Статті в журналах: "Industrial plant monitoring"

1

Ge, Zhiqiang, and Junghui Chen. "Plant-Wide Industrial Process Monitoring: A Distributed Modeling Framework." IEEE Transactions on Industrial Informatics 12, no. 1 (February 2016): 310–21. http://dx.doi.org/10.1109/tii.2015.2509247.

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2

Intelligent Applications Ltd. "Industrial plant/process condition monitoring and fault diagnosis products." Knowledge-Based Systems 1, no. 2 (March 1988): 124. http://dx.doi.org/10.1016/0950-7051(88)90014-7.

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3

Gupta, Sumeet, Shekhar Verma, G. S. Tomar, and Raj Kumar Abrol. "Intelligent Industrial Data Acquisition and Energy Monitoring using Wireless Sensor Networks." International Journal of Grid and High Performance Computing 2, no. 3 (July 2010): 44–59. http://dx.doi.org/10.4018/jghpc.2010070104.

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Most of the application-oriented research in the field of Wireless Sensor Networks has been in remote monitoring, including environmental, building automation, and security. However, this paper presents the methodology followed for implementation of a Wireless Sensor Network based solution in a process plant for energy management and leak detection. The sensor network acquires data pertaining to detection of leakage in a plant. The network further serves effectively as a maintenance and diagnostic system that is used to manage the plant and conserve energy in a process plant. The critical design issues, testing methodologies and implementation problems pertaining to the system are also presented. Additionally, special focus has been placed on the calculations pertaining to the network life time.

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4

Figliuolo Brandão, Rozilda. "Monitoring of Fugitive Emissions in Petrochemical Plant." Water Science and Technology 29, no. 8 (April 1, 1994): 125–33. http://dx.doi.org/10.2166/wst.1994.0395.

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The U.S. Environmental Protection Agency (EPA) estimates that a third of the emissions into the atmosphere in some industrial plants is due to Fugitive Emissions. It defines Fugitive Emissions as the diffuse release of volatile organic compounds (VOC) or hydrocarbons into the atmosphere, through pumps, valves, connections, open-ended lines, compressors, etc., establishing emission patterns and monitoring frequency. COPENE Petroquimica do Nordeste S/A has been implanting a program of fugitive emissions adapted to the reality, trying to promote a continuous improvement in its employees' working conditions and in environmental protection. This paper presents the methodology for the elaboration of this program and the conclusions of some surveys which were already completed.

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5

Weng, Hao, and Jinji Gao. "A Wireless Routing Protocol for Pumps Monitoring in Large Industrial Plant." Research Journal of Applied Sciences, Engineering and Technology 5, no. 9 (March 20, 2013): 2870–77. http://dx.doi.org/10.19026/rjaset.5.4819.

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6

Aguilar-López, Ricardo, Rafael Martínez-Guerra, Juan Mendoza-Camargo, and María Isabel Neria-González. "Monitoring of an industrial wastewater plant employing finite-time convergence observer." Journal of Chemical Technology & Biotechnology 81, no. 6 (2006): 851–57. http://dx.doi.org/10.1002/jctb.1458.

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7

Sharif, M. A., and R. I. Grosvenor. "Process plant condition monitoring and fault diagnosis." Proceedings of the Institution of Mechanical Engineers, Part E: Journal of Process Mechanical Engineering 212, no. 1 (February 1, 1998): 13–30. http://dx.doi.org/10.1243/0954408981529268.

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The paper reviews current research work in the field of process condition monitoring and fault diagnosis. The review compares and contrasts the applicability and efficiency of different techniques, and concentrates on methods which monitor the main process variables. From the wide range of methods and process variables, temperature, flowrate and liquid level are used here in comparing the limitations and applications of each method. The scope of the paper ranges from basic, well established techniques to the latest reported monitoring strategies for each of the process variables. Furthermore, the different methods of fault diagnosis deemed to be relevant in process plant are reviewed. The detection of the internal leakage in the control valves and motor faults are discussed in detail, as examples of the monitoring of vital process plant components. The paper then outlines areas of future work, such as the development of a user friendly interface. This interface is based on state transition diagrams (STDs) as well as on the use of a knowledge based system (KBS) to model and diagnose faults in vital process plant components such as control valves.

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8

Filgueiras, Viviane, Enrique Luis Lima, and José Carlos Pinto. "Long-term statistical stability of industrial plants: Performance indicators and monitoring of an industrial pet plant." Canadian Journal of Chemical Engineering 91, no. 9 (April 18, 2013): 1523–37. http://dx.doi.org/10.1002/cjce.21819.

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9

Ahsan, Q., R. I. Grosvenor, and P. W. Prickett. "Distributed On-Line System for Process Plant Monitoring." Proceedings of the Institution of Mechanical Engineers, Part E: Journal of Process Mechanical Engineering 220, no. 2 (May 1, 2006): 61–77. http://dx.doi.org/10.1243/09544089jpme53.

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This paper describes a methodology for monitoring industrial processes and plant that can be implemented cost-effectively within small-to-medium enterprises. The methodology is based on a network of 8-bit microcontrollers that communicate with each other on a controller area network bus. Ethernet connectivity is provided so that remote users can access the system on the internet. The software models developed for data acquisition nodes and the design of remote user interfaces and supervisory nodes are also explained. The system is aimed at providing specific maintenance guidance and fault identification, rather than gathering data for off-line analysis. Overly complicated processing is avoided to make real-time implementation possible, using 8-bit microcontrollers. The methodology emphasizes the use of process controller signals for fault detection and sensor signals for fault isolation. The suitability of the methodology is explored by acquiring signals from a laboratory-based process rig. Suitable monitoring techniques for the system in time and frequency domains are also discussed.

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10

Farrell, D. M., B. J. Robbins, J. Stallings, S. Cardoso, and W. Bakker. "Crack growth monitoring on industrial plant using established electrical resistance ‘scanner’ technology." Insight - Non-Destructive Testing and Condition Monitoring 50, no. 12 (December 2008): 690–94. http://dx.doi.org/10.1784/insi.2008.50.12.690.

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11

Kirk, K. J., A. McNab, A. Cochram, I. Hall, and G. Hayward. "Ultrasonic arrays for monitoring cracks in an industrial plant at high temperatures." IEEE Transactions on Ultrasonics, Ferroelectrics and Frequency Control 46, no. 2 (March 1999): 311–19. http://dx.doi.org/10.1109/58.753019.

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12

Ge, Zhiqiang. "Review on data-driven modeling and monitoring for plant-wide industrial processes." Chemometrics and Intelligent Laboratory Systems 171 (December 2017): 16–25. http://dx.doi.org/10.1016/j.chemolab.2017.09.021.

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13

West, G. M., S. D. J. McArthur, and D. Towle. "Industrial implementation of intelligent system techniques for nuclear power plant condition monitoring." Expert Systems with Applications 39, no. 8 (June 2012): 7432–40. http://dx.doi.org/10.1016/j.eswa.2012.01.107.

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14

KLEINER, MORRIS M., GERALD NICKELSBURG, and ADAM PILARSKI. "Monitoring, Grievances, and Plant Performance." Industrial Relations 34, no. 2 (April 1995): 169–89. http://dx.doi.org/10.1111/j.1468-232x.1995.tb00367.x.

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15

Kacarska, Marija, Vesna Arnautovski-Toseva, and Sanja Veleva. "Automatic control of industrial peak loads." Facta universitatis - series: Electronics and Energetics 22, no. 3 (2009): 329–39. http://dx.doi.org/10.2298/fuee0903329k.

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Automatic control of equipment is anticipated to represent the next logical step in the progression from passive monitoring toward plant wide automation. Automatic transfer functions, load-shedding and load sequencing are expected to find increasing application. In this paper a device named Peak Load for monitoring and control of power consumption in industrial plants is presented. It is a PLC based maxigraph developed upon the analysis of efficient and optimized use of the electrical energy and is planned to be used by medium and big industrial energy consumers with purpose to decrease the cost of their production. .

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16

H.C, Prof Inyiama, and Dimoji D.O. "SMS Based Remote Monitoring and Control of Industrial Processes using Artificial." International Journal of Computer Engineering and Information Technology 12, no. 1 (January 31, 2020): 1–13. http://dx.doi.org/10.47277/ijceit/12(1)1.

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This paper presents artificial neural network (ANN) based intelligent control system for effective monitoring and control of industrial processes based on Global System for Mobile Communication network (GSM). This system provides ideal solution for monitoring critical oil/gas plant variables such as temperature, pressure, level and flow- rate. Historical and real time data can be accessed worldwide using the GSM network. The proposed system monitors and controls these variables from the remote location and whenever it crosses the set limit, a microcontroller will sends an SMS to concerned plant personnel(s) mobile phone via GSM network. The concerned personnel can control the system through his mobile phone by sending AT Commands to GSM MODEM and in turn to the microcontroller A Nokia N90 series GSM mobile phone was interfaced with a PC via RS 232 serial port. A PC was used as SMS gateway as well as to create a database to store different records to provide list of changes. An SMS enable was also introduced to enable reporting agent to communicate with the plant. Assembly language, C Language and Visual BASIC were used at different stages to program the necessary hardware. Data obtained from this experiment were analyzed using MATLAB. The performance evaluation and the curve generated with MATLAB shows that using ANN controllers to control industrial Process gives better result/performance than on/off controllers

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17

S, Kamalakkannan, and Lavanya J. "Automatic Drilling and Tapping Machine Monitoring using NodeMcu." Bulletin of Scientific Research 2, no. 1 (April 23, 2020): 22–28. http://dx.doi.org/10.34256/bsr2014.

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Industrial automation is most emerging technology, and now a day’s industries almost are operated by automation. Most of the industrial plants, are automated without any operator machine interaction. Using arduino IDE and matlab simulink software, program is developed to indicate the machine status and number of job counts to the server. In this work, consideration was given to nodeMCU controller for drilling and tapping machine monitoring which can be operated both manually and automatically. This system gives a real-time view of the industrial plant, reduction in troubleshooting time for faults and also it assures safety of operator.

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18

Yin, Shen, Juan J. Rodriguez-Andina, and Yuchen Jiang. "Real-Time Monitoring and Control of Industrial Cyberphysical Systems: With Integrated Plant-Wide Monitoring and Control Framework." IEEE Industrial Electronics Magazine 13, no. 4 (December 2019): 38–47. http://dx.doi.org/10.1109/mie.2019.2938025.

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19

Şekertekin, A., Ş. H. Kutoglu, S. Kaya, and A. M. Marangoz. "MONITORING THE SURFACE HEAT ISLAND (SHI) EFFECTS OF INDUSTRIAL ENTERPRISES." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLI-B6 (June 17, 2016): 289–93. http://dx.doi.org/10.5194/isprs-archives-xli-b6-289-2016.

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The aim of this study is to present the effects of industrial enterprises on Land Surface Temperature (LST) and to retrieve Surface Heat Island (SHI) maps of these regions. SHI is one of the types of Urban Heat Island (UHI) and as the urban areas grow in a city, UHI effect becomes bigger. The city centre of Zonguldak was chosen as study area and Landsat 5 satellite data were used as materials. Zonguldak has important industrial enterprises like thermal power plants and iron and steel plant. ERDEMIR is the biggest iron and steel plant in Turkey and it is one of the biggest ones in Europe, as well. There are three operating thermal power plants in the region namely CATES, ZETES1 and ZETES2. In order to investigate these industrial regions, Landsat 5 satellite data were processed using mono-window algorithm to retrieve LST and they were acquired on 11.09.1987, 18.09.2007 and 29.09.2011, respectively. The obtained results revealed that from 1987 to 2011, spatial and temporal variability in LST in industrial enterprises became higher than the surroundings. Besides, the sizes of SHIs in 2011 are bigger than the ones in 1987. For the countries and governments, having industrial enterprises is crucial for the development and it is also important to present the community better conditions in life. Thus, decision makers should consider mitigating the effects of these regions on LST.

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20

Şekertekin, A., Ş. H. Kutoglu, S. Kaya, and A. M. Marangoz. "MONITORING THE SURFACE HEAT ISLAND (SHI) EFFECTS OF INDUSTRIAL ENTERPRISES." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLI-B6 (June 17, 2016): 289–93. http://dx.doi.org/10.5194/isprsarchives-xli-b6-289-2016.

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Анотація:

The aim of this study is to present the effects of industrial enterprises on Land Surface Temperature (LST) and to retrieve Surface Heat Island (SHI) maps of these regions. SHI is one of the types of Urban Heat Island (UHI) and as the urban areas grow in a city, UHI effect becomes bigger. The city centre of Zonguldak was chosen as study area and Landsat 5 satellite data were used as materials. Zonguldak has important industrial enterprises like thermal power plants and iron and steel plant. ERDEMIR is the biggest iron and steel plant in Turkey and it is one of the biggest ones in Europe, as well. There are three operating thermal power plants in the region namely CATES, ZETES1 and ZETES2. In order to investigate these industrial regions, Landsat 5 satellite data were processed using mono-window algorithm to retrieve LST and they were acquired on 11.09.1987, 18.09.2007 and 29.09.2011, respectively. The obtained results revealed that from 1987 to 2011, spatial and temporal variability in LST in industrial enterprises became higher than the surroundings. Besides, the sizes of SHIs in 2011 are bigger than the ones in 1987. For the countries and governments, having industrial enterprises is crucial for the development and it is also important to present the community better conditions in life. Thus, decision makers should consider mitigating the effects of these regions on LST.

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21

Zumoffen, David, Lautaro Braccia, and Patricio Luppi. "Data-Driven Plant-Wide Control Performance Monitoring." Industrial & Engineering Chemistry Research 58, no. 16 (April 2019): 6576–91. http://dx.doi.org/10.1021/acs.iecr.8b06293.

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22

Abramov, A., A. Chepurnov, A. Etenko, M. Gromov, A. Konstantinov, D. Kuznetsov, E. Litvinovich, et al. "iDREAM: industrial Detector of REactor Antineutrinos for Monitoring at Kalinin nuclear power plant." Journal of Instrumentation 17, no. 09 (September 1, 2022): P09001. http://dx.doi.org/10.1088/1748-0221/17/09/p09001.

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Abstract The paper is devoted to the description of the iDREAM detector and its systems. iDREAM is a prototype detector designed to demonstrate the feasibility of antineutrino detectors for remote reactor monitoring and safeguard purposes. Antineutrinos are detected with a 1 ton liquid scintillator via inverse beta decay on protons. In order to suppress cosmic muons, gamma and neutron background, the detector is housed in a dedicated shielding. The detector is installed at the Kalinin nuclear power plant (Russia), 20 m from the 3 GWth reactor core.

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23

Ren, Hao, Zhiwen Chen, Zhaohui Jiang, Chunhua Yang, and Weihua Gui. "An Industrial Multilevel Knowledge Graph-Based Local–Global Monitoring for Plant-Wide Processes." IEEE Transactions on Instrumentation and Measurement 70 (2021): 1–15. http://dx.doi.org/10.1109/tim.2021.3125110.

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24

Yamamoto, Tetsuhiko, Akirou Shimameguri, Morimasa Ogawa, Iori Hashimoto, and Manabu Kano. "Application of Statistical Process Monitoring with External Analysis to an Industrial Monomer Plant." IFAC Proceedings Volumes 37, no. 1 (January 2004): 379–84. http://dx.doi.org/10.1016/s1474-6670(17)38761-x.

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25

Jiang, Qingchao, Xuefeng Yan, and Biao Huang. "Review and Perspectives of Data-Driven Distributed Monitoring for Industrial Plant-Wide Processes." Industrial & Engineering Chemistry Research 58, no. 29 (July 8, 2019): 12899–912. http://dx.doi.org/10.1021/acs.iecr.9b02391.

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26

Chaparro-Cárdenas, Silvia L., Julian Andres Ramirez Bautista, Wilson Gamboa Contreras, Andrés Leonardo Moreno-Chacón, and Frank Carlos Vargas-Tangua. "Plant electrophysiology: bibliometric analysis, methods and applications in the monitoring of plant-environment interactions." DYNA 88, no. 218 (September 6, 2021): 112–23. http://dx.doi.org/10.15446/dyna.v88n218.92405.

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Plants have mechanisms to perceive and transmit information between their organs and tissues to respond quickly to abiotic and biotic external stimuli from the environment, producing different electrical potential types. It is reported on the generation and conduction of electrochemical impulses within different tissues and organs of the plant, which have been acquired using different methods to use them in various applications in the improvement of the agro-industrial sector and the development of different types of phytosensors. In this review paper, the various studies that have been carried out since Pfeffer, Burdon-Sanderson, Darwin, Haberlandt, and Bose discovered electrical activity in plants until today are reported. Plants provide mechanisms to perform biosensors based on responding to environmental changes, opening a great path for the design of low-cost and highly sensitive sensors and sensor networks, the current trend is towards experimental analysis using various stimuli.

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27

Zhu, Wanhao, Zhidong Wang, and Zifan Zhang. "Renovation of Automation System Based on Industrial Internet of Things: A Case Study of a Sewage Treatment Plant." Sensors 20, no. 8 (April 12, 2020): 2175. http://dx.doi.org/10.3390/s20082175.

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The Industrial Internet of Things (IIoT) is of great significance to the improvement of industrial efficiency and quality, and to reduce industrial costs and resources. However, there are few openly-reported practical project applications based on the IIoT up to now. For legacy automation devices in traditional industry, it is especially challenging to realize the upgrading of industrial automation adopting the IIoT technology with less investment. Based on the practical engineering experience, this paper introduces the automation renovation of a sewage treatment plant. The legacy automation devices are upgraded by the central controller of a STM32 processor (Produced by STMicroelectronics company, located in Geneva, Switzerland), and the WeChatApplet (Developed by Tencent company, located in Shenzhen, China) is used as the extended host computer. A set of remote monitoring and control systems of sewage treatment based on the IIoT is built to realize the wide-area monitoring and control of sewage treatment. The paper describes the field hardware system, wide-area monitoring and control application program, management cloud platform and security technologies in detail. The actual operation results show that the monitoring system has the requirements of high accuracy, good real-time performance, reliable operation and low cost.

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28

Niksa-Rynkiewicz, Tacjana, Natalia Szewczuk-Krypa, Anna Witkowska, Krzysztof Cpałka, Marcin Zalasiński, and Andrzej Cader. "Monitoring Regenerative Heat Exchanger in Steam Power Plant by Making Use of the Recurrent Neural Network." Journal of Artificial Intelligence and Soft Computing Research 11, no. 2 (January 29, 2021): 143–55. http://dx.doi.org/10.2478/jaiscr-2021-0009.

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Abstract Artificial Intelligence algorithms are being increasingly used in industrial applications. Their important function is to support operation of diagnostic systems. This paper presents a new approach to the monitoring of a regenerative heat exchanger in a steam power plant, which is based on a specific use of the Recurrent Neural Network (RNN). The proposed approach was tested using real data. This approach can be easily adapted to similar monitoring applications of other industrial dynamic objects.

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29

Gurov, I. O. "Quantitative assessment of renovation of “Petmol” plant in Saint-Petersburg." Vestnik Tomskogo gosudarstvennogo arkhitekturno-stroitel'nogo universiteta. JOURNAL of Construction and Architecture 23, no. 6 (December 26, 2021): 28–41. http://dx.doi.org/10.31675/1607-1859-2021-23-6-28-41.

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The standardized harmful effect of industrial production on buildings is one of the reasons for the plant withdrawal to the outskirts. The paper examines a particular case of renovation of the urban industrial area for residential commercial development. The energy consumption, environmental pollution, demographic burden, drains. and other indicators are analyzed. The calculation results show that restrained urban conditions can surpass the industrial in terms of the negative impact on the environment, and therefore renovation leads to an increase in resource consumption and deterioration of the environmental situation. Air monitoring data are used to confirm the correctness of the calculations.

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30

Maturana, Francisco P., Juan L. Asenjo, Neethu S. Philip, and Shweta Chatrola. "Merging Agents and Cloud Services in Industrial Applications." Applied Computational Intelligence and Soft Computing 2014 (2014): 1–8. http://dx.doi.org/10.1155/2014/124872.

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A novel idea to combine agent technology and cloud computing for monitoring a plant floor system is presented. Cloud infrastructure has been leveraged as the main mechanism for hosting the data and processing needs of a modern industrial information system. The cloud offers unlimited storage and data processing in a near real-time fashion. This paper presents a software-as-a-service (SaaS) architecture for augmenting industrial plant-floor reporting capabilities. This reporting capability has been architected using networked agents, worker roles, and scripts for building a scalable data pipeline and analytics system.

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31

Solnitsev, R. I., and Lei Wang. "Modeling the interaction between energy source enterprises and industrial enterprises as “Nature-Technology” closed-loop control systems." Advances in Engineering Technology Research 1, no. 3 (February 9, 2023): 746. http://dx.doi.org/10.56028/aetr.3.1.746.

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This paper focuses on models of interaction between energy source enterprises and industrial enterprises in order to minimize and control atmospheric emissions. Based on these models, computer simulations of “Nature-Technology” closed-loop control systems-energy source enterprises and industrial enterprises at the meta, macro and mini-models are carried out within the concept of “Nature-Technology” closed-loop control systems, taking into account the existing constraints of China norms and standards with inputs from the Beijing region of China. The simulations are based on a combined heat and power plant and a steel (cement) plant. Overall energy consumption and emissions monitoring based on computer modelling of energy source enterprises and industrial enterprises, including consideration of standards and guidelines for environmental and energy policies and plans in the Beijing region of China.

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32

Nadakatti, Mahantesh, A. Ramachandra, and A. N. Santosh Kumar. "Artificial intelligence‐based condition monitoring for plant maintenance." Assembly Automation 28, no. 2 (April 18, 2008): 143–50. http://dx.doi.org/10.1108/01445150810863725.

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Kalunga, Joseph, Simon Tembo, and Jackson Phiri. "Incorporating Environmental Protection Requirement in Industrial IoT Access Control Security Using Arduino Technology MQ2 and DHT11 Sensor Networks." International Journal of Advances in Scientific Research and Engineering 08, no. 04 (2022): 97–122. http://dx.doi.org/10.31695/ijasre.2022.8.4.9.

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This paper presents the development of environmental monitoring mechanism based on Arduino Sensor Technology for Industrial Internet of Things (Industrial IoT) Critical Infrastructure (CI) Protection in an Access Control role. Access control of hazardous substances is one of the most vulnerable aspects of Industrial IoT CI. The idea behind this study is to harden environmental security through live ecological monitoring of Temperature, Humidity and emitted hazardous substances or gases due to Industrial activities and processes in Smart CI places such as Nuclear Processing Plant, Thermal Generation Power Industries, Fossil Processing Plant, Military Chemical warfare plant, food processing factory, Agriculture Chemical Manufacturing Plant and many other CI industries. Live monitoring is one of the most important security requirements for any cyber-Access Control Mechanism. The literature revealed that similar systems were developed and implemented in different organizations and with different System Requirements and specifications. However, most CI industries have not automated environmental monitoring requirements and integrated the requirement into a broad institution security continuum. The consequence of neglecting environmental security is climate change. Furthermore, Toxic gas pollution affects millions of people around the world and contributes to about 5.4 percent of deaths worldwide. Pollution kills more people than the combination of malaria, AIDS, and tuberculosis hence the development of security mechanisms to monitor pollutants in the atmosphere. The main objective of this study was to develop a computer-based application for monitoring environmental hazardous substances such as extreme temperature, humidity, carbon dioxide (CO2), carbon monoxide (CO), and Smoke in the atmosphere surrounding Industrial IoT CI Industries. The system development approach employed was the Arduino engineering process model. To achieve this objective, cheaper ecological sensor Networks that include MQ2 and DHT11 Arduino Sensors are connected to Arduino Uno Microcontroller through a solderless breadboard Arduino component. The backend database was MySQL Relational database management system. The developed prototype application produced a number of results including live monitoring of temperature, humidity, CO2, CO, Smoke, and many others. A system evaluation process was conducted and the result indicated 99.999% accuracy levels. The results, it evidence that the developed prototype application can improve environmental security in Industrial IoT CI institutions.

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34

Soares, Rafael M., Maurício M. Câmara, Thiago Feital, and José Carlos Pinto. "Digital Twin for Monitoring of Industrial Multi-Effect Evaporation." Processes 7, no. 8 (August 15, 2019): 537. http://dx.doi.org/10.3390/pr7080537.

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Digital twins are rigorous mathematical models that can be used to represent the operation of real systems. This connection allows for deeper understanding of the actual states of the analyzed system through estimation of variables that are difficult to measure otherwise. In this context, the present manuscript describes the successful implementation of a digital twin to represent a four-stage multi-effect evaporation train from an industrial sugar-cane processing unit. Particularly, the complex phenomenological effects, including the coupling between thermodynamic and fluid dynamic effects, and the low level of instrumentation in the plant constitute major challenges for adequate process operation. For this reason, dynamic mass and energy balances were developed, implemented and validated with actual industrial data, in order to provide process information for decision-making in real time. For example, the digital twin was able to indicate failure of process sensors and to provide estimates for the affected variables in real time, improving the robustness of the operation and constituting an important tool for process monitoring.

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35

Ignac-Nowicka, Jolanta. "Visual Monitoring as a Tool in Industrial Security Engineering. Case Study." Multidisciplinary Aspects of Production Engineering 4, no. 1 (September 1, 2021): 107–19. http://dx.doi.org/10.2478/mape-2021-0010.

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Abstract The article presents the use of video monitoring in a production company on the example of municipal thermal power plant. After analyzing the hazards and work inconvenience occurring in the analyzed enterprise, video surveillance zones have been designated with the division into the indoor and outdoor monitoring system. Video surveillance is provided for production, auxiliary and delivery processes. Moreover, video monitoring performs a control function over the occupation health in workstations at risk of explosion or fire. In addition, observation points have been set up in the visual monitoring system, among which the internal ones are served by the dispatcher responsible for the production process, while the external are operated by security guards of the facility.

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Albița, Anca, and Dan Selișteanu. "A Compact IIoT System for Remote Monitoring and Control of a Micro Hydropower Plant." Sensors 23, no. 4 (February 5, 2023): 1784. http://dx.doi.org/10.3390/s23041784.

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Remote monitoring and operation evaluation applications for industrial environments are modern and easy means of exploiting the provided resources of specific systems. Targeted micro hydropower plant functionalities (such as tracking and adjusting the values of functional parameters, real-time fault and cause signalizing, condition monitoring assurance, and assessments of the need for maintenance activities) require the design of reliable and efficient devices or systems. The present work describes the design and implementation procedure of an Industrial Internet of Things (IIoT) system configured for a basic micro hydropower plant architecture and assuring simple means of customization for plant differences in structure and operation. The designed system features a set of commonly used functions specific to micro hydropower exploitation, providing maximum performance and efficiency.

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37

van der Waarde, J., J. Krooneman, B. Geurkink, A. van der Werf, D. Eikelboom, C. Beimfohr, J. Snaidr, C. Levantesi, and V. Tandoi. "Molecular monitoring of bulking sludge in industrial wastewater treatment plants." Water Science and Technology 46, no. 1-2 (July 1, 2002): 551–58. http://dx.doi.org/10.2166/wst.2002.0533.

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Fluorescent In Situ Hybridisation (FISH) was used to monitor the presence of filamentous microorganisms in industrial wastewater treatment plants (WWTPs). Monitoring with a restricted set of FISH probes in WWTPs from potato industry showed growth and decline of Thiothrix populations that could be linked to operational procedures. In a follow up project new FISH probes were developed for filamentous bacteria in industrial WWTPs and 70 WWTPs were analysed for presence of these filaments. Several newly described species of filamentous bacteria appear to be common and dominant in industrial WWTPs. Monitoring of a WWTP from textile industry showed growth and decline of one of these organisms when operational conditions in the plant were varied. The present paper demonstrates that bulking sludge in industrial wastewater treatment plants can effectively be monitored using a combination of standard chemical analyses and the FISH technique.

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38

MORÁN, ANTONIO, JUAN J. FUERTES, SERAFÍN ALONSO, CARLOS DEL CANTO, and MANUEL DOMÍNGUEZ. "TIME SERIES FOR FAULT DETECTION IN AN INDUSTRIAL PILOT PLANT." International Journal of Modern Physics B 26, no. 25 (September 10, 2012): 1246003. http://dx.doi.org/10.1142/s0217979212460034.

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Forecasting the evolution of industrial processes can be useful to discover faults. Several techniques based on analysis of time series are used to forecast the evolution of certain critical variables; however, the amount of variables makes difficult the analysis. In this way, the use of dimensionality reduction techniques such as the SOM (Self-Organizing Map) allows us to work with less data to determine the evolution of the process. SOM is a data mining technique widely used for supervision and monitoring. Since the SOM is projects data from a high dimensional space into a 2-D, the SOM reduces the number of variables. Thus, time series with the variables of the low dimensional projection can be created to make easier the prediction of future values in order to detect faults.

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Chitransh, Apar, and Birinderjit Singh Kalyan. "ARM Microcontroller Based Wireless Industrial Automation System." Indian Journal of Microprocessors and Microcontroller 1, no. 2 (September 10, 2021): 8–11. http://dx.doi.org/10.35940/ijmm.b1705.091221.

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In modern era most of the work being completed by the new and advanced various technology. Most of the industries are being run on the robotics technologies. But in INDIA most of the company are running in various technologies as like embedded system, plc, Arduino for sensing the alcohol detection and gas detection system and most important thing microcontroller. In this paper we discuss the ARM microcontroller based wireless industrial automation system. This automation consists the coordinator module and sensor module. In which one module is connected with the monitoring computer that is called the coordinator module and for connecting with the monitor of the computer it is also called the centralized unit. And the sensor module is an ARM microcontroller for a monitoring and controlling the whole plant. The coordinator unit main work is to collects the all type of data from the sensor module and provide that information to the IP network. For better communication between these two modules, we use the best technology is ZIGBEE technology. Its main work to preset the changing and control the plant various parameter. ARM microcontroller using the embedded c language coding. This paper we do the deeply study about the ARM microcontroller and about the wireless industrial automation system and the term of ZIGBEE technology.

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40

Chitransh, Apar, and Birinderjit Singh Kalyan. "ARM Microcontroller Based Wireless Industrial Automation System." Indian Journal of Microprocessors and Microcontroller 1, no. 2 (September 10, 2021): 8–11. http://dx.doi.org/10.54105/ijmm.b1705.091221.

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In modern era most of the work being completed by the new and advanced various technology. Most of the industries are being run on the robotics technologies. But in INDIA most of the company are running in various technologies as like embedded system, plc, Arduino for sensing the alcohol detection and gas detection system and most important thing microcontroller. In this paper we discuss the ARM microcontroller based wireless industrial automation system. This automation consists the coordinator module and sensor module. In which one module is connected with the monitoring computer that is called the coordinator module and for connecting with the monitor of the computer it is also called the centralized unit. And the sensor module is an ARM microcontroller for a monitoring and controlling the whole plant. The coordinator unit main work is to collects the all type of data from the sensor module and provide that information to the IP network. For better communication between these two modules, we use the best technology is ZIGBEE technology. Its main work to preset the changing and control the plant various parameter. ARM microcontroller using the embedded c language coding. This paper we do the deeply study about the ARM microcontroller and about the wireless industrial automation system and the term of ZIGBEE technology.

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41

Amodio, M., G. de Gennaro, A. Di Gilio, and M. Tutino. "Monitoring of the Deposition of PAHs and Metals Produced by a Steel Plant in Taranto (Italy)." Advances in Meteorology 2014 (2014): 1–10. http://dx.doi.org/10.1155/2014/598301.

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A high time-resolved monitoring campaign of bulk deposition of PAHs and metals was conducted near the industrial area and at an urban background site in province of Taranto (Italy) in order to evaluate the impact of the biggest European steel plant. The deposition fluxes of the sum of detected PAHs at the industrial area ranged from 92 to 2432 ng m−2d−1. In particular the deposition fluxes of BaP, BaA, and BkF were, on average, 10, 14, and 8 times higher than those detected at the urban background site, respectively. The same finding was for metals. The deposition fluxes of Ni (19.8 µg m−2d−1) and As (2.2 µg m−2d−1) at the industrial site were about 5 times higher than those at the urban background site, while the deposition fluxes of Fe (57 mg m−2d−1) and Mn (1.02 mg m−2d−1) about 31 times higher. Precipitation and wind speed played an important role in PAH deposition fluxes. Fe and Mn fluxes at the industrial site resulted high when wind direction favored the transport of air masses from the steel plant to the receptor site. The impact of the industrial area was also confirmed by IP/(IP + BgP), IP/BgP, and BaP/BgP diagnostic ratios.

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42

Mehrabi, A., N. Mehrshad, and M. Massinaei. "Machine vision based monitoring of an industrial flotation cell in an iron flotation plant." International Journal of Mineral Processing 133 (December 2014): 60–66. http://dx.doi.org/10.1016/j.minpro.2014.09.018.

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Bhat, Sartaj Ahmad, Jaswinder Singh, Keshav Singh, and Adarsh Pal Vig. "Genotoxicity monitoring of industrial wastes using plant bioassays and management through vermitechnology: A review." Agriculture and Natural Resources 51, no. 5 (October 2017): 325–37. http://dx.doi.org/10.1016/j.anres.2017.11.002.

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Stefanescu, Denis, Patxi Galán-García, Leticia Montalvillo, Juanjo Unzilla, and Aitor Urbieta. "Industrial Data Homogenization and Monitoring Scheme with Blockchain Oracles." Smart Cities 6, no. 1 (January 10, 2023): 263–90. http://dx.doi.org/10.3390/smartcities6010013.

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Research efforts on Distributed Ledger Technologies (DLTs) for industrial applications have constantly been increasing over the last years. The use of DLTs in the Industry 4.0 paradigm provides traceability, integrity, and immutability of the generated industrial data. However, Industry 4.0 ecosystems are typically composed of multiple smart factory clusters belonging to several companies, which are immersed in constant interaction with other business partners, clients, or suppliers. In such complex ecosystems, multiple DLTs are necessarily employed to maintain the integrity of the data throughout the whole process, from when the data is generated until it is processed at higher levels. Moreover, industrial data is commonly heterogeneous, which causes compatibility issues, along with security and efficiency issues in the homogenization process. Thus, the data needs to be pre-processed and homogenized in a secure manner before being exploited. Consequently, in this work, we address the issues mentioned above by providing an industrial raw data pre-processing and homogenization process according to a standard data model. We employ decentralized blockchain oracles to guarantee the integrity of the external data during the homogenization process. Hereafter, we design an interoperable plant blockchain for trustworthy storage and processing of the resulting homogenized data across several industrial plants. We also present a prototype implementation of the aforementioned scheme and discuss its effectiveness. Finally, we design a monitoring scheme to overview the usage the performance of the architecture processes and identify possible performance and security issues.

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45

Kuznetsov, P. N., and D. Y. Kotelnikov. "Automated complex of intelligent monitoring of a solar power plant." Journal of Physics: Conference Series 2094, no. 5 (November 1, 2021): 052025. http://dx.doi.org/10.1088/1742-6596/2094/5/052025.

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Abstract A solution for automated monitoring and diagnostics of photovoltaic modules of industrial solar power plants is proposed. The solution is based on the use of an unmanned aerial vehicle with a specialized payload and a ground-based intelligent information and control system to detect problem areas of the station, in particular partial shading and pollution. To perform the detection procedures, a neural network based on the Fast R-CNN architecture with the learning algorithm – Inception v2 (COCO) was used. The results of preliminary tests showed that the accuracy of detecting problem areas is at least 92%. The article presents a mathematical model that allows calculating the installed power monitored by the complex, depending on the type of station and UAV, meteorological parameters, and the performance of computing equipment. Numerical calculations have shown that when using the FIMI X8SE UAV and a computing device based on the RTX2080 GPU, the installed monitored power will be up to 7.5 MW.

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Fadhil, Tamara Z. "Wireless Control and Monitoring of Industrial Processes by AVR and LabVIEW." Journal of University of Human Development 3, no. 2 (June 30, 2017): 855. http://dx.doi.org/10.21928/juhd.v3n2y2017.pp855-861.

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This paper presents expansion, enhancement, design and implementation of wireless SCADA systems to control a variety of industrial processes from a master location which include authorizing vast monitoring for pipelines, natural gas, petroleum fields, water and transportation systems, chemical plants, utilities, oil refineries, power generation, electrical grid and an immense assortment of industrialization functionality. The control of environmental temperature, oil pressure, gases concentration, fuel tank level in power industrial plant had been collected and analyzed with a high power capacity 1 MW, based on Master terminal unit (MTU) design for data acquisition from Remote Terminal Unit (RTU) sensors and wireless data transfer using 2.4 GHz RF module, makes sensors data collection come true.

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Rizaluddin, Andri Taufick, and Henggar Hardiani. "Online Monitoring of Effluent Quality for Assessing the Effect of Wastewater Treatment Plant to Discharge into the Receiving Water: a review." Jurnal Riset Teknologi Pencegahan Pencemaran Industri 12, no. 1 (May 27, 2021): 7–19. http://dx.doi.org/10.21771/jrtppi.2021.v12.no1.p7-19.

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In general, industries that use water in their production process will produce wastewater which usually contains a lot of polluting contaminants. It will affects the surrounding environment by contaminating the water bodies, which will adversely affect the health life of all living beings. Pollution that occurs in the some rivers in Indonesia has begun to raise concern for Indonesian Goverment. Some of the river locations already have heavy poluted status. The pollution is mostly caused by industrial waste and domestic waste along the river. Treatment plants for wastewater effluents are mandatory for any industry which discharges their wastewater effluents into the environment. Information on monitoring the quality of industrial wastewater is very important to be perceived by examining changes in water quality condition that are getting better or worse. It is necessary to develop a system that monitors the condition of industrial wastewater. Industrial wastewater monitoring is a device system that collects real time data. Online monitoring technology is one part that plays an important role in supporting activities to control marine environmental pollution. Real‐time monitoring of wastewater quality remains an unresolved problem to the wastewater treatment industry. One of the problem in most industries in Indonesia is that the operational and performance of wastewater treatment plants (WWTP) are still not optimal, and need to be improved. The application of industrial technology concept 4.0 and automation systems in the industry is expected to improve the WWTP supervision process which has advantages such as reducing down time, reducing consumption of raw materials, reducing the energy used, increasing productivity, improving product quality and making efficient use of resources and processes, so as to reduce industrial operating costs.

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48

Verellen, Thomas, Florian Verbelen, Kurt Stockman, and Jan Steckel. "Beamforming Applied to Ultrasound Analysis in Detection of Bearing Defects." Sensors 21, no. 20 (October 13, 2021): 6803. http://dx.doi.org/10.3390/s21206803.

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The bearings of rotating machinery often fail, leading to unforeseen downtime of large machines in industrial plants. Therefore, condition monitoring can be a powerful tool to aid in the quick identification of these faults and make it possible to plan maintenance before the fault becomes too drastic, reducing downtime and cost. Predictive maintenance is often based on information gathered from accelerometers. However, these sensors are contact-based, making them less attractive for use in an industrial plant and more prone to breakage. In this paper, condition monitoring based on ultrasound is researched, where non-invasive sensors are used to record the noise originating from different defects of the Machinery Fault Simulator. The acoustic data are recorded using a sparse microphone array in a lab environment. The same array was used to record real spatial noise in a fully operational plant which was later added to the acoustic data containing the different defects with a variety of Signal To Noise ratios. In this paper, we compare the classification results of the noisy acoustic data of only one microphone to the beamformed acoustic data. We do this to investigate how beamforming could improve the classification process in an ultrasound condition-monitoring application in a real industrial plant.

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49

Verellen, Thomas, Florian Verbelen, Kurt Stockman, and Jan Steckel. "Beamforming Applied to Ultrasound Analysis in Detection of Bearing Defects." Sensors 21, no. 20 (October 13, 2021): 6803. http://dx.doi.org/10.3390/s21206803.

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The bearings of rotating machinery often fail, leading to unforeseen downtime of large machines in industrial plants. Therefore, condition monitoring can be a powerful tool to aid in the quick identification of these faults and make it possible to plan maintenance before the fault becomes too drastic, reducing downtime and cost. Predictive maintenance is often based on information gathered from accelerometers. However, these sensors are contact-based, making them less attractive for use in an industrial plant and more prone to breakage. In this paper, condition monitoring based on ultrasound is researched, where non-invasive sensors are used to record the noise originating from different defects of the Machinery Fault Simulator. The acoustic data are recorded using a sparse microphone array in a lab environment. The same array was used to record real spatial noise in a fully operational plant which was later added to the acoustic data containing the different defects with a variety of Signal To Noise ratios. In this paper, we compare the classification results of the noisy acoustic data of only one microphone to the beamformed acoustic data. We do this to investigate how beamforming could improve the classification process in an ultrasound condition-monitoring application in a real industrial plant.

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Prosekov, A. Yu. "HYDRO POWER PLANT “KRAPIVINSKY”: CURRENT STATE AND POSSIBLE RISKS." Bulletin оf Kamchatka State Technical University, no. 56 (2021): 54–63. http://dx.doi.org/10.17217/2079-0333-2021-56-54-63.

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Rational nature management is a priority in the development of science and technology based on environ-mental monitoring. Natural ecosystems located in industrial areas are under significant anthropogenic pres-sure, as a result of which the negative impact on the environment and biodiversity has increased. Various archival documents and other sources of scientific and technical information on the construction and current state of the Krapivsky reservoir were analyzed. The study results allowed to justify theoretically the need for a comprehensive ecological monitoring of the reservoir’s zone of influence and its current condition. The importance of its practical implementation on a systematic methodological basis using the earth remote sensing and geoinformation mapping was detected.

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