A New Method for Parameters Extraction of Extruded Surface

2011 ◽  
Vol 474-476 ◽  
pp. 834-839
Author(s):  
Luo Heng Yan ◽  
Zhong Min Huangfu
Keyword(s):  
Reverse Engineering ◽  
Random Sampling ◽  
Least Squares Method ◽  
Consensus Algorithm ◽  
Measure Data ◽  
Model Parameters ◽  
Cad Model ◽  
Parameters Extraction ◽  
Random Sampling Consensus ◽  
Crucial Parameter

The purpose of reverse engineering is to convert a large points cloud into a CAD model. Parameters extraction for extruded surface from measure data is an important problerm in reverse engineering. Extruded direction is a crucial parameter of extruded surface. In this paper, random sampling consensus algorithm combined with Least-Squares method is used to extract the extruded direction of extruded surface. Experimental results show effectiveness, robustness and accuracy of this proposed approach.

Parameters Extraction of Rotational Surface Using a New Method

2011 ◽  
Vol 320 ◽  
pp. 610-615
Author(s):  
Luo Heng Yan ◽  
Zhong Min Huangfu
Keyword(s):  
Reverse Engineering ◽  
Least Squares Method ◽  
Consensus Algorithm ◽  
Measure Data ◽  
Model Parameters ◽  
Rotational Axis ◽  
Rotational Surface ◽  
Parameters Extraction ◽  
Random Sampling Consensus ◽  
Crucial Parameter

The purpose of reverse engineering is to convert a large points cloud into a CAD model. Parameters extraction for rotational surface from measure data is an important problem in reverse engineering. Rotational axis is a crucial parameter of rotational surface. In this paper, random sampling consensus algorithm combined with Least-Squares method is used to extract the rotational axis of rotational surface. Experimental results show effectiveness, robustness and accuracy of this proposed approach.

Improved random sampling consensus algorithm for vision navigation of intelligent harvester robot

2020 ◽  
Vol 47 (6) ◽  
pp. 881-887
Author(s):  
Bin Li ◽  
Yu Yang ◽  
Chengshuai Qin ◽  
Xiao Bai ◽  
Lihui Wang
Keyword(s):  
Real Time ◽  
Precision Agriculture ◽  
Random Sampling ◽  
Median Filter ◽  
Detection Algorithm ◽  
Consensus Algorithm ◽  
Vision Navigation ◽  
Content Type ◽  
Navigation Path ◽  
Random Sampling Consensus

Purpose Focusing on the problem that the visual detection algorithm of navigation path line in intelligent harvester robot is susceptible to interference and low accuracy, a navigation path detection algorithm based on improved random sampling consensus is proposed. Design/methodology/approach First, inverse perspective mapping was applied to the original images of rice or wheat to restore the three-dimensional spatial geometric relationship between rice or wheat rows. Second, set the target region and enhance the image to highlight the difference between harvested and unharvested rice or wheat regions. Median filter is used to remove the intercrop gap interference and improve the anti-interference ability of rice or wheat image segmentation. The third step is to apply the method of maximum variance to thresholding the rice or wheat images in the operation area. The image is further segmented with the single-point region growth, and the harvesting boundary corner is detected to improve the accuracy of the harvesting boundary recognition. Finally, fitting the harvesting boundary corner point as the navigation path line improves the real-time performance of crop image processing. Findings The experimental results demonstrate that the improved random sampling consensus with an average success rate of 94.6% has higher reliability than the least square method, probabilistic Hough and traditional random sampling consensus detection. It can extract the navigation line of the intelligent combine robot in real time at an average speed of 57.1 ms/frame. Originality/value In the precision agriculture technology, the accurate identification of the navigation path of the intelligent combine robot is the key to realize accurate positioning. In the vision navigation system of harvester, the extraction of navigation line is its core and key, which determines the speed and precision of navigation.

Constructing and model-fitting receiver operator characteristics using continuous data.

2018 ◽  
Author(s):  
Josephine Ann Urquhart ◽  
Akira O'Connor
Keyword(s):  
Signal Detection ◽  
Least Squares Method ◽  
Model Fitting ◽  
Simulated Data ◽  
Continuous Variable ◽  
Continuous Data ◽  
Model Parameters ◽  
Operating Characteristics ◽  
Unequal Variance ◽  
Discrete Discrimination

Receiver operating characteristics (ROCs) are plots which provide a visual summary of a classifier’s decision response accuracy at varying discrimination thresholds. Typical practice, particularly within psychological studies, involves plotting an ROC from a limited number of discrete thresholds before fitting signal detection parameters to the plot. We propose that additional insight into decision-making could be gained through increasing ROC resolution, using trial-by-trial measurements derived from a continuous variable, in place of discrete discrimination thresholds. Such continuous ROCs are not yet routinely used in behavioural research, which we attribute to issues of practicality (i.e. the difficulty of applying standard ROC model-fitting methodologies to continuous data). Consequently, the purpose of the current article is to provide a documented method of fitting signal detection parameters to continuous ROCs. This method reliably produces model fits equivalent to the unequal variance least squares method of model-fitting (Yonelinas et al., 1998), irrespective of the number of data points used in ROC construction. We present the suggested method in three main stages: I) building continuous ROCs, II) model-fitting to continuous ROCs and III) extracting model parameters from continuous ROCs. Throughout the article, procedures are demonstrated in Microsoft Excel, using an example continuous variable: reaction time, taken from a single-item recognition memory. Supplementary MATLAB code used for automating our procedures is also presented in Appendix B, with a validation of the procedure using simulated data shown in Appendix C.

ТИРИСТОРНЫЙ ЭФФЕКТ В СВЧ ИС, ИЗГОТОВЛЕННЫХ ПО SIGE БИКМОП-ТЕХНОЛОГИЯМ

2020 ◽  
Vol 96 (3s) ◽  
pp. 612-614
Author(s):  
В.В. Елесина ◽  
И.О. Метелкин
Keyword(s):  
Integrated Circuits ◽  
Extraction Procedure ◽  
Compact Model ◽  
Model Parameters ◽  
Cad Systems ◽  
Parameters Extraction ◽  
Sige Bicmos ◽  
Bicmos Integrated Circuits ◽  
Basic Parameters ◽  
Radiation Induced

Проведен анализ случаев возникновения тиристорного эффекта в СВЧ ИС, изготовленных по технологии SiGe БиКМОП, при воздействии ионизирующего излучения. Рассмотрены области СВЧ ИС, чувствительные к возникновению ТЭ, определены основные параметры тиристорных структур. Проведена апробация подхода к восстановлению параметров схемно-топологической радиационно-ориентированной модели тиристорной структуры для САПР. The paper analyzes ionizing radiation induced latchup in microwave SiGe BiCMOS integrated circuits (ICs). Critical parts of ICs sensitive to latchup have been identified and basic parameters of corresponding parasitic thyristor structures have been determined. An approach has been approved to the thyristor structure compact model parameters extraction procedure intended for use in CAD systems.

scholarly journals Determination of synchronous generator nonlinear model parameters based on power rejection tests using a gradient optimization algorithm

2017 ◽  
Vol 65 (4) ◽  
pp. 479-488 ◽  
Author(s):  
A. Boboń ◽  
A. Nocoń ◽  
S. Paszek ◽  
P. Pruski
Keyword(s):  
Parameter Estimation ◽  
Objective Function ◽  
Optimization Algorithm ◽  
Least Squares Method ◽  
Synchronous Generator ◽  
Operating Conditions ◽  
Model Parameters ◽  
State Variables ◽  
Starting Point ◽  
Gradient Optimization

AbstractThe paper presents a method for determining electromagnetic parameters of different synchronous generator models based on dynamic waveforms measured at power rejection. Such a test can be performed safely under normal operating conditions of a generator working in a power plant. A generator model was investigated, expressed by reactances and time constants of steady, transient, and subtransient state in the d and q axes, as well as the circuit models (type (3,3) and (2,2)) expressed by resistances and inductances of stator, excitation, and equivalent rotor damping circuits windings. All these models approximately take into account the influence of magnetic core saturation. The least squares method was used for parameter estimation. There was minimized the objective function defined as the mean square error between the measured waveforms and the waveforms calculated based on the mathematical models. A method of determining the initial values of those state variables which also depend on the searched parameters is presented. To minimize the objective function, a gradient optimization algorithm finding local minima for a selected starting point was used. To get closer to the global minimum, calculations were repeated many times, taking into account the inequality constraints for the searched parameters. The paper presents the parameter estimation results and a comparison of the waveforms measured and calculated based on the final parameters for 200 MW and 50 MW turbogenerators.

scholarly journals Least Squares Estimations for the General Linear Model Parameters with Epsilon Skew Normal Error Term

2020 ◽  
pp. 636-645
Author(s):  
Hussain Karim Nashoor ◽  
Ebtisam Karim Abdulah
Keyword(s):  
Least Squares ◽  
Linear Model ◽  
Least Squares Method ◽  
General Linear Model ◽  
Ordinary Least Squares ◽  
Skewed Distribution ◽  
General Linear ◽  
Average Error ◽  
Model Parameters ◽  
Skew Normal

Examination of skewness makes academics more aware of the importance of accurate statistical analysis. Undoubtedly, most phenomena contain a certain percentage of skewness which resulted to the appearance of what is -called "asymmetry" and, consequently, the importance of the skew normal family . The epsilon skew normal distribution ESN (μ, σ, ε) is one of the probability distributions which provide a more flexible model because the skewness parameter provides the possibility to fluctuate from normal to skewed distribution. Theoretically, the estimation of linear regression model parameters, with an average error value that is not zero, is considered a major challenge due to having difficulties, as no explicit formula to calculate these estimates can be obtained. Practically, values for these estimates can be obtained only by referring to numerical methods. This research paper is dedicated to estimate parameters of the Epsilon Skew Normal General Linear Model (ESNGLM) using an adaptive least squares method, as along with the employment of the ordinary least squares method for estimating parameters of the General Linear Model (GLM). In addition, the coefficient of determination was used as a criterion to compare the models’ preference. These methods were applied to real data represented by dollar exchange rates. The Matlab software was applied in this work and the results showed that the ESNGLM represents a satisfactory model. 

scholarly journals The identification of a device based on a Peltier element by the least squares method

2020 ◽  
pp. 17-27
Author(s):  
Vladimir Grinkevich ◽  
Keyword(s):  
Mathematical Model ◽  
Least Squares ◽  
Least Squares Method ◽  
Control Object ◽  
Object Identification ◽  
Model Parameters ◽  
Peltier Element ◽  
Transport Delay ◽  
Non Linear ◽  
The Mathematical Model

The evaluation of the mathematical model parameters of a non-linear object with a transport delay is considered in this paper. A temperature controlled stage based on a Peltier element is an identification object in the paper. Several input signal implementations are applied to the input of the identification object. The least squares method is applied for the calculation of the non-linear differential equitation parameters which describe the identification object. The least squares method is used due to its simplicity and the possibility of identification non-linear objects. The parameters values obtained in the process of identification are provided. The plots of temperature changes in the temperature control system with a controller designed based on the mathematical model of the control object obtained as a result of identification are shown. It is found that the mathematical model obtained in the process of identification may be applied to design controllers for non-linear systems, in particular for a temperature stage based on a Peltier element, and for self-tuning controllers. However, the least square method proposed in the paper cannot estimate the transport delay time. Therefore it is required to evaluate the time delay by temperature transient processes. Dynamic object identification is applied when it is required to obtain a mathematical model structure and evaluate the parameters by an input and output control object signal. Also, identification is applied for auto tuning of controllers. A mathematical model of a control object is required to design the controller which is used to provide the required accuracy and stability of control systems. Peltier elements are applied to design low-power and small- size temperature stage . Hot benches based on a Peltier element can provide the desired temperature above and below ambient temperature.

scholarly journals ANALYSIS AND COMPARISON OF DIFFERENT APPROACHES TO THE PROBLEM OF MEMRISTOR MODEL PARAMETERS EXTRACTION

2021 ◽  
Author(s):  
Yevgeny Shamin ◽  
Dmitry Zhevnenko ◽  
Fedor Meschaninov ◽  
Vladislav Kozhevnikov ◽  
Yevgeny Gornev
Keyword(s):  
Extraction Process ◽  
Original Version ◽  
Model Parameters ◽  
Parameters Extraction ◽  
Extraction Algorithm

The work is devoted to the analysis of various approaches to the problem of the empirical memristor model parameters extraction. A description of the peculiarities of the extraction process is given, and an original version of the extraction algorithm is proposed. The proposed algorithm is compared with other considered ones.

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