Academic literature on the topic 'Drying system control'
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Journal articles on the topic "Drying system control"
Di, Shuyu, and Shumei Di. "The Development and Implementation of Alcohol Plant Fan Drying Control System." International Journal of Modeling and Optimization 4, no. 2 (February 2014): 137–40. http://dx.doi.org/10.7763/ijmo.2014.v4.361.
Full textAprillia, Bandiyah Sri, Brahmantya Aji Pramudita, and Prisma Megantoro. "Temperature Control System on Greenhouse Effect Gaplek Dryer." JURNAL INFOTEL 14, no. 1 (February 26, 2022): 50–56. http://dx.doi.org/10.20895/infotel.v14i1.736.
Full textYuan, Yan Wei, Zheng Sun, Shu Jun Li, Xin Dong, Jun Ning Zhang, and Li Ming Zhou. "Adaptive Control System of Coated Seed Dryer." Applied Mechanics and Materials 536-537 (April 2014): 1261–66. http://dx.doi.org/10.4028/www.scientific.net/amm.536-537.1261.
Full textFeng, Jingxiao, and Xijuan Wang. "Research on electrical automatic control system based on PLC." Journal of Physics: Conference Series 2258, no. 1 (April 1, 2022): 012079. http://dx.doi.org/10.1088/1742-6596/2258/1/012079.
Full textWang, Zheng Shun, Yu Dou, and Chang Jian Zhou. "Studying on Expert Control System Used in the Electromagnetic Drying." Advanced Materials Research 588-589 (November 2012): 1573–76. http://dx.doi.org/10.4028/www.scientific.net/amr.588-589.1573.
Full textМарсов, Вадим Израилевич, Александр Маркович Колбасин, Марина Юрьевна Абдулханова, and Андрей Валентинович Курилин. "Two-channel control system of thermal drying." Automation and Control in Technical Systems, no. 2 (January 4, 2015): 132. http://dx.doi.org/10.12731/2306-1561-2014-2-13.
Full textDi, Shu Yu, and Huan Yu Chi. "Design and Simulation of Automatic Control System for Feed-Drier." Applied Mechanics and Materials 548-549 (April 2014): 990–94. http://dx.doi.org/10.4028/www.scientific.net/amm.548-549.990.
Full textPeng, Yuhao, and Tianping Ren. "Design of Heat Exchange System of Sand Core Drying Furnace." Journal of Physics: Conference Series 2083, no. 3 (November 1, 2021): 032056. http://dx.doi.org/10.1088/1742-6596/2083/3/032056.
Full textJia Heming, Song Wenlong, Wang Haitao, and Yang Xin. "Immune PID Algorithm of Wood Drying Control System." International Journal of Advancements in Computing Technology 4, no. 9 (May 31, 2012): 248–58. http://dx.doi.org/10.4156/ijact.vol4.issue9.29.
Full textKONDO, Yoshio. "A Drying System Using Wavelength Control Infrared Heater." Journal of the Surface Finishing Society of Japan 66, no. 7 (2015): 300–304. http://dx.doi.org/10.4139/sfj.66.300.
Full textDissertations / Theses on the topic "Drying system control"
Fengming, Li. "Modeling and Control of Algae Harvesting, Dewatering and Drying (HDD) Systems." Case Western Reserve University School of Graduate Studies / OhioLINK, 2012. http://rave.ohiolink.edu/etdc/view?acc_num=case1333480231.
Full textLi, Zhenfeng 1968 Oct 9. "Design of a microcontroller-based, power control system for microwave drying." Thesis, McGill University, 2004. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=82278.
Full textWiese, Johannes Jacobus. "System identification and model-based control of a filter cake drying process." Thesis, Stellenbosch : University of Stellenbosch, 2011. http://hdl.handle.net/10019.1/6654.
Full textENGLISH ABSTRACT: A mineral concentrate drying process consisting of a hot gas generator, a flash dryer and a feeding section is found to be the bottleneck in the platinum concentrate smelting process. This operation is used as a case study for system identification and model-based control of dryers. Based on the availability of a month's worth of dryer data obtained from a historian, a third party modelling and control software vendor is interested in the use of this data for data driven model construction and options for dryer control. The aimed contribution of this research is to use only data driven techniques and attempt an SID experiment and use of this model in a controller found in literature to be applicable to the dryer process. No first principle model was available for simulation or interpretation of results. Data were obtained for the operation from the plant historian, reduced, cleaned and investigated for deterministic information through surrogate data comparison – resulting in usable timeseries from the plant data. The best datasets were used for modelling of the flash dryer and hot gas generator operations individually, with the hot gas generator providing usable results. The dynamic, nonlinear autoregressive models with exogenous inputs were identified by means of a genetic programming with orthogonal least squares toolbox. The timeseries were reconstructed as a latent variable set, or “pseudo-embedding”, using the delay parameters as identified by average mutual information, autocorrelation and false nearest neighbours. The latent variable reconstruction resulted in a large solution space, which need to be investigated for an unknown model structure. Genetic Programming is capable of identifying unknown structures. Freerun prediction stability and sensitivity analysis were used to assess the identified best models for use in model based control. The best two models for the hot gas generator were used in a basic model predictive controller in an attempt to only track set point changes. One step ahead modelling of the flash dryer outlet air temperature was unsuccessful with the best model obtaining a validation R2 = 43%. The lack of process information contained in the available process variables are to blame for the poor model identification. One-step ahead prediction of the hot gas generator resulted in a top model with validation R2 = 77.1%. The best two hot gas generator models were implemented in a model predictive controller constructed in a real time plant data flow simulation. This controller's performance was measured against set point tracking ability. The MPC implementation was unsuccessful due to the poor freerun prediction ability of the models. The controller was found to be unable to optimise the control moves using the model. This is assigned to poor model freerun prediction ability in one of the models and a too complex freerun model structure required. It is expected that the number of degrees of freedom in the freerun model is too much for the optimiser to handle. A successful real time simulation architecture for the plant dataflow could however be constructed in the supplied software. It is recommended that further process measurements, specifically feed moisture content, feed temperature and air humidity, be included for the flash dryer; closed loop system identification be investigated for the hot gas generator; and a simpler model structure with smaller reconstructed latent variable regressor set be used for the model predictive controller.
AFRIKAANSE OPSOMMING: 'n Drogings proses vir mineraal konsentraat bestaan uit drie eenhede: 'n lug verwarmer-, 'n blitsdroeër- en konsentraat toevoer eenheid. Hierdie droeër is geïdentifiseer as die bottelnek in die platinum konsentraat smeltingsproses. Die droeër word gebruik as 'n gevallestudie vir sisteem identifikasie asook model-gebasseerder beheer van droeërs. 'n Maand se data verkry vanaf die proses databasis, het gelei tot 'n derde party industriële sagteware en beheerstelsel maatskappy se belangstelling in data gedrewe modelering en beheer opsies vir die drogings proses. Die doelwit van hierdie studie is om data gedrewe modeleringstegnieke te gebruik en die model in 'n droeër-literatuur relevante beheerder te gebruik. Geen eerste beginsel model is beskikbaar vir simulasie of interpretasie van resultate nie. Die verkrygde data is gereduseer, skoon gemaak en bestudeer om te identifiseer of die tydreeks deterministiese inligting bevat. Dit is gedoen deur die tydreeks met stochastiese surrogaat data te vergelyk. Die mees gepaste datastelle is gebruik vir modellering van die blitsdroeër en lugverwarmer afsonderlik. Die nie-liniêre, dinamiese nie-linieêre outeregressie modelle met eksogene insette was deur 'n genetiese programmering algoritme, met ortogonale minimum kwadrate, identifiseer. Die betrokke tydreeks is omskep in 'n hulp-veranderlike stel deur gebruik te maak van vertragings-parameters wat deur gemiddelde gemeenskaplike inligting, outokorrelasie en vals naaste buurman metodes verkry is. Die GP algoritme is daartoe in staat om the groot oplossings ruimte wat deur hierdie hulp-veranderlike rekonstruksie geskep word, te bestudeer vir 'n onbekende model struktuur. Die vrye vooruitskattings vermoë, asook die model sensitiwiteit is inag geneem tydens die analiese van die resultate. Die beste modelle se gepastheid tot model voorspellende beheer is gemeet deur die uitkomste van 'n sensitiwiteits analise, asook 'n vrylopende voorspelling, in oënskou te neem. Die een-stap vooruit voorspellende model van die droeër was onsusksesvol met die beste model wat slegs 'n validasie R2 = 43% kon behaal. Die gebrekkige meet instrumente in die droeër is te blameer vir die swak resultate. Die een-stap vooruit voorspellende model van die lug verwarmer wat die beste gevaar het, het 'n validasie R2 = 77.1% gehad. 'n Basiese model voorspellende beheerder is gebou deur die 2 beste modelle van slegs die lugverwarmer te gebruik in 'n intydse simulasie van die raffinadery data vloei struktuur. Hierdie beheerder se vermoë om toepaslike beheer uit te oefen, is gemeet deur die slegs die stelpunt te verander. Die beheerder was egter nie daartoe in staat om die insette te optimeer, en so die stelpunt te volg nie. Hierdie onvermoë is as gevolg van die kompleks vrylopende model struktuur wat oor die voorspellingsvenster optimeer moet word, asook die onstabiele vryvooruitspellings vermoë van die modelle. Die vermoede is dat die loslopende voorspelling te veel vryheids grade het om die insette maklik genoeg te optimeer. Die intydse simulasie van die raffinadery se datavloei struktuur was egter suksesvol. Beter meting van noodsaaklike veranderlikes vir die droër, o.a. voginhoud van die voer, voer temperatuur, asook lug humiditeit; geslotelus sisteem identifikasie vir die lugverwarmer; asook meer eenvoudige model struktuur vir gebruik in voorspellende beheer moontlik vermag deur 'n kleiner hulp veranderlike rekonstruksie te gebruik.
LIMA, Wellington Sousa. "Análises de sistemas de secagem: solar, elétrico e misto na produção de banana passa." Universidade Federal de Campina Grande, 2017. http://dspace.sti.ufcg.edu.br:8080/jspui/handle/riufcg/969.
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Este trabalho apresenta um estudo comparativo de sistemas de secagem para produção de banana passa. Foram utilizados um secador solar de exposição indireta com sistema de aquisição e controle das propriedades termodinâmicas do ar de secagem, e um secador elétrico automatizado com sistema de supervisão e controle embarcados . Os sistemas de secagem estudados neste trabalho foram: secagem solar, secagem elétrica e secagem mista (secagem solar seguida de secagem elétrica). Os testes experimentais foram realizados na UFCG em Campina Grande, PB, para secagem de banana prata (Musa spp.). O produto final obtido pelos três sistemas de secagem apresentou boa qualidade em relação ao aspecto visual, com um percentual de umidade em base úmida menor que 25%, compatível com o recomendado pela Resolução RDC n° 272/05 da ANVISA. O sistema de aquisição e controle de dados, como inovação no secador solar, utilizando a plataforma Arduino, garantiu a medição de temperatura e umidade relativa do ar de secagem nas entradas e saídas do coletor solar e da câmara de secagem, e também o acionamento e controle da convecção forçada no sistema de secagem para manter a temperatura no interior da câmara de secagem entre 40ºC e 60ºC. Como resultado, são apresentados os valores obtidos para rendimento do secador solar, consumo específico de energia (CEE), eficiência do processo de secagem e tempo de secagem. Por meio dos experimentos com o secador solar e com o secador elétrico foram obtidas as curvas de cinética de secagem da banana. Os resultados foram comparados e mostraram que o modelo matemático de Page é apropriado para predizer o tempo de secagem. O coeficiente de determinação (R²) obtido na secagem elétrica, na secagem mista e na secagem solar com controle, foram superiores ao obtido na secagem solar sem controle, isso demostra a importância do controle das propriedades termodinâmicas nos processos de secagem. Com relação ao CEE, o processo de secagem elétrica apresentou um CEE de 379,33 kWh por ciclo com temperatura de 45ºC e 225,54 kWh por ciclo com temperatura de 55ºC. Por outro lado o processo de secagem mista apresentou um CEE de 295,87 kWh por ciclo, a uma temperatura de 45ºC, e o processo de secagem solar apresentou um CEE médio de 45,83 kWh por ciclo. Isso mostra a grande vantagem comparativa do secador solar em relação ao secador elétrico. Com relação à eficiência mássica para os três processos de secagem, os mesmos apresentaram eficiências mássicas equivalentes em torno de 89%, o que já era esperado. Com relação aos rendimentos térmicos do secador solar, obtidos nos processos de secagem solar com controle e sem controle da temperatura , foram respectivamente 27,85% e 30,65%. Esses resultados são ligeiramente maiores que os reportados na literatura, o que indica que o secador solar desenvolvido na UFCG apresenta um elevado padrão na secagem de banana, além do fácil manuseio, construção e operacionalidade.
This paper presents a comparative study of drying systems for the production of dried bananas. An indirect solar exposure dryer with acquisition system and control of the thermodinamic properties of the drying air, and an automatized electric dryer with embedded control and supervision system were used. The drying systems studied in this paper were: solar drying, electrical drying and mixed drying (solar drying followed by electrical drying). The experimental tests were performed at the UFCG in Campina Grande, PB, for the drying of bananas (Musa spp.). The final product obtained by the three drying systems presented good visual aspect, scent and flavour, and moisture percentage at moist base less than 25%, compatible to the resolution RDC nº 272/05 of the ANVISA. The acquisition system a nd data control, added as inovation at the solar dryer, using the Arduino plataform, granted the measurement of the temperature and air relative moisture of drying air, both in the entrance and exit of the solar colector of the drying chamber, and also the activation and control of the forced convection of the drying system to keep the temperature in the drying chamber between 40ºC and 60ºC. As results, the obtained values to the drying system efficiency are presented, specific comsuption of energy (CEE), drying system efficiency and drying time. Through the experiments with the solar and the electric dryers, the curves that represent the drying kinectics of the banana were obtained. The results were compared and showed that Page’s mathematical model is adequate to predict the drying time. The determination coefficient (R²) obtained at the electric dryer was superior to the solar dryer, this shows that the control system of the thermodinamics properties of the drying air is more efficient on the electric dryer. In relation to the CEE, the electric drying showed a CEE of 379.33 kWh per cycle with a temperature of 45ºC and 225.54 kWh per cycle at the temperature of 55ºC . On the other hand, the mixed drying had a CEE of 295.87 kWh per cycle, at a temperature of 45 ºC, and the solar drying a medium CEE of 45.83 kWh per cycle. This shows the great comparative advantage of the solar dryer when compared to the electric dryer. In relation to the massic efficiency to the 3 drying processes, they showed equivalente massi c efficiency around 89%, which was expected. In relation to the thermic efficiencies of the solar dryer, obtained on the experiments with and without temperature control, were respectively 27.85%, 30.65%, these results show that the obtained resulsts are slightly superior to the results reported on the literature, which indicates that the solar dryer under development in the UFCG shows high efficiency to perform the drying of bananas, although its easy to construct and operate.
Евсина, Наталья Александровна. "Синтез нечеткого регулятора для системы управления процессом сушки капиллярно-пористых материалов." Thesis, НТУ "ХПИ", 2015. http://repository.kpi.kharkov.ua/handle/KhPI-Press/19590.
Full textThe thesis on Candidate Degree in Technical Sciences: Specialty 05.13. 03 - management systems and processes.– National Technical University "Kharkov Polytechnic Institute", Kharkov 2015. This thesis is devoted to the development and improvement of the synthesis method of a fuzzy regulator which ensures the specified quality to control the drying of the capillary and porous materials in a convection oven of periodic action and allows creating the control systems basing on the expert knowledge. The work describes the improved method of the optimal control sensitivity analysis in a linear system with a quadratic quality criterion which allowed obtaining the control insensitivity conditions to a slightly changed parameters in a closed system. Basing on the performed analysis the thesis shows the necessity to perform a joint research of the optimized functionality sensitivity and the sensitivity of the optimal movementtrajectory. The thesis offers a simple synthesis algorithm of the fuzzy and logical regulator which provides the ability to use a standard format describing the linguistic variables and a minimum set of the operating rules. The regulators built on the basis of fuzzy logic in some cases are capable to provide higher quality rates of the transition processes in comparison with classic regulators. Using the synthesis methods of fuzzy control algorithms, it is possible to optimize the difficult control loops omitting mathematical model specification.
Євсіна, Наталя Олександрівна. "Синтез нечіткого регулятора для системи управління процесом сушіння капілярно-пористих матеріалів." Thesis, НТУ "ХПІ", 2016. http://repository.kpi.kharkov.ua/handle/KhPI-Press/19587.
Full textThe thesis on Candidate Degree in Technical Sciences: Specialty 05.13. 03 - management systems and processes.– National Technical University "Kharkov Polytechnic Institute", Kharkov 2015. This thesis is devoted to the development and improvement of the synthesis method of a fuzzy regulator which ensures the specified quality to control the drying of the capillary and porous materials in a convection oven of periodic action and allows creating the control systems basing on the expert knowledge. The work describes the improved method of the optimal control sensitivity analysis in a linear system with a quadratic quality criterion which allowed obtaining the control insensitivity conditions to a slightly changed parameters in a closed system. Basing on the performed analysis the thesis shows the necessity to perform a joint research of the optimized functionality sensitivity and the sensitivity of the optimal movementtrajectory. The thesis offers a simple synthesis algorithm of the fuzzy and logical regulator which provides the ability to use a standard format describing the linguistic variables and a minimum set of the operating rules. The regulators built on the basis of fuzzy logic in some cases are capable to provide higher quality rates of the transition processes in comparison with classic regulators. Using the synthesis methods of fuzzy control algorithms, it is possible to optimize the difficult control loops omitting mathematical model specification.
Li, Zhenfeng 1968 Oct 9. "Aroma detection and control in passive and dynamic food systems for superior product." Thesis, McGill University, 2008. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=115879.
Full textPassive aroma detection of unprocessed foods and dynamic aroma detection during food processing was undertaken using a fast GC analyzer -- zNose. During the study on the passive aroma detection, the aroma of Chinese spirits (Fenjiu) and mango (Mangifera indica L.) fruits, (i.e., liquid and solid states, respectively) was analyzed. In the study of Chinese spirits, aroma profiles of Fenjiu liquor samples of different quality levels were acquired and used for quality classification and prediction. Measurements of dielectric properties of the samples were also conducted to estimate alcohol concentration. In the study of mango fruits, aroma changes of mango samples were monitored during their shelf life and used to evaluate mango quality. Ripening and rots were detected with 80% and 93% accuracy, respectively.
During the study of dynamic aroma detection, a real-time aroma monitoring and control system was developed for use during microwave drying. Aroma signals of a processed food item were detected with zNose and analyzed with a fuzzy logic algorithm to determine the optimal food drying temperature. Phase control was used to adjust the microwave power level to meet temperature requirements. Carrot (Daucus carota L.) and apple (Malus domestica Borkh) were selected as representatives of vegetables and fruits. In carrot drying, samples could be dried in a short time at high temperatures but the interior of some sample cubes was burnt. Drying at a lower temperature extended the drying process, but led to a great loss of aroma in the finished product.' The best results were obtained at 60°C. Based on these results, a fuzzy logic controller was designed and employed to control the drying process according to carrot aroma changes. To investigate the possibility of aroma improvement without zNose assistance, a linear control method was developed whereby a temperature control profile imitated the fuzzy logic control, but aroma control was not included. With these new control strategies, the carrot color and flavour were significantly improved and less time and power were consumed. Similar results were achieved when apple was microwave-dried. Apple aroma was monitored online during microwave drying processes and controlled with similar fuzzy and linear control strategies. Apple color, aroma, and overall appearance remained intact with the new strategies and less time and power were consumed. In contrast to the carrot drying, a different linear temperature profile was required for apple drying in terms of aroma retention.
Raut, Sharvari [Verfasser]. "Optimizing drying processes for agricultural products utilising non-invasive measurement and adaptive control systems / Sharvari Raut." Kassel : Universitätsbibliothek Kassel, 2021. http://d-nb.info/1240918372/34.
Full textShin, Hae Soo. "Effect of irrigation systems, partial root zone drying irrigation and regulated deficit, on plant parasitic nematode populations in grapevine." University of Western Australia. School of Earth and Geographical Sciences, 2006. http://theses.library.uwa.edu.au/adt-WU2006.0046.
Full textČermák, Jiří. "Návrh elektročásti zařízení na máčení a sušení jader pro tvorbu odlitků." Master's thesis, Vysoké učení technické v Brně. Fakulta elektrotechniky a komunikačních technologií, 2017. http://www.nusl.cz/ntk/nusl-318169.
Full textBooks on the topic "Drying system control"
Holmes, Jonathan, and Philipp Hoelzmann. The Late Pleistocene-Holocene African Humid Period as Evident in Lakes. Oxford University Press, 2017. http://dx.doi.org/10.1093/acrefore/9780190228620.013.531.
Full textBook chapters on the topic "Drying system control"
Chang, T. N., and Y. H. Ma. "Application of Optimal Control Strategy to Hybrid Microwave and Radiant Heat Freeze Drying System." In Drying ’85, 249–53. Berlin, Heidelberg: Springer Berlin Heidelberg, 1985. http://dx.doi.org/10.1007/978-3-662-21830-3_31.
Full textFei, Qiang, BiaoJin, Lijing Yan, Lian Yao Tang, and Rong Chen. "Research on Intelligent Control System of Corn Ear Vertical Drying Bin." In Advanced Intelligent Technologies for Industry, 249–54. Singapore: Springer Nature Singapore, 2022. http://dx.doi.org/10.1007/978-981-16-9735-7_23.
Full textGao, Xiaoyang, Yang Bi, Lili Zhang, Jingjing Chen, and Jianmin Yun. "The Temperature Fuzzy Control System of Barleythe Malt Drying Based on Microcontroller." In IFIP Advances in Information and Communication Technology, 771–78. Boston, MA: Springer US, 2009. http://dx.doi.org/10.1007/978-1-4419-0209-2_79.
Full textFauchoux, M. T., C. J. Simonson, D. A. Torvi, R. M. Eldeeb, and T. Ojanen. "Cost Effective and Energy Efficient Control of Indoor Humidity in Buildings with Hygroscopic Building Materials and Desiccants in the HVAC System." In Drying and Wetting of Building Materials and Components, 175–96. Cham: Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-04531-3_8.
Full textMartynenko, Alex. "What Is the Future of Intelligent Systems in Drying?" In Intelligent Control in Drying, 441–43. Boca Raton : Taylor & Francis, a CRC title, part of the Taylor & Francis imprint, a member of the Taylor & Francis Group, the academic division of T&F Informa, plc, 2018. | Series: Advances in drying science & technology: CRC Press, 2018. http://dx.doi.org/10.1201/9780429443183-22.
Full textNadian, Mohammad Hossein. "Intelligent Control of Fruit Drying Based on Computer Vision Systems." In Intelligent Control in Drying, 253–80. Boca Raton : Taylor & Francis, a CRC title, part of the Taylor & Francis imprint, a member of the Taylor & Francis Group, the academic division of T&F Informa, plc, 2018. | Series: Advances in drying science & technology: CRC Press, 2018. http://dx.doi.org/10.1201/9780429443183-14.
Full textAghbashlo, Mortaza, Soleiman Hosseinpour, and Arun S. Mujumdar. "Artificial Neural Network-Based Modeling and Controlling of Drying Systems." In Intelligent Control in Drying, 155–72. Boca Raton : Taylor & Francis, a CRC title, part of the Taylor & Francis imprint, a member of the Taylor & Francis Group, the academic division of T&F Informa, plc, 2018. | Series: Advances in drying science & technology: CRC Press, 2018. http://dx.doi.org/10.1201/9780429443183-9.
Full textBobkov, Vladimir, Maksim Dli, and Alexandr Fedulov. "Simulation Modeling for Drying Process of Pellets from Apatite-Nephenine Ores Waste." In Studies in Systems, Decision and Control, 241–51. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-66081-9_19.
Full textDubois, Olivier, Jean-Louis Nicolas, and Alain Billat. "A Radial Basis Function Network Model for the Adaptive Control of Drying Oven Temperature." In Neural Network Engineering in Dynamic Control Systems, 239–54. London: Springer London, 1995. http://dx.doi.org/10.1007/978-1-4471-3066-6_12.
Full textBobkov, Vladimir, and Maksim Dli. "Optimal Control for Energy and Resource Efficiency in the Drying Process of Pellets from Apatite-Nepheline Ores." In Studies in Systems, Decision and Control, 253–62. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-66081-9_20.
Full textConference papers on the topic "Drying system control"
Artemova, Svetlana V., Anatoli A. Artemov, Andrey I. Ladynin, and Maria A. Kamenskaia. "Drying Control Information System." In 2020 IEEE Conference of Russian Young Researchers in Electrical and Electronic Engineering (EIConRus). IEEE, 2020. http://dx.doi.org/10.1109/eiconrus49466.2020.9039189.
Full textKozlova, Liudmila P., Aleksandr M. Belov, and Olga A. Kozlova. "Cellulose Drying Machine Control System Simulation." In 2021 IEEE Conference of Russian Young Researchers in Electrical and Electronic Engineering (ElConRus). IEEE, 2021. http://dx.doi.org/10.1109/elconrus51938.2021.9396264.
Full textWei Zhang, Li Peng, and Ning Gao. "New far-infrared drying control system design." In 2010 Chinese Control and Decision Conference (CCDC). IEEE, 2010. http://dx.doi.org/10.1109/ccdc.2010.5498559.
Full textLI, CHANGYOU, and HUA BAN. "SELF-ADAPTIVE CONTROL SYSTEM OF GRAIN DRYING DEVICE." In The Proceedings of the 5th Asia-Pacific Drying Conference. World Scientific Publishing Company, 2007. http://dx.doi.org/10.1142/9789812771957_0073.
Full textMa, Hong, Wei Zhang, and Simon X. Yang. "Systems modeling and intelligent control of meat drying process." In 2015 10th System of Systems Engineering Conference (SoSE). IEEE, 2015. http://dx.doi.org/10.1109/sysose.2015.7151964.
Full textGerasimov, Dmitriy A., Anton I. Sidorenko, Evgeniy S. Povernov, and Evgeniy V. Sypin. "System of automated process control of vacuum drying." In 2012 IEEE 13th International Conference and Seminar of Young Specialists on Micro/Nanotechnologies and Electron Devices (EDM 2012). IEEE, 2012. http://dx.doi.org/10.1109/edm.2012.6310214.
Full textJiang, Zhaoliang, Wenping Liu, Qingyue Wei, and Zhishen Li. "Temperature Simulation and Control System for Automobile Coating Line Drying Rooms." In ASME 2015 International Manufacturing Science and Engineering Conference. American Society of Mechanical Engineers, 2015. http://dx.doi.org/10.1115/msec2015-9375.
Full textSitumorang, Zakarias, Retantyo Wardoyo, Sri Hartati, Jazi Eko Istiyanto, Abdul Halim Hakim, Pandian Vasant, and Nader Barsoum. "COMPUTATION OF PARAMETRIC ADAPTIVE FUZZY CONTROLLER FOR WOOD DRYING SYSTEM." In POWER CONTROL AND OPTIMIZATION: Proceedings of the Second Global Conference on Power Control and Optimization. AIP, 2009. http://dx.doi.org/10.1063/1.3223923.
Full textLiu, Tong, Shan Liang, and Jinglu Hu. "Expert Control System based Hierarchical Control Strategy for Tunnel Microwave Rice Drying." In 2019 18th European Control Conference (ECC). IEEE, 2019. http://dx.doi.org/10.23919/ecc.2019.8795661.
Full textLili Zhang and Xiangyou Wang. "Research on real-time control system of infrared drying process." In 2010 3rd IEEE International Conference on Computer Science and Information Technology (ICCSIT 2010). IEEE, 2010. http://dx.doi.org/10.1109/iccsit.2010.5564925.
Full textReports on the topic "Drying system control"
ANGLESEY, M. O. System Configuration Management Implementation Procedure for the Cold Vacuum Drying Facility Monitoring and Control System. Office of Scientific and Technical Information (OSTI), October 2000. http://dx.doi.org/10.2172/805643.
Full textWHITEHURST, R. Cold Vacuum Drying (CVD) Facility Safety Class Instrumentation & Control System Design Description. Office of Scientific and Technical Information (OSTI), December 1999. http://dx.doi.org/10.2172/798859.
Full textWHITEHURST, R. Cold Vacuum Drying (CVD) Facility Safety Class Instrumentation and Control System Design Description SYS 93-2. Office of Scientific and Technical Information (OSTI), July 1999. http://dx.doi.org/10.2172/797516.
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