Spatial acoustic radiation characteristics analysis is the precondition of reducing the noise influence of outdoor power transformer while multi-physical field coupling method can be applied to quantify and reveal these acoustic characteristics of a running power transformer. In this study, based on the theoretical analysis about noise generation and dissemination process, an acoustic radiation model about oil-immersed power transformer was established and verified with field test data in time and frequency domain. Then, far-field analysis and directivity analysis were accomplished to characterize acoustic field of power transformer under multiple operating conditions. Finally, the acoustic radiation influence on potential surrounding buildings were analyzed and discussed. The visual results and conclusion provide acoustic guide for the optimal planning and design about both power substation and ambient buildings.

Active noise control (ANC) technology can be able to reduce the low frequency noise effectively, and has been widely applied in limited enclosed equipment, such as cars, aircraft cockpits, and headphones, etc. Compared with the traditional noise reduction methods, ANC technology is a cost-effective method in handling the low-frequency noise of transformers. An experimental ANC system in a virtual substation is designed and constructed. An adaptive signal tracking ANC algorithm is proposed, and a set of ANC experimental prototypes applied to a virtual substation is designed. Based on the proposed algorithm, the distributions of the acoustics and spectral characteristics of transformer noise in substations are analyzed. Experimental results show that the effective noise reduction can be achieved an average of 5 dB(A) in a given region with respect to the absence of the ANC system.

Combining the theory of correlation and simple ant colony optimization blind algorithms, basing on the transmission cluster partition model of wireless sensor networks, we propose a new blind detection scheme. The scheme first uses blind detection algorithm based on simple ant colony optimization algorithms to derive the reference node information and in turn, to estimate the transmission channel. It then combines the anti-estimated transmission channel of reference sensor nodes to recover other non-reference nodes information in the clusters according to the correlation among the transmission signal of each sensor in the model. Simulation results show the feasibility of the scheme.