scholarly journals Adaptive Sensor Array Error Calibration Based Impact Localization on Composite Structure

2020 ◽  
Vol 10 (11) ◽  
pp. 4042
Author(s):  
Li Ren ◽  
Yongteng Zhong ◽  
Jiawei Xiang ◽  
Zhiling Wang
Keyword(s):  
Cost Function ◽  
Composite Structure ◽  
Sensor Array ◽  
Fiber Composite ◽  
Initial Estimate ◽  
Music Algorithm ◽  
Error Calibration ◽  
The Cost ◽  
The Impact ◽  
Impact Localization

Gains and phases delay induced by sensor position error would significantly degrade the performance of high-resolution two-dimensional multiple signal classification (2D-MUSIC) algorithm, which resulting in low positioning estimation accuracy and poor imaging. In this study, adaptive piezoelectric sensor array calibration based method is proposed for impact localization on composite structure. First, observed signal vector from the sensor array is represented by error calibration matrix with unknown gains and phases, and then it used to construct the cost function including sensor array parameters. Second, a 2D-MUSIC algorithm based on linear attenuation calibration is applied for estimating the initial estimate of impact location. Finally, substituting the initial estimate, the cost function is minimized by adaptive iterative to calculate the sensor array error parameters and the exact location of the impact source. Both finite element method (FEM) simulation and experimental results on carbon-fiber composite panel demonstrate the validity and effectiveness of the proposed method.

scholarly journals Multiple Signal Classification-Based Impact Localization in Composite Structures Using Optimized Ensemble Empirical Mode Decomposition

2018 ◽  
Vol 8 (9) ◽  
pp. 1447 ◽  
Author(s):  
Yongteng Zhong ◽  
Jiawei Xiang ◽  
Xiaoyu Chen ◽  
Yongying Jiang ◽  
Jihong Pang
Keyword(s):  
Composite Structures ◽  
Sensor Array ◽  
Ensemble Empirical Mode Decomposition ◽  
Signal Classification ◽  
Music Algorithm ◽  
Multiple Signal Classification ◽  
Multiple Signal ◽  
Mode Decomposition ◽  
The Impact ◽  
Impact Localization

Multiple signal classification (MUSIC) algorithm-based structural health monitoring technology is a promising method because of its directional scanning ability and easy arrangement of the sensor array. However, in previous MUSIC-based impact location methods, the narrowband signals at a particular central frequency had to be extracted from the wideband Lamb waves induced by each impact using a wavelet transform. Additionally, the specific center frequency had to be obtained after carefully analyzing the impact signal, which is time consuming. Aiming at solving this problem, this paper presents an improved approach that combines the optimized ensemble empirical mode decomposition (EEMD) and two-dimensional multiple signal classification (2D-MUSIC) algorithm for real-time impact localization on composite structures. Firstly, the impact signal at an unknown position is obtained using a unified linear sensor array. Secondly, the fast Hilbert Huang transform (HHT) with an optimized EEMD algorithm is introduced to extract intrinsic mode functions (IMFs) from impact signals. Then, all IMFs in the whole frequency domain are directly used as the input vector of the 2D-MUSIC model separately to locate the impact source. Experimental data collected from a cross-ply glass fiber reinforced composite plate are used to validate the proposed approach. The results show that the use of optimized EEMD and 2D-MUSIC is suitable for real-time impact localization of composite structures.

The effect of environmental regulations: a restricted cost function for Korean manufacturing industries

2007 ◽  
Vol 12 (1) ◽  
pp. 91-104 ◽  
Author(s):  
MYUNGHUN LEE
Keyword(s):  
Cost Function ◽  
Raw Materials ◽  
Environmental Regulations ◽  
Environmental Conservation ◽  
Manufacturing Industries ◽  
Parameter Estimates ◽  
Productive Activities ◽  
The Cost ◽  
The Impact ◽  
Percent Decline

Environmental conservation requires society to consider the trade-off between allocating resources to productive activities and pollution control activities. Therefore, it is informative to measure the effect of environmental regulations on firms' productivity. This paper attempts to estimate the impact of environmental regulations on Korean manufacturing industries. Despite being key inputs in the manufacturing process, raw materials have often been excluded from the cost function due to the lack of price data. A restricted cost function is used to improve the reliability of parameter estimates. Empirical results indicate that environmental regulations caused a 12 percent decline in the average annual rate of productivity growth over the period 1982–93.

scholarly journals The Impacts of Representing the Correlation of Errors in Radar Data Assimilation. Part I: Experiments with Simulated Background and Observation Estimates

2014 ◽  
Vol 142 (11) ◽  
pp. 3998-4016 ◽  
Author(s):  
Dominik Jacques ◽  
Isztar Zawadzki
Keyword(s):  
Data Assimilation ◽  
Cost Function ◽  
Radar Data ◽  
Spatial Correlations ◽  
Radar Observations ◽  
Lack Of Information ◽  
Data Thinning ◽  
The Cost ◽  
The Impact ◽  
Radar Data Assimilation

Abstract In radar data assimilation, statistically optimal analyses are sought by minimizing a cost function in which the variance and covariance of background and observation errors are correctly represented. Radar observations are particular in that they are often available at spatial resolution comparable to that of background estimates. Because of computational constraints and lack of information, it is impossible to perfectly represent the correlation of errors. In this study, the authors characterize the impact of such misrepresentations in an idealized framework where the spatial correlations of background and observation errors are each described by a homogeneous and isotropic exponential decay. Analyses obtained with perfect representation of correlations are compared to others obtained by neglecting correlations altogether. These two sets of analyses are examined from a theoretical and an experimental perspective. The authors show that if the spatial correlations of background and observation errors are similar, then neglecting the correlation of errors has a small impact on the quality of analyses. They suggest that the sampling noise, related to the precision with which analysis errors may be estimated, could be used as a criterion for determining when the correlations of errors may be omitted. Neglecting correlations altogether also yields better analyses than representing correlations for only one term in the cost function or through the use of data thinning. These results suggest that the computational costs of data assimilation could be reduced by neglecting the correlations of errors in areas where dense radar observations are available.

scholarly journals On a Reduction for a Class of Resource Allocation Problems

2021 ◽  
Author(s):  
Martijn H. H. Schoot Uiterkamp ◽  
Marco E. T. Gerards ◽  
Johann L. Hurink
Keyword(s):  
Resource Allocation ◽  
Cost Function ◽  
Objective Function ◽  
Allocation Problem ◽  
Resource Allocation Problem ◽  
Special Cases ◽  
Input Parameters ◽  
The Cost ◽  
The Impact ◽  
Shared Structure

In the resource allocation problem (RAP), the goal is to divide a given amount of a resource over a set of activities while minimizing the cost of this allocation and possibly satisfying constraints on allocations to subsets of the activities. Most solution approaches for the RAP and its extensions allow each activity to have its own cost function. However, in many applications, often the structure of the objective function is the same for each activity, and the difference between the cost functions lies in different parameter choices, such as, for example, the multiplicative factors. In this article, we introduce a new class of objective functions that captures a significant number of the objectives occurring in studied applications. These objectives are characterized by a shared structure of the cost function depending on two input parameters. We show that, given the two input parameters, there exists a solution to the RAP that is optimal for any choice of the shared structure. As a consequence, this problem reduces to the quadratic RAP, making available the vast amount of solution approaches and algorithms for the latter problem. We show the impact of our reduction result on several applications, and in particular, we improve the best-known worst-case complexity bound of two problems in vessel routing and processor scheduling from [Formula: see text] to [Formula: see text]. Summary of Contribution: The resource allocation problem (RAP) with submodular constraints and its special cases are classic problems in operations research. Because these problems are studied in many different scientific disciplines, many conceptual insights, structural properties, and solution approaches have been reinvented and rediscovered many times. The goal of this article is to reduce the amount of future reinventions and rediscoveries by bringing together these different perspectives on RAPs in a way that is accessible to researchers with different backgrounds. The article serves as an exposition on RAPs and on their wide applicability in many areas, including telecommunications, energy, and logistics. In particular, we provide tools and examples that can be used to formulate and solve problems in these areas as RAPs. To accomplish this, we make three concrete contributions. First, we provide a survey on algorithms and complexity results for RAPs and discuss several recent advances in these areas. Second, we show that many objectives for RAPs can be reduced to a (simpler) quadratic objective function, which makes available the extensive collection of fast and efficient algorithms for quadratic RAPs to solve these problems. Third, we discuss the impact that RAPs and the aforementioned reduction result can make in several application areas.

scholarly journals Impact of ozone observations on the structure of a tropical cyclone using coupled atmosphere–chemistry data assimilation

2015 ◽  
Vol 15 (8) ◽  
pp. 11573-11597
Author(s):  
S. Lim ◽  
S. K. Park ◽  
M. Zupanski
Keyword(s):  
Air Quality ◽  
Data Assimilation ◽  
Cost Function ◽  
Positive Impact ◽  
Eastern China ◽  
Chemical Information ◽  
Chemistry Data ◽  
Air Quality Forecast ◽  
The Cost ◽  
The Impact

Abstract. Since the air quality forecast is related to both chemistry and meteorology, the coupled atmosphere–chemistry data assimilation (DA) system is essential to air quality forecasting. Ozone (O3) plays an important role in chemical reactions and is usually assimilated in chemical DA. In tropical cyclones (TCs), O3 usually shows a lower concentration inside the eyewall and an elevated concentration around the eye, impacting atmospheric as well as chemical variables. To identify the impact of O3 observations on TC structure, including atmospheric and chemical information, we employed the Weather Research and Forecasting model coupled with Chemistry (WRF-Chem) with an ensemble-based DA algorithm – the maximum likelihood ensemble filter (MLEF). For a TC case that occurred over the East Asia, our results indicate that the ensemble forecast is reasonable, accompanied with larger background state uncertainty over the TC, and also over eastern China. Similarly, the assimilation of O3 observations impacts atmospheric and chemical variables near the TC and over eastern China. The strongest impact on air quality in the lower troposphere was over China, likely due to the pollution advection. In the vicinity of the TC, however, the strongest impact on chemical variables adjustment was at higher levels. The impact on atmospheric variables was similar in both over China and near the TC. The analysis results are validated using several measures that include the cost function, root-mean-squared error with respect to observations, and degrees of freedom for signal (DFS). All measures indicate a positive impact of DA on the analysis – the cost function and root mean square error have decreased by 16.9 and 8.87%, respectively. In particular, the DFS indicates a strong positive impact of observations in the TC area, with a weaker maximum over northeast China.

scholarly journals Ensemble data assimilation of total column ozone using a coupled meteorology–chemistry model and its impact on the structure of Typhoon Nabi (2005)

2015 ◽  
Vol 15 (17) ◽  
pp. 10019-10031 ◽  
Author(s):  
S. Lim ◽  
S. K. Park ◽  
M. Zupanski
Keyword(s):  
Data Assimilation ◽  
Cost Function ◽  
Positive Impact ◽  
Eastern China ◽  
Chemical Information ◽  
Elevated Concentration ◽  
Total Column Ozone ◽  
Rms Error ◽  
The Cost ◽  
The Impact

Abstract. Ozone (O3) plays an important role in chemical reactions and is usually incorporated in chemical data assimilation (DA). In tropical cyclones (TCs), O3 usually shows a lower concentration inside the eyewall and an elevated concentration around the eye, impacting meteorological as well as chemical variables. To identify the impact of O3 observations on TC structure, including meteorological and chemical information, we developed a coupled meteorology–chemistry DA system by employing the Weather Research and Forecasting model coupled with Chemistry (WRF-Chem) and an ensemble-based DA algorithm – the maximum likelihood ensemble filter (MLEF). For a TC case that occurred over East Asia, Typhoon Nabi (2005), our results indicate that the ensemble forecast is reasonable, accompanied with larger background state uncertainty over the TC, and also over eastern China. Similarly, the assimilation of O3 observations impacts meteorological and chemical variables near the TC and over eastern China. The strongest impact on air quality in the lower troposphere was over China, likely due to the pollution advection. In the vicinity of the TC, however, the strongest impact on chemical variables adjustment was at higher levels. The impact on meteorological variables was similar in both over China and near the TC. The analysis results are verified using several measures that include the cost function, root mean square (RMS) error with respect to observations, and degrees of freedom for signal (DFS). All measures indicate a positive impact of DA on the analysis – the cost function and RMS error have decreased by 16.9 and 8.87 %, respectively. In particular, the DFS indicates a strong positive impact of observations in the TC area, with a weaker maximum over northeastern China.

Landing Motion of a Legged Robot with Minimization of Impact Force and Joint Torque

2015 ◽  
Vol 27 (1) ◽  
pp. 32-40 ◽  
Author(s):  
Xianglong Wan ◽  
◽  
Takateru Urakubo ◽  
Yukio Tada
Keyword(s):  
Cost Function ◽  
Numerical Optimization ◽  
Impact Force ◽  
Contact Point ◽  
Joint Torque ◽  
Legged Robot ◽  
Joint Torques ◽  
Singular Configuration ◽  
The Cost ◽  
The Impact

<div class=""abs_img""><img src=""[disp_template_path]/JRM/abst-image/00270001/04.jpg"" width=""300"" />Optimal motion of a legged robot</div> This paper deals with an optimal landing motion of a four-link legged robot that minimizes the impact force at the contact point and the joint torques necessary during the motion. The cost function for optimization is given as the weighted sum of the impact force and the joint torques. The configuration of the robot that is close to a singular configuration is advantageous in minimizing the joint torques for a heavy torso, while the configuration where the leg is bent is advantageous in reducing the impact force. This is shown by numerical optimization results with different weights for the cost function and a theoretical analysis of a simplified model of the robot. </span>

scholarly journals ARRAY RADIATION PATTERN RECOVERY UNDER RANDOM ERRORS USING CLUSTERED LINEAR ARRAY

2022 ◽  
Vol 26 (1) ◽  
pp. 43-54
Author(s):  
Ahmed J. Abdulqader ◽  
◽  
Raad H. Thaher ◽  
Jafar R. Mohammed ◽  
◽  
...  
Keyword(s):  
Cost Function ◽  
Linear Array ◽  
Design Stage ◽  
Simulation Studies ◽  
Random Errors ◽  
Random Weight ◽  
Array Aperture ◽  
The Cost ◽  
The Impact ◽  
Entire Array

In practice, random errors in the excitations (amplitude and phase) of array elements cause undesired variations in the array patterns. In this paper, the clustered array elements with tapered amplitude excitations technique are introduced to reduce the impact of random weight errors and recover the desired patterns. The most beneficial feature of the suggested method is that it can be used in the design stage to count for any amplitude errors instantly. The cost function of the optimizer used is restricted to avoid any unwanted rises in sidelobe levels caused by unexpected perturbation errors. Furthermore, errors on element amplitude excitations are assumed to occur either randomly or sectionally (i.e., an error affecting only a subset of the array elements) through the entire array aperture. The validity of the proposed approach is entirely supported by simulation studies.

scholarly journals Application of the Levenberg-Marquardt Scheme to the MUSIC Algorithm for AOA Estimation

2013 ◽  
Vol 2013 ◽  
pp. 1-8 ◽  
Author(s):  
Joon-Ho Lee ◽  
Sung-Woo Cho ◽  
So-Hee Jeong
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Cost Function ◽  
Convergence Property ◽  
Signal Classification ◽  
Simultaneous Estimation ◽  
Music Algorithm ◽  
Multiple Signal Classification ◽  
Levenberg Marquardt ◽  
The Cost

We note that the cost function of the MUSIC (multiple signal classification) algorithm is quadratic in an array vector and that it can be expressed in a least squares form. Based on this observation, we present a rigorous Levenberg-Marquardt (LM) formulation of the MUSIC algorithm for simultaneous estimation of an azimuth and an elevation. We show a convergence property and compare the performance of the LM-based MUSIC algorithm with that of the standard MUSIC algorithm via Monte-Carlo simulation. We also compare the performance of the MUSIC algorithm with that of the Capon algorithm both for the standard implementation and for the LM-based implementation.

Sign in / Sign up

Export Citation Format

Share Document