22results about How to "Improved noise suppression" patented technology

The invention relates to the technical field of wind power generation control, in particular to a generator device and a control method thereof. The method comprises the following steps of performing real-time monitoring on noise frequency, amplitude and phase when a generator device operates, and generating a noise characteristic data set; extracting the main frequency and phase characteristics of a noise source from the noise characteristic data set, and performing reverse analysis on the data to generate reverse sound wave signal data opposite to the phase of the noise source; and the reverse sound wave generating device transmits the reverse sound wave signal data to the generator device, outputs reverse sound waves through a broadband loudspeaker, superposes the reverse sound waves and original noise in the space, and monitors the noise after noise reduction in real time to obtain noise reduction effect feedback data. According to the invention, noise characteristics are monitored in real time, matched reverse sound wave signals are extracted and reversely generated, reverse sound wave characteristics are dynamically adjusted, closed-loop adaptive control is formed, and efficient and stable noise reduction of a generator device is realized.

The invention provides a signal noise suppression method and system, a storage medium and electronic equipment, and the method comprises the steps: obtaining the original data of a partial discharge signal of a switch cabinet, and carrying out the feature extraction of the partial discharge signal; performing noise suppression on the partial discharge signal after feature extraction, determining a signal-to-noise ratio and a mean square error, and judging the quality of a noise suppression effect according to the signal-to-noise ratio and the mean square error; and optimizing a noise suppression effect according to a comparison result of the noise-suppressed data and the noise-free signal. According to the invention, feature extraction is carried out on the partial discharge signal and then noise suppression is carried out, so that the accuracy of signal feature extraction is improved; the noise suppression effect is continuously optimized according to the comparison result of the data after noise suppression and the noiseless signal, and the noise suppression precision of the complex noise feature in the partial discharge signal of the switch cabinet is improved.

The invention discloses a combined preprocessing and fusion decoding method based on electroencephalogram signals and functional near-infrared signals, which comprises the following steps of: synchronously acquiring the electroencephalogram signals and the functional near-infrared signals, taking a task trigger event as a unified time reference, and carrying out basic preprocessing of time alignment and modal self-adaption on two modal signals to obtain a functional near-infrared signal; a pre-trained cross-modal noise joint modeling module is utilized to perform joint modeling on cross-modal joint noise features caused by a common noise source, collaborative denoising processing is performed on multi-modal signals based on the cross-modal joint noise features, multi-modal denoising representation is obtained, a cross-modal feature interactive modeling mode based on an attention mechanism is obtained, and the multi-modal noise is obtained. And dynamically modeling the correlation between different modal features, realizing deep fusion of multi-modal complementary information, carrying out decoding processing based on the fused features, and outputting a corresponding brain-computer interface control instruction or task identification result. According to the method, the decoding accuracy and robustness of the brain-computer interface system in a complex task scene are enhanced.

The invention relates to the technical field of power supplies, in particular to a signal processing system and electronic equipment. The signal processing system comprises a filter circuit and a debugging circuit. The filter circuit comprises a filter module and a control module; the filtering module is used for generating a first suppression signal after receiving a noise signal generated by a noise source; the control module is used for evaluating a target elimination signal matched with the noise signal and dynamically analyzing an error with the target elimination signal to generate a second suppression signal, and the first suppression signal and the second suppression signal serve as noise suppression signals; and the debugging circuit is used for acquiring an error between the noise suppression signal and the target elimination signal and performing gain adjustment processing on the filter circuit. Through the above mode, the precision of suppressing the noise signal of the switching power supply module can be improved, and the noise suppression signal can be adaptively and dynamically adjusted based on the noise signal, so that the generalization of the signal processing system is improved.

The application discloses a kind of active shock absorption and steady control system and method based on voice coil motor, it is related to mechanical vibration control technical field.The method is by obtaining the phase signal synchronous with excitation source, directly from waveform look-up table index and output opposite phase drive instruction, drive voice coil motor to generate counterforce.Meanwhile, the system uses the residual acceleration of non-causal filtering processing in background, and adaptively updates waveform look-up table.The application adopts feedforward control, avoids the phase delay caused by filtering in traditional feedback control, can accurately suppress high-frequency periodic vibration with very low delay, significantly improves operation comfort.

The application discloses the technical fields of measurement, and particularly discloses a kind of measurement circuit for detecting weak current in multi-channel nanopore system, it includes: overcurrent protection module, switch matrix module, R-TIA module, overvoltage protection module, signal processing module, signal acquisition module, DAC module;Overcurrent protection module input port is connected with nanopore, overcurrent protection module output port is connected with the input port of switch matrix module in series, the output port of switch matrix module is connected with the negative input port of R-TIA module in series, the output of R-TIA module is connected with the input port of overvoltage protection module, the output port of overvoltage protection module is connected with the negative input of operational amplifier OPA2 of signal processing module, signal processing module is connected with signal acquisition module;The output of DAC module is connected with the positive input of operational amplifier OPA2 in R-TIA module and signal processing module respectively.

The invention discloses a wide-narrow band hybrid active noise control system and method with acoustic feedback compensation, and belongs to the technical field of active noise control. According to the system provided by the invention, the acoustic feedback compensation subsystem is adopted, so that the influence of acoustic feedback on a reference signal is effectively overcome, and the quality of the reference signal is improved; a wide-narrow band reference signal synthesis structure based on the combination of a front serial self-adaptive band-pass filter and a rear parallel self-adaptive band-pass filter is adopted to obtain a wide-band reference signal and a narrow-band reference signal to respectively provide reliable input for a wide-band secondary sound source synthesis subsystem and a narrow-band secondary sound source synthesis subsystem; therefore, the stability, convergence and noise reduction performance of the system are improved on the whole. The system provided by the invention can cope with non-stably changed wide-narrow band mixed target noise. The system provided by the invention does not need a non-acoustic reference microphone, so that not only is frequency deviation avoided, but also the hardware cost of the system is reduced, and the practical application range of the system is widened.

The application discloses an optical power collection device and method, relates to the technical field of optical signal detection, and comprises the following: a photoelectric detector for converting an optical signal into a current signal; a transimpedance amplifier for converting the current signal into a pulse voltage signal; a peak detector for detecting the peak value of the pulse voltage signal; an RC filter network for filtering noise of the pulse voltage signal; a low-frequency amplifier for amplifying the low-frequency pulse voltage signal; an ADC collection module for converting the amplified pulse voltage signal into a digital signal; a first feedback network for adjusting the gain of the transimpedance amplifier; a second feedback network for adjusting the gain of the low-frequency amplifier; and a microcontroller for controlling the first feedback network to adjust the gain of the transimpedance amplifier according to the peak value of the pulse voltage signal and for controlling the second feedback network to adjust the gain of the low-frequency amplifier according to the digital signal.

The utility model relates to a stable power supply device for an airborne multispectral photoelectric system. The stable power supply device comprises an input filtering anti-reverse circuit, a peak surge suppression circuit, a DC-DC conversion circuit, a voltage acquisition reporting circuit and an output filtering circuit which are connected in sequence, the peak surge suppression circuit comprises a normal switching stage peak loop, an input power supply switching power-on loop and an ultrahigh peak power supply loop. The DC-DC conversion circuit comprises a first path of non-isolated output P1 and a second path of isolated output P2. According to the stable power supply device, on one hand, the dynamic response of the power supply is improved, the stability of the power supply is greatly improved, and meanwhile, the output precision and the anti-interference capability are improved.

The application discloses a power supply noise suppression circuit of a voltage-controlled oscillator, which comprises a power supply input end, a mean value unit, a noise sampling unit, an integral unit and a proportional addition unit, wherein the power supply input end provides an input voltage; the mean value unit is connected with the power supply input end, and the mean value unit obtains a power supply voltage average value according to the input voltage; the noise sampling unit is connected with the power supply input end and the mean value unit respectively, so as to obtain a power supply voltage instantaneous value according to the input voltage, and obtain a noise signal according to the difference between the power supply voltage average value and the power supply voltage instantaneous value; the integral unit is connected with the noise sampling unit, and the integral unit processes the noise signal to obtain a compensation signal; the proportional addition unit is connected with the integral unit, so as to obtain a voltage control signal of the voltage-controlled oscillator after the compensation signal is compensated; thus, the noise suppression effect is good, and the on-chip integration is easy.

The application provides a motor efficiency reduction heating control method and device and a vehicle. The optimal balance between efficiency and noise is achieved by shortening the noise deterioration interval and combining real-time feedback adjustment. The method comprises the following steps: in response to the motor efficiency reduction heating function being turned on, determining the motor efficiency reduction heating target speed under the current driving working condition; before the target speed of the motor changes to the efficiency reduction heating target speed, reading a set of noise reduction parameters matched with the current driving working condition from the pre-stored control parameter set and preloading; making the current target speed of the motor change to the efficiency reduction heating target speed according to a preset rule; during the current target speed changing process and the running stage after reaching the efficiency reduction heating target speed, collecting the running state feedback signal of the motor in real time and constructing an evaluation function; taking the noise reduction parameters as optimization variables, and taking the minimum value of the evaluation function as the optimization target, the specific value of the noise reduction parameters is adjusted in real time within the preset parameter constraint range of the noise reduction parameters.

The invention discloses a multi-channel noise suppression method based on a two-stage deep complex network, and the method comprises the steps: constructing a deep complex gating convolution attention network, and carrying out the correlation modeling of a complex frequency spectrum; enhancing a multi-channel noisy signal by using a two-stage deep complex network; in the beam forming stage, amplitude and phase enhancement is carried out on the multi-channel complex spectrum, and a single-channel complex spectrum with coarse noise reduction is obtained; and in the post-filtering stage, refining processing is carried out on the single-channel complex frequency spectrum subjected to coarse noise reduction, and noise is further suppressed. According to the method, a noise suppression task is divided into a beam forming stage and a post-filtering stage through a two-stage enhancement strategy, the problems of noise residue and target sound signal distortion are effectively avoided, in addition, a complex frequency spectrum is modeled by adopting a complex network structure in the two-stage network, and the noise suppression efficiency is improved. Meanwhile, the amplitude and phase information of the signal are enhanced, the phase distortion is reduced, and the quality and naturalness of the signal are improved.

The application discloses a linear voltage stabilizing circuit based on NMOS regulating tube, comprising a bias voltage generating circuit, a voltage division feedback circuit, an oscillator circuit, a charge pump circuit and a pre-voltage stabilizing circuit, wherein the bias voltage is generated through the bias voltage generating circuit; the output voltage is divided to obtain a feedback voltage through the voltage division feedback circuit; the feedback voltage is amplified and then input to the oscillator circuit to generate an oscillation signal; the generated oscillation signal is input to the charge pump circuit; the gate voltage of the NMOS regulating tube is adjusted through the charge pump circuit, so as to obtain the output voltage; the pre-voltage stabilizing circuit widens the input voltage range, so that the linear voltage stabilizing circuit can work in a high input voltage environment; the linear voltage stabilizing circuit based on the NMOS regulating tube has the characteristics of wide input range and low voltage difference, fast transient response speed, and is fully compatible with the thin gate oxide process.

The present application relates to the technical fields of electromagnetic noise suppression, and relates to a brushless motor electromagnetic noise suppression method and system based on harmonic current injection, comprising: confirming a noise brushless motor and a motor monitoring device, obtaining motor data of the noise brushless motor, using the motor monitoring device to analyze the noise of the noise brushless motor, obtaining a motor noise signal, performing frequency spectrum feature analysis on the motor noise signal, obtaining noise order, electromagnetic noise amplitude and electromagnetic characteristic frequency, performing phase-sensitive detection on the motor noise signal based on the noise order, the electromagnetic characteristic frequency and the electric angle time signal, obtaining the motor relative phase, performing adaptive fine tuning on the preliminary harmonic current data set based on the motor monitoring device and the vector voltage time signal set, obtaining a target harmonic signal set, performing harmonic injection on the noise brushless motor based on the target harmonic signal set, obtaining a noise suppression motor, and completing electromagnetic noise suppression of the brushless motor. The present application can reduce the electromagnetic noise level of the brushless motor.

The invention belongs to the technical field of vibration noise control, and particularly relates to a two-dimensional acoustic focusing structure based on a sound wave black hole effect, which comprises an upper structural plate, a lower structural plate and a sound wave black hole structure, an air domain is formed between the upper structural plate and the lower structural plate, and the bottom end of the sound wave black hole structure is arranged on the plates and used for gathering and dissipating sound waves. An existing one-dimensional sound wave black hole technology is expanded to a two-dimensional structure, incident waves are gradually gathered to the central area of the black hole, and therefore the sound wave focusing capacity of the two-dimensional structure is improved.

The application provides a semiconductor test image denoising method and system based on Taylor expansion, and relates to the technical field of image processing.The method flow is as follows: an array test image of a semiconductor is acquired, and frequency domain analysis is performed on the array test image to obtain periodic characteristics and directionality characteristics of the array; a structure-aware Taylor expansion model is constructed based on the periodic characteristics and the directionality characteristics of the array; a structure-aligned sampling network is established based on the periodic characteristics and the directionality characteristics of the array, and pixel reconstruction is performed based on the structure-aware Taylor expansion model to obtain pixel reconstruction values; multi-scale image fusion is performed based on all the pixel reconstruction values to obtain a final denoised image.The application realizes effective suppression of complex noise while perfectly maintaining the periodicity and directionality structure characteristics of the semiconductor array through the structure-aware Taylor model and intelligent multi-scale fusion.

The application provides an airborne wind measurement laser radar dynamic adaptive attitude-position collaborative compensation system and method which can dynamically adapt to flight states and accurately couple attitude and position interference. The system comprises a GNSS positioning module (1), a MEMS-IMU attitude sensing module (2), a two-stage coordinate conversion module (3), a dynamic speed solving module (4), an adaptive collaborative compensation module (5) and a laser radar wind measurement module (6). The method comprises the following steps: S1, multi-source data synchronous acquisition, S2, ECEF coordinate system conversion, S3, ENU coordinate system conversion, S4, dynamic speed solving, S5, dynamic weight adaptive compensation, S6, data output and feedback storage. The application is applied to the technical field of wind measurement laser radar.

A cultivated land edge refinement detection method based on semantic guidance of RoI attention comprises the following steps: preparing high-resolution remote sensing image data containing intensive agricultural plots, and carrying out standardization and noise suppression preprocessing on the high-resolution remote sensing image data; the method comprises the following steps: constructing a shared encoder-double parallel decoder multi-task model, extracting multi-scale features through a shared encoder, outputting a cultivated land area semantic probability graph by using a semantic segmentation decoder, and outputting an initial edge strength graph by using an edge detection decoder; based on the semantic probability graph, generating a dynamic multi-scale RoI mask adaptive to the irregular form of the cultivated land through binarization, morphological optimization and adaptive resolution adjustment; semantic intermediate features and edge intermediate features are extracted, channel cascade fusion is carried out, differential modulation is carried out on the fusion features through an RoI attention mechanism, cultivated land area edges are focused, non-cultivated land noise is inhibited, and a refined edge intensity graph is output through detail optimization; and performing non-maximum suppression, fracture edge completion and vectorization processing on the refined edge graph to generate cultivated land edge vector data meeting geographic information business requirements. According to the method, deep collaboration of semantic information and edge features is realized, the omission ratio and the false detection ratio are greatly reduced, the method is adaptive to diversified cultivated land scenes such as fragmentation and connection, and refined detection of cultivated land edges is realized.

The disclosed embodiment is about a method and electronic device for noise suppression, including: downsampling a speech signal; preprocessing the speech signal within the sampling rate to divide the speech signal into multiple sub-bands; normalizing the speech data corresponding to each sub-band; inputting the speech data of each sub-band into the pre-trained target neural network model corresponding to each sub-band to obtain multiple groups of result data corresponding to each sub-band; synthesizing the multiple groups of result data to obtain the final noise suppression result. In this embodiment, by decomposing the speech signal into different sub-bands, constructing different deep learning networks for processing different sub-bands, and finally synthesizing the noise suppression results of each sub-band, it is more refined and has a better noise suppression effect.

The application provides a tablet touch signal recognition and processing method. Through a dynamic noise suppression formula, a time attenuation factor and an adaptive adjustment coefficient are used to realize dynamic adjustment of noise suppression strength according to signal time characteristics and strength. Compared with the existing static filtering algorithm, the noise suppression effect is improved by more than 30%, and the signal distortion rate is reduced to less than 5%. According to a feature adaptive fusion weight formula, feature weights are dynamically allocated according to real-time interference strength. In the interference scene of water stains, dust and the like, the recognition accuracy still remains more than 95%, which is improved by 15-20% compared with the fixed weight fusion algorithm. A dynamic decision threshold formula combines real-time confidence and historical correct recognition rate to avoid the scene adaptation defects of the fixed threshold. A fuzzy classification judgment formula solves the fuzzy judgment problem of the touch signal. The average delay of the whole signal processing process is controlled within 8 ms, which is reduced by more than 40% compared with the prior art (15-20 ms), and the fluency of touch response is improved.

The present application belongs to the technical field of medical image processing, and proposes a brain function image noise suppression method based on space-time features. The present application provides a brain function image noise suppression method and system based on space-time features. Compared with the traditional noise suppression method, the present application aims to independently implement targeted noise elimination and signal enhancement in the time domain and the spatial domain. Compared with the existing method which only focuses on global changes and overall trends, the present application adds a sliding window to process the segmented time-varying features, and uses methods such as independent covariate regression to effectively identify and remove the noise of the time and space features, thereby achieving better noise suppression effect.

Provided are a rotor, a motor, and a wiper motor with which it is possible to inhibit an increase in operating noise and deterioration in rotor characteristics, and to reduce material cost for permanent magnets. An arc center C2 of an outer circumferential surface 32b of a rotor core 32 and an arc center C3 of an inner circumferential surface 33b of a permanent magnet 33 are off-centered radially outward from a rotational axis C1, with the circumferential center disposed on the radially outermost side. An angle θ1 formed by salient pole side surfaces 35a facing each other of circumferentially adjacent two salient poles 35 is equal to an angle θ2 formed by magnet side surfaces 33a on both sides circumferentially of the permanent magnet 33. When the distance between the outer circumferential surface 32b of the rotor core 32 and the radially outermost end of the salient poles 35 is Lt, and the distance between the inner circumferential surface 33b of the permanent magnet 33 and the radially outermost end of the magnet side surfaces 33a is Lme, the distances Lt, Lme are set such that the relationship Lme < Lt is satisfied.