Research on a Tri-axial Differential-Drive In-Pipe Robot

Jiang, Shengyuan; Jiang, Xudong; Lü, Jie; Li, Jianyong; Lv, Xiangyan

doi:10.1007/978-3-540-88513-9_110

Cited by 1 publication

(2 citation statements)

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“…Jiang et al in [49] propose a three-axis differential drive pipe robot, which consists of a differential mechanism and a mechanism for adapting to variations in pipe diameter. The robot is equipped with three pairs of drive wheels.…”

Section: Adapting Mechanisms Based On Combined Linkagesmentioning

confidence: 99%

“…Jiang et al in [49] propose a three-axis differential drive pipe robot, a differential mechanism and a mechanism for adapting to variations i The robot is equipped with three pairs of drive wheels. A 3-DOF tri-axial mechanism for steering allows the robot to easily adapt to any existing pi After the differential output, a bevel gear and a set of synchronous belts vide the required torque to the driving wheels.…”

Section: Adapting Mechanisms Based On Combined Linkagesmentioning

confidence: 99%

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Adapting Mechanisms for In-Pipe Inspection Robots: A Review

Rusu

Tătar

2022

Applied Sciences

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In-pipe inspection robots have proven useful in examining the inside of pipes without affecting their structure, therefore, the interest in researching these robots has constantly increased over time. There are many different types of inspection robots, but the most commonly used are the wall pressed type. This paper proposes a review of the wall pressed type inspection robots in terms of adapting mechanisms. By adapting mechanism is meant a simple linkage or a combination of linkages, with an active or passive force generation system used to adapt the robot to variations in pipe diameter. The characteristics of the different adaptation mechanisms are compared and analyzed regarding the type of linkages used, how the pressure force on the pipe wall is obtained, and the possibility of ensuring the movement through inclined or vertical pipes with elbows and branches.

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Section: Adapting Mechanisms Based On Combined Linkagesmentioning

confidence: 99%

Section: Adapting Mechanisms Based On Combined Linkagesmentioning

confidence: 99%