Acoustic leak localization method based on signal segmentation and statistical analysis

Author(s):  
Georgios-Panagiotis Kousiopoulos ◽  
Nikolaos Karagiorgos ◽  
Dimitrios Kampelopoulos ◽  
Vasileios Konstantakos ◽  
Spyridon Nikolaidis
Author(s):  
Jiangyang Huang ◽  
Shane M. Farritor ◽  
Ala’ Qadi ◽  
Steve Goddard

This paper investigates the control and localization of a heterogeneous (different sensor, mechanical, computational capabilities) group of mobile robots. The group considered here has several inexpensive sensor-limited and computationally-limited robots which follow a leader robot in a desired formation over long distances. This situation is similar to a search, de-mining, or planetary exploration situation where there are several deployable/disposable robots led by a more sophisticated leader. Specifically, the robots in this paper are designed for highway safety applications where they automatically deploy and maneuver safety barrels commonly used to control traffic in highway work zones. Complex sensing and computation are performed by the leader while the followers perform simple operations under the leader’s guidance. This architecture allows followers to be simple, inexpensive and have minimal sensors. Theoretical and statistical analysis of a tracking-based localization method is provided. A simple follow-the-leader control method is also presented. Experimental results of localization and follow-the-leader formation-motion are included.


Measurement ◽  
2021 ◽  
Vol 171 ◽  
pp. 108835
Author(s):  
Wenming Wang ◽  
Dashan Yang ◽  
Jifeng Zhang ◽  
Liyun Lao ◽  
Yuanfang Yin ◽  
...  

2018 ◽  
Vol 18 (15) ◽  
pp. 6115-6122 ◽  
Author(s):  
Xianming Lang ◽  
Ping Li ◽  
Jiangtao Cao ◽  
Yan Li ◽  
Hong Ren

2012 ◽  
Vol 233 ◽  
pp. 200-203
Author(s):  
He Hong Qin ◽  
Tao Wang ◽  
Wei Fan

A novel air leak diagnosis and localization method for vessels is proposed. The tempreture field around the leak changes during air inflation and deflation.The changing phenomenon is acquired by thermal camera and the best detecting time is confirmed by temperature curves.Then a local gray-entropy difference algorithm is used to identify the leak area from infrared images captured during inflation and deflation. The gray information of local gray-entropy enhances the difference between leak area and non-leak area largely meanwhile the entropy information of local gray-entropy improves robustness performance.Experiments verify that the leak localization method is effective and sensitive.


Author(s):  
Adria Soldevila ◽  
Joaquim Blesa ◽  
Tom Norgaard Jensen ◽  
Sebastian Tornil-Sin ◽  
Rosa M. Fernandez-Canti ◽  
...  

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