scholarly journals Load Reconstruction Technique UsingD-Optimal Design and Markov Parameters

2015 ◽  
Vol 2015 ◽  
pp. 1-9
Author(s):  
Deepak K. Gupta ◽  
Anoop K. Dhingra
Keyword(s):  
Linear Prediction ◽  
System Modeling ◽  
Prediction Algorithm ◽  
System Response ◽  
Reconstruction Technique ◽  
Markov Parameters ◽  
Solution Approach ◽  
Load Transducer ◽  
Measured Response

This paper develops a technique for identifying dynamic loads acting on a structure based on impulse response of the structure, also referred to as the system Markov parameters, and structure response measured at optimally placed sensors on the structure. Inverse Markov parameters are computed from the forward Markov parameters using a linear prediction algorithm and have the roles of input and output reversed. The applied loads are then reconstructed by convolving the inverse Markov parameters with the system response to the loads measured at optimal locations on the structure. The structure essentially acts as its own load transducer. It has been noted that the computation of inverse Markov parameters, like most other inverse problems, is ill-conditioned which causes their convolution with the measured response to become quite sensitive to errors in system modeling and response measurements. The computation of inverse Markov parameters (and thereby the quality of load estimates) depends on the locations of sensors on the structure. To ensure that the computation of inverse Markov parameters is well-conditioned, a solution approach, based on the construction ofD-optimal designs, is presented to determine the optimal sensor locations such that precise load estimates are obtained.

scholarly journals Design of Auto-tuning Relay Feedback controller for Shell Heavy Oil Fractionator

2018 ◽  
Vol 218 ◽  
pp. 02007
Author(s):  
Wahyudi ◽  
Sela Martasia ◽  
Budi Setiyono ◽  
Iwan Setiawan
Keyword(s):  
Heavy Oil ◽  
System Modeling ◽  
Control Technique ◽  
System Response ◽  
Relay Feedback ◽  
End Point ◽  
Column Type ◽  
Point Composition ◽  
Auto Tuning ◽  
The Difference

Auto-tuning relay feedback is one of the control techniques, which is used to solve the non-linear, long delay time, and disturbance's problems. This control technique is the development of Ziegler-Nichols that can be done automatically without doing system modeling. In this paper, auto-tuning relay feedback is used in the control system response to optimization of Shell Heavy Oil Fractionator (SHOF) system so the output of product composition as expected. SHOF is a distillation column type used to separate crude oil into desired products based on the difference in the boiling point of each product. PI regulators of relay feedback are used to control the valves on the SHOF with three inputs and three outputs that has been decoupled. Based on the tests, the average values of IAE at top end point composition (Y1) obtained with disturbance and no disturbance are 83.17 and 10.933, respectively. At the side end point composition (Y2), the average values of IAE with disturbance and no disturbance are obtained respectively, 336.38 and 42.3467. The average values of IAE at bottom reflux temperature (Y3) with disturbance and no disturbance are obtained 0.15 and 0.13, respectively.

scholarly journals МОДЕЛЬ ПРОЦЕСУ ВІДНОВЛЕННЯ ІНФОРМАЦІЇ З УШКОДЖЕНИХ НОСІЇВ

2018 ◽  
Vol 120 (2) ◽  
pp. 26-37
Author(s):  
В. Б. Швайченко ◽  
О. П. Гребінь ◽  
Н. Ф. Левенець
Keyword(s):  
Conceptual Model ◽  
System Modeling ◽  
Recovery Process ◽  
Sound Quality ◽  
Computer Processing ◽  
System Model ◽  
Information Recovery ◽  
Restoration Process ◽  
Processing Modes

Improving the quality of the restored information in the process of restoration and restoration of phonograms.Synthesis of the system model on the basis of analysis of the processes of restoration and restoration of phonograms from media of various types and computer processing. The characteristics of the conceptual model of the restoration and restoration of the phonogram are determined. The structure of the system model of the information recovery process is developed. A lot of concepts and connections between concepts are defined. The structure of the system modeling restoration and restoration of phonograms is defined. A conceptual model of the restoration and restoration process is proposed. The distribution of artifacts over the playback and processing modes of a phonogram is justified. Details of the type of content with features of the effect on the state of the phonogram.The solutions obtained are the basis of the methodology for carrying out the process of restoration and restoration of phonograms by the criterion of sound quality.

Meteorological Data Forecast using RNN

2020 ◽  
pp. 905-920
Author(s):  
Stefan Balluff ◽  
Jörg Bendfeld ◽  
Stefan Krauter
Keyword(s):  
Neural Networks ◽  
Wind Speed ◽  
Linear Prediction ◽  
Learning Algorithm ◽  
Meteorological Data ◽  
System Modeling ◽  
Descent Method ◽  
Gradient Descent Method ◽  
Earth System Modeling ◽  
Set Up

Gathering knowledge not only of the current but also the upcoming wind speed is getting more and more important as the experience of operating and maintaining wind turbines is increasing. Not only with regards to operation and maintenance tasks such as gearbox and generator checks but moreover due to the fact that energy providers have to sell the right amount of their converted energy at the European energy markets, the knowledge of the wind and hence electrical power of the next day is of key importance. Selling more energy as has been offered is penalized as well as offering less energy as contractually promised. In addition to that the price per offered kWh decreases in case of a surplus of energy. Achieving a forecast there are various methods in computer science: fuzzy logic, linear prediction or neural networks. This paper presents current results of wind speed forecasts using recurrent neural networks (RNN) and the gradient descent method plus a backpropagation learning algorithm. Data used has been extracted from NASA's Modern Era-Retrospective analysis for Research and Applications (MERRA) which is calculated by a GEOS-5 Earth System Modeling and Data Assimilation system. The presented results show that wind speed data can be forecasted using historical data for training the RNN. Nevertheless, the current set up system lacks robustness and can be improved further with regards to accuracy.

Evaluation of three-dimensional iterative image reconstruction in virtual monochromatic imaging at 40 kilo-electron volts: phantom and clinical studies to assess the image noise and image quality in comparison with other reconstruction techniques

2020 ◽  
Vol 93 (1110) ◽  
pp. 20190675
Author(s):  
Takuya Ishikawa ◽  
Shigeru Suzuki ◽  
Yoshiaki Katada ◽  
Tomoko Takayanagi ◽  
Rika Fukui ◽  
...  
Keyword(s):  
Clinical Study ◽  
Image Reconstruction ◽  
Image Quality ◽  
Three Dimensional ◽  
Image Noise ◽  
Reconstruction Technique ◽  
Iterative Image Reconstruction ◽  
Virtual Monochromatic Imaging ◽  
Monochromatic Imaging

Objective: The purpose of this study was to evaluate the image quality in virtual monochromatic imaging (VMI) at 40 kilo-electron volts (keV) with three-dimensional iterative image reconstruction (3D-IIR). Methods: A phantom study and clinical study (31 patients) were performed with dual-energy CT (DECT). VMI at 40 keV was obtained and the images were reconstructed using filtered back projection (FBP), 50% adaptive statistical iterative reconstruction (ASiR), and 3D-IIR. We conducted subjective and objective evaluations of the image quality with each reconstruction technique. Results: The image contrast-to-noise ratio and image noise in both the clinical and phantom studies were significantly better with 3D-IIR than with 50% ASiR, and with 50% ASiR than with FBP (all, p < 0.05). The standard deviation and noise power spectra of the reconstructed images decreased in the order of 3D-IIR to 50% ASiR to FBP, while the modulation transfer function was maintained across the three reconstruction techniques. In most subjective evaluations in the clinical study, the image quality was significantly better with 3D-IIR than with 50% ASiR, and with 50% ASiR than with FBP (all, p < 0.001). Regarding the diagnostic acceptability, all images using 3D-IIR were evaluated as being fully or probably acceptable. Conclusions: The quality of VMI at 40 keV is improved by 3D-IIR, which allows the image noise to be reduced and structural details to be maintained. Advances in knowledge: The improvement of the image quality of VMI at 40 keV by 3D-IIR may increase the subjective acceptance in the clinical setting.

scholarly journals A 3D Unstructured Mesh FDTD Scheme for EM Modelling

2020 ◽  
Vol 28 (1) ◽  
pp. 181-213
Author(s):  
A. Gansen ◽  
M. El Hachemi ◽  
S. Belouettar ◽  
O. Hassan ◽  
K. Morgan
Keyword(s):  
Unstructured Mesh ◽  
Fdtd Method ◽  
Solution Approach ◽  
Transmission Problems ◽  
Electromagnetic Interactions ◽  
Tetrahedral Elements ◽  
Hexahedral Elements ◽  
Volume Method ◽  
Difference Time

AbstractThe Yee finite difference time domain (FDTD) algorithm is widely used in computational electromagnetics because of its simplicity, low computational costs and divergence free nature. The standard method uses a pair of staggered orthogonal cartesian meshes. However, accuracy losses result when it is used for modelling electromagnetic interactions with objects of arbitrary shape, because of the staircased representation of curved interfaces. For the solution of such problems, we generalise the approach and adopt an unstructured mesh FDTD method. This co-volume method is based upon the use of a Delaunay primal mesh and its high quality Voronoi dual. Computational efficiency is improved by employing a hybrid primal mesh, consisting of tetrahedral elements in the vicinity of curved interfaces and hexahedral elements elsewhere. Difficulties associated with ensuring the necessary quality of the generated meshes will be discussed. The power of the proposed solution approach is demonstrated by considering a range of scattering and/or transmission problems involving perfect electric conductors and isotropic lossy, anisotropic lossy and isotropic frequency dependent chiral materials.

scholarly journals An Early Intestinal Cancer Prediction Algorithm Based on Deep Belief Network

2019 ◽  
Vol 9 (1) ◽  
Author(s):  
Jing-Jing Wan ◽  
Bo-Lun Chen ◽  
Yi-Xiu Kong ◽  
Xing-Gang Ma ◽  
Yong-Tao Yu
Keyword(s):  
Colorectal Cancer ◽  
Early Stage ◽  
Prediction Algorithm ◽  
Medical Doctors ◽  
Cancer Prediction ◽  
Treatment And Prevention ◽  
Learning Technique ◽  
Previous Prediction ◽  
High Computational Complexity

AbstractThe incidence of colorectal cancer (colorectal cancer, CRC) in China has increased in recent years, and its mortality rate has become one of the highest among all cancers. CRC also increasingly affects people’s health and quality of life, and the workloads of medical doctors have further increased due to the lack of sufficient medical resources in China. The goal of this study was to construct an automated expert system using a deep learning technique to predict the probability of early stage CRC based on the patient’s case report and the patient’s attributes. Compared with previous prediction methods, which are either based on sophisticated examinations or have high computational complexity, this method is shown to provide valuable information such as suggesting potentially important early signs to assist in early diagnosis, early treatment and prevention of CRC, hence helping medical doctors reduce the workloads of endoscopies and other treatments.

Comparing planar image quality of rotating slat and parallel hole collimation: influence of system modeling

2008 ◽  
Vol 53 (7) ◽  
pp. 1989-2002 ◽  
Author(s):  
Roel Van Holen ◽  
Stefaan Vandenberghe ◽  
Steven Staelens ◽  
Ignace Lemahieu
Keyword(s):  
Image Quality ◽  
System Modeling ◽  
Planar Image ◽  
Parallel Hole

Haptic Data Compression Based on Linear Prediction

2013 ◽  
Vol 712-715 ◽  
pp. 2712-2715
Author(s):  
Feng Hua Guo
Keyword(s):  
Data Reduction ◽  
Haptic Perception ◽  
Linear Prediction ◽  
Least Squares Method ◽  
Reduction Rate ◽  
Perceptual Quality ◽  
Data Packets ◽  
Data Reduction Technique ◽  
Prediction Approach

A new linear prediction-based haptic data reduction technique is presented. The prediction approach relies on the least-squares method to reduce the number of data packets. Knowledge from human haptic perception is incorporated into the architecture to assess the perceptual quality of the compressed haptic signals. Experiments prove the effectiveness of the proposed approach in data reduction rate.

Smart Production System Modeling: Bernoulli Serial Line Case

2020 ◽  
Author(s):  
Yuting Sun ◽  
Tianyu Zhu ◽  
Liang Zhang
Keyword(s):  
Manufacturing Industry ◽  
Ad Hoc ◽  
New Technologies ◽  
System Modeling ◽  
Critical Issue ◽  
Smart Manufacturing ◽  
Serial Production ◽  
Modeling Process ◽  
Serial Line

Abstract The manufacturing industry has entered the era of Industry 4.0/Smart Manufacturing. New technologies have dramatically changed the way manufacturing activities are carried out on the factory floor. In addition to an enhanced level of equipment automation, automation of decision-making has been one of the key objectives of these new initiatives. On the other hand, a critical issue that has been overlooked is the construction of mathematical models in manufacturing research and studies, which are typically done manually. This manual, ad-hoc nature of mathematical modeling is quite problematic when modeling the job flow in a manufacturing process. As a result, the quality of the models obtained may heavily depend on the experience and personal preference of the modeler. The goal of this paper is to develop a method to standardize and automate the modeling process using standard manufacturing key performance indices in the framework of Bernoulli serial production line model.

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