Large areas of muddy sediments on the coastal shelves of China provide important samples for studying climate and ecological changes. Analysis of a large number of such samples, which is essential for systematic study...Large areas of muddy sediments on the coastal shelves of China provide important samples for studying climate and ecological changes. Analysis of a large number of such samples, which is essential for systematic study on environmental information recorded in mud areas because of complicated sedimentary environment and variable sedimentary rate, requires a fast and economical method. In this study, we investigated the potential of X-ray fluorescence core scanner （XRFS）, a fast analytical instrument for measuring the elemental concentrations of muddy sediments, and observed a significant correlation between the element concentrations of muddy sediments determined by regular X-ray fluorescence spectrometer （XRF） and XRFS, respectively. The correlations are mainly determined by excitation energy of elements, but also influenced by solubility of element ions. Furthermore, we found a striking link between A1 concentrations and marine-originated organic carbon （MOC）, a proxy of marine primary productivity. This indicates that MOC is partly controlled by sedimentary characteristics. Therefore, XRFS method has a good potential in fast analysis of a large number of muddy sediment samples, and it can also be used to calibrate MOC in ecological study of coastal seas.展开更多
Aimed at the long and narrow geometric features and poor generalization ability of the damage detection in conveyor belts with steel rope cores using the X-ray image,a detection method of damage X-ray image is propose...Aimed at the long and narrow geometric features and poor generalization ability of the damage detection in conveyor belts with steel rope cores using the X-ray image,a detection method of damage X-ray image is proposed based on the improved fully convolutional one-stage object detection(FCOS)algorithm.The regression performance of bounding boxes was optimized by introducing the complete intersection over union loss function into the improved algorithm.The feature fusion network structure is modified by adding adaptive fusion paths to the feature fusion network structure,which makes full use of the features of accurate localization and semantics of multi-scale feature fusion networks.Finally,the network structure was trained and validated by using the X-ray image dataset of damages in conveyor belts with steel rope cores provided by a flaw detection equipment manufacturer.In addition,the data enhancement methods such as rotating,mirroring,and scaling,were employed to enrich the image dataset so that the model is adequately trained.Experimental results showed that the improved FCOS algorithm promoted the precision rate and the recall rate by 20.9%and 14.8%respectively,compared with the original algorithm.Meanwhile,compared with Fast R-CNN,Faster R-CNN,SSD,and YOLOv3,the improved FCOS algorithm has obvious advantages;detection precision rate and recall rate of the modified network reached 95.8%and 97.0%respectively.Furthermore,it demonstrated a higher detection accuracy without affecting the speed.The results of this work have some reference significance for the automatic identification and detection of steel core conveyor belt damage.展开更多
The article is to study the development of computer-aided design of X-ray microtomography—the device for investigating the structure and construction of three-dimensional images of organic and inorganic objects on th...The article is to study the development of computer-aided design of X-ray microtomography—the device for investigating the structure and construction of three-dimensional images of organic and inorganic objects on the basis of shadow projections. This article provides basic information regarding CAD of X-ray microtomography and a scheme consisting of three levels. The article also shows basic relations of X-ray computed tomography, the generalized scheme of an X-ray microtomographic scanner. The methods of X-ray imaging of the spatial microstructure and morphometry of materials are described. The main characteristics of an X-ray microtomographic scanner, the X-ray source, X-ray optical elements and mechanical components of the positioning system are shown. The block scheme and software functional scheme for intelligent neural network system of analysis of the internal microstructure of objects are presented. The method of choice of design parameters of CAD of X-ray microtomography aims at improving the quality of design and reducing costs of it. It is supposed to reduce the design time and eliminate the growing number of engineers involved in development and construction of X-ray microtomographic scanners.展开更多
A new technology for detecting a tiny residual core in the small inner cavity of complex castings is proposed. The residual core is identified by using image recognition technology. Tracer processing and image signal ...A new technology for detecting a tiny residual core in the small inner cavity of complex castings is proposed. The residual core is identified by using image recognition technology. Tracer processing and image signal processing are combined to enhance the image contrast. The relationships between the concentration of tracer, the size of the residual core, the wall thickness of the castings and the contrast were obtained. Based on the experimental data, the minimum detectable amount of residual core under different conditions was obtained. The results show that the minimum detectable amount decreases from 4.398 mg to 0.438 mg for the 1.0 mm wall thickness casting when the concentration of tracer increases from 0% to 20%. The signal-to-noise ratio(SNR) of the detection results increases by 27.010 by means of average filtering and linear point operation. The subtraction of image and image background was performed, and then the boundary extraction was carried out to obtain a clear and reliable result. The experimental results show that the non-traced residual core cannot be detected for a blade with a thickness less than 5 mm. The residual core of 1 mm thickness can be barely identified by artificial recognition after tracer processing and image processing, while the residual core of 0.6 mm thickness can be detected clearly using image recognition technology.展开更多
基金supported by the National Basic Research Program of China(2010CB428902)National Natural Science Foundation of China(40876088)
文摘Large areas of muddy sediments on the coastal shelves of China provide important samples for studying climate and ecological changes. Analysis of a large number of such samples, which is essential for systematic study on environmental information recorded in mud areas because of complicated sedimentary environment and variable sedimentary rate, requires a fast and economical method. In this study, we investigated the potential of X-ray fluorescence core scanner （XRFS）, a fast analytical instrument for measuring the elemental concentrations of muddy sediments, and observed a significant correlation between the element concentrations of muddy sediments determined by regular X-ray fluorescence spectrometer （XRF） and XRFS, respectively. The correlations are mainly determined by excitation energy of elements, but also influenced by solubility of element ions. Furthermore, we found a striking link between A1 concentrations and marine-originated organic carbon （MOC）, a proxy of marine primary productivity. This indicates that MOC is partly controlled by sedimentary characteristics. Therefore, XRFS method has a good potential in fast analysis of a large number of muddy sediment samples, and it can also be used to calibrate MOC in ecological study of coastal seas.
文摘Aimed at the long and narrow geometric features and poor generalization ability of the damage detection in conveyor belts with steel rope cores using the X-ray image,a detection method of damage X-ray image is proposed based on the improved fully convolutional one-stage object detection(FCOS)algorithm.The regression performance of bounding boxes was optimized by introducing the complete intersection over union loss function into the improved algorithm.The feature fusion network structure is modified by adding adaptive fusion paths to the feature fusion network structure,which makes full use of the features of accurate localization and semantics of multi-scale feature fusion networks.Finally,the network structure was trained and validated by using the X-ray image dataset of damages in conveyor belts with steel rope cores provided by a flaw detection equipment manufacturer.In addition,the data enhancement methods such as rotating,mirroring,and scaling,were employed to enrich the image dataset so that the model is adequately trained.Experimental results showed that the improved FCOS algorithm promoted the precision rate and the recall rate by 20.9%and 14.8%respectively,compared with the original algorithm.Meanwhile,compared with Fast R-CNN,Faster R-CNN,SSD,and YOLOv3,the improved FCOS algorithm has obvious advantages;detection precision rate and recall rate of the modified network reached 95.8%and 97.0%respectively.Furthermore,it demonstrated a higher detection accuracy without affecting the speed.The results of this work have some reference significance for the automatic identification and detection of steel core conveyor belt damage.
文摘The article is to study the development of computer-aided design of X-ray microtomography—the device for investigating the structure and construction of three-dimensional images of organic and inorganic objects on the basis of shadow projections. This article provides basic information regarding CAD of X-ray microtomography and a scheme consisting of three levels. The article also shows basic relations of X-ray computed tomography, the generalized scheme of an X-ray microtomographic scanner. The methods of X-ray imaging of the spatial microstructure and morphometry of materials are described. The main characteristics of an X-ray microtomographic scanner, the X-ray source, X-ray optical elements and mechanical components of the positioning system are shown. The block scheme and software functional scheme for intelligent neural network system of analysis of the internal microstructure of objects are presented. The method of choice of design parameters of CAD of X-ray microtomography aims at improving the quality of design and reducing costs of it. It is supposed to reduce the design time and eliminate the growing number of engineers involved in development and construction of X-ray microtomographic scanners.
基金supported by the National Natural Science Foundation of China(No.51475120)Major Program of National Natural Science Foundation of China(No.U1537201)
文摘A new technology for detecting a tiny residual core in the small inner cavity of complex castings is proposed. The residual core is identified by using image recognition technology. Tracer processing and image signal processing are combined to enhance the image contrast. The relationships between the concentration of tracer, the size of the residual core, the wall thickness of the castings and the contrast were obtained. Based on the experimental data, the minimum detectable amount of residual core under different conditions was obtained. The results show that the minimum detectable amount decreases from 4.398 mg to 0.438 mg for the 1.0 mm wall thickness casting when the concentration of tracer increases from 0% to 20%. The signal-to-noise ratio(SNR) of the detection results increases by 27.010 by means of average filtering and linear point operation. The subtraction of image and image background was performed, and then the boundary extraction was carried out to obtain a clear and reliable result. The experimental results show that the non-traced residual core cannot be detected for a blade with a thickness less than 5 mm. The residual core of 1 mm thickness can be barely identified by artificial recognition after tracer processing and image processing, while the residual core of 0.6 mm thickness can be detected clearly using image recognition technology.
