基于智能数据融合的车内噪声主动控制算法

Active Noise Control Algorithm for Vehicle Interior Noise Based on Intelligent Data Fusion

为解决车辆噪声主动控制系统中参考信号在车内容易受到次级声源的污染和以发动机转速信号作为参考只能控制发动机阶次噪声的问题,提出一种基于智能数据融合的车内噪声主动控制算法。首先根据传递路径分析结果选择对车内噪声贡献量大的车外测点信号,然后将发动机转速信号和车外测点信号进行数据融合作为参考信号,再利用迭代变步长FxLMS算法对驾驶员耳侧噪声进行主动控制。基于试验采集的不同工况车内噪声进行仿真分析,结果表明,所提出的算法相较于采用发动机转速信号作为参考信号的方法在总声压级上降低了4.4 dB(A)。

In the vehicle active noise control system,in order to avoid the reference signal being easily polluted by secondary sound sources in the car and the problem that the engine speed signal as a reference signal can only control the order noise of the engine,this article proposed an active control algorithm for vehicle interior noise based on intelligent data fusion.The active control algorithm firstly selected the signal of measuring points outside the vehicle which contributed greatly to the interior noise according to the result of Transmission Path Analysis(TPA),then engine speed signal and the signal from the measurement point outside the vehicle were used to perform data fusion as a reference signal,then the Iterative Variable Step-size FxLMS(IVS-FxLMS)algorithm was used to actively control the driver’s ear noise.Finally vehicle interior noise was collected under different working conditions for simulation and analysis.The results show that the algorithm proposed in this paper reduces the total sound pressure level by 4.4 dB(A)compared with using the engine speed signal as the reference signal.