Author
Sebastian Oberst
Other affiliations: Commonwealth Scientific and Industrial Research Organisation, Technische Universität München, University of New South Wales ...read more
Bio: Sebastian Oberst is an academic researcher from University of Technology, Sydney. The author has contributed to research in topics: Brake & Disc brake. The author has an hindex of 15, co-authored 81 publications receiving 929 citations. Previous affiliations of Sebastian Oberst include Commonwealth Scientific and Industrial Research Organisation & Technische Universität München.
Topics: Brake, Disc brake, Nonlinear system, Vibration, Recurrence plot
Papers published on a yearly basis
Papers
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TL;DR: In this paper, the authors analyzed the brake squeal data obtained from a full brake system on a noise dynamometer with nonlinear analysis techniques and showed that lower dimensional attractors are isolated and quantified by dynamic invariants such as correlation dimension estimates or Lyapunov exponents.
117 citations
TL;DR: In this article, the correlation analysis between the time-averaged friction coefficient and peak sound pressure data is performed by applying a semblance analysis and a joint recurrence quantification analysis.
113 citations
TL;DR: In this article, the authors developed guidelines for numerical vibration and acoustic analysis of brake squeal using models of simplified brake systems with friction contact by considering the selection of appropriate elements, contact and mesh; extraction of surface velocities via forced response; and calculation of the acoustic response itself.
70 citations
TL;DR: In this paper, the authors applied the complex eigenvalue analysis, the direct steady-state analysis and the transient nonlinear time domain analysis to an isotropic pad-on-disc finite element model representing a simple model of a brake system.
66 citations
TL;DR: In this paper, a meta-atom with Willis coupling was proposed, which is much simpler and less prone to thermo-viscous losses than previously reported structures, and the authors performed two-dimensional experiments to measure the strong Willis coupling.
Abstract: Acoustic metamaterials are structures with exotic acoustic properties, with promising applications in acoustic beam steering, focusing, impedance matching, absorption and isolation. Recent work has shown that the efficiency of many acoustic metamaterials can be enhanced by controlling an additional parameter known as Willis coupling, which is analogous to bianisotropy in electromagnetic metamaterials. The magnitude of Willis coupling in a passive acoustic meta-atom has been shown theoretically to have an upper limit, however the feasibility of reaching this limit has not been experimentally investigated. Here we introduce a meta-atom with Willis coupling which closely approaches this theoretical limit, that is much simpler and less prone to thermo-viscous losses than previously reported structures. We perform two-dimensional experiments to measure the strong Willis coupling, supported by numerical calculations. Our meta-atom geometry is readily modeled analytically, enabling the strength of Willis coupling and its peak frequency to be easily controlled.
52 citations
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01 Mar 1995
TL;DR: This thesis applies neural network feature selection techniques to multivariate time series data to improve prediction of a target time series and results indicate that the Stochastics and RSI indicators result in better prediction results than the moving averages.
Abstract: : This thesis applies neural network feature selection techniques to multivariate time series data to improve prediction of a target time series. Two approaches to feature selection are used. First, a subset enumeration method is used to determine which financial indicators are most useful for aiding in prediction of the S&P 500 futures daily price. The candidate indicators evaluated include RSI, Stochastics and several moving averages. Results indicate that the Stochastics and RSI indicators result in better prediction results than the moving averages. The second approach to feature selection is calculation of individual saliency metrics. A new decision boundary-based individual saliency metric, and a classifier independent saliency metric are developed and tested. Ruck's saliency metric, the decision boundary based saliency metric, and the classifier independent saliency metric are compared for a data set consisting of the RSI and Stochastics indicators as well as delayed closing price values. The decision based metric and the Ruck metric results are similar, but the classifier independent metric agrees with neither of the other metrics. The nine most salient features, determined by the decision boundary based metric, are used to train a neural network and the results are presented and compared to other published results. (AN)
1,545 citations
1,196 citations
TL;DR: In this article, the authors propose a Cybernetics or Control and Communication in the Animal and the Machine (CACM) for controlling and communicating with animals and the machines.
Abstract: (1963). Cybernetics, or Control and Communication in the Animal and the Machine. Technometrics: Vol. 5, No. 1, pp. 128-130.
934 citations