Title: Fatigue studies using Piezoelectric sensors 

Summary: Defects in real mechanical, industrial and aerospace structures frequently have complex shapes. Most real structures are typically prone to multiple fatigue cracks and their propagation can be monitored by observing changes in the structural stiffness resulting from strength reduction as a function of the number of loading cycles. In addition, strain variations on the structural surface can be captured using digital equipments. The present work monitors two specimens (AISI 4340 steel) with electrode sparked hemispherical defects on their surfaces. Multiple-cracks emanating from these defects, under fatigue cyclic loading were monitored using piezoelectric wafer based electromechanical impedance (EMI) technique, and digital image correlation (DIC) system. EMI technique uses signature comparison of healthy and damaged state of the structure to depict the occurrence of crack and its growth. Images of DIC system captures initial sightings of surface hair-line cracks from the corners of machined defects and their propagation till merging. Thus, a signature analysis based technique such as EMI and image processing technology such as DIC were found to complement each other to expedite the prediction of early crack and their appearance on the surface. 

Furthermore, our Research consistently focuses on the monitoring of fatigue cracks and structural damage in various metallic structures, particularly using advanced non-destructive evaluation techniques.

The core methodologies explored are the piezoelectric transducer (PZT) based electromechanical impedance (EMI) technique and the Digital Image Correlation (DIC) system. The studies demonstrate how these techniques are applied to:

• Monitor fatigue crack propagation originating from complex defects (e.g., hemispherical, double surface defects) in materials like AISI 4340 steel.

• Utilize the EMI technique to detect crack occurrence and growth by comparing structural impedance signatures in healthy versus damaged states.

• Employ the DIC system to capture the initial appearance of hairline surface cracks and track their propagation, including instances where multiple cracks interact and merge.

• Showcase the complementary nature of EMI (signature analysis) and DIC (image processing), where they enhance each other's capabilities for expedited prediction of early crack initiation and surface manifestation.

• Assess the efficiency of EMI for comprehensive load and damage assessment, even along the thickness of PZT transducers in structural monitoring applications, as demonstrated in studies involving welded beams.

Overall, the research highlights the robustness and synergy of EMI and DIC as effective tools for real-time, in-situ fatigue damage monitoring in mechanical, industrial, and aerospace structures.

Articles:

Annamdas V. G. M, Chew Y , Pang J. H. L , Hoh H. J, Zhou K and Song B (2014) "Fatigue growth analysis of interacting and merging surface defects using PZT transducer based impedance method and digital image correlation system.", Journal of Nondestructive Evaluation, Volume 33(3), pp 413-426, DOI: 10.1007/s10921-014-0237-9. Publisher: Springer US.

Annamdas V. G. M, Pang J. H. L, Chew Y, Hoh H J, Zhou K and Song B (2014) "Fatigue Monitoring of double surface defects using PZT based Electromechanical Impedance and Digital image correlation methods ", Advanced Materials. Research Vols. 891-892, pp 551-556, Trans Tech Publications, Switzerland doi:10.4028/www.scientific.net/AMR.891-

892.551 (selected from 11th international congress on fatigue) [ISBN:1662-8985]

Annamdas V. G. M, Lim S .I, Pang J. H. L and Soh C. K (2014) "Monitoring of fatigue in welded beams using piezoelectric transducer based impedance technique", Journal of Nondestructive Evaluation, Volume 33, Issue 1, pp 124-140, DOI:10.1007/s10921-013-0209-5 Publisher: Springer US,

Annamdas V. G. M, Pang J. H. L, Zhou K and Song B (2013) "Efficiency of Electromechanical Impedance for Load and Damage Assessment along Thickness of PZT Transducers in Structural Monitoring" Journal of Intelligent Material systems and structures, Volume 24, Issue 16, pp. 2008-2022, Doi:10.1177/1045389X13488252

People : Annamdas V. G. M., Chew Y., Pang J. H. L., Hoh H. J., Zhou K., Song B., Lim S. I., Soh C. K., Mr. Chew Youxiang, Mr. Chee Ming Feng Kevin, Mr. Tan Yong Quan, Fan, Sun, Xueni, Zhang.