Graph-theoretic analysis of discrete-phase-space states for condition change detection and quantification of information

摘要

Data collected from devices and human condition may be used to forewarn of critical events such as machine/structural failure or events from brain/heart wave data stroke. By monitoring the data, and determining what values are indicative of a failure forewarning, one can provide adequate notice of the impending failure in order to take preventive measures. This disclosure teaches a computer-based method to convert dynamical numeric data representing physical objects (unstructured data) into discrete-phase-space states, and hence into a graph (structured data) for extraction of condition change.

主权项

1. A machine-readable non-transitory data storage device having a series of preprogrammed code which, when loaded on a computer apparatus, causes the computing apparatus to:
receive a stream of time-serial numeric data representing a physical object; convert the data to structured data; and analyze the structured network with graph-theoretic analysis to detect condition change in the time-serial numerical data and to quantify changes among phase-space dynamical states of the structured data, wherein the analysis of the structured network comprises:
partitioning the received data to define the plurality of phase-space dynamical states, for each phase-space dynamical state, each state represented as a node in a mathematical graph and each state-to-state transition represented as a link in the mathematical graph;computing the dissimilarity measures between the mathematical graphs of the phase-space dynamical states;establishing, using the phase-state dynamical states, a baseline state and obtaining average dissimilarity between each contiguous phase-space dynamical state and the baseline state;classifying dynamical change based on a plurality of successive occurrences of phase-space dynamical states above a threshold; andtraining the classification of dynamical change to minimize prediction distance.