Detection of Elevator Cable Slippage Using Streaming Image Process Algorithm

Abstract

Elevators are the most common transportation tool in modern buildings. To satisfy the safety requirement, it is mandatory to carry out regular maintenance in a certain period of time. Among maintenance items, the determination of the traction compartment cable slippage status is one of the greatest challenges in the elevator industry, but a simple and effective method is still lacking. Currently, in a real situation, the inspection accuracy relies considerably on suitable personnel experiences, and the inspection process is also time-consuming. Accordingly, we aim to develop an automatic streaming image process model for the detection of the elevator cable slipping distance. First, the geometric shape of an ellipse is established from a captured circle image. Second, the ellipse is averaged and segmented into 360° with a predefined label as a reference point. Third, the circumference formula is applied to the calculation of the cable slipping distance. Finally, the outcome of the arithmetic operation is sent to the cloud database through a graphical user interface (GUI) on the web for monitoring purposes. The experimental results reveal that the standard deviation is as small as 1.153 mm, and the measurement uncertainty is only 0.258 mm, demonstrating high accuracy, rapidity, and robustness.