Doctor of Philosophy (PhD)
First Advisor's Name
Ibrahim Nur Tansel
First Advisor's Committee Title
Second Advisor's Name
Jean H. Andrian
Second Advisor's Committee Title
Third Advisor's Name
Third Advisor's Committee Title
Fourth Advisor's Name
Fourth Advisor's Committee Title
Fifth Advisor's Name
Fifth Advisor's Committee Title
structural health monitoring method, manufacturing process monitoring, piezoelectric, laser scanning vibrometer, digital signal processor, surface response to excitation method
Date of Defense
During the past two decades, many researchers have developed methods for the detection of structural defects at the early stages to operate the aerospace vehicles safely and to reduce the operating costs. The Surface Response to Excitation (SuRE) method is one of these approaches developed at FIU to reduce the cost and size of the equipment. The SuRE method excites the surface at a series of frequencies and monitors the propagation characteristics of the generated waves. The amplitude of the waves reaching to any point on the surface varies with frequency; however, it remains consistent as long as the integrity and strain distribution on the part is consistent. These spectral characteristics change when cracks develop or the strain distribution changes. The SHM methods may be used for many applications, from the detection of loose screws to the monitoring of manufacturing operations.
A scanning laser vibrometer was used in this study to investigate the characteristics of the spectral changes at different points on the parts. The study started with detecting a load on a plate and estimating its location. The modifications on the part with manufacturing operations were detected and the Part-Based Manufacturing Process Performance Monitoring (PbPPM) method was developed. Hardware was prepared to demonstrate the feasibility of the proposed methods in real time.
Using low-cost piezoelectric elements and the non-contact scanning laser vibrometer successfully, the data was collected for the SuRE and PbPPM methods. Locational force, loose bolts and material loss could be easily detected by comparing the spectral characteristics of the arriving waves. On-line methods used fast computational methods for estimating the spectrum and detecting the changing operational conditions from sum of the squares of the variations. Neural networks classified the spectrums when the desktop – DSP combination was used. The results demonstrated the feasibility of the SuRE and PbPPM methods.
Fekrmandi, Hadi, "Development of New Structural Health Monitoring Techniques" (2015). FIU Electronic Theses and Dissertations. 1863.
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