33 results about "Reference noise" patented technology

The invention provides an active noise reduction method capable of restraining divergence and a microphone vibration reduction device, belongs to the technical field of automobile active noise reduction, and detects the sealing condition of a cab through automobile door sensors, automobile window sensors and skylight sensors. If the microphone is closed, noise signals are collected by using errors on the microphone vibration damping device and a reference microphone, and secondary noise signals are generated by an active noise reduction filter and are played by a loudspeaker; if yes, the engine rotating speed in the vehicle CAN signal is read, and a reference noise signal is generated and played. A cab sealing state and an active noise reduction system operation state are displayed on an instrument panel, and the operation state is determined according to noise signal acquisition and noise reduction signal playing conditions. The noise reduction mode can be automatically switched according to the cab sealing state, the noise in the vehicle is effectively reduced when the cab is sealed, the reference noise is reasonably played when the cab is opened, and the influence on the robustness of a system filter is reduced. Related information is displayed on the instrument panel, so that a user can visually know the cab state and the system operation condition.

The invention discloses a multi-mode composite fault diagnosis method and system for a variable-frequency asynchronous motor. The method comprises the following steps: synchronously acquiring a vibration acceleration signal X, a rotating speed signal R and a current signal D of the variable-frequency asynchronous motor; performing adaptive noise reduction on the vibration acceleration signal X by using a rotating speed driven harmonic wavelet packet-variational mode decomposition method to obtain a reconstructed signal Y; filtering the current signal D through dual-mode collaborative filtering and soft reference noise, and outputting a noise reduction signal S through dual-channel fusion processing; extracting a pass frequency speed effective value and an acceleration kurtosis from the reconstructed signal Y, and extracting a current effective value, a peak coefficient, a degradation coefficient and a harmonic distortion sequence from the noise reduction signal S; vibration, rotating speed and current characteristics are fused to set expert mechanism model rules, and fault types are output according to the rules. The early weak fault sensitivity can be improved, and accurate, real-time and automatic early warning of composite faults such as bearing damage, rotor bar breakage and air gap eccentricity under complex working conditions can be realized without manual intervention.

The application provides a high-density surface electromyography signal hardware filtering device and method based on FPGA, comprising: an sEMG signal input module for collecting multi-channel noisy surface electromyography signals and at least one reference noise signal; an LMS adaptive filtering calculation module for receiving the noisy surface electromyography signals and the reference noise signal, adopting a fixed-point number operation system and executing an LMS adaptive filtering algorithm through a parallel pipeline structure to output a filtered error signal; a data buffer and output interface module for buffering and outputting the filtered surface electromyography signals; and an FPGA main control module connected with the sEMG signal input module, the LMS adaptive filtering calculation module and the data buffer and output interface module for controlling the work of each module. The application realizes the LMS adaptive filtering algorithm on the FPGA platform, and solves the problems of insufficient real-time performance and large processing delay of software filtering when facing high-density multi-channel sEMG signal processing.

The invention relates to the technical field of intelligent sensing systems, and discloses a method and a device for detecting the bearing capacity of a pavement engineering construction material, and the method comprises the steps: synchronously collecting a mixed signal and a pure noise signal through a main measurement sensor and a reference noise sensor, constructing a multi-dimensional observation matrix, and carrying out the centralization and whitening preprocessing, thereby obtaining the bearing capacity of the pavement engineering construction material. And blind source separation is carried out by adopting an independent component analysis algorithm based on maximized non-Gaussian property, a target bearing capacity response signal with a super Gaussian characteristic is identified according to a kurtosis value of each source signal component, and then a dynamic deformation modulus is calculated. The system comprises a sensor array module, a synchronous acquisition module, a data processing module based on FPGA hardware acceleration and a result output storage module. According to the invention, strong coherent vibration noise can be effectively suppressed, signal details are completely reserved, and high-precision and real-time bearing capacity detection is realized.

The application relates to a vehicle sealing performance detection method and device, a vehicle, a storage medium and a product. The method comprises the following steps: acquiring original acoustic signals collected by a main microphone array arranged in a to-be-detected area of a vehicle and reference noise signals collected by a reference microphone array arranged in a reference area of the vehicle; performing background noise filtering processing on the original acoustic signals based on the reference noise signals to obtain target acoustic signals; extracting target acoustic features corresponding to the target acoustic signals; determining a feature similarity between the target acoustic features and reference acoustic features corresponding to a current running state of the vehicle; and in a case where the feature similarity is smaller than a similarity threshold, determining a sealing performance detection result of the to-be-detected area according to the target acoustic features. The method can continuously and comprehensively detect the sealing performance of the vehicle during driving.

The invention provides a multi-channel synchronous sampling system for weak current detection and a control method thereof. According to the method, a low-noise trans-impedance amplifier array is used for converting multiple paths of weak current signals into multiple paths of analog voltage signals; at least one reference channel for outputting reference noise data; the synchronous analog-to-digital conversion array is used for synchronously sampling the multi-path analog voltage signals and the reference noise data after receiving the global conversion starting signal sent by the field programmable gate array, and converting the multi-path analog voltage signals and the reference noise data into multi-path synchronous first digital data to be output; the field programmable gate array is used for receiving the first digital data and carrying out delay compensation and amplitude correction on the first digital data to obtain multiple paths of time-aligned and amplitude-normalized second digital data; and a filter for referencing the first digital data converted from the reference noise data and eliminating the common-mode noise component in the second digital data to output purified third digital data.

The present application provides a signal processing method and a related apparatus. The method comprises: acquiring N quantized audio features of raw non-speech audio, wherein N is a positive integer greater than or equal to 1; determining a first predicted silence audio feature based on the N quantized audio features and reference noise; and determining, based on the first predicted silence audio feature and a first neural network, first non-speech audio corresponding to the raw non-speech audio.

This invention provides an active noise cancellation method and microphone vibration damping device that suppresses divergence, belonging to the field of automotive active noise cancellation technology. It detects the cabin's sealing status using sensors on the doors, windows, and sunroof. If sealed, noise signals are collected using the error on the microphone vibration damping device and a reference microphone. These signals are then processed by an active noise cancellation filter to generate a secondary noise signal, which is played through a speaker. If open, the engine speed is read from the vehicle's CAN signal to generate a reference noise signal, which is also played. The dashboard displays the cabin sealing status and the active noise cancellation system's operating status, determined based on the noise signal collection and noise cancellation signal playback. This invention automatically switches noise cancellation modes according to the cabin's sealing status, effectively reducing interior noise when sealed and appropriately playing reference noise when open, minimizing the impact on the system filter's robustness. Relevant information is displayed on the dashboard, allowing users to intuitively understand the cabin status and system operation.

The invention relates to a pressure sensor and a sensor. The pressure sensor comprises a sensor element (WB) in the form of a Wheatstone bridge and having four piezoresistive resistors (R1, R2, R3, R4), and a reference element (RW) in the form of a reference Wheatstone bridge and having four piezoresistive reference resistors (R5, R6, R7, R8), the reference resistors (R5, R6, R7, R8) being arranged in the same way as the resistors (R1, R2, R3, R4), the pressure sensor being arranged on a single crystal and comprising a cavity closed on one side by a diaphragm, the resistors (R1, R2, R3, R4) being arranged at least partially on the diaphragm, the reference resistors (R5, R6, R7, R8) not being arranged on the diaphragm, the first to fourth resistors (R1, R2, R3, R4) respectively being identical to the fifth to eighth resistors (R5, R6, R7, R8) in that they are constructed in the same way, and the reference Wheatstone bridge (RW) serving as a reference noise source for subsequent signal processing.

The application discloses a continuous monitoring single-arm multi-modal acquisition system and a feature fidelity denoising method, and relates to the physiological signal monitoring technical field.The system comprises an electrocardiosignal acquisition module, a multi-modal signal acquisition module, a communication module, a power module and an upper computer.The method is applied to the system and specifically comprises the following steps: taking a motion signal as a reference input, modeling and adaptively suppressing motion noise in an electrocardiosignal to obtain a signal after preliminary denoising; and inputting the signal after preliminary denoising and reference noise information into a pre-trained reconstruction model to generate a reconstructed signal.The application overcomes the technical problem that it is difficult to balance portability and signal acquisition quality in an existing off-site scene.The application can be widely applied to the physiological signal monitoring technical field.

The invention discloses a receiving sensitivity testing method and system based on a Bluetooth HCI command and conduction isolation, and relates to the technical field of wireless communication testing. The method comprises the following steps: constructing an electromagnetic shielding test environment, and carrying out system calibration in the test environment to obtain a power calibration value and an inherent loss value; measuring background noise power of each channel, and determining an optimal test channel and a power compensation factor in combination with a reference noise threshold; according to the Bluetooth communication protocol physical layer parameters and the target packet error rate, determining the number of theoretical transmitted data packets, and calculating a judgment threshold of the number of successfully received data packets; searching a critical attenuation value, iteratively adjusting the attenuation value of the programmable attenuator according to a judgment threshold value, and adjusting an attenuation step value according to the change rate of the number of successfully received data packets; and calculating the final receiving sensitivity based on the power calibration value, the inherent loss value, the critical attenuation value and the power compensation factor. By optimizing electromagnetic shielding, channel selection and three-stage scanning, the accuracy of receiving sensitivity testing is improved.

This application relates to a method, apparatus, and computer device for cross-domain adversarial example detection. The method includes: acquiring an unknown sample set and the signal-to-noise ratio (SNR) of the transmission channel for each unknown sample in the unknown sample set; filtering adversarial examples and samples to be detected from the unknown sample set according to a preset reference noise distribution; inputting the samples to be detected into multiple pre-trained adversarial detection models to obtain multiple adversarial probabilities for the samples to be detected; the adversarial detection models are used to predict the probability that the sample to be detected is an adversarial example, and different adversarial detection models target different types of interference; and obtaining the adversarial detection result of the sample to be detected based on the SNR of the transmission channel of the sample to be detected and the adversarial probabilities of the sample to be detected. This method can improve the accuracy of adversarial example detection.

This specification provides one or more embodiments of an in-vehicle audio equalization method, apparatus, storage medium, and program product. The method includes: acquiring a background noise signal of the current in-vehicle environment and determining the gain difference spectrum of the background noise signal relative to a reference noise signal of a quiet environment; performing track-by-track processing on the currently playing media audio signal to obtain multiple independent audio tracks corresponding to different frequency ranges; for each independent audio track, determining a corresponding gain adjustment amount from the gain difference spectrum based on its frequency range, and applying a corresponding gain adjustment to the independent audio track when the gain adjustment amount meets a gain condition; merging the signals of each independent audio track to output as a processed media audio signal, thereby improving speech clarity and music listening experience while significantly improving the accuracy and naturalness of audio equalization.

The invention relates to the technical field of deep groove bearing detection, in particular to a deep groove bearing rolling body surface defect detection method and system. Through layered vibration signal acquisition, low-frequency reference noise self-adaptive elimination and rolling body motion trail modeling, accurate detection of micron-sized defects on the surface of a deep groove bearing rolling body is realized, different signal channels of the rolling body and a bearing seat are effectively covered by constructing a multi-source vibration sensing layered acquisition system, and the detection precision of the deep groove bearing rolling body is improved. By synchronously acquiring low-frequency reference noise and high-frequency micro-impact signals and performing self-adaptive time domain noise cancellation, interference such as equipment background noise and gear meshing is remarkably suppressed, a rolling body motion and impact pulse correlation model is established by using structural parameters and real-time rotation parameters, and pure micro-impact signals are directionally enhanced, so that the precision of the rolling body motion and impact pulse correlation model is improved. Through multi-dimensional feature extraction and three-dimensional closed-loop analysis, accurate positioning and authenticity verification of defect features are realized, and graded early warning of rolling body surface defects is completed in combination with a defect grade threshold and an early warning rule.

The application provides a lower limb movement state electroencephalogram movement artifact removal method, equipment and a storage device, the corresponding electromyogram reference noise is estimated according to the movement speed and speed change of the lower limb; the movement artifact is preliminarily eliminated through adaptive noise cancellation to the electromyogram reference noise; the signal processed through the adaptive noise cancellation is subjected to variational mode decomposition, and the intrinsic mode function of each order variable is obtained; the intrinsic mode function of each order is subjected to independent component analysis, and the independent component is obtained; the time domain feature, the frequency spectrum feature and the intersequence similarity of the independent component are calculated, then the artifact is identified and removed through hierarchical clustering identification, and the remaining components are reconstructed to obtain the processed independent component, i.e. the reconstructed electroencephalogram signal. The application has the beneficial effect that the interference caused by electromyogram noise when the lower limb speed changes can be quickly responded.

The invention discloses a signal noise reduction and power supply optimization method for an earphone internal circuit, and the method comprises the core steps: collecting a real-time power supply voltage, a real-time interference signal frequency, a real-time circuit temperature and a real-time load resistance based on a synchronous collection time sequence control logic, correcting a reference noise reduction coefficient based on a parameter coupling effect, and obtaining a dynamic noise reduction coefficient; and adjusting the reference power supply current based on the dynamic noise reduction coefficient and the real-time load resistance to obtain a self-adaptive power supply current, and calculating a noise reduction-power supply comprehensive performance index based on the dynamic noise reduction coefficient and the self-adaptive power supply efficiency. According to the method, through synchronous acquisition and multi-parameter coupling linkage adjustment, the core problem of independent optimization of noise reduction and power supply in the prior art is solved, collaborative adaptation of noise reduction and power supply is realized, and the operation stability of an earphone circuit is improved.

The invention relates to a terminal self-judgment fast random access method, which is applied to a terminal and comprises the following steps of: after random selection of an access opportunity is completed and before a random access preamble message is sent, transmitting an own IMEI Z sequence on an access declaration resource corresponding to the selected access opportunity, simultaneously and synchronously receiving signals on the noise measurement resource and the access declaration resource corresponding to the access opportunity; measuring the reference noise power according to the signal on the noise measurement resource, and calculating the own signal power according to the signal on the access declaration resource; performing access conflict judgment according to the reference noise power and the self signal power; and selecting a proper random access flow according to a conflict judgment result. According to the invention, the access speed of the terminal can be accelerated.

The invention discloses a method for improving phase noise through double-loop mixing, and relates to the technical field of phase noise improvement, and the method comprises the following steps: enabling a reference signal and the output of a controlled voltage-controlled oscillator (VCO) to form a first phase-locked loop, namely a main loop, through a first phase detector PD-A and a first loop filter LF-A, and carrying out the closed-loop locking of the VCO; the output branch of the VCO is sent to a frequency mixer, and the output of the VCO is mixed with a reference signal or a frequency multiplication signal and a frequency division signal of the reference signal to obtain a frequency mixing signal; and inputting the frequency mixing signal into a second phase detector PD-B and forming a second feedback path, namely an auxiliary ring, through a second loop filter LF-B, wherein the feedback quantity of the auxiliary ring is injected into or adjusts the control end of the VCO or is injected into a phase-locked frequency divider ILFD to realize tuning of the VCO. Through a mixing complementary double-ring structure, the balance of the noise suppression capability of a single ring in different offset ranges is broken through, reference noise and parasitic response introduced when the bandwidth of the single loop is expanded are avoided, and meanwhile, the problem that only harmonic injection or single injection path is difficult to cover the whole spectrum is solved.

The application discloses a kind of steel rail surface damage multichannel magnetic flux leakage detection signal denoising methods, with steel rail surface multichannel magnetic flux leakage signal as input: first, the original magnetic flux leakage signal of each channel is decomposed into several intrinsic mode components using VMD, adaptive separation of noise and damage characteristics is realized, and the component selection method based on distance correlation coefficient is used to remove the component mainly containing noise;Second, the remaining components are denoised by the reference noise elimination algorithm of distance correlation coefficient and normalized energy;Finally, the remaining components after denoising are reconstructed to obtain the denoised magnetic flux leakage signal.The method provides a better denoising method for screening and identifying the magnetic flux leakage signal of rail surface defects, significantly improves the signal-to-noise ratio and reduces the root mean square error, and significantly removes the magnetic flux leakage vibration noise.

The invention relates to the field of image processing, in particular to a transformer substation intrusion target cross-modal tracking system fusing vision and acoustics, which comprises a vision monitoring module, an acoustics monitoring module and a filtering tracking module. And the vision module obtains a target azimuth angle by using a camera image and Kalman filtering. The acoustic module collects sound through a microphone array, obtains an observation azimuth angle and a denoising azimuth angle by adopting a random denoising and time delay estimation positioning method, and records the difference between the observation azimuth angle and the visual filtering angle and between the denoising azimuth angle and the visual filtering angle. The filtering tracking module adaptively judges the fusion opportunity by analyzing the difference between the distribution characteristic of the recorded difference and the visual tracking error characteristic; and then taking average noise extracted by historical effective denoising operation as reference noise and removing the reference noise, and finally fusing an acoustic azimuth angle and a visual azimuth angle to realize accurate tracking. According to the invention, the problem of unreliable tracking of a single sensor in a complex environment is solved, and robust, continuous and automatic tracking of an intrusion target is realized.

The invention relates to an active noise reduction method and device with adjustable noise reduction intensity of equipment, computer equipment and a medium, and the method comprises the steps: obtaining a reference noise signal and an error noise signal of the equipment; obtaining a noise reduction intensity adjustment coefficient based on the signal intensity of the reference noise signal; updating the reference noise signal according to the noise reduction intensity adjustment coefficient to obtain an updated reference noise signal; according to the error noise signal and the updated reference noise signal, an FXLMS algorithm is adopted, and active noise reduction secondary sound waves are generated. In the whole process, the noise reduction intensity adjustment coefficient is determined based on the signal intensity of the reference noise signal to adapt to different noise reduction intensity environments, so that the adaptability of active noise reduction of the whole equipment is good. In addition, the invention further provides the range hood, an active noise reduction module is arranged in the range hood, the active noise reduction module carries out active noise reduction by adopting the active noise reduction method capable of adjusting the noise reduction intensity of the equipment, and effective active noise reduction can be achieved.

This invention discloses a continuous monitoring single-arm multimodal acquisition system and a feature-fidelity denoising method. The system includes: an electrocardiogram (ECG) signal acquisition module, a multimodal signal acquisition module, a communication module, a power supply module, and a host computer. The method, applied to the system described above, specifically includes: using a motion signal as a reference input, performing online modeling and adaptive suppression of motion noise in the ECG signal to obtain a pre-denoised signal; inputting the pre-denoised signal and reference noise information into a pre-trained reconstruction model to generate a reconstructed signal. This invention overcomes the technical problem of balancing portability and signal acquisition quality in existing out-of-hospital scenarios. This invention can be widely applied in the field of physiological signal monitoring technology.

The invention relates to a time-frequency dual-robust filtering method for demagnetization diagnosis of a permanent magnet motor, which belongs to the field of fault diagnosis of the permanent magnet motor, and comprises the following steps: loading an original signal of the permanent magnet motor, and carrying out time-domain filtering through a self-adaptive Hampel filter; framing windowing processing: converting the signal after time domain filtering into a frequency domain signal; training a Gaussian process regression model by using a normal sample; calculating a reference noise spectrum; performing frequency domain depth noise reduction by adopting a weighted spectral subtraction method; and reconstructing the filtered signal. According to the invention, sudden abnormal values and pulse interference can be effectively eliminated; and frequency domain deep noise reduction is carried out through weight spectrum subtraction, so that deep suppression can be carried out in a strong noise frequency band, and weak suppression or reservation can be carried out in a weak noise frequency band and a frequency band possibly containing fault characteristics. According to the method, weak characteristic components related to demagnetization faults can be reserved and even enhanced while background noise is restrained to the maximum extent, loss of diagnosis information is fundamentally avoided, and the diagnosis reliability is improved.

The application provides a DAS signal denoising method, device, medium and product, relates to the technical field of signal processing, and the method comprises the following steps: when a target vibration signal meets an abnormal feature, denoising strategies are executed in turn according to priorities. The execution process comprises the following steps: reference noise data is used to denoise the signal, the denoised signal is input into a neural network classifier, and the maximum classification probability value output by the neural network classifier is used as a denoising score. If the denoising score obtained by a certain strategy exceeds a preset threshold value, subsequent strategies are immediately stopped, and the denoised signal and the classification result corresponding to the strategy are output as the final result. If all the strategies are executed and none of the denoising scores exceeds the threshold value, the signal and the classification result corresponding to the strategy with the highest denoising score are selected as the final result. The scheme solves the technical problem that the denoising effect of a monitoring signal is poor when a spatial reference noise denoising scheme is used for a DAS system that encounters large-scale and continuous environmental noise interference.

The application relates to the technical field of signal filtering, in particular to an ultrasonic signal common-mode noise balance filtering system and method in a strong noise environment, which comprises the following steps: collecting a mixed signal and a reference noise signal in a strong noise environment; dividing the reference noise signal in a preset time window into intervals, analyzing the confusion degree of the frequency spectrum of the reference noise signal in each interval, combining the propeller rotating speed of a UAV to determine the characteristic coefficient of each time window; analyzing the number distribution of the frequency spectrum peak points of the reference noise signal in each time window to determine the characteristic index of each time window; adjusting the step of the adaptive filtering algorithm; and using the adaptive filtering algorithm and a noise cancellation algorithm to obtain the ultrasonic signal after noise elimination and the balance noise signal. The application can more accurately perform noise cancellation in a strong noise environment and improve the recovery effect of the ultrasonic signal.

The application relates to a circuit structure and working method of a micro gas sensor array, and belongs to the technical field of integrated circuits. The circuit structure comprises a multiplexer (MUX), a programmable gain amplifier (PGA), a low-pass filter (LPF), a driver (Drive), a successive approximation register analog-to-digital converter (SAR ADC), a digital control module (Digital Control) and an IIC interface for communication. In view of the demand for high precision and strong robustness of sensor signals, a common-source common-gate floating reverse dynamic amplifier is adopted in a SAR ADC noise shaping circuit, so that the insensitivity of the circuit to process, voltage and temperature (PVT) changes is significantly improved; the number of voltage-controlled delays in a time domain comparator (COMP) is increased, so that input reference noise is reduced; a hundred-nanosecond-level super-long delay module (DELAY) is integrated after asynchronous SAR logic, so that SAR ADC sampling errors are effectively reduced, and the measurement precision of the whole system is improved.

The invention belongs to the field of intelligent manufacturing and industrial process control, and relates to a caking early warning method and system in a solid beverage granulation process. The method comprises the steps that the material temperature, the environment humidity, the stirring motor torque and the adhesive spraying rate are collected in real time, and the fluctuation entropy of torque time sequence data is calculated; determining reference noise distribution according to the spraying rate variance, calculating a noise adjustment coefficient in combination with the fluctuation entropy, and generating an enhanced feature set by the disturbance parameter; constructing a multi-decision tree early warning model, and setting an information gain threshold value of node splitting according to a noise adjustment coefficient to control the depth of the tree; generating a verification set by disturbing historical boundary samples, and calculating the weight of each tree according to the confusion matrix; and performing weighted combination on classification results of all the trees, and outputting a caking early warning signal. According to the invention, accurate and reliable real-time early warning of the caking risk in the solid beverage granulation process can be realized, and the production stability and the product qualification rate can be improved in an assisted manner.

This application provides a data processing method, apparatus, device, medium, and product, relating to the field of wireless communication technology. Applied to lightweight RedCap terminals, the method includes: calculating the theoretical reference signal received power when the moving speed exceeds a preset speed threshold or the service demand is identified as an emergency location service; calculating the residual characteristic between the actual measured primary cell reference signal received power and the theoretical reference signal received power; determining the actual noise floor based on the actual received bandwidth, a preset reference bandwidth, and a preset reference noise floor; and inputting the actual measured primary cell reference signal received power, neighboring cell reference signal received power, residual characteristic, the terminal's original signal-to-interference-plus-noise ratio (SINR) measurement, and the actual noise floor into a pre-trained random forest regression model to obtain the predicted distance between the terminal and the primary serving cell base station. The method of this application improves the accuracy of RedCap terminal distance prediction.