Accurate Detection Method of Aviation Bearing Based on Local Characteristics
Aviation bearing assembled detection is the final barrier to quality and safety. Therefore, an accurate detection method of aviation bearing that is based on local characteristics is designed to solve the detection problem of mis-assembly and miss-assembly of balls in aviation bearing assembled. Whe...
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doaj-794a643d564e4701a962f2a371ce73992020-11-25T00:40:41ZengMDPI AGSymmetry2073-89942019-08-01119106910.3390/sym11091069sym11091069Accurate Detection Method of Aviation Bearing Based on Local CharacteristicsPing Xue0Yali Jiang1Hongmin Wang2Hai He3School of Automation, Harbin University of Science and Technology, Harbin150080, ChinaSchool of Automation, Harbin University of Science and Technology, Harbin150080, ChinaSchool of Automation, Harbin University of Science and Technology, Harbin150080, ChinaSchool of Automation, Harbin University of Science and Technology, Harbin150080, ChinaAviation bearing assembled detection is the final barrier to quality and safety. Therefore, an accurate detection method of aviation bearing that is based on local characteristics is designed to solve the detection problem of mis-assembly and miss-assembly of balls in aviation bearing assembled. When considering the spatial limitation of aviation bearing assembled image acquisition, the dynamic distribution of balls and the interference of lubricating grease on the surface, a dynamic local ball segmentation model that is based on U-Net network with symmetrical structure is designed to achieve the accurate segmentation of the local ball region of aviation bearing. Subsequently, an incomplete circle fitting algorithm is designed based on the segmented local ball image and Hough transform principle. These two algorithms make the measurement error of aviation bearing ball size less than 100 μm. Using bearings validates the algorithm. The results show that the accuracy of dynamic local ball segmentation model that is based on U-Net network with symmetrical structure is over 99%. At the same time, on the basis of accurate segmentation in aviation bearing local ball, the designed Hough circle algorithm is used for circle detection. The experimental results show that the false detection rate of mis-assembly and miss-assembly of balls is less than 3%. Further, the goal of zero-missed detection of mis-assembly and miss-assembly of balls in aviation bearing is achieved. The accurate segmentation of aviation bearing local ball and the effective identification of mis-assembly and miss-assembly of balls are realized. This method can provide a theory for the improvement of mis-assembly and miss-assembly of balls detection in aviation bearing. Furthermore, it has high application value.https://www.mdpi.com/2073-8994/11/9/1069aviation bearinglocal characteristicsU-Net networkHough transform |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Ping Xue Yali Jiang Hongmin Wang Hai He |
spellingShingle |
Ping Xue Yali Jiang Hongmin Wang Hai He Accurate Detection Method of Aviation Bearing Based on Local Characteristics Symmetry aviation bearing local characteristics U-Net network Hough transform |
author_facet |
Ping Xue Yali Jiang Hongmin Wang Hai He |
author_sort |
Ping Xue |
title |
Accurate Detection Method of Aviation Bearing Based on Local Characteristics |
title_short |
Accurate Detection Method of Aviation Bearing Based on Local Characteristics |
title_full |
Accurate Detection Method of Aviation Bearing Based on Local Characteristics |
title_fullStr |
Accurate Detection Method of Aviation Bearing Based on Local Characteristics |
title_full_unstemmed |
Accurate Detection Method of Aviation Bearing Based on Local Characteristics |
title_sort |
accurate detection method of aviation bearing based on local characteristics |
publisher |
MDPI AG |
series |
Symmetry |
issn |
2073-8994 |
publishDate |
2019-08-01 |
description |
Aviation bearing assembled detection is the final barrier to quality and safety. Therefore, an accurate detection method of aviation bearing that is based on local characteristics is designed to solve the detection problem of mis-assembly and miss-assembly of balls in aviation bearing assembled. When considering the spatial limitation of aviation bearing assembled image acquisition, the dynamic distribution of balls and the interference of lubricating grease on the surface, a dynamic local ball segmentation model that is based on U-Net network with symmetrical structure is designed to achieve the accurate segmentation of the local ball region of aviation bearing. Subsequently, an incomplete circle fitting algorithm is designed based on the segmented local ball image and Hough transform principle. These two algorithms make the measurement error of aviation bearing ball size less than 100 μm. Using bearings validates the algorithm. The results show that the accuracy of dynamic local ball segmentation model that is based on U-Net network with symmetrical structure is over 99%. At the same time, on the basis of accurate segmentation in aviation bearing local ball, the designed Hough circle algorithm is used for circle detection. The experimental results show that the false detection rate of mis-assembly and miss-assembly of balls is less than 3%. Further, the goal of zero-missed detection of mis-assembly and miss-assembly of balls in aviation bearing is achieved. The accurate segmentation of aviation bearing local ball and the effective identification of mis-assembly and miss-assembly of balls are realized. This method can provide a theory for the improvement of mis-assembly and miss-assembly of balls detection in aviation bearing. Furthermore, it has high application value. |
topic |
aviation bearing local characteristics U-Net network Hough transform |
url |
https://www.mdpi.com/2073-8994/11/9/1069 |
work_keys_str_mv |
AT pingxue accuratedetectionmethodofaviationbearingbasedonlocalcharacteristics AT yalijiang accuratedetectionmethodofaviationbearingbasedonlocalcharacteristics AT hongminwang accuratedetectionmethodofaviationbearingbasedonlocalcharacteristics AT haihe accuratedetectionmethodofaviationbearingbasedonlocalcharacteristics |
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