Application of Image Processing to Health Monitoring for Wire Rope of Lift systems

K. Minagawa, S. Fujita
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Abstract

Rupture of wire ropes is one of severe accidents in lift systems.  Before rupture by aging degradation, diameter of wire ropes decreases and surface of wire ropes is rusted.  Thus diameters and red rust of wire ropes should be checked in periodic inspections of lift systems in Japan.  The diameters are usually measured by using vernier calipers or scales, and red rust is checked with eyes, so there are errors and difference among inspectors.  Therefore development of a new monitoring system for the diameters and red rust is required in order to ensure qualities of the inspection and manage the inspection data efficiently.  Meanwhile image processing technology has recently been applied to various industries such as automatic driving vehicles.  This paper proposes and constructs a health monitoring system for wire rope using image processing.  The system consists of a digital camera and a computer.  The digital camera takes a photograph of a wire rope and the photograph is analyzed by the computer.  The diameter is calculated from the number of pixels of the rope, and red rust is detected by resolving the colour of the photograph into RGB data.  This paper describes image processing method for inspection of wire rope and results of verification tests.  Photography condition suitable for monitoring was investigated.  As a result, the measurement error was less than 1% by adjusting photographing condition.
图像处理在电梯钢丝绳健康监测中的应用
钢丝绳断裂是电梯系统中的严重事故之一。在老化退化断裂前,钢丝绳直径减小,钢丝绳表面生锈。因此,在日本电梯系统的定期检查中应该检查钢丝绳的直径和红锈。通常用游标卡尺或标尺测量直径,用眼睛检查红锈,因此检查员之间存在误差和差异。因此,为了保证检测质量和有效地管理检测数据,需要开发一种新的直径和红锈监测系统。同时,图像处理技术最近也被应用到自动驾驶汽车等各个行业。提出并构建了一种基于图像处理的钢丝绳健康监测系统。该系统由一台数码相机和一台计算机组成。数码相机拍下钢丝绳的照片,然后由计算机分析照片。根据绳子的像素数计算直径,并通过将照片的颜色分解为RGB数据来检测红锈。本文介绍了钢丝绳检测的图像处理方法及验证试验结果。探讨了适合监测的摄影条件。通过调整拍摄条件,测量误差小于1%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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