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Criteria for Data Consistency Evaluation Prior to Modal Parameter Estimation

Patil, Vivek
http://rave.ohiolink.edu/etdc/view?acc_num=ucin1627667589352536

Abstract Details

2021, MS, University of Cincinnati, Engineering and Applied Science: Mechanical Engineering.
Experimental modal analysis (EMA), which is an integral part of vibration analysis, deals with finding the dynamic characteristics of a system, namely the natural frequencies, damping, and the corresponding mode shapes. One of the essential requirements to ensure the validity of results obtained in experimental modal analysis (EMA) is the consistency or regularity of the input-output measurements. The non-conformity of the measurement set to the constraints can result in deviation from the structural system's actual characteristics. A consistent data set meets the constraints of methods in modal parameter estimation (MPE) and uniformly portrays identical information. Many validation procedures in the form of principal component analysis (PCA), synthesis correlation coefficient, modal assurance criterion (MAC) exist as a post MPE check to verify the estimated model's quality and hence of the measured data. However, since these methods are employed post-MPE, there is a need for pre-MPE methods to check the validity of measurements beforehand and save any additional effort. This thesis work attempts to develop some of the data sanity checks over the collected experimental data before the modal estimation procedure is performed to ensure that the measurements are consistent with respect to each other and comply with experimental modal analysis assumptions. Building on the concept of reciprocity and driving point, MATLAB based tools are developed which identifies the driving points and performs consistency evaluation. A system equivalent reduction-expansion process (SEREP) based method is then explored, which checks each measurement's consistency to the entire data set. The calibration consistency is evaluated by calculating the frequency response assurance criterion (FRAC) and frequency response scale factor (FRSF) values between the cross-frequency response function measurements. The performance of these developed methods is then tested using analytical and experimental data sets. The results show that these techniques can precisely spot and identify various imperfect measurements and warn the user about the potential errors in the measurement set.
Randall Allemang, Ph.D. (Committee Chair)
Michael Mains, M.S. (Committee Member)
Allyn Phillips, Ph.D. (Committee Member)
98 p.
Mechanical Engineering
data consistency evaluation; SEREP; reciprocity; driving point evaluation; calibration; modal parameter estimation

Recommended Citations

Citations

  • Patil, V. (2021). Criteria for Data Consistency Evaluation Prior to Modal Parameter Estimation [Master's thesis, University of Cincinnati]. OhioLINK Electronic Theses and Dissertations Center. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1627667589352536

    APA Style (7th edition)

  • Patil, Vivek. Criteria for Data Consistency Evaluation Prior to Modal Parameter Estimation. 2021. University of Cincinnati, Master's thesis. OhioLINK Electronic Theses and Dissertations Center, http://rave.ohiolink.edu/etdc/view?acc_num=ucin1627667589352536.

    MLA Style (8th edition)

  • Patil, Vivek. "Criteria for Data Consistency Evaluation Prior to Modal Parameter Estimation." Master's thesis, University of Cincinnati, 2021. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1627667589352536

    Chicago Manual of Style (17th edition)

ucin1627667589352536
153
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This open access ETD is published by University of Cincinnati and OhioLINK.