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Krishna Kumar Maurya^*, Anupam Rawat, Rama Shanker
Structural Durability & Health Monitoring, Vol.16, No.2, pp. 97-128, 2022, DOI:10.32604/sdhm.2022.015732
Abstract Structural health monitoring (SHM) is a process for determination of presence, location, severity of damages and remaining life of the infrastructures. SHM is widely applied in aerospace, mechanical and civil engineering systems to assess the conditions of structures to improve the operation, safety, serviceability and reliability, respectively. There are various SHM techniques for monitoring the health of structures such as global response based and local techniques. Damages occur in the structures due to its inability to withstand intended design loadings, physical environment and chemical environment. Therefore, damage identification is necessary to improve the durability of the structures for protection against… More >

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ARTICLE

Yongfeng Fang^1,3, Kong Fah Tee^2,*
Structural Durability & Health Monitoring, Vol.16, No.2, pp. 129-143, 2022, DOI:10.32604/sdhm.2022.020301
Abstract In this article, structural probabilistic and non-probabilistic reliability have been evaluated and compared under big data condition. Firstly, the big data is collected via structural monitoring and analysis. Big data is classified into different types according to the regularities of the distribution of data. The different stresses which have been subjected by the structure are used in this paper. Secondly, the structural interval reliability and probabilistic prediction models are established by using the stress-strength interference theory under big data of random loads after the stresses and structural strength are comprehensively considered. Structural reliability is computed by using various stress types,… More >

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ARTICLE

Guansi Liu^1,2, Keqin Ding^2,*, Hui Jin^1,*, Fangxiong Tang², Li Chen²
Structural Durability & Health Monitoring, Vol.16, No.2, pp. 145-161, 2022, DOI:10.32604/sdhm.2022.022241
Abstract With the construction of automated docks, health monitoring technology as a parallel safety assurance technology for unmanned hoisting machinery has become a hot spot in the development of the industry. Hoisting machinery has a huge structure and numerous welded joints. The complexity and nonlinearity of the welded structure itself makes the structural failure parts random and difficult to arrange for monitoring sensors. In order to solve the problem of effectiveness and stability of the sensor arrangement method for monitoring the structure of hoisting machinery. Using the global and local search capabilities enhanced by the complementary search mechanism, a structural vibration… More >

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Yisu Xi¹, Binkai Shi², Wei Xu^1,3,*, Jing Ge⁴, Huaxin Zhu⁵, Dragoslav Sumarac^6,7
Structural Durability & Health Monitoring, Vol.16, No.2, pp. 163-177, 2022, DOI:10.32604/sdhm.2022.022082
Abstract With the aid of non-contact measurements of vibrating surfaces through laser scanning, operating deflection shapes (ODSs) with high spatial resolutions can be used to graphically characterize damage in plane structures. Although numerous damage identification approaches relying on laser-measured ODSs have been developed for plate-type structures, they cannot be directly applied to circular cylinders due to the gap between equations of motions of plates and circular cylinders. To fill this gap, a novel approach is proposed in this study for damage identification of circular cylinders. Damage-induced discontinuities of the derivatives of ODSs can be used to graphically manifest the occurrence of… More >

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Kelong Huang, Jie Yan, Lei Zhang^*, Faye Zhang, Mingshun Jiang, Qingmei Sui
Structural Durability & Health Monitoring, Vol.16, No.2, pp. 179-194, 2022, DOI: 10.32604/sdhm.2022.018202
Abstract A structural displacement field reconstruction method is proposed to aim at the problems of deformation monitoring and displacement field reconstruction of flexible plate-like structures in the aerospace field. This method combines the deep neural network model of the cross-layer connection structure with the fiber grating sensor network. This paper first introduces the principle of strain detection of fiber grating sensor, studies the mapping relationship between strain and displacement, and proposes a strain-displacement conversion model based on an improved neural network. Then the intelligent structure deformation monitoring system is built. By controlling the stepping distance of the motor to produce different… More >

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