203 results about "Active noise control system" patented technology

Active noise control system and method for controlling an acoustic noise generated by a noise source at a listening location, in which system and method sound is picked up in the surroundings of the listening location by a sound sensor; an electrical noise signal which corresponds to the acoustic noise of the noise source is generated and filtered adaptively in accordance with control signals. The adaptively filtered noise signal is irradiated into the surroundings of the listening location by a sound reproduction device, where a secondary path transfer function extends between the sound reproduction device and sound sensor. The noise signal is filtered with a transfer function that models the secondary path transfer function. The signals which provided by the sound sensor after first filtering serve as control signals for the adaptive filtering.

An active control of an unwanted noise signal at a listening site radiated by a noise source uses a reference signal that has an amplitude and/or frequency such that it is masked for a human listener at the listening site by the unwanted noise signal and/or a wanted signal present at the listening site in order to adapt for the time-varying secondary path in a real time manner such that a user doesn't fell disturbed by an additional artificial noise source.

An active noise control system generates an anti-noise signal to drive a speaker to produce sound waves to destructively interfere with an undesired sound in a quiet zone. The anti-noise signal is generated with an adaptive filter having filter coefficients. The coefficients of the adaptive filter may be adjusted based on a first filter adjustment from a first listening region, and a second filter adjustment from a second listening region. A first weighting factor may be applied to the first filter adjustment, and a second weighting factor may be applied to the second filter adjustment. The first and second weighting factors may dictate the location and size of the quiet zone as being outside or partially within at least one of the first listening region and the second listening region.

An active noise control system is provided to specify an input transducer, an error transducer, an output transducer and an active noise controller for generating an anti-phase canceling acoustic signal to attenuate an input noise and to output a reduced noise. The active noise control system also performs on-line secondary path modeling. For this purpose the active noise control system comprises, in addition to known systems, a secondary path change detection circuitry (6), a signal distinguishing circuitry (7) and an auxiliary noise control circuitry (8), all of them being used to model said secondary path. FIG. 3

An active noise control system generates an anti-noise signal to drive a speaker to produce sound waves to destructively interfere with an undesired sound in a targeted space. The speaker is also driven to produce sound waves representative of a desired audio signal. Sound waves are detected in the target space and a representative signal is generated. The representative signal is combined with an audio compensation signal to remove a signal component representative of the sound waves based on the desired audio signal and generate an error signal. The active noise control adjusts the anti-noise signal based on the error signal. The active noise control system converts the sample rates of an input signal representative of the undesired sound, the desired audio signal, and the error signal. The active noise control system converts the sample rate of the anti-noise signal.

An active noise control system prevents a continuous muffled sound from being generated as an abnormal sound under a high sound pressure from a speaker when a microphone as a sound detector is covered, and reduces noise immediately when the microphone is uncovered. A first threshold value as an upper limit value and a second threshold value as a lower limit value are provided for the filter coefficient of an adaptive notch filter. When the filter coefficient is greater than the first threshold value, a control sound is faded out according to a forgetting process. When the filter coefficient is smaller than the second threshold value, an adaptive control process is resumed. Even if the microphone is covered, the filter coefficient does not exceed the first threshold value as the upper limit value.

An active noise control system is capable of canceling out noise in the passenger compartment of a vehicle based on low-frequency road noise. The active noise control system has a feed-forward control unit for being supplied with reference signals highly correlated to noise from a noise source and generating a noise cancellation signal which is out of phase to noise in the passenger compartment of the vehicle, and a canceling sound generating unit disposed in the passenger compartment for generating a noise canceling sound in response to the noise cancellation signal from said feed-forward control unit. The active noise control system also has microphones for generating reference signals which are positioned respectively near the base of the front seat, near the center of a roof, and within a trunk compartment, i.e., respectively at vibrational antinodes of a primary or secondary acoustic normal mode of the passenger compartment in the longitudinal direction thereof. Output signals from the microphones are supplied as the reference signals.

Methods for modeling the secondary path of an ANC system to improve convergence and tracking during noise control operation, and their associated uses are provided. In one aspect, for example, a method for modeling a secondary path for an active noise control system is provided. Such a method may include receiving a reference signal, filtering the reference signal with an initial secondary path model to obtain a filtered reference signal, calculating an autocorrelation matrix from the filtered reference signal, and calculating a plurality of eigenvalues from the autocorrelation matrix. The method may further include calculating a maximum difference between the plurality of eigenvalues and iterating a test model to determine an optimized secondary path model having a plurality of optimized eigenvalues that have a minimized difference that is less than the maximum difference of the plurality of eigenvalues, such that the optimized secondary path model may be utilized in the active noise control system.

An active noise control system includes a source unit for generating regenerative signals, an ANC unit for processing signals so as to actively cancel noise, sensors for detecting the information on the inside and outside of a vehicle, a vehicle interior voice discriminating unit for discriminating voice of conversation generated in the vehicle interior, an amplifier for amplifying the signals processed by ANC unit and reproducing transducers for reproducing the signals amplified by the amplifier.

A frequency detecting circuit estimates the frequency fp of a propeller shaft based on the frequency fc of vehicle speed pulses, and calculates a control frequency fp′ which is a harmonic of the frequency fp. A basic signal generator generates a basic cosine wave signal xp1 and a basic sine wave signal xp2 of the control frequency fp′. Adaptive filters and an adder generate a control signal Scp for canceling a driveline noise produced in a passenger compartment by the propeller shaft. A speaker outputs a canceling sound based on the control signal Scp into the passenger compartment.

An active noise control system cancels vibration and noise based on an output from an adaptive notch filter. When the difference between a current engine pulse value input to the adaptive notch filter and a past engine pulse value within a predetermined time period exceeds a predetermined level, an engine pulse monitor turns off a switch to stop the output from the adaptive notch filter. As a result, when there is a sudden change in the engine rpm, the output from the adaptive notch filter is stopped before the renewal speed of the adaptive notch filter coefficient becomes too fast to follow and the coefficient diverges, to prevent generation of abnormal sound. With this active noise control system, the user will not hear any abnormal sound from the adaptive notch filter even when there is a sudden change in the engine pulse.

An active noise control system generates an anti-noise signal to drive a first speaker group including at least one speaker to produce sound waves to destructively interfere with an undesired sound in at least one quiet zone. The active noise control system receives error signals representative of a combination of undesired sound and destructively interfering sound waves produced by the first speaker group. The active noise control system may select a second speaker group to replace the first speaker group based on the error signals.

The invention protects a cross-updated active noise control system based on a novel algorithm for online identification of a secondary channel. The noise control system comprises 6 modules of noise signal filtering, momentum FxLMS algorithm, white noise generator, secondary channel modeling, main channel path and third adaptive filter update module. The object of the noise control system is to solve the problem that an active noise cancellation (ANC) system has a slow convergence speed and a small noise reduction amount in indoor noise-cancellation applications. The innovation lies in the factthat the unevenness of the power spectral density of a noise signal greatly affects the convergence speed of a control filter and a modeling filter in the indoor noise-cancellation applications. Themomentum FxLMS algorithm is proposed to update the weight of the control filter, and a variable step size LMS algorithm is used to update the weight of the modeling filter. The third adaptive filter using the Newton LMS algorithm is used to eliminate an error signal and the signal related to the reference input signal, and improves the modeling accuracy of the modeling filter and the convergence speed of the entire ANC system.

The adaptive speed to changes in a primary source noise is increased through a noise detecting means feeding parallel multi-passband means and multi-transverse adaptive filter means, where each adaptive filter has its own individual adaptive step size means adjusted automatically according to the signal strength at each passband output. The output from each of the multi-adaptive filter means drives a secondary canceling source generating means where each multi-adaptive filter means is automatically adjusted to produce minimum sound in its passband at an error detecting means. Alternatively, the output from the noise detecting means is negated through a negation means, passed through a plant neutralization inverse means and an inverse delay means before driving the secondary source generating means. The secondary source output is aligned and match in amplitude to that of the primary sources, through a delay buffer means and an amplitude regulator means, which are adjusted successively until the output at the error detector means is a minimum.

An active noise control system includes a plurality of adaptive filters. The plurality of adaptive filters each receives an input signal representative of an undesired sound. The adaptive filters may each generate an output signal based on the input signal. The output signals are used to generate an anti-noise signal configured to drive a speaker to produce sound waves to destructively interfere with the undesired sound.

The invention provides an active noise control system, which comprises an environmental noise acquisition device, a high-speed analog-to-digital conversion device, a playback audio receiving device, a signal processing device, a high-speed digital-to-analog conversion device, a power amplifying device and a telephone receiver, wherein the signal processing device is electrically connected with the high-speed analog-to-digital conversion device and the playback audio receiving device, and the telephone receiver is electrically connected onto the power amplifying device. The signal processing device comprises an environmental noise digital signal input end, a playback audio digital signal input end, an air noise signal filtering module, an antiphase filter module based on a secondary acoustic feedback channel, a playback audio gain control adjusting module, a frequency response compensating module based on a secondary channel, a coefficient storage module, a signal superposition module and a mixed audio digital signal output end, wherein the environmental noise digital signal input end is used for receiving noise digital signals of an air noise environment. Compared with the prior art, the active noise control system is more effective in noise elimination.

An active noise control system and method for tuning an acoustic noise signal at a listening position are disclosed in which a first weighting element is connected in the filter coefficient copy path and/or a second weighting element is connected in the microphone path.

An air induction system with active noise control includes a self-cleaning air filter that is integrated within an air intake housing. The self-cleaning air filter filters out contaminants such as dust and dirt particulates from air flowing through the intake housing. The self-cleaning filter is powered and controlled by the same electronic unit that is used to power the active noise control system.

The various embodiments set forth an active noise cancellation system that includes a source separation algorithm. The source separation algorithm enables the identification of acoustic inputs from a particular sound source based on a reference signal generated with one or more microphones. Consequently, the identified acoustic inputs can be cancelled or damped in a targeted listening location via an acoustic correction signal, where the acoustic correction signal is generated based on a sound source separated from the reference signal. Advantageously, the reference signal can be generated with a microphone, even though such a reference signal may include a combination of multiple acoustic inputs. Thus, noise sources that cannot be individually measured, for example with an accelerometer mounted to a vibrating structure, can still be identified and actively cancelled.

The invention relates to a method for predicting the denoising effect of an active noise control system. The method comprises the steps that acoustic-structure coupling models of a vehicle body structure and a vehicle inner cavity are built; M microphones and K loudspeakers are arranged; primary signal vectors d corresponding to the M microphones are acquired; a transfer function matrix H is acquired; the weighted value lambda i of each microphone is set to constitute a diagonal matrix lambda; the steady-state output X of the loudspeakers is solved; distribution situations of sound fields in a vehicle are calculated under the simultaneous action of engine force stimulation and loudspeaker stimulation; the distribution situations of the sound fields in the vehicle are observed by adjusting the number and the positions of the loudspeakers and the number and the positions of the microphones to acquire the denoising effect of the active noise control system in different hardware arrangement schemes. When the method is compared with the prior art, because the denoising effect of the system in different hardware arrangement schemes can be compared to evaluate hardware arrangement of the system and optimize the hardware arrangement schemes, and design and development of the active noise control system are facilitated.

The invention discloses an active ventilated and soundproof window, which comprises a soundproof window. The source ventilated and soundproof window is characterized in that: the soundproof window is provided with an active soundproof ventilation device which comprises a ventilation channel which is communicated with the indoor and the outdoor and an active noise control system. In the invention, the conventional ventilated and soundproof window is provided with the active soundproof ventilation device, and low-frequency noises are counteracted and absorbed by using active noise control technology; and meanwhile, a sound-absorption layer consisting of sound-absorbing materials is coated on the inner wall of the ventilation channel and high and middle-frequency noises are absorbed by a sound-absorbing structure in the ventilation channel. Thus, the low-frequency and high-frequency noises can be effectively reduced under the condition of maintaining high ventilation performance.

The invention discloses a mining multi-wave self-adaptive active noise control system which comprises the following modules: a primary sensor array 9, an error sensor array 10, a loudspeaker array 1, a power amplification circuit module 2, a low-pass filter 3, an A/D conversion module 8, a D/A conversion module 4, an ANC controller 13, a field programmable gate array (FPGA) 7, a wireless transmission module 5, an explosion-proof enclosure 14, a spare battery circuit 11 and a main power supply circuit 12, wherein input noise signals are firstly converted to digital signals by the A/D conversion module 8, are subject to data processing, self-adaptive filtering, time delay and phase inversion by the ANC controller 13, are converted by the D/A conversion module 4, are processed by the low-pass filter 3 and the power amplification circuit module 2 and then are output by the loudspeaker array 1, the loudspeaker array 1 outputs sound waves which have the same frequency but opposite phases with main noise and are used for offsetting primary noise, residual error signals are fed back to the ANC controller 13 after being processed by the power amplification circuit module 2 and the A/D conversion module 8, the error signals are used for adjusting the weight coefficient of an self-adaptive filter, and secondary signals are changed according to the variation of the weight coefficient so as to minimize the error signals.

An active noise control system is provided which cancels a noise using a sound radiated from a speaker driven by an output from an adaptive notch filter. The system employs output signals from an adder or simulation cosine-wave and sine-wave signals, an error signal or an output signal from a microphone, and a compensated signal from the adder or a signal available for acoustically transferring an output from the adaptive notch filter to the microphone in accordance with initial transfer characteristics to update the filter coefficient of the adaptive notch filter. This configuration allows the system to operate with stability even when the acoustic transfer characteristics vary with time or under circumstances where there exists a significant amount of incoming external noises. The system also prevents overcompensation for a noise at the ears of a passenger in a vehicle, thereby proving an ideal noise reduction effect.

The invention provides an engine noise control method based on an FXLMS algorithm aiming at the problem of in-vehicle noise caused by an engine air inlet system, belonging to the field of noise control. The method comprises the following steps: S1, establishing a main control system model of engine intake noise by using an FXLMS algorithm, and constructing a reference signal x (k) of the main control system model by using the rotating speed of the engine; S2, establishing an off-line identification structure, identifying a secondary channel transfer function H2(z) in an active control system model, and providing an identification result to the active control system model; and S3, controlling the engine noise by using the identified active noise control system model. In addition, an improved variable step length algorithm is proposed. The algorithm adds the parameter gamma to the step length of the normalized algorithm and replaces beta in the sine variable step length to adjust the amplitude range of the step length. The algorithm not only has the advantages of fast convergence and small steady-state error of the sine variable step length algorithm, but also has the characteristicsthat the normalized algorithm is suitable for a time-varying reference signal, and the parameter is easy to select.