On some critical machinery vibration monitoring algorithm and its application for incipient fault detection and localization

Further development of proposed earlier [1] critical machinery vibration monitoring algorithm intended for faults early detection, unlike standard monitoring techniques, is propounded. The algorithm is founded on nondimensional S-discriminants, calculated from current amplitude-clipped vibration signal parameters referred to the ones for the machine being in good (normal) condition. These parameters have an inherent high sensibility to amplitude spikes magnitude and amount growth, which takes place at vibration signal under the machine degradation, due to suppressing intrinsic machine vibration hash. The paper shows that really effective high speed machinery condition monitoring technique based on using casing vibration data should mandatory take into account the acceleration parameters calculated both in wide and narrow frequency bands.