

Zhang

Shi

et al. 2021

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Purpose The purpose of this study was to solve the problem of pose measurement of various parts for a precision assembly system. Design/methodology/approach A novel alignment method which can achieve high-precision pose measurement of microparts based on monocular microvision system was developed. To obtain the precise pose of parts, an area-based contour point set extraction algorithm and a point set registration algorithm were developed. First, the part positioning problem was transformed into a probability-based two-dimensional point set rigid registration problem. Then, a Gaussian mixture model was fitted to the template point set, and the contour point set is represented by hierarchical data. The maximum likelihood estimate and expectation-maximization algorithm were used to estimate the transformation parameters of the two point sets. Findings The method has been validated for accelerometer assembly on a customized assembly platform through experiments. The results reveal that the proposed method can complete letter-pedestal assembly and the swing piece-basal part assembly with a minimum gap of 10 µm. In addition, the experiments reveal that the proposed method has better robustness to noise and disturbance. Originality/value Owing to its good accuracy and robustness for the pose measurement of complex parts, this method can be easily deployed to assembly system.

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Vision based in-process inspection for countersink in automated drilling and riveting

Cited by 26 publications

References 22 publications

A novel accurate positioning method of reference hole for complex surface in aircraft assembly

A novel accurate positioning method of reference hole for complex surface in aircraft assembly

Segmentation of Drilled Holes in Texture Wooden Furniture Panels Using Deep Neural Network

A contour-guided pose alignment method based on Gaussian mixture model for precision assembly

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