In the X-ray digital images of small-diameter copper tube soldering structures, the significant variations in defect size, morphology, and contrast make automatic defect recognition challenging. To address this
In the study by Hou et al., a model was constructed to detect welding defects such as cracks and blowholes contained in the X-ray image after the welding [8]. Machine learning has been also applied to laser welding. Chaki et al. searched for welding process parameters of hybrid welding ...
Thus, the dataset is the time series evolution of the key parameters of the process. Figure 14. Mold cavity picture and example of acquired machine pressure. Experimental data provided by EURECAT [26]. The DOE was designed in order to obtain seven different part qualities: good, short shot,...
It is true that complex systems exhibit a hierarchical structure from a model perspective, delineated into multiple layers based on their granularity. Similarly, in the temporal domain, models can be static, capturing a snapshot of the system at a given moment, or they can be dynamic, capturing...
for the realization of a generalized trained CNN model, which can process the multi-class dataset for the identification of welding defects. The effectiveness of the proposed method is confirmed by testing its performance in processing an industrial dataset. The intended dataset contains 4479 X-ray ...
Conventional X-ray computed tomography has been widely used to investigate the ductile mechanism in-situ, e.g. [42], [43], [44], this technique is favorable in particular for bar-like specimens. In contrast, the present study employees synchrotron-radiation computed laminography (SRCL) to ...
atomic volume versus Fe results in variations inrof less than 2%. The MNSP number density (N) was calculated by dividing the number of clusters in the dataset by the total volume in the analyzed tip. Precipitates on the edge of the tip are not included in the determining the size ...
The effectiveness of the proposed method is confirmed by testing its performance in processing an industrial dataset. The intended dataset contains 4479 X-ray images and belongs to six groups: cavity, cracks, inclusion slag, lack of fusion, shape defects, and normal defects. The devised ...
Hence, defect detection is of utmost importance. Du et al. [99] introduced a defect detection and classification method for Si-PV cells based on IRT and CNN. The method involved fine-tuning the LeNet-5, VGG-16, and GoogleNet models after generating the dataset. After 71 training iterations...
Oxford PV has announced a five year research project with the University of Oxford to develop a thin-film multi-junction perovskite solar cell, with a target 37% efficiency and long term stability. The GBP 5 million ... Raynergy Tek sets new world record for OPV power conversion efficiency ...