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Article
Publication date: 19 September 2016

Ziqiang Cui, Qi Wang, Qian Xue, Wenru Fan, Lingling Zhang, Zhang Cao, Benyuan Sun, Huaxiang Wang and Wuqiang Yang

Electrical capacitance tomography (ECT) and electrical resistance tomography (ERT) are promising techniques for multiphase flow measurement due to their high speed, low…

Abstract

Purpose

Electrical capacitance tomography (ECT) and electrical resistance tomography (ERT) are promising techniques for multiphase flow measurement due to their high speed, low cost, non-invasive and visualization features. There are two major difficulties in image reconstruction for ECT and ERT: the “soft-field”effect, and the ill-posedness of the inverse problem, which includes two problems: under-determined problem and the solution is not stable, i.e. is very sensitive to measurement errors and noise. This paper aims to summarize and evaluate various reconstruction algorithms which have been studied and developed in the word for many years and to provide reference for further research and application.

Design/methodology/approach

In the past 10 years, various image reconstruction algorithms have been developed to deal with these problems, including in the field of industrial multi-phase flow measurement and biological medical diagnosis.

Findings

This paper reviews existing image reconstruction algorithms and the new algorithms proposed by the authors for electrical capacitance tomography and electrical resistance tomography in multi-phase flow measurement and biological medical diagnosis.

Originality/value

The authors systematically summarize and evaluate various reconstruction algorithms which have been studied and developed in the word for many years and to provide valuable reference for practical applications.

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Article
Publication date: 19 June 2017

Qi Wang, Pengcheng Zhang, Jianming Wang, Qingliang Chen, Zhijie Lian, Xiuyan Li, Yukuan Sun, Xiaojie Duan, Ziqiang Cui, Benyuan Sun and Huaxiang Wang

Electrical impedance tomography (EIT) is a technique for reconstructing the conductivity distribution by injecting currents at the boundary of a subject and measuring the…

Abstract

Purpose

Electrical impedance tomography (EIT) is a technique for reconstructing the conductivity distribution by injecting currents at the boundary of a subject and measuring the resulting changes in voltage. Image reconstruction for EIT is a nonlinear problem. A generalized inverse operator is usually ill-posed and ill-conditioned. Therefore, the solutions for EIT are not unique and highly sensitive to the measurement noise.

Design/methodology/approach

This paper develops a novel image reconstruction algorithm for EIT based on patch-based sparse representation. The sparsifying dictionary optimization and image reconstruction are performed alternately. Two patch-based sparsity, namely, square-patch sparsity and column-patch sparsity, are discussed and compared with the global sparsity.

Findings

Both simulation and experimental results indicate that the patch based sparsity method can improve the quality of image reconstruction and tolerate a relatively high level of noise in the measured voltages.

Originality/value

EIT image is reconstructed based on patch-based sparse representation. Square-patch sparsity and column-patch sparsity are proposed and compared. Sparse dictionary optimization and image reconstruction are performed alternately. The new method tolerates a relatively high level of noise in measured voltages.

Details

Sensor Review, vol. 37 no. 3
Type: Research Article
ISSN: 0260-2288

Keywords

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Article
Publication date: 4 March 2020

Ziqiang Han, Lei Wang and Jianwen Wei

This study examines the recovery of households after disasters from the sustainable livelihood approach (SLA) perspective.

Abstract

Purpose

This study examines the recovery of households after disasters from the sustainable livelihood approach (SLA) perspective.

Design/methodology/approach

This study analyzes the perception of recovery by using a longitudinal household survey data set collected from a Chinese county devastated by the 2008 Wenchuan earthquake. The analysis compares the changes of livelihood capitals (financial, natural, physical, social, human) between 2012 and 2009 and recovery perception.

Findings

The results demonstrate that both the current status of financial, natural, and social capital and the changes of the capitals between 2009 and 2012 are positively correlated with the perceived level of recovery. The associations between the current status and the change of physical capital and recovery perception are insignificant. In contrast, with a greater change of human capital between 2009 and 2012, participants have a lower perception of recovery.

Originality/value

By investigating a longitudinal data, this study indicates that (1) household recovery should be considered as multidimensional, (2) the SLA could be a feasible framework to measure recovery, and (3) individual's recovery perception is dependent on the various dimensions of recovery measures.

Details

Disaster Prevention and Management: An International Journal, vol. 30 no. 2
Type: Research Article
ISSN: 0965-3562

Keywords

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Article
Publication date: 17 July 2019

Yong-Hua Li, Ziqiang Sheng, Pengpeng Zhi and Dongming Li

How to get a lighter and stronger anti-rolling torsion bar has become a barrier for the development of high-speed railway vehicles. The purpose of this paper is to realize…

Abstract

Purpose

How to get a lighter and stronger anti-rolling torsion bar has become a barrier for the development of high-speed railway vehicles. The purpose of this paper is to realize the multi-objective optimization of an anti-rolling torsion bar with a Modified Non-dominated Sorting Genetic Algorithm III (MNSGA-III), which aims to obtain a better design scheme of an anti-rolling torsion bar device.

Design/methodology/approach

First, the Non-dominated Sorting Genetic Algorithm III (NSGA-III) uses a simulated binary crossover (SBX) operator and a polynomial mutation operator, while the MNSGA-III algorithm proposed in this paper introduces an arithmetic crossover and an adaptive mutation operator to change the crossover and mutate operator in NSGA-III. Second, two algorithms are tested by ZDT3, ZDT4 functions. Both algorithms set the same population size and evolutionary generation, and then compare the results of NSGA-III and MNSGA-III. Finally, MNSGA-III is applied to the multi-objective model of an anti-rolling torsion bar which is established by taking the mass and stiffness of the torsion bar as the optimization object. After that, it obtains the Pareto solution set by solving the multi-objective model with MNSGA-III. The only optimal solution selected from the Pareto solution set is compared with the traditional design scheme of an anti-rolling torsion bar.

Findings

The MNSGA-III converges faster than NSGA-III. Besides, MNSGA-III has better diversity of Pareto solutions than NSGA-III and is closer to the ideal Pareto frontier. Comparing with the results before the optimization, it shows that the volume of the anti-rolling torsion bar reduces by 1.6 percent and the stiffness increases by 3.3 percent. The optimized data verifies the effectiveness of this method proposed in this paper.

Originality/value

The simulated binary crossover operator and polynomial mutation operator of NSGA-III are changed into an arithmetic crossover operator and an adaptive mutation operator, respectively, which improves the optimization performance of the algorithm.

Details

International Journal of Structural Integrity, vol. 12 no. 1
Type: Research Article
ISSN: 1757-9864

Keywords

Content available
Article
Publication date: 22 October 2019

Li Xuemei, Yun Cao, Junjie Wang, Yaoguo Dang and Yin Kedong

Research on grey systems is becoming more sophisticated, and grey relational and prediction analyses are receiving close review worldwide. Particularly, the application of…

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Abstract

Purpose

Research on grey systems is becoming more sophisticated, and grey relational and prediction analyses are receiving close review worldwide. Particularly, the application of grey systems in marine economics is gaining importance. The purpose of this paper is to summarize and review literature on grey models, providing new directions in their application in the marine economy.

Design/methodology/approach

This paper organized seminal studies on grey systems published by Chinese core journal database – CNKI, Web of Science and Elsevier from 1982 to 2018. After searching the aforementioned database for the said duration, the authors used the CiteSpace visualization tools to analyze them.

Findings

The authors sorted the studies according to their countries/regions, institutions, keywords and categories using the CiteSpace tool; analyzed current research characteristics on grey models; and discussed their possible applications in marine businesses, economy, scientific research and education, marine environment and disasters. Finally, the authors pointed out the development trend of grey models.

Originality/value

Although researches are combining grey theory with fractals, neural networks, fuzzy theory and other methods, the applications, in terms of scope, have still not met the demand. With the increasingly in-depth research in marine economics and management, international marine economic research has entered a new period of development. Grey theory will certainly attract scholars’ attention, and its role in marine economy and management will gain considerable significance.

Details

Marine Economics and Management, vol. 2 no. 2
Type: Research Article
ISSN: 2516-158X

Keywords

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