基于LMS自适应滤波算法的电力变压器有源降噪系统

Active Noise Control System Based on LMS Adaptive Filter Algorithm for Transformer Power Noise Reduction

为了有效抑制电力变压器产生的高分贝低频噪声,针对变压器有源降噪系统开展了相关研究。结合实验条件,在分析变压器噪声时域及频域特点的基础上,合理选择了有源降噪系统类型。通过仿真和理论分析了收敛系数、滤波阶数以及系统采样频率对有源降噪系统采用的LMS自适应滤波算法收敛性、稳定性以及降噪效果的影响。搭建了变压器噪声在线监测及有源降噪软件控制平台,并针对变压器噪声特点合理选择了硬件系统设备。结果表明,在变压器噪声有源降噪实验中,噪声低频区域降噪效果显著,在误差传声器处取得了5-10 d B的降噪效果,平均声能量密度下降了68.38%-90%,验证了LMS算法的有效降噪性,以及所构建的有源降噪系统对变压器噪声在线监测与抑制的可靠性。

In order to reduce the high-decibel low-frequency noise generated by power transformer, it is necessary to analyze the active control of the transformer noise system. According to the time-domain and frequency-domain characteristics of the transformer noise and the experiment condition, we selected an appropriate type active noise control system. On the basis of simulation and theory analysis, we investigated the effects of step side, the filter order, sampling rate on the stability, convergence, and noise reduction of LMS adaptive filter algorithm for transformer power noise reduction. Then we designed the transformer noise on-line monitoring and active noise control software system, and chose the hardware devices based on the noise characteristics. The results show that, in the transformer noise reduction experiment, the low frequency part of the noise will be reduced effectively, and the system has achieved 5-10 dB noise reduction and 68.38%-90% decline in average sound energy density, which verify the feasibility of LMS algorithm and the reliability of on-line monitoring system with software platform and hardware devices.