There have been steadily growing requirements from the academia and industry, demanding non-invasive methods and reliable measurement systems of research devoted to operational mode analysis (OMA). Due to the simplicity of performing only structures surface vibration measurements, OMA is frequently applied in machine fault diagnosis (MFD) and structure health monitoring (SHM). OMA can handle big structures, such as bridges, buildings, machines, etc. However, there is still an open question: how to properly handle the harmonic effects of rotating components and the difficulty of closely estimating space modes are still a nightmare to deal with. Therefore, the main objective of this paper is to identify the structure of natural frequencies by the regeneration of frequency response functions (FRFs) for complex structures based on OMA. The novelty of our approach is to use the random decrement technique (RDT), correlation function estimation (CFE), and enhanced Ibrahim time method (EITM) to overcome OMA’s difficulties and limitations. To reduce further rotational harmonics effects, gear mesh and side band frequencies, digital signal processing techniques based on notching filters, and liftering analysis techniques were also used. All the experiments were performed at the laboratory test rig and conducted by using three accelerometers, one impedance hammer, one force sensor, and one data acquisition board. To reduce data’s variabilities, each test was measured three times for 5 min. The data sampling frequency for all the experiments was 25.6 kHz. To validate the proposed methodology, extensive OMA tests were performed for the generation of FRFs. The measured objects were a steel bar, induction motor, and gearbox. Five structural natural frequencies for the induction motor and eight structural natural frequencies for the gearbox were generated, respectively.
Read full abstract