Fluid-borne noise is one of the main components of hydraulic noise. Its attenuation may have a significant effect on the cost of hydraulic systems. Standard passive silencers and dampers can be useful in reducing it in certain frequency ranges; however, these tend to be heavy, bulky and expensive. Active control algorithms, which are a comparatively recent means of reducing fluid-borne noise, can be applied to overcome this compromise. The work presented in this thesis is the development of some active control algorithms utilized in a simple hydraulic system to cancel a number of harmonic orders of fluid-borne noise generated by a servo valve or a real pump. To realize cancellation the filtered reference least mean square (FXLMS) adaptive control method is mainly presented. Furthermore, a fast response servo valve is applied as an actuator to generate a proper anti-noise flow signal in real-time. For simplicity, an off-line identification method for the secondary path is applied in the time invariant working condition. Moreover, ripple reflection from both ends of the hydraulic circuit can produce different effects under different working conditions. In order to execute the cancellation without any prior information about the dynamics of hydraulic systems, the on-line secondary path identification method is discussed. However, in this algorithm an auxiliary white-noise signal applied to an on-line method may contribute to residual noise and an extra computation burden may be added to the whole control system. The performance of these control algorithms is firstly investigated via simulation in a hydraulic pipe model and the real-time application on a test rig using a servo valve as a noise source. Finally, these schemes are realized in a simple hydraulic system with a real pump noise source. The fluid-borne noise can be attenuated by about 20 dB in normal working conditions.
| Identifer | oai:union.ndltd.org:bl.uk/oai:ethos.bl.uk:501639 |
| Date | January 2008 |
| Creators | Wang, Lin |
| Contributors | Johnston, David |
| Publisher | University of Bath |
| Source Sets | Ethos UK |
| Detected Language | English |
| Type | Electronic Thesis or Dissertation |
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