Paper
28 September 2022 Research on image analysis software of elevator wire rope defects
Shuangchang Feng, Wenhao Shen, Chen Wang, Bufan Chen
Author Affiliations +
Proceedings Volume 12339, Second International Conference on Cloud Computing and Mechatronic Engineering (I3CME 2022); 1233924 (2022) https://doi.org/10.1117/12.2655025
Event: Second International Conference on Cloud Computing and Mechatronic Engineering (I3CME 2022), 2022, Chendu, China
Abstract
As an important part of the elevator structure, wire rope carries all loads so that it may be broken due to broken wire, wear and tear, corrosion and so on. The traditional elevator wire rope detection method is inefficient and may cause danger to the inspector. The inspectors observe the defect of the wire rope with eyes and measure the diameter of the wire rope with vernier caliper. In this article, an elevator wire rope defect image analysis software is designed. It can measure without any modification to the elevator brake. so as to avoid the impact of the modification on the performance of the elevator brake. This method is suitable for long-term on-site monitoring and can be used as one of the detection technologies of elevator monitoring system. The software has three main functions: picture browsing and reading function, image processing function and historical data query function. Through processing the image and outputting the treatment results of the wire rope, the software provides professional reference of the elevator safety for the inspector. By comparing the change of wire rope defeat, the inspector can judge whether the wire rope of the elevator still meets the requirements.
© (2022) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Shuangchang Feng, Wenhao Shen, Chen Wang, and Bufan Chen "Research on image analysis software of elevator wire rope defects", Proc. SPIE 12339, Second International Conference on Cloud Computing and Mechatronic Engineering (I3CME 2022), 1233924 (28 September 2022); https://doi.org/10.1117/12.2655025
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KEYWORDS
Inspection

Image processing

Image analysis

Defect detection

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