A LINEAR REGRESSION MODEL FOR THE IDENTIFICATION OF UNBALANCE CHANGES IN ROTATING MACHINES

This paper presents a numerical method for the full identification of multi-plane unbalance changes in a multi-bearing rotating machine. This new method is a further development of the methods for one and two-plane identification of unbalance changes. In modern rotating machinery, it is common practice to place permanent probes into the main supporting bearings as a means of “health monitoring” or “condition monitoring”. These probes pick up the real-time vibration signals from a machine during its operation. By reprocessing these monitored signals and comparing them against developed criteria, the location and magnitude of any unbalance change during the machineʹs operation is identified. This is achieved by using the algorithm that combines the processed signals with the use of a non-linear mathematical model for the rotating machine. Assumption is made that the steady state responses before and after the unbalance change takes are available for comparison, and that the mathematical model as well as the dynamic and static properties of the system under consideration are truly representative. Verification of the proposed algorithm has been conducted using computer simulations of a real machine.