Gaozheng Zhao¹, Changchao Liu¹, Lingyu Sun¹, Ning Yang², Lei Zhang¹, Mingshun Jiang¹, Lei Jia¹, Qingmei Sui^1,*

Structural Durability & Health Monitoring, Vol.16, No.1, pp. 81-96, 2022, DOI:10.32604/sdhm.2022.016905

Abstract Fatigue crack prediction is a critical aspect of prognostics and health management research. The particle filter algorithm based on Lamb wave is a potential tool to solve the nonlinear and non-Gaussian problems on fatigue growth, and it is widely used to predict the state of fatigue crack. This paper proposes a method of lamb wave-based early fatigue microcrack prediction with the aid of particle filters. With this method, which the changes in signal characteristics under different fatigue crack lengths are analyzed, and the state- and observation-equations of crack extension are established. Furthermore, an experiment is conducted to verify the feasibility… More >

Saqlain Abbas^1,2,*, Zulkarnain Abbas³, Xiaotong Tu⁴, Yanping Zhu¹

Journal on Artificial Intelligence, Vol.3, No.3, pp. 97-113, 2021, DOI:10.32604/jai.2021.023020

Abstract The performance and reliability of structural components are greatly influenced by the presence of any abnormality in them. To this purpose, structural health monitoring (SHM) is recognized as a necessary tool to ensure the safety precautions and efficiency of both mechanical and civil infrastructures. Till now, most of the previous work has emphasized the functioning of several SHM techniques and systematic changes in SHM execution. However, there exist insufficient data in the literature regarding the patent-based technological developments in the SHM research domain which might be a useful source of detailed information for worldwide research institutes. To address this research… More >

Yihua Wang¹, Zhenhuan Zhou¹, Hao Xu^1,*, Shuai Li², Zhanjun Wu¹

Structural Durability & Health Monitoring, Vol.15, No.2, pp. 85-101, 2021, DOI:10.32604/sdhm.2021.014256

Abstract For practical engineering structures, it is usually difficult to measure external load distribution in a direct manner, which makes inverse load identification important. Specifically, load identification is a typical inverse problem, for which the models (e.g., response matrix) are often ill-posed, resulting in degraded accuracy and impaired noise immunity of load identification. This study aims at identifying external loads in a stiffened plate structure, through comparing the effectiveness of different methods for parameter selection in regulation problems, including the Generalized Cross Validation (GCV) method, the Ordinary Cross Validation method and the truncated singular value decomposition method. With demonstrated high accuracy,… More >

Ahmed Silik^1,2, Mohammad Noori^3,*, Wael A. Altabey^1,4, Ramin Ghiasi¹, Zhishen Wu¹

Structural Durability & Health Monitoring, Vol.15, No.1, pp. 1-22, 2021, DOI:10.32604/sdhm.2021.012751

Abstract A critical problem facing data collection in structural health monitoring, for instance via sensor networks, is how to extract the main components and useful features for damage detection. A structural dynamic measurement is more often a complex time-varying process and therefore, is prone to dynamic changes in time-frequency contents. To extract the signal components and capture the useful features associated with damage from such non-stationary signals, a technique that combines the time and frequency analysis and shows the signal evolution in both time and frequency is required. Wavelet analyses have proven to be a viable and effective tool in this… More >

Xueping Fan^*, Guanghong Yang, Zhipeng Shang, Xiaoxiong Zhao, Yuefei Liu^*

Structural Durability & Health Monitoring, Vol.15, No.1, pp. 69-83, 2021, DOI:10.32604/sdhm.2021.011922

Abstract This article presented a new data fusion approach for reasonably predicting dynamic serviceability reliability of the long-span bridge girder. Firstly, multivariate Bayesian dynamic linear model (MBDLM) considering dynamic correlation among the multiple variables is provided to predict dynamic extreme deflections; secondly, with the proposed MBDLM, the dynamic correlation coefficients between any two performance functions can be predicted; finally, based on MBDLM and Gaussian copula technique, a new data fusion method is given to predict the serviceability reliability of the long-span bridge girder, and the monitoring extreme deflection data from an actual bridge is provided to illustrated the feasibility and application… More >

Saqlain Abbas^1,2,*, Fucai Li¹, Zulkarnain Abbas^3,4, Taufeeq Ur Rehman Abbasi⁵, Xiaotong Tu⁶, Riffat Asim Pasha⁷

Sound & Vibration, Vol.55, No.1, pp. 1-18, 2021, DOI:10.32604/sv.2021.013754

Abstract Structural health monitoring (SHM) is recognized as an efficient tool to interpret the reliability of a wide variety of infrastructures. To identify the structural abnormality by utilizing the electromechanical coupling property of piezoelectric transducers, the electromechanical impedance (EMI) approach is preferred. However, in real-time SHM applications, the monitored structure is exposed to several varying environmental and operating conditions (EOCs). The previous study has recognized the temperature variations as one of the serious EOCs that affect the optimal performance of the damage inspection process. In this framework, an experimental setup is developed in current research to identify the presence of fatigue… More >

Amirabbas Haidarpour, Kong Fah Tee^*

Structural Durability & Health Monitoring, Vol.14, No.1, pp. 1-17, 2020, DOI:10.32604/sdhm.2020.08792

Abstract This paper provides a model updating approach to detect, locate, and characterize damage in structural and mechanical systems by examining changes in measured vibration responses. Research in vibration-based damage identification has been rapidly expanding over the last few decades. The basic idea behind this technology is that modal parameters (notably frequencies, mode shapes, and modal damping) are functions of the physical properties of the structure (mass, damping, and stiffness). Therefore, changes in the physical properties will cause changes in the modal properties which could be obtained by structural health monitoring (SHM). Updating is a process fraught with numerical difficulties. These… More >

Meiling Zhuang^1,2,3, Changqing Miao^1,2,*, Rongfeng Chen^1,2

Structural Durability & Health Monitoring, Vol.14, No.1, pp. 51-79, 2020, DOI:10.32604/sdhm.2020.07663

Abstract Taizhou Yangtze River Bridge as a long-span suspension bridge, the finite element model (FEM) of it is established using the ANSYS Software. The beam4 element is used to simulate the main beam to establish the “spine beam” model of the Taizhou Yangtze River Bridge. The calculated low-order vibration mode frequency of the FEM is in good agreement with the completion test results. The model can simulate the overall dynamic response of the bridge. Based on the vehicle load survey, the Monte Carlo method is applied to simulate the traffic load flow. Then the overall dynamic response analysis of FEM is… More >

Amafabia, Daerefa-a Mitsheal¹, Montalvão, Diogo², David-West, Opukuro¹, Haritos, George¹

Structural Durability & Health Monitoring, Vol.11, No.2, pp. 91-147, 2017, DOI:10.3970/sdhm.2017.011.091

Abstract Structural Health Monitoring (SHM) is the process of collecting, interpreting and analysing data from structures in order to determine its health status and the remaining life span. Composite materials have been extensively use in recent years in several industries with the aim at reducing the total weight of structures while improving their mechanical properties. However, composite materials are prone to develop damage when subjected to low to medium impacts (i.e. 1-10 m/s and 11-30 m/s respectively). Hence, the need to use SHM techniques to detect damage at the incipient initiation in composite materials is of high importance. Despite the availability… More >

Clyde K Coelho, Cristobal Hiche, Aditi Chattopadhyay

Structural Durability & Health Monitoring, Vol.7, No.1&2, pp. 65-82, 2011, DOI:10.3970/sdhm.2011.007.065

Abstract Low velocity impacts on composite plates often create subsurface damage that is difficult to diagnose. Fiber Bragg grating (FBG) sensors can be used to detect subsurface damage in composite laminates due to low velocity impact. This paper focuses on the prediction of impact loading in composite structures as a function of time using a support vector regression approach. A time delay embedding feature extraction scheme is used since it can characterize the dynamics of the impact using the sensor signals. The novelty of this approach is that it can be applied on complex geometries and does not require a dense… More >