The machine vision-based defect detection for cylinder liner is a challenging task due to irregular shape, various and small defects on the cylinder liner surface. To improve the accuracy of defect detection by machine vision a deep learning-based defect detection method for cylinder liner was explored in this paper. First, a machine vision system was designed based on the analysis of the causes and types of defects to obtain the field images for establishing an original dataset. Then the dataset was augmented by a modified augmentation method which combines the region of interest automatic extraction method with the traditional augmentation methods. Except for introduction of the anchor configuration optimization method, an XML file-based method of highlighting defect area was proposed to address the problem of tiny defect detection. The optimal model was experimentally determined by considering the network model, the training strategy and the sample size. Finally, the detection system was developed and the network model was deployed. Experiments are carried out and the results of the proposed method compared with those of the traditional methods. The results show that the detection accuracies of sand, scratch and wear defects are 77.5%, 70% and 66.3% which are improved by at least 26.3% compared with the traditional methods. The proposal can be used for field defect detection of cylinder liner.
Abstract. In recent years China's wind power industry has developed rapidly. Yaw system is an important part of the wind power generation system. Its effectiveness not only affects the wind energy capture efficiency of the system, but also related to the safe operation of the wind power system. In this article, the working principle of the yaw system is described. And the current research status of control mode in China is commented. The function of the yaw system can be divided into two aspects, one is tracing wind accurately, the other is automatic untwisting. Research indicates that, using some new control strategy, such as hill-climbing control(HCC) algorithm, PLC algorithm, fuzzy control, static neural network and many kinds of other algorithm applied to the yaw system, can enhance the stability and robust of yaw system, and increase mechanical life of yaw system. However the technology for automatic untwisting has been ignored, researching new control strategy that can trace wind precisely and achieve automatic twisting is worthy of attention. Determine whether untwisting or not and complete action through the parameters in the algorithm above can improve the economy and stability of yaw system, create great value.
A high-precision camera intrinsic parameters calibration method based on concentric circles was proposed. Different from Zhang’s method, its feature points are the centers of concentric circles. First, the collinearity of the projection of the center of concentric circles and the centers of two ellipses which are imaged from the concentric circles was proved. Subsequently, a straight line passing through the center of concentric circles was determined with four tangent lines of concentric circles. Finally, the projection of the center of concentric circles was extracted with the intersection of the straight line and the line determined by the two ellipse centers. Simulation and physical experiments are carried out to analyze the factors affecting the accuracy of circle center coordinate extraction and the results show that the accuracy of the proposed method is higher. On this basis, several key parameters of the calibration target design are determined through simulation experiments and then the calibration target is printed to calibrate a binocular system. The results show that the total reprojection error of the left camera is reduced by 17.66% and that of the right camera is reduced by 21.58% compared with those of Zhang’s method. Therefore, the proposed calibration method has higher accuracy.
Water is an essential commodity upon which all life on Earth depends. According to the United Nations, one quarter of the world's population experience water scarcity. Serious water scarcity will block social development and endanger human health .In this paper, I establish model to help figure out the problem of water scarcity. In the first part, I used the analytic hierarchy, by looking at the bottom of the data and determine the weight of each layer to calculate the water demand. In the same way, I can get the total amount of water supply, and with (the water supply, the water demand) for the coordinates of the point in the coordinate system of 1 by 1 square area, I introduce a new parameter-the water stress indicator to divided the square area into several small areas. So that I can determine the extent of water scarcity in the region through the location of the point. In the second part, I chose Shandong Province, China as a severe water shortage area, and chose the Liaoning Province and Jiangxi Province as a comparison, bring the data into the model, by its position validates that our model is correct and universal significance. By substituting the three cities' data in, I found that the results obtained are in good agreement with the water map, which means our model is universal and correct. This model can be used to analyze the current situation of water resources in a region, also can be used to predict future trends. The disadvantage is that the water is a necessity of life, so I ignore the impact of price factors on it, which may cause minor errors.
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