2009 IEEE International Conference on Robotics and Automation 2009
DOI: 10.1109/robot.2009.5152337
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On autonomous detection of pressured air and gas leaks using passive IR-thermography for mobile robot application

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Cited by 51 publications
(35 citation statements)
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“…The number of scientific papers that deal with the problem of thermographic detection and quantification of compressed air leaks is scanty. Kroll et al [34] report on a novel method for automatic detection of compressed air leaks using software tools for thermogram analysis and pattern recognition. The autonomous analysis of thermogram allows application of autonomous robots, which contribute to easier and safer remote detection of leaks.…”
Section: Infrared Thermographymentioning
confidence: 99%
“…The number of scientific papers that deal with the problem of thermographic detection and quantification of compressed air leaks is scanty. Kroll et al [34] report on a novel method for automatic detection of compressed air leaks using software tools for thermogram analysis and pattern recognition. The autonomous analysis of thermogram allows application of autonomous robots, which contribute to easier and safer remote detection of leaks.…”
Section: Infrared Thermographymentioning
confidence: 99%
“…Examples include the discovery and monitoring of underground fires at mines or landfills [115][116][117][118][119][120][121][122][123], the thermal characteristics of landfill processes [124,125], seeps or the release of leachate into the environment [126,127], or structural characteristics of landfill caps and other remediation methods [36,[128][129][130].…”
Section: Thermal Infrared Applicationsmentioning
confidence: 99%
“…The pipeline can produce indicative signals which are analogous to leakage signal under standard operation. Therefore, designing a costeffective and reliable leak detection system is quite needful for products pipelines [7][8][9]. A guideline has been build up to assess the performance of leak detection systems to check the veracity of pipelines in USTs [10].…”
Section: Introductionmentioning
confidence: 99%