Date of Award


Degree Type


Degree Name

Master of Engineering Science


Mechanical and Materials Engineering


Dr S.F. Asokanthan


This thesis is mainly concerned with the application of Stochastic Subspace Identification algorithms to extract dynamic characteristics of smaller-scale structural elements. It also emphasizes the development of a suitable identification procedure for extracting modal characteristics of insect’s sensory systems, which are typically of the order of microns in length. The traditional way of extracting modal parameters by forming a transfer function is not practical for micron-scale structures owing to the practical limitations in applying a quantifiable input to excite such structures. Output-only identification and Stochastic Subspace Identification (SSI) methods attempt to extract modal parameters from the output response data and hence eliminate the need for quantifying the input. The input in this case is assumed as a broad band white noise and is assumed to arise from ambient sources. A program, Modal Analysis on Civil Engineering Structures (MACEC), is used as a modal analysis tool for extracting the modal parameters of macro as well as micron­ size structures. It provides a Graphical User Interface (GUI) for performing output-only system identification within the MATLAB programming environment. MACEC offers system identification via two different methods: SSI and Peak Picking Method (PPM) and provides animated visualization of mode shapes. As part of this thesis, a detailed verification for using this program for analysing micron-size structures is performed. An experiment is carried out on a meter long beam where data is collected using Laser Doppler Vibrometry (LDV) and mode shapes and modal frequencies are identified via MACEC. These results are also verified from the data collected using conventional system identification methods. The same methodology is then employed on further experiments which are carried out on submillimeter size beams. The data in this case is collected using Microscope Scanning Vibrometer (MSV). Frequencies are identified using SSI via MACEC. Based on the procedure used for submillimeter size beams, a preliminary experiment is carried out on micron-size mechanoreceptor hair on the cercus of a cricket and modal frequencies are identified using SSI via MACEC. The test procedures and methodology developed in this case is envisaged further work to be performed in the area of dynamic characterization of insect’s sensory systems.



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