Letteratura scientifica selezionata sul tema "Clogging detection"
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Articoli di riviste sul tema "Clogging detection":
Liu, Huaqing, Zhen Hu, Shiying Song, Jian Zhang, Lichao Nie, Hongying Hu, Fengmin Li e Zhengyu Liu. "Quantitative Detection of Clogging in Horizontal Subsurface Flow Constructed Wetland Using the Resistivity Method". Water 10, n. 10 (26 settembre 2018): 1334. http://dx.doi.org/10.3390/w10101334.
Zhu, Sha, Ying Xu, Chunyang Zu, Yuexiang Li e Zifeng Yu. "Study on the method of detecting oil pipeline clogging by fluid oscillation theory". Journal of Physics: Conference Series 2418, n. 1 (1 febbraio 2023): 012039. http://dx.doi.org/10.1088/1742-6596/2418/1/012039.
Vong, Chin Nee, e Peter Ako Larbi. "Development and Prototype Testing of an Agricultural Nozzle Clog Detection Device". Transactions of the ASABE 64, n. 1 (2021): 49–61. http://dx.doi.org/10.13031/trans.13519.
Diniz, Ana P. M., Patrick M. Ciarelli, Evandro O. T. Salles e Klaus F. Coco. "Long short-term memory neural networks for clogging detection in the submerged entry nozzle". Decision Making: Applications in Management and Engineering 5, n. 1 (20 marzo 2022): 154–68. http://dx.doi.org/10.31181/dmame0313052022d.
Johansson, A., e A. Medvedev. "Detection of incipient clogging in pulverized coal injection lines". IEEE Transactions on Industry Applications 36, n. 3 (2000): 877–83. http://dx.doi.org/10.1109/28.845065.
Abouelazayem, Shereen, Ivan Glavinić, Thomas Wondrak e Jaroslav Hlava. "Switched MPC Based on Clogging Detection in Continuous Casting Process". IFAC-PapersOnLine 53, n. 2 (2020): 11491–96. http://dx.doi.org/10.1016/j.ifacol.2020.12.589.
Becker, Vincent, Thilo Schwamm, Sven Urschel e Jose Alfonso Antonino-Daviu. "Fault Investigation of Circulation Pumps to Detect Impeller Clogging". Applied Sciences 10, n. 21 (27 ottobre 2020): 7550. http://dx.doi.org/10.3390/app10217550.
Bai, Xue-Dong, Wen-Chieh Cheng, Brian B. Sheil e Ge Li. "Pipejacking clogging detection in soft alluvial deposits using machine learning algorithms". Tunnelling and Underground Space Technology 113 (luglio 2021): 103908. http://dx.doi.org/10.1016/j.tust.2021.103908.
Qiu, Xuefeng, Jiandong Wang, Haitao Wang, Chuanjuan Wang, Yuechao Sun e Guangyong Li. "Elimination of Clogging of a Biogas Slurry Drip Irrigation System Using the Optimal Acid and Chlorine Addition Mode". Agriculture 12, n. 6 (28 maggio 2022): 777. http://dx.doi.org/10.3390/agriculture12060777.
Ibrahim, Najihah, Fadratul Hafinaz Hassan, Nor Muzlifah Mahyuddin e Noorhazlinda Abd Ra. "Cellular Automaton based Fire Spreading Simulation in Closed Area: Clogging Region Detection". International Journal of Engineering & Technology 7, n. 4.44 (1 dicembre 2018): 37. http://dx.doi.org/10.14419/ijet.v7i4.44.26859.
Tesi sul tema "Clogging detection":
Zhang, Yueqian. "Resource Clogging Attacks in Mobile Crowd-Sensing: AI-based Modeling, Detection and Mitigation". Thesis, Université d'Ottawa / University of Ottawa, 2020. http://hdl.handle.net/10393/40082.
Mohamadi, Parian Sadat. "Système innovant de détection du colmatage des filtres à air basé sur les e-textiles". Electronic Thesis or Diss., Centrale Lille Institut, 2023. http://www.theses.fr/2023CLIL0012.
In this study, thermoplastic polyurethane (TPU) nanofibers were fabricated by optimizing electrospinning parameters. In order to make the membranes conductive, the carbon ink was printed on the surface of TPU nanofibers membranes using different patterns. Mechanical tests, electromechanical measurements, and cycle testing demonstrated suitable mechanical properties, resistance changes during stretching, andrepeatability of the sensor performance. To optimize the sensor ability, membranes with structured holeswere fabricated to minimize the pressure drop. Then, the pressure drop and resistance change of the sensorswith various printing patterns were measured in a ventilation tunnel. Comparison with M5 filters showedthat the pressure drop of these printed structured membranes was similar to air filters, and did not cause anincrease in the pressure drop of the system. Moreover, the resistance change of the sensor under differentair velocities indicated high sensitivity. In conclusion, this study successfully developed a facile andscalable technique to fabricate textile sensors for detecting air velocity in air filters
Capitoli di libri sul tema "Clogging detection":
Kaur, Kuljit, e Harpreet Kaur. "Removal of Microplastic Contaminants from Aquatic Environment". In Microplastic Pollution: Causes, Effects and Control, 69–92. BENTHAM SCIENCE PUBLISHERS, 2023. http://dx.doi.org/10.2174/9789815165104123010007.
Hahn Schlam, Federico, e Fermín Martínez Solís. "WSN System Warns Producer When Micro-Sprinklers Do Not Work in Fruit Trees". In Nut Crops - New Insights [Working Title]. IntechOpen, 2022. http://dx.doi.org/10.5772/intechopen.106023.
Atti di convegni sul tema "Clogging detection":
Beck, David, Florian Brokhausen e Paul Uwe Thamsen. "Time-Resolved Measurements for the Detection of Clogging Mechanisms". In ASME 2022 Fluids Engineering Division Summer Meeting. American Society of Mechanical Engineers, 2022. http://dx.doi.org/10.1115/fedsm2022-86961.
Cowart, Jim, Patrick Moore, Harrison Yosten, Leonard Hamilton e Dianne Luning Prak. "Diesel Engine Acoustic Emission Airflow Clogging Diagnostics With Machine Learning". In ASME 2018 Internal Combustion Engine Division Fall Technical Conference. American Society of Mechanical Engineers, 2018. http://dx.doi.org/10.1115/icef2018-9601.
Kim, Tae Yoon, e Young-Ho Cho. "An Electrical Particle Velocity Profiler for In-Channel Clogging Detection and Flow Pattern Characterization". In TRANSDUCERS 2007 - 2007 International Solid-State Sensors, Actuators and Microsystems Conference. IEEE, 2007. http://dx.doi.org/10.1109/sensor.2007.4300245.
Choudhari, Sahil J., Sujay B. J., Swarit Anand Singh e K. A. Desai. "Utilizing Vision-Based Object Detection Algorithms in Recognizing Uncommon Operating Conditions for CNC Milling Machine". In ASME 2023 18th International Manufacturing Science and Engineering Conference. American Society of Mechanical Engineers, 2023. http://dx.doi.org/10.1115/msec2023-105311.
Choudhari, Sahil J., Swarit Anand Singh, Aitha Sudheer Kumar e K. A. Desai. "Machine Setup Abnormality Detection Using Machine Vision and Deep Learning". In ASME 2022 17th International Manufacturing Science and Engineering Conference. American Society of Mechanical Engineers, 2022. http://dx.doi.org/10.1115/msec2022-85519.
Moore, Patrick, Dianne Luning Prak, Len Hamilton e Jim Cowart. "Diesel Engine Acoustic Diagnostics With Machine Learning During Various Degradation Modes". In ASME 2019 Internal Combustion Engine Division Fall Technical Conference. American Society of Mechanical Engineers, 2019. http://dx.doi.org/10.1115/icef2019-7120.
Kumar, Ankit, Amit Priyadarshan e Pragadeesh K. Sekar. "Monitoring Mechanical Equipment on an Offshore Rig with Contrastive Learning on Acoustic Features". In ADIPEC. SPE, 2022. http://dx.doi.org/10.2118/211145-ms.
Nnanna, A. G. Agwu, Chenguang Sheng, Kimberly Conrad e Greg Crowley. "Performance Assessment of Pre-Filtration Strainer of an Ultrafiltration Membrane System by Particle Size Analysis". In ASME 2015 International Mechanical Engineering Congress and Exposition. American Society of Mechanical Engineers, 2015. http://dx.doi.org/10.1115/imece2015-53447.
Tan, Yongwen, Yang Chen, Andrew W. Peterson e Mehdi Ahmadian. "Monitoring and Detecting Fouled Ballast Using Forward-Looking Infrared Radiometer (FLIR) Aerial Technology: Possibilities and Limitations". In 2019 Joint Rail Conference. American Society of Mechanical Engineers, 2019. http://dx.doi.org/10.1115/jrc2019-1327.
Hosseini, SayedMohammad, Yongwen Tan e Mehdi Ahmadian. "Forward-Looking Infrared Radiometry (FLIR) Application for Detecting Ballast Fouling". In 2020 Joint Rail Conference. American Society of Mechanical Engineers, 2020. http://dx.doi.org/10.1115/jrc2020-8032.
Rapporti di organizzazioni sul tema "Clogging detection":
Seginer, Ido, Louis D. Albright e Robert W. Langhans. On-line Fault Detection and Diagnosis for Greenhouse Environmental Control. United States Department of Agriculture, febbraio 2001. http://dx.doi.org/10.32747/2001.7575271.bard.