scholarly journals A New Algorithm for Reconstructing Two-Dimensional Temperature Distribution by Ultrasonic Thermometry

2015 ◽  
Vol 2015 ◽  
pp. 1-10 ◽  
Author(s):  
Xuehua Shen ◽  
Qingyu Xiong ◽  
Weiren Shi ◽  
Shan Liang ◽  
Xin Shi ◽  
...  
Keyword(s):  
Temperature Distribution ◽  
Ultrasound Velocity ◽  
Least Square Method ◽  
Reconstruction Algorithm ◽  
Industrial Applications ◽  
Least Square ◽  
Distribution Models ◽  
Practical Applications ◽  
Reconstruction Performance ◽  
Reconstructed Temperature

Temperature, especially temperature distribution, is one of the most fundamental and vital parameters for theoretical study and control of various industrial applications. In this paper, ultrasonic thermometry to reconstruct temperature distribution is investigated, referring to the dependence of ultrasound velocity on temperature. In practical applications of this ultrasonic technique, reconstruction algorithm based on least square method is commonly used. However, it has a limitation that the amount of divided blocks of measure area cannot exceed the amount of effective travel paths, which eventually leads to its inability to offer sufficient temperature information. To make up for this defect, an improved reconstruction algorithm based on least square method and multiquadric interpolation is presented. And then, its reconstruction performance is validated via numerical studies using four temperature distribution models with different complexity and is compared with that of algorithm based on least square method. Comparison and analysis indicate that the algorithm presented in this paper has more excellent reconstruction performance, as the reconstructed temperature distributions will not lose information near the edge of area while with small errors, and its mean reconstruction time is short enough that can meet the real-time demand.

scholarly journals A Method for Reconstruction of Boiler Combustion Temperature Field Based on Acoustic Tomography

2021 ◽  
Vol 2021 ◽  
pp. 1-11
Author(s):  
Yuhui Wu ◽  
Xinzhi Zhou ◽  
Li Zhao ◽  
Chenlong Dong ◽  
Hailin Wang
Keyword(s):  
Temperature Field ◽  
Temperature Distribution ◽  
Optimal Parameter ◽  
Interpolation Method ◽  
Least Square Method ◽  
Reconstruction Algorithm ◽  
Least Square ◽  
Temperature Fields ◽  
Acoustic Tomography ◽  
Measured Temperature

Acoustic tomography (AT), as a noninvasive temperature measurement method, can achieve temperature field measurement in harsh environments. In order to achieve the measurement of the temperature distribution in the furnace and improve the accuracy of AT reconstruction, a temperature field reconstruction algorithm based on the radial basis function (RBF) interpolation method optimized by the evaluation function (EF-RBFI for short) is proposed. Based on a small amount of temperature data obtained by the least square method (LSM), the RBF is used for interpolation. And, the functional relationship between the parameter of RBF and the root-mean-square (RMS) error of the reconstruction results is established in this paper, which serves as the objective function for the effect evaluation, so as to determine the optimal parameter of RBF. The detailed temperature description of the entire measured temperature field is finally established. Through the reconstruction of three different types of temperature fields provided by Dongfang Boiler Works, the results and error analysis show that the EF-RBFI algorithm can describe the temperature distribution information of the measured combustion area globally and is able to reconstruct the temperature field with high precision.

The Boiler Temperature Field Reconstruction Algorithm Based on Genetic Algorithm

2011 ◽  
Vol 88-89 ◽  
pp. 269-273
Author(s):  
Cheng Zhi Li ◽  
Fu Qun Shao ◽  
Zhe Kan ◽  
Hai Xiang Fan
Keyword(s):  
Genetic Algorithm ◽  
Temperature Field ◽  
Least Square Method ◽  
Reconstruction Algorithm ◽  
Acoustic Method ◽  
Least Square ◽  
Experimental Result ◽  
Field Reconstruction ◽  
Single Path ◽  
Temperature Field Reconstruction

The traditional power station boiler temperature field reconstruction algorithm is sensitive to the time of flight. In the boiler movement, the temperature field has symmetric distribution feature within the boiler. On the basis of the boiler temperature field reconstruction fundamental by using the acoustic method, the paper presents a new two dimension temperature field reconstruction algorithm, which combines the single path method and genetic algorithm. Firstly, the algorithm makes sure the temperature distribution by using single path function. It uses the points denote the temperatures on each path, and plots the mesh, which can represent the temperature preliminary distribution, by using the Bezier spline principle and linear multistep integration. Finally, the surface mesh is Interpolated and fitted by using genetic algorithm. The experimental result proved that, compared to the least square method, the new reconstruction algorithm has the feature of higher accuracy and higher reconstruction speed.

Prediction of Log-Transmissivity

1995 ◽  
Vol 26 (1) ◽  
pp. 1-20 ◽  
Author(s):  
Steen Christensen
Keyword(s):  
Prediction Error ◽  
Regression Line ◽  
Specific Capacity ◽  
Covariance Structure ◽  
Prediction Method ◽  
Least Square Method ◽  
Least Square ◽  
Practical Applications ◽  
Well Efficiency ◽  
The Mean

The log-transmissivity may in many cases be predicted from the log-transformed specific capacity of wells by applying a linear statistical model. The coefficients of the linear equation can be estimated by the least-square method. It is shown that if the estimated slope of the line differs from unity then it may indicate that the specific capacity is correlated with the well efficiency. The above prediction method is applied to case studies of aquifers in three different formations: the prediction should not be used for a homogeneous fluvioglacial formation because the variance of the well efficiency dominates the variance of the transmissivity; the prediction is fair for a heterogeneous fluvioglacial formation; and the prediction is poor for a homogeneous limnic formation. In the study of the first formation a correlation between specific capacity and well efficiency can be identified directly from the slope of the regression line. If the predictor values are taken from the drillers log then the standard error of prediction in all the cases is 0.35. This seems to be unacceptable in most practical applications. However, if one needs to predict the mean of a domain and the domain contains a number of observations of the predictor, then the averaging will reduce the prediction error. The averaging procedure ought to take the covariance structure of the variables into consideration.

scholarly journals DOA Estimation and Self-Calibration under Unknown Mutual Coupling

Sensors ◽  
2019 ◽  
Vol 19 (4) ◽  
pp. 978
Author(s):  
Dong Qi ◽  
Min Tang ◽  
Shiwen Chen ◽  
Zhixin Liu ◽  
Yongjun Zhao
Keyword(s):  
Mutual Coupling ◽  
Linear Equations ◽  
Least Square Method ◽  
Calibration Method ◽  
Least Square ◽  
Frequency Distributions ◽  
Steering Vector ◽  
Practical Applications ◽  
Time Frequency ◽  
Self Calibration

In practical applications, the assumption of omnidirectional elements is not effective in general, which leads to the direction-dependent mutual coupling (MC). Under this condition, the performance of traditional calibration algorithms suffers. This paper proposes a new self-calibration method based on the time-frequency distributions (TFDs) in the presence of direction-dependent MC. Firstly, the time-frequency (TF) transformation is used to calculate the space-time-frequency distributions (STFDs) matrix of received signals. After that, the estimated steering vector and corresponding noise subspace are estimated by the steps of noise removing, single-source TF points extracting and clustering. Then according to the transformation relationship between the MC coefficients, steering vector and MC matrix, we deduce a set of linear equations. Finally, with two-step alternating iteration, the equations are solved by least square method in order to estimate DOA and MC coefficients. Simulations results show that the proposed algorithm can achieve direction-dependent MC self-calibration and outperforms the existing algorithms.

scholarly journals An Inverse Approach of Damage Identification Using Lamb Wave Tomography

Sensors ◽  
2019 ◽  
Vol 19 (9) ◽  
pp. 2180 ◽  
Author(s):  
Yaolu Liu ◽  
Shijie Zhou ◽  
Huiming Ning ◽  
Cheng Yan ◽  
Ning Hu
Keyword(s):  
Damage Identification ◽  
Lamb Waves ◽  
Damage Index ◽  
Least Square Method ◽  
Reconstruction Algorithm ◽  
Least Square ◽  
Low Velocity Impact ◽  
Low Velocity ◽  
Inverse Approach ◽  
Wave Tomography

A pulse laser combined LWT technique with a two-stage reconstruction algorithm was proposed to realize rapid damage location, or even the evaluation of damage size for plate-like structures. Since the amplitude of Lamb waves in propagation is highly sensitive to damage, including inside damage, the change of the attenuation coefficient of Lamb waves in the inspection region was used as a damage index to reconstruct damage images. In stage one, the rough area of the damage was identified by a comparison of the amplitude of the testing signal data and reference data (undamaged state). In stage two, the damage image was reconstructed using an inverse approach based on the least-square method. In order to verify the effectiveness of the proposed rapid approach, experiments on an aluminum plate with a non-penetrating notch and a carbon fiber-reinforced plastic laminated plate with internal delamination induced by a low-velocity impact were carried out. The results show that the notch can be detected with accurate location, and the delamination image can be reconstructed successfully.

Development of a Gas Flow Sensor Based on FS5 Hot-Film Probe

2014 ◽  
Vol 568-570 ◽  
pp. 537-541
Author(s):  
Lei Yang ◽  
Jia Qiang Yang
Keyword(s):  
High Precision ◽  
Output Voltage ◽  
Gas Flow ◽  
Characteristic Curve ◽  
Measurement Data ◽  
Least Square Method ◽  
Industrial Applications ◽  
Least Square ◽  
Flow Sensor ◽  
Hot Film

On the basis of thermal measuring method, a hot-film gas flow sensor is proposed. Its sensitive element is a FS5 probe, which is integrated with measuring resistance and temperature compensating resistance inside. In order to achieve temperature compensation, the main measuring circuit is designed. Considering minimizing errors in this circuit, the temperature correcting circuit is added to further modify output voltage. By fitting measurement data of gas flow and the final output voltage with least square method, an operating characteristic curve is obtained as well as its 4th order polynomial. Under equivalent conditions, the proposed sensor, a high-precision standard sensor and an industrial sensor are experimented upon and the contrast analysis of their measurement results is given. The experimental results prove that the proposed sensor has high precision with measurement error less than 3%. Therefore the proposed sensor is feasible for industrial applications.

Existing Railway Horizontal Alignment Reconstruction Algorithm Based on Line Segments Identification

2013 ◽  
Vol 405-408 ◽  
pp. 1772-1776 ◽  
Author(s):  
Wei Liu ◽  
Jian Hong Wang ◽  
Yang Li ◽  
Wei Li
Keyword(s):  
Least Square Method ◽  
Reconstruction Algorithm ◽  
Least Square ◽  
Engineering Practice ◽  
Line Segments ◽  
Horizontal Alignment ◽  
On Line ◽  
Abnormal Points ◽  
Transition Curves ◽  
Circular Curve

A Line Segments Identification model is put forward to realize the existing railway horizontal alignment reconstruction. Firstly, Hough transform based on constraint adjustment quantity is introduced to reject the abnormal points that will affect the quality of the identification in latter steps. Then total least square method is used to get the linear segments, after which the circular curve segments and the transition curves segments will be got. At last, an evaluation function which has four arguments: circular curve radius , two transition curves length and length of straight line between curves was built and its function value is the sum of squares of all distances from measuring points to reconstruction alignment, based on the function , optimal alignment will be solved out by Powell method. Example shows that the reconstruction result is considerably superior to the traditional method and is feasible for the engineering practice.

scholarly journals Identification, Decomposition and Segmentation of Impulsive Vibration Signals with Deterministic Components—A Sieving Screen Case Study

Sensors ◽  
2020 ◽  
Vol 20 (19) ◽  
pp. 5648 ◽  
Author(s):  
Karolina Gąsior ◽  
Hanna Urbańska ◽  
Aleksandra Grzesiek ◽  
Radosław Zimroz ◽  
Agnieszka Wyłomańska
Keyword(s):  
Damage Detection ◽  
Regime Switching ◽  
Real Data ◽  
Least Square Method ◽  
Diagnostic Procedures ◽  
High Amplitude ◽  
Industrial Applications ◽  
Least Square ◽  
Raw Material ◽  
Rolling Element Bearing

Condition monitoring is a well-established field of research; however, for industrial applications, one may find some challenges. They are mostly related to complex design, a specific process performed by the machine, time-varying load/speed conditions, and the presence of non-Gaussian noise. A procedure for vibration analysis from the sieving screen used in the raw material industry is proposed in the paper. It is more for pre-processing than the damage detection procedure. The idea presented here is related to identification and extraction of two main types of components: (i) deterministic (D)—related to the unbalanced shaft(s) and (ii) high amplitude, impulsive component randomly (R) appeared in the vibration due to pieces of ore falling down of moving along the deck. If we could identify these components, then we will be able to perform classical diagnostic procedures for local damage detection in rolling element bearing. As deterministic component may be AM/FM modulated and each impulse may appear with different amplitude and damping, there is a need for an automatic procedure. We propose a method for signal processing that covers two main steps: (a) related to R/D decomposition and including signal segmentation to neglect AM/FM modulations, iterative sine wave fitting using the least square method (for each segment), signal filtering technique by subtraction fitted sine from the raw signal, the definition of the criterion to stop iteration by residuals analysis, (b) impulse segmentation and description (beginning, end, max amplitude) that contains: detection of the number of impulses in a decomposed random part of the raw signal, detection of the max value of each impulse, statistical analysis (probability density function) of max value to find regime-switching), modeling of the envelope of each impulse for samples that protrude from the signal, extrapolation (forecasting) envelope shape for samples hidden in the signal. The procedure is explained using simulated and real data. Each step is very easy to implement and interpret thus the method may be used in practice in a commercial system.

scholarly journals 3D Temperature Distribution Reconstruction in Furnace Based on Acoustic Tomography

2019 ◽  
Vol 2019 ◽  
pp. 1-15 ◽  
Author(s):  
Qian Kong ◽  
Genshan Jiang ◽  
Yuechao Liu ◽  
Jianhao Sun
Keyword(s):  
Temperature Field ◽  
Temperature Distribution ◽  
Hot Spot ◽  
Temperature Fields ◽  
Acoustic Tomography ◽  
Reconstruction Method ◽  
Distribution Models ◽  
Reconstructed Temperature ◽  
Value Decomposition ◽  
Radial Basis Function Approximation

3D temperature distribution measurement in a furnace based on acoustic tomography (AT) calculates temperature field through multipath acoustic time-of-flight (TOF) data. In this paper, a new 3D temperature field reconstruction model based on radial basis function approximation with polynomial reproduction (RBF-PR) is proposed for solving the AT inverse problem. In addition, the modified reconstruction method that integrates the advantages of the TSVD and Tikhonov regularization methods is presented to reduce the sensitivity of noise on perturbations with the ill-posed problems and improve the reconstruction quality (RQ). Numerical simulations are implemented to evaluate the effectiveness of the proposed reconstruction method using different 3D temperature distribution models, which include the one-peak symmetry distribution, one-peak asymmetry distribution, and two-peak symmetry distribution. To study the antinoise ability of our method, noises are added to the value of TOF. 3D display of reconstructed temperature fields and reconstruction errors is given. The results indicate that our model can reconstruct the temperature distribution with higher accuracy and better antinoise ability compared with the truncated generalized singular value decomposition (TGSVD). Besides that, the proposed method can determine the hot spot position with higher precision, and the temperature error of the hot spot is lower than the other compared methods.

Sign in / Sign up

Export Citation Format

Share Document