82 results about "Active noise control" patented technology

The invention provides a control method and a control system for building an independent acoustic space of an automobile cabin, which are applied to the technical field of sound field control of the automobile cabin, and are used for inputting a multi-channel vibration signal acquired in real time into a deep learning noise prediction model to obtain an in-automobile background noise prediction value at a future moment; the prediction noise is filtered by the secondary path estimation model and then is used as a feedforward reference signal for active noise reduction, and the prediction noise and a residual signal collected by a bright area error microphone are jointly used for weight updating of an adaptive filter; the updated filter generates a reverse-phase noise elimination signal and the reverse-phase noise elimination signal is played by a secondary loudspeaker in real time so as to counteract background noise of the bright area; and closed-loop adjustment of the noise reduction effect is formed based on the sound pressure level contrast ratio of the bright and dark areas, so that the independent acoustic space is kept stable in the time-varying environment of vehicle driving. According to the method, the low noise of the bright area and the isolated sound field of the dark area in the vehicle are realized by fusing deep learning noise prediction and active noise control, and the personalized auditory experience in the vehicle can be remarkably improved.

The invention relates to an active noise reduction device, an active noise reduction method and a range hood, and the active noise reduction device comprises a sound signal collection device which is used for collecting a noise signal; the controller is electrically connected with the sound signal acquisition device, and the controller is configured to generate a noise reduction signal for counteracting the noise signal according to the noise signal acquired by the sound signal acquisition device; the sound signal transmitting device is electrically connected with the controller and is used for transmitting a noise reduction signal; the device is characterized in that the sound signal transmitting device comprises a plurality of plasma loudspeakers which are circumferentially arranged around the noise source, and the plasma loudspeakers are configured to be capable of generating electric arcs through high-voltage electricity so as to drive air to produce sound through the vibration of the electric arcs. The active noise reduction device can be suitable for a complex noise environment, is slightly influenced by the environment and is low in complexity; and the discharge parameters of the plasma loudspeaker can be obtained through a noise reduction method so as to meet the real-time requirement of a dynamic noise environment, and the method is suitable for active noise control, sound field regulation and control and other scenes.

The application relates to the field of active noise reduction technology, in particular to an ANC (active noise control) active noise reduction simulation system, which comprises a first pickup sensor, a second pickup sensor, a simulation module, a microprocessor and a mediation unit. External sound of an ANC earphone is collected by the first pickup sensor, then noise reduction processing is carried out by using a noise reduction controller, internal sound of the ANC earphone is collected by the second pickup sensor, and waveform of the internal sound of the ANC earphone is simulated by the simulation module, then the waveform is compared with a preset optimal waveform by the microprocessor, parameters of a noise reduction filter are adjusted by the mediation unit, and features of the simulated sound waveform are extracted conveniently, the noise reduction module of the noise reduction earphone is systematically and visually adjusted, and noise reduction performance difference between left and right earphones is minimized.

The invention discloses an active noise control method based on multichannel adaptive filtering, and relates to the technical field of automobile noise control and signal processing. The invention discloses an active noise control method based on multi-channel adaptive filtering. The method comprises the following steps: acquiring original noise signals at different positions in a vehicle through a reference microphone; performing multi-band band-pass filtering on the acquired noise signal to extract noise components of a target frequency band; inputting the filtered reference signal into a multi-channel adaptive filtering controller to generate an anti-noise signal; estimating a secondary path to generate an actual anti-noise signal based on the transmission path of the loudspeaker and the error microphone; through a feedback signal collected by an error microphone, closed-loop iteration is carried out to update and control a filter coefficient, and real-time offset and dynamic convergence of a noise signal are realized; through vector superposition of an original noise signal and an actual anti-noise signal, efficient and real-time suppression of multi-channel and broadband noise is realized. The method has more excellent multi-target noise reduction performance and robustness.

Techniques are described herein for classification-based selective pass-through for wearable audio components with active noise control (ANC). Embodiments receive ambient noise with a first artificial neural network pre-trained to classify attention-seeking audio (ASA) components present in the ambient noise. A conditional signal is output based at least on the classification. For example, the first pre-trained network generates an embedded space representation (ESR) characterizing the ASA component, and the conditional signal is based on the ESR. A second artificial neural network is pre-trained to generate a pass-through audio output based on the same ambient audio and the conditional signal, so that the pass-through audio output corresponds to the ASA component. The pass-through audio output is delayed past an ANC processing window so that essentially all the ambient noise except for the ASA component is cancelled by the ANC.

An electronic system with heat dissipation and feed-forward active noise control function includes a fan module, an embedded controller, a reference microphone, a multi-channel speaker module, a beamforming control module and an active noise reduction controller. The beamforming control module controls the orientation of the multi-channel speaker module. The multi-channel speaker module provides anti-phase noise signals to cancel noise according to a speaker control signal. The reference microphone detects broadband noise generated by the fan module in operation to provide a corresponding broadband noise signal. A virtual microphone module of the active noise reduction controller provides a virtual error signal according to a transfer function between the reference microphone and a physical error microphone, a transfer function between the multi-channel speaker module and the physical error microphone and the broadband noise signal, and generates the speaker control signal according to a synchronization signal, the broadband noise signal and the virtual error signal.

The application provides an underwater structure noise control method based on a parametric secondary sound source, which comprises the following steps: firstly, using the sound pressure and normal velocity information of a structure surface, a far-field noise prediction method is adopted to obtain the radiation noise at a virtual reference point in the far field, thereby providing an input basis for parametric secondary sound source control; secondly, a multi-channel parametric sound field model is established to verify the controllability of the parametric secondary sound field, and a regularization least square algorithm is adopted to obtain multi-channel signal emission parameters by taking the sum of the sound pressures at multiple virtual reference points in the far field as the minimum target; finally, when the monitoring information of the underwater structure is missing, a local control strategy is adopted to obtain the underwater structure noise control effect. The application is directed to directional control in the accurate area of far-field noise prediction, solves the problem of poor traditional active noise reduction effect caused by missing monitoring information, improves the reliability and stability of the system, and lays a theoretical foundation for the application of underwater structure active noise control technology.

The invention discloses an in-vehicle active noise control method and system based on a convolutional recurrent network, and the method comprises the steps: obtaining reference signals collected by a sensor in real time, forming a cache data set by M reference signals, and enabling reference data in the cache data set to slide rightwards for a jump length after a short-time Fourier transform sliding window; the reference signals in the cache data set are subjected to short-time Fourier transform according to algorithm updating frequency, and one frame of time-frequency data is formed in each time of short-time Fourier transform; storing the N frames of time-frequency data by adopting a first-in first-out principle; and inputting the N frames of time-frequency data into the trained convolutional cyclic network model, and outputting an output signal for controlling a loudspeaker according to inverse Fourier transform. According to the method, the recurrent neural network is used for dynamically storing and updating time sequence steps, the noise reduction capability of the depth model is reserved, and the requirement for real-time noise reduction of the whole vehicle is met.

Methods of classifying and using acoustic filters for active noise control in hearing systems, such as headphones. The acoustic filters are determined and stored in a memory in the hearing system, making it therefore possible to quickly and efficiently select and use a certain filter in order to improve filter performance and filter stability in the hearing system.

The invention provides an active noise reduction system which may be self-contained within a headset of the system, wherein circuitry within the system applies an active noise reduction profile to a signal to the speakers in the headset, to provide active noise reduction to the user of the headset, the system being arranged to receive power both from a power supply external to the system and from a battery of the system and to automatically modify the active noise reduction applied, in dependence on whether or not the system is connected to an external power supply.

Machine learning network topologies, and training systems and methods therefor, are described for implementing unified sound conversion (USC), such as for automated name detection. Such automated name detection can support automated attention handling in wearable audio components with active noise control (ANC) to suppress ambient sound. Embodiments of USC network topologies include a feature generator comprising a convolutional encoder, an axial self-attention (ASA) block, and a deconvolutional decoder. A MEL converter generates input filter bank energies (FBEs) from an audio sample of a spoken word. The feature generator is trained to estimate output FBEs from the input FBEs, such that the output FBEs represent the linguistic information of the spoken word absent any speaker-specific suprasegmental features.

The invention discloses a multi-channel active noise control method capable of reducing the calculated amount. The method comprises the following steps: (1) building a multi-channel ANC system, wherein the system comprises M (Mgt; 1) the number of the microphones; (2) measuring a secondary channel transfer function; (3) selecting Q (Qlt; m) microphones, calculating a weighting matrix by using the latest T signals collected by the microphone system, and weighting the signals of the selected Q microphones to obtain a signal of a Q channel for controlling the updating of a filter; (4) updating a control filter; and (5) calculating the output of the control filter, and inputting the output into the secondary sound source for playing. According to the method, the Q microphones are randomly selected in each period of time, and the Q microphone signals are weighted to obtain the update signal of the control filter, so that the calculation amount can be greatly reduced, and the global noise reduction effect can be obtained.

The invention discloses an active noise control method, device and system in a vehicle, a medium and equipment. The method comprises the following steps: playing a first audio signal through a loudspeaker in the vehicle; collecting the first audio signal played by the loudspeaker through a microphone in the vehicle to obtain a second audio signal; determining a reference secondary path between the speaker and the microphone based on the first audio signal and the second audio signal; obtaining a target correction parameter; wherein the target correction parameter is obtained based on the down-sampling parameter and the up-sampling parameter; correcting the reference secondary path by using the target correction parameter to obtain a corrected secondary path; based on the modified secondary path, an active noise control algorithm is operated to perform active noise control of the interior of the vehicle. The secondary path which is more accurate and complete and can be directly used for an active noise control algorithm can be obtained, so that the active noise control effect in the vehicle is improved, and driving quietness is improved.

The present application provides an audio parameter determination method, a related apparatus, and a communication system. When placed in an earphone case, a wireless earphone can detect whether the earphone case is opened. When the earphone case is opened, the wireless earphone can collect environmental sound by means of a microphone so as to perform scene detection. The scene detection can be used for detecting one or more pieces of environmental information such as the noise level and scene type of an environment where the wireless earphone is located. On the basis of a scene detection result, the earphone can determine audio parameters for implementing an active noise control function / hearthrough function / augment hearing function. In this way, appropriate audio parameters can be determined before a user wears the earphone, so as to provide the user with an optimal use experience of the active noise control function / hearthrough function / augment hearing function immediately after the user wears the earphone.

The present application belongs to the technical field of active noise control, and particularly relates to a substation active control noise reduction method, device, equipment and medium. The active noise control method provided by the present application divides the noise distribution map of the noise elimination array area into a first grid array by grid division of the active control noise eliminator array corresponding to the noise distribution map. Each first grid is further divided into a second grid array by grid division, and each first grid corresponds to a second grid array. The sound pressure level in each second grid is determined, the sound pressure level of each first grid is determined according to the sound pressure level of each second grid in the second grid array, the control sound pressure level of the corresponding noise elimination unit is determined according to the sound pressure level of the first grid, and noise reduction is further performed. The present application collects the distribution of noise at the discharge interface, each noise elimination unit can independently control the active noise reduction amplitude, and the corresponding noise reduction effect can be adopted according to the noise distribution at the noise discharge interface to accurately adjust the noise discharge in the corresponding area of the noise reduction unit.

The invention provides a noise elimination method and device, electronic equipment and a vehicle, and the method comprises the steps: collecting time series data of environment noise in the vehicle, analyzing the time series data, and determining a main noise type and noise intensity spatial distribution; activating a target noise reduction channel of a target partition in the vehicle through noise intensity spatial distribution, and determining an original reference signal of a reference microphone in the target noise reduction channel through a main noise type; performing secondary path estimation and forward path calculation of a preset adaptive filter on the original reference signal to obtain a first noise reduction driving signal for the loudspeaker; acquiring a historical reference signal of the reference microphone and a training noise signal of the error microphone, and inputting the historical reference signal and the training noise signal into a preset depth active noise control network to output a second noise reduction driving signal; and adaptive weighting is performed on the first noise reduction driving signal and the second noise reduction driving signal to obtain a target noise reduction driving signal, and elimination of the vehicle environment noise is completed through the target noise reduction driving signal, so that the user experience is improved.

The invention relates to the technical field of active noise control, and provides a binaural cooperative active noise control method based on a combined cost function. The objective of the invention is to solve the problems of asynchronous convergence rates of left and right ears and inconsistent steady-state errors caused by factors such as physiological structure difference of left and right ear canals, inconsistent wearing fitness of earphones and asymmetrical directivity of loudspeakers. According to the method, a combined cost function including an overall error term, an instantaneous error term and an accumulative error term is constructed, the contribution proportion of each error term is automatically adjusted through a dynamic weight adjustment mechanism, and the weight of a control filter is updated based on a gradient descent method, so that the convergence speed and the steady-state error of a left sound channel and a right sound channel tend to be consistent. The consistency and balance of the binaural active noise control performance can be improved, and the method can be suitable for application scenes such as active noise reduction earphones and intelligent cabins.

This application discloses a noise control method and a near-ear open-back audio device, relating to the field of acoustic processing technology. The noise control method is applied to a near-ear open-back audio device, which includes at least two first microphones. The noise control method includes: acquiring ambient noise signals collected by each first microphone; performing noise pattern recognition based on the ambient noise signals to obtain a target noise pattern; performing noise localization based on the ambient noise signals to obtain a target noise direction; selecting a target noise reduction controller from a plurality of preset noise reduction controllers that corresponds to the target noise pattern and target noise direction; and performing active noise control based on the target noise reduction controller. This application provides a solution for applying active noise control in a near-ear open-back audio device and improving the noise control effect.

The application discloses a kind of active control method, device and car of automobile interior noise combined with virtual sensing.The method can include: for the interior noise of vehicle at different speeds, by reference signal, physical monitoring signal and virtual error signal respectively construct multiple groups of auxiliary filter containing optimal control filter information and observation filter containing the transfer function between physical monitoring point and virtual error point;By mean method, construct composite observation filter;At different speeds, based on least mean square estimation error matching mechanism, by reference signal, physical monitoring signal, auxiliary filter, composite observation filter, active noise control is carried out at noise reduction target position.The present application can significantly reduce the noise at ear at different speeds while the arrangement position of error microphone does not affect the normal activities of passengers, improve the comfort of riding.

The invention discloses a narrow-band FxLMS active noise reduction method with low calculation complexity, and relates to the technical field of active noise control. The method comprises the following steps: generating a synchronous reference signal group based on a noise fundamental frequency and a harmonic frequency thereof; calculating and storing the phase offset of the reference signal group filtered by the secondary path estimation model in advance; collecting an error signal, and iteratively updating an accumulated value related to the reference signal group; and calculating and outputting a control signal based on the phase offset and the accumulated value. According to the method, convolution operation which is carried out in real time and is huge in calculation amount in a traditional algorithm is equivalently replaced with simple multiplication operation through strict mathematical derivation, on the premise that the convergence speed, the steady-state error, the noise reduction amount and other core performance of the traditional narrowband FxLMS algorithm are completely kept, the calculation complexity and memory occupation during operation are greatly reduced, and the method is suitable for large-scale popularization and application. The method is especially suitable for the deployment of an embedded platform with limited computing resources.

Provided is a mobile terminal capable of reducing cost for carrying out active noise control and / or active sound effect control. Provided is a mobile terminal that carries out active noise control in which, in order to reduce driving source sound transmitted from a driving source to the vehicle interior of a vehicle, a first control signal for outputting cancellation sound from a speaker provided in the vehicle interior is generated, and / or active sound effect control in which a second control signal for outputting from the speaker a sound effect resembling the driving source sound is generated, wherein the vehicle has an on-vehicle system that controls the speaker, and the first control signal and / or the second control signal is transmitted to the on-vehicle system.

The embodiment of the present application relates to the fan noise reduction technical field, and particularly discloses an active noise reduction method for a portable fan, which comprises: obtaining a noise signal; the noise signal is a dynamic comprehensive noise signal comprising air inlet noise, air outlet noise, fan blade noise and / or motor noise generated when the portable fan is running; noise control processing is carried out on the noise signal based on a pre-trained noise reduction model to obtain a noise control instruction; a noise reduction signal is sent based on the noise control instruction to carry out active noise control on the portable fan; wherein, within a preset error allowable range, the phase of the noise reduction signal and the noise signal is opposite, the frequency and amplitude are the same, and the noise signal is used for destructive interference. The present application dynamically analyzes the dynamic comprehensive noise signal generated inside and outside the cavity when the fan is running, and sends a corresponding noise reduction signal according to the dynamic comprehensive noise signal, so as to realize active noise control on the fan, thereby reducing the noise level when the fan is running.

The application relates to the earphone technical field, and in particular to an earphone noise reduction method, an earphone noise reduction device, a computer readable storage medium and an earphone. The method comprises the following steps: in the case that the noise reduction mode of the earphone is a first mode (without active noise control), simultaneously acquiring sound wave data for a first preset time length through a feedforward microphone and a feedback microphone of the earphone; on the other hand, in the case that the noise reduction mode of the earphone is a second mode (active noise control), simultaneously acquiring sound wave data for a second preset time length through the feedforward microphone and the feedback microphone. According to the actual parameters of a default filter in the earphone in the second mode and the sound wave data acquired in the two modes respectively, target parameters of the filter are determined, and a target filter is determined based on the target parameters. The application can adapt to the individual needs of different ears and different wearing modes, and can achieve a high level of noise reduction effect in different ears and different wearing modes.

The application relates to the field of fan noise reduction technology, and particularly discloses an active noise reduction device for a portable fan, which comprises a signal collector arranged in a cavity of the portable fan and used for collecting noise signals generated by the portable fan in real time when the portable fan is running; a signal processor arranged in the cavity and electrically connected with the signal collector, used for calling a pre-trained noise reduction model to perform noise control processing on the noise signals, and obtaining noise control instructions; and a signal generator arranged in the cavity and electrically connected with the signal processor, used for obtaining the noise control instructions and emitting noise reduction signals according to the noise control instructions to perform active noise control on the portable fan; wherein, within a preset error allowable range, the noise reduction signals and the noise signals are opposite in phase, same in frequency and same in amplitude, and are used for performing destructive interference on the noise signals. The application realizes destructive interference on the noise signals by emitting the noise reduction signals, so that the noise level during the running of the fan is reduced.

This invention belongs to the field of industrial noise control technology and discloses an active noise control method for vibration noise in precast beam factories. The method includes the following steps: S1, signal preprocessing and frequency band focusing; S2, secondary path identification and modeling; S3, calculation of the filtered reference signal; S4, initialization of control parameters; S5, calculation of the desired signal for the main path; S6, main loop processing. The beneficial effects of this invention are as follows: 1. An adaptive divergence detection mechanism based on error signal energy monitoring is introduced into the traditional SAS-FxLMS algorithm. When the error energy exceeds a preset multiple of the original energy, the algorithm is determined to be diverging, and a recovery mechanism is automatically triggered. 2. When the norm exceeds a preset threshold, the weight vector is scaled proportionally to reduce its norm to within the threshold range, ensuring the numerical stability of the algorithm. 3. The transfer function models of the main path and secondary paths are optimized according to the characteristics of the target frequency band center frequency (150Hz); the algorithm parameters are dynamically adjusted according to the peak factor, RMS value, and other characteristic parameters of the input signal.

Disclosed herein, among other things, are systems and methods for active noise cancellation (ANC) for hearing device applications. A method includes estimating a first sound pressure on an ear drum of a wearer of the hearing device caused by a hearing processing signal, estimating a second sound pressure on the ear drum of the wearer of the hearing device caused by a leakage path of the hearing device, and computing a ratio of the first sound pressure and the second sound pressure to predict a comb-filtering effect for the hearing device. The method also includes computing an ANC controller using the computed ratio in one or more frequency ranges, and canceling leaked sound into an ear canal of the wearer for the hearing device in the one or more frequency ranges using the ANC controller.

Techniques are described herein for classification-based selective pass-through for wearable audio components with active noise control (ANC). Embodiments receive ambient noise with a first artificial neural network pre-trained to classify attention-seeking audio (ASA) components present in the ambient noise. A conditional signal is output based at least on the classification. For example, the first pre-trained network generates an embedded space representation (ESR) characterizing the ASA component, and the conditional signal is based on the ESR. A second artificial neural network is pre-trained to generate a pass-through audio output based on the same ambient audio and the conditional signal, so that the pass-through audio output corresponds to the ASA component. The pass-through audio output is delayed past an ANC processing window so that essentially all the ambient noise except for the ASA component is cancelled by the ANC.

The invention discloses a virtual sensing active noise control algorithm based on grey wolf algorithm optimization and VBAP interpolation. The method comprises the following steps: 1, measuring and recording the distance between a virtual sensor and a physical sensor; step 2, calculating the weighted weight of the physical sensor by adopting a VBAP (Video Broadband Access Point) method; 3, obtaining a sound pressure signal by using the physical sensor, weighting the sound pressure signal of the physical sensor by using the calculated weight, and estimating to obtain a sound pressure signal at the virtual sensor; and step 4, based on the estimated sound pressure signal at the virtual sensor, optimizing the coefficient of the control filter by adopting a grey wolf algorithm so as to realize active noise control. The method has no requirements on the number and layout of the physical sensors, can effectively estimate the sound pressure, can be applied to any active noise control algorithm, is robust to the characteristic and azimuth change of the noise source position, and is robust to the change of the secondary path, such as the position change of the secondary source, the position change of the virtual sensor and the like.

An embodiment detects, using a sensor installed within a building, a first position of a first noise source. The embodiment generates a first noise control configuration comprising a first directional acoustic loudspeaker and a first frequency and first amplitude of a first acoustic tone, the first frequency and first amplitude of the first acoustic tone, when generated by the first directional acoustic loudspeaker, selected to attenuate the first noise source at a first distance from the first position. The embodiment generates, according to the first noise control configuration, the first acoustic tone.