Intelligent Model Based Imbalance Fault Detection and Identification System of a Turbocharger Based on Vibration Analysis

Abstract

Inappropriate fault detection of turbocharger’s operating parameters has generated unnecessary economic loss due to unplanned down-time. This results to a combination of late and inaccurate diagnosis of the turbocharger faults by the employed maintenance systems. This study, used a Model-based fault diagnosis approach to identify imbalance fault in a turbocharger rotor system. In this approach, the generalized theoretical equation of motion for both healthy and faulty system models of a complete turbocharger rotor, were developed using the Finite element method. A test rig for the turbocharger rotor with sensors to monitor its dynamic behavior under the influence of the aforementioned faulty condition was also developed. Following Modal Expansion, curve fitting technique was used to minimize the error between a set of equivalent experimental and numerical results.

From the results, the theoretical Frequency response functions developed from Finite Element Method fault models had good agreement with the Time and frequency-based responses measured from experimental data for the induced imbalance fault condition, hence, validating the theoretical fault models developed in this study. Using Modal Expansion technique, data from nodal residual forces generated from the developed numerical fault model was compared with measured corresponding experimental nodal residual forces data. The results showed good agreement between the theoretical and experimental findings. Hence, the Model based fault identification scheme implemented in this study successfully identified the magnitude, severity and exact location of imbalance faulty conditions.

Keywords: Model based, fault detection and identification, Turbocharger, vibration, Modal expansion, Test rig, Imbalance, modelling.

DOI: 10.7176/ISDE/12-2-06

Publication date: August 30^th 2021