Abstract
This work presents an original software and hardware system whose objective is to detect pressure leaks. Two methods for detection of leaks are considered: the first one is based on an industrial vision system, the second one on a proprietary ultrasonic sensor using Fast Fourier Transformation (FFT). Automation of the measuring process has been done by an industrial six axis robotic arm. For experiments three original laboratory stands have been used.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsReferences
Alves, T., Oliveir, C., Sanin, C., Szczerbicki, E.: From knowledge based vision systems to cognitive vision. Procedia Comput. Sci. 126, 1855–1864 (2018)
Arifin, B.M.S., Li, Z., Shah, S.L.: Pipeline leak detection using particle filters. IFAC-PapersOnLine 48 (2015)
Chen, S., Xiong, J., Guo, W., Bu, R., Zheng, Z., Chen, Y., Yang, Z., Lin, R.: Colored rice quality inspection system using machine vision. J. Cereal Sci. 88, 87–95 (2019)
Chethan, Y., Ravindra, H.V., Krishnegowda, Y.T.: Optimization of machining parameters in turning Nimonic-75 using machine vision and acoustic emission signals by Taguchi technique. Measurement 144, 144–154 (2019)
Giesko, T.: Liquid leak detection using laser triangulation. Institute for Sustainable Technologies, National Research Institute, Radom, vol. 2, pp. 91–97 (2006)
Shaoyan, H., Mingyue, D., Ming, Y.: Sparse-view ultrasound diffraction tomography using compressed sensing with nonuniform FFT. Comput. Math. Methods Med. (2014). Article 329350
Murvay, P., Silea, I.: A survey on gas leak detection and localization techniques. J. Loss Prev. Process Ind. 25, 966–973 (2012)
Operating manual Leakage detector LD 400. CS Instruments GmbH
Pal, B.: Fourier transform ultrasound spectroscopy for the determination of wave propagation parameters. Ultrasonics 73, 140–143 (2017)
Radgen, P.: Efficient Compressed Air Systems. EU-Twinning Project SL04/EN/01 Integrated Pollution Prevention and Control (IPPC) (2006)
Rong, D., Xie, L., Ying, Y.: Computer vision detection of foreign objects in walnuts using deep learning. Comput. Electron. Agric. 162, 1001–1010 (2019)
Seeber, S.: Spectral Analysis of Ultrasound. Mid Atlantic Infrared Services
Sizeland, E.: Ultrasonic devices improve gas leak detection in challenging environments. Emerson Process Management. World Oil 25 (2014)
Sones, R., Novini, A.R.: Machine vision system and method for non-contact container inspection. United States Patent 6172748 (2011)
Wang, J., Tchapmi, L., Ravikumara, A., McGuire, B.C., Zimmerle, D., Savarese, S., Brandt, A.: Machine vision for natural gas methane emissions detection using an infrared camera. Manuscript submitted to Applied Energy
Xue, H., Wu, D., Wang, Y., Zhao, Z., Chen, T., Teng, Y.: Research on ultrasonic leak detection methods of fuel tank. In: 2015 IEEE International Ultrasonics Symposium (IUS), Taipei, Taiwan, pp. 1–4 (2015)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2020 Springer Nature Switzerland AG
About this paper
Cite this paper
Wojtulewicz, A., Ławryńczuk, M. (2020). A System for Detection of Pressure Leaks. In: Bartoszewicz, A., Kabziński, J., Kacprzyk, J. (eds) Advanced, Contemporary Control. Advances in Intelligent Systems and Computing, vol 1196. Springer, Cham. https://doi.org/10.1007/978-3-030-50936-1_28
Download citation
DOI: https://doi.org/10.1007/978-3-030-50936-1_28
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-50935-4
Online ISBN: 978-3-030-50936-1
eBook Packages: Intelligent Technologies and RoboticsIntelligent Technologies and Robotics (R0)