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作 者:戚军 Qi Jun(Chongqing Pinzhi Construction Engineering Quality Testing Co.,Ltd.,Chongqing 404100)
机构地区:[1]重庆品智建设工程质量检测有限公司,重庆404100
出 处:《西部特种设备》2025年第1期55-59,共5页Western Special Equipment
摘 要:随着现代建筑技术的飞速发展,电梯作为高层建筑中的重要交通工具,其运行状态的安全性和可靠性至关重要。传统的电梯检测方法多依赖于人工定期检查和维护,不仅效率低下,而且难以及时发现潜在的安全隐患。本文提出了一种基于机器视觉的室内电梯运行状态实时检测技术。该技术通过安装于电梯内部的摄像头捕捉电梯运行过程中的实时视频流,并利用机器学习算法对视频内容进行分析,实现对电梯运行状态的自动监测和故障诊断。该技术不仅提高了检测效率,而且能够准确识别出电梯运行过程中的异常情况,为电梯的预防性维护和及时维修提供了有力的技术支持。With the rapid development of modern building technology,as an important means of transportation in high-rise buildings,the safety and reliability of elevator operation are crucial.Traditional elevator inspection methods often rely on manual regular inspections and maintenance,which not only have low efficiency but also are difficult to detect potential safety hazards in a timely manner.This article proposes a real-time detection technology for indoor elevator operation status based on machine vision.This technology captures real-time video streams during elevator operation through cameras installed inside the elevator,and analyzes the video content using machine learning algorithms to achieve automatic monitoring and fault diagnosis of elevator operation status.This technology not only improves detection efficiency,but also accurately identifies abnormal situations during elevator operation, providing strong technical support for preventive maintenance and timely repair of elevators.
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