Abstract
Thanks to the fast development of micro-electro-mechanical systems (MEMS) technologies, MEMS accelerometers show great potentialities for machine condition monitoring. To overcome the problems of a poor signal to noise ratio (SNR), complicated modulation, and high costs of vibration measurement and computation using conventional integrated electronics piezoelectric accelerometers, a triaxial MEMS accelerometer-based on-rotor sensing (ORS) technology was developed in this study. With wireless data transmission capability, the ORS unit can be mounted on a rotating rotor to obtain both rotational and transverse dynamics of the rotor with a high SNR. The orthogonal outputs lead to a construction method of analytic signals in the time domain, which is versatile in fault detection and diagnosis of rotating machines. Two case studies based on an induction motor were carried out, which demonstrated that incipient bearing defect and half-broken rotor bar can be effectively diagnosed by the proposed measurement and analysis methods. Comparatively, vibration signals from translational on-casing accelerometers are less capable of detecting such faults. This demonstrates the superiority of the ORS vibrations in fault detection of rotating machines.
Highlights
Condition monitoring (CM) of rotating machines receives much attention to ensure the high reliability, productivity and safety of rotating machines
The principle is the proportional Doppler frequency shift to a surface that occurs when light is scattered by a moving surface and an exhaustive introduction of Laser Doppler vibrometer (LDV) systems is given in reference [5]
The comparison study of two gravity cancellation methods was carried out by Mones et al [16] and the analytic signal method has higher accuracy. These aforementioned applications focus on the tangential acceleration from the Mechanical Systems (MEMS) accelerometers, aiming to get the torsional vibration in a low frequency range
Summary
Condition monitoring (CM) of rotating machines receives much attention to ensure the high reliability, productivity and safety of rotating machines. The comparison study of two gravity cancellation methods was carried out by Mones et al [16] and the analytic signal method has higher accuracy These aforementioned applications focus on the tangential acceleration from the MEMS accelerometers, aiming to get the torsional vibration in a low frequency range. Thanks to the cost-effective, compact and highperformance MEMS accelerometers, the ORS technology was developed to overcome the intricate and time varying transmission paths and poor SNR of the conventional vibration signals by considering the working principles of rotating machines. Vibration signals acquired from a running machine using on-casing accelerometers are always subjected to various background noise and complex signal transmission paths, which significantly weaken machine fault signatures To minimize these influencing factors and extract desired signals for early fault detection and accurate diagnosis, a promising approach is to develop advanced sensing methods for high SNR signals. The inherent orthogonality between axes leads to unique benefits in characterising ORS vibrations
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