基于视觉现实的大型机械监控系统

Yusi Zhang, Jun Ruan
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引用次数: 4

摘要

大型机械(如门式起重机)作为港口机械中的关键设备,其安全可靠的运行对生产的安全运行有着重要的影响。然而,传统传感器的局限性、故障的多样性以及用于机械故障诊断的专家知识的复杂性,给龙门起重机的在线健康监测和故障诊断带来了很大的挑战。光纤布拉格光栅(FBG)传感器已成功应用于桥梁、大坝、石油化工设备等大型结构的在线健康监测。本文采用FGB传感器采集龙门吊钢结构关键部位的应变数据,实现了龙门吊的在线健康监测。在Windows Presentation Foundation (WPF)平台上实现了虚拟现实环境下龙门吊的在线监控。此外,我们还开发了虚拟现实系统来研究设备的三维建模和动态监控。该系统可以根据用户的需要,通过应力分析判断龙门吊的健康状况,预见钢结构存在的安全隐患。这样可以减少盲目的维护工作,并将先进的预测性维护与虚拟现实技术相结合,呈现更好的监控效果。
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Large-scale machinery monitoring system based on the visual reality
As the key equipment in port machinery, Large-scale machinery's (like gantry crane) safe and reliable operation will significantly influence on the safety operation of production. However, the limitations of traditional sensor, the diversity of failure and the complexity of expert knowledge used for mechanical fault diagnosis bring big challenges to online health monitoring and fault diagnosis of gantry crane. Fiber Bragg Grating (FBG) sensors have been successfully applied to the online health monitoring of larger-scale structures including bridges, dams, petrochemical equipment, etc. This paper implements the online health monitoring of gantry crane by employing FGB sensors to collect strain data of the key points in the steel structure of gantry crane. We have achieved the online monitoring the gantry crane under a virtual reality environment on the platform of Windows Presentation Foundation (WPF). Moreover, we have developed virtual reality system to study the establishing of 3D modeling and the dynamic monitoring of equipment. According the needs of users, this system could determine the health status of gantry cranes and foresee the security risks existing in the steel structures by stress analysis. In this way, the blind maintenance work can be reduced and the advanced predictive maintenance can combine with the technology of virtual reality to present a better monitoring result.
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