Design and evaluation of multi-axis vibration shaker concepts

Elastic bodies exhibit structural resonance and mode shapes at various natural frequencies. In order to avoid structural overloads and equipment malfunctions, elastic systems, mechanical and/or electrical must be evaluated and tested for their performance over the entire frequency range of their operations. Shaker systems replicate the dynamic loads encountered in a field environment, and are used for vibration testing of elastic structures. Such vibration testing ensures the reliable performance of the final product; The objective of this research project, sponsored by the Army Research Lab (ARL), is the design and Finite Element evaluation of a new multi-axis shaker system, which will be used to test and improve the performance of mechanical and electronic components exposed to severe dynamic loaDing The new shaker system should meet three major design specifications. One, the system should have six degrees of freedom. Two, the system must work in a frequency range from 10 Hz to 3,000 Hz. Three, the system should be sturdy enough to carry payloads up to 25 lbs; In order to develop a sound design methodology, theoretical performance predictions based on finite element analysis were compared with experimental records from an existing smaller shaker system. Structural modifications aimed at improving shaker characteristics were implemented and the performance of the modified shaker was tested experimentally. The predicted and actual dynamics of both small shaker systems were found to agree well in terms of predicting resonant modes and frequency response spectra

Binary sequences with prescribed autocorrelations

Imperial Users onl

Digital Measurement of Partial Discharge

Various new measurement techniques have been developed for a high voltage phenomenon referred to as partial discharge. Partial discharge is a localized breakdown of the high voltage insulation system which is observed as low level, random emissions. Both electrical and acoustic emissions have been measured in underground power cables, solid cast power transformers and in lumped specimens. Typical problems complicating the measurements are the randomness of the emission, high levels of interference and extreme distortion of the signal by the propagation path. Various signal processing techniques have been adapted to the measurement of partial discharge. The techniques investigated are capable of reducing noise in the measurements and have provided orders of magnitude improvement in sensitivity over ordinary methods. Some of the techniques studied are capable of providing information about the location of the partial discharge site

Statistical Vibro-Acoustic Modelling of Nonlinear Systems with Applications in Vehicles

Designing quiet cars has become an important issue in the automotive industry, where passive and active noise control techniques can be employed to improve the acoustic comfort without compromising the vehicle performance. At the design stage of a noise control system, the estimation of the structure-borne sound pressure levels in the car cabin is a challenging problem, as uncertainties in a physical structural-acoustic system have an impact on the vehicle dynamics at high frequencies. Additionally, the response of the system can be affected by nonlinearities in the vibrations transmission path. Therefore, this research has been focused in developing computationally efficient vibro-acoustic models to predict the statistical structural-acoustic response of a system to random inputs, as well as analysing the degree of dependency of the response to nonlinear behaviour in the interface between the excitation and the structure. Key aspects of the impact that a nonlinear transmission path might have in the response of a statistical structural-acoustic system, were investigated from an equivalent damper model of the structural vibrating subsystem, under the assumption of weak acoustic coupling and the infinite plate theory. Numerical data in the time domain were generated from the simplified nonlinear system excited by random inputs with known power spectral density. The effects of nonlinearities were observed and quantified in the power spectral density of the response, as well as in the reduction of coherence between the input and output. Additionally, the Wiener theory in the frequency domain has been explored to estimate the degree of contribution of a nonlinearity of second order to the total response of the system. Finally, an extended hybrid Finite Element-Statistical Energy Analysis (FE-SEA) model was proposed to analyse the response of a deterministic-statistic structural-acoustic system, where the nonlinear transmission path is considered as a deterministic structure. The equations of an existing FE-SEA approach, based on the diffuse field reciprocity, have been generalised to include prescribed displacements as inputs, in addition to external forces. The nonlinear analysis with the FE-SEA approach has been carried out by adopting the concept of equivalent linearisation of the deterministic dynamic stiffness matrix, and the capability of the approach has been validated against experimental data from a physical nonlinear structural-acoustic setup

An enhanced predictive hierarchical power management framework for islanded microgrids

This paper proposes an enhanced three-layer predictive hierarchical power management framework for secure and economic operation of islanded microgrids. The tertiary control, guaranteeing the microgrid economic operation, is built upon the semi-definite programming-based AC optimal power flow model, which periodically sends power references to secondary control. To mitigate uncertainties arising from renewable generations and loads, a centralized linear model predictive control (MPC) controller is proposed and implemented for secondary control. The MPC controller can effectively regulate the microgrid system frequency by closely tracking reference signals from the tertiary controller with low computational complexity. Droop-based primary controllers are implemented to coordinate with the secondary MPC controller to balance the system in real time. Both synchronous generators (SGs) and solar photovoltaics (PVs) are simulated in the microgrid power management framework. A unified linear input-state estimator (ULISE) is proposed for SG state variable estimation and control anomaly detection due to compromised cyber-physical system components, etc. Simulation results demonstrated that SG states can be accurately estimated, while inconsistency in control signals can be effectively detected for an enhanced MPC. Furthermore, comparing with conventional proportional-integral (PI) control, the proposed hierarchical power management scheme exhibits superior frequency regulation capability whilst maintaining lower system operating costs

Developing an Enhanced Adaptive Antenna Beamforming Algorithm for Telecommunication Applications

As a key enabler for advanced wireless communication technologies, smart antennas have become an intense field of study. Smart antennas use adaptive beamforming algorithms which allow the antenna system to search for specific signals even in a background of noise and interference. Beamforming is a signal processing technique used to shape the antenna array pattern according to prescribed criteria. In this thesis, a comparative study is presented for various adaptive antenna beamforming algorithms. Least mean square (LMS), normalized least mean square (NLMS), recursive least square (RLS), and sample matrix inversion (SMI) algorithms are studied and analyzed. The study also considers some possible adaptive filter combinations and variations, such as: LMS with SMI weights initialization, and combined NLMS filters with a variable mixing parameter. Furthermore, a new adaptive variable step-size normalized least mean square (VSS-NLMS) algorithm is proposed. Sparse adaptive algorithms, are also studied and analyzed, and two-channel estimations sparse algorithms are applied to an adaptive beamformer, namely: proportionate normalized least-mean-square (PNLMS), and lp norm PNLMS (LP-PNLMS) algorithms. Moreover, a variable step size has been applied to both of these algorithms for improved performance. These algorithms are simulated for antenna arrays with different geometries and sizes, and results are discussed in terms of their convergence speed, max side lobe level (SLL), null depths, steady-state error, and sensitivity to noise. Simulation results confirm the superiority of the proposed VSS-NLMS algorithms over the standard NLMS without the need of using combined filters. Results also show an improved performance for the sparse algorithms after applying the proposed variable step size