The present invention relates to the technology field of environment noise attenuating, and more particularly to a design method for feedforward active noise control system using analog filter.
The development of technology along with the advancement in science helps to bring in fast industrial manufacture, having good transport facilities and high tech electronic products, but also leads noise pollution to blanket the living environment. It should be known that, sound (noise) is measured in a unit called decibel (dB) or A-weighted decibels (dBA). For example, sound produced by an ordinary conversation is about 60 dBA. On the other hand, by using a decibel meter, it can be measured that fridge noise and air conditioner's operation noise are both around 60 dBA. Moreover, noises make by car horns, railway train, police sirens and take-off of airplanes are measured in a range between 100 dBA and 130 dBA. Not only that, there are also noise pollution blanketing the rural environment, including noise of leaf blower operation (˜110 dBA), noise of grain dryer operation (82-102 dBA) and noise of manure spreader operation (90-105 dBA).
From above descriptions, it is understood that, how to effectively attenuate environmental noises have now become an important issue. Currently, passive noise control (PNC) and active noise control (ANC) are two principal noise attenuating ways, and the ANC technique has been widely applied in noise attenuation because of the good development of adaptive signal processing techniques and digital signal processors (DSPs). For example, Hyundai motor company utilizes the ANC technique to attenuate engine noise, and Noctua (company) applies the ANC technique in noise attenuation of radiator fan.
During a normal operation of the ANC system 1′, however, the causality constraint will be violated in case of the acoustic/electric delays in the ANC system 1′ exceeding the acoustic delay of the primary path. As a result, the noise attenuating performance of the ANC system 1′ dramatically degrades as the degree of noncausality increases. Thus, the positions of the noise source, the reference microphone 1RM′ and the error microphone 1EM′ are critical when designing and manufacturing the ANC system 1′ in order to improve the noise attenuating performance.
As explained in more detail below, the primary path starts at the position of the reference microphone 1RM′ and ends at the position of the error microphone 1EM′. On the other hand, ANC technique follows the principle of the destructive wave interference, reducing an unwanted acoustic noise generated by a primary source through an anti-noise produced by a secondary source. The secondary path is composed by the transfer functions of the error microphone 1EM′, the pre-amplifier 13′, the anti-aliasing filter 14′, the analog-to-digital converter (ADC) in the DSP chip 1DP′, the digital-to-analog converter (DAC) in the DSP chip 1DP′, the reconstruction filter 11′, the power amplifier 12′, the loudspeaker 1LS′, and the acoustic path from loudspeaker 1LS' to error microphone 1EM′. Therefore, computing the secondary path's transfer function (i.e., S(z)) lead the computing loading of the DSP chip 1DP′ to become heavy. As a result, not only the DSP chip 1DP′ needs spending even more time to achieve the convergence of the ANC computing, but also the adaptive filter is updated to be a high-order filter. However, heavy computing loading of the adaptive algorithm would enlarge the electronic delay in case of the design of the ANC system is in consideration of the causality constraint of the acoustic delay of the primary path and the electronic delay of the secondary path.
Therefore, resulted from the fact that the design of the circuit and/or the constituting units of the DSP chip 1DP′ is too complicated, a noise-cancelling earbuds or a noise-canceling headset using the conventional ANC system 1′ show cannot show a satisfying price—performance ratio. In addition, because the adaptive filter provided in the DSP chip 1DP′ is a high-order digital filter, it is impossible to design a physical analog circuit for disposing in the DSP chip 1DP′ to execute the same filter function as the high-order digital filter.
From above descriptions, it is understood that there are rooms for improvement in the conventional ANC system 1′. In view of that, inventors of the present application have made great efforts to make inventive research and eventually provided a design method for feedforward active noise control system using analog filter.
The primary objective of the present invention is to disclose a design method for feedforward active noise control (ANC) system using analog filter. In which, at least one noise collecting system is adopted for collecting a real environmental noise so as to generate a reference signal and a target signal. Subsequently, according to the reference signal and the target signal, a first adaptive system identifying unit is enabled to complete a first system identification process for producing a first adaptive filter. After that, a second adaptive system identifying unit is enabled to complete a second system identification process based on the reference signal, the target signal and the first adaptive filter so as to produce a second adaptive filter. Then, after the second adaptive filter is converted to a low-order digitally-controlled filter by using a system identification tool, the digitally-controlled filter is further converted to a physical analog filter circuit. Consequently, a feedforward ANC system comprising the physical analog filter circuit, a pre-amplifier unit, a reference microphone, and a mixer is established.
It is worth mentioning that, because the feedforward ANC system not includes any DSP chip, analog-to-digital converter and digital-to-analog converter, it is able to find that the feedforward active noise control system can not only exhibit an outstanding noise cancelling ability, but also has an advantage of low manufacturing cost.
In order to achieve the primary objective of the present invention, inventors of the present invention provides an embodiment of the design method for feedforward active noise control system, comprising following steps:
In one embodiment, the forgoing second noise collecting system comprises:
In one embodiment, the forgoing first noise collecting system also comprises a second pre-amplifier, a first A/D conversion circuit, and a second A/D conversion circuit, and further comprises:
In one embodiment, the forgoing first system identifying unit comprises:
In one embodiment, the forgoing second system identifying unit comprises:
In a practicable embodiment, the forgoing system identification tool is a mathematical program such as a C programming language.
In a practicable embodiment, the forgoing physical analog filter circuit comprises a plurality of low-order filters coupled to each other by a cascade connecting way.
In a practicable embodiment, the first adaptive filter and the second adaptive filter are both a finite impulse response (FIR) filter, and the analog filter W(s) is an infinite impulse response (IIR) filter.
The invention as well as a preferred mode of use and advantages thereof will be best understood by referring to the following detailed description of an illustrative embodiment in conjunction with the accompanying drawings, wherein:
To more clearly describe a design method for feedforward active noise control system disclosed by the present invention, embodiments of the present invention will be described in detail with reference to the attached drawings hereinafter.
The present invention discloses a design method for feedforward active noise control system using analog filter In which, at least one noise collecting system is adopted for collecting a real environmental noise so as to generate a reference signal and a target signal. Subsequently, according to the reference signal and the target signal, a first adaptive system identifying unit is enabled to complete a first system identification process for producing a first adaptive filter. After that, a second adaptive system identifying unit is enabled to complete a second system identification process based on the reference signal, the target signal and the first adaptive filter so as to produce a second adaptive filter. Then, after the second adaptive filter is converted to a low-order digitally-controlled filter by using a system identification tool, the digitally-controlled filter is further converted to a physical analog filter circuit. Consequently, a feedforward ANC system comprising the physical analog filter circuit, a pre-amplifier unit, a reference microphone, and a mixer is established.
With reference to
As explained in more detail below, the first noise collecting system NC2 is developed for acquiring the first digital reference signal x(n) and the digital target signal d(n) that are transmitted in the primary path P(z). As
Subsequently, method flow is proceeded to step S3, so as to let the first noise collecting system NC2 transmit the first digital reference signal x(n) and the digital target signal d(n) to a first system identifying unit AI1 having a first adaptive filter Ŝ(z), and then enabling the first system identifying unit AI1 to complete an adaptive system identification of the first adaptive filter Ŝ(z). As
Therefore, during executing the step S3, the first adaptive filter Ŝ(z) produces a first digital output signal y(n) based on the first digital reference signal x(n), and the first digital subtracter A1 applies a subtraction operation to the first digital output signal y(n) and the digital target signal d(n) so as to produce a first digital error signal e1(n). Subsequently, the first adaptive algorithm unit ALc1 adaptively modulates at least one filter parameter of the first adaptive filter 5 (z) according to the first digital error signal e1(n) and the first digital reference signal x(n), thereby making the first digital error signal e1(n) approach zero.
In a practicable embodiment, the first adaptive algorithm unit ALc1 is an algorithm, such as least mean square (LMS) algorithm, normalized least mean square (NLMS) algorithm or Filtered-x LMS algorithm. Of course, the first adaptive algorithm unit ALc1 provided in the first system identifying unit AI1 is not limited to be the forgoing LMS, NLMS or Filtered-x LMS. In other words, engineers skilled in development and manufacture of ANC system should know that, there are many other mathematical algorithms suitable for being used as the first adaptive algorithm unit ALc1. On the other hand, the first adaptive filter Ŝ(z) can be a finite impulse response (FIR) filter or an infinite impulse response (IIR) filter. For example, when using LMS algorithm as the first adaptive algorithm unit ALc1 so as to be provided in the first system identifying unit AI1, it utilizes following mathematical formulas to complete the adaptive system identification of the first adaptive filter Ŝ(z):
y(n)=Σl=0L−1Ŝl(n)·x(n−l); (I)
e
1(n)=d(n)−y(n); and (II)
Ŝ
l(n+1)=Ŝl(n)+μx(n−1)e1(n). (III)
In the above-listed mathematical formulas, y(n) is the first digital output signal, d(n) is the digital target signal, x(n) is the first digital reference signal, e1(n) is the first digital error signal, Ŝl (n) is a weight vector, μ is a step size of the first adaptive filter Ŝ(z), and L is a length of the first adaptive filter Ŝ(z). That is, after the adaptive system identification of the first adaptive filter Ŝ(z) is completed, an estimated transfer function of the secondary path S(z) (i.e., the first adaptive filter Ŝ(z)) is acquired.
After completing the step S3, step S4 is then executed for establishing a second noise collecting system NC1 to receive a first analog reference signal x(t) that is acquired from the real environmental, and then generating a first digital reference signal x(n) and a digital target signal d(n).
The first audio collecting device AC1, functioning like the first microphone M1 of
As
After completing the step S4, step S5 is next executed for letting the second noise collecting system NC1 transmit the first digital reference signal x(n) and the digital target signal d(n) to a second system identifying unit AI2 having a second adaptive filter W(z), and then enabling the second system identifying unit AI2 to complete an adaptive system identification of the second adaptive filter W(z). As
As described in more detail below, the second adaptive filter W(z) receives the first digital reference signal x(n), and is configured for also generating (outputting) a first digital output signal y(n). Herein, it needs to note that, one of the two first adaptive filters Ŝ(z) is coupled to the second adaptive filter W(z) for receiving the first digital output signal y(n) so as to generate a second digital output signal y′(n). On the other hand, the other one first adaptive filters Ŝ(z) is coupled to the first digital reference signal x(n) so as to generate a second digital reference signal x′(n). Moreover, the second digital subtracter A2 is coupled to the digital target signal d(n) and the second digital output signal y′(n), and the second adaptive algorithm unit ALc2 is coupled to the second adaptive filter W(z), the second digital reference signal x′(n), and the second digital subtracter A2. Therefore, during executing the step S5, the second digital subtracter A2 applies a subtraction operation to the second digital output signal y′(n) and the digital target signal d(n), so as to produce and transmit a second digital error signal e2(n) to the second adaptive algorithm unit ALc2. Subsequently, the second adaptive algorithm unit ALc2 adaptively modulates at least one filter parameter of the second adaptive filter W(z) according to the second digital error signal e2(n) and the second digital reference signal x′(n), thereby making the second digital error signal e2(n) approach zero.
In a practicable embodiment, the second adaptive algorithm unit ALc2 is an algorithm, such as least mean square (LMS) algorithm, normalized least mean square (NLMS) algorithm or Filtered-x LMS algorithm. Of course, the second adaptive algorithm unit ALc2 provided in the second system identifying unit AI2 is not limited to be the forgoing LMS, NLMS or Filtered-x LMS. In other words, engineers skilled in development and manufacture of ANC system should know that, there are many other mathematical algorithms suitable for being used as the second adaptive algorithm unit ALc2. On the other hand, the second adaptive filter w(z) can be a finite impulse response (FIR) filter or an infinite impulse response (IIR) filter. For example, when using LMS algorithm as the second adaptive algorithm unit ALc2 so as to be provided in the second system identifying unit AI1, it utilizes following mathematical formulas to complete the adaptive system identification of the second adaptive filter w(z):
y(n)=Σl=0L−1wl(n)·x(n−l); (IV)
e
2(n)=d(n)−y′(n); (V)
x′(n)=Σm=0M−1Ŝm(n)·x(n−m); and (VI)
w
l(n+1)=wl(n)+μx′(n−1)e2(n). (VI)
In the above-listed mathematical formulas, y(n) is the first digital output signal, y′(n) is the second digital output signal, d(n) is the digital target signal, x(n) is the first digital reference signal, x′(n) is the second digital reference signal, e2(n) is the second digital error signal, wl(n) is a weight vector, Ŝm (n) is a weight vector, μ is a step size of the second adaptive filter W′(z), and L and M are both a filter length.
After completing the step S5, step S6 is next executed for converting the second adaptive filter W(z) to an analog filter W(s) by using a system identification tool, wherein the analog filter W(s) is a low-order filter. The system identification tool is a mathematical program like C programming language, and functions as a system identification system as shown in
As
In an exemplary embodiment, the analog filter w(s) is a 6-order filter, such that it is hard to convert the analog filter w(s) to a physical analog filter circuit. Accordingly, the mathematical program is utilized again in order to further convert the analog filter w(s) to an analog filter comprising three low-order filter unit coupled to each other by a cascade connecting way.
After the analog filter comprising three cascade-connected low-order filter units is obtained, the analog filter is consequently converted to a KHN (Kerwin-Huelsman-Newcomb) filter circuit for being as the physical analog filter circuit 10. As
The above description is made on embodiments of the present invention. However, the embodiments are not intended to limit scope of the present invention, and all equivalent implementations or alterations within the spirit of the present invention still fall within the scope of the present invention.
Number | Date | Country | Kind |
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110106483 | Feb 2021 | TW | national |