Condition-Based Monitoring of a Centrifugal Pump Using Mahalanobis-Taguchi System

In this paper, a condition-based monitoring (CBM) model that uses the Mahalanobis-Taguchi System (MTS) for fault detection, isolation, and prognostics is presented. The proposed scheme fuses data from multiple sensors into a single system level performance metric using Mahalanobis Distance (MD) and generates fault clusters based on MD values. MD thresholds derived from the clustering analysis are used for fault detection and isolation. When a fault is detected, the prognostics scheme, which monitors the progression of the MD values over time, is initiated. Then, using a linear approximation, time to failure is estimated. The performance of the scheme has been validated via experiments performed on a mono-block centrifugal water pump testbed. The pump has been instrumented with vibration, pressure, temperature and flow sensors and experiments involving healthy and various types of faulty operating conditions have been performed. The experiments show that the proposed approach renders satisfactory results for centrifugal water pump fault detection, isolation and prognostics.