Academic literature on the topic 'Process control Dynamics Data processing'
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Journal articles on the topic "Process control Dynamics Data processing"
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Park, Suk Yung, and Arthur D. Kuo. "An Optimal Estimator Model of Multi-Sensory Processing in Human Postural Control." Key Engineering Materials 277-279 (January 2005): 148–54. http://dx.doi.org/10.4028/www.scientific.net/kem.277-279.148.
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We hypothesized that multi-sensory processing at the central nervous system (CNS) in human postural control can be described using an optimal estimator model. The estimates on body dynamics from multi-sensory signals contain sensory noise, transmission delays, and process disturbances. The state estimates approximate actual body movement. Erroneous estimates degrade the performance of feedback control and could cause a loss of balance if distorted severely. To test the hypothesis, we examined the frequency response of a visually-induced postural sway with stimulus frequency ranging from 0.075 to 1Hz and established an optimal estimator model. Two healthy young (33yrs ± 1) subjects stood on a force platform located 1.25m behind a projection screen with their arms crossed over their chests. They were asked to maintain an upright posture against the sinusoidal visual field stimuli. Each sinusoidal visual stimulus was generated by a projector for 200secs in pitch direction with a maximum pitch angle of 20o. Kinematics data was recorded to calculate the frequency response function of the center of mass (COM). There were three components in the modeling procedure: a biomechanical model of body and sensor dynamics, a linear feedback control model to stabilize the biomechanical model, and a state estimator to estimate body dynamic states based on multi-sensory outputs. We modeled the sensor dynamics of the semicircular canal, otolth, vision, and muscle spindles at the ankle and hip joint. We used the Kalman filter and linear quadratic regulator to determine feedback gains. Results showed that the frequency response function of a visually-induced postural sway decreased as stimulus frequency increased, and this low-pass filtering characteristic with an approximate cutoff frequency of 0.2Hz was also simulated by the postural feedback control model with optimal estimator. Low-pass filtering characteristics of the frequency response are mainly due to body and sensor dynamics, which show reduced responses for high frequency stimulus. The Kalman filter represents that the CNS utilizes redundant sensory information in a way that minimizes discrepancies between actual body dynamics and estimated body dynamics based on sensory output and an internal model. The results suggest that the CNS may make use of an internal representation of body dynamics, and can integrate sensory information in an optimal way to best estimate human postural responses.
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Kotenko, Igor, and Igor Parashchuk. "Multi-criteria security assessment of control and diagnostic data on the technological processes." MATEC Web of Conferences 298 (2019): 00071. http://dx.doi.org/10.1051/matecconf/201929800071.
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A mathematical model of the dynamics of changes in the state of security indicators of control and diagnostic data on the technological process is proposed. It is constructed using Markov chains and takes into account the probabilistic-temporal mechanism for changing the state of data protection indicators of this class. Based on this model, a methodological approach has been developed for multi-criteria assessment of the security of control and diagnostic data on the technological process. The approach is based on the analysis of current deviations of the values of data protection indicators from the requirements for them, takes into account and eliminates the uncertainty of the initial diagnostic information. The proposed methodological approach also allows one to take into account transients that affect security when introducing control over the structure, parameters and modes of collection and processing of control and diagnostic data about the technological process in various conditions.
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Fu, Gang, Ming Xin Kou, and Ren Long Li. "Design and Implementation of Driving Mechanism on Software Aerospace Measurement and Control System." Advanced Materials Research 989-994 (July 2014): 3084–87. http://dx.doi.org/10.4028/www.scientific.net/amr.989-994.3084.
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According to the signal processing unit in aerospace measurement and control system between the flow of water features, this paper proposes a software suitable for aerospace measurement and control system of driving mechanism. This paper first introduces the basic structure of aerospace measurement and control system software, having studied the static and dynamic data stream driving mechanism on the basis of detailed discusses the design and implementation process of this kind of driving mechanism of data stream. It adopts the method of message control, according to the dynamic data flow driven mechanism, realize the process of the signal processing unit and each signal processing unit between the data flow between the internal thread. Compared the same sort of dynamic data stream driving mechanism, the drive mechanism possesses the advantages of flexibility and easy to implement.
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Rahmanov, Mikhail, Andrey Shishkin, Vladimir Komkov, and Irina Alpackaya. "Simulation of pedestrian dynamics based withemantic trajectory segmentation." E3S Web of Conferences 363 (2022): 04005. http://dx.doi.org/10.1051/e3sconf/202236304005.
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The article analyzes the existing methods of information processing necessary for the functioning of the system of intelligent control over unregulated pedestrian crossings based on aggregation and data processing by means of IOT. The state space model of the switching Kalman filter is considered, the development of mathematical software for the analysis and processing of information based on the results of intelligent control over unregulated pedestrian crossings, in particular with semantic segmentation of trajectories using agent-based models, is carried out. An MDA (Markov Decision Process) state space model is presented, a Hidden Markov Model (HMM) which has discrete hidden variables. The developments for the development of the following subsystems are presented: activity detector subsystem. Receives video frames as input, supports the static object model (background model) and returns the hotspot mask for the current frame; subsystems for detecting and tracking objects (pedestrians and cars). Based on the video frame and hotspot mask, it detects and accompanies objects of a given class, returning their coordinates; trajectory analysis subsystem. Analyzing the history of movement of pedestrians and cars, returns the facts of traffic violations.
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Umetalieva, Ch T., N. Y. Temirbaeva, and B. N. Nurtaev. "THEORY OF BUILDING AUTOMATED CONTROL SYSTEMS." Herald of KSUCTA, №2, Part 1, 2022, no. 2-1-2022 (April 30, 2022): 295–99. http://dx.doi.org/10.35803/1694-5298.2022.2.295-299.
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The task of collecting, processing and disseminating (exchanging) information stood at all stages of human development. For a long time, the main tools for solving it were the human brain, hearing and language. Storing information in computer memory gives a fundamentally new quality of dynamics, that is, the ability to quickly recover and use it directly in problems solved on a computer. Modern printing equipment, equipped with modern computers, allows, if necessary, to quickly present any selected information on paper. In the process of development of the administrative data management system, the need arose for an automated facility management system (ACS).
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Whitehead, Peter S., Mathilde M. Ooi, Tobias Egner, and Marty G. Woldorff. "Neural Dynamics of Cognitive Control over Working Memory Capture of Attention." Journal of Cognitive Neuroscience 31, no. 7 (July 2019): 1079–90. http://dx.doi.org/10.1162/jocn_a_01409.
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The contents of working memory (WM) guide visual attention toward matching features, with visual search being faster when the target and a feature of an item held in WM spatially overlap (validly cued) than when they occur at different locations (invalidly cued). Recent behavioral studies have indicated that attentional capture by WM content can be modulated by cognitive control: When WM cues are reliably helpful to visual search (predictably valid), capture is enhanced, but when reliably detrimental (predictably invalid), capture is attenuated. The neural mechanisms underlying this effect are not well understood, however. Here, we leveraged the high temporal resolution of ERPs time-locked to the onset of the search display to determine how and at what processing stage cognitive control modulates the search process. We manipulated predictability by grouping trials into unpredictable (50% valid/invalid) and predictable (100% valid, 100% invalid) blocks. Behavioral results confirmed that predictability modulated WM-related capture. Comparison of ERPs to the search arrays showed that the N2pc, a posteriorly distributed signature of initial attentional orienting toward a lateralized target, was not impacted by target validity predictability. However, a longer latency, more anterior, lateralized effect—here, termed the “contralateral attention-related negativity”—was reduced under predictable conditions. This reduction interacted with validity, with substantially greater reduction for invalid than valid trials. These data suggest cognitive control over attentional capture by WM content does not affect the initial attentional-orienting process but can reduce the need to marshal later control mechanisms for processing relevant items in the visual world.
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Eghbali, Zahra, and Mina Zolfy Lighvan. "A Hierarchical Approach for Accelerating IoT Data Management Process Based on SDN Principles." MENDEL 25, no. 1 (June 24, 2019): 121–30. http://dx.doi.org/10.13164/mendel.2019.1.121.
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Internet of things is a new technology that connects billions of smart devices through the Internet. This important technology is heavily affecting different aspects of human life and plays an important role in variety of domains. The number of smart devices connecting to IoT and the amount of data gathered or produced by these devices are increasing. This large volume of data requires a lot of effort for processing and analysis. In order to organize, secure and balance the load in IoT, the novel and creative ideas for IoT design and management are required. Software Defined Networking is a new and promising paradigm and its main idea is to decouple the control and management operations from physical devices and setting them inside a logically centralized control layer. Due to its unique capabilities, SDN can be a good choice for managing dynamic and complicated networks such as IoT. In this paper, a distributed approach is proposed for accelerating data management and balancing the load between IoT devices. The proposed framework makes it possible to apply different kinds of management, security and load balancing strategies using a distributed control plane. Experimental results indicate that our scheme exhibits a reduction in the average turnaround time and the average waiting time and it will improve the processing performance. The proposed approach will also distribute tasks between devices, so that there will be no under-loaded device when a part of network is under the processing pressure.
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Yailymova, Hanna, Bohdan Yailymov, Andrii Shelestov, and Tetiana Krasilnikova. "INTELLECTUAL METHODS AND MODELS OF SATELLITE DATA PROCESSING IN LANDFILLS MONITORING PROBLEMS." International Scientific Technical Journal "Problems of Control and Informatics" 2, no. 2 (March 1, 2022): 128–40. http://dx.doi.org/10.34229/2786-6505-2022-2-9.
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The article is devoted to solving an important applied problem of landfill search based on machine learning methods using high-resolution satellite data. The problem of accumulation and storage of waste in legal and unauthorized landfills is relevant today. Millions of tons of household waste are generated in Ukraine every year. The largest areas for landfills are occupied in Donetsk, Dnipropetrovsk, Odesa, Zaporizhzhia regions. So, in the Donetsk region the areas under landfills occupy 330 hectares. Various technologies based on satellite data and artificial intelligence methods are used to monitor landfills. Currently, there are services that track the location of landfills, but do not provide information about the territory of the landfill and changes in its area over time. In the process of research, the important task of separating landfills from quarries and artificial objects by combining pixel-based and object-based classification was solved. The main purpose of the work was to develop intelligent information technology based on the neural network approach and build on its basis a geospatial product of landfills for the Donetsk region, namely classification maps of landfills. The proposed machine learning algorithm based on historical and modern satellite data allows tracking the area of the landfill and its changes over time. The developed information technology was tested on the territory of four territorial communities in Donetsk region, namely Olhyn, Myrnohrad, Kurakhiv and Pokrovsky communities. As a result of the research, an information panel was also developed, which provides operational data and allows to assess the dynamics of changes in landfills in the region in time and space. The developed technology is of practical importance for the development of waste management and management programs in local communities.
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Joostberens, Jarosław, Aurelia Rybak, and Aleksandra Rybak. "Identification of the Dynamic Properties of the Coal Flotation Process as a Control Object with the Use of the Kalman Filter." Energies 15, no. 21 (October 25, 2022): 7926. http://dx.doi.org/10.3390/en15217926.
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For various sorts of hard coal, enrichment by flotation is used for feed consisting of grains smaller than 0.5 mm. Regarding process automation, coal flotation is a multidimensional, dynamic nonlinear object of control, for which the main control signal is the flow rate of the flotation agent. Typically, in Polish coal-processing facilities the monitoring and control systems of the flotation process can only measure the parameter of the waste quality (content of ash in flotation tailings). This naturally becomes an output signal, enabling an indirect assessment of the ongoing process. Therefore, knowledge of the dynamic properties of the flotation process, analysed as an object with one control input (the flow rate of the flotation agent) and with one output for measuring (content of ash in flotation tailings) may be material in designing automatic control systems for this operation. It is important to use an appropriate identification method when developing a model of the dynamics of the flotation process, especially if the model parameters are to be determined on an ongoing basis. This article discusses the research method and presents the results of applying the method of identifying the dynamic properties of the coal flotation process with the use of the Kalman filter. We carried out a comparative analysis of the results obtained by this method based on the Kalman algorithm and the method of least squares, taken as the reference method. The presented parameters of the dynamic models were calculated based on actual data obtained from industrial tests conducted at the coal-processing plant at one of the Polish mines. It was demonstrated that, for control purposes, the Kalman algorithm can be successfully applied in identification of the coal flotation process. This is due to the fact that it gives satisfactory results in relation to the adopted reference method despite the fact that it is a recursive algorithm.
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Zhao, Lin. "Numerical Control Lathe Cutting Force Signal On-Line Monitoring Design." Applied Mechanics and Materials 711 (December 2014): 329–32. http://dx.doi.org/10.4028/www.scientific.net/amm.711.329.
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The main research direction of Numerical control lathe cutting force signal on-line monitoring is to process real-time monitoring, using the sensor, charge amplifier, video acquisition card and computer to collect data and signal. Signal acquisition makes use of the piezoelectric sensor signals and send them to the computer in order to acquire the real-time data and display the dynamic signal so that monitor the process. Signal processing is the course that data will be collected for subsequent processing and analyzing. It includes display, filtering, correlation analysis, spectral analysis, etc. We can conclude the signal’s characteristics after the time domain and frequency domain analysis of signals.
Dissertations / Theses on the topic "Process control Dynamics Data processing"
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Alici, Semra. "Dynamic data reconciliation using process simulation software and model identification tools." Access restricted to users with UT Austin EID Full text (PDF) from UMI/Dissertation Abstracts International, 2001. http://wwwlib.umi.com/cr/utexas/fullcit?p3025133.
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Morgan, Clifford Owen. "Development of computer aided analysis and design software for studying dynamic process operability." Thesis, Georgia Institute of Technology, 1986. http://hdl.handle.net/1853/10187.
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Sabri, Dina O. "Process control using an optomux control board." Virtual Press, 1987. http://liblink.bsu.edu/uhtbin/catkey/484759.
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In this thesis process control concepts were used to develop software that could be adapted to a real world situation. The software was used to control a simple temperature regulating experiment. This experiment was used to demonstrate the use of OPTOMUX analog and digital input/output devices in controlling a process. The goal of this experiment was to use the input/output devices in controlling the temperature of the box within specified tolerances for a designated period of time. To accomplish optimal use of equipment and optimal control, a mathematical model was derived to predict the behavior of the process under control. The pattern observed while the temperature was increasing toward room temperature closely resembled an exponential function. For temperatures above room temperatures the curve then approximated a square root function. The pattern followed when decreasing the temperature-was exponential throughout. The time required to collect all the significant data in the case of increasing the temperature was two hours. In the case of decreasing temperature, one hour. Beyond these time limits the temperature remained essentially constant. The maximum temperature value that could be reached was six degrees above room temperature and the minimum two degrees below room temperature.
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Tian, Yu-Chu. "Dynamics analysis and integrated design of real-time control systems." School of Electrical and Information Engineering, 2009. http://hdl.handle.net/2123/5743.
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Doctor of Philosophy (PhD)Real-time control systems are widely deployed in many applications. Theory and practice for the design and deployment of real-time control systems have evolved significantly. From the design perspective, control strategy development has been the focus of the research in the control community. In order to develop good control strategies, process modelling and analysis have been investigated for decades, and stability analysis and model-based control have been heavily studied in the literature. From the implementation perspective, real-time control systems require timeliness and predictable timing behaviour in addition to logical correctness, and a real-time control system may behave very differently with different software implementations of the control strategies on a digital controller, which typically has limited computing resources. Most current research activities on software implementations concentrate on various scheduling methodologies to ensure the schedulability of multiple control tasks in constrained environments. Recently, more and more real-time control systems are implemented over data networks, leading to increasing interest worldwide in the design and implementation of networked control systems (NCS). Major research activities in NCS include control-oriented and scheduling-oriented investigations. In spite of significant progress in the research and development of real-time control systems, major difficulties exist in the state of the art. A key issue is the lack of integrated design for control development and its software implementation. For control design, the model-based control technique, the current focus of control research, does not work when a good process model is not available or is too complicated for control design. For control implementation on digital controllers running multiple tasks, the system schedulability is essential but is not enough; the ultimate objective of satisfactory quality-of-control (QoC) performance has not been addressed directly. For networked control, the majority of the control-oriented investigations are based on two unrealistic assumptions about the network induced delay. The scheduling-oriented research focuses on schedulability and does not directly link to the overall QoC of the system. General solutions with direct QoC consideration from the network perspective to the challenging problems of network delay and packet dropout in NCS have not been found in the literature. This thesis addresses the design and implementation of real-time control systems with regard to dynamics analysis and integrated design. Three related areas have been investigated, namely control development for controllers, control implementation and scheduling on controllers, and real-time control in networked environments. Seven research problems are identified from these areas for investigation in this thesis, and accordingly seven major contributions have been claimed. Timing behaviour, quality of control, and integrated design for real-time control systems are highlighted throughout this thesis. In control design, a model-free control technique, pattern predictive control, is developed for complex reactive distillation processes. Alleviating the requirement of accurate process models, the developed control technique integrates pattern recognition, fuzzy logic, non-linear transformation, and predictive control into a unified framework to solve complex problems. Characterising the QoC indirectly with control latency and jitter, scheduling strategies for multiple control tasks are proposed to minimise the latency and/or jitter. Also, a hierarchical, QoC driven, and event-triggering feedback scheduling architecture is developed with plug-ins of either the earliest-deadline-first or fixed priority scheduling. Linking to the QoC directly, the architecture minimises the use of computing resources without sacrifice of the system QoC. It considers the control requirements, but does not rely on the control design. For real-time NCS, the dynamics of the network delay are analysed first, and the nonuniform distribution and multi-fractal nature of the delay are revealed. These results do not support two fundamental assumptions used in existing NCS literature. Then, considering the control requirements, solutions are provided to the challenging NCS problems from the network perspective. To compensate for the network delay, a real-time queuing protocol is developed to smooth out the time-varying delay and thus to achieve more predictable behaviour of packet transmissions. For control packet dropout, simple yet effective compensators are proposed. Finally, combining the queuing protocol, the packet loss compensation, the configuration of the worst-case communication delay, and the control design, an integrated design framework is developed for real-time NCS. With this framework, the network delay is limited to within a single control period, leading to simplified system analysis and improved QoC.
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Tian, Yu-Chu. "Dynamics analysis and integrated design of real-time control systems." Connect to full text, 2008. http://ses.library.usyd.edu.au/handle/2123/5743.
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Thesis (Ph. D.)--University of Sydney, 2009.Title from title screen (viewed November 30, 2009). Submitted in fulfilment of the requirements for the degree of Doctor of Philosophy to the School of Electrical and Information Engineering in the Faculty of Engineering & Information Technologies. Degree awarded 2009; thesis submitted 2008. Includes bibliographical references. Also available in print form.
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Koeppen, Kyle Bruce. "Virtual access hydraulics experiment for system dynamics and control education." Thesis, Georgia Institute of Technology, 2001. http://hdl.handle.net/1853/15906.
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黎浩然 and Ho-yin Albert Lai. "Artificial intelligence based thermal comfort control with CFD modelling." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 1999. http://hub.hku.hk/bib/B3122278X.
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Lakshmanan, Nithya M. "Estimation and control of nonlinear batch processes using multiple linear models." Thesis, Georgia Institute of Technology, 1997. http://hdl.handle.net/1853/11835.
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Jones, Patricia Marie. "Constructing and validating a model-based operator's associate for supervisory control." Thesis, Georgia Institute of Technology, 1988. http://hdl.handle.net/1853/24274.
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Davenport, George Andrew 1965. "A process control system for biomass liquefaction." Thesis, The University of Arizona, 1989. http://hdl.handle.net/10150/558114.
Full textBooks on the topic "Process control Dynamics Data processing"
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F, Edgar Thomas, and Mellichamp Duncan A, eds. Process dynamics and control. New York: Wiley, 1989.
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Seborg, Dale E. Process dynamics and control. 3rd ed. Hoboken, N.J: John Wiley & Sons, Inc., 2011.
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Process dynamics and control. 3rd ed. Hoboken, N.J: John Wiley & Sons, Inc., 2011.
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F, Edgar Thomas, and Mellichamp Duncan A, eds. Process dynamics and control. 2nd ed. Hoboken, NJ: Wiley, 2004.
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F, Edgar Thomas, and Mellichamp Duncan A, eds. Process dynamics and control. New York: Wiley, 1989.
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A, Mellichamp Duncan, and Edgar Thomas F, eds. Process dynamics and control. 2nd ed. Hoboken, NJ: Wiley, 2004.
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Georgiadis, Michael C. Dynamic process modeling. Weinheim: Wiley-VCH, 2011.
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Georgiadis, Michael C., Julio R. Banga, and Efstratios N. Pistikopoulos. Dynamic process modeling. Weinheim: Wiley-VCH, 2011.
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E, Rijnsdorp John, International Federation of Automatic Control. Working Group on Chemical Process Control., and European Federation of Chemical Engineering., eds. Dynamics and control of chemical reactors, distillation columns, and batch processes: Selected papers from the IFAC Symposium, Maastricht, the Netherlands, 21-23 August 1989. Oxford, England: Published for the International Federation of Automatic Control by Pergamon Press, 1990.
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G, Bike Stacy, ed. Fluid mechanics for chemical engineers. Upper Saddle River, N.J: Prentice Hall PTR, 1999.
Find full textBook chapters on the topic "Process control Dynamics Data processing"
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Lampe, Bernhard P., and Efim N. Rosenwasser. "Parametric Transfer Matrices for Sampled-Data Control Systems with Linear Continuous Periodic Process and Control Delay." In Advances in Delays and Dynamics, 17–31. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-53426-8_2.
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Wang, Xue Z. "Data Pre-Processing for Feature Extraction, Dimension Reduction and Concept Formation." In Data Mining and Knowledge Discovery for Process Monitoring and Control, 29–60. London: Springer London, 1999. http://dx.doi.org/10.1007/978-1-4471-0421-6_3.
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Burattin, Andrea. "Streaming Process Mining." In Lecture Notes in Business Information Processing, 349–72. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-08848-3_11.
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AbstractStreaming process mining refers to the set of techniques and tools which have the goal of processing a stream of data (as opposed to a finite event log). The goal of these techniques, similarly to their corresponding counterparts described in the previous chapters, is to extract relevant information concerning the running processes. This chapter presents an overview of the problems related to the processing of streams, as well as a categorization of the existing solutions. Details about control-flow discovery and conformance checking techniques are also presented together with a brief overview of the state of the art.
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Pourbafrani, Mahsa, Shreya Kar, Sebastian Kaiser, and Wil M. P. van der Aalst. "Remaining Time Prediction for Processes with Inter-case Dynamics." In Lecture Notes in Business Information Processing, 140–53. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-98581-3_11.
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AbstractProcess mining techniques use event data to describe business processes, where the provided insights are used for predicting processes’ future states (Predictive Process Monitoring). Remaining Time Prediction of process instances is an important task in the field of Predictive Process Monitoring (PPM). Existing approaches have two key limitations in developing Remaining Time Prediction Models (RTM): (1) The features used for predictions lack process context, and the created models are black-boxes. (2) The process instances are considered to be in isolation, despite the fact that process states, e.g., the number of running instances, influence the remaining time of a single process instance. Recent approaches improve the quality of RTMs by utilizing process context related to batching-at-end inter-case dynamics in the process, e.g., using the time to batching as a feature. We propose an approach that decreases the previous approaches’ reliance on user knowledge for discovering fine-grained process behavior. Furthermore, we enrich our RTMs with the extracted features for multiple performance patterns (caused by inter-case dynamics), which increases the interpretability of models. We assess our proposed remaining time prediction method using two real-world event logs. Incorporating the created inter-case features into RTMs results in more accurate and interpretable predictions.
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Copăcenaru, Olimpia, Adrian Stoica, Antonella Catucci, Laura De Vendictis, Alessia Tricomi, Savvas Rogotis, and Nikolaos Marianos. "Copernicus Data and CAP Subsidies Control." In Big Data in Bioeconomy, 265–90. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-71069-9_20.
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AbstractThis chapter integrates the results of three pilots developed within the framework of the Horizon 2020 DataBio project. It aims to provide a broad picture of how products based on Earth Observation techniques can support the European Union’s Common Agricultural Policy requirements, whose fulfillments are supervised by National and Local Paying Agencies operating in Romania, Italy and Greece. The concept involves the use of the same data sources, mainly multitemporal series of Copernicus Sentinel-2 imagery, but through three different Big Data processing chains, tailored to each paying agency’s needs in terms of farm compliance assessment. Particularities of each workflow are presented together with examples of the results and their accuracy, calculated by validation against independent sources. Business value aspects for each use case are also discussed, emphasizing the way in which the automation of the CAP requests verification process through satellite technologies has increased the efficiency and reduced cost and time resources for the subsidy process. We end the chapter by highlighting the benefits of continuous satellite tracking as a substitute, but also complementary to the classical field control methods, and also the enormous potential of Earth Observation-based products for the agri-food market.
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Huber, Monika, Sascha Wessel, Gerd Brost, and Nadja Menz. "Building Trust in Data Spaces." In Designing Data Spaces, 147–64. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-93975-5_9.
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AbstractData is becoming increasingly valuable and must be protected. At the same time, data becomes an economic asset and companies can benefit from exchanging data with each other. The International Data Spaces enable companies to share data while ensuring data sovereignty and security.Data providers can keep control over the processing of their data by utilizing usage control policies, including the verification that these usage control policies are enforced by the data consumer. For this, data processing devices, called connectors, must prove their identity and the integrity of their software stack and state.In this chapter, we present the overall security concept for building trust in data spaces enabling data sovereignty and usage control enforcement. The concept builds on a certification process for components and operational environments utilizing the multiple eye principle. This process is technically mapped to a public key infrastructure providing digital certificates for connector identities and software signing. Finally, the third building block is the architecture and system security of the connectors where usage control must be enforced, the identity and integrity of other connectors and their software stack and state must be verified, and the actual data processing happens.
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Loi, Doan Huy, S. H. S. Jayakody, and Kyoji Sassa. "Teaching Tool “Undrained Dynamic Loading Ring Shear Testing with Video”." In Progress in Landslide Research and Technology, Volume 1 Issue 2, 2022, 325–59. Cham: Springer International Publishing, 2023. http://dx.doi.org/10.1007/978-3-031-18471-0_25.
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AbstractUndrained dynamic-loading ring-shear apparatus (UDRA) is most appropriate to study landslide dynamics by simulating the entire process from the initial stage of stress before landslide occurrence and stress changes due to static, dynamic loading or pore pressure changes or other types of stress loading to the formation of a sliding surface and the steady-state shear resistance. This paper describes the mechanical structure of the apparatus of UDRA and provides a manual for readers to begin using the UDRA. Specific steps for testing procedures with video tutorials and data analysis are also provided in this paper. The paper concludes with a manual from start to finish for common ring shear tests: undrained monotonic shear stress control test, undrained cyclic loading test, undrained seismic loading test, and pore pressure control test.
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Klein, Julia, and Tatjana Petrov. "Understanding Social Feedback in Biological Collectives with Smoothed Model Checking." In Leveraging Applications of Formal Methods, Verification and Validation. Adaptation and Learning, 181–98. Cham: Springer Nature Switzerland, 2022. http://dx.doi.org/10.1007/978-3-031-19759-8_12.
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AbstractBiological groups exhibit fascinating collective dynamics without centralised control, through only local interactions between individuals. Desirable group behaviours are typically linked to a certain fitness function, which the group robustly performs under different perturbations in, for instance, group structure, group size, noise, or environmental factors. Deriving this fitness function is an important step towards understanding the collective response, yet it easily becomes non-trivial in the context of complex collective dynamics. In particular, understanding the social feedback - how the collective behaviour adapts to changes in the group size - requires dealing with complex models and limited experimental data. In this work, we assume that the collective response is experimentally observed for a chosen, finite set of group sizes. Based on such data, we propose a framework which allows to: (i) predict the collective response for any given group size, and (ii) automatically propose a fitness function. We use Smoothed Model Checking, an approach based on Gaussian Process Classification, to develop a methodology that is scalable, flexible, and data-efficient; We specify the fitness function as a template temporal logic formula with unknown parameters, and we automatically infer the missing quantities from data. We evaluate the framework over a case study of a collective stinging defence mechanism in honeybee colonies.
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Chinazzo, André, Christian De Schryver, Katharina Zweig, and Norbert Wehn. "A Custom Hardware Architecture for the Link Assessment Problem." In Lecture Notes in Computer Science, 57–75. Cham: Springer Nature Switzerland, 2022. http://dx.doi.org/10.1007/978-3-031-21534-6_4.
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AbstractHeterogeneous accelerator enhanced computing architectures are a common solution in embedded computing, mainly due to the constraints in energy and power efficiency. Such accelerator enhanced systems dispatch data- and computing-intensive tasks to specialized, optimized and thus efficient hardware units, leaving most control flow tasks for the more generic but less efficient central processing units (CPUs). Nowadays, also high-performance computing (HPC) systems are becoming more heterogeneous by incorporating accelerators into the computing nodes.In this chapter, we introduce the concept of heterogeneous computing and present the design of a hardware accelerator for solving the Link Assessment (LA) problem, in introduced Chapter 3. The hardware accelerator integrates its main dedicated processing units with a customized cache design and light-weight data path. We provide detailed area, energy, and timing results for a 28 nm application specific integrated circuit (ASIC) process and DDR3 memory devices. Compared to an CPU-based cluster, our proposed solution uses 38x less memory and is 1030x more energy efficient for processing a users-movies dataset with half a million edges.
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Félix Mora-Camino and Luiz Gustavo Zelaya Cruz. "Advances in Data Processing for Airlines Revenue Management." In Computational Models, Software Engineering, and Advanced Technologies in Air Transportation, 132–45. IGI Global, 2010. http://dx.doi.org/10.4018/978-1-60566-800-0.ch008.
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In this communication advances in data processing techniques applied to Airlines Revenue Management are displayed. The general introduction presents a brief review of Airlines Revenue Management. The first of the paper introduces the problem of updating the probability distributions of demand for reservations. This updating process, facing the stochastic nature of demand for travel, is a cornerstone for the design of an efficient on-line decision support system to control the reservation process for a flight by an airline. The considered problem is formulated as a dual geometric problem to which an unconstrained nonconvex, primal geometric problem is associated. A genetic algorithm optimization approach is proposed to solve the primal geometric problem, and then the classical geometric primal-dual transformations provide the solution to the initial problem. Then, the second part of the paper considers the design of a new Decision Support System for improving the reservation control process of airlines. A new recursive Dynamic Programming model for maximum expected revenue evaluation is defined, which, contrarily to other approaches, takes explicitly into account daily booking request arrivals. A practical Backward Dynamic Programming algorithm is established, leading to the design of an on-line optimisation module for Revenue Management. In this study two cases are considered. The first one considers that fare classes are not physically confined and the obtained results are extended in the second case to cover the situations where confinement of fare classes (Business Class and Economy Class) is applied.
Conference papers on the topic "Process control Dynamics Data processing"
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Ren, Yong, and Qian Wang. "Physics-Informed Gaussian Process Based Optimal Control of Laser Powder Bed Fusion." In ASME 2020 Dynamic Systems and Control Conference. American Society of Mechanical Engineers, 2020. http://dx.doi.org/10.1115/dscc2020-3197.
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Abstract Regulating the melt-pool size to a constant reference value during the build process is a challenging task in Laser Powder Bed Fusion additive manufacturing (LPBF-AM). This paper considers adjusting laser power to achieve a constant melt-pool volume during laser processing of a multi-track build under LPBF-AM. First, a Gaussian Process Regression (GPR) is applied to model the variation of the melt-pool volume along the deposition distance, with physics-informed input features. Then a constrained finite-horizon optimal control problem is formulated, with a quadratic cost function defined to minimize the difference between the melt-pool volume and a reference value. A projected gradient descent algorithm is applied to compute the sequence of laser power in the proposed optimal control problem. The GPR modeling of melt-pool dynamics is trained and tested using simulated data sets generated from a commercial finite-element based AM software, and the same commercial AM software is used to evaluate the control performance. Simulation results demonstrate the effectiveness of the proposed GPR modeling and optimal control in regulating melt-pool volume for building multi-track parts with LPBF-AM.
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Galkowski, K., E. Rogers, A. Gramacki, J. Gramacki, and D. H. Owens. "Dynamic process initial conditions in repetitive processes. Controllability and stability analysis." In 1999 Information, Decision and Control. Data and Information Fusion Symposium, Signal Processing and Communications Symposium and Decision and Control Symposium. Proceedings (Cat. No.99EX251). IEEE, 1999. http://dx.doi.org/10.1109/idc.1999.754169.
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Walther, Tino, and Hans-Joachim Bargstädt. "Automated data acquisition to show the actual performance during the construction process." In IABSE Congress, New York, New York 2019: The Evolving Metropolis. Zurich, Switzerland: International Association for Bridge and Structural Engineering (IABSE), 2019. http://dx.doi.org/10.2749/newyork.2019.1565.
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<p>In times of workplace digitalization, Building Information Modeling (BIM) is indispensable to the construction industry due to the potential of consistent data tracking and usage. Based on a dynamic working environment as well as specific internal requirements of individual companies, object-oriented planning and processing with BIM-methods still needs adaptation efforts in order to be widely acceptable in the realization phase and on the construction site. Thus, the mapping of actual data on site is deemed the “Achilles’ heel” of successful project control.</p><p>This paper presents a concept for automated data acquisition in complex infrastructure construction sites – especially regarding the processes of road construction and earthworks – with emphasis on different innovative digital methods from which actual values regarding the construction progress can be derived and compared to a target model or digital twin. The objective is to avoid subjective misinterpretations, minimize project risks and turn the project into a more responsible enterprise altogether.</p>
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Hartman, Daniel A. "Real-Time Detection of Processing Flaws During Inertia Friction Welding of Critical Components." In ASME Turbo Expo 2012: Turbine Technical Conference and Exposition. American Society of Mechanical Engineers, 2012. http://dx.doi.org/10.1115/gt2012-68014.
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Outside of statistical process control, current manufacturing quality control is founded upon a “make-then-inspect” mindset [1]. While this approach is an important part of the quality control process, post-process inspection is labor intensive, a bottleneck to continuous production throughput, costly, subject to human interpretation, and susceptible to missing subtle defects. This paper presents the application of in-process quality control (IPQC) during inertia friction welding of critical components. This paper is a follow-on to a preliminary investigation into a new sensing technique for real-time inspection of product quality during friction welding [2]. The previous effort explored the feasibility of modeling the approach that an experienced friction welding operator uses to distinguish anomalous process behavior during friction welding. In particular, a non-contact, audio-based sensor was used to capture the audible process dynamics during inertia friction welding of a dual-alloy component. The previous work employed a neural-network-based data mining technique to locate and identify features within the audio data that can be used to discriminate acceptable from unacceptable process behavior. This paper extends the previous work by providing a formal methodology for automatic, real-time, nondestructive, inspection of rotary friction welding.
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Fathi, Alireza, Mohammad Durali, Ehsan Toyserkani, and Amir Khajepour. "Control of the Clad Height in Laser Powder Deposition Process Using a PID Controller." In ASME 2006 International Mechanical Engineering Congress and Exposition. ASMEDC, 2006. http://dx.doi.org/10.1115/imece2006-13949.
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Laser Powder Deposition (LPD) process is an advanced material processing technique which has many applications. Despite this fact, reliable and accurate control schemes have not yet fully developed for the process. In this paper, the problem of controlling the clad height in the LPD process is studied. Due to a faster response of the process to change in scanning velocity over the laser power, the scanning velocity is selected as the input control variable. Since the governing equations of the LPD process are complex for designing a controller, an identified nonlinear dynamic model is used. The model is a Hammerstein model with a linear dynamic and a nonlinear memoryless block. The model parameters are identified offline using experimental data. The controller has a proportional-integral-derivation (PID) architecture. The controller was implemented on the real plant to asses its performance in the fabrication of several metallic parts composed of stainless steel.
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Doumanidis, Charalabos, Nikolaos Fourligkas, and George Korizis. "Thermal Modeling and Control of Material Processing in Scan Welding." In ASME 1998 International Mechanical Engineering Congress and Exposition. American Society of Mechanical Engineers, 1998. http://dx.doi.org/10.1115/imece1998-1033.
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Abstract The paper focuses on thermal analysis of scan welding, a new joining technique redesigned to ensure the composite morphologic, material and mechanical integrity of the weld. This is obtained by real-time control of the temperature field by a proper dynamic heat input distribution on the weld surface. This distribution is implemented in scan welding by a single torch, sweeping the joint surface by a controlled reciprocating motion, and power adjusted by feedback of infrared temperature data in-process. A numerical simulation and an analytical multivariable model of the thermal field in scan welding is established, using real-time identification of its parameters. An adaptive thermal control scheme is thus implemented and validated computationally and experimentally on a robotic Gas-Tungsten Arc Welding setup. The resulting thermal features of scan welding are analyzed in terms of material structure and properties of the weldment.
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Mehta, Parikshit, Mathew Kuttolamadom, and Laine Mears. "Machining Process Power Monitoring: Bayesian Update of Machining Power Model." In ASME 2012 International Manufacturing Science and Engineering Conference collocated with the 40th North American Manufacturing Research Conference and in participation with the International Conference on Tribology Materials and Processing. American Society of Mechanical Engineers, 2012. http://dx.doi.org/10.1115/msec2012-7277.
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Monitoring the CNC machine tool power provides valuable information that aids condition based maintenance, machine efficiency and machining process monitoring. Cutting force in machining process is an interesting variable to measure from monitoring and control point of view. Although the direct methods of measuring the cutting force exist, prohibitive costs do not allow deployment in industrial environment. In the indirect methods of measuring force, measuring the spindle motor current to estimate the cutting power and consequently the cutting force is popular. This work discusses the calibration of spindle current based torque sensor for the estimation of the cutting force in turning operation. The work undertakes handling uncertainty in measurement of the cutting torque measurement. Considering the steady state value, the cutting torque is represented as a polynomial function of the speed and measured power. Though the identification of the unknown coefficients can be done based on the offline tests, in current work, the Bayesian update of coefficients is proposed. This method allows online learning of these coefficients. The cutting torque value based on the model has some variability due to variation in the coefficients and unmodeled dynamics. The iterative learning happens in three stages, namely — Prior belief, likelihood function establishment and update in prior belief with observed data producing posterior belief. The establishment of the priors is done through some offline tests. The likelihood function accounts for noise in the measurement of torque. And finally, Markov Chain Monte Carlo (MCMC) simulations help sampling from unknown posterior distribution. This scheme has ability to sample from any distribution. A single update cycle shows high reduction in the variability of the torque. Experimental data is produced to verify the effectiveness of method; the Bayesian update scheme outperforms least-square polynomial fit method consistently for different cutting speeds and cutting load values.
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Belanger, F., D. Millan, and X. Cyril. "Submarine Autopilot Performance Optimization with System Identification." In International Ship Control Systems Symposium. IMarEST, 2018. http://dx.doi.org/10.24868/issn.2631-8741.2018.014.
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Computer simulation models play a vital role in the assessment of a ship’s autopilot design. A well-tuned autopilot will contribute to reducing rudder activity, thereby minimizing wear on the actuation plant and also generally reducing fuel consumption. The equations that describe the ship motion dynamics contain a large number of hydrodynamic coefficients that must be calculated as accurately as possible to justify the use of a simulation model and its relevance to predicting the ship manoeuvring characteristics. Proper prediction of the ship performance is an essential pre-requisite in the process of tuning the autopilot. The hydrodynamic coefficients can be calculated by using theoretical methods or by carrying out experiments on the actual ship or on a scaled model of the ship. System Identification (SI) is an experiment-based approach and in this paper the authors present an algorithm that can estimate the coefficients with great accuracy. These coefficients can classically be obtained in a towing tank using a captive model, and with a planar motion mechanism and a rotating arm. Generally, these systems are costly and entail expensive trials programs, and SI methods have been developed in an effort to obviate some of those problems and limitations. They typically process ship manoeuvring data obtained from a free-running scaled model or full-scale trials. While similar to a surface ship, the motion dynamics of a submarine introduce additional challenges for SI methods. This is because the submarine manoeuvres in “three dimensions”, which adds complexity and more hydrodynamic coefficients to the equations. The standard submarine simulation model, also referred to as the Gertler and Hagen equations, incorporates over 120 coefficients. To calculated these coefficients, the SI algorithm uses a Square-Root Unscented Kalman filter (SR-UKF). One of its appealing features is that it calculates all the coefficients by processing data from a single submarine manoeuvre that has a repeating sinusoidal pattern in both depth and course. The manoeuvre can be performed in a towing tank by a free-running scaled model of the submarine, or it can be performed at sea on the full-scale submarine as part of the sea trials schedule.
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Makarov, Mikhail, and Alexandr Astafiev. "Synthesis of special operating decisions as part of adaptive control of a mobile robot." In V International Scientific Workshop on Modeling, Information Processing and Computing. CEUR-WS.org, 2022. http://dx.doi.org/10.47813/dnit-mip5/2022-3091-12-17.
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This paper presents theory behind synthesis of special operating decisions in mobile robotics. The authors have developed and implemented an experimental research methodology to substantiate the theoretical and practical significance of the proposed decision structure for incorporation of quasi-cognitive mechanisms in the process of intelligent data processing in such robotics. This paper presents research and testing of a computer model of the abstract decision-making component that analyzes the movement trajectory of a mobile object in the operational space of a mobile robotic system. This approach towards intelligent decisionmaking can be tested for effectiveness by whether it enables the system to detect change in the parameters of the analyzed dynamic object that are important for autonomous analysis of the environment. One finding is that using this novel operating decision structure to improve autonomy contributes to the emergence of a behavior strategy that bypasses the combinatorial methods configured during the development; this improves the system’s adaptability to change in its environment.
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Kang, Yonggang, Mingyuan Chen, Xiduo Chen, Zhihao Chen, and Huan Xiao. "Simulation and Accuracy Guarantee Technology of Fuselage Component Trial Assembly Based on Dynamic Process Model." In ASME 2021 International Mechanical Engineering Congress and Exposition. American Society of Mechanical Engineers, 2021. http://dx.doi.org/10.1115/imece2021-70296.
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Abstract Modern aircraft fuselage size is large, structural rigidity is weak, the docking process is complex, accuracy guarantee is difficult and assembly efficiency is low. Especially in the plug-in butt joint assembly process of large fuselage parts, there is the inherent problem of invisible and unmeasurable docking end surfaces. It is more likely to lead to interference or uneven gaps in the docking process, and eventually lead to repeated trial assembly and decline in the consistency of the connection quality. That will affect the assembly efficiency and fatigue characteristics of the local structure. Aiming at the plug-in butt joint assembly of large fuselage parts, this paper integrates digital measurement technology, numerical control positioning technology and virtual simulation technology, through measurement modeling and trial assembly simulation to guide the digital positioning and docking process. It makes the invisible and unmeasurable process of insertion digitally visible. Through the integration of point cloud data acquisition and pre-processing, digital twin modeling and assembly simulation, a dynamic process model for trial assembly simulation is constructed. A complete test environment for the joint assembly of the fuselage barrel parts was built. Research was conducted on the reduced test pieces of MA700 front fuselage and middle fuselage. We developed a large space measurement module, a spatial attitude solution module, an integrated control module and a virtual simulation module. The effectiveness of the fuselage component trial assembly simulation based on dynamic process model and accuracy assurance technology was verified.
Reports on the topic "Process control Dynamics Data processing"
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Cook, Samantha, Marissa Torres, Nathan Lamie, Lee Perren, Scott Slone, and Bonnie Jones. Automated ground-penetrating-radar post-processing software in R programming. Engineer Research and Development Center (U.S.), September 2022. http://dx.doi.org/10.21079/11681/45621.
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Ground-penetrating radar (GPR) is a nondestructive geophysical technique used to create images of the subsurface. A major limitation of GPR is that a subject matter expert (SME) needs to post-process and interpret the data, limiting the technique’s use. Post-processing is time-intensive and, for detailed processing, requires proprietary software. The goal of this study is to develop automated GPR post-processing software, compatible with Geophysical Survey Systems, Inc. (GSSI) data, in open-source R programming. This would eliminate the need for an SME to process GPR data, remove proprietary software dependencies, and render GPR more accessible. This study collected GPR profiles by using a GSSI SIR4000 control unit, a 100 MHz antenna, and a Trimble GPS. A standardized method for post-processing data was then established, which includes static data removal, time-zero correction, distance normalization, data filtering, and stacking. These steps were scripted and automated in R programming, excluding data filtering, which was used from an existing package, RGPR. The study compared profiles processed using GSSI software to profiles processed using the R script developed here to ensure comparable functionality and output. While an SME is currently still necessary for interpretations, this script eliminates the need for one to post-process GSSI GPR data.
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Bhatt, Parth, Curtis Edson, and Ann MacLean. Image Processing in Dense Forest Areas using Unmanned Aerial System (UAS). Michigan Technological University, September 2022. http://dx.doi.org/10.37099/mtu.dc.michigantech-p/16366.
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Imagery collected via Unmanned Aerial System (UAS) platforms has become popular in recent years due to improvements in a Digital Single-Lens Reflex (DSLR) camera (centimeter and sub-centimeter), lower operation costs as compared to human piloted aircraft, and the ability to collect data over areas with limited ground access. Many different application (e.g., forestry, agriculture, geology, archaeology) are already using and utilizing the advantages of UAS data. Although, there are numerous UAS image processing workflows, for each application the approach can be different. In this study, we developed a processing workflow of UAS imagery collected in a dense forest (e.g., coniferous/deciduous forest and contiguous wetlands) area allowing users to process large datasets with acceptable mosaicking and georeferencing errors. Imagery was acquired with near-infrared (NIR) and red, green, blue (RGB) cameras with no ground control points. Image quality of two different UAS collection platforms were observed. Agisoft Metashape, a photogrammetric suite, which uses SfM (Structure from Motion) techniques, was used to process the imagery. The results showed that an UAS having a consumer grade Global Navigation Satellite System (GNSS) onboard had better image alignment than an UAS with lower quality GNSS.
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Engel, Bernard, Yael Edan, James Simon, Hanoch Pasternak, and Shimon Edelman. Neural Networks for Quality Sorting of Agricultural Produce. United States Department of Agriculture, July 1996. http://dx.doi.org/10.32747/1996.7613033.bard.
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The objectives of this project were to develop procedures and models, based on neural networks, for quality sorting of agricultural produce. Two research teams, one in Purdue University and the other in Israel, coordinated their research efforts on different aspects of each objective utilizing both melons and tomatoes as case studies. At Purdue: An expert system was developed to measure variances in human grading. Data were acquired from eight sensors: vision, two firmness sensors (destructive and nondestructive), chlorophyll from fluorescence, color sensor, electronic sniffer for odor detection, refractometer and a scale (mass). Data were analyzed and provided input for five classification models. Chlorophyll from fluorescence was found to give the best estimation for ripeness stage while the combination of machine vision and firmness from impact performed best for quality sorting. A new algorithm was developed to estimate and minimize training size for supervised classification. A new criteria was established to choose a training set such that a recurrent auto-associative memory neural network is stabilized. Moreover, this method provides for rapid and accurate updating of the classifier over growing seasons, production environments and cultivars. Different classification approaches (parametric and non-parametric) for grading were examined. Statistical methods were found to be as accurate as neural networks in grading. Classification models by voting did not enhance the classification significantly. A hybrid model that incorporated heuristic rules and either a numerical classifier or neural network was found to be superior in classification accuracy with half the required processing of solely the numerical classifier or neural network. In Israel: A multi-sensing approach utilizing non-destructive sensors was developed. Shape, color, stem identification, surface defects and bruises were measured using a color image processing system. Flavor parameters (sugar, acidity, volatiles) and ripeness were measured using a near-infrared system and an electronic sniffer. Mechanical properties were measured using three sensors: drop impact, resonance frequency and cyclic deformation. Classification algorithms for quality sorting of fruit based on multi-sensory data were developed and implemented. The algorithms included a dynamic artificial neural network, a back propagation neural network and multiple linear regression. Results indicated that classification based on multiple sensors may be applied in real-time sorting and can improve overall classification. Advanced image processing algorithms were developed for shape determination, bruise and stem identification and general color and color homogeneity. An unsupervised method was developed to extract necessary vision features. The primary advantage of the algorithms developed is their ability to learn to determine the visual quality of almost any fruit or vegetable with no need for specific modification and no a-priori knowledge. Moreover, since there is no assumption as to the type of blemish to be characterized, the algorithm is capable of distinguishing between stems and bruises. This enables sorting of fruit without knowing the fruits' orientation. A new algorithm for on-line clustering of data was developed. The algorithm's adaptability is designed to overcome some of the difficulties encountered when incrementally clustering sparse data and preserves information even with memory constraints. Large quantities of data (many images) of high dimensionality (due to multiple sensors) and new information arriving incrementally (a function of the temporal dynamics of any natural process) can now be processed. Furhermore, since the learning is done on-line, it can be implemented in real-time. The methodology developed was tested to determine external quality of tomatoes based on visual information. An improved model for color sorting which is stable and does not require recalibration for each season was developed for color determination. Excellent classification results were obtained for both color and firmness classification. Results indicted that maturity classification can be obtained using a drop-impact and a vision sensor in order to predict the storability and marketing of harvested fruits. In conclusion: We have been able to define quantitatively the critical parameters in the quality sorting and grading of both fresh market cantaloupes and tomatoes. We have been able to accomplish this using nondestructive measurements and in a manner consistent with expert human grading and in accordance with market acceptance. This research constructed and used large databases of both commodities, for comparative evaluation and optimization of expert system, statistical and/or neural network models. The models developed in this research were successfully tested, and should be applicable to a wide range of other fruits and vegetables. These findings are valuable for the development of on-line grading and sorting of agricultural produce through the incorporation of multiple measurement inputs that rapidly define quality in an automated manner, and in a manner consistent with the human graders and inspectors.
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Blumwald, Eduardo, and Avi Sadka. Citric acid metabolism and mobilization in citrus fruit. United States Department of Agriculture, October 2007. http://dx.doi.org/10.32747/2007.7587732.bard.
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Accumulation of citric acid is a major determinant of maturity and fruit quality in citrus. Many citrus varieties accumulate citric acid in concentrations that exceed market desires, reducing grower income and consumer satisfaction. Citrate is accumulated in the vacuole of the juice sac cell, a process that requires both metabolic changes and transport across cellular membranes, in particular, the mitochondrial and the vacuolar (tonoplast) membranes. Although the accumulation of citrate in the vacuoles of juice cells has been clearly demonstrated, the mechanisms for vacuolar citrate homeostasis and the components controlling citrate metabolism and transport are still unknown. Previous results in the PIs’ laboratories have indicated that the expression of a large number of a large number of proteins is enhanced during fruit development, and that the regulation of sugar and acid content in fruits is correlated with the differential expression of a large number of proteins that could play significant roles in fruit acid accumulation and/or regulation of acid content. The objectives of this proposal are: i) the characterization of transporters that mediate the transport of citrate and determine their role in uptake/retrieval in juice sac cells; ii) the study of citric acid metabolism, in particular the effect of arsenical compounds affecting citric acid levels and mobilization; and iii) the development of a citrus fruit proteomics platform to identify and characterize key processes associated with fruit development in general and sugar and acid accumulation in particular. The understanding of the cellular processes that determine the citrate content in citrus fruits will contribute to the development of tools aimed at the enhancement of citrus fruit quality. Our efforts resulted in the identification, cloning and characterization of CsCit1 (Citrus sinensis citrate transporter 1) from Navel oranges (Citrus sinesins cv Washington). Higher levels of CsCit1 transcripts were detected at later stages of fruit development that coincided with the decrease in the juice cell citrate concentrations (Shimada et al., 2006). Our functional analysis revealed that CsCit1 mediates the vacuolar efflux of citrate and that the CsCit1 operates as an electroneutral 1CitrateH2-/2H+ symporter. Our results supported the notion that it is the low permeable citrateH2 - the anion that establishes the buffer capacity of the fruit and determines its overall acidity. On the other hand, it is the more permeable form, CitrateH2-, which is being exported into the cytosol during maturation and controls the citrate catabolism in the juice cells. Our Mass-Spectrometry-based proteomics efforts (using MALDI-TOF-TOF and LC2- MS-MS) identified a large number of fruit juice sac cell proteins and established comparisons of protein synthesis patterns during fruit development. So far, we have identified over 1,500 fruit specific proteins that play roles in sugar metabolism, citric acid cycle, signaling, transport, processing, etc., and organized these proteins into 84 known biosynthetic pathways (Katz et al. 2007). This data is now being integrated in a public database and will serve as a valuable tool for the scientific community in general and fruit scientists in particular. Using molecular, biochemical and physiological approaches we have identified factors affecting the activity of aconitase, which catalyze the first step of citrate catabolism (Shlizerman et al., 2007). Iron limitation specifically reduced the activity of the cytosolic, but not the mitochondrial, aconitase, increasing the acid level in the fruit. Citramalate (a natural compound in the juice) also inhibits the activity of aconitase, and it plays a major role in acid accumulation during the first half of fruit development. On the other hand, arsenite induced increased levels of aconitase, decreasing fruit acidity. We have initiated studies aimed at the identification of the citramalate biosynthetic pathway and the role(s) of isopropylmalate synthase in this pathway. These studies, especially those involved aconitase inhibition by citramalate, are aimed at the development of tools to control fruit acidity, particularly in those cases where acid level declines below the desired threshold. Our work has significant implications both scientifically and practically and is directly aimed at the improvement of fruit quality through the improvement of existing pre- and post-harvest fruit treatments.