WO1994024662A1 - Methode de calcul de la ponderation de filtres pour systemes de neutralisation des ondes de pression - Google Patents

Methode de calcul de la ponderation de filtres pour systemes de neutralisation des ondes de pression Download PDF

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Publication number
WO1994024662A1
WO1994024662A1 PCT/US1994/004368 US9404368W WO9424662A1 WO 1994024662 A1 WO1994024662 A1 WO 1994024662A1 US 9404368 W US9404368 W US 9404368W WO 9424662 A1 WO9424662 A1 WO 9424662A1
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WIPO (PCT)
Prior art keywords
calibration data
filter weights
weights
transducers
calculating
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PCT/US1994/004368
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English (en)
Inventor
J. Paul Martinez
Donald W. Cooley
Kenneth G. Oetzel
Carla P. Woodworth
V. Bradford Mason
Julia A. Oekin-Meza
Anne R. Hessing
D. Kent Peterson
Richard H. Steinberger
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Sri International
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Publication of WO1994024662A1 publication Critical patent/WO1994024662A1/fr

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    • H—ELECTRICITY
    • H03—ELECTRONIC CIRCUITRY
    • H03H—IMPEDANCE NETWORKS, e.g. RESONANT CIRCUITS; RESONATORS
    • H03H21/00—Adaptive networks
    • H03H21/0012—Digital adaptive filters
    • G—PHYSICS
    • G10—MUSICAL INSTRUMENTS; ACOUSTICS
    • G10K—SOUND-PRODUCING DEVICES; METHODS OR DEVICES FOR PROTECTING AGAINST, OR FOR DAMPING, NOISE OR OTHER ACOUSTIC WAVES IN GENERAL; ACOUSTICS NOT OTHERWISE PROVIDED FOR
    • G10K11/00—Methods or devices for transmitting, conducting or directing sound in general; Methods or devices for protecting against, or for damping, noise or other acoustic waves in general
    • G10K11/16—Methods or devices for protecting against, or for damping, noise or other acoustic waves in general
    • G10K11/175—Methods or devices for protecting against, or for damping, noise or other acoustic waves in general using interference effects; Masking sound
    • G10K11/178—Methods or devices for protecting against, or for damping, noise or other acoustic waves in general using interference effects; Masking sound by electro-acoustically regenerating the original acoustic waves in anti-phase
    • G10K11/1781—Methods or devices for protecting against, or for damping, noise or other acoustic waves in general using interference effects; Masking sound by electro-acoustically regenerating the original acoustic waves in anti-phase characterised by the analysis of input or output signals, e.g. frequency range, modes, transfer functions
    • G10K11/17813—Methods or devices for protecting against, or for damping, noise or other acoustic waves in general using interference effects; Masking sound by electro-acoustically regenerating the original acoustic waves in anti-phase characterised by the analysis of input or output signals, e.g. frequency range, modes, transfer functions characterised by the analysis of the acoustic paths, e.g. estimating, calibrating or testing of transfer functions or cross-terms
    • G—PHYSICS
    • G10—MUSICAL INSTRUMENTS; ACOUSTICS
    • G10K—SOUND-PRODUCING DEVICES; METHODS OR DEVICES FOR PROTECTING AGAINST, OR FOR DAMPING, NOISE OR OTHER ACOUSTIC WAVES IN GENERAL; ACOUSTICS NOT OTHERWISE PROVIDED FOR
    • G10K11/00—Methods or devices for transmitting, conducting or directing sound in general; Methods or devices for protecting against, or for damping, noise or other acoustic waves in general
    • G10K11/16—Methods or devices for protecting against, or for damping, noise or other acoustic waves in general
    • G10K11/175—Methods or devices for protecting against, or for damping, noise or other acoustic waves in general using interference effects; Masking sound
    • G10K11/178—Methods or devices for protecting against, or for damping, noise or other acoustic waves in general using interference effects; Masking sound by electro-acoustically regenerating the original acoustic waves in anti-phase
    • G10K11/1785—Methods, e.g. algorithms; Devices
    • G10K11/17853—Methods, e.g. algorithms; Devices of the filter
    • G—PHYSICS
    • G10—MUSICAL INSTRUMENTS; ACOUSTICS
    • G10K—SOUND-PRODUCING DEVICES; METHODS OR DEVICES FOR PROTECTING AGAINST, OR FOR DAMPING, NOISE OR OTHER ACOUSTIC WAVES IN GENERAL; ACOUSTICS NOT OTHERWISE PROVIDED FOR
    • G10K11/00—Methods or devices for transmitting, conducting or directing sound in general; Methods or devices for protecting against, or for damping, noise or other acoustic waves in general
    • G10K11/16—Methods or devices for protecting against, or for damping, noise or other acoustic waves in general
    • G10K11/175—Methods or devices for protecting against, or for damping, noise or other acoustic waves in general using interference effects; Masking sound
    • G10K11/178—Methods or devices for protecting against, or for damping, noise or other acoustic waves in general using interference effects; Masking sound by electro-acoustically regenerating the original acoustic waves in anti-phase
    • G10K11/1785—Methods, e.g. algorithms; Devices
    • G10K11/17857—Geometric disposition, e.g. placement of microphones
    • G—PHYSICS
    • G10—MUSICAL INSTRUMENTS; ACOUSTICS
    • G10K—SOUND-PRODUCING DEVICES; METHODS OR DEVICES FOR PROTECTING AGAINST, OR FOR DAMPING, NOISE OR OTHER ACOUSTIC WAVES IN GENERAL; ACOUSTICS NOT OTHERWISE PROVIDED FOR
    • G10K11/00—Methods or devices for transmitting, conducting or directing sound in general; Methods or devices for protecting against, or for damping, noise or other acoustic waves in general
    • G10K11/16—Methods or devices for protecting against, or for damping, noise or other acoustic waves in general
    • G10K11/175—Methods or devices for protecting against, or for damping, noise or other acoustic waves in general using interference effects; Masking sound
    • G10K11/178—Methods or devices for protecting against, or for damping, noise or other acoustic waves in general using interference effects; Masking sound by electro-acoustically regenerating the original acoustic waves in anti-phase
    • G10K11/1787—General system configurations
    • G10K11/17879—General system configurations using both a reference signal and an error signal
    • G10K11/17881—General system configurations using both a reference signal and an error signal the reference signal being an acoustic signal, e.g. recorded with a microphone
    • G—PHYSICS
    • G10—MUSICAL INSTRUMENTS; ACOUSTICS
    • G10K—SOUND-PRODUCING DEVICES; METHODS OR DEVICES FOR PROTECTING AGAINST, OR FOR DAMPING, NOISE OR OTHER ACOUSTIC WAVES IN GENERAL; ACOUSTICS NOT OTHERWISE PROVIDED FOR
    • G10K2210/00—Details of active noise control [ANC] covered by G10K11/178 but not provided for in any of its subgroups
    • G10K2210/10—Applications
    • G10K2210/103—Three dimensional
    • G—PHYSICS
    • G10—MUSICAL INSTRUMENTS; ACOUSTICS
    • G10K—SOUND-PRODUCING DEVICES; METHODS OR DEVICES FOR PROTECTING AGAINST, OR FOR DAMPING, NOISE OR OTHER ACOUSTIC WAVES IN GENERAL; ACOUSTICS NOT OTHERWISE PROVIDED FOR
    • G10K2210/00—Details of active noise control [ANC] covered by G10K11/178 but not provided for in any of its subgroups
    • G10K2210/30—Means
    • G10K2210/301—Computational
    • G10K2210/3019—Cross-terms between multiple in's and out's
    • G—PHYSICS
    • G10—MUSICAL INSTRUMENTS; ACOUSTICS
    • G10K—SOUND-PRODUCING DEVICES; METHODS OR DEVICES FOR PROTECTING AGAINST, OR FOR DAMPING, NOISE OR OTHER ACOUSTIC WAVES IN GENERAL; ACOUSTICS NOT OTHERWISE PROVIDED FOR
    • G10K2210/00—Details of active noise control [ANC] covered by G10K11/178 but not provided for in any of its subgroups
    • G10K2210/30—Means
    • G10K2210/301—Computational
    • G10K2210/3041—Offline
    • G—PHYSICS
    • G10—MUSICAL INSTRUMENTS; ACOUSTICS
    • G10K—SOUND-PRODUCING DEVICES; METHODS OR DEVICES FOR PROTECTING AGAINST, OR FOR DAMPING, NOISE OR OTHER ACOUSTIC WAVES IN GENERAL; ACOUSTICS NOT OTHERWISE PROVIDED FOR
    • G10K2210/00—Details of active noise control [ANC] covered by G10K11/178 but not provided for in any of its subgroups
    • G10K2210/30—Means
    • G10K2210/301—Computational
    • G10K2210/3046—Multiple acoustic inputs, multiple acoustic outputs
    • G—PHYSICS
    • G10—MUSICAL INSTRUMENTS; ACOUSTICS
    • G10K—SOUND-PRODUCING DEVICES; METHODS OR DEVICES FOR PROTECTING AGAINST, OR FOR DAMPING, NOISE OR OTHER ACOUSTIC WAVES IN GENERAL; ACOUSTICS NOT OTHERWISE PROVIDED FOR
    • G10K2210/00—Details of active noise control [ANC] covered by G10K11/178 but not provided for in any of its subgroups
    • G10K2210/30—Means
    • G10K2210/301—Computational
    • G10K2210/3049—Random noise used, e.g. in model identification
    • G—PHYSICS
    • G10—MUSICAL INSTRUMENTS; ACOUSTICS
    • G10K—SOUND-PRODUCING DEVICES; METHODS OR DEVICES FOR PROTECTING AGAINST, OR FOR DAMPING, NOISE OR OTHER ACOUSTIC WAVES IN GENERAL; ACOUSTICS NOT OTHERWISE PROVIDED FOR
    • G10K2210/00—Details of active noise control [ANC] covered by G10K11/178 but not provided for in any of its subgroups
    • G10K2210/30—Means
    • G10K2210/301—Computational
    • G10K2210/3052—Simulation
    • G—PHYSICS
    • G10—MUSICAL INSTRUMENTS; ACOUSTICS
    • G10K—SOUND-PRODUCING DEVICES; METHODS OR DEVICES FOR PROTECTING AGAINST, OR FOR DAMPING, NOISE OR OTHER ACOUSTIC WAVES IN GENERAL; ACOUSTICS NOT OTHERWISE PROVIDED FOR
    • G10K2210/00—Details of active noise control [ANC] covered by G10K11/178 but not provided for in any of its subgroups
    • G10K2210/30—Means
    • G10K2210/301—Computational
    • G10K2210/3057—Variation of parameters to test for optimisation
    • G—PHYSICS
    • G10—MUSICAL INSTRUMENTS; ACOUSTICS
    • G10K—SOUND-PRODUCING DEVICES; METHODS OR DEVICES FOR PROTECTING AGAINST, OR FOR DAMPING, NOISE OR OTHER ACOUSTIC WAVES IN GENERAL; ACOUSTICS NOT OTHERWISE PROVIDED FOR
    • G10K2210/00—Details of active noise control [ANC] covered by G10K11/178 but not provided for in any of its subgroups
    • G10K2210/30—Means
    • G10K2210/321—Physical
    • G10K2210/3216—Cancellation means disposed in the vicinity of the source

Definitions

  • This invention relates generally to sound dampening techniques and more particularly to methods and apparatus for active noise cancellation.
  • active noise control refers to any electro-acoustical method in which an undesired sound wave is canceled by a second sound wave that has the same amplitude but is 180° out of phase.
  • active noise control is most often used to attenuate low frequency noise and vibration.
  • HVAC heating, ventilation, and air conditioning
  • Martinez et al assigned to the assignee of this present application, and entitled “Method and Apparatus for the Active Reduction of Compression Waves” describes a multichannel active noise control system which includes a plurality of input microphones and at least one (but preferably more) output loudspeakers.
  • the number of channels defined by the system is equal to the product of the number of input microphones and the number of output loudspeakers.
  • This multichannel noise control system is very advantageous in that it provides three-dimensional noise cancellation in unbounded environments.
  • the calculation of filter weights is relatively straightforward, as was the case with prior art noise cancellation systems.
  • the Wiener least-squares minimization methods as taught in Optimum Signal Processing. An Introduction, by S. J. Orfanidis, Macmillan Publishing Company, 1988, or the Widrow-Hoff algorithm as taught in Adaptive Signal Processing, by B. Widrow and S. Stearns, Prentice-Hall, Inc., 1985, are suitable for calculating filter weights if the number of channels is small.
  • traditional methods for calculating filter weights become cumbersome because thousands of linear equations must be solved simultaneously. Using standard techniques, these computations can take days or even weeks. It would therefore be desirable to have a faster method for calculating filter weights for large multichannel noise control systems of the kind described in the Martinez et al. patent application.
  • the present invention comprises a method of calculating filter weights for compression wave cancellation systems such as multichannel noise control systems.
  • the method includes the steps of configuring a system, collecting calibration data, preprocessing the data, calculating the forward filter weights W and the neutralization filter weights Wc, simulating the system to predict performance, and loading a set of filter weights (W and Wc) into the signal processor of a multichannel noise control system.
  • the number and placement of a plurality of input transducers (microphones) and output transducers (loudspeakers) is determined.
  • the placement of input transducers depends on the directional characteristics of the noise source; the placement of the output transducers governs the size and shape of the quiet zone.
  • the calibration data collection step determines the transfer functions of four parameters which define the multichannel system.
  • Input microphone calibration data M is the response of the input microphones to typically wideband signals emitted from a noise source.
  • Quiet zone calibration data Q is the response of the quiet zone microphones to the noise source.
  • Loudspeaker calibration data L is the response of the quiet zone microphones to signals emitted from the loudspeakers.
  • Coupling calibration data C is the response of the input microphones to signals emitted from the loudspeakers.
  • the preprocessing step windows, averages, deconvolves, and filters the calibration data in preparation for filter weight calculations.
  • the filter weight calculation step can optionally use power or energy constraints on the signals feeding the output transducers; it also offers a choice of a direct or an iterative method.
  • the direct method for calculating filter weights is used for systems with less than twelve channels, and the iterative method is used for systems with twelve or more channels.
  • the final step is a simulation of system performance based on the calculated forward filter weights W and the neutralization filter weights Wc. If system performance is determined to be inadequate, the configuration of the system can be modified, or the parameters used in the calculation of the forward filter weights W can be tweaked to improve system performance.
  • the preprocessing and compute filter weights steps can then be repeated to produce a new set of filter weights. Once the filter weights in the simulated system appear to meet system requirements, they are loaded into the signal processor of the multichannel noise control system.
  • the principal advantage of the present invention is that it provides a means for calibrating large, multichannel active noise control systems that are computationally more demanding but capable of greater performance than single channel systems of the prior art. Furthermore, for large systems, the iterative method of the present invention for calculating forward filter weights is much faster than the direct method, greatly reducing computer processing time. System constraints can be taken into account when calculating filter weights, so that optimum performance can be realized with imperfect transducers. Finally, the invention facilitates system design in that different signal processors can be simulated and their performance compared before a design is committed to hardware.
  • Figure 1 is a pictorial view of a compression wave cancellation system
  • FIG. 2 is a block diagram representing the compression wave cancellation system of Fig. 1;
  • Figure 3 is a block diagram of the signal processing unit (SPU) 20 of Figs. 1 and 2;
  • SPU signal processing unit
  • Figure 4 is a flow diagram of a method for calculating filter weights in accordance with the present invention.
  • Figure 5 is an example of a noise control system produced by the Configure System step 48 of Fig. 4;
  • Figures 6a and 6b are graphs used to illustrate the Calibration Data Collection step 50 of Fig.4;
  • Figure 7 is a flow diagram of a process for calculating the forward filter weights W and neutralization filter weights Wc of the Compute W and Wc step
  • Figure 8 is a flow diagram of a direct method for calculating forward filter weights W within the process illustrated in Fig.7;
  • Figure 9 is a flow diagram of an iterative method for calculating forward filter weights W within the process illustrated in Fig. 7;
  • Figure 10 is a block diagram of a system simulation used to simulate performance in the Simulate Performance step 56 of Fig.4.
  • a multichannel apparatus 10 is used to reduce undesired compression waves 12 in a medium 14 produced by a source 16.
  • a full description of apparatus 10 can be found in U.S. patent application serial number 07/697,154 filed on May 8, 1991, on behalf of Martinez et al., assigned to the assignee of this application and entitled "Method and Apparatus for the Active Reduction of Compression Waves", said application being incorporated herein by reference.
  • apparatus 10 includes a number of input transducers such as microphones 18a and 18b (collectively input transducers 18), a signal processing unit (SPU) 20, and a number of output transducers such as loudspeakers 22a, 22b, 22c, and 22d (collectively output transducers 22).
  • the term "loudspeaker” means any electro-acoustical transducer capable of transforming electrical signals into compression waves in a medium.
  • a quiet zone transducer such as microphone 24 can be used to detect the effectiveness of apparatus 10 in reducing undesired compression waves in a quiet zone 26 of medium 14.
  • Microphone 24 can be moved to a number of positions 24' to evaluate the effectiveness of apparatus 10 at various angular positions relative to source 16. Alternatively, a number of quiet zone microphones can be used to simultaneously measure the residual compression waves in the quiet zone.
  • Fig. 2 illustrates the system of Fig. 1 in block diagram form.
  • Medium 14 in this example is air, and the propagation paths through medium 14 are represented by the transmission path boxes 28, 30, 32, and 34. . Sounds traveling along transmission paths 28 (from source 16) and transmission paths
  • Input transducers 18 convert the combined compression waves from summer 36 to electrical signals 38.
  • SPU 20 processes electrical signals 38 to produce complementary electrical signals 40.
  • Output transducers 22 produce complementary compression waves in medium 14 along transmission paths 32 to at least partially cancel the compression waves created by source 16 along transmission paths 30.
  • SPU 20 includes a pair of input summers 42a and 42b, eight forward filters F, four output summers 44a, 44b, 44c, and 44d, and eight neutralization filters N.
  • the two digit subscripts of the forward filters F identify the inputs and outputs they couple together. For example, forward filter F j j couples input 1 to output 1, and forward filter F 23 couples input 2 to output 3.
  • the eight neutralization filters have two digit subscripts where the first digit indicates which input the filter is coupled to and the second digit which output it is coupled to.
  • SPU 20 further includes a pair of input buffers 43a and 43b coupled to the two input microphones 18a and 18b, respectively, and four output buffers 45a, 45b, 45c, and 45d coupled to the loudspeakers 22a, 22b, 22c, and 22d, respectively.
  • summers 42a and 42b In the forward path of SPU 20, inputs 1 and 2 are presented to summers 42a and 42b, respectively, and the output of each summer is applied to four forward filters F.
  • the signal from summer 42a on a line 46a is applied to forward filters F, j , F 12 , F 13 , and F 14 .
  • the signal from summer 42b on a line 46b is applied to forward filters F 2 ⁇ , F 22 , F 23 , and F 24 .
  • the outputs of the forward filters F are applied to summers 44a-d in the following fashion: the signals from filters F j j and F 21 are applied to summer 44a, the signals from filters F, 2 and F 22 are applied to summer 44b, the signals from filters F j and
  • output signals 1-4 are fed back through neutralization filters N to summers 42a and 42b. More specifically, neutralization filters N j j , N 1 , N 13 , and N 14 feed back the signals from outputs 1-4 to summer 42a, and neutralization filters N 21 , N 22 , N 23 , and N 24 feed back the signals from outputs 1-4 to summer 42b.
  • the filters F and N can be made from discrete components such as inductors, capacitors, and resistors. Preferably, however, the filters F and N are digital filters and part of a digital SPU 20.
  • input buffers 43a and 43b include analog-to-digital (A D) converters which convert the analog signals from microphones 18a and 18b into digital inputs 1 and 2, respectively.
  • the input buffers can also include pre-amplifiers, anti-aliasing (low-pass) filters, etc.
  • Lines 46a and 46b carry the digital sum calculated by digital summers 42a and 42b to the digital forward filters F.
  • the outputs of the digital forward filters are applied to digital summers 44a-d to produce digital outputs 1-4.
  • Output buffers 45a-d include digital-to-analog (D/A) converters to convert the digital outputs 1-4 to analog signals capable of driving loudspeakers 22a - 22d.
  • the output buffers can include reconstruction filters, power amplifiers, etc.
  • the digital signals on outputs 1-4 are fed back through digital neutralization filters N to digital summers 42a and 42b.
  • the weights of the forward filters F and the neutralization filters N can be calculated by the conventional techniques described previously. However, as the number of channels of SPU 20 increases, it becomes increasingly difficult to calculate the filter weights in a reasonable period of time.
  • the present invention comprises methods for quickly and efficiently generating filter weights for large multichannel noise control systems.
  • FIG. 4 is a flow diagram illustrating a process for generating filter weights in accordance with the present invention.
  • the system is configured by positioning a number of input microphones and loudspeakers with respect to a noise source and a designated quiet zone (see Fig. 5).
  • calibration data are collected.
  • the calibration data are then preprocessed in step 52, where the signals are windowed, averaged, deconvolved, and filtered in preparation for filter weight calculations.
  • Forward and neutralization filter weights are computed in step 54, and system performance is simulated in step 56. If the simulated performance is substandard, steps 52, 54, and 56 are repeated, as indicated by broken line 57.
  • the values of W and Wc are downloaded into the SPU. When the calibrated system is activated, the antinoise substantially cancels the undesired noise in the quiet zone.
  • FIG. 5 is a diagram showing the physical configuration of an active noise control system.
  • the numbers and locations of the input microphones, loudspeakers, and quiet zone microphones are determined by the specific noise problem to be solved.
  • a system 10' is shown as consisting of a signal processing unit (SPU) 20', two input microphones Mi and M2, four loudspeakers Li, L2, L3, L4, and two quiet zone microphones Qi and Q2.
  • a complex, wideband , noise source S produces compression waves which are to be canceled by complementary compression waves produced by system 10'.
  • Quiet zone 66 is the spatial region where noise reduction is to be achieved; the boundary of the quiet zone is indicated by a broken line 68.
  • every input microphone (Mj and M2) is preferably connected to every loudspeaker (L ⁇ t L2, L 3 , L4) through a forward filter.
  • the forward filter weights W will be chosen to minimize the residual noise in the quiet zone.
  • Figures 6a and 6b illustrate a preferred method for collecting calibration data in accordance with the present invention.
  • input microphone calibration data M To produce a set of filter weights, input microphone calibration data M, quiet zone calibration data Q, loudspeaker calibration data L, and coupling calibration data C are collected. SPU 20' is bypassed during the data collection process.
  • a "Condition A” is used as illustrated in Fig. 6a, where the noise source S is active over its entire operating range and the loudspeakers are turned off.
  • a "Condition B" is used as illustrated in Fig. 6b, where the noise source S is turned off and the loudspeakers are energized, one at a time, with a probe signal p.
  • the Q data now comprise the time series Q1S1 .
  • noise source S is turned off and the loudspeakers are energized, one at a time, with a probe signal p.
  • L is activated and data are simultaneously collected at the input (M ⁇ ,M 2 ) and quiet zone (Q ⁇ ,Q 2 ) microphones.
  • L 2 is activated and data are collected at the input and quiet zone microphones, and so on, until all four loudspeakers (L ⁇ ,L 2 ,L 3 ,L4) have been used.
  • Probe signal p can be any well defined wideband signal of brief duration such as an impulse or, preferably, a burst of pseudo-random noise. The duration of probe signal p is usually less than 1 sec, so that it is feasible to repeat the measurement several times.
  • Figure 6b shows the subset of data resulting from the activation of loudspeakers Lj and L 2 . Similar data are obtained from the activation of loudspeakers L 3 and L 4 .
  • the data collected in the quiet zone are the L data, which comprise the time series Q ⁇ ⁇ p, Q 1 L2/?, Q 1 3 P, Q 1 L 4 /7, Q 2 1 ?, Q 2 2 , Q 2 L 3 P, and Q2L 4 J.
  • the data collected with the input microphones are the C data, which comprise the time series MJLJ ?, M ⁇ h 2 p, M ⁇ L 3 /?,MjL 4 p, M 2 L 1 /?, M 2 L2/?, M 2 L 3 /?, and M 2 L 4 P.
  • the C data are used to compute the neutralization filter weights W c .
  • the neutralization filters serve to reduce the effects of coupling (acoustic feedback) from the loudspeakers to the input microphones.
  • the collected data are preprocessed in several ways prior to the computation of W and W c .
  • the original M and Q data obtained under Condition A (Fig. 6a) are windowed at the desired time slots SI, S2, and S3 to provide more compact descriptions of source characteristics.
  • the L and C data obtained under Conditions B (Fig. 6b) are averaged to improve the signal-to-noise ratio of these measurements. Because the forward filter weights calculation code requires the impulse response of the loudspeakers
  • the averaged L data are deconvolved with probe signal p.
  • the Q data and either the L or the M data are filtered to select the optimal forward filter frequency band.
  • step 52 the data records available for the forward and neutralization filter weight calculations are as depicted below: Q1L Q1L Q1 L Q1 L
  • i quiet zone location
  • j loudspeaker number
  • k input microphone number
  • t time slot number
  • r Q + XW
  • r a vector describing the residual noise in the quiet zone
  • Q a vector describing the noise source as measured in the quiet zone
  • X a crosspoint matrix obtained by convolving microphone data with loudspeaker data
  • W a vector containing all forward filter weights.
  • Li 1 is the loudspeaker time series of length "a” corresponding to quiet zone location 1 and loudspeaker number 1; M ⁇ is the input microphone time series of length "b” corresponding to input microphone number 1 and time slot number 1; and Q ⁇ is the quiet zone time series of length "c” corresponding to quiet zone location 1 and time slot number 1.
  • the convolution matrices L ⁇ and Mn are calculated from time series Ln and Mn prior to computing Xn.
  • a necessary condition for selecting the number of taps ⁇ is that a + b + ⁇ - 2 > 2.
  • step 70 the length of the forward filters ( ⁇ ) is chosen.
  • the length of the forward filters is one of the determinants of the filter characteristics.
  • step 72 a weight calculation method is chosen. For small systems (less than 12 channels), a direct weight calculation method is preferred because of its relative simplicity and accuracy. For larger system, (12 channels or more), an iterative weight calculation method is preferred for speed.
  • step 74 a decision is made whether or not to use system constraints. If not, the forward filter weights W are calculated in step 76 (using the method selected in step 72), and the neutralization filter weights W c are calculated in step 77.
  • step 78 the forward filters weights W are computed in step 78 (using the method selected in step 72), and a comparison is made in step 80 to determine whether or not the constraints have been satisfied. If the constraints are satisfied, step 77 is performed immediately. If the constraints are not satisfied, the calculation parameters for W are updated in step 82, and steps 78, 80, and 82 are repeated iteratively until the constraints are satisfied. Finally, the neutralization filter weights are computed in step 77.
  • Step 70 selects the length of the forward filters, which is defined as the number of delay-line taps ⁇ . Filter length is determined in part by the bandwidth requirement of the noise control system and in part by the need to treat delayed reflections in a multipath environment (e.g., a room with reflecting walls). However, as is evident from the above discussion, long filters are computationally very demanding. In the preferred embodiment of this invention, ⁇ is in the range 100 - 500.
  • step 72 it is determined whether a direct or an iterative method will be used to compute filter weights.
  • the direct method is fast enough for noise control systems with fewer than 12 channels; the iterative method is needed for larger systems, which are computationally more demanding and would take too much time to calibrate with the direct method.
  • constraints in step 74 allows for the calculation of forward filter weights W while constraining certain quantities.
  • Either a peak power constraint or an energy constraint can be applied to weight amplitude, loop gain, or loudspeaker input.
  • a peak power constraint limits the maximum value of the quantity to be constrained. For example, a peak power constraint can be placed on the loudspeaker inputs so that the loudspeakers always operate in their linear range.
  • An energy constraint limits the sum of the squares of the elements of the quantity to be constrained.
  • Steps 76 and 78 compute the forward filter weights using the method selected in step 72.
  • the direct method will be discussed with reference to Fig.
  • the direct method begins with step 84, the calculation of the crosspoint matrix
  • step 86 the normal equation
  • step 88 an efficient Block Toeplitz package is used to solve for W:
  • an iterative method 90 in accordance with the present invention begins with step 92, where the forward filter weight vector W is set to a preselected initial value.
  • This initial value can be zero, but user or system experience may allow the selection of a non-zero initial value which converges more quickly on a proper filter weight.
  • step 94 the crosspoint matrix
  • step 96 an error score (i.e., a measure of how well the weights are converging) is computed from
  • step 98 a decision is made as to whether this error score exceeds a set threshold. If the error score exceeds the threshold, in step 100, the direction vector v is updated at each iteration by its previous value and the current iteration's error score. A new forward filter value W is calculated from
  • Steps 96, 98, and 100 are repeated until the error score no longer exceeds the threshold.
  • the iterative method for weight calculation is primarily an implementation of a conjugate gradient algorithm that achieves a significant speed-up by exploiting the structure of the crosspoint matrix.
  • the problem can be written as
  • M] j and L] i are the Fourier transforms of the time series Mi i and Ln. and F is the Fourier matrix generated by
  • j and k are indices that go from 1 to n
  • n is the matrix order
  • the matrix calculations for the single input, single output, single channel case show the advantage of writing the normal equations in a form that offers a per-iteration calculation savings. Although mathematically more complicated, all results can be extended to the multichannel case. In practice, all calculations can be done much more simply and quickly by first calculating the standard FFT of Mn , Ln , Wn , and Qn . and then performing the convolutions in the frequency domain.
  • Fig. 10 the simulate performance step 56 of Fig. 4 is illustrated in greater detail.
  • the simulation takes the transfer functions S, M, C, Wc, W, and L and combines them with summers 102, 104, and 106 to create a simulated residual r. More specifically, M and C are combined in summer 102, and the output of summer 102 is combined with the output of Wc in summer 104.
  • the output of summer 104 is applied to filter W, and the output of W is applied to Wc, C, and L.
  • the output of L is combined with S in summer 106 to derive the simulated residual r.
  • the filter weights W and Wc are considered able to meet system requirements and suitable for loading into a hardware signal processor (step 58 of Fig. 4).

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  • Physics & Mathematics (AREA)
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  • Acoustics & Sound (AREA)
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  • Soundproofing, Sound Blocking, And Sound Damping (AREA)

Abstract

Méthode de calcul de la pondération de filtres destinés à un système (10) à canaux multiples de neutralisation des ondes de pression, caractérisée par les étapes suivantes: configuration du système (48), receuil des données de calibrage (50), prétraitement des données de calibrage (52), calcul de la pondération des filtres (54), simulation du fonctionnement du système (56), téléchargement de la pondération des filtres. Le calcul de la pondération des filtres est indiqué pour ce qui concerne les filtres avant (F) et les filtres de neutralisation (N). L'étape de configuration du système spécifie le nombre et la localisation des transducteurs d'entrée (18) et des transducteurs de sortie (22). L'étape de receuil détermine la réponse de tous les transducteurs d'entrée et de zone calme (24) à un signal sonore (16) et à une sélection de transducteurs de sortie. L'étage de prétraitement visualise, déconvolutionne et filtre les données de calibrage en vue du calcul de la pondération des filtres. Les pondérations des filtres avant et de neutralisation dérivent de données prétraitées et peuvent être soumises à des limites de puissance ou d'énergie. Le calcul des pondérations des filtres avant pour des petits systèmes multicanaux peut se faire directement, mais pour les grands systèmes multicanaux, il est préférable de procéder par itération. Enfin, les performances du système sont l'objet d'une simulation basée sur les pondérations calculées des filtres avant et des filtres de neutralisation pour déterminer les retouches éventuelles à apporter aux pondérations avant de les télécharger dans une unité de traitement de signaux.
PCT/US1994/004368 1993-04-21 1994-04-20 Methode de calcul de la ponderation de filtres pour systemes de neutralisation des ondes de pression WO1994024662A1 (fr)

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WO1999017275A1 (fr) * 1997-10-01 1999-04-08 Digisonix, Inc. Systeme de commande adaptatif a adaptation par contrainte d'efficience
US6198829B1 (en) * 1995-07-13 2001-03-06 Societe Pour Les Applications Du Retournement Temporel Process and device for focusing acoustic waves
GB2383224A (en) * 2001-12-17 2003-06-18 Siemens Vdo Automotive Inc Digital filter modelling for active noise cancellation
GB2445984A (en) * 2007-01-25 2008-07-30 Sonaptic Ltd Feedforward ambient noise reduction
US7449851B2 (en) 2001-04-20 2008-11-11 Maschinenfabrik Reinhausen Gmbh Arrangement for automatically influencing a mains supply and motor drive therefor
EP2420411A1 (fr) * 2009-04-15 2012-02-22 Pioneer Corporation Dispositif actif antibruit de vibration
CN111785243A (zh) * 2020-06-10 2020-10-16 厦门市派美特科技有限公司 一种耳机有源降噪方法及系统

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EP0512445A2 (fr) * 1991-05-08 1992-11-11 Adam Opel Aktiengesellschaft Dispositif actif d'atténuation du bruit utilisant des signaux radio pour le cycle de calibration
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Cited By (15)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US6198829B1 (en) * 1995-07-13 2001-03-06 Societe Pour Les Applications Du Retournement Temporel Process and device for focusing acoustic waves
US6978028B2 (en) 1995-07-13 2005-12-20 Societe Pour Les Applications Du Retournement Temporel Process and device for focusing acoustic waves
AU740931B2 (en) * 1997-10-01 2001-11-15 Digisonix, Inc. Adaptive control system with efficiently constrained adaptation
WO1999017275A1 (fr) * 1997-10-01 1999-04-08 Digisonix, Inc. Systeme de commande adaptatif a adaptation par contrainte d'efficience
US6094601A (en) * 1997-10-01 2000-07-25 Digisonix, Inc. Adaptive control system with efficiently constrained adaptation
US7449851B2 (en) 2001-04-20 2008-11-11 Maschinenfabrik Reinhausen Gmbh Arrangement for automatically influencing a mains supply and motor drive therefor
GB2383224A (en) * 2001-12-17 2003-06-18 Siemens Vdo Automotive Inc Digital filter modelling for active noise cancellation
GB2383224B (en) * 2001-12-17 2005-08-03 Siemens Vdo Automotive Inc Digital filter modeling for active noise cancellation
US7450725B2 (en) 2001-12-17 2008-11-11 Mahle International Gmbh Digital filter modeling for active noise cancellation
GB2445984A (en) * 2007-01-25 2008-07-30 Sonaptic Ltd Feedforward ambient noise reduction
GB2445984B (en) * 2007-01-25 2011-12-07 Sonaptic Ltd Ambient noise reduction
EP2420411A1 (fr) * 2009-04-15 2012-02-22 Pioneer Corporation Dispositif actif antibruit de vibration
EP2420411A4 (fr) * 2009-04-15 2017-05-03 Pioneer Corporation Dispositif actif antibruit de vibration
CN111785243A (zh) * 2020-06-10 2020-10-16 厦门市派美特科技有限公司 一种耳机有源降噪方法及系统
CN111785243B (zh) * 2020-06-10 2024-02-09 厦门市派美特科技有限公司 一种耳机有源降噪方法及系统

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