Feasibility of Rotor Fault Detection from a Fluid Dynamics Perspective

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Article Type:
Research/Original Article (دارای رتبه معتبر)
Abstract:

The majority of condition monitoring techniques employed today consider the acquisitioning and analysis of structural responses as a means of profiling machine condition and performing fault detection. Modern research and newer technologies are driving towards non-contact and non-invasive methods for better machine characterisation. Yet current literature lacks investigations into the monitoring and detection of anomalous conditions using fluid dynamic behaviour. If one considers unshrouded rotors which are exposed to a full field of fluid interaction such as helicopter rotors and wind turbines amongst others, such an approach could potentially be beneficial. In this work, time-dependent fluid dynamic data is numerically simulated around a helicopter tail rotor blade using URANS CFD with the Open FOAM software package. Pressures are probed at locations in the field of the rotor and compared to results attained in an experimental investigation where good correlation is seen between the results. A blade is modelled with a seeded fault in the form of a single blade out of plane by 4°. Comparisons are drawn between the blade in its ‘healthy’ and ‘faulty’ configurations. It is observed that the fault can be detected by deviations in the amplitudes of the pressure signals for a single revolution at the probed locations in the field. These deviations manifest as increases in the frequency spectrum at frequencies equivalent to the rotational rate (1 per revolution frequencies). The results described are assessed for their fidelity when the pressure is probed at different locations in the domain of the rotor. Deviations in the pressure profiles over the surface of the blades are also seen for the asymmetric rotor configuration, but may prove too sensitive for practical application.

Language:
English
Published:
Journal Of Applied Fluid Mechanics, Volume:13 Issue: 6, May -Jun 2020
Pages:
1743 to 1758
https://magiran.com/p2188614  
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