基于视觉的龙门起重机系统控制

A. Okubanjo, O. Oyetola, O. Adekomaya
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引用次数: 4

摘要

重型材料处理需要一个复杂的工具,以实现高效和最佳的操作。近年来,龙门吊在处理能力、有效性、及时性和安全性方面被认为是一种可靠的选择。然而,如何在最短的时间内使小车尽可能快地定位到所需的设定点,而不出现超调和载荷引起的振荡,一直是起重机动态控制中的难题。在经典控制的基础上,提出、测试和实现了几种控制算法。近年来,视觉控制已被引入到机电一体化领域,作为一个很小或没有影响的桥梁。本文提出了一种基于视觉的软件控制模型,其中网络摄像头作为捕获传感器,使用国家仪器LabVIEW作为编程工具进行图像处理和起重机控制。随后,通过小车位置阶跃递增的实验验证了算法的正确性。结果分析表明,与安装的传感器相比,网络摄像头在小车定位和载荷振荡最小化方面的性能处于最佳水平。
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VISION BASED CONTROL OF GANTRY CRANE SYSTEM
Heavy materials handling requires a sophisticated tool for efficient and optimum operations. In recent times, gantry cranes are considered as a dependable choice in terms of handling capacity, effectiveness, timeliness and safety. However, positioning of a trolley to the desired set point as fast as possible within minimum time without overshoot and payload induced oscillation have remained obstacles in crane dynamic control. Several control algorithms have been proposed, tested and implemented based on classical control. Recently, vision control has been introduced in the field of mechatronics as a bridging gap with little or no impact. In this paper, a vision based software control model is proposed such that webcam serves as a capturing sensor and the National Instrument LabVIEW is used as a programming tool for both image processing and crane control. Subsequently, the results of the proposed algorithm are experimentally validated by step increase in the trolley position. According to the results analysis, it is evident that the webcam performance is at an optimum level when compared with the installed sensor in positioning the trolley and minimizing the payload oscillation.
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