Literature DB >> 32041159

Influence of the PZT Sensor Array Configuration on Lamb Wave Tomography Imaging with the RAPID Algorithm for Hole and Crack Detection.

Songlai Wang1, Wanrong Wu1, Yiping Shen2, Yi Liu3, Shuai Jiang2.   

Abstract

The tomography technique is an effective way to quantitatively evaluate damage from reconstruction imaging in structure health monitoring (SHM). The reconstruction algorithm for the probabilistic inspection of damage (RAPID) algorithm based on the signal difference coefficient (SDC) feature is a promising approach due to its superior performance. This paper focuses on the influence of different patterns of PZT (Lead Zirconate Titanate) sensor array configurations, i.e., the circular, square, and parallel array, on reconstruction image qualities for evaluating hole and crack damage. Variable shape parameters are applied to account for the unequal damage distances of different actuator-sensor pairs. Considering the directionality scattering fields of cracks, the angular scattering pattern of the SDC values are studied by simulation. The SDC variations for different groups of sensing paths at the same actuator are applied to predict the crack orientation. An improved RAPID algorithm is proposed by defining an additional SDC value of 1 in the path along the predicted crack orientation, which is determined by the point of the actuator causing the minimal SDC variation and the center point of the initial reconstruction image of the crack. The results show that the improved RAPID algorithm is effective for the evaluation of crack damage. Reconstruction image qualities with three PZT sensor array configurations for both holes and cracks are compared. The research is significant for selecting the PZT sensor array configuration in SHM.

Entities:  

Keywords:  PZT sensor array configuration; RAPID algorithm; crack orientation; tomography image quality

Year:  2020        PMID: 32041159     DOI: 10.3390/s20030860

Source DB:  PubMed          Journal:  Sensors (Basel)        ISSN: 1424-8220            Impact factor:   3.576


  4 in total

1.  Damage Localization in Composite Plates Using Wavelet Transform and 2-D Convolutional Neural Networks.

Authors:  Guillermo Azuara; Mariano Ruiz; Eduardo Barrera
Journal:  Sensors (Basel)       Date:  2021-08-30       Impact factor: 3.847

2.  Application of Sensor Path Weighting RAPID Algorithm on Pitting Corrosion Monitoring of Aluminum Plate.

Authors:  Duo Xu; Weifang Zhang; Lu Han; Xuerong Liu; Weiwei Hu
Journal:  Materials (Basel)       Date:  2022-05-30       Impact factor: 3.748

3.  Damage Classification Using Supervised Self-Organizing Maps in Structural Health Monitoring.

Authors:  Gilbert A Angulo-Saucedo; Jersson X Leon-Medina; Wilman Alonso Pineda-Muñoz; Miguel Angel Torres-Arredondo; Diego A Tibaduiza
Journal:  Sensors (Basel)       Date:  2022-02-15       Impact factor: 3.576

4.  Assessment of Damage in Composite Pressure Vessels Using Guided Waves.

Authors:  Vittorio Memmolo; Leandro Maio; Fabrizio Ricci
Journal:  Sensors (Basel)       Date:  2022-07-11       Impact factor: 3.847

  4 in total

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