Cross Correlation for Condition Monitoring of Variable Load and Speed Gearboxes

Jordan Mcbain,Markus Timusk

doi:10.1155/2014/543056

Abstract

The ability to identify incipient faults at an early stage in the operation of machinery has been demonstrated to provide substantial value to industry. These benefits for automated, in situ, and online monitoring of machinery, structures, and systems subject to varying operating conditions are difficult to achieve at present when they are run in operationally constrained environments that demand uninterrupted operation in this mode. This work focuses on developing a simple algorithm for this problem class; novelty detection is deployed on feature vectors generated from the cross correlation of vibration signals from sensors mounted on disparate locations in a power train. The behavior of these signals in a gearbox subject to varying load and speed is expected to remain in a commensurate state until a change in some physical aspect of the mechanical components, presumed to be indicative of gearbox failure. Cross correlation will be demonstrated to generate excellent classification results for a gearbox subject to independently changing load and speed. It eliminates the need to analyze the highly complex dynamics of this system; it generalizes well across untaught ranges of load and speed; it eliminates the need to identify and measure all predominant time-varying parameters; it is simple and computationally inexpensive.

Highlights

The dynamics of the vibrations generated by a gearbox subject to changing load and speed are complex and nonlinear
A common approach in detecting failure in sensors employs decision rules based on the cross correlation of their signals; in broaching this technique to variable-state machinery, the authors note that vibrations at disparate locations in a power train should be correlated to one another
The cross correlation signal between these vibration signals should remain commensurate until components of the train change—a state presumed indicative of faults

Summary

Introduction

The dynamics of the vibrations generated by a gearbox subject to changing load and speed are complex and nonlinear. The cross correlation technique should eliminate or mitigate all of these drawbacks This approach should provide an excellent means of failure detection in systems whose dynamics are too complex for traditional approaches and may extend well beyond the monitoring of variable load and speed gearboxes. To validate these conclusions, the necessary theoretical background is first explored including a review of cross correlation and how it is presently employed in this field as well as an overview of other existing approaches for solving this class of problems. The results are demonstrated to establish the flexibility of this simple approach

Background

Experimental Configuration

Classification Results

Sensitivity Analysis

Automation

Conclusions