Model Based Identification of the Measured Vibration Multi-fault Diagnostic Signals Generated by a Large Rotating Machine

Large rotating machines are usually affected by more or less severe vibrations excited simultaneously by various manufacturing errors and operational defects. In order to identify the causes of these adverse effects on the basis of measured diagnostic signals registered during a regular operation, it is necessary to obtain a theoretical basis regarding possible dynamic responses of the monitored machine to its most likely failures. This paper shows how to achieve this target on the example of monitoring results of a large blower used in the mining industry. In the advanced structural hybrid model of the rotor shaft system of this blower, in addition to the impact of static unbalance, there is included simultaneous interaction of dynamic unbalance of the blower overhung rotor, parallel and angular misalignments of the shaft sections, inner anisotropy of the couplings, pressure pulsation of the working medium caused by incorrect stagger angles of the blower rotor blades, and electromagnetic pull of rotors of the driving electric motors. The contribution of the above-mentioned imperfections to the dynamic behavior of the system will be identified by means of a multi-fault model-based identification method using the harmonic excitation approach, where vibratory motions are described in the space of modal coordinates and malfunction effects are modelled by the use of equivalent external loadings. Computational examples will be devoted to demonstrating the influence of a faulty setting of the stagger angles of the blower blades on lateral vibrations of the entire rotating system with the simultaneous influence of the aforementioned imperfections.