학술논문
An In-Pipe Leak Detection Robot With a Neural-Network-Based Leak Verification System
Document Type
Periodical
Author
Source
IEEE Sensors Journal IEEE Sensors J. Sensors Journal, IEEE. 19(3):1153-1165 Feb, 2019
Subject
Language
ISSN
1530-437X
1558-1748
2379-9153
1558-1748
2379-9153
Abstract
This paper presents a custom designed in-pipe inspection robot that is developed for a pipe of diameter 0.203 m, commonly found in the oil and gas industry. Several pressure sensors are incorporated on board the robot that are used for detecting leaks. The robot has a propeller arrangement that not only drives the robot forward but also helps simulate a flow in an empty pipe, and thus aids the detection of leaks. Furthermore, the leak detection system is augmented by a neural network-based verification framework that improves the robustness of leak detection by allowing the operator to check their identification of a leak by passing it through a neural network-based system. This paper presents the details of the construction of the actual robot and presents experimental data, which show successful neural-networks-based detection of leaks in various scenarios.