27 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.

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 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.

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 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 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.

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.

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 invention relates to a self-adaptive weighted recursive filtering method of an ultrasonic gas flowmeter, in particular to a method for carrying out self-adaptive weighted and recursive filtering processing on transit time measurement data in the ultrasonic gas flowmeter, and belongs to the field of ultrasonic flow measurement. The method comprises the following steps: S1, taking downstream transit time and countercurrent transit time obtained in a current measurement period as input data of a filtering algorithm; s2, reference transit time under the zero-flow working condition is introduced, and down-flow transit time decrement and counter-flow transit time increment are calculated; and S3, according to a difference value between the downstream transit time decrement and the countercurrent transit time increment and a change relationship between a current measurement value and a previous filtering output value, constructing an adaptive weight of the measurement data, and carrying out weighted recursive average operation on the transit time data in a preset filtering window to obtain a stable transit time filtering result. According to the scheme, by combining the physical consistency characteristics of the forward and reverse flow transit time, abnormal or incredible measurement data are inhibited, and the influence of flow field fluctuation, gas parameter change and system noise on the transit time measurement result is effectively reduced. Compared with a traditional filtering method, the method has the advantages that no extra hardware circuit needs to be added, high-stability filtering processing can be achieved only by depending on transition time data, and the measurement reliability of the ultrasonic gas flowmeter is improved.

This invention discloses an optical communication signal processing method and apparatus. The interference suppression method includes performing a first-stage recursive filtering process on the received signal after photodetection using a first smoothing factor to extract a first component of the interference signal, and then using this component to perform a first-stage interference cancellation process on the received signal to obtain a first-stage correction signal. This recursive filtering configuration can effectively extract and eliminate multipath interference in the optical communication system, while requiring minimal computational resources and power consumption. This significantly improves the reception quality and bit error rate performance of the optical communication system while significantly reducing the computational complexity and power consumption during high-speed computation.

The application provides a recursive filtering method for a state-saturated system based on a high-speed network under the influence of a deception attack. The method specifically comprises the following steps: constructing a dynamic model of a state-saturated system to be studied, wherein the dynamic model comprises a system state and a measurement output model, and conditions that functions in the dynamic model satisfy are set; constructing a new measurement model based on a high-speed network and a random deception attack according to the measurement output model, and setting constraints that the deception attack satisfies; designing a state-saturated recursive filter according to the dynamic model and the new measurement model; obtaining a filtering error dynamic equation according to the system dynamic model and the filter model, and calculating a filtering error covariance upper bound; obtaining an optimal filter gain by minimizing the filtering error covariance upper bound; and verifying the effectiveness of the recursive filtering method through a numerical simulation example. The simulation experiment verifies the effectiveness of the proposed recursive filtering method, and the method is suitable for online calculation and exhibits good real-time performance.

Noise-canceling headphones. Headphones (10) include: - an electro-acoustic transducer (16); - at least one noise-canceling chain including: - an external microphone (31A, 31B) and an internal microphone (32); - a noise-canceling filter (30) for processing the signal from the external microphone (31A, 31B) to produce an external noise-canceling signal (sE), which noise-canceling filter (30) includes: - mounted between the external microphone (31A, 31B) and the output delivering the external noise-canceling signal (sE): at least one finite impulse response (FIR) filter (38); and at least one recursive (IIR) filter (40), - an update unit (252) for each finite impulse response (FIR) filter (38);and - a unit (42) for updating the recursive filters (IIR) based on at least one external anti-noise setpoint signal for the recursive filter (sRABE-f 1, sRABE-f2) from the external microphone (31A, 31B) and a raw error signal (em) from the internal microphone (32). Figure for the abstract: 2;

The invention discloses a hyperspectral image classification method based on superpixel spectrum similarity measurement, which comprises the following steps of: extracting first three principal components to synthesize a false color image based on principal component analysis, and generating spatial coherent superpixel units by adopting an entropy rate superpixel segmentation algorithm, so that not only is the integrity of a spatial structure maintained, but also the internal spectrum information is reserved; performing edge preserving filtering processing on the original hyperspectral image by adopting domain transformation recursive filtering; spectral domain noise separation and data dimension reduction are carried out through maximum noise fraction transformation, and minimum-maximum normalization processing is carried out on all spectral features to eliminate dimension differences; the minimum spectral Euclidean distance between a test sample and each category of training samples is calculated in each superpixel unit to form a distance matrix, the most representative test pixel is screened by adopting a k-nearest neighbor average strategy to calculate a similarity score, and finally a category label with the highest similarity score is allocated to all pixels in the whole superpixel.

This application relates to the fields of industrial automation control and wireless communication technology, and discloses a 4G real-time transmission system for the operation data of a metallurgical remote-controlled rail locomotive. The system includes an onboard terminal layer, a 4G transmission network layer, and a ground control layer. The onboard data acquisition unit uses an embedded microprocessor to construct a discrete state-space model and performs recursive filtering on sensor data to output standard physical quantities. The 4G transmission unit communicates encrypted with the ground via a dedicated APN channel and the MQTT protocol. The ground data processing server executes instruction and data co-verification logic, quantifies service execution deviations to assess link quality, and triggers QoS adjustments or dual-link redundant transmission accordingly. Furthermore, the system utilizes a local ring buffer and cross-transmission mechanism to dynamically adjust the retransmission rate based on signal strength after network recovery. This invention effectively filters out noise in the industrial environment and solves the problems of difficulty in identifying hidden connection faults and the blockage of real-time channels by historical data retransmission.

The application provides a kind of tubing leak detection method and system based on maximum entropy unscented Kalman filtering under coding and decoding mechanism, belong to tubing leak detection field.To solve the problem that the existing oil pipeline leak detection method lacks in detection and positioning accuracy of leakage point due to nonlinear characteristics, non-gaussian noise and limited transmission channel.The application establishes the dynamic model of oil pipeline system, introduces dynamic coding and decoding mechanism to construct recursive filter structure;Using unscented transformation to get priori estimation and error covariance;Then calculate the upper bound matrix of estimation error covariance by matrix inequality, introduce the maximum correlation entropy index to calculate the estimation error and gain matrix;Finally, by setting virtual leakage point to estimate leakage, to determine whether the pipeline leaks and locate the leakage point.Simulation results show that the application can effectively cope with real-time and reliability challenges under complex working conditions, and provides an efficient state estimation method for oil pipeline leak detection.

The application belongs to the technical field of computer vision. The application provides a hyperspectral space-spectrum mask variational auto-encoding anomaly detection method for on-site security. The space-spectrum joint mask technology designed in the embodiment of the disclosure fully utilizes the multi-dimensional information of space and spectrum, improves the difficulty of effectively reconstructing the abnormal area in the reconstruction process of the network, makes the network pay more attention to the normal spatial and spectral features when learning the image data distribution, and significantly improves the detection ability of complex abnormal scenes. The VAE reconstruction network and the mask combination mechanism designed fully utilize the advantages of probability modeling of VAE and the advantages of attention mechanism of mask, improve the accuracy and generalization ability of anomaly detection, and strengthen the explainability of the model. And the residual image processing method designed through the domain transformation recursive filter effectively relieves the noise problem caused by the complex background, and realizes higher detection precision and robustness.