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International Telemetering Conference Proceedings / October 30-November 02, 1995 / Riviera Hotel, Las Vegas, Nevada / Measurement of vibration and acoustic signals at various locations in the launch vehicle is important to establish the vibration and acoustic environment encountered by the launch vehicle during flight. The vibration and acoustic signals are wideband and require very large telemetry bandwidth if directly transmitted to ground. The DSP based Signal Processing Unit is designed to measure and analyse acoustic and vibration signals onboard the launch vehicle and transmit the computed spectrum to ground through centralised baseband telemetry system. The analysis techniques employed are power spectral density (PSD) computations using Fast Fourier Transform (FFT) and 1/3rd octave analysis using digital Infinite Impulse Response (IIR) filters. The programmability of all analysis parameters is achieved using EEPROM. This paper discusses the details of measurement and analysis techniques, design philosophy, tools used and implementation schemes. The paper also presents the performance results of flight models.

The thesis addresses the problem of structural damage detection using inverse sensitivity based methods. The focus here is on characterization with regard to identification, location, and, quantification of structural damage in linear time invariant (LTI) systems, using vibration data. The study encompasses both analytical and experimental methods. A suite of five algorithms for damage detection, namely, inverse eigensensitivity method that is refined to account for cross orthogonality between distinct modes, damping dependent eigensolutions, and sensitivity with respect to points of antiresonance and minima, inverse FRF method that includes refinements in terms of inclusion of second order sensitivity, response function method (RFM) based on first order Taylor’s expansion, a newly proposed inverse sensitivity method based on singular values of FRF matrix, and method based on response time histories, are presented. The scope of these methods vis-à-vis the need for model reduction, ability to deal with incomplete data, ill-posedness of governing equations and the need for regularization, sensitivity with respect to measurement noise, ability to identify damping characteristics, the highest and lowest magnitudes of changes in structural properties, and the ability to characterize systems with closely spaced natural frequencies that the methods can detect are discussed. The performance of proposed procedures is illustrated by considering a five degrees-of-freedom (dof) mass-spring-dashpot system and subsequently applied on three archetypal structural systems using analytical and experimental methods. In the examples presented, factors, such as, completeness of measured data in time and frequency, nature (proportional/non-proportional) and magnitude of damping, levels of changes in structural properties, modal truncations, number of governing equations for system parameters, and efficacy of regularization techniques are investigated. The study also highlights the difficulties in implementing the damage detection algorithm based on real life noisy vibration data. A comparative study on the suitability of each of these methods in locating and quantifying of different damage scenarios has been reported. A critical review of performance of the various methods is presented. The thesis concludes with a summary on the contributions made and also deliberates on future avenues for research and development in this area of research.