机器人
无线
管道(软件)
软件
灵活性(工程)
工程类
模拟
无线网络
机械臂
移动机器人
嵌入式系统
计算机科学
实时计算
人工智能
计算机硬件
机械工程
电信
统计
程序设计语言
数学
作者
Kunlun Wu,Haifeng Sang,Yanhao Xing,Yao Lu
出处
期刊:Industrial Robot-an International Journal
[Emerald Publishing Limited]
日期:2022-08-19
卷期号:50 (1): 145-161
被引量:4
标识
DOI:10.1108/ir-02-2022-0043
摘要
Purpose Pipeline robots are often used in pipeline non-destructive testing. Given the need for long-range in-pipe inspections, this study aims to develop a wireless in-pipe inspection robot for image acquisition. Design/methodology/approach In this paper, an in-pipe robot with a new mechanical system is proposed. This system combines a three-arm load-bearing structure with spring sleeves and a half-umbrella diametric change structure, which can ensure the stability of the camera when acquiring images while maintaining the robot’s flexibility. In addition, data were transmitted wirelessly via a system that uses a 433 MHz ultra-high frequency and wireless local-area network–based image transmission system. Software and practical tests were conducted to verify the robot’s design. A preliminary examination of the robot’s cruising range was also conducted. Findings The feasibility of the robot was demonstrated using CATIA V5 and MSC ADAMS software. The simulation results showed that the centre of mass of the robot remained in a stable position and that it could function in a simulated pipeline network. In the practical test, the prototype functioned stably, correctly executed remote instructions and transmitted in near real-time its location, battery voltage and the captured images. Additionally, the tests demonstrated that the robot could successfully pass through the bends in a 200-mm-wide pipe at any angle between 0° and 90°. In actual wireless network conditions, the electrical system functioned for 44.7 consecutive minutes. Originality/value A wheeled wireless robot adopts a new mechanical system. For inspections of plastic pipelines, the robot can adapt to pipes with diameters of 150–210 mm and has the potential for practical applications.
科研通智能强力驱动
Strongly Powered by AbleSci AI