Solving the screw compressor rotor-forming grinding wheel using the edge detection method based on the graphic method

2019 ◽  
Vol 233 (5) ◽  
pp. 967-979 ◽  
Author(s):  
Jian Yang ◽  
Fang-Hong Sun ◽  
Zheng Lu
Keyword(s):  
Edge Detection ◽  
Detection Method ◽  
Grinding Wheel ◽  
Screw Compressor ◽  
Graphic Method ◽  
Grinding Wheels ◽  
Helical Surface ◽  
Compressor Rotor ◽  
Edge Detection Method ◽  
Screw Rotors

As a complex grinding wheel for special use, the screw compressor rotor-forming grinding wheel needs to be designed according to the specific profile of the workpiece. The design process is complicated and difficult to grasp, and various design issues are likely to occur. This study is based on the design theory of helical rotor-forming grinding wheels. Here, disc-shaped forming grinding wheels for machining a helical surface were studied, with discrete point workpiece cross-sections as examples. MATLAB was used as the development tool, and the Unigraphics motion simulation function was applied to establish a 3D model of screw rotors and design the forming grinding wheel for machining the helical surface. Additionally, the edge shape of the grinding wheel obtained with the analytical method and the edge shape obtained with the edge detection method based on the graphic method and the alpha-shape algorithm were compared. The results of this comparison show that the edge shape of the grinding wheel obtained by the edge detection method had high precision and was easy to solve. This method can also be used for the design of other similar conjugated products such as gears, worms, and grinding wheels. The research findings provide important reference value for the design and machining of screw rotors and grinding wheels.

Solving the conjugate tooth profile of screw compressor rotors using edge detection method based on Alpha Shape algorithm

2019 ◽  
Vol 233 (6) ◽  
pp. 1217-1230
Author(s):  
Jian Yang ◽  
Fang-Hong Sun ◽  
Zheng Lu
Keyword(s):  
Edge Detection ◽  
Detection Method ◽  
Screw Compressor ◽  
Male And Female ◽  
Cloud Data ◽  
Alpha Shape ◽  
Rotor Profile ◽  
Fast Processing ◽  
Edge Detection Method ◽  
Rotor Profiles

While designing a screw compressor, the design of the rotor profiles is the most important because rotor profiles essentially determine the overall performance of the screw compressor. In the field of rotor design, the mutual solution of male and female rotors is characterized by shortcomings such as complex and error-prone calculation, and unsolvable interference. In this study, an edge detection method based on the Alpha Shape algorithm was proposed to avoid the complex calculation process in the traditional planar meshing theory and quickly obtain the point cloud data with singularity points removed. The results show that, with relatively high accuracy and fast processing speed, this algorithm can extract comparatively desirable edges so as to obtain data of the female (male) rotor profile based on the conjugate male (female) rotor profile. The analytical method and the experimental method were used to compare the data of the conjugate rotors, verifying the correctness of the design, which efficiently and highly accurately overcame the problems in mutual solution of male and female rotors. This method can also be applied to design similar conjugate products such as gears, worms, and milling cutters.

scholarly journals Cut-Edge Detection Method for Rice Harvesting Based on Machine Vision

Agronomy ◽  
2020 ◽  
Vol 10 (4) ◽  
pp. 590
Author(s):  
Zhenqian Zhang ◽  
Ruyue Cao ◽  
Cheng Peng ◽  
Renjie Liu ◽  
Yifan Sun ◽  
...  
Keyword(s):  
Machine Vision ◽  
Edge Detection ◽  
Detection Method ◽  
Region Of Interest ◽  
Average Error ◽  
Vertical Projection ◽  
Cut Edge ◽  
Fitting Method ◽  
Combine Harvester ◽  
Edge Detection Method

A cut-edge detection method based on machine vision was developed for obtaining the navigation path of a combine harvester. First, the Cr component in the YCbCr color model was selected as the grayscale feature factor. Then, by detecting the end of the crop row, judging the target demarcation and getting the feature points, the region of interest (ROI) was automatically gained. Subsequently, the vertical projection was applied to reduce the noise. All the points in the ROI were calculated, and a dividing point was found in each row. The hierarchical clustering method was used to extract the outliers. At last, the polynomial fitting method was used to acquire the straight or curved cut-edge. The results gained from the samples showed that the average error for locating the cut-edge was 2.84 cm. The method was capable of providing support for the automatic navigation of a combine harvester.

Research on Improvement Algorithm of Image Edge Detection

2014 ◽  
Vol 539 ◽  
pp. 141-145
Author(s):  
Shui Li Zhang
Keyword(s):  
Cognitive Psychology ◽  
Edge Detection ◽  
High Frequency ◽  
Detection Method ◽  
Low Frequency ◽  
Frequency Information ◽  
Image Edge Detection ◽  
Improvement Algorithm ◽  
Image Edge ◽  
Edge Detection Method

This paper presents new theorems Stevens edge detection method based on cognitive psychology on. Firstly, based on the number of the image is decomposed into high-frequency and low-frequency information, and the high-frequency information extracted by subtracting the maximum number of images to the image after the filter, then the amount of high frequency information into psychological cognitive psychology based on Stevenss theorem. The algorithm suppression refined edge after the non-minimum, applications Pillar K-means algorithm to extract image edge. Experimental results show that: the brightness of the image is converted to the amount of psychological edge can better unify under different brightness values.

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