Jeffrey S. Mayer

Pattern identification in dynamical systems via symbolic time series analysis

This paper presents symbolic time series analysis (STSA) of multi-dimensional measurement data for pattern identification in dynamical systems. The proposed methodology is built upon concepts derived from Information Theory and Automata Theory. The objective is not merely to classify the time series patterns but also to identify the variations therein. To achieve this goal, a symbol alphabet is constructed from raw data through partitioning of the data space. The maximum entropy method of partitioning is extended to multi-dimensional space. The resulting symbol sequences, generated from time series data, are used to model the dynamical information as finite state automata and the patterns are represented by the stationary state probability distributions. A novel procedure for determining the structure of the finite state automata, based on entropy rate, is introduced. The diversity among the observed patterns is quantified by a suitable measure. The efficacy of the STSA technique for pattern identification is demonstrated via laboratory experimentation on nonlinear systems.

Electric-Field-Assisted Directed Assembly of Transition Metal Dichalcogenide Monolayer Sheets

Directed assembly of two-dimensional (2D) layered materials, such as transition metal dichalcogenides, holds great promise for large-scale electronic and optoelectronic applications. Here, we demonstrate controlled placement of solution-suspended monolayer tungsten disulfide (WS2) sheets on a substrate using electric-field-assisted assembly. Micrometer-sized triangular WS2 monolayers are selectively positioned on a lithographically defined interdigitated guiding electrode structure using the dielectrophoretic force induced on the sheets in a nonuniform field. Triangular sheets with sizes comparable to the interelectrode gap assemble with an observed preferential orientation where one side of the triangle spans across the electrode gap. This orientation of the sheets relative to the guiding electrode is confirmed to be the lowest energy configuration using semianalytical calculations. Nearly all sheets assemble without observable physical deformation, and postassembly photoluminescence and Raman spectroscopy characterization of the monolayers reveal that they retain their as-grown crystalline quality. These results show that the field-assisted assembly process may be used for large-area bottom-up integration of 2D monolayer materials for nanodevice applications.

Early detection of voltage imbalances in three-phase induction motors

Online monitoring of induction motor health is of increased interest, as the industrial processes that depend on the motors become more complex and as performance to cost ratio of monitoring technology (e.g. sensors, microprocessors) has increased dramatically. Much efforts have been directed towards developing methods that use conventional signal processing and pattern classification techniques. This paper proposes a novel technique for early detection of stator voltage imbalances in three-phase induction motors, which is built upon the theories of wavelet transforms and symbolic time series analysis.

Broken Rotor Bar detection using Symbolic Wavelet Analysis

Rotor bar faults have been of interest for the past several decades as being one of the major causes of failure in induction machines. This paper provides a powerful yet simple methodology for the detection of these faults. The methodology utilizes a combination of machine modeling concepts along with wavelet and symbolic dynamic analysis to ensure early detection with a low false alarm rate

Automated technique for determination and stability analysis of periodic steady state for DC-DC converters

A general technique is developed for the finding and stability analysis of periodic state-space orbits in switched DC power converter systems. The technique is exact for circuits with ideal components and is easily programmed, which makes it a useful tool for automated circuit analysis and design. A computer procedure is created in MATLAB that can find and analyze periodic orbits for systems of arbitrary complexity with given state-space matrices and inputs. An example of such analysis is presented for a buck converter circuit with first order controller.

Symbolic identification of dynamical systems: Theory and experimental validation

This paper proposes a syntactic method of system identification in dynamical systems. The underlying concept involves abstraction of a qualitative description of the dynamical system by state-space embedding of the output data-stream and discretization of the resultant pseudo-state and input spaces. The task of system identification is achieved through grammatical inference techniques, and the deviation of the plant output from the nominal estimated language generates a measure of anomaly in the system. This system identification technique has been experimentally validated for detection of anomalous behavior on a laboratory apparatus of a permanent magnet synchronous motor (PMSM) undergoing gradual demagnetization.

Automated state-space simulation of small-scale and vehicular electric power systems

The design of increasingly complex electromechanical systems containing AC machine-power converter subsystems requires efficient methods of simulating the machine and power converter dynamics. While circuit-oriented simulations can be used for this application, state-space methods offer greater flexibility in modeling the nonelectrical components and in the choice of integration algorithms and software. State-space methods have the disadvantage, however, of requiring special attention when interconnecting individual component models to represent an overall system. In this paper, a state-space power converter model that can be readily connected with other component model and which is computationally efficient is obtained using a combination of circuit (graph) theory and reference frame transformations. An alternator-rectifier that is part of a pulse-power system is used to demonstrate the model and its implementation. In addition, an automated tool which handles the task of assembling a system simulation from a library of component models is described.

Reduced power consumption in AMLCDs through dynamic power management

— A strategy is presented for reducing the power consumed by the fluorescent backlight in an active-matrix liquid-crystal display (AMLCD). This strategy centers on dynamically minimizing the backlight intensity, based on the content of the images being displayed. Implementation of this dynamic power-management strategy requires very little additional logic in the video controller.