Search Results (8)

It is difficult to detect several detailed defects when detecting surface defects in bamboo strips. The morphology of these defect characteristics exhibits relatively simple patterns but closely resembles the underlying fiber texture or coloration, as exemplified by cracks, mildew, wormholes, and burr formation. In this regard, this study proposes an improved model based on the YOLOv8 deep learning network. The improved model uses dynamic convolution and a Ghost module to improve the C3k2 modules in YOLOv8 to reconstruct its backbone and neck parts, where the research introduces the DySample module to replace the original upsample module to avoid the loss of feature information of targets after the network is used multiple times, further ensuring the detection effect of detailed features, as well as the EMA mechanism in the neck part. Experimental validation of the developed model demonstrated robust detection performance, achieving mAP values of 93.1%, 92.9%, 92.2%, and 92.2% for burr, mildew, cracking, and wormhole detection, with a total mAP of 92.6% and a precision of 81.5%; at the same time, the weight was decreased by 14%. The experimental results show that the improved model in this study has a certain detection effect on difficult-to-identify features on the surface of bamboo strips. This research demonstrates that employing YOLOv8 helps in detecting several challenging minor defects in bamboo strips. Full article

This study evaluates the influence of rotational speed on the mechanical and microstructural properties of T-joints fabricated via friction stir welding (FSW) using dissimilar aluminum alloys, AA5083 and AA6082, for naval applications. Three types of joints were produced by maintaining a constant traverse speed of 100 mm/min and varying the tool rotational speed at 500, 700, and 900 rpm. Mechanical performance was assessed through pull-out tests and microhardness measurements. The joints fabricated at 500 rpm demonstrated superior mechanical properties, including a more uniform hardness distribution and higher pull-out strength, attributed to optimized material mixing and heat input at this speed. In contrast, higher rotational speeds led to defect formation, such as wormholes, and compromised mechanical performance. These findings underscore the importance of optimizing rotational speed to enhance joint quality, making FSW a viable solution for manufacturing durable, lightweight structures in demanding marine environments. Full article

This paper reports on investigations of the air-coupled ultrasonic (ACU) method to detect common defects in solid timber panels made of Chinese fir (Cunninghamia lanceolata (Lamb.) Hook.). The ACU technology is a non-contact method for nondestructive timber testing with quicker scanning rates compared to contact methods. A testbed was set up consisting of commercially available piezo-ceramic ACU transducers and in-house manufactured signal processing circuits. To demonstrate the suitability of the ACU technique, through-transmission measurement results are presented for samples with defects such as knots, wormholes, and cracks. Pulse compression methods (Barker-coded method) were used to improve the power of received signals based on cross-correction algorithms. Results showed defects of timber panels made of Chinese fir can be detected with a thickness of less than 40 mm. Defects larger than 3 mm in diameter could be detected with high precision. Applying the pulse compression method showed better results than using common sine signals as excitation signals since it increased the signal-to-noise ratio, which is especially important for air-coupled measurement of high-attenuation materials like timber materials. The measurement results on reference samples demonstrated that ACU technology is a promising method for timber defect detection, especially for the quality assessment of engineered wood products. Full article

The various “defect wormholes” developed by Klinkhamer have recently attracted considerable attention—especially in view of the fact that the simplest example, the so-called “vacuum defect wormhole”, was claimed to be an everywhere-vacuum everywhere-Ricci-flat exact solution to the Einstein equations. This claim has been conclusively refuted by Feng, and in the current article, we take a deeper look at exactly what goes wrong. The central issue is this: Although Klinkhamer’s specific representation of the metric $g_{ab}$ is smooth ($C^{\infty }$), his inverse metric $g^{ab}$ is not even everywhere continuous ($C^0$), being undefined at the wormhole throat. This situation implies that one should very carefully investigate curvature tensors at the throat using the Israel–Lanczos–Sen thin-shell formalism. Doing so reveals the presence of a delta-function energy-condition-violating thin shell of matter at the wormhole throat. The “defect wormholes” are thus revealed to be quite ordinary “cut-and-paste” thin-shell wormholes, but represented in a coordinate system that is unfortunately pathological at exactly the same place that all the interesting physics occurs. To help clarify the situation, we shall focus on the behavior of suitable coordinate invariants—the Ricci scalar, the eigenvalues of the mixed $R^a{}_b$ Ricci tensor, and the eigenvalues of the mixed $R^{ab}{}_{cd}$ Riemann tensor. Full article

The semantic segmentation of annual rings is a research topic of interest in wood chronology. To solve the problem of wood annual rings being difficult to segment in dense areas and being greatly affected by defects such as cracks and wormholes, this paper builds a DAF-Net++ model which is based on U-Net whose backbone network is VGG16 and filled with dense jump links, CBAM and DCAM. In this model, VGG16 is used to enhance the extraction ability of image features, dense jump links are used to fuse semantic information of different levels, DCAM provides weighting guidance for shallow features, and CBAM solves the loss of down-sampling information. Taking a Chinese fir wood as the experimental object, 1700 CT images of wood transverse section were obtained by medical CT equipment and 120 of them were randomly selected as the dataset, which was expanded by cropping and rotation, among others. DAF-Net++ was used for training the model and segmentation of the annual rings, and finally the performance of the model was evaluated. The training method is freeze training followed by thaw training, and takes Focal Loss as the loss function, ReLU as the activation function, and Adam as the optimizer. The experimental results show that, in the segmentation of CT images of Chinese fir annual rings, the MIoU of DAF-Net++ is 93.67%, the MPA is 96.76%, the PA is 96.63%, and the Recall is 96.76%. Compared with other semantic segmentation models such as U-Net, U-Net++, DeepLabv3+, etc., DAF-Net++ has better segmentation performance. Full article

Bobbin tool friction stir welding (BTFSW) is a variant of the FSW process which uses the special two-shoulder tool that forms the top and bottom of a weld surface. As such, a significant simplification of the welding setup is achieved. One of the dominant parameters of the BTFSW process is the interference between the tool shoulder pinch gap and the weld metal thickness. In this research, the influence of interference of the square pin tool with convex shoulders on process temperature, microstructure, tensile, impact, and bend performance were studied, and appropriate correlations were devised. The base metal was an aluminum–magnesium alloy in which the interference varied in the range of 0.1 to 0.5 mm. Wormhole defects and irregularities were found in all specimens except in the specimen welded with 0.4 mm interference. An optimal interference of 0.4 mm resulted in the best mechanical properties, which, in terms of tensile strength and reduction of area, were similar to the base metal. Furthermore, the impact strength was significantly higher, which was attributed to the grain refinement effect in the nugget zone. Full article

Bobbin tool friction stir welding (BTFSW) utilizes a special tool that possesses two shoulders interconnected by a pin instead of one: the top shoulder and the pin in the conventional FSW tool. This greatly simplifies the kinematics in the otherwise complicated setup of FSW since the bottom shoulder forms the bottom surface of the weld, without the need for a backing plate. Moreover, the tool enters the base metal sideways and travels, forming the joint in a straight line while rotating, without the need for downward and upward motion at the beginning and end of the process. This paper presents a study on the BTFSW tool geometry and parameters on the risk of wormhole defect formation in the AA5005 aluminum–magnesium alloy and the wormhole effect on mechanical properties. It was shown that higher stress imposed by the tool geometry on the joint has a significant influence on heating, an effect similar to the increased rotational speed. Optimal kinematic and geometrical tool properties are required to avoid wormhole defects. Although weld tensile strengths were lower (between ~111 and 115 MPa) compared with a base metal (137 MPa), the ductile fracture was obtained. Furthermore, all welds had a higher impact strength (between ~20.7 and 27.8 J) compared with the base material (~18.5 J); it was found that the wormhole defect only marginally influences the mechanical properties of welds. Full article

Friction stir welding is a method of materials processing that enables the joining of similar and dissimilar materials. The process, as originally designed by The Welding Institute (TWI), provides a unique approach to manufacturing—where materials can be joined in many designs and still retain mechanical properties that are similar to, or greater than, other forms of welding. This process is not free of defects that can alter, limit, and occasionally render the resulting weld unusable. Most common amongst these defects are kissing bonds, wormholes and cracks that are often hidden from visual inspection. To identify these defects, various nondestructive testing methods are being used. This paper presents background to the process of friction stir welding and identifies major process parameters that affect the weld properties, the origin, and types of defects that can occur, and potential nondestructive methods for ex-situ detection and in-situ identification of these potential defects, which can then allow for corrective action to be taken. Full article