Academic literature on the topic 'Clogging detection'

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Journal articles on the topic "Clogging detection"

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Surówka, Artur Dawid, Marcin Kosiba, Teemu Mikkelä, Asko Kavala, and Marcin Firla. "Low-Parameter Critic-Based Multivariate WGAN Model for Clogging Detection in Drives." Power Electronics and Drives 10, no. 1 (2025): 125–39. https://doi.org/10.2478/pead-2025-0008.

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Abstract Efficient detection of anomalies in the cooling system of variable frequency drives (VFDs) is crucial to minimise downtime costs from overheating. Smart condition monitoring tools, especially those using machine/deep learning, have proven effective for failure detection. Recent research has focussed on environmental factors, such as pollution and humidity, affecting VFDs. Clogging is particularly harmful as it can damage power electronics, leading to extended downtimes. This study explores the use of Wasserstein Generative Adversarial Networks (WGANs) for detecting clogging in drives,
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Liu, Huaqing, Zhen Hu, Shiying Song, et al. "Quantitative Detection of Clogging in Horizontal Subsurface Flow Constructed Wetland Using the Resistivity Method." Water 10, no. 10 (2018): 1334. http://dx.doi.org/10.3390/w10101334.

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Substrate clogging seriously affects the lifetime and treatment performance of subsurface flow constructed wetlands (SSF CWs), and the quantitative detection of clogging is the key challenge in the management of substrate clogging. This paper explores the feasibility of the resistivity method to detect the clogging degree of an SSF CW. The clogged substrate was found to have a high water-holding capacity, which led to low apparent resistivity in the draining phase. On the basis of the resistivity characteristics, clogging quantification was performed with a standard laboratory procedure, i.e.,
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Zhu, Sha, Ying Xu, Chunyang Zu, Yuexiang Li, and Zifeng Yu. "Study on the method of detecting oil pipeline clogging by fluid oscillation theory." Journal of Physics: Conference Series 2418, no. 1 (2023): 012039. http://dx.doi.org/10.1088/1742-6596/2418/1/012039.

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Abstract In order to solve the problem of pipeline clogging detection, a mathematical model of pipeline clogging detection is established by applying fluid oscillation theory. The amplitude of each component harmonic in different periods is expressed by Fourier series, and then the clogging attenuation parameters of each harmonic are obtained. According to the ratio of harmonic of two separate components and the plugging attenuation parameter, the plugging position and magnitude are determined respectively. Through the analysis of numerical simulation and experimental results, it can be conclu
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Liu, Taihua, Bing Lv, Wenqi Zhu, Chenghao Song, and Xianghao Shen. "Optimisation design of water-fertiliser infiltration device based on TRIZ theory." Journal of Physics: Conference Series 2827, no. 1 (2024): 012028. http://dx.doi.org/10.1088/1742-6596/2827/1/012028.

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Abstract This paper is based on functional flow and modular design to optimize the design of water-fertilizer integrated percolation irrigation device. Functional decomposition and the construction of functional structure model are completed, and the detection module and the delivery and irrigation module are identified as the modules to be optimized. Apply TRIZ theory to solve the power supply problem of the detection module in harsh environment and design the energy conversion structure. For the clogging problem of the irrigator, an anti-clogging design, labyrinth flow channel and unclogging
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Vong, Chin Nee, and Peter Ako Larbi. "Development and Prototype Testing of an Agricultural Nozzle Clog Detection Device." Transactions of the ASABE 64, no. 1 (2021): 49–61. http://dx.doi.org/10.13031/trans.13519.

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HighlightsPrototypes of an agricultural nozzle clog detection system (for 18 nozzles) have been successfully developed.Spray quality characteristics (droplet size, pattern, and coverage) were not significantly affected when testing the device with extended-range nozzles (TeeJet XR8004).Most of the spray quality characteristics were significantly affected when testing the device with ultra low-drift nozzles (John Deere PSULDQ2004).Abstract. Agricultural nozzles are the main components that perform the spraying of agrochemicals, and their proper functionality is a key element for uniform spray a
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Diniz, Ana P. M., Patrick M. Ciarelli, Evandro O. T. Salles, and 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, no. 1 (2022): 154–68. http://dx.doi.org/10.31181/dmame0313052022d.

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The clogging in the Submerged Entry Nozzle (SEN), responsible for controlling the steel flow in continuous casting, is one of the main problems faced by steelmaking process, since it can increase the frequency of interruptions in the operation for the maintenance and/or exchange of its equipment. Although it is a problem inherent to the process, not identifying the clogging can result in losses associated with the process yield, as well as compromising the product quality. In order to detect the occurrences of clogging in a real steel industry from historical data of process variables, in this
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Johansson, A., and A. Medvedev. "Detection of incipient clogging in pulverized coal injection lines." IEEE Transactions on Industry Applications 36, no. 3 (2000): 877–83. http://dx.doi.org/10.1109/28.845065.

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Lai, Xiao, and Guanglong Fu. "Sugarcane Feed Volume Detection in Stacked Scenarios Based on Improved YOLO-ASM." Agriculture 15, no. 13 (2025): 1428. https://doi.org/10.3390/agriculture15131428.

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Improper regulation of sugarcane feed volume can lead to harvester inefficiency or clogging. Accurate recognition of feed volume is therefore critical. However, visual recognition is challenging due to sugarcane stacking during feeding. To address this, we propose YOLO-ASM (YOLO Accurate Stereo Matching), a novel detection method. At the target detection level, we integrate a Convolutional Block Attention Module (CBAM) into the YOLOv5s backbone network. This significantly reduces missed detections and low-confidence predictions in dense stacking scenarios, improving detection speed by 28.04% a
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Abouelazayem, Shereen, Ivan Glavinić, Thomas Wondrak, and Jaroslav Hlava. "Switched MPC Based on Clogging Detection in Continuous Casting Process." IFAC-PapersOnLine 53, no. 2 (2020): 11491–96. http://dx.doi.org/10.1016/j.ifacol.2020.12.589.

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Becker, Vincent, Thilo Schwamm, Sven Urschel, and Jose Alfonso Antonino-Daviu. "Fault Investigation of Circulation Pumps to Detect Impeller Clogging." Applied Sciences 10, no. 21 (2020): 7550. http://dx.doi.org/10.3390/app10217550.

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Pumps have a wide range of applications. Methods for fault detection of motors are increasingly being used for pumps. In the context of this paper, a test bench is built to investigate circulation pumps for faults. As a use case, the fault of impeller clogging was first measured and then examined with the help of motor current signature analysis. It can be seen that there are four frequencies at which there is an increase in amplitude in case of a fault. The sidebands around the supply frequency are in particular focus. The clogging of three and four of a total of seven channels leads to the h
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Dissertations / Theses on the topic "Clogging detection"

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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.

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Mobile Crowdsensing (MCS) has emerged as a ubiquitous solution for data collection from embedded sensors of the smart devices to improve the sensing capacity and reduce the sensing costs in large regions. Due to the ubiquitous nature of MCS, smart devices require cyber protection against adversaries that are becoming smarter with the objective of clogging the resources and spreading misinformation in such a non-dedicated sensing environment. In an MCS setting, one of the various adversary types has the primary goal of keeping participant devices occupied by submitting fake/illegitimate sensing
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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.

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Dans cette étude, des nanofibres en polyuréthane thermoplastique (TPU) ont été fabriquées en optimisant les paramètres d'électrofilage. Afin de rendre les membranes conductrices, l'encre de carbone a été imprimée sur la surface des membranes de nanofibres de TPU en utilisant différents motifs. Des tests mécaniques, des mesures électromécaniques et des tests cycliques ont démontré des propriétés mécaniques adaptées, des variations de résistance lors de l'étirement et une répétabilité des performances du capteur.Afin d'optimiser les capacités du capteur, des membranes avec des trous structurés o
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Book chapters on the topic "Clogging detection"

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Kaur, Kuljit, and Harpreet Kaur. "Removal of Microplastic Contaminants from Aquatic Environment." In Microplastic Pollution: Causes, Effects and Control. BENTHAM SCIENCE PUBLISHERS, 2023. http://dx.doi.org/10.2174/9789815165104123010007.

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Microplastics (MPs) contamination has recently been recognized as a serious global concern for global food security and modern society's well-being due to its widespread presence in the aquatic and terrestrial environment. According to a growing number of reports, micro- and nanosized plastic components have been discovered in nearly every part of the world, from the bottom of the ocean to the mountain top. Microplastics have become prevalent in the environment due to the gradual disposal of plastic waste, a lack of conventional detection processes with particular removal techniques, and a slow disposal rate. By adsorbing various heavy metals, pathogens, and other chemical additives frequently utilised in the production of raw plastic, microplastics have been shown to work as potential vectors. At the tertiary level of the food chain, microplastics are consumed by marine organisms such as fish and crustaceans, and then by humans. This phenomenon is responsible for clogging digestive systems, disrupting digestion, and ultimately reducing the reproductive growth of entire living species. As a result of these repercussions, microplastics have become a growing concern as a new possible risk, demanding the management of microplastics in aquatic media. This review chapter gives a comprehensive overview of existing and newly developed technologies for detecting and removing microplastics from aquatic environments in order to minimise the ultimate possible impact on aquatic habitats.
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Hahn Schlam, Federico, and 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.

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Salts in the irrigation water cause micro-sprinklers to clog. Farmers find it difficult to detect sprinkler clog due to the great number of trees grown in commercial orchards, causing a reduction in yield and timing problems. In this article, IoT can support farmers with daily soil moisture detection. A wireless sensor network, WSN was developed to warn the farmer from micro-sprinkling clogging. Trees were gathered into groups of 9 trees, where the central tree holds the master microcontroller and the other eight trees presented slave microcontrollers (nodes). The system uses BLE (Bluetooth Low Energy) to communicate between the master microcontroller by BLE. A second WSN using lasers was also tested but resulted to be a little more expensive. Soil moisture sensor performance against corrosion and current consumption was analyzed being the best sensors the V1.2 capacitance probe and the sprinkler-encoder one. When micro-sprinklers did not apply water to a tree, its number was transmitted via LoRa from the master to the producer\'s smartphone to warn him/her. A hexacopter was used to detect canopy stress from a height of 30 m, but only after 7 days of water removal did the NDVI indexes detect it.
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Conference papers on the topic "Clogging detection"

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Surówka, Artur Dawid, Teemu Mikkelä, Asko Kavala, and Marcin Firla. "Dual-Mode Hidden Markov Models For Smart Detection Of Clogging In Variable Frequency Drives." In 2024 IEEE 21st International Power Electronics and Motion Control Conference (PEMC). IEEE, 2024. http://dx.doi.org/10.1109/pemc61721.2024.10726395.

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Lutterbach, Márcia Teresa Soares, Luciana Silva Contador, Mariana Machado Galvão, Viviane de Oliveira, Marcelo Araújo, and Gutemberg de Souza Pimenta. "Real-time PCR Applied to Quantification of SRB in Bottom Water from Fuel Tanks." In CORROSION 2011. NACE International, 2011. https://doi.org/10.5006/c2011-11233.

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Abstract Microorganisms can grow in different types of fuels. The presence of water in the fuel is crucial for the growth of bacteria, fungi and yeasts. Microorganisms may grow in the presence of oxygen (aerobic) or in its absence (anaerobic), feeding primarily on hydrocarbon fuel, minerals and other impurities in the water. The amount of water required for microbial growth is very small. A fuel containing only 1% of water presents favorable conditions for the development of microbial colonies and spores can survive in the presence of only 5 -80 ppm of water. In practice, the bottoms of storag
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Beck, David, Florian Brokhausen, and 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.

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Abstract The effects of clogging in pumps are manifold and change over time. This is demonstrated with time-resolved observations of the operating data on a test rig at the chair of fluid system dynamics of the Technische Universität Berlin. On the test rig, the head, flow, power consumption and efficiency of different pumps operating with artificial wastewater are recorded. In the data, different clogging behavior reflect in the operating parameters. There are three major clogging-induced characteristics to be differentiated in the time-resolved measurements. For some aggregates there is a ra
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Brokhausen, Florian, Lena Marie Rost, and Paul Uwe Thamsen. "Frequency Domain Analysis of Transient Discharge Pressure Harmonics for Clogging Detection in Wastewater Pumps." In ASME 2024 Fluids Engineering Division Summer Meeting collocated with the ASME 2024 Heat Transfer Summer Conference and the ASME 2024 18th International Conference on Energy Sustainability. American Society of Mechanical Engineers, 2024. http://dx.doi.org/10.1115/fedsm2024-122110.

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Abstract Due to the heterogeneous nature of wastewater, the operation of wastewater pumps exhibits challenges beyond the optimization of efficiency and hydraulic performance. Instead, operationality is a paramount feature. The main cause for malfunctions in wastewater pumps is the phenomenon of clogging of the pump impeller to a state of total blockage. There exist automatic procedures to resolve this type of clogging, most prevailing the so-called cleaning sequence. However, the current implementation in practice exhibits the downside of under-determined triggering solutions. This work presen
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Cowart, Jim, Patrick Moore, Harrison Yosten, Leonard Hamilton, and 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.

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A diesel engine electrical generator set (’gen-set’) was instrumented with in-cylinder indicating sensors as well as acoustic emission microphones near the engine. Air filter clogging was emulated by progressive restriction of the engine’s inlet air flow path during which comprehensive engine and acoustic data were collected. Fast Fourier Transforms (FFTs) were analyzed on the acoustic data. Dominant FFT peaks were then applied to supervised machine learning neural network analysis with MATLAB based tools. The progressive detection of the air path clogging was audibly determined with correlati
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Kim, Tae Yoon, and 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.

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Choudhari, Sahil J., Sujay B. J., Swarit Anand Singh, and 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.

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Abstract Although Computer Numerical Control (CNC) machines were designed to perform tasks with the least human intervention, operator involvement is mandatory to ensure fault-free operations. Numerous technological solutions utilizing Artificial Intelligence, sensor fusion, Internet of Things (IoT), machine vision, etc., have been developed for process, component, and machine monitoring to impart smartness and autonomous operating abilities. The primary focus of these solutions is to monitor process faults such as tool wear, chatter, static deflections, and cutting forces to assist the operat
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Choudhari, Sahil J., Swarit Anand Singh, Aitha Sudheer Kumar, and 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.

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Abstract Machine tools can perform manufacturing operations autonomously with minimal involvement of machine operators. However, significant human expertise is required while machine setup to minimize machine faults, downtime, and scrap parts for achieving better productivity. The machine setup involves activities such as the presence/absence of a correct cutting tool in the spindle, adequate placement of workpiece on the fixture, ensuring proper coolant flow, clogging of chips, etc. The present machine shops employ skilled human operators to perform these tasks with a checklist for ensuring c
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Rahman, Md Anisur, Md Asif Hasan Khan, and Jinki Kim. "Nozzle Pressure Defect Detection in Extrusion-Based Bio 3D Printing Using Video-Based Motion Estimation." In ASME 2024 Conference on Smart Materials, Adaptive Structures and Intelligent Systems. American Society of Mechanical Engineers, 2024. http://dx.doi.org/10.1115/smasis2024-140392.

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Abstract The emergence of bio-additive manufacturing marks a crucial advancement in the field of biomedical engineering. For successful biomedical applications including bioprinted organ transplants, ensuring the quality of printed structures poses a significant challenge. Among the major challenges encountered in ensuring the structural integrity of bioprinting, nozzle clogging stands out as one of the frequent concerns in the process. It disrupts the uniform distribution of extrusion pressure, leading to the formation of defective structures. This study focused on detecting defects arising f
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Moore, Patrick, Dianne Luning Prak, Len Hamilton, and 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.

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Abstract A diesel engine electrical generator set (‘gen-set’) was instrumented with an in-cylinder pressure indicating system as well as an acoustic emission sensor near the engine. Air filter clogging, rocker arm gap and fuel cetane changes were applied during which engine combustion and acoustic data were collected. Fast Fourier Transforms (FFTs) were analyzed on the acoustic data. FFT data were then applied to categorical supervised machine learning neural network analysis with MATLAB based tools. The detection of the various degradation modes was audibly determined with correlation coeffic
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Reports on the topic "Clogging detection"

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Seginer, Ido, Louis D. Albright, and Robert W. Langhans. On-line Fault Detection and Diagnosis for Greenhouse Environmental Control. United States Department of Agriculture, 2001. http://dx.doi.org/10.32747/2001.7575271.bard.

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Background Early detection and identification of faulty greenhouse operation is essential, if losses are to be minimized by taking immediate corrective actions. Automatic detection and identification would also free the greenhouse manager to tend to his other business. Original objectives The general objective was to develop a method, or methods, for the detection, identification and accommodation of faults in the greenhouse. More specific objectives were as follows: 1. Develop accurate systems models, which will enable the detection of small deviations from normal behavior (of sensors, contro
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