Automated crack detection of train rivets using fluorescent magnetic particle inspection and instance segmentation.

The railway rivet is one of the most important and easily damaged parts of the connection. If rivets develop cracks during the production process, their load-bearing capacity will be reduced, thereby increasing the risk of failure. Fluorescent magnetic particle flaw detection (FMPFD) is a widely used inspection method for train fasteners. Manual inspection is not only time-consuming but also prone to miss detection, therefore intelligent detection system has important application value. However, the fluorescent crack images obtained by FMPFD present challenges for intelligent detection, such as the dense, multi-scaled and uninstantiated cracks. In addition, there is limited research on fluorescent rivet crack detection. This paper adopts instance segmentation to achieve automatic cracks detection of rivets. A decentralized target center and low overlap rate labeling method is proposed, and a Gaussian-weighted correction post-processing method is introduced to improve the recall rate in the areas of dense cracks. An efficient channel spatial attention mechanism for feature extraction is proposed in order to enhance the detection of multi-scale cracks. For uninstantiated cracks, an improvement of crack detection in uninstantiated regions based on multi task feature learning is proposed, thoroughly utilizing the semantic and spatial features of the fluorescent cracks. The experimental results show that the improved methods are better than the baseline and some cutting-edge algorithms, achieving a recall rate and mAP0.5 of 86.4% and 90.3%. In addition, a single coil non-contact train rivet composite magnetization device is built for rivets that can magnetize different shapes of rivets and has universality.

Research on Photoacoustic Synthetic Aperture Focusing Technology Imaging Method of Internal Defects in Cylindrical Components.

Cylindrical components are parts with curved surfaces, and their high-precision defect testing is of great significance to industrial production. This paper proposes a noncontact internal defect imaging method for cylindrical components, and an automatic photoacoustic testing platform is built. A synthetic aperture focusing technology in the polar coordinate system based on laser ultrasonic (LU-pSAFT) is established, and the relationship between the imaging quality and position of discrete points is analyzed. In order to verify the validity of this method, small holes of Φ0.5 mm in the aluminum alloy rod are tested. During the imaging process, since a variety of waveforms can be excited by the pulsed laser synchronously, the masked longitudinal waves reflected by small holes need to be filtered and windowed to achieve high-quality imaging. In addition, the influence of ultrasonic beam angle and signal array spacing on imaging quality is analyzed. The results show that the method can accurately present the outline of the small hole, the circumferential resolution of the small hole is less than 1° and the dimensional accuracy and position error are less than 0.1 mm.