Characterization of Surface Integrity of Ti6Al4V Alloy Machined by Using Wire Electrical Discharge Machining Process

Tonday, Hulas Raj; Tigga, Anand Mukut

doi:10.1016/j.matpr.2019.03.049

Cited by 3 publications

(3 citation statements)

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“…In formula (1), A is the neighborhood determined first, and K is A the number of pixels in. The selected (i, j) 8 neighborhoods are used as the filtering template, then the formula (1) becomes the formula (2). At this time, the window is a 3 × 3 pixel, and the mean filtering is commonly used as a weighted template.…”

Section: Image Preprocessing Of Double-column Metal Partsmentioning

confidence: 99%

“…The physical and mechanical properties of the layer also change. 2 At present, non-contact measurement methods in optics are usually used to measure the size of metal parts. Optical measurement systems such as laser scanning or chromatographic analysis using visible light are usually complicated.…”

Section: Introductionmentioning

confidence: 99%

“…The machining quality of metal parts not only refers to the machining accuracy, but also includes the surface quality of machining, which is the characterization of the integrity of the surface layer after machining. The physical and mechanical properties of the layer also change 2 . At present, non‐contact measurement methods in optics are usually used to measure the size of metal parts.…”

Section: Introductionmentioning

confidence: 99%

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Application of subpixel edge detection in quality control of double‐column metal parts

Xie

Chen

2023

Adv Control Appl

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At present, most of the parts of mechanical equipment are made of metal, so the accurate detection and extraction of important characteristic parameters of metal parts is the key to determine the quality of mechanical equipment. In order to accurately extract and measure the feature size of metal parts, this research first carried out image preprocessing. Threshold segmentation is performed, and the target traits are extracted from the image to obtain the ROI. Finally, the preprocessed image is extracted from the image by the sub‐pixel edge extraction technology to extract the feature size of the circle to be measured. The difference between the measured value of the characteristic dimension of the spring bearing seat and the gasket and the real value measured by the research method is within the range of 5 and 4 μm, respectively, and both of them meet the requirements of the characteristic dimension accuracy. When the feature size of the two is repeatedly measured, the variation range of the detection results of the spring bearing seat and the gasket is within 9 and 7 μm respectively, and the detection value is much smaller than the feature size tolerance. The detection accuracy of the method can reach 95.394%. The score was 96.029 and the AUC value was 0.93, both higher than other methods. The results show that the use of sub‐pixels on metal parts The edge extraction method is extremely accurate. The research method can effectively improve the detection accuracy of the feature size of metal parts, which is of great significance to the development of the entire metal parts processing industry.

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Section: Image Preprocessing Of Double-column Metal Partsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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