Due to the influence of various factors in the production process of metal industrial products, there will be many kinds of defects on the surface. Quality inspection on the surface of metal products is particularly important to ensure the quality of industrial production. This paper based on the Inception-Resnet-V2 network to study the defect detection of steel plates. The network model is improved by adding a CBAM attention module to the original network, which increases the weight of defect-related information, reduces the interference of useless features, and then improves detection accuracy. At the same time, we use Softpool replace the traditional Maxpool pooling method to retain fine- grained feature information and fully capture more image features. Then the detection accuracy can be further improved. In this paper, the steel plate defect images are used as the dataset to train the improved network model. The improved network model can effectively identify cracks, impurities, pitting surface, oxide scale, scratches and other defects on the surface of steel plate. We compare the detection accuracy of the proposed network model with the VGG16, Resnet50 and YOLOv5 network models. The results show that the proposed network architecture significantly improves the defect detection accuracy
In this paper, the method of Radial basis function(RBF) to Electronic Speckle Pattern Interferometry (ESPI)information extraction is studied, mainly including: the filtering method based on radial basis function for ESPI fringe patterns with wide density; introducing the radial basis function to interpolate the number of fringe in the fringe skeleton method. Thermal deformation phase measurement of Al2O3 ceramic substrate at the circumstance of thermal load was estimated based on the ESPI. In the experiment, four ESPI fringe patterns at different moment at the beginning of the experiment were captured. The RBF filtering method and the fringe skeleton method with RBF interpolating were used to estimating the thermal deformation phase measurement. The acquiring out-of-plane displacements by our method were in good agreement with the real deformation under the stepped-up thermal load gradually. This measurement can provide assistance for studying the performance of ceramic substrate in the process of laser processing.
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