When capturing a QR code on a cylinder, there may be geometric distortions due to the angle of the camera and the cylindrical deformation, which makes the QR code difficult to recognize. To solve this problem, a correction algorithm for QR codes is proposed in this paper. First, the boundary of the QR code on the cylinder is extracted by a morphological algorithm and geometry calculations. Then, the feature points on the image are accurately located. Next, the standard size of the QR code is determined by using the cross-ratio method in descriptive geometry. Finally, the image is corrected by perspective projection. It is proven that the algorithm can correct the distortion of the cylinder image effectively, and it has the ability to properly identify cylindrical QR codes.

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A nondestructive testing method for curved surfaces based on the multi-Gaussian beam model is proposed in this study. The multi-Gaussian beam model for composites coupled with water is introduced into an automatic ultrasonic testing system. A mathematical model of the received beam field is established to analyze the effect of different testing parameters on the receiving transducer. The normal vector can be calculated by variational methods to achieve the transmitting transducer's position and orientation. The position and orientation of the receiving transducer can be achieved by coordinate transformation method. The simulation and experiments illustrate the validity and effectiveness of the proposed method. Experimental results indicate that the received signal is strong and measurement accuracy is high with the proposed method. The proposed method provides an effective solution to curved composite surface parts and would significantly benefit industrial development.

Anomaly monitoring of production line processing equipment based on machine vision is an important method for ensuring its efficient and stable operation. However, problems related to dynamic scenes, accidental and non-transcendental anomalies, image vulnerability to the severe vibrations of machining equipment, and difficulty in accepting the missing detection are significant obstacles to abnormality monitoring in the machining process. A periodic motion scene decomposition method is presented in this paper to solve dynamic scenes, occasional anomalies, severe vibrations, and other issues. Through optimization of the morphological structural elements, the feature points of the 'abnormality' region are obtained, and a Gaussian weighting formula is derived to detect the anomaly and improve the accuracy of detection. This method, which is verified by experiments, effectively overcomes problems related to the machining process and achieves good detection results.

Purpose – Nondestructive testing based on cooperative twin-robot technology is a significant issue for curved-surface inspection. To achieve this purpose, this paper aims to present a kinematic constraint relation method relative to two cooperative robots. Design/methodology/approach – The transformation relation of the twin-robot base frame can be determined by driving the two robots for a series of handclasp operations on three points that are noncollinear in space. The transformation relation is used to solve the cooperative motion problem of the twin-robot system. Cooperative motions are divided into coupled and combined synchronous motions on the basis of the testing tasks. The position and orientation constraints for the two motion modes are also explored. Findings – Representative experiments between two industrial robots are conducted to validate the theoretical developments in kinematic constraint analysis. Artificial defects are clearly visible in the C-scan results, thereby verifying the validity and the effectiveness of the proposed method. Originality/value – The transformation relation of the twin-robot base frame is built under a series of handclasp operations. The position and orientation constraints for the coupled and combined synchronous motions are explored. Theoretical foundations of trajectory planning method for the transmitting and receiving transducers of the cooperative twin-robot system are presented.