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International Standard Serial Number:
ISSN 1001-4551
Sponsor:
Zhejiang University;
Zhejiang Machinery and Electrical Group
Edited by:
Editorial of Journal of Mechanical & Electrical Engineering
Chief Editor:
ZHAO Qun
Vice Chief Editor:
TANG ren-zhong,
LUO Xiang-yang
Tel:
86-571-87041360,87239525
Fax:
86-571-87239571
Add:
No.9 Gaoguannong,Daxue Road,Hangzhou,China
P.C:
310009
E-mail:
meem_contribute@163.com
Abstract: Aiming at solving the problem of large error in the non-contact measurement of traction sheave wear in different lighting conditions, an automatic measurement algorithm of traction sheave wear based on improved DeepLabV3 was proposed. First, the physical model of the traction sheave rope groove was built, a data set of traction sheave rope groove was built based on the collected traction sheave rope groove images. Then, the DeepLabV3s model with squeeze-and-excitation networks (SEnet) and efficient channel attention networks (ECAnet) dual attention mechanism was used to train the data set to classify wire rope and traction sheave. An image processing algorithm integrating the image features of the traction sheave, which using correlation matching algorithm identified and intercepted the target area to locate the wear point and calculate it, was proposed. Finally,in order to verify the performance of the above algorithm, a measurement experiment platform was built, and the robustness verification and error analysis experiments of the algorithm were carried out.The experimental results show that, through algorithm measurement, the absolute error is less than 0.049mm, the root mean square error is less than 0.044mm, and the operating time is less than 2.50s. The results indicate that, comparing with the traditional measurement, it has the characteristics of high precision, automation and non-contact, and can quickly and accurately measure the wear of the traction sheave rope groove in different lighting conditions, which solves the problem of non-contact measurement of traction wheel wear under different lighting environments.
Key words: non-contact measurement; wear loss; attention mechanism; measurement error; image processing; traction sheave rope groove
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