Shape principal component analysis as a targetless photogrammetric technique for condition monitoring of rotating machines

Abstract

Rotating machines are widely used in engineering for applications which include power generation and machine propulsion systems. These machines have to be accurately monitored and maintained to avoid system failures. Vibration analysis, which involves the use of contact and non-contact measurement techniques to capture vibrational data indicative of the condition of a machine, is normally used for this purpose. 3D Point Tracking (3DPT) and Digital Image Correlation (DIC) constitute photogrammetric-based optical non-contact measurement techniques that have proven to be efficient for the vibration analysis of rotating machinery. In addition to complex image processing software and tracking algorithms, these two approaches typically require surface preparation in the form of markers and speckle patterns. These requirements limit the applicability of photogrammetry as a condition monitoring tool, especially when it comes to industrial environments. This paper proposes 2D shape analysis for target-less non-contact measurement in condition monitoring of rotating machines. Through comparison to measurements captured using conventional proximity probes on an experimental test setup, it is also illustrated how different dynamic characteristics of a rotating system can be distinguished using this measurement approach.