Hardware implementation of auto-mutual information function for condition monitoring

TL;DR

This paper demonstrates a hardware implementation of the auto-mutual information function for condition monitoring of electrical motors, using FPGA technology to detect motor aging through vibration data analysis.

Contribution

It introduces a novel hardware implementation of the auto-mutual information function for motor condition monitoring, validated with experimental vibration data.

Findings

Hardware implementation is feasible and effective.

Auto-mutual information can detect motor aging.

Attractor reconstruction from vibration data is complex.

Abstract

This study is aimed at showing applicability of mutual information, namely auto-mutual information function for condition monitoring in electrical motors, through age detection in accelerated motor aging. Vibration data collected in artificial induction motor experiment is used for verification of both the original auto-mutual information function algorithm and its hardware implementation in Verilog, produced from an initial version made with Matlab HDL (Hardware Description Language) Coder. A conceptual model for industry and education based on a field programmable logic array development board is developed and demonstrated on the auto-mutual information function example, while suggesting other applications as well. It has also been shown that attractor reconstruction for the vibration data cannot be straightforward.