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The purpose of active noise control is to generate an anti-noise signal from a speaker to minimize the noise level of the original signal. Traditional noise control techniques use passive treatments to minimize the noise level. For example, the automobile industry minimizes the noise level in the car cabin by using mufflers to absorb the engine noise. These traditional noise control techniques can minimize noise that has a medium or high frequencies. However, these techniques cannot minimize noise that has a low frequency. With active noise control, you can produce an anti-noise signal with the same low frequency as the low-frequency noise signal. The phases of the anti-noise signal are opposite to those of the low-frequency noise signal. When the two signals reach the same point, they satisfy the superposition principle and negate each other.
|Note Active noise control performs optimally when controlling monotone noise in a spatially simple and small sound field. For example, you can use this technique to minimize the noise level of a low-frequency sound waveform traveling through a duct.|
You can use an adaptive filter to generate the anti-noise signal. The following figure shows a diagram of an active noise control system.
In this active noise control system, you need two microphones and one speaker. Place one microphone close to the noise source and place the other microphone in the sound field where you want to minimize the noise. The microphone close to the noise source is known as the primary microphone. The microphone in the sound field is known as the error microphone. Use the speaker, known as the control speaker, to transmit the anti-noise signal that the adaptive filter generates.
In the previous figure, y(n) is the output signal from the adaptive filter. During the noise control process, the adaptive filter adjusts the filter coefficients and transmits the output signal to the control speaker. The adaptive filter in the active noise control application is a filtered-x least mean squares (LMS) adaptive filter, whose diagram is different from the diagram of a typical adaptive filter. In the previous figure, notice that the filtered-x LMS adaptive filter does not have the input signal d(n). Instead, the adaptive filter requires the error signal e(n) as the input signal. The error microphone acquires the error signal.
The path from the output of the adaptive filter to the sound field where you place the error microphone is known as a secondary path, which usually contains a digital-to-analog converter (DAC), control speaker, error microphone, acoustic path from the control speaker to the error microphone, and analog-to-digital converter (ADC). The DAC converts the digital signal y(n) to an analog signal to drive the control speaker. The ADC converts the analog signal that the error microphone acquires to a digital signal.
In the previous figure, is the impulse response of the secondary path. Adaptive filters do not estimate the impulse response of the secondary path. You must estimate the impulse response of the secondary path before implementing an active noise control system.
Refer to the Active Noise Control (Simulated) VI in the examples\Adaptive Filters\Applications\Active Noise Control directory for an example that uses the Adaptive Filter Toolkit to perform active noise control.