Document Type



Doctor of Philosophy (PhD)


Mechanical Engineering

First Advisor's Name

Ibrahim Nur Tansel

First Advisor's Committee Title

Committee Chair

Second Advisor's Name

Jean H. Andrian

Second Advisor's Committee Title

Committee Member

Third Advisor's Name

Yiding Cao

Third Advisor's Committee Title

Committee Member

Fourth Advisor's Name

Bilal El-Zahab

Fourth Advisor's Committee Title

Committee Member

Fifth Advisor's Name

Igor Tsukanov

Fifth Advisor's Committee Title

Committee Member


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.





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