Home / Advanced Search

  • Title/Keywords

  • Author/Affliations

  • Journal

  • Article Type

  • Start Year

  • End Year

Update SearchingClear
  • Articles
  • Online
Search Results (16)
  • Open Access

    ARTICLE

    Fatigue Crack Detection in Steel Plates Using Guided Waves and an Energy-Based Imaging Approach

    Mingyu Lu1,*, Kaige Zhu1, Qiang Wang2

    Structural Durability & Health Monitoring, Vol.15, No.3, pp. 207-225, 2021, DOI:10.32604/sdhm.2021.017720

    Abstract The increasing use of ultrasonic guided waves (GWs) has been shown to have great potential for the detection of fatigue cracks and non-fatigue type damages in metallic structures. This paper reports on a study demonstrating an energy-based damage imaging approach in which signal characteristics identified through relative time differences by fatigue crack (RTD/f) through different sensor paths are used to estimate the location of fatigue crack in steel plates based on GWs generated by an active piezoceramic transducer (PZT) network. The propagation of GWs in the original 10 mm-thick plate was complicated due to its… More >

  • Open Access

    ARTICLE

    Experimental Study of Effect of Temperature Variations on the Impedance Signature of PZT Sensors for Fatigue Crack Detection

    Saqlain Abbas1,2,*, Fucai Li1, Zulkarnain Abbas3,4, 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… More >

  • Open Access

    ARTICLE

    An Investigation into Active Strain Transfer Analysis in a Piezoceramic Sensor System for Structural Health Monitoring Using the Dual Boundary Element Method

    S.P.L. Leme1, M.H. Aliabadi2, L.M. Bezerra1, P.W. Partridge1

    Structural Durability & Health Monitoring, Vol.3, No.3, pp. 121-132, 2007, DOI:10.3970/sdhm.2007.003.121

    Abstract The coupled electromechanical behaviour of a thin piezoceramic sensor bonded to a stiffened panel subjected to membrane mechanical loadings is examined. The sensor is characterised by an electrostatic line model bonded to a damaged panel modelled by the dual boundary element method. Numerical results obtained demonstrate that the proposed method is capable of modelling changes in the signal output due to presence of cracks. Also presented is a numerical model for detecting fatigue crack growth in a stiffened panel using piezoceramic sensors. More >

  • Open Access

    ARTICLE

    Crack Detection and Localization on Wind Turbine Blade Using Machine Learning Algorithms: A Data Mining Approach

    A. Joshuva1, V. Sugumaran2

    Structural Durability & Health Monitoring, Vol.13, No.2, pp. 181-203, 2019, DOI:10.32604/sdhm.2019.00287

    Abstract Wind turbine blades are generally manufactured using fiber type material because of their cost effectiveness and light weight property however, blade get damaged due to wind gusts, bad weather conditions, unpredictable aerodynamic forces, lightning strikes and gravitational loads which causes crack on the surface of wind turbine blade. It is very much essential to identify the damage on blade before it crashes catastrophically which might possibly destroy the complete wind turbine. In this paper, a fifteen tree classification based machine learning algorithms were modelled for identifying and detecting the crack on wind turbine blades. The More >

  • Open Access

    ARTICLE

    Detection of Graphene Cracks By Electromagnetic Induction, Insensitive to Doping Level

    Taeshik Yoon1,†, Sumin Kang1,†, Tae Yeob Kang1, Taek-Soo Kim1,2,*

    CMES-Computer Modeling in Engineering & Sciences, Vol.120, No.2, pp. 351-361, 2019, DOI:10.32604/cmes.2019.06672

    Abstract Detection of cracks is a great concern in production and operation processes of graphene based devices to ensure uniform quality. Here, we show a detection method for graphene cracks by electromagnetic induction. The time varying magnetic field leads to induced voltage signals on graphene, and the signals are detected by a voltmeter. The measured level of induced voltage is correlated with the number of cracks in graphene positively. The correlation is attributed to the increasing inductive characteristic of defective graphene, and it is verified by electromagnetic simulation and radio frequency analysis. Furthermore, we demonstrate that More >

  • Open Access

    ARTICLE

    Matrix Crack Detection in Composite Plate with Spatially Random Material Properties using Fractal Dimension

    K. Umesh1, R. Ganguli1

    CMC-Computers, Materials & Continua, Vol.41, No.3, pp. 215-240, 2014, DOI:10.3970/cmc.2014.041.215

    Abstract Fractal dimension based damage detection method is investigated for a composite plate with random material properties. Composite material shows spatially varying random material properties because of complex manufacturing processes. Matrix cracks are considered as damage in the composite plate. Such cracks are often seen as the initial damage mechanism in composites under fatigue loading and also occur due to low velocity impact. Static deflection of the cantilevered composite plate with uniform loading is calculated using the finite element method. Damage detection is carried out based on sliding window fractal dimension operator using the static deflection. More >

Displaying 11-20 on page 2 of 16. Per Page