Active Noise Cancellation: The Unwanted Signal and the Hybrid Solution (2011)

IntroductionThe need to eliminate unwanted sounds is greater, as this is an expression of the limited tolerance that we have as individuals to the perception of sounds generated by industrial equipment, appliances and some general properties that are unpleasant for most people.Vibrations mechanical engines in operation, digging machinery and electricity generators, are just a few examples of processes or equipments that can produce signals nuisance to human ear.While mitigating these unwanted sounds already exists today, the methods used are based on passive elements that offer a poor response to low frequency sounds.This drawback happens (Kuo & Morgan, 1996), when the wavelength of the signal is long compared to the size of the muffler liabilities.The relevance in the treatment of low-frequency sounds is that they produce fatigue and loss of concentration, thus affecting the performance of people, machinery and equipment present.That is, low-frequency sounds produced very intense vibrations that can fracture structures in the team very long periods of exposure.ANC Systems must respond to changes in frequency of the primary noise with which they are working.In other words, the primary non-stationary noise vary, hence to get an acceptable cancellation we must use some kind of adaptive system, that carried out many operations at a high speed.To satisfy the requirements those ANC systems, it should be used digital signal processors (PDSs) compute based on adaptive algorithms and adaptive filters.The ability of an adaptive filter to operate and respond satisfactorily to an unknown environment, and variations that may be involved in signal reference, to make a powerful adaptive filter for signal processing and control applications.There are various types of adaptive filters but generally all share the characteristic of working with an input signal (input vector), and a desired response (output vector), these two signals are used to compute an estimate of error (error signal), which allows to control the coefficients of the adjustable filter.In this chapter, it's proposed a new Hybrid active noise control (ANC) system.The main feature of the proposed system is the consideration of both, the online secondary path modeling and the acoustic feedback.The objective is to realize improved performance at a reasonable computational cost in a Hybrid ANC system that considers two of the more important troubles of the ANC.In the proposed system, two least mean square (LMS) adaptive filters are used in the noise control process, one for the Feedforward stage and the other for the Feedback stage, both of them use the same error signal as used in the www.intechopen.comAdaptive Filtering Applications 50 adaptation of the modeling filter (Romero et al, 2008).Moreover, the method of online secondary path modeling is an adaptation of the method proposed by (Akhtar et al, 2006) in which a variable step size (VSS-LMS) algorithm is used to adapt the modeling filter.With the VSS-LMS algorithm a small step size is required initially for the modeling filter and later its value is increased accordingly.The combination of the Feedback and Feedforward stages, gives to the system a solid robustness in frequency domain.Finally, the computer simulations are presented to show the success of the proposed system. Adaptive filters 2.1 What is an adaptive filter?An adaptive filter responds to changes in its parameters, like for example: its resonance frequency, input signal or transfer function that varies with time.This behavior is possible due to the adaptive filter coefficients vary over time and are updated automatically by an adaptive algorithm.Therefore, these filters can be used in applications where the input signal is unknown or not necessarily stationary.An adaptive filter is made up of two parts: a digital filter and an adaptive algorithm.The block diagram of an adaptive filter is shown in Figure 1, we can see that the adaptive algorithm needs, two input signals, () xn and () en as its references to set the parameters of the digital filter and update its coefficients. How to referenceIn order to correctly reference this scholarly work, feel free to copy and paste the following: