19 results about "Active noise control system" patented technology

This invention discloses a low-frequency noise reduction and sound insulation device for industrial applications, belonging to the field of noise control technology. The device includes an outer soundproof cover, an inner composite sound-absorbing structure, and an active noise control system. The outer soundproof cover is constructed of high-density board. The inner composite sound-absorbing structure is located on the inner wall of the outer soundproof cover and includes an acoustic metamaterial layer and a micro-perforated plate layer, which are spaced apart to form a first resonant cavity. The active noise control system includes: an error microphone embedded in the inner wall of the outer soundproof cover; a controller electrically connected to the error microphone; and a secondary sound source electrically connected to the controller and installed on the inner wall of the outer soundproof cover. This invention achieves broadband passive sound absorption through the composite structure of acoustic metamaterial and micro-perforated plate, providing a high signal-to-noise ratio environment for the active control system. Furthermore, the active control system based on the FxLMS algorithm precisely cancels residual low-frequency line spectra, achieving efficient and stable low-frequency noise reduction.

The invention provides an active noise control system for a vehicle exhaust system and a working method.The active noise control system comprises a control unit, a sound source emitter and an error microphone, the control unit obtains the real-time rotating speed of an engine through a vehicle CAN bus, the sound source emitter is arranged in a pipeline of the exhaust system, and the error microphone is arranged in the pipeline of the exhaust system; the sound source emitter is arranged in the engine and is in communication connection with the control unit, and the sound wave transmission direction of the sound source emitter is opposite to the noise transmission direction of the engine; and the error microphone is arranged in the exhaust pipeline at the downstream of the sound source emitter and is in communication connection with the control unit. The problems that an existing silencer is large in size, and the space and the silencing effect cannot be considered at the same time are solved.

The application discloses an active noise reduction control system and method of a smart phone, comprising an environmental sound acquisition module, a motion state sensing module, a deep learning processing module, a noise reduction signal generation module, a noise reduction execution module, a user preference setting module, a scene recognition module and a power management module; the environmental sound acquisition module collects signals in all directions through a multi-microphone spatial array, and wide frequency response and high sampling rate ensure data quality; the motion state sensing module monitors phone motion parameters in real time to provide a basis for noise reduction strategy adjustment; the deep learning processing module adopts a hybrid model architecture combined with GPU acceleration to accurately analyze noise characteristics; the noise reduction signal generation module can generate adaptive noise reduction signals according to analysis results; and the noise reduction execution module adopts active feedback control and multi-mode sound generation strategies; the application significantly improves the accuracy, adaptability and intelligent level of noise reduction, and greatly improves the auditory experience of users when using the phone in different scenarios.

The invention provides a hybrid active noise control method of a new variable step size LMS algorithm based on a piecewise function, and the method comprises the steps: 1, collecting original data through an acoustic sensor, and carrying out the preprocessing of the collected original data through MATLAB, and obtaining a reference signal; 2, dividing the convergence process of the LMS algorithm into an initial stage, a transition stage and a steady-state stage on the basis of the difference between the expected response signal and the filtered output signal, designing a corresponding step length function for each stage to obtain a segmented step length function, and obtaining a new variable step length LMS algorithm based on the segmented step length function; 3, verifying the convergence speed, the steady-state precision and the steady-state stability of the new variable step size LMS algorithm based on a mean square error (MSE); and step 4, realizing actual noise control of the industrial workshop based on the hybrid active noise control system fused with the new variable step size LMS algorithm. According to the method, the algorithm is rapidly converged, meanwhile, the high-steady-state noise reduction precision is guaranteed, and the noise suppression effect continuously approaches to the optimal effect.

An active noise control system capable of canceling noise independently of displacement of a user's head is provided. In a first system signal processing section (111), adaptive filters (1111-1114) generate noise canceling sounds, a first system selector (1117) selects an output of a first system auxiliary filter corresponding to a noise canceling position matching a detected position of the user's right ear, out of outputs of a plurality of first system auxiliary filters (1116) corresponding to different noise canceling positions, respectively, a first system subtracter (1115) subtracts the selected output from an output of a first microphone (13), and outputs the result as an error signal to the first system adaptive filters and second system adaptive filters of a second system signal processing section (112). The noise canceling positions corresponding to the plurality of first system auxiliary filters are arranged at prescribed intervals only within a space in which the user seated on a seat can move the right ear by turning, laterally bending the head within a prescribed range in the up-down and front-back directions.

Provided is an active noise control system capable of well canceling noise regardless of displacement of a user's ear. In a first system signal processing section (111), a first system auxiliary filter (1116) generates a correction signal that corrects an error signal from a noise signal, a first system subtracter (1115) subtracts the correction signal from an output of a first microphone (13) as the error signal, adaptive filters (1111-1114) perform adaptive operation using the error signal, and generate a canceling sound to be output from a first speaker (12). A DMS (18) detects a position of the user's ear. If the position of the user's ear moves, a controller (16) stops the adaptive operation, updates a transfer function of the first system auxiliary filter to a transfer function corresponding to a noise canceling position that matches the position of the user's ear, then gradually changes a transfer function of the adaptive filter to a transfer function corresponding to the matching noise canceling position, and resumes the adaptive operation after the change is completed.

The embodiment of the invention discloses a fault detection method for a self-adaptive noise reduction system of a range hood and the range hood. The fault detection method comprises the following steps: controlling a plurality of loudspeakers to sound in sequence; respectively acquiring a plurality of reference microphone sound pressure distribution signals acquired by each reference microphone when each loudspeaker sounds and a plurality of error microphone sound pressure distribution signals acquired by each error microphone when each loudspeaker sounds; and according to the plurality of reference microphone sound pressure distribution signals and the plurality of error microphone sound pressure distribution signals, whether each loudspeaker, each reference microphone and each error microphone have a function fault is judged. According to the embodiment of the invention, the fault source can be accurately positioned by combining test signal excitation and sound pressure analysis, the problem that the microphone type cannot be distinguished due to the fact that a traditional detection method only depends on a single physical signal is solved, and the method is particularly suitable for a multi-microphone and multi-loudspeaker self-adaptive complex active noise control system and has a wide application prospect. Accurate fault detection of the self-adaptive noise reduction system in the range hood is realized.

The invention relates to the technical field of intelligent control, in particular to a compressor unit working noise control system based on data analysis. The compressor unit working noise control system based on data analysis comprises a sound pressure segmentation demarcation module, a frequency band change extraction module, a sound energy concentration drifting module, a target frequency band locking module and an absorption execution triggering module. According to the method, fine division of a sound pressure trend in operation is realized by constructing a sound pressure change boundary, a frequency abrupt change region is extracted, a drift path with concentrated sound energy is captured, a target frequency position is screened according to frequency change direction consistency and time continuity, and a focusing frequency is further accurately corresponding to a control frequency band; the shielded area is adjusted in a linkage mode to achieve directional intervention and coverage control over a key noise propagation path, the frequency locking precision, the energy focusing stability, the dynamic response sensitivity and the synergistic effect efficiency of sound absorption shielding are improved, and therefore an active noise control system based on the characteristic evolution trend is established.

The invention discloses a method and a system for judging an iteration state of an active noise control system, and belongs to the technical field of active noise control. The method aims at solving the problems that an existing method depends on error signals for judgment, so that the judgment standard is fuzzy, and the accuracy is insufficient. According to the core scheme, monitoring of external error signals is abandoned, and essential analysis is conducted on the internal state of the algorithm. The method specifically comprises the steps of obtaining weight coefficients of all control filters of a system in real time; calculating the norm as a characteristic quantity; performing sliding window processing on the characteristic quantity; state indexes such as slope, variance and mean value change are calculated based on window data; and finally, judging whether the system is in a convergence or divergence state according to the indexes, and triggering stabilization operation during divergence. According to the method, the judgment standard is clearer and more accurate, and system hardware damage can be effectively prevented.

The application discloses a kind of vehicle active noise control systems and fusion method thereof, system includes acceleration sensor, microphone, speaker and controller, acceleration sensor, microphone and controller access vehicle A2B bus, controller also accesses vehicle CAN bus, controller includes engine noise active controller and road noise active controller, the sound signal picked up by microphone is output as error signal to engine noise active controller and road noise active controller respectively;Road noise active controller and engine noise active controller generate first excitation signal and second excitation signal using signal respectively, and controller outputs two excitation signals to corresponding speaker after fusion and runs.The vehicle active noise control system and fusion method thereof provided by the application realize the fusion of car ENC algorithm and RNC algorithm, reduce the consumption of computing power, and reduce the number and cost of vehicle microphones by sharing the same set of microphones.

The invention discloses a feed-forward active noise control system and method based on a synchronous identification strategy. The system comprises a secondary sound source synthesis subsystem, a sound feedback channel online identification subsystem, a secondary channel online identification subsystem, a first auxiliary filtering subsystem and a second auxiliary filtering subsystem. Meanwhile, by utilizing the first auxiliary filtering subsystem, the independence between the secondary sound source synthesis subsystem and the secondary channel online identification subsystem is improved, and user parameter selection and system implementation are facilitated; a residual noise component which is separated by the first auxiliary filtering subsystem and is related to a reference signal is used as input of a global auxiliary noise amplitude adjustment module, so that the contribution of introduced global auxiliary noise to residual noise is effectively reduced, and the overall noise reduction performance of the system is improved; according to the method, a synchronous identification strategy of the sound feedback channel and the secondary channel is adopted, complex time-varying characteristics of the sound feedback channel and the secondary channel in an actual environment can be effectively dealt with, and the noise reduction application level of the system is improved.

The invention provides an active noise control method and device based on frequency dynamic tracking and a storage medium, and belongs to the technical field of active noise control. Comprising the following steps: configuring an active noise control system comprising an FxLMS algorithm unit: sending a reference signal into an adaptive filter for processing, and adding a frequency correction weight coefficient into the reference signal by a frequency correction unit; the output of the adaptive filter is summed by the first comparison unit and then sent to the secondary channel unit to generate a secondary output signal; the reference signal is also sent to the secondary channel estimation unit to obtain a filtering reference signal and is sent to the FxLMS algorithm unit; the second comparison unit sends an error signal between the target narrow-band noise and the secondary output signal into the FxLMS algorithm unit; and the FxLMS algorithm unit performs adaptive iteration updating on the weight coefficients of the first adaptive filter and the second adaptive filter and the frequency correction weight coefficient of the frequency correction unit until the active noise control system converges.

The application discloses a substation active noise control system of semi-closed sound insulation structure, which combines passive sound insulation and active noise control technology, and comprises a semi-closed sound insulation structure, sound-absorbing material, a reference microphone, an error microphone, a secondary sound source and an adaptive control system; an opening is arranged on a side wall of the semi-closed sound insulation structure; the sound-absorbing material is arranged on the inner wall surface of the wall corresponding to the opening side of the semi-closed sound insulation structure, the sound-absorbing material is arranged in a gap mode corresponding to the inner wall surface, and the sound-absorbing material adopts a single-layer parallel type micro-perforated sheet of a sound-absorbing structure; the reference microphone is used for collecting a primary noise signal of a transformer at the opening; the error microphone is used for collecting a noise signal after cancellation; the secondary sound source is used for emitting a cancellation sound signal under the control of the adaptive control system; the adaptive control system receives the primary noise signal and generates a noise cancellation signal for eliminating noise by using an adaptive algorithm according to the primary noise signal; after digital-analog conversion, the output power of the secondary sound source is controlled, so that the substation noise can be effectively controlled.

An active noise control system is provided which uses a single microphone to cancel noise for multiple seats. A first seat noise control device (3) corrects sound picked up by the microphone (9) to sound at a listening position of a user seated at the first seat, uses the sound as an error, uses an adaptive filter with sound of a second seat audio source (2) as input to generate a cancellation sound which cancels sound of the second seat audio source (2) at the first seat, and outputs from a first seat speaker (7). A second seat noise control device (4) corrects sound picked up by the microphone (9) to sound at a listening position of a user seated at the second seat, uses the sound as an error, uses an adaptive filter with sound of the first seat audio source (1) as input to generate a cancellation sound which cancels sound of the first seat audio source (1) at the second seat, and outputs from a second seat speaker (8).

An active noise control system, an active noise control method and an engineering vehicle. The active noise control method is used for noise control in a noise suppression area of an engineering vehicle, and comprises: obtaining at least two sets of original noise data of different sources of an engineering vehicle on the basis of the current working mode of the engineering vehicle; performing partial coherence analysis on each set of original noise data on the basis of the at least two sets of original noise data, so as to obtain respective sets of decoupled noise data with the influence of other sets of original noise data eliminated; generating active noise reduction signals corresponding to the respective sets of decoupled noise data; generating a sound-emitting device drive signal on the basis of the active noise reduction signals corresponding to the respective sets of decoupled noise data; and on the basis of the current working mode, sending the sound-emitting device drive signal to a noise-suppression sound-emitting device located in or near a noise suppression region, such that the noise-suppression sound-emitting device emits a sound wave for suppressing noise in the noise suppression region.

Techniques are described herein for progressive training of a machine learning network for name embedding. Embodiments seek to refine embedding models so that automated name detection, automated attention handling, and other similar features can be applied to active noise control systems in a manner that is robust to noise and competing speech. Embodiments begin by training a foundation model based on a name detection paradigm. Progressive training is used, based initially on the foundation model, to teach progressive machine learning networks to generate unified embeddings for each of multiple linguistic classes robustly in the presence of noise and / or competing speech. Those networks are ultimately used to train a robust name embedding (RNE) model to produce target outputs (e.g., classifications, acoustic segments, etc.) according to the name detection paradigm.

This invention discloses a robust feedforward-type wideband and narrowband hybrid active noise control system and method, belonging to the field of active noise control technology. The system utilizes a first linear predictive filtering subsystem to synthesize narrowband and wideband reference signals, overcoming the frequency offset problem. By employing a second linear predictive filtering subsystem and an auxiliary filtering subsystem, the independence among the wideband secondary sound source synthesis subsystem, the narrowband secondary sound source synthesis subsystem, and the online identification subsystem of the secondary channels is improved, enhancing the accuracy and speed of online identification of the secondary channels and improving the overall system's dynamic performance. Simultaneously, the impact of introduced auxiliary noise on residual noise is reduced, improving the overall system's noise suppression performance. Furthermore, this invention utilizes an online identification module for the secondary channels, which can handle the complex time-varying nature of the secondary channels without requiring the installation of non-acoustic sensors, reducing physical space requirements and hardware costs, and broadening its practical noise reduction application range.

The invention discloses a method for controlling active noise of a portable small-flow oxygen generator, and the method comprises the following steps: S1, improving an oxygen generator model, and adding a fixing device for placing a loudspeaker and a microphone; s2, determining that the distance between the reference sensor and the error sensor is 60mm, and the distance between the loudspeaker and the error sensor is 5mm; s3, building an active noise control platform according to the layout of the loudspeaker and the microphone; s4, due to the fact that the propagation speed of the sound in the air is 343 m / s, the time of the reference signal propagating from the reference microphone to the error microphone is calculated to be about 0.175 milliseconds according to a formula; s5, judging the sound propagation time, wherein 0.05 ms is the time delay of the whole link of the active noise control system; and S6, installing the loudspeaker and the microphone according to the above steps, and carrying out a noise reduction test.

The application discloses a narrow-band feedforward-feedback hybrid active noise control system and method, and belongs to the technical field of active noise control. The system separates the narrow-band residual noise component related to the reference signal and the residual noise component unrelated to the reference signal from the residual noise by using an auxiliary filtering subsystem; the system separates the narrow-band residual noise component and the wide-band residual noise component from the residual noise component unrelated to the reference signal by using a linear prediction filtering subsystem; the system improves the independence among the feedforward active noise control subsystem, the feedback active noise control subsystem and the secondary path online identification subsystem by using the auxiliary filtering subsystem and the linear prediction filtering subsystem, improves the dynamic performance of the system, and introduces an auxiliary noise adjustment module to improve the noise suppression performance of the system. The application effectively reduces the narrow-band target noise components related to the reference signal and unrelated to the reference signal, improves the noise reduction performance, and widens the application range.