DocumentCode
2042861
Title
Subway lining segment faulting detection based on Kinect sensor
Author
Xinwen Gao ; Liqing Yu ; Zhengzhe Yang
Author_Institution
Sch. of Mechatron. Eng. & Autom., Shanghai Univ., Shanghai, China
fYear
2015
fDate
2-5 Aug. 2015
Firstpage
1076
Lastpage
1081
Abstract
As a kind of tunnel diseases, faulting seriously affect the safety of the tunnel. It is essential to detect lining segment faulting effectively. Compare to traditional detection equipment with high price such as laser camera, a new measurement method for faulting detection by Kinect sensor with low price is proposed. After preprocessing the depth image data, which can be obtained the height difference image by double diagonal difference algorithm. Since the height difference image contains a lot of noise, this paper presents a method of combining the improved median filtering and connectivity domain filtering to solve it. Then recognise faulting, grouting hole and bolt hole through the shape feature. To extract faulting and thinning it. Finally, this paper puts forward a new algorithm called global search, which can identify and calculate the different forms of faulting. The experimental results show that the algorithm can detect and automatically identifies the subway lining segment faulting.
Keywords
fault diagnosis; image denoising; median filters; railway safety; railways; Kinect sensor; bolt hole; connectivity domain filtering; depth image data; double diagonal difference algorithm; global search algorithm; grouting hole; height difference image; median filtering; subway lining segment faulting detection; tunnel safety; Fasteners; Feature extraction; Filtering; Image segmentation; Noise; Standards; faulting; height difference image; kinect; shape feature;
fLanguage
English
Publisher
ieee
Conference_Titel
Mechatronics and Automation (ICMA), 2015 IEEE International Conference on
Conference_Location
Beijing
Print_ISBN
978-1-4799-7097-1
Type
conf
DOI
10.1109/ICMA.2015.7237635
Filename
7237635
Link To Document