341 results about "Noise threshold" patented technology

The invention relates to the field of concrete crack monitoring, in particular to a solid waste aggregate concrete crack real-time monitoring method and system, and the method comprises the steps: collecting sensor data in real time; calculating a deviation value between the current data and the initial reference data; when the deviation value exceeds a threshold value, the deviation value is used for compensating the subsequently collected sensor data; updating the initial reference data by using the mean value of the compensated data in the previous period; processing the compensated data in different channels, extracting strain accumulation trend characteristics in a long-term channel through a large time window, and extracting acoustic emission instantaneous characteristics in a short-term channel through a small time window; setting a long-term feature weight to be higher than a short-term feature weight, calculating a long-term feature change rate, and when the change rate is stable, improving the long-term weight and reducing the short-term weight, and filtering features lower than a noise threshold in a short-term channel; and fusing the weighted long-term features with the effective short-term features, and inputting the fused features into a pre-training model to obtain a fracture state prediction result in a future predetermined period.

The invention discloses a three-dimensional model automatic construction method for intelligently identifying an active fault, which belongs to the field of three-dimensional modeling, and comprises the following steps of: judging whether a small earthquake catalog accords with small earthquake cluster property or not through a nearest neighbor index method; setting a critical distance and a noise threshold value of hierarchical clustering on the basis of conforming to the small earthquake clustering property, and obtaining a small earthquake catalogue of a cluster; establishing a high-density three-dimensional slice with a self-defined step length and setting the overlapping degree of each section projection along the direction of the cluster earthquake to obtain earthquake data describing a fault, and carrying out random sampling consistent fitting on the earthquake to obtain a fault interpretation line; constructing an active fault three-dimensional initial model through a spatial interpolation method; and determining the spatial relationship of each branch fault, and constructing a final active fault three-dimensional model. According to the three-dimensional model automatic construction method for intelligently identifying the active fault, the three-dimensional model of the active fault can be directly constructed based on the small earthquake catalog, and a new method is provided for depicting the three-dimensional model of the active fault.

The embodiment of the invention relates to the technical field of pulse diagnosis, and discloses a pulse analysis method based on a pulse diagnosis instrument, which comprises the following steps: processing a pressure change signal within a set time to obtain an original pulse waveform signal associated with a user; performing high-frequency denoising processing on the first pulse frequency signal according to a set noise threshold value; acquiring all wavelet coefficients associated with the high-frequency detail signal, traversing all the wavelet coefficients, determining that the absolute value of the wavelet coefficient at a certain point is greater than the absolute value of the wavelet coefficient adjacent to the wavelet coefficient, and taking the wavelet coefficient as a signal abrupt change point; generating a corresponding pulse image of the user based on the pulse condition data of the user within a set time range; and inputting the obtained pulse condition graph of the user into a pre-constructed standard pulse condition model to determine a pulse condition type result of the user, and outputting the pulse condition type result of the user. According to the scheme provided by the embodiment of the invention, the user can conveniently, quickly and accurately know the pulse condition and the physique state of the user, and the use convenience is improved.

The invention discloses a self-adaptive filtering method and system for an intelligent electric energy meter, and relates to the technical field of power grid signal processing, and the method comprises the steps: obtaining a power grid voltage and current signal set collected by a target intelligent electric energy meter historically, and obtaining a signal noise spectrum data set and a noise level evaluation result through spectrum analysis and noise level evaluation; if the result exceeds a preset noise threshold value, identifying an interference type and building a noise adaptive filtering multi-channel, integrating and deploying the noise adaptive filtering multi-channel into a target intelligent electric meter to complete signal filtering test and effect evaluation, and dynamically optimizing and generating an electric energy meter adaptive filtering multi-channel based on the obtained multi-channel filtering effect index parameter; and finally, signal filtering closed-loop control is realized. The technical problem that a traditional electric energy meter is weak in filtering pertinence and cannot adapt to dynamic noise of a power grid in electric power related scenes with complex dynamic interference is solved, and the technical effects that the electric variable measurement accuracy of the electric energy meter is improved, and the adaptive capacity of the electric energy meter to different interference scenes is enhanced are achieved.

The invention discloses a high-frequency oscillation mode identification method and device of a power system, equipment and a medium. The method comprises the following steps: acquiring an original signal from the power system; performing parameter optimization on a preset variational mode decomposition model by adopting a black wing plinux optimization algorithm to obtain a target variational mode decomposition model; calling a target variational mode decomposition model to decompose the original signal to obtain a plurality of intrinsic mode components; calculating an autocorrelation coefficient corresponding to each intrinsic mode component, and selecting at least one oscillation characteristic component according to a comparison result of the autocorrelation coefficient and a preset noise threshold; and carrying out oscillation mode identification on each oscillation characteristic component by adopting a preset energy operator, and determining corresponding dominant high-frequency oscillation information. Therefore, high-frequency oscillation information identification of the broadband signal of the power grid is realized, and important oscillation information in the broadband signal is effectively prevented from being lost.

The invention discloses a cable defect analysis method and system in a cable laying process, and the method comprises the steps: dividing a current data sequence according to a preset data division strategy, obtaining at least one current data sub-sequence, and obtaining cable images of different monitoring positions according to the at least one current data sub-sequence; preprocessing the cable image to obtain a target cable image, and performing cable contour and background region segmentation on the target cable image to obtain a cable contour image; calculating a cable area based on the cable contour image, and extracting cable surface features; analyzing the surface features of the cable based on a set noise threshold, and removing noise features to obtain optimized surface features of the cable; and analyzing the surface features of the optimized cable based on the defect detection model, and outputting surface defect information. The accuracy and the real-time performance of defect detection are remarkably improved, the manual inspection cost and the leakage detection risk are reduced, and reliable guarantee is provided for safe operation of the cable.

A satellite tracking channel has a frequency loop tracking a carrier frequency of a satellite signal. A first indication of a spoofed signals is generated based on a determined satellite signal noise floor value associated with the satellite tracking channel and a tracking channel signal noise threshold associated with the satellite tracking channel. A second indication of a spoofed signal is generated based on a determining satellite tracking phase noise associated with the satellite tracking channel and a tracking channel phase noise threshold associated with the satellite tracking channel. Reception of a spoofed signal on the satellite tracking channel is detected based on the generated first indication of a spoofed signal and the generated second indication of the spoofed signal.

The embodiment of the invention provides a 5G base station frequency point determination method and device, equipment and a medium, and the method comprises the steps: obtaining a scanning starting frequency band, a scanning ending frequency band, scanning times, a scanning stopping bottom noise threshold value and an expected bandwidth list, and starting from the maximum bandwidth, according to the scanning starting frequency band, the scanning ending frequency band and a selectable bandwidth value, determining the frequency point of a 5G base station; determining a to-be-verified base station frequency point; for the to-be-verified base station frequency point, scanning the to-be-verified base station frequency point according to the number of scanning times in the scanning data to obtain a plurality of pieces of corresponding ground noise information; processing a plurality of pieces of ground noise information of base station frequency points to obtain a target ground noise mean value; and when the target bottom noise mean value is smaller than the scanning stopping bottom noise threshold value, taking the to-be-verified base station frequency point and the corresponding target bandwidth value as the target base station frequency point and the target bandwidth value of the target base station. According to the technical scheme provided by the embodiment of the invention, the base station frequency point and bandwidth are automatically set according to the frequency spectrum scanning result, the frequency point with serious interference is avoided, and the stability of the network is improved.

In certain aspects, an active noise control (ANC) method and system for a headphone are disclosed. It is determined whether a music signal is played by a speaker of the headphone. Responsive to the music signal not being played by the speaker and a noise level of an ambient noise signal being greater than a noise threshold, a set of noise feedforward (FF) signals is obtained based on a set of FF microphone signals acquired by a set of FF microphones of the headphone. A noise feedback (FB) signal is obtained based on a first FB microphone signal acquired by a FB microphone of the headphone. A set of leakage monitoring parameters is obtained based on the set of noise FF signals and the noise FB signal. A set of FF filter parameters for a set of FF filters is adjusted based on the set of leakage monitoring parameters.

The invention provides a unit noise centralized adjustment method and system, a frequency conversion unit and an air conditioner, and the method comprises the steps that the current area temperature and unit noise data are obtained in real time, and the unit load needed by the current area is calculated according to the current area temperature and the area target temperature; according to the capacity and the accumulated operation time of each unit, under the condition that the unit load is met, the number of the units needing to be started is determined, and then frequency modulation is conducted step by step to avoid the resonant frequency; whether the current unit noise data is larger than a preset environment noise threshold value or not is judged, if yes, frequency modulation is carried out on the basis that the unit load needed by the current area is met, and the current unit noise data is made to be smaller than or equal to the preset environment noise threshold value. The technical problem that modular scheduling cannot be carried out in the prior art is solved, noise and energy efficiency in the whole system are kept balanced and efficient by searching a balance point between noise reduction and unit capacity, and the effects of noise reduction and energy saving are achieved.

Examples herein relate to ambient noise level detection. For instance, in some examples an electronic device includes a cooling resource and a processor resource to alter an operational speed of the cooling resource from an initial operational speed to a first altered operational speed, detect an ambient noise level, compare the ambient noise level to a first noise threshold, and restrict the operational speed of the cooling resource to be less than the initial operational speed.

An operating method of a wireless communication device includes: receiving a reference signal transmitted from a second wireless device; calculating a reference noise value based on the reference signal; calculating, by the processor, a noise threshold value based on the reference noise value; receiving a first data signal transmitted from the second wireless device; calculating a data noise value based on the first data signal; comparing, by the processor, the data noise value with the noise threshold value; determining whether interference occurs in a target symbol based on a result of the comparison; adjusting the noise threshold value based on the data noise value when it is determined that the interference has occurred in the target symbol; and receiving a second data signal transmitted from the second wireless device, and using the adjusted noise threshold value in processing the second data signal.

The invention relates to the technical field of voice control of household electrical appliances, particularly provides a voice control method of an intelligent household electrical appliance and the intelligent household electrical appliance, and aims to solve the problem that an existing voice control system cannot accurately recognize an effective voice instruction in a noisy environment. In order to achieve the purpose, the voice control method of the intelligent household electrical appliance comprises the following steps: after a voice control function is started, collecting audio data within a preset duration; environment noise and voice instructions of the surrounding environment in the audio data are recognized; when the environmental noise is greater than or equal to a preset noise threshold value, acquiring a voice keyword in the voice instruction; according to the voice control method disclosed by the invention, when the surrounding environment noise is greater than the preset noise threshold value, the environment noise and the voice instruction in the acquired audio data can be identified, and the intelligent household electrical appliance is controlled by identifying the keyword in the voice instruction; the accuracy of recognizing the voice instruction in the audio data is improved.

Techniques to detect and differentiate the clutter patterns received by a sensor, such as a weather radar, from the desired signal. The systems and analysis techniques of this disclosure may separate the target signal from noise, interference, and clutter, in situations where the desired signal amplitude may be below a noise threshold. The systems and techniques of this disclosure may include algorithms to analyze signals from weather radar, and other sensors, when the clutter predominates and prevents the desired signal from being identified. Differentiating clutter from the received weather signals may be an issue in any situation when an interference is co-present with the desired signal. The challenge to isolate the desired signal from noise and clutter may increase multifold when the antenna size decreases. Therefore, the techniques of this disclosure may be useful for small sized weather radar antennae.

The invention provides an optimized otoacoustic reflected signal detection method, and aims to improve the accuracy of quality analysis and anomaly recognition of otoacoustic signals, the method mainly comprises the steps of TE noise threshold optimization, artifact elimination, similarity calculation, wavelet noise reduction, DP data processing and the like, the noise threshold is dynamically adjusted through self-adaptive threshold control, and the accuracy of the quality analysis and anomaly recognition of the otoacoustic signals is improved. The signal reliability is enhanced; a T-shaped window and a band-pass filtering technology are utilized, noise is effectively filtered, and the signal-to-noise ratio is improved; the signal matching degree and stability are further enhanced through the frequency domain coherence spectrum method and wavelet noise reduction; the continuous sound processing and small cavity identification strategy ensures the data integrity and accurately distinguishes the influence of different environments and earplug states.

The invention provides a continuous pulse signal processing and cardiac function evaluation system, which comprises a data acquisition module, a preprocessing module, a signal evaluation module, a feature extraction module and a cardiac function evaluation module, and is characterized in that a sample data set is established by acquiring a sample of a continuous pulse signal and evaluating the cardiac function of the sample; a noise threshold is set for continuous pulse signals in a sample data set for filtering and noise reduction processing, normalization processing is carried out, a preprocessed data set is formed, the pulse quality score of each continuous pulse signal is calculated according to the amplitude and the power spectral density of the continuous pulse signals, the continuous pulse signals are screened according to the pulse quality scores, and the continuous pulse signals are obtained. Time domain feature extraction and frequency domain feature extraction are conducted on the screened continuous pulse signals, a cardiac function evaluation model is established according to a neural network and trained, the continuous pulse signals collected by the collection module, the age and the gender serve as input of the evaluation model, and cardiac function evaluation is completed.

Techniques to detect and differentiate the clutter patterns received by a sensor, such as a weather radar, from the desired signal. The systems and analysis techniques of this disclosure may separate the target signal from noise, interference, and clutter, in situations where the desired signal amplitude may be below a noise threshold. The systems and techniques of this disclosure may include algorithms to analyze signals from weather radar, and other sensors, when the clutter predominates and prevents the desired signal from being identified. Differentiating clutter from the received weather signals may be an issue in any situation when an interference is co-present with the desired signal. The challenge to isolate the desired signal from noise and clutter may increase multifold when the antenna size decreases. Therefore, the techniques of this disclosure may be useful for small sized weather radar antennae.

The invention provides a force direction feedback system and method of pneumatic pressure. The system generates a first oscillation signal changing along with air pressure and a second oscillation signal with fixed frequency through a signal conversion module; and the counter counts the cycles of the two paths of oscillation signals. The back noise calibration module samples environment back noise by using a second oscillation signal in a frequency division manner, and eliminates back noise interference in a force count value through a subtractor, so that the problem of detection deviation caused by environment air pressure fluctuation is solved; and the dual-threshold comparison module screens the difference signal through a back noise threshold and an anti-shake threshold, generates a force conversion value, and avoids error output caused by slight fluctuation and shake. The differential operation module processes the force conversion value in combination with the second oscillation signal, the accurate pneumatic force value is output through signal correlation, the pneumatic direction can be distinguished by means of comparison with the fixed reference, and finally accurate and stable feedback of the pneumatic pressure force and direction is achieved.

The invention discloses a range hood control method and device, a household appliance and a readable storage medium, and the method comprises the steps: obtaining the back pressure and the current exhaust air rate of a range hood, and determining the resistance coefficient of the range hood according to the back pressure and the current exhaust air rate; a backpressure air volume curve matched with the resistance coefficient is determined from preset backpressure air volume curves, and a target backpressure air volume curve is obtained; determining the current rotating speed of a fan of the range hood according to the back pressure, the current exhaust air rate and the target back pressure air rate curve; and when the noise generated by the current rotating speed is greater than a preset noise threshold value, reducing the current rotating speed to a target rotating speed or automatically reducing the current rotating speed to the target rotating speed according to a rotating speed adjusting instruction sent by a user. According to the control method, the target back pressure air volume curve is obtained through matching according to the determined resistance, the rotating speed of the draught fan when the user uses the range hood currently is determined based on the target back pressure air volume curve, different optimal rotating speeds are set for different users according to the back pressure and the exhaust air volume, and the user experience is improved.

The invention relates to the field of image processing, in particular to a fish and shrimp denoising enhancement and intelligent identification method based on a two-dimensional sonar image, which comprises the following steps: extracting a sonar image water background, dividing regions and calculating a signal-to-noise ratio, dynamically adjusting a noise threshold, and denoising to obtain a salient image. And a multi-rotation-angle convolution kernel set is constructed based on a size statistics preset ellipse parameter. And clustering salient image pixel points, setting a bounding rectangle as a suspected target area, and judging the consistency of continuous frame targets through an optical flow algorithm. And dynamically adjusting a convolution kernel weight enhancement image, training a YOLO model to recognize a target, superposing recognition results and providing statistical information. According to the method, the fish and shrimp targets with variable sizes and directions in the sonar image are accurately identified and tracked by utilizing dynamic noise threshold adjustment and a multi-angle convolution kernel set in combination with a denoising enhancement technology based on a signal-to-noise ratio and an optical flow algorithm, the limitation of a traditional method is effectively overcome, and reliable technical support is provided for target detection in a complex underwater environment.

The invention discloses a seabed obstacle identification method based on multi-beam point cloud data and related equipment. The method comprises the following steps: acquiring the multi-beam point cloud data of a target area; performing statistics on the basis of the elevation difference between the adjacent sounding point clouds to obtain a frequency-based elevation difference histogram; fitting an attenuation model according to the elevation difference histogram, determining a noise threshold value based on the attenuation model, and dividing the multi-beam point cloud data into a real terrain point cloud and a noise point cloud by using the noise threshold value; a multi-beam real terrain point cloud is obtained through iterative denoising division; and based on the multi-beam real terrain point cloud, obstacle identification is carried out by using the elevation slope, and obstacle information of the target area is obtained. According to the method, through the automatic processes of determining the noise threshold value through the fitting attenuation model and iterative denoising, a traditional interactive filtering method depending on experience of technicians is replaced, the data processing efficiency is greatly improved, and the method can be widely applied to the technical field of data processing.

The invention discloses a scene-adaptive multipath time delay alignment method and device for a wireless communication system, and the method comprises the steps: employing an SISO channel detection system to actually measure channel data, employing rectangular or RRC shaping filtering to generate a CAZAC oversampling sequence as a template function, calculating a cross-correlation matrix of an IQ signal and the template function, and enabling the CAZAC oversampling sequence to serve as the template function; a noise threshold is calculated based on the median power and the false alarm rate, dynamic threshold filtering is executed, a cross-correlation matrix after denoising is generated, and preliminary estimation of the time domain impulse response is completed; extracting multipath time delay and complex gain from the cross-correlation matrix by using an SAGE algorithm; drawing a power delay spectrum PDP for the channel impulse response; and performing alignment operation on the PDP in combination with the geographical location information of the transceiver during actual measurement. According to the method, the defect of traditional alignment in a severe scene is overcome, the statistical modeling accuracy is improved, the multipath time delay can be effectively aligned through experimental verification, and reliable support is provided for channel modeling.

The invention belongs to the technical field of capacitive touch keys, and particularly relates to a double-frequency double-value detection method applied to touch. Comprising the following steps: initializing settings; respectively adopting two frequency points to carry out touch scanning, wherein the two frequency points are respectively dynamic change frequency points; after the touch values are collected at the two frequency points for multiple times, the multiple touch values of the two frequency points are averaged, primary filtering is carried out, and the average value is used for subsequent key state judgment; subtracting the last touch average value from the current touch average value of the two frequency points to obtain a difference value, and judging whether the difference value is greater than a preset noise threshold value or not; respectively subtracting the touch average values of the two frequency points from corresponding base values to obtain difference values; judging the noise state of the current key; updating the base value of the current key; the problems that detection of a single frequency point is prone to strong magnetic interference and response of a plurality of fixed frequency points is slow are solved, strong interference resistance and sensitivity are improved, and meanwhile hardware cost can be reduced.

A voice mixing conversion method includes: performing a noise reduction processing on the initial generated speech based on a noise threshold to generate a post-noise reduction speech; calculating a first quality score and a second quality score, wherein in response to a number of the initial generated speech being 1, the first quality score is calculated based on the initial generated speech, and the second quality score is calculated based on the post-noise reduction speech; and determining whether the first quality score is greater than the second quality score, wherein in response to the first quality score being greater than the second quality score, the initial generated speech is output, otherwise the post-noise reduction speech is output.

The invention provides a communication method and device. The method comprises that a first communication device sends first information to a second communication device, the first information can comprise at least one of a first parameter, a second parameter or a third parameter, the first parameter is used for indicating a feedback mode of a CIR measurement report, the second parameter is used for indicating a reference CIR branch, and the third parameter is used for indicating configuration of a noise threshold. Therefore, according to the method, at least one parameter of the first parameter, the second parameter or the third parameter is added in the first information, flexible perception control parameter configuration can be supported, flexible feedback of the CIR measurement report can be realized, and different application scene requirements can be met.

The invention provides a server fan speed regulation method and device based on a BMC (Baseboard Management Controller). The method provided by the invention comprises the following steps: determining the type of a server based on the condition that the server is equipped with a noise sensor; matching a corresponding noise determination method based on the server type, and determining a real-time noise value based on the noise determination method; comparing the real-time noise value with a noise threshold value, and determining a corresponding noise interval; acquiring a CPU utilization rate and a GPU utilization rate of the server; calculating a feedback value based on the CPU usage rate and the GPU usage rate; and in the noise interval, determining a corresponding speed regulation method based on a matching relationship between the feedback value and a plurality of feedback intervals, and regulating the speed of a fan on the server based on the speed regulation method. According to the server fan speed regulation method and device based on the BMC provided by the invention, dual optimization of heat dissipation efficiency and low noise is realized by intelligently regulating and controlling the rotating speed of the server fan.

The invention provides a control method and device of a twin-tub washing machine, the twin-tub washing machine and a storage medium. The method comprises the steps of obtaining operation noise of the twin-tub washing machine, and determining whether the operation noise is larger than a noise threshold value or not; under the condition that the operation noise is larger than the noise threshold value, operation parameters of a first barrel and a second barrel of the double-barrel washing machine are obtained; control parameters of the twin-tub washing machine are determined according to the operation parameters of the first tub, the operation parameters of the second tub and the operation noise, the control parameters are adopted to control the twin-tub washing machine so as to eliminate resonance of the twin-tub washing machine, and the control parameters comprise the control duration and the control rotating speed. The problems that an existing twin-tub washing machine is prone to causing the resonance phenomenon, the service life of equipment is shortened, and user experience is affected are solved.

A system including at least one memory storing instructions, and at least one processor in communication with the at least one memory is disclosed. The at least one processor is configured to execute the stored instructions to: (i) control a light detection and ranging (LiDAR) sensor to emit a pulse into an environment of the LiDAR sensor; (ii) generate temporal histograms corresponding to a signal detected by a detector of the LiDAR sensor for the pulse emitted by the LiDAR sensor; (iii) denoise a temporal waveform generated based on the temporal histograms; (iv) estimate ambient light; (v) determine a noise threshold corresponding to the ambient light; (vi) determine a peak of a plurality of peaks that has a maximum intensity; and (vii) add the peak to a point cloud.

The present invention belongs to the technical field of capacitive touch buttons, and particularly relates to a dual-frequency dual-value detection method applied to touch. It includes: initialization setting; using two frequency points for touch scanning respectively, and the two frequency points are dynamically changing frequency points; after collecting touch values ​​at the two frequency points for multiple times, averaging the multiple touch values ​​at the two frequency points respectively, performing a first-level filtering, and the average value is used for subsequent key state determination; by calculating the current touch average value of the two frequency points minus the last touch average value, the difference is obtained, and it is determined whether the difference is greater than a preset noise threshold; the touch average values ​​of the two frequency points are respectively subtracted from the corresponding base values ​​to obtain the difference; judging the noise state of the current key; updating the base value of the current key; the present invention solves the problem that single frequency point detection is susceptible to strong magnetic interference and multiple fixed frequency points respond slowly, while improving resistance to strong interference and sensitivity, it can reduce hardware costs.

A weather prediction method includes generating radiance differences as a difference between measured radiances from satellites and forecast satellite radiances generated by a radiative transfer model and forecasted state profiles output by a numerical weather prediction (NWP) model. When the radiance differences exceed a noise threshold, the method includes generating updated state profiles by generating radiance-sensitivities using a Jacobian model and the forecasted state profiles; constructing a Kalman-gain matrix from background error covariance (BEC) matrices and the radiance-sensitivities; generating filtered state-profile changes from the Kalman-gain matrix and the radiance differences; updating the state profiles by adding the filtered state-profile changes to the forecasted state profiles to yield updated state profiles.