26 results about "Pulse noise" patented technology

The invention relates to the technical field of communication, in particular to a signal detection method and system based on Gini gamma correlation coefficient matrix eigenvalues. The method comprises the following steps: acquiring signals received by multiple paths of sensors, and calculating rank statistics of each path of received signal; calculating Gini gamma correlation coefficients of any two paths of received signals to form a correlation coefficient matrix; obtaining characteristic values of the Gini gamma correlation coefficient matrix, and calculating a geometric mean value and an arithmetic mean value of the characteristic values; constructing test statistics based on the ratio of the geometric mean value to the arithmetic mean value; comparing the test statistic with the detection threshold to complete the detection process; according to the method, the influence of a large abnormal value in the pulse noise is effectively suppressed through Gini gamma correlation transformation, the test statistic constructed based on the ratio of the geometric mean value to the arithmetic mean value of the characteristic values shows excellent robustness in a pulse interference environment, and the signal detection performance is remarkably improved; signal detection can be carried out under background noise containing pulse components.

The invention discloses an aircraft fuel quantity measurement self-adaptive filtering method, system and device based on multi-dimensional statistic dynamic adaptation and a medium. The method comprises the following steps that S01, signals are collected and preprocessed; dividing a fuel quantity digital signal output by a sensor into continuous time blocks according to a fixed time window; s02, calculating a multi-dimensional statistical magnitude; comprising the mean value, variance and kurtosis of the current time block; s03, performing multi-stage filtering processing; s04, performing data fusion and conversion; and keeping the original value of the data pulse point, and combining the original value with the fine filtering result of the non-pulse point to obtain a complete filtered signal. By monitoring the multi-dimensional statistical characteristics (mean value, variance and peak value) of a fuel quantity signal in real time and combining a coarse filtering-pulse detection-fine filtering multi-stage structure, filtering parameters are dynamically adjusted, efficient suppression of mixed noise (low-frequency shaking, Gaussian noise and pulse noise) is achieved, and the precision of fuel measurement under complex working conditions is improved.

The application relates to the technical field of power line carrier communication, and discloses a PLC signal pulse noise processing method and device and communication equipment, the method comprising the following steps: acquiring a current time domain signal collected by a current sampling point; slidingly buffering the current time domain signal into a buffer window, the buffer window comprising a plurality of buffer positions arranged continuously, and each buffer position storing a time domain signal; judging whether there are continuous target time domain signals of a preset number on any side of a target buffer position, the target buffer position being one of the plurality of buffer positions and being used for outputting a time domain signal of the sampling point, and the target time domain signal being a time domain signal with a signal strength greater than or equal to a preset threshold; and processing the time domain signal output by the target buffer position according to the judgment result. According to whether the signal strength of the continuous number of time domain signals is greater than the preset threshold, the time domain signal output from the specific buffer position in the buffer window is processed, the misjudgment can be reduced, and the signal quality is improved.

The invention discloses an underwater acoustic anti-interference transmission method and system based on sparse time-frequency characteristic mapping, and the method comprises the steps: adaptively generating a fractional order linear frequency modulation waveform with a specific time-frequency shearing slope at a transmitting end according to the Doppler state of an underwater acoustic channel, and achieving the physical layer focusing of transmitted energy; at a receiving end, constructing a hybrid observation model comprising a wide block sparse channel component and a narrow block sparse burst noise component, and inferring posterior probability distribution of environmental burst noise in a fractional order domain through joint iteration by using a dual-channel variational Bayesian algorithm; and finally, recovering an original signal through soft threshold interference cancellation and fractional order channel equalization. Through active feature mapping of the waveform and heterogeneous sparse joint inference of the receiving end, the problem of communication failure caused by underwater acoustic high-dynamic Doppler diffusion and marine organism impulse noise interference is effectively solved, and the transmission reliability in a severe underwater acoustic environment is remarkably improved.

The application provides a high-degree-of-freedom DOA estimation method based on a mirror image co-prime array in a pulse noise environment, and relates to the technical field of array signal processing, and comprises the following steps: S1: obtaining an observation signal by relying on non-circular signal characteristics; S2: calculating a pseudo-covariance matrix based on the information of the observation signal and a square-based correlation entropy operator to suppress the pulse noise; S3: vectorizing the pseudo-covariance matrix to obtain a virtual vector, removing redundant rows in the virtual vector, and performing truncation and sorting according to positions corresponding to continuous virtual array elements to obtain a virtual array receiving signal; S4: performing spatial smoothing on the virtual array receiving signal to obtain a full-rank reconstructed covariance matrix; S5: obtaining a noise subspace by performing eigenvalue decomposition on the covariance matrix; and S6: obtaining an accurate DOA estimation value by performing spectral peak searching on the noise subspace by using a MUSIC algorithm. The method has a high degree of freedom, can accurately complete DOA estimation in a pulse noise environment, and has good performance.

The method comprises the following steps: dividing real-time ocean noise time domain data of a polar region into a plurality of observation time periods, calculating a kurtosis value of each observation time period, further dividing each observation time period into a plurality of short time periods, and calculating short-time energy of each short time period; if the kurtosis value of the observation time period is greater than a threshold value and the short-time energy of a short time period in the observation time period is greater than an average value, judging that pulse noise exists in the observation time period, extracting a pulse noise signal, detecting a pulse event in the pulse noise signal, and taking a key parameter of the pulse event as a feature extraction result; and for an observation time period without pulse noise, acoustic characteristics of background noise without pulse are extracted through a frequency domain method and characteristic parameters. Through signal separation and feature extraction, the data transmission quantity is remarkably reduced, the transmission efficiency and the effective information quantity of the data are improved, meanwhile, the noise detection accuracy is improved, the polar region severe environment can be better adapted, and the requirement for long-term monitoring is met.

The invention discloses a transmission optimization method and device and related equipment, and belongs to the technical field of power line carrier communication. The transmission optimization method is applied to a first device, and comprises the following steps: carrying out pulse noise monitoring on a channel to obtain first channel state information, and carrying out white noise monitoring on the channel to obtain second channel state information; determining diversity mode parameters according to the first channel state information, and determining modulation mode parameters according to the second channel state information; and according to the communication transmission parameters, generating a first frame, and sending the first frame to the second device, the first frame being used for indicating the second device to communicate based on the communication transmission parameters, the communication transmission parameters comprising diversity mode parameters and modulation mode parameters. According to the method, the accuracy of channel state evaluation is improved by jointly monitoring the white noise and the pulse noise, the diversity times and the modulation mode are dynamically adjusted according to the channel state, collaborative optimization of the diversity times and the modulation mode is achieved, and the method can be applied to interference complex scenes.

The application relates to the technical field of communication interference elimination, in particular to a pulse interference elimination method for a power carrier communication chip, which comprises the following steps: acquiring carrier signals of each communication node in a power carrier communication network and the length of a power line between any two communication nodes; acquiring suspected pulse noise points; calculating pulse noise weights of the suspected pulse noise points; intercepting each suspected pulse signal in the carrier signal; obtaining a pulse noise spectrum diagram of each communication node; calculating line loss ratios between any two communication nodes; obtaining a comprehensive pulse spectrum diagram of each communication node; calculating an attenuation ratio of each frequency position; obtaining a noise suppression spectrum diagram; and obtaining a carrier signal after noise suppression based on the noise suppression spectrum diagram, so as to eliminate pulse interference in the carrier signal. The application dynamically filters the frequency domain characteristics of the carrier signal, and improves the communication quality of the power carrier communication chip.

The invention discloses a method and system for suppressing non-pulse noise to accurately measure pulse arrival time, and the method comprises the steps: S1, generating pulsar simulation parameters which comprise a rotation period P, a flow density S1250 and a pulse arrival phase delay standard deviation sigma delta p; s2, constructing a pulsar standard contour Q (x), and generating based on a pulse contour type Ptype, a sub-pulse number and a sub-pulse contour shape; s3, simulating multi-epoch observation data, injecting noise, adding phase delay delta p, and generating an average contour q (x); s4, judging a pulse region: positioning a candidate pulse region through baseline identification, and screening a final pulse region according to a contour type; s5, calculating a phase difference delta x between the standard contour and the average contour by using a phase gradient method; and S6, comparing a difference value between the phase difference delta x and the analog phase delay delta p, and verifying whether higher timing accuracy is obtained by removing the noise in the non-pulse region or not. The pulsar timing precision is remarkably improved by reducing noise interference in a non-pulse area, and the pulsar timing method is suitable for a high-precision scientific target.

The application relates to the field of underwater acoustic signal processing and discloses a deep learning method and device for weak line spectrum joint detection and reconstruction under non-Gaussian pulse noise. In order to solve the problem that in the prior art, a weak line spectrum detection method mainly extracts target features by using experience knowledge, and the performance of the method depends on the cognitive degree of an operator for samples to a great extent, and the problem that underwater acoustic signal processing technology under a Gaussian noise assumption is directly applied to signal detection under non-Gaussian noise, which causes the performance to decrease or even fail, the technical scheme provided by the application is as follows: a weak line spectrum joint detection and reconstruction method comprises the following steps: collecting pulse noise, and constructing a ship line spectrum data set according to the noise; pre-processing the data set to obtain a lofar graph; extracting weak features of the lofar graph, and obtaining a line spectrum detection and reconstruction result; training a preset model according to the lofar graph and the result, and outputting a trained model. The application is suitable for weak line spectrum detection and reconstruction under Gaussian pulse noise.

The application provides a time delay-Doppler joint estimation method under polar pulse noise interference. On the basis of the orthogonal matching pursuit algorithm, the maximum correlation entropy criterion and the l1 norm constraint are introduced to enhance the robustness under the pulse noise, and a fast solving algorithm based on a distributed iterative optimization strategy is used to improve the calculation efficiency. Compared with the existing same type estimation method, the method has a wider application range, higher estimation accuracy and stronger robustness.

The invention relates to the field of hearing aids, in particular to an impulse noise suppression method and system for a hearing aid, and the system comprises a machine body module, a processing module, a protection module and a driving module. The hearing aid main body comprises a shell, a sound receiver, and a battery, a charging interface, a processor, a broadcaster and keys which are arranged in the sound receiver, the external ear hanging piece is hung at the external ear part and is used for mounting and supporting the hearing aid main body, and sudden pulse noise is inhibited by setting the maximum upper limit of the volume when the player plays; the driving module drives the sound receiving device to rotate, so that the follow-up sound processing module can process pulse noise conveniently, meanwhile, the driving module can drive the protective net to wrap the sound receiving device, at the moment, the protective net can reduce sonic boom caused by air flow impact when the sound receiving device receives sound and filter some unnecessary noise to a certain extent, external pulse noise interference is further prevented, and the sound receiving device can be used for sound receiving. Therefore, the hearing aid can be normally used under the interference of pulse noise.

The invention relates to a direction-of-arrival estimation method, in particular to a high-robustness self-adaptive direction-of-arrival estimation method, and solves the technical problems of low direction-of-arrival estimation precision and poor robustness and stability in a time-varying environment due to pulse noise interference in a traditional MUSIC algorithm. According to the invention, the logarithmic compression operator is adopted to compress the array signal, so that the overall signal-to-noise ratio of the array signal can be remarkably improved, the pulse noise interference is suppressed, and the estimation precision of the direction of arrival is improved; besides, a self-adaptive adjustment mechanism of compression parameters is introduced, the situation that the compression strength is not matched with the noise environment possibly existing during fixed parameter compression is avoided, impulse noise interference from different sources can be dealt with, and the robustness and stability of direction-of-arrival estimation in the complex time-varying environment are improved; meanwhile, a dual-branch direction-of-arrival estimation framework based on a PAST algorithm and an EWMA algorithm not only ensures the real-time performance of adaptive adjustment of compression parameters, but also can improve the precision of direction-of-arrival estimation.

The invention provides a voltage sag detection method and device based on a Teager energy operator and morphological filtering, and relates to the technical field of power system sag protection and electric energy quality monitoring. The method comprises the following steps: firstly, converting a three-phase voltage signal into a voltage component under a two-phase static coordinate system through Clark conversion; secondly, a virtual instantaneous voltage power modulus containing a fundamental wave offset mechanism is constructed, and sag characteristic components can be effectively extracted; then, a morphological filtering combination filter is used for conducting denoising processing on the differential power signals, high-frequency impulse noise interference is eliminated, and pure characteristic signals are obtained; and finally, calculating an energy spectrum of the pure characteristic signal by using a Teager energy operator, and carrying out voltage sag detection in combination with a self-adaptive dynamic threshold, so as to judge the starting and ending moments of the voltage sag. According to the invention, the voltage sag can be accurately detected within 1ms, and the anti-noise performance is excellent.

The application discloses a high-order off-grid DOA estimation method and system based on an extended coprime array and belongs to the field of polar water sound detection. The method comprises the following steps: acquiring signals received by the extended coprime array to form a receiving data matrix; introducing a phase fraction low-order moment method to construct a phase fraction low-order moment matrix C, vectorizing C, removing redundancy and rearranging to obtain a single-snapshot continuous virtual uniform linear array signal vector z1; based on z1, using a division method of an overlapping subarray to construct a multiple measurement signal vector matrix Z; using a high-order Taylor expansion term to construct an off-grid model, using an extrapolation-based iterative sparse projection algorithm to jointly estimate a sparse signal matrix and a grid offset according to the matrix Z, and estimating the DOA of a target. The application provides a new solution to the problems of performance decline of a conventional DOA estimation method in a polar pulse noise environment and a limited number of detectable targets of a traditional uniform linear array.

The application relates to a smart meter communication pulse noise suppression method and system, a terminal and a medium, and relates to the field of smart meter communication. The method comprises the following steps: monitoring a signal waveform received by a smart meter; identifying whether pulse noise interference exists in the signal waveform based on a preset pulse noise characteristic model; if the pulse noise interference exists, determining the start and end positions of the pulse noise interference in the time dimension, and generating an interference interval corresponding to the start and end positions; suppressing a first waveform segment located in the interference interval to obtain a preliminary purified signal; reconstructing the preliminary purified signal by using a second waveform segment to generate a reconstructed signal, the second waveform segment being a waveform segment not interfered with before and after the interference interval; and performing demodulation and error correction decoding processing on the reconstructed signal to obtain effective communication data. The application has the effects of guaranteeing accurate transmission of power consumption information and improving data integrity.

The application provides an industrial energy consumption control method and system, wherein the method comprises: collecting energy consumption data through the data acquisition device; sequentially performing high-frequency noise removal and pulse noise removal on the energy consumption data to obtain denoised energy consumption data; extracting time domain features, frequency domain features and industrial mechanism features from the denoised energy consumption data to form feature data; inputting the feature data into a lightweight model deployed in an edge gateway to output future energy consumption prediction data; when the prediction deviation of the future energy consumption prediction data exceeds an energy consumption threshold, automatically generating a device control strategy and controlling the edge executor to execute the device control strategy to dynamically adjust device parameters, so that the removal of data noise, the optimization of model training and deployment, and the real-time and automation of device control can be realized.

The invention discloses a wireless communication noise reduction earphone and a noise reduction method thereof, and relates to the technical field of earmuff type noise reduction earphones. The earphone framework takes a main control circuit and a wireless communication circuit as a core and is supplemented by voice enhancement, active noise reduction, interception, power management and an external interface circuit, the main control circuit overall plans operation logic and cooperates with multiple modules, and the wireless communication circuit supports multi-person simultaneous conference in the same group and multi-person simultaneous voice receiving, so that wireless multi-party communication independent of external equipment is realized. According to the noise reduction method, a composite active noise reduction technology is adopted, voice enhancement and an impulse noise protection mechanism are combined, voice and noise signals are separated through frequency spectrum subtraction, and noise reduction and environment perception are balanced in cooperation with an environment monitoring function. The problems that a traditional earphone depends on external equipment for communication, noise reduction and safety perception are contradictory in a complex environment and the like are solved, a collaborative operation scene is adapted, and voice definition and use convenience in a noisy environment are improved.

The utility model discloses an aluminum profile with a noise reduction function, and belongs to the technical field of aluminum profiles, the aluminum profile comprises an aluminum profile bottom plate, a reinforcing rib is fixedly connected to the top of the aluminum profile bottom plate, a sound absorption plate is placed on the top of the reinforcing rib, and a plurality of mounting grooves are formed in the upper surface of the aluminum profile bottom plate and the lower surface of the sound absorption plate; an aluminum profile round rod is inserted into the mounting groove, and a damping ring is arranged between the aluminum profile round rod and the mounting groove. The general frame of the pet cage is assembled through cooperation of the aluminum profile bottom plate, the reinforcing ribs and the sound-absorbing plates, the mounting grooves are formed in the aluminum profile bottom plate and the sound-absorbing plates, the aluminum profile round rods are inserted into the mounting grooves to form a fence of the pet cage, and the damping rings are embedded into the joints of the aluminum profile round rods and the mounting grooves, so that the pet cage can be conveniently assembled and disassembled. The damping ring can buffer vibration energy, pulse noise generated by shaking of the aluminum profile is reduced, sound made by pets is absorbed by arranging the sound absorption plate and the sound absorption cotton, and a dual noise reduction mechanism is formed.

The application discloses an airplane lifesaving explosion cutting pulse noise detection method based on a simulation platform, the simulation platform comprises a seat model, a hatch model and a simulation man model; the method comprises the following steps: arranging components of the simulation platform and adjusting characteristic parameters so as to be consistent with parameters of a detection scene when a pyrotechnic device explodes; recording adjustment parameters and corresponding data of the simulation platform; setting detection points according to pulse noise detection requirements, measuring and recording the blast center distance of the detection points; and performing explosion cutting pulse noise test to obtain test data. According to the application, the airplane lifesaving explosion cutting pulse noise detection scene can be simulated and corresponding test can be performed, and accurate and effective test data can be obtained.

The invention relates to an electric power signal pulse noise filtering algorithm based on mathematical morphology and an electric power signal random noise filtering algorithm based on mathematical morphology. The electric power signal pulse noise filtering algorithm based on mathematical morphology comprises the following steps: S1, determining a maximum pulse width, namely the number of occupied points; and S2, carrying out opening operation and closing operation on the voltage and current digital signals. And S3, marking an area in which the positive and negative pulse noise amplitudes exceed a threshold value. And S4, continuously applying the odd positive integer width horizontal straight line structure elements to an area in which the positive pulse noise amplitude exceeds a threshold value and which is not overlapped with the area in which the negative pulse noise amplitude exceeds the threshold value to perform opening operation. And S5, continuously applying the odd positive integer width horizontal straight line structure elements to a region in which the negative impulse noise amplitude exceeds a threshold value and is not overlapped with a region in which the positive impulse noise amplitude exceeds the threshold value to perform closed operation. And S6, alternately performing opening and closing operation on the areas which exceed the threshold value and are overlapped by applying horizontal straight line structure elements.

The invention relates to the field of fault diagnosis, in particular to a shield tunneling machine main bearing fault detection method based on angular domain synchronous averaging, which comprises the following steps: S1, collecting relevant signals (vibration data, angle data and rotating speed data) of a shield tunneling machine main bearing; s2, converting the time domain vibration signal to an angular domain; s3, angular domain signal preprocessing (extracting fragments with the same revolution number, and adopting cubic spline interpolation for resampling); s4, executing angular domain synchronous averaging; s5, calculating an order spectrum and analyzing fault features; and S6, performing online application. According to the method, a time domain signal is converted to an angular domain to realize alignment with a rotating phase, a data standard is unified through preprocessing, random pulse noise is effectively inhibited through synchronous averaging, periodic fault features are enhanced, fault related order components can be clearly identified in combination with order spectrum analysis, and the accuracy of fault detection is improved. Therefore, the accuracy and reliability of fault detection of the main bearing of the shield tunneling machine under complex working conditions are improved.

The application discloses a combined microphone contact type electric connection structure, which comprises a first connector and a second connector, and the first connector and the second connector have a combined state and a pre-combined state; a first conductor, a second conductor and a plurality of third conductors are arranged on the first connector, and the first conductor and the second conductor are electrically connected with a microphone; two first conductive contacts and two second conductive contacts are arranged on the second connector, the two first conductive contacts are electrically connected with a microphone circuit respectively, the two second conductive contacts are electrically connected with a power supply and a power input end of the microphone circuit respectively; the two first conductive contacts are always in contact with the first conductor and the second conductor respectively; when the first connector and the second connector are in the pre-combined state, the two second conductive contacts are disconnected; and when the first connector and the second connector are in the combined state, the two second conductive contacts are in contact with the same third conductor. The application can effectively eliminate the pulse noise generated when the microphone is combined and connected.

The invention provides a quality factor measurement circuit and method. The circuit comprises an excitation source, a resistance-inductive system, a capacitor, a voltage measurement device, a dual-channel acquisition system and a processor. The voltage signals are adopted for calculation, amplitude scaling, measurement and collection are more convenient through the voltage signals, in the principle of the invention, the output voltage of the excitation source is noiseless, and the voltage at the two ends of the capacitor cannot be suddenly changed, so that the voltage at the two ends of the capacitor does not have high-frequency glitch noise and impulse noise, and the waveform signal-to-noise ratio is high; and in combination with appropriate capacitor types, packaging, filtering and other means, the external noise can be remarkably suppressed, and high accuracy is achieved.

The application provides a power distribution network harmonic measurement method and system based on adaptive detection and parallel calculation, belongs to the technical field of dynamic harmonic measurement, and comprises the following steps: acquiring a power distribution network signal and performing discrete sampling in an observation time window to obtain a discrete signal sequence; calculating kurtosis, spectral entropy and residual gradient norm of the initial residual vector; dynamically adjusting an adaptive threshold parameter based on the kurtosis, spectral entropy and residual gradient norm; calculating a pulse noise detection threshold according to the adaptive threshold parameter; performing point-by-point comparison on the initial residual vector by using the pulse noise detection threshold, identifying a pulse noise occurrence position, and forming a pulse noise support set; constructing an enhanced basis matrix based on the pulse noise support set; decomposing a pseudo-inverse of the enhanced basis matrix into four sub-block matrices; performing parallel calculation on the four sub-block matrices; and finally obtaining amplitudes, phases, first derivatives and second derivatives of each harmonic.

The invention relates to the technical field of geophysical exploration signal processing, and discloses an ocean magnetotelluric data denoising method and related equipment, and the method comprises the steps: constructing a training data set, and training a model to obtain a dual-path noise recognition model and a generative reconstruction model; performing preprocessing and windowing on the new ocean magnetotelluric original data to be processed to obtain a plurality of data windows; performing parallel noise identification on each data window to obtain a periodic noise mask and a random pulse noise mask; carrying out fusion processing to obtain a comprehensive noise mask, and marking noise data points needing to be reconstructed in the data window by the comprehensive noise mask; and performing signal reconstruction on the data window based on the generative reconstruction model and the comprehensive noise mask to obtain a processed clean data window, and performing splicing processing to obtain a complete de-noised ocean magnetotelluric time sequence. According to the method, the defects of an existing MMT data processing technology in the aspect of coping with long-period and multi-type mixed noise are overcome.