scholarly journals The Enhancement of 3D Scans Depth Resolution Obtained by Confocal Scanning of Porous Materials

2017 ◽  
Vol 17 (6) ◽  
pp. 273-281 ◽  
Author(s):  
Dalibor Martisek ◽  
Jana Prochazkova
Keyword(s):  
Porous Materials ◽  
Least Square Method ◽  
Depth Resolution ◽  
Least Square ◽  
Vertical Resolution ◽  
Limit Value ◽  
Random Events ◽  
Confocal Scanning ◽  
The Difference ◽  
3D Scans

Abstract The 3D reconstruction of simple structured materials using a confocal microscope is widely used in many different areas including civil engineering. Nonetheless, scans of porous materials such as concrete or cement paste are highly problematic. The well-known problem of these scans is low depth resolution in comparison to the horizontal and vertical resolution. The degradation of the image depth resolution is caused by systematic errors and especially by different random events. Our method is focused on the elimination of such random events, mainly the additive noise. We use an averaging method based on the Lindeberg-Lévy theorem that improves the final depth resolution to a level comparable with horizontal and vertical resolution. Moreover, using the least square method, we also precisely determine the limit value of a depth resolution. Therefore, we can continuously evaluate the difference between current resolution and the optimal one. This substantially simplifies the scanning process because the operator can easily determine the required number of scans.

scholarly journals Solution of inverse heat conduction equation with the use of Chebyshev polynomials

2016 ◽  
Vol 37 (4) ◽  
pp. 73-88 ◽  
Author(s):  
Magda Joachimiak ◽  
Andrzej Frąckowiak ◽  
Michał Ciałkowski
Keyword(s):  
Inverse Problem ◽  
Chebyshev Polynomials ◽  
Direct Problem ◽  
Least Square Method ◽  
Least Square ◽  
Random Disturbance ◽  
Inverse Heat Conduction ◽  
Chebyshev Nodes ◽  
The Difference ◽  
The Stability

AbstractA direct problem and an inverse problem for the Laplace’s equation was solved in this paper. Solution to the direct problem in a rectangle was sought in a form of finite linear combinations of Chebyshev polynomials. Calculations were made for a grid consisting of Chebyshev nodes, what allows us to use orthogonal properties of Chebyshev polynomials. Temperature distributions on the boundary for the inverse problem were determined using minimization of the functional being the measure of the difference between the measured and calculated values of temperature (boundary inverse problem). For the quasi-Cauchy problem, the distance between set values of temperature and heat flux on the boundary was minimized using the least square method. Influence of the value of random disturbance to the temperature measurement, of measurement points (distance from the boundary, where the temperature is not known) arrangement as well as of the thermocouple installation error on the stability of the inverse problem was analyzed.

Application of Photoelectric Sensor in Vehicle Power Control System

2020 ◽  
Vol 15 (6) ◽  
pp. 700-706
Author(s):  
Yifan Zhao ◽  
Mengyu Wang ◽  
Kai Wang
Keyword(s):  
Power Control ◽  
Electric Energy ◽  
Least Square Method ◽  
Least Square ◽  
Motor Speed ◽  
Time Calculation ◽  
The Mean ◽  
The Difference ◽  
Artificial Neural Network Ann ◽  
Mean Square Errors

Due to its characteristics of using clean electric energy and bringing no damage to the environment, electric vehicles (EVs) have become a new developmental direction for the automotive industry. Its reliability issues have also attracted the attention of experts and professionals. In the field of automotive power control, from the perspective of motor control, this study uses the photoelectric sensors (PSs) as the research objects and elaborates on the measurement principles of motor speed with PSs. Meanwhile, a diagnosis scheme is proposed for various faults in the measurement. Among them, the measurement speed is converted by the photoelectric signal, and the measured waveform is amplified. In the fault detection process, the Radial Basis Function (RBF) artificial neural network (ANN) is analyzed. By using this method, the difference in the motor speed detected by the sensor is calculated to determine the cause of the failure. The test uses the least-square method to compare the tested motor speed with the actual motor speed. The results show that PSs can measure the motor speed of EVs. As for the motor failures, the mean square errors (MSEs) of motor speeds generated by different faults are compared to determine the fault points according to the speed changes. In addition, the cause of motor failure can be determined by the real-time calculation of the speed differences. The above tests fully prove the effectiveness of measuring the speed of electric motors by PSs; therefore, PSs have broad application prospects in vehicle power control systems.

Simulation and Research for Gas Boiler Based on the Vague Set PID

2014 ◽  
Vol 556-562 ◽  
pp. 2101-2104
Author(s):  
Gang Zhao ◽  
Jian Li
Keyword(s):  
Dynamic Performance ◽  
Least Square Method ◽  
Equation Model ◽  
Hot Water ◽  
Least Square ◽  
Vague Set ◽  
Pid Algorithm ◽  
Static Performance ◽  
Self Tuning ◽  
The Difference

Gas hot water boiler is widely used as heating equipment in everyday life. Because gas hot water boiler has the characteristics of nonlinear, large inertia and disturbances, so it is particularly important to build a precise mathematical model. Then the difference equation model of the system is identified by the least square method according to the collected data in this paper. Writing M file in the MATLAB software to get the continuous transfer function, and setting up Vague Set PID simulation, fuzzy self-tuning PID simulation and conventional PID algorithm in SIMULINK. By comparing among the three kinds of adjusting method, We get that Vague Set PID not only in regulation time, overshoot and effect of dynamic performance is superior compared the other two controller models , but also enhance the robustness and adaptability of the system, has a good dynamic, static performance..

Optimal Weighted Least Square Data Fusion Method for Redundant IMU Based on Calculation of Measurement Error

2012 ◽  
Vol 241-244 ◽  
pp. 149-155
Author(s):  
Chuan Xing ◽  
Hai Zhang
Keyword(s):  
Measurement Error ◽  
Data Fusion ◽  
Measurement Errors ◽  
Least Square Method ◽  
Least Square ◽  
Weighted Least Square ◽  
Weighted Matrix ◽  
Measurement Results ◽  
The Difference ◽  
Projection Error

A dodecahedron non-orthogonal redundant IMU configuration was selected as model. To improve fusion accuracy, we proposed an effective calculation method for measurement errors based on the correlation between measurement errors and fusion errors. The method considered the difference between traditional data fusion vector’s projection and measurement results, and then made a conversion from projection error to measurement error. Combined with optimal weighted least square method, measurement error was used to generate an optimal weighted matrix, and this made data fusion errors minimum. Simulations also proved that the fusion result of this method is more accurate than the result of traditional method.

scholarly journals Analysis And Modelling Of Geoelectric Data Modeling For The Identication Of Groundwater aquifer At Cisarua Area, West Bandung

2020 ◽  
Vol 17 (2) ◽  
pp. 22
Author(s):  
A Daniswara ◽  
Darharta Dahrin ◽  
Setianingsih Setianingsih
Keyword(s):  
Least Square Method ◽  
Least Square ◽  
Resistivity Method ◽  
Soil Zone ◽  
Groundwater Aquifer ◽  
Geological Conditions ◽  
Aquifer Characteristic ◽  
The Difference ◽  
Agricultural Business ◽  
Geoelectric Data

Groundwater is the main need of society in everyday life. Groundwater is one of renewable resources but it doesn’t mean that it can be exploitated without limit. Several factors that affect the availability of groundwater derived from nature such as geological conditions, rainfall, and green areas should be considered. Water in the soil is stored in a porous layer and has a good permeability is called an aquifer. Cisarua area is located in West Bandung regency, West Java which is a hilly area that has a topography with a slope ranging from normal to steep. The land use in this area is still dominated with plantation and forest as green area. Groundwater aquifer characteristics in that area needs to be examined and analysed for the needs of the community and agricultural business. In this research, the writer used inversion modeling technique of geoelectric data to visualize the condition of subsurface. Resistivity inversion modelling of apparent resistivity data as a result of resistivity method with Wenner-Schlumberger configuration is then carried out with least-square method. The initial model is modified in an iterative manner such that the sum of square error of the difference between the model response and the observed data values is minimized. The result of resistivity modelling is used for analysis of aquifer characteristic such as lithology, depth and structure along with considering geological reference. As the result of modelling, the area of measurement is divided into three zones which are Zone of aeration, Zone of Saturation, and endapan formasi. Zone of aeration is located at depth 0-25 m with resistivity 20-100 Ohm.m and the predicted lithology is gravel or weathered soil. Zone of Saturation (akuifer) is located at depth 25-60 m with resistivity 4-30 Ohm.m and the predicted lithology is sandstone or clay. Endapan Formasi Cibereum is located at more than 60 m from ground with resistivity more than 100 Ohm.m and the predicted lithology is sandy tuff or dry breccia.

Rapid Ambiguity Resolution for Single Frequency Receiver

2015 ◽  
Vol 713-715 ◽  
pp. 1309-1312
Author(s):  
Yong Guo Yang ◽  
Jun Tao Xu
Keyword(s):  
Ambiguity Resolution ◽  
Regularization Method ◽  
Least Square Method ◽  
Least Square ◽  
Single Frequency ◽  
Evolutionary Method ◽  
Observation Matrix ◽  
The Difference

The algorithm of rapid ambiguity resolution for single frequency receivers is presented in this paper. Firstly, a sequential least square method is applied to decrease dimensions of the observation matrix of satellites. And then, the regularization method is applied to improve the accuracy of the float solution of ambiguities. Finally, the evolutionary method is applied to search the fixing solution of ambiguities. The experiment results show that the proposed method is fast and efficient for users to perform kinematical positioning and the difference between the positioning results of the proposed method and the results of GrafNav is in 2.5 cm.

scholarly journals Research on Roll Stabilizing Based on Energy Optimization for Autonomous Surface Vehicle

2014 ◽  
Vol 2014 ◽  
pp. 1-15 ◽  
Author(s):  
Hongjian Wang ◽  
Linlin Wang ◽  
Lixin Pan
Keyword(s):  
Energy Consumption ◽  
Difference Equation ◽  
Least Square Method ◽  
Least Square ◽  
Roll Motion ◽  
Motion Model ◽  
Recursive Least Square ◽  
Autonomous Surface Vehicle ◽  
The Difference ◽  
Fin Stabilizer

Considering the case of ASV (autonomous surface vehicle) navigating with low speed near water surface, a new method for design of roll motion controller is proposed in order to restrain wave disturbance effectively and improve roll stabilizing performance. Control system design is based on GPC (general predictive control) theory and working principle of zero-speed fin stabilizer. Coupling horizontal motion model of ASV is decoupled, and an equivalent transfer function of roll motion is obtained and transformed into a discrete difference equation through inverse Laplace transformation and Euler approximation. Finally, predictive model of GPC, namely, the difference equation of roll motion, is given. GPC algorithm of ASV roll motion is derived from performance index based on roll stabilizing performance and energy consumption used for driving fin stabilizer. In allusion to time-variant parameters in roll motion model, recursive least square method is adopted for parameter estimation. Simulation results of ASV roll motion control show better stabilizing performance and minimized energy consumption improved by self-adaptive GPC.

scholarly journals Generalized Sparse Polarization Array for DOA Estimation Using Compressive Measurements

2021 ◽  
Vol 2021 ◽  
pp. 1-10
Author(s):  
Tao Chen ◽  
Jian Yang ◽  
Weitong Wang ◽  
Muran Guo
Keyword(s):  
Degrees Of Freedom ◽  
Elevation Angle ◽  
Least Square Method ◽  
Estimation Algorithm ◽  
Doa Estimation ◽  
Least Square ◽  
Polarization Angle ◽  
Estimation Performance ◽  
The Difference ◽  
Cramer Rao Bound

The compressive array method, where a compression matrix is designed to reduce the dimension of the received signal vector, is an effective solution to obtain high estimation performance with low system complexity. While sparse arrays are often used to obtain higher degrees of freedom (DOFs), in this paper, an orthogonal dipole sparse array structure exploiting compressive measurements is proposed to estimate the direction of arrival (DOA) and polarization signal parameters jointly. Based on the proposed structure, we also propose an estimation algorithm using the compressed sensing (CS) method, where the DOAs are accurately estimated by the CS algorithm and the polarization parameters are obtained via the least-square method exploiting the previously estimated DOAs. Furthermore, the performance of the estimation of DOA and polarization parameters is explicitly discussed through the Cramér-Rao bound (CRB). The CRB expression for elevation angle and auxiliary polarization angle is derived to reveal the limit of estimation performance mathematically. The difference between the results given in this paper and the CRB results of other polarized reception structures is mainly due to the use of the compression matrix. Simulation results verify that, compared with the uncompressed structure, the proposed structure can achieve higher estimated performance with a given number of channels.

Advances of the Correlation Mapping Method to Eliminate the Peak-Locking Effect in PIV Analysis

2005 ◽  
Author(s):  
Jun Chen ◽  
Joseph Katz
Keyword(s):  
Correlation Function ◽  
Least Square Method ◽  
Mapping Method ◽  
Plane Motion ◽  
Least Square ◽  
Random Errors ◽  
Correlation Peak ◽  
Out Of Plane ◽  
The Difference ◽  
Locking Effect

The Peak-locking effect causes mean bias in most of the existing correlation based algorithms for PIV data analysis. This phenomenon is inherent to the Sub-pixel Curve Fitting (SPCF) through discrete correlation values, which is used to obtain the sub-pixel part of the displacement. A new technique for obtaining sub-pixel accuracy, the Correlation Mapping Method (CMM), was proposed by Chen & Katz [1, 2]. This new method works effectively and the peak-locking disappears in all the previous test cases, including applying to both synthetic and experimental images. The random errors are also significantly reduced. In this paper, an optimization of the algorithm is reported. Using sub-pixel interpolation, the cross-correlation function between image 1 and image 2 is expressed as a polynomial function with unknown displacement, in which the coefficients are determined by the autocorrelation function of the image 1. This virtual correlation function can be matched with the exact correlation value at every point in the vicinity of the discrete correlation peak (a 5×5 pixels area is chosen in the present study). A least square method is used to find the optimal displacement components that minimize the difference between the real and virtual correlation values. The performances of this method at the presence of background noise and out-of-plane motion are investigated by using synthetic images, as well as the influence of under-resolved particle images, and compared with the result of the SPCF method. The advantage of the CMM over SPCF is demonstrated in these studies.

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