42 results about "Recursive filter" patented technology

The invention discloses an offshore wind power cable line fault early warning method and system, and relates to the technical field of cable line fault early warning, and the method comprises the following steps: laying a three-dimensional distributed optical fiber temperature array along an offshore wind power cable, and monitoring the cable thermal field space distribution in combination with an active acoustic dispersion imaging technology; acquiring initial evolution trajectory data of the edge high-temperature region; and on the basis of the initial evolution trajectory data, constructing a coupling relationship among the ocean current parameter, the sediment disturbance characteristic and the cable heat conduction parameter, forming an ocean current-sediment-heat conduction coupled digital twin model, and dynamically correcting a virtual scene of the cable burial depth in the model through a recursive filtering algorithm. Through combination of thermal field monitoring, digital twin modeling and intelligent intervention, accurate early warning and dynamic response of offshore wind power cable faults are realized, the operation and maintenance efficiency is improved, system self-optimization and cross-scene migration are supported, and the safety and intelligent level of cable operation are significantly enhanced.

The invention relates to the technical field of power transmission line sag measurement, in particular to a power transmission line sag measurement method based on laser point cloud data, which comprises the following steps: controlling a laser radar module and a multispectral imaging module to perform time-space synchronous data acquisition on a power transmission line area, and generating an auxiliary three-dimensional point cloud through a data fusion and compensation module; fusing the laser point cloud and the auxiliary three-dimensional point cloud by adopting an adaptive weighted average algorithm to generate a fused point cloud; performing dynamic filtering processing on continuous multi-frame point cloud data through a dynamic filtering module based on Kalman filtering and an established conductor dynamic model, filtering out high-frequency vibration components, and extracting a steady-state position point cloud of the conductor; the sag value of the power transmission line is calculated through the sag calculation module, so that cooperative sensing and data adaptive fusion of the multi-source sensor in a severe environment are completed, recursive filtering processing is performed on continuous multi-frame point cloud data, and a more real and more accurate data basis is provided for sag calculation.

A circuit and corresponding method perform timestamp filtering. The circuit includes recursive filter logic that implements a recursive least-squares (RLS) filter. The circuit (i) generates a filtered timestamp from a received timestamp by filtering the received timestamp via the recursive filter logic. The recursive filter logic applies the RLS filter to a portion of the received timestamp. A number of bits of the portion is less relative to a total number of bits of the received timestamp. The circuit outputs the filtered timestamp generated. Applying the RLS filter to the portion enables the circuit to be more efficient (e.g., smaller adders, fewer flipflops, etc.), thereby reducing area and power consumption of the circuit.

This invention relates to the field of spacecraft attitude control technology, and more particularly to an ultra-precise and ultra-stable on-orbit adaptive control method and system for pointing under additional stiffness disturbances. This on-orbit adaptive control method, by applying specific excitations to actuators and measuring their responses, combined with a recursive filtering algorithm, can accurately identify the total actuator stiffness, including the additional stiffness of the cable, in real-time on-orbit, overcoming problems caused by differences in ground testing environments and time-varying stiffness. Based on the real-time identified stiffness values, the parameters of the axial compensation controller and the actuator compensation controller are dynamically adjusted, enabling the control system to adapt to changes in the additional stiffness of the cable and maintain excellent control performance at all times. By employing dual compensation control at the axial load level and the actuator level, additional stiffness disturbances are synergistically suppressed at both the overall system and local actuator levels, improving the comprehensiveness and accuracy of control, and achieving ultra-precise and ultra-stable on-orbit adaptive control for pointing under cable additional stiffness disturbances.

The headset includes an electro-acoustic transducer, at least one noise reduction processing chain including external and internal microphones, a processing filter including mounted in parallel between the external microphone and an adder, at least one elementary filter each including a recursive filter and an elementary variable gain amplifier, a control unit for the gain of each elementary amplifier according to a signal coming from the external microphone and an error signal coming from the internal microphone.The processing filter includes an open-loop main filter connected at the input to the external microphone and the output of which is connected, to the adder, and to the input of the or each elementary filter.

The invention belongs to the field of circuits and systems, and particularly relates to a two-dimensional recursive filter design based on an improved particle swarm optimization algorithm. Comprising the following steps: 1) performing mathematical analysis on a transfer function of a two-dimensional recursive filter to establish a model; 2) finding out an optimal parameter set by using an improved particle swarm optimization algorithm, and enabling the sum of squares of errors between the amplitude response of the designed filter and the amplitude response of an ideal filter to be minimum; 3) integrating a dynamic inertia weight strategy, a dynamic learning factor and a prying strategy into a particle swarm optimization algorithm; 4) setting algorithm operation parameters; and 5) by minimizing the objective function, obtaining a parameter set and combining the parameter set with a filter model structure to form an optimal two-dimensional recursive digital filter meeting conditions. According to the scheme, the stability of the filter can be ensured, and compared with the previous scheme, the amplitude response of the two-dimensional recursive digital filter is closer to that of an ideal two-dimensional recursive digital filter.

The embodiment of the invention provides a video defogging method and device, electronic equipment and a medium. The method comprises the following steps: acquiring a foggy video; determining a background image of the foggy video; determining a dark channel image of the background image according to the background image of the foggy video; performing recursive filtering processing on the dark channel image to obtain a target image; determining an atmospheric transmissivity estimation value according to the target image; and carrying out defogging processing on the foggy video according to the atmospheric transmissivity estimation value. According to the embodiment of the invention, the target image is obtained by carrying out recursive filtering processing on the dark channel image, the atmospheric transmissivity estimation value can be directly determined so as to carry out defogging processing, the process is simple, the calculation amount is small, and the defogging efficiency of the video can be improved.

The invention provides a multi-sensor target fusion method and system based on sequential filtering, and belongs to the technical field of intelligent driving, and the method comprises the steps: obtaining a fusion track of a plurality of target sensors, and calculating a track state at a current moment according to a track state at a previous moment; adopting a greedy algorithm to respectively match the plurality of target sensors with the current time track; and updating the track state by adopting sequential filtering according to the matched measurement value. According to the method, the greedy algorithm is adopted for matching, the time complexity is far smaller than that of a KM algorithm and the like, but an approximate global optimal matching result can be achieved in most cases, and the calculation amount can be reduced to a great extent. According to the method, sequential filtering is adopted to update the flight path state, the method serves as a recursive filtering algorithm, measurement data are comprehensively considered, meanwhile, the method is easy to implement, optimal estimation of the system state can be provided based on the minimum mean square error criterion, and in addition, filtering parameters and measurement weight values can be adjusted according to the actual situation.

The application discloses a method for electronic countermeasure cooperative jamming suppression in a frequency offset scene, which comprises the following steps: S1. At the jammer, after the interference data x(n) is converted by a digital-to-analog converter and up-converted, a transmission jamming signal is generated and transmitted; S2. At the authorized receiver, after the jamming signal is transmitted through a wireless channel, the jamming signal is received simultaneously with an expected signal, down-converted to obtain a baseband receiving signal, and analog-to-digital converted to obtain a baseband digital signal; S3. The baseband receiving signal is expressed in a matrix form; S4. The fast-changing cooperative jamming joint channel coefficient is estimated, and the cooperative jamming is reconstructed and cancelled to complete the interference suppression. The application can effectively cancel the cooperative jamming under a frequency offset multipath channel, and does not need to accurately estimate the frequency offset value, but sets a frequency offset value interval, and uses multiple adaptive recursive filters in parallel to estimate the cooperative jamming coefficient.

A pixel filter has a filter module that performs a first recursive filter operation in a first direction through a sequence of pixels to form a first filtered pixel value for each pixel, and performs a second recursive filter operation in a second direction through the sequence of pixels to form a second filtered pixel value for each pixel, the first and second recursive filter operations forming a respective filtered pixel value for a given pixel in dependence on the pixel value at that pixel and the filtered pixel value preceding that pixel in their respective direction of operation. The filtered pixel value of the preceding pixel is scaled by a measure of similarity between data associated with that pixel and its preceding pixel. Filter logic combines the first and second filtered pixel values formed by the first and second recursive filter operations to generate a filter output for the pixel, for each pixel of the sequence.

A circuit and corresponding method generate a filtered timestamp. The circuit comprises recursive filter logic. The circuit generates the filtered timestamp from a received timestamp by filtering the received timestamp via the recursive filter logic. The recursive filter logic reduces jitter in the filtered timestamp relative to jitter of the received timestamp. The jitter represents a deviation of the received timestamp from a target (ideal) timestamp. The circuit outputs the filtered timestamp generated. The filtered timestamp is a more accurate representation of the target timestamp, relative to the received timestamp, due to the jitter reduced.

The application relates to the technical field of partial discharge detection, and discloses a recursive filtering parallel partial discharge detection method and system based on time-frequency characteristics, computer equipment and a storage medium, wherein through the time-frequency characteristics of a partial discharge signal, after a series of collection, conversion, filtering, detection and analysis operations, efficient identification and positioning of the partial discharge can be automatically realized, the method and system are suitable for general detection of various partial discharges, have good adaptability and high reliability.

The invention belongs to the field of circuits and systems, and particularly relates to a two-dimensional recursive filter design method based on a P system and a collaborative optimization strategy, which comprises the following steps of: 1) establishing a model by performing mathematical analysis on a transfer function of a two-dimensional recursive filter; 2) combining a crossover mutation operator which is strong in global search capability but is easy to fall into local optimum, a cosine enhancement operator which is strong in local search capability but is slightly insufficient in population diversity mining, and a mixed membrane structure of a P system into a novel mixed operator capable of balancing convergence and diversity; 3) embedding an object updating rule represented by the operator into a P system with a mixed membrane structure to form a novel P system optimization algorithm (PHOA); 4) taking a numerical value combination of objects in the object set of the novel P system optimization algorithm as a model parameter group of a two-dimensional recursive filter, substituting the model parameter group into the two-dimensional recursive filter model, and calculating an error function between a two-dimensional recursive filter model parameter amplitude response M (omega1, omega2) and an ideal two-dimensional filter amplitude response Md (omega1, omega2); and 5) by minimizing the objective function, obtaining a parameter set and combining the parameter set with a filter model structure to form an optimal two-dimensional recursive digital filter meeting conditions. According to the scheme, the stability of the filter can be ensured, and compared with the previous scheme, the amplitude response of the two-dimensional recursive digital filter is closer to that of an ideal two-dimensional recursive digital filter.

The present invention relates to a cascaded filter and a fundamental wave extraction method thereof, belonging to the technical field of digital signal processing. The method includes: determining an initial value of an interpolation factor M; substituting the interpolation factor into the cascaded filter to obtain a filtering result corresponding to the initial value; the cascaded filter includes a shaping filter and a masking filter, the shaping filter is an FIR filter, and the shaping filter is obtained by interpolating M - 1 zeros between adjacent impulse response coefficients of a prototype filter; the masking filter is a recursive filter; adjusting the magnitude of the interpolation factor, comparing the filtering results corresponding to different interpolation factors, and taking the value of the interpolation factor with the best filtering result as the final value of the interpolation factor; the cascaded filter performs fundamental wave extraction according to the final value of the interpolation factor. In the present invention, the increase of the M value does not affect the computational amount of the recursive filter, and thus does not affect the computational amount of the overall cascaded filter. Therefore, when the M value is relatively large, the extraction efficiency of the fundamental wave is improved.

The invention relates to the technical field of power system network security, in particular to power market attack detection and compensation based on a three-step recursive filter, which comprises the following steps: establishing a discretized state space model fused with a power market dynamic mechanism, and modeling an attack as unknown input; sequentially executing time updating, measurement updating and attack signal estimation through a three-step recursive filtering structure, and synchronously realizing minimum variance unbiased estimation of a system state and a false data injection attack; and performing real-time dynamic feed-forward compensation on an attacked system output link by adopting a redundancy analysis method based on the accurately estimated attack signal. The method has the advantages that attack detection, estimation and compensation are integrated, a sensing-diagnosis-suppression closed-loop active defense system is formed, the estimation result of the optimal statistical property can be provided in the noise environment, and the network security and operation reliability of the multi-region power market coupling system are remarkably improved.

The invention provides an earphone noise reduction method and system, a readable storage medium and a computer. The method comprises the following steps: preprocessing external audio data to obtain preprocessed data; performing frame-by-frame processing on the pre-processed data to extract a Mel-frequency cepstrum coefficient, and calculating a first-order difference and a second-order difference of the Mel-frequency cepstrum coefficient to represent time-frequency characteristic data of noise in the pre-processed data; an expected frequency response of a recursive filter is constructed based on the passive noise reduction function and the active noise reduction function of the earphone; by taking the expected frequency response as a target, optimizing the coefficient of the recursive filter by using an adaptive algorithm to obtain a recursive optimized filter; and fusing the recursive optimization filter and a preset audio noise reduction model to construct a fusion noise reduction model, and performing noise reduction on the earphone by using the fusion noise reduction model. According to the method, a fusion noise reduction model of genetic algorithm optimization and frequency band constraint is constructed, so that the earphone effectively inhibits system instability and squeal phenomena caused by wearing changes and the like.

The present disclosure relates to a method and apparatus for reducing noise included in real-time image data. The method for reducing noise included in real-time image data, according to an aspect, may comprise the steps of: acquiring first output data by inputting at least one frame before a time point t and at least one frame after the time point t, from among a plurality of frames included in real-time image data, into a neural network model; acquiring second output data by inputting a frame at the time point t, at least one frame before the time point t, and at least one frame after the time point t, from among the plurality of frames, into a motion correction network and a recursive filter; training a noise correction model by using at least one of the first output data and the second output data; and reducing noise included in the real-time image data by using the trained noise correction model.

The invention provides a multi-rate system event fusion estimation method under a complex condition, and relates to the technical field of automatic control, and the technical key points are as follows: constructing a state equation of an MRS and a measurement equation of sensor nodes: converting the MRS into an SRS, and performing sampling period unification on each sensor node in an interval to obtain the state equation and the measurement equation of the SRS; designing a local recursive filter, receiving a measured value based on an event triggering mechanism, calculating an upper bound of a filtering error covariance, and deducing a recursive relationship through an inequality technology; filter parameters are designed, and the upper bound of the filtering error covariance is minimized in a recursive mode; and fusing the estimation results of the local filters by using a CI fusion method to obtain global fusion estimation and fusion covariance. Even if the method is influenced by random nonlinearity, sensor degradation and event triggering, the sampling values of different sensors in the multi-rate system can still be fused and estimated quickly and efficiently.

The present application relates to a hyperspectral image sub-pixel positioning method with edge preservation, comprising: S1, using a Gaussian blur kernel and an original hyperspectral image to perform non-blind deconvolution to reduce the point spread function effect in the original hyperspectral image; S2, using a domain transform recursive filter to filter the result of step S1 to play a role in edge preservation and noise reduction; S3, obtaining an abundance image through a linear spectral unmixing technique; S4, using an interpolation method to up-sample the abundance image to obtain soft class values of each type of sub-pixel; S5, using a class assignment strategy to assign a class label to each sub-pixel to obtain the final sub-pixel positioning result. The present application can effectively process the point spread function effect and the noise such as texture details in the image, thereby improving the sub-pixel positioning accuracy.

The invention relates to the technical field of spacecraft attitude control, in particular to an on-orbit self-adaptive control method and system for ultra-precise and ultra-stable pointing under additional stiffness disturbance. According to the on-orbit adaptive control method, the specific excitation is applied to the actuator, the response of the actuator is measured, and the recursive filtering algorithm is combined, so that the total stiffness of the actuator including the additional stiffness of the cable can be accurately identified in an on-orbit manner in real time, and the problems caused by ground test environment difference and stiffness time variation are solved. The parameters of the axial compensation controller and the actuator compensation controller are dynamically adjusted based on the rigidity value identified in real time, so that the control system can adapt to the change of the additional rigidity of the cable, and the excellent control performance is always kept. Axial load level and actuator level dual compensation control is adopted, additional stiffness disturbance is cooperatively restrained from the two aspects of an overall actuator and a local actuator of the system, the comprehensiveness and accuracy of control are improved, and ultra-precision and ultra-stable pointing on-orbit self-adaptive control under cable additional stiffness disturbance is achieved.

This disclosure provides systems, methods, and devices for the prevention of color leakage in Field Sequential Display while maintaining display brightness. In a first aspect, a method of signal processing includes receiving a first frame of a first color of image data; selecting a modified first frame of the first color by applying a recursive filter to the first frame, wherein the recursive filter is associated with at least one previous frame of a second color different from the first color; and selecting first pixel drive values associated with the modified first frame. Other aspects and features are also claimed and described.

The invention relates to the technical field of vehicle control, and discloses a two-wheeled vehicle state estimation method, device and equipment and a medium, and the method comprises the steps: firstly predicting a vehicle state based on obtained inertia measurement data, and further generating a key correction signal by using preset kinematics constraint; kinematic constraints specifically relate to physical characteristics of contact points of wheels of the two-wheeled vehicle and a road surface in normal positions and normal and tangential speeds. Finally, within a recursive filtering model, the correction signal is used to update the foregoing predicted vehicle state, thereby obtaining an accurate and reliable target two-wheeled vehicle state estimation. Through combination of inertial prediction and physical constraint correction, a drift problem in state estimation is effectively solved.

The embodiment of the invention provides a discrete semiconductor device testing method and related equipment thereof, and is applied to the technical field of semiconductor testing. The semiconductor discrete device testing method comprises the following steps: carrying out a composite stress working condition test on a semiconductor discrete device to be tested according to an electric stress condition and a thermal stress condition so as to synchronously collect an original real-time response data set, and carrying out filtering and working condition feature extraction processing on the real-time response data set to generate a device state time sequence queue, and performing spatial conversion and recursive filtering estimation on the device state time sequence queue according to a state space mapping strategy to generate aging state trend data, and performing aging time sequence prediction on the device state time sequence queue and the aging state trend data according to a constraint condition set to obtain life probability distribution data. According to the method, aging parameters are estimated through online multi-channel electrothermal response acquisition, feature normalization and unscented Kalman filtering, and conditional probabilistic residual life evaluation is provided in combination with time sequence fusion prediction with prospective covariables.

This disclosure provides systems, methods, and devices for the prevention of color leakage in Field Sequential Display while maintaining display brightness. In a first aspect, a method of signal processing includes receiving a first frame of a first color of image data; selecting a modified first frame of the first color by applying a recursive filter to the first frame, wherein the recursive filter is associated with at least one previous frame of a second color different from the first color; and selecting first pixel drive values associated with the modified first frame. Other aspects and features are also claimed and described.

This disclosure provides systems, methods, and devices for the prevention of color leakage in Field Sequential Display while maintaining display brightness. In a first aspect, a method of signal processing includes receiving a first frame of a first color of image data; selecting a modified first frame of the first color by applying a recursive filter to the first frame, wherein the recursive filter is associated with at least one previous frame of a second color different from the first color; and selecting first pixel drive values associated with the modified first frame. Other aspects and features are also claimed and described.

The present invention provides a method for calibrating the head of a fault traveling wave. The method comprises obtaining a measurement value sequence of a current traveling wave signal; performing mean filtering on the measurement value sequence according to a fixed-width sliding window to obtain a filtered data sequence; roughly determining the position of the traveling wave head based on the filtered data sequence, selecting noise samples, and obtaining a noise sample data set; calculating noise distribution parameters based on the noise sample data set; constructing a recursive filter based on the noise distribution parameters; recursively filtering the measurement value sequence based on the recursive filter to obtain a signal estimation value sequence; and performing head calibration based on the signal estimation value sequence. The present invention has the ability to adaptively identify noise characteristics, can effectively filter out noise in the fault traveling wave measurement signal, improve the signal-to-noise ratio of the traveling wave signal, and has high head calibration accuracy and reliability.

The invention relates to the technical field of roughness measurement, and discloses a metal part surface roughness online measurement and feedback control method, which comprises the following steps: acquiring a structured light image modulated by a surface to be measured to obtain an original stripe image; performing phase demodulation on the original fringe image, extracting phase distribution data, and converting the phase distribution data into a three-dimensional space coordinate point cloud of the surface to be measured; obtaining a theoretical residual height in the current machining process parameters, and performing multi-scale wavelet decomposition on the three-dimensional space coordinate point cloud to obtain an initial roughness parameter; inputting the initial roughness parameter and the main shaft rotating speed, the feeding speed, the cutting depth and the accumulated cutting time which are acquired in real time into a recursive filter of the metal part so as to generate a target roughness value; a machining parameter adjusting instruction is generated; the machining parameter adjusting instruction is transmitted to a numerical control terminal of the metal part so as to adjust follow-up cutting parameters; according to the invention, the efficiency of online measurement and feedback control of the surface roughness of the metal part can be improved.

The invention relates to the field of industrial automatic detection, in particular to a non-contact laser online measurement method for the thickness of a corrugated board. The method comprises the following steps: collecting a vertical distance signal of the surface of a corrugated board and a real-time pulse signal of a conveyor belt, and constructing an equidistant spatial domain sequence; calculating instantaneous gradient and local energy characteristics of the sequence, calculating a separation coefficient by using a nonlinear classification function, and adaptively updating a vibration datum line through recursive filtering to obtain geometric thickness; based on a viscoelastic mechanical model, calculating vertical acceleration by utilizing second-order difference of a vibration datum line, and calculating compression deformation quantity generated by inertia force in combination with corrugated board surface density and dynamic compressive modulus; and superposing the geometric thickness and the compression deformation quantity to obtain a real physical thickness. According to the method, vibration and texture of frequency domain overlapping are analyzed through phase space projection, dynamic compression errors are compensated from the physical level, and the measurement precision under the high-speed working condition is improved.

The invention discloses a data privacy protection dynamic filtering method in a low-precision measurement environment. The method comprises the following steps: 1, analyzing and establishing a time-varying network system model; 2, designing a coupling filter structure, and determining the upper bound of a prediction step error covariance matrix; 3, solving an estimator adjustment parameter; 4, substituting into a coupling filter to obtain a state deduction at a sampling point; if yes, continuing to execute the next step, and if not, jumping out of circulation, and ending algorithm operation; 5, calculating the upper bound of the covariance of the state inference error; and repeating the step 1 to the step 4 until a cut-off condition is satisfied. According to the method, interference under the combined action of a low-precision measurement environment and data privacy protection is effectively overcome, the robustness of a time-varying recursive filtering algorithm is guaranteed, and the filtering precision is remarkably improved.

The present invention relates to the technical field of centrifugal pump fault diagnosis and classification, and specifically to a method for fault diagnosis of centrifugal pump acoustic radiation signals, comprising: obtaining a first acoustic radiation signal under different working conditions; filtering the first acoustic radiation signal with a non-recursive filter to obtain a second acoustic radiation signal; converting the one-dimensional time series of the second acoustic radiation signal into a two-dimensional GASF image as a sample set using a Gram angle field; improving a densely connected convolutional network structure and optimizing the hyperparameter combination of the network structure using a Bayesian optimization algorithm to obtain an acoustic radiation signal fault diagnosis model; and using the acoustic radiation signal fault diagnosis model to perform centrifugal pump fault diagnosis. The present invention converts a one-dimensional time series signal into a two-dimensional image, which can retain the time information of the fault feature and help improve the fault recognition rate. At the same time, the Bayesian optimization algorithm obtains the hyperparameters of the improved densely connected convolutional network, so that the improved densely connected convolutional network has a faster convergence speed and a higher fault recognition accuracy.