Trajectory planning method for improving alignment accuracy of probes for dual-robot air-coupled ultrasonic testing system

Guo, Chunhui; Xu, Chunguang; Xiao, Di; Hao, Juan; Zhang, Hanming

doi:10.1177/1729881419842713

Cited by 9 publications

(4 citation statements)

References 16 publications

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“…Ultrasound is one of the most common nondestructive testing techniques in composite inspection. It covers a range of transducer types including single element, phased array [4], air-coupled [5] and immersed transducers. Combining with flexible data acquisition methods such as pulse-echo, pitch-catch and Full Matrix Capture, ultrasonic testing is able to detect diverse defect types with position, size and depth information in reused composite [6,7] as well as new composite material [8,9].…”

Section: Non-destructive Testing Methodsmentioning

confidence: 99%

Composite Repair and Remanufacturing

Freeden

Wit²,

Caba³

et al. 2022

Systemic Circular Economy Solutions for Fiber Reinforced Composites

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For the reuse of components and structures made of fiber composite materials, a complete remanufacturing process chain is necessary to prepare the parts for a further life cycle. The first step is to dismantle the parts to be reused. Fiber composite components are mostly joined using adhesive technology, so that solution techniques are required for adhesive connections. One possibility is the separation of the adhesive layer by means of thermally expanding particles. Adhesive residues are removed by laser so that the components can be glued again after reprocessing. The decisive factor for which process is used for the remanufacturing of the components is the state at the end of the life cycle. Non-destructive testing methods offer a very good option for detecting damage, planning necessary repairs and direct reuse of damage-free components. Repairs to fiber composite structures have been carried out in aviation for a long time and are accordingly established. These processes can be transferred to the repair of automotive fiber composite components. Many technical solutions were developed and tested as part of the project. Future research work is aimed at further development, particularly with regard to the automation of the technologies in order to enable an industrial application of the recycling of automobile components made of fiber composites.

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Section: Non-destructive Testing Methodsmentioning

confidence: 99%

Composite Repair and Remanufacturing

Freeden

Wit²,

Caba³

et al. 2022

Systemic Circular Economy Solutions for Fiber Reinforced Composites

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“…In [13], a dual-robot air-coupled ultrasonic non-destructive testing scheme is shown and introduces the structure of the system and a general calibration method for the workpiece frame of a dual-robot system in detail. A tangential constraint method, which makes the probes completely aligned during the inspection process, is proposed.…”

Section: Introductionmentioning

confidence: 99%

Methodology for the Generation of High-Quality Ultrasonic Images of Complex Geometry Pieces Using Industrial Robots

Aparicio

León

Parrilla

et al. 2023

Sensors

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Industrial robotic arms integrated with server computers, sensors and actuators have revolutionized the way automated non-destructive testing is performed in the aeronautical sector. Currently, there are commercial, industrial robots that have the precision, speed and repetitiveness in their movements that make them suitable for use in numerous non-destructive testing inspections. Automatic ultrasonic inspection of complex geometry parts remains one of the most difficult challenges in the market. The closed configuration, i.e., restricted access to internal motion parameters, of these robotic arms makes it difficult for an adequate synchronism between the movement of the robot and the acquisition of the data. This is a serious problem in the inspection of aerospace components, where high-quality images are necessary to assess the condition of the inspected component. In this paper, we applied a methodology recently patented for the generation of high-quality ultrasonic images of complex geometry pieces using industrial robots. The methodology is based on the calculation of a synchronism map after a calibration experiment and to introduce this corrected map in an autonomous, independent external system developed by the authors to obtain precise ultrasonic images. Therefore, it has been shown that it is possible to establish the synchronization of any industrial robot with any ultrasonic imaging generation system to generate high-quality ultrasonic images.

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“…For most application scenarios of industrial robots, it is necessary to predict the position and pose of the target object to complete the corresponding task. Xu Chunguang's team [1,2] developed a robotic ultrasonic inspection system, which requires the calibration of the fixture coordinate system of the workpiece to be inspected and the inspection coordinate system of the dual robotic arms. Furthermore, the digital model is used to locate the ultrasonic testing reference point of the regular shape workpiece, and the automatic control of the ultrasonic testing of the robotic arm is finally realized.…”

Section: Introductionmentioning

confidence: 99%

A Point Cloud-Based Feature Recognition and Path Planning Method

Chen

Wang

Huang

2022

Shock and Vibration

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Based on the research background of in situ automatic ultrasonic phased array inspection of irregular porous castings, due to the limited in situ inspection stations, complex shape of irregular porous castings, and extreme multireflection structural features, it is necessary to identify the positioning inspection features among multiple features to be inspected and plan the optimal inspection path. This research is interested in the porous location recognition and its detection path planning of irregular porous castings. For this, a point cloud-based multifeature contour recognition and location algorithm were proposed to simultaneously extract and locate the hole feature and cylindrical feature from an irregular porous castings. Furthermore, a detection path planning method was put forward to search the shortest robot’s detection path based on the above acquired features by visual recognition and positioning technology. First, through the calibration of the industrial robot tool coordinate system and the internal and external parameters of the camera, the “EyeinHand” hand-eye conversion relationship was established. Second, the robot vision system collects the point cloud information of the area to be inspected and performs point cloud splicing, the accuracy of the original data, the removal of noise such as invalid points, outliers and internal noise points, on this basis, the boundary curve of the hole to be inspected was extracted, the cylindrical equation was fitted, its geometric center was calculated, and the central coordinates and axis direction of the contour of the hole to be inspected were obtained. Finally, all the detection paths were traversed through the multibranch tree to obtain the optimal detection path of the detection points of multiple targets. The experimental results show that the positioning accuracy of the feature of the hole to be inspected by the vision system is 0.107 mm, the aperture extraction accuracy is 0.002 mm, the cylinder fitting accuracy is 0.04 mm, and the calculation accuracy of the angle between the two axes is within 0.4. When the number of features to be inspected is different, the average moving distance can be saved by 10.7% by using the end effector after path optimization. The feasibility of in situ automatic ultrasonic phased array detection for irregular porous castings using by visual positioning is verified.

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Trajectory planning method for improving alignment accuracy of probes for dual-robot air-coupled ultrasonic testing system

Cited by 9 publications

References 16 publications

Composite Repair and Remanufacturing

Composite Repair and Remanufacturing

Methodology for the Generation of High-Quality Ultrasonic Images of Complex Geometry Pieces Using Industrial Robots

A Point Cloud-Based Feature Recognition and Path Planning Method

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