Comprehensive Joint Time-Frequency Analysis toward Condition Based Maintenance Regimes for Electrical and Mechanical Components

Based upon a framework of time-frequency analysis, a path towards systematic and comprehensive implementation of condition based maintenance (CBM), or maintenance only upon evidence of need, is outlined for both electrical and mechanical systems. Specifically, metrics are proposed for helicopter drivetrain systems and electrical cable. Using principles of time-frequency analysis, metrics for health assessment in non-destructive and non-invasive tests provide a basis for diagnostic and prognostic analysis. A form of Rényi entropy or Rényi information based mutual information measure is proposed for comparing vibration data from multiple sensors toward the creation of new condition indicators for use in rotorcraft. Using similar methodology, a process for non-invasively assessing the health of low voltage instrumentation cables and medium to high voltage feeder and transmission cables is proposed by way of Joint Time-frequency Domain Reflectometry (JTFDR). From this starting point of derived health indicators for separate systems, research is proposed to facilitate the practical implementation of such technology. A new concept of non-parametric signal detection and classification technique is proposed using mutual information measures in the time-frequency domain. The time-frequency based self and mutual information is defined in terms of the cross time-frequency distribution. Based on time-frequency mutual information theory, this paper presents applications of the proposed technique to real-world vibration data obtained from a dedicated condition based maintenance experimental testbed. Baseline, unbalanced, and misaligned experimental settings of helicopter drive train bearings and shafts are quantitatively distinguished by the proposed techniques. With unbalance quantifiable by variance in the in-phase mutual information and misalignment quantifiable by variance in the quadrature mutual information developed and presented herein, machine health classification can be accomplished by use of statistical bounding regions. Electrical, reflectometry-based methods of health evaluation are proposed and will be compared to existing methods of high voltage test such as high voltage withstand and partial discharge, which can be destructive when applied to cables. Surface wave insulation health assessment is proposed as a means of connecting to a cable under test in a noninvasive manner. Also, toward a new standard of smart grid active condition based maintenance strategies, joint time-frequency domain reflectometry is proposed for monitoring the health of high temperature superconducting (HTS) cable. Conditions of localized impedance fluctuation due to coolant leak have been simulated with the reflectometry assessment properly detecting minute changes in cable impedance and indicating location and severity of faulted segments.