Analysis of a Real-Time Capable Cable Force Computation Method

2014 ◽  
pp. 227-238 ◽  
Author(s):  
Katharina Müller ◽  
Christopher Reichert ◽  
Tobias Bruckmann
Keyword(s):  
Real Time ◽  
Computation Method ◽  
Cable Force

A Real Time Power System Harmonic Estimator Considering Fundamental Frequency Variations

2010 ◽  
Vol 11 (4) ◽  
Author(s):  
Mohammad Reza Dadash Zadeh
Keyword(s):  
Power Systems ◽  
Power System ◽  
Real Time ◽  
Fundamental Frequency ◽  
Digital Signal Processor ◽  
Sampling Rate ◽  
Window Size ◽  
Digital Signal ◽  
Computation Method ◽  
Harmonic Components

A new technique based on orthogonal filters and iterative frequency tracking is proposed to estimate harmonic components in power systems for real time applications. Frequency interpolation is used to estimate fundamental frequency and harmonics when the nominal frequency of the signal is a non-integer value. Fixed data window size and fixed sampling rate are the two advantageous features of the proposed technique. An off-line computation method with linear interpolation is proposed to reduce the number of computations involved during the generation of filter coefficients. The proposed technique was implemented using a real-time DSP (digital signal processor) data acquisition system. The performance of the proposed technique was studied by estimating the harmonic components of various signals. A FFT (Fast Fourier Transform) based technique was also used to estimate harmonic components for comparison. It has been shown that the accurate fundamental frequency is computed using iterative technique, and then accurate harmonic components are estimated when the fundamental frequency is not equal to the power system nominal frequency.

STRONG REAL-TIME QRS COMPLEX DETECTION

2017 ◽  
Vol 17 (08) ◽  
pp. 1750111 ◽  
Author(s):  
M. M. BENOSMAN ◽  
F. BEREKSI-REGUIG ◽  
E. GORAN SALERUD
Keyword(s):  
Heart Rate ◽  
Real Time ◽  
Trunk Muscles ◽  
Computation Method ◽  
Ecg Signal ◽  
Qrs Complex ◽  
Rr Intervals ◽  
Ecg Signals ◽  
Qrs Complex Detection ◽  
Complex Detection

Heart rate variability (HRV) analysis is used as a marker of autonomic nervous system activity which may be related to mental and/or physical activity. HRV features can be extracted by detecting QRS complexes from an electrocardiogram (ECG) signal. The difficulties in QRS complex detection are due to the artifacts and noises that may appear in the ECG signal when subjects are performing their daily life activities such as exercise, posture changes, climbing stairs, walking, running, etc. This study describes a strong computation method for real-time QRS complex detection. The detection is improved by the prediction of the position of [Formula: see text] waves by the estimation of the RR intervals lengths. The estimation is done by computing the intensity of the electromyogram noises that appear in the ECG signals and known here in this paper as ECG Trunk Muscles Signals Amplitude (ECG-TMSA). The heart rate (HR) and ECG-TMSA increases with the movement of the subject. We use this property to estimate the lengths of the RR intervals. The method was tested using famous databases, and also with signals acquired when an experiment with 17 subjects from our laboratory. The obtained results using ECG signals from the MIT-Noise Stress Test Database show a QRS complex detection error rate (ER) of 9.06%, a sensitivity of 95.18% and a positive prediction of 95.23%. This method was also tested against MIT-BIH Arrhythmia Database, the result are 99.68% of sensitivity and 99.89% of positive predictivity, with ER of 0.40%. When applied to the signals obtained from the 17 subjects, the algorithm gave an interesting result of 0.00025% as ER, 99.97% as sensitivity and 99.99% as positive predictivity.

scholarly journals Regional probabilistic situational awareness and forecasting of COVID-19

2021 ◽  
Author(s):  
Solveig Engebretsen ◽  
Alfonso Diz-Lois Palomares ◽  
Gunnar &Oslashvind Isaksson R&oslash ◽  
Anja Br&aringthen Kristoffersen ◽  
Jonas Christoffer Lindstr&oslashm ◽  
...  
Keyword(s):  
Real Time ◽  
Situational Awareness ◽  
Disease Spread ◽  
Mobile Phone Data ◽  
Computation Method ◽  
Detection Probabilities ◽  
Before And After ◽  
Imported Cases ◽  
Approximate Bayesian ◽  
And Control

Mathematical models and statistical inference are fundamental for surveillance and control of the COVID-19 pandemic. Several aspects cause regional heterogeneity in disease spread. Individual behaviour, mobility, viral variants and transmission vary locally, temporally and with the season, and interventions and vaccination are often implemented regionally. Therefore, we developed a new regional changepoint stochastic SEIR metapopulation model. The model is informed by real-time mobility estimates from mobile phone data, laboratory-confirmed cases, and hospitalisation incidence. To estimate locally and time-varying transmissibility, case detection probabilities, and missed imported cases, we present a new sequential Approximate Bayesian Computation method allowing inference in useful time, despite the high parametric dimension. We test our approach on Norway and find that three-week-ahead predictions are precise and well-calibrated, suitable for real-time surveillance. By comparing the reproduction number before and after lockdown, we find a national transmissibility reduction of 85% (95% CI 78%-89%). The estimated effect varied regionally and was larger for the most populated regions than in the national average.

A Computational Method for the Estimation of the Geometrical and Thermophysical Properties of Tumor Using Contact Thermometry

2021 ◽  
Author(s):  
Nimmi Sudarsan ◽  
Arathy K ◽  
Linta Antony ◽  
Sudheesh R S ◽  
Muralidharan M N ◽  
...  
Keyword(s):  
Surface Temperature ◽  
Real Time ◽  
Thermophysical Properties ◽  
Human Subjects ◽  
Research Work ◽  
Estimation Method ◽  
Computational Method ◽  
Heat Transfer Analysis ◽  
Computation Method ◽  
Geometric Center

Abstract Contact thermometry is the measurement of surface temperature using sensors in contact with the medium. These surface temperatures can be potential indicators of any abnormality possibly a tumor. This research work presents a computation method that makes use of contact thermometry to estimate the geometric center, size and thermophysical properties of breast tumor. Wearable thermal sensors captured real time surface temperature readings from discrete point locations. The continuous heat distribution over the domain was formulated using forward heat transfer analysis. The optimization method estimated tumor parameters of the breast and a 3D thermal model was developed from the estimated parameters. Laboratory experiments on breast phantoms were done to validate the estimation method. Furthermore, real time temperature readings of human subjects were recorded and the estimated location and size were then compared with the mammogram results. It was found that, the estimated 2D geometric center and the size in diameter of the tumor closely matches with the mammogram results. Further the thermophysical properties estimated using the proposed method had a higher order in subjects having a tumor making it a tool for breast cancer screening.

Discrete Deformation Models for Real-Time Computation of Compliant Mechanisms

2013 ◽  
Author(s):  
Jingjing Ji ◽  
Kok-Meng Lee
Keyword(s):  
Real Time ◽  
Force Feedback ◽  
Compliant Mechanisms ◽  
Simulated Data ◽  
Operating Conditions ◽  
Practical Implementation ◽  
Computation Method ◽  
Beam Model ◽  
Path Lengths ◽  
External Forces

This paper presents the formulation of a reduced-order linear discrete–path approximation in state space and its solution as a function of path lengths for a 3D curvature-based beam model (CBM). Solutions to both forward and inverse problems are discussed; the former is essential for real-time deformed shape visualization whereas the latter is much needed for haptic force feedback. The method is illustrated with an application example where a 2D beam is characterized by a 6th order CBM. Practical implementation shows that when external forces as system input are expressed in global coordinates, the CBM can be decoupled into two 2nd order systems enabling parallel computing of the deformed shape and the orientation and moment, and effectively reducing the table size for storing the operating conditions. The proposed real-time computation method has been validated by verifying results against published experimental and MSM simulated data.

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