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Random Error in Strain Calculation using Regularized Polynomial Smoothing (RPS) and Point-wise Least Squares (PLS) in Digital Image Correlation

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OPTICS AND LASERS IN ENGINEERING 2021年 142卷 106590-106590页

作者： Li, Xin Fang, Gang Zhao, Jiaqing Zhang, Zhengming Sun, Libin Wang, Haitao Wu, Xinxin Tsinghua Univ Collaborat Innovat Ctr Adv Nucl Energy Technol Inst Nucl & New Energy Technol Key Lab Adv Reactor Engn & SafetyMinist Educ Beijing 100084 Peoples R China Tsinghua Univ Dept Mech Engn Beijing 100084 Peoples R China

The strain error analysis is greatly concerned recently as digital image correlation (DIC) is used to measure the heterogeneous deformation. This paper focuses on the estimation of random error and under-matched error caused by two strain calculation methods, i.e. the point-wise least squares (PLS) and the regularized polynomial smoothing method (RPS). Two assumptions are put forward on the noise error of the calculated displacement that are: a) it is pure random error without bias and b) in each strain window, it is the independent Gaussian white noise with zero-mean. Based on the assumptions, the random error of displacement and strain is estimated, and the under-matched error of displacement and strain is theoretically analyzed by the aid of Laplacian operator. These two error solutions are verified by some stimulated experiments. Then for the typical kernel function of 3rd order polynomial, a self-adaptive algorithm minimizing the total error is proposed to choose the optimal parameters, i.e. window size and parameter... Experiments show that when the original displacement noise conforms to the assumptions strictly, 1) the estimated random error and under-matched error agrees very well with the experimental value, 2) the self-adaptive algorithm can give the optimal parameters in restoring the displacement and strain field, and 3) the estimation of random error and under-matched error is affected by DIC noise greatly, and it is better to use low-pass Gaussian filter before utilizing self-adaptive algorithm.

关键词： Digital image correlation Displacement smoothing Strain random error self-adaptive algorithm

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self-adaptive MRPBIL-DE for 6D robot multiobjective trajectory planning

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EXPERT SYSTEMS WITH APPLICATIONS 2019年 136卷 133-144页

作者： Bureerat, Sujin Pholdee, Nantiwat Radpukdee, Thana Jaroenapibal, Papot Khon Kaen Univ Fac Engn Sustainable & Infrastruct Res & Dev Ctr Dept Mech Engn Khon Kaen 40002 Thailand Khon Kaen Univ Fac Engn Dept Ind Engn Khon Kaen 40002 Thailand

This work presents self-adaptive multiobjective real-code population-based incremental learning hybridised with differential evolution (MRPBIL-DE) for solving a 6D robot trajectory planning multiobjective optimisation problem. The objective functions are assigned to minimise travelling time and minimise maximum jerk taking place during motion while the constraints are velocity, acceleration and jerk constraints. A five order polynomial function is used to represent a motion equation while the motion path is divided into two sub-paths;from initial to intermediate positions and from intermediate to final positions. The optimiser is used to find a set of design variables including joint positions, velocities and accelerations at intermediate positions, moving time from the initial to intermediate positions, and that from the intermediate to final positions. Several multiobjective meta-heuristics (MOMHs) along with the proposed algorithm are used to solve the trajectory optimisation problem of robot manipulators while their performances are investigated. The results indicated that the proposed algorithm is effective and efficient for multiobjective robot trajectory planning optimisation problem. The results obtained from such a method are set as the baseline for further study of robot trajectory planning optimisation. (C) 2019 Elsevier Ltd. All rights reserved.

关键词： Multiobjective meta-heuristic algorithm Robot trajectory planning multiobjective Optimisation self-adaptive algorithm Time-jerk minimisation

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self-adaptive Neighbor Discovery in Wireless Sensor Networks with Sectored-Antennas

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COMPUTER STANDARDS & INTERFACES 2020年 70卷 103427-000页

作者： Mir, Zeeshan Hameed Ko, Young-Bae Higher Coll Technol Fac Comp Informat Sci POB 4114 Fujairah U Arab Emirates Ajou Univ Dept Software & Comp Engn POB 16499 Suwon South Korea

Integration of sectored antenna in wireless networks improves network performance through increased network capacity and extended transmission range. However, incorporating sectored antenna makes the trivial process of discovering neighbors even more challenging and complicated. Moreover, due to the duty-cycled nature of Wireless Sensor Networks (WSNs), self-adaptive and distributed neighbor discovery mechanisms are highly sought-after. In this paper, we present a Neighbor Discovery with Sectored Antenna (NDSA) protocol for WSNs with the sectored antenna. NDSA distinguish itself from other protocols in four distinct ways. Firstly, the introduction of super-frame like structure to support the duty-cycled operation of WSNs. Secondly, the protocol adapts its operation according to the network dynamics by leveraging the in-network information. Thirdly, a cooperative mechanism through which nodes utilize the information about their discovered neighbors to avoid an excessive exchange of control messages. Finally, handling the channel access details to discover neighbors faster with fewer message collisions. Through a comprehensive simulation-based study, the results show that the proposed protocol outperformed the random and serialized approaches to neighbor discovery in terms of discovery latency while significantly minimizing the communication overhead.

关键词： Neighbor discovery Sectored-Antenna Wireless Sensor Network MAC protocol self-adaptive algorithm

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An evolutionary discretized Lambert approach for optimal long-range rendezvous considering impulse limit

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AEROSPACE SCIENCE AND TECHNOLOGY 2019年 94卷 105400-000页

作者： Shirazi, Abolfazl Ceberio, Josu Lozano, Jose A. BCAM Bilbao 48009 Spain Univ Basque Country UPV EHU Donostia San Sebastian 20018 Spain

In this paper, an approach is presented for finding the optimal long-range space rendezvous in terms of fuel and time, considering limited impulse. In this approach, the Lambert problem is expanded towards a discretized multi-impulse transfer. Taking advantage of an analytical form of multi-impulse transfer, a feasible solution that satisfies the impulse limit is calculated. Next, the obtained feasible solution is utilized as a seed for generating individuals for a hybrid self-adaptive evolutionary algorithm to minimize the total time, without violating the impulse limit while keeping the overall fuel mass the same as or less than the one associated with the analytical solution. The algorithm eliminates similar individuals and regenerates them based on a combination of Gaussian and uniform distribution of solutions from the fuel-optimal region during the optimization process. Other enhancements are also applied to the algorithm to make it auto-tuned and robust to the initial and final orbits as well as the impulse limit. Several types of the proposed algorithm are tested considering varieties of rendezvous missions. Results reveal that the approach can successfully reduce the overall transfer time in the multi-impulse transfers while minimizing the fuel mass without violating the impulse limit. Furthermore, the proposed algorithm has superior performance over standard evolutionary algorithms in terms of convergence and optimality. (C) 2019 Elsevier Masson SAS. All rights reserved.

关键词： Discretized Lambert problem Long-range rendezvous self-adaptive algorithm Impulse limit Evolutionary approach Optimal transfer

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Improving the Performance of Actor-Based Programs Using a New Actor to Thread Association Technique 1

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18th IFIP WG 6.1 International Conference on Distributed Applications and Interoperable Systems (DAIS) held as Part of the 13th International Federated Conference on Distributed Computing Techniques (DisCoTec)

作者： Rahemi, Fahimeh Khamespanah, Ehsan Khosravi, Ramtin Univ Tehran Sch Elect & Comp Engn Tehran Iran Reykjavik Univ Sch Comp Sci Reykjavik Iceland

ISBN: (数字)9783319937670

ISBN: (纸本)9783319937670;9783319937663

Finding the most efficient policy for the association of objects with threads is one of the main challenges in the deployment of concurrently executing objects, including actors. For the case of actor-based programs, libraries, frameworks, and languages provide fine tuning facilities for associating actors with threads. In practice, programmers use the default policy for the initial deployment of actors and the default policy is replaced with some other policies considering runtime behaviors of actors. Although this ad-hoc approach is widely used by programmers, it is tedious and time-consuming for large-scale applications. To reduce the time-consumption of the ad-hoc approach, a set of heuristics is proposed with the aim of balancing computations of actors across threads. This technique results in performance improvement;however, it relies on the static analysis of source codes and actors' behaviors, ends in the inappropriate configuration of systems in distributed environments. In this paper, we illustrate conditions that the proposed heuristics do not work well and propose a new approach based on the runtime profile of actors for better association of actors with threads. We also show how this approach can be extended to a fully self-adaptive approach and illustrated its applicability using a set of case studies.

关键词： Actors Thread association self-adaptive algorithm Runtime analysis

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Design of nuclear radiation level gauge based on normalized LMS filtering correction

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Journal of Measurement Science and Instrumentation 2019年第2期10卷 103-108页

作者： WU Zuo-peng WANG Xiao-peng WU Xu School of Electronic and Information Engineering Lanzhou Jiaotong UniversityLanzhou 730070China

In the measurement of liquid level in industrial site environment,noise interference can affect the measurement *** order to improve the measurement accuracy of liquid level in the viscous state,a nuclear radiation level measurement system based on the least mean square(LMS)filtering correction method is *** system uses STM32F103 as the control core and adopts HART bus HT1200M chip for remote signal transmission and *** adaptive LMS algorithm can be used for more accurate filtering,calculating iterative weight vector,updating weighted coefficient,effectively removing system measurement noise and improving the measurement *** results show that the nuclear radiation level gauge based on normalized LMS can correct the measurement system accuracy in adaptive rules,improve the measurement accuracy to meet the requirements of industrial field environment for liquid level measurement and enhance the industrial automation control degree.

关键词： least mean square(LMS) nuclear radiation method self-adaptive algorithm weighted coefficient updating level gauge

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self-adaptive Histogram Equalization Image Enhancement Based on Canny Operator

Self-adaptive Histogram Equalization Image Enhancement Based...

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Annual Conference of the Chinese-Society-for-Optical-Engineering (CSOE) on Applied Optics and Photonics China (AOPC) - Optical Sensing and Imaging Technology and Applications

作者： Du, Ya-ni Zhou, Hui-xin Ma, Zhen-hua Yu, Yue Qin, Han-lin Tan, Wei Xidian Univ Sch Phys & Optoelect Engn Xian 710071 Shaanxi Peoples R China

ISBN: (数字)9781510614062

ISBN: (纸本)9781510614062;9781510614055

Traditional histogram equalization method always leads to the gray level reduction and loss of details. In this paper, an efficient and self-adaptive image enhancement algorithm is proposed based on canny operator and histogram equalization. The canny operator is used to extract the detail information which could be preserved in the enhanced image. The shortcomings of histogram equalization can thus be overcome. The experimental results with infrared images show that our method can preserve more image details and improve the image contrast and suppress noise effectively, which indicates a better performance for infrared image enhancement.

关键词： Histogram equalization image enhancement canny operator self-adaptive algorithm

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A Two-stage Codebook Design Based on Beam Perturbation for Massive MIMO Systems 31

A Two-stage Codebook Design Based on Beam Perturbation for M...

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31st IEEE International Conference on Advanced Information Networking and Applications (IEEE AINA)

作者： Yuan, Jiangwei Li, Xiaohui Pu, Wenjuan Yuan, Ruiyang Xidian Univ State Key Lab Integrated Serv Networks Xian 710071 Shaanxi Peoples R China Xidian Univ Collaborat Innovat Ctr Informat Sensing & Underst Xian 710071 Shaanxi Peoples R China

ISBN: (纸本)9781509062317

Aiming at reducing the overhead of codebook design and improving the performance of massive multiple-input multiple-output (MIMO) systems, a novel two-stage codebook design is presented in this paper. Using the householder-transform, which perturbs the first-codebook beam direction, the second-codebook can be easily obtained. In addition, the second-codebook maintains the properties of the first-codebook and further simplifies the modality of perturbation. Then we introduce a self-adaptive algorithm for codebook selection to maximize the system performance. The self-adaptive algorithm dynamically chooses the optimal codeword of a two-stage codebook then feeds back one of the codewords to the transmitter, and it reduces feedback overhead and avoids the inaccurate channel matching caused by only using the second-codebook. Specifically, the algorithm increases the acceleration of codebook selection and reduces the complexity and blindness. The simulation results suggest that the proposed perturbation-based codebook design can improve the system bit error rate (BER) performance and can be applied to the case of multi-stream.

关键词： massive MIMO system first-codebook second-codebook self-adaptive algorithm

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self-adaptive algorithms for proximal split feasibility problems and strong convergence analysis

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FIXED POINT THEORY AND APPLICATIONS 2015年第1期2015卷 1-13页

作者： Yao, Yonghong Yao, Zhangsong Abdou, Afrah A. N. Cho, Yeol Je King Abdulaziz Univ Dept Math Jeddah 21589 Saudi Arabia Tianjin Polytech Univ Dept Math Tianjin 300387 Peoples R China Nanjing Xiaozhuang Univ Sch Informat Engn Nanjing 211171 Jiangsu Peoples R China Gyeongsang Natl Univ Dept Math Educ Chinju 660701 South Korea Gyeongsang Natl Univ RINS Chinju 660701 South Korea

The purpose of the paper is to study the proximal split feasibility problems. For solving the problems, we present new self-adaptive algorithms with the regularization technique. By using these algorithms, we give som... 详细信息

关键词： proximal split feasibility problem self-adaptive algorithm fixed point method strong convergence

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Digital image correlation with self-adaptive scheme for interpolation bias reduction

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MEASUREMENT SCIENCE AND TECHNOLOGY 2017年第7期28卷 075008-075008页

作者： Tu, Peihan Guangdong Univ Technol Sch Automat Guangzhou 510006 Guangdong Peoples R China

In digital image correlation (DIC), the systematic error caused by intensity interpolation at sub-pixel positions, namely the overall interpolation bias, includes both interpolation bias and noise-induced bias. The overall interpolation bias is especially significant when the noise level is high or the image contrast is low. There is a pressing need to reduce the overall interpolation bias to improve the accuracy of DIC. However, existing approaches such as using a low-pass filter or a high-order interpolation require manually selected algorithm parameters, and cannot reduce the bias automatically. It is known that the overall interpolation bias is highly correlated with image gradient (and thus the contrast of the speckle image). This provides an opportunity to reduce the bias simply by adjusting the gradients. Inspired by the image enhancement technique which is used to alter image gradients (thus image contrast) by nonlinearly transforming its intensities (RGB, gray-value, etc), a DIC algorithm called the gray-level adaptive DIC (GA-DIC), based on a new correlation criterion with an additional adjustable parameter which controls the gradients, is proposed to reduce the overall interpolation bias. Both numerical and real experiments are applied to verify the feasibility and effectiveness of the GA-DIC. The results show that the proposed algorithm can reduce the overall interpolation bias without empirically selecting algorithm hyperparameters. Its effect is more significant in cases with higher image noise and poorer image quality.

关键词： digital image correlation systematic errors self-adaptive algorithm interpolation bias noise-induced bias

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