11 results about "Nonlinear filtering" patented technology

The application provides a kind of nonlinear filtering method of pulse eddy current detection signal, belong to nondestructive testing technical field, can at least partially solve the problem that magnetic field decay voltage signal is greatly influenced by noise in pulse eddy current detection, traditional smoothing filter is easy to introduce signal distortion.The method is used for the pulse eddy current detection signal receiving processing of metal structure with cladding layer, comprising: collecting magnetic field decay voltage signal in pulse eddy current detection process;Nonlinear compression transformation is carried out on the time axis corresponding to the magnetic field decay voltage signal;Smooth filtering time window of preset length is set on the time axis after nonlinear compression, and the corresponding conventional time interval is determined;The magnetic field decay voltage signal falling into the conventional time interval is carried out smoothing filter processing, and the filtered pulse eddy current detection signal is obtained.The application makes the filtering process match the time characteristics of the magnetic field decay signal, improves the stability of signal processing, and is beneficial to subsequent wall thickness or state evaluation.

The application relates to the technical field of ecological protection and restoration, and discloses a multi-star lily and competitive species interaction regulation and population natural renewal restoration method and system, which comprises the following steps: based on multi-period sample plot monitoring data, a multi-star lily-competitive species dynamic model containing non-integer time lag and nonlinear density index is established; nonlinear filtering is adopted to perform state online estimation on noise-containing monitoring data, and state estimation values and uncertainty measurements thereof are output; according to the state estimation values and the uncertainty measurements thereof, rolling optimization regulation and decision-making are performed through scene analysis and weight construction based on gradient difference; the natural renewal restoration potential is evaluated, and the grade of auxiliary measures is determined; and the restoration scheme is dynamically adjusted in a monitoring-estimation-decision-implementation-remonitoring closed loop. The application can be used for competitive regulation and ecological restoration of a multi-star lily degraded population in a karst mountain meadow, and the stability of the multi-star lily degraded population restoration is improved.

This invention provides a biomimetic lateral line communication system based on propeller wake field perception, belonging to the field of underwater communication technology. Based on the lateral line perception mechanism of fish, it utilizes the flow field disturbance signal generated by the interaction between the propeller and the flow field as the communication signal to achieve network communication for underwater robots. The flow field disturbance of the main propeller is converted into a carrier signal to increase the transmission distance and intensity, while the disturbance of the modulation propeller is converted into a modulation signal for information transmission. A neural network model and a nonlinear filtering model are used to achieve signal modulation and demodulation, exhibiting good environmental adaptability and improving the working efficiency and accuracy of the detection system. The beneficial effects of this invention are: the signal source used for biomimetic navigation perception is the flow field medium fluctuation signal, which can provide a novel approach and practical detection sensing means for underwater covert detection and guidance tracking technology.

This invention relates to the field of underwater positioning technology, specifically to an AUV cooperative positioning method based on generalized maximum correlation entropy and capacitive Kalman filtering (CKF) that can effectively improve positioning accuracy. This invention employs GMCC and introduces a generalized Gaussian density kernel function to measure the error of the nonlinear filtering algorithm using generalized correlation entropy. The generalized Gaussian kernel function has the advantages of having many parameters, flexible variation, and adaptability. It can achieve the maximum correlation entropy when the error is minimized. Because the generalized Gaussian kernel contains even-order higher moments of the errors of two variables, it can better handle heavy-tailed noise and large outliers. Experimental verification shows that the technical solution of this invention has better robustness and reliability, and can better handle problems such as outliers and heavy-tailed noise interference. Compared with the traditional CKF, this invention can improve positioning accuracy.

This invention provides a method, system, and device for detecting and locating leaks in water supply pipes based on a probabilistic model and nonlinear filtering. The method includes: acquiring information about the water supply pipeline, such as the length, diameter, friction, and elastic modulus of each pipe; constructing a pure hydraulic model based on the water supply network information; solving the continuity and momentum equations of the water supply network using the method of characteristics; establishing a probabilistic multiple leakage model based on the circumferential stress and yield stress of the pipes, combined with the solution of the differential equation system, to determine the location and quantity of leaks in the pipeline; and using nonlinear filtering to estimate the state space in a noisy environment to achieve real-time correction and prediction of leaks. This invention considers the situation of multiple leaks in the water supply network and the water pressure difference between horizontal and non-horizontal pipes. Starting from a pure hydraulic model, it effectively solves the original partial differential equation system using the method of characteristics, effectively reducing the high false alarm rate problem of deterministic models.

The present disclosure provides methods and systems for determining information of a sample location. One system includes a computer subsystem configured to input one or more images of a sample location into a zone-based neural network configured to perform digital nonlinear filtering on the one or more images to thereby generate filtered images of the sample location. The computer subsystem is further configured to determine information of the sample location from the filtered images.

This invention relates to the field of cable inspection technology and discloses a machine vision-based online inspection system for surface defects in cable sheaths using a small sample size. The system includes acquiring multi-angle surface image sequences during cable transmission using an industrial camera array; a lighting compensation device dynamically adjusts light source parameters based on the reflective characteristics of the cable sheath material to eliminate glare and shadow interference; an image feature extraction engine performs multi-scale texture decomposition on the compensated images to generate a primary feature set containing local grayscale change rates, directional gradient histograms, and spatial frequency distributions; a defect feature enhancement module enhances the edge continuity of cracks and pits through nonlinear filtering to form an enhanced defect feature map. Based on a small sample feature comparison library, a real-time defect detector locates abnormal regions with differences exceeding a threshold through pixel-by-pixel similarity calculation, adapting to the real-time inspection needs of cable production lines.

Systems and methods are provided for automated image analysis of volumetric image data depicting blood vessels. Volumetric imaging data, such as computed tomography angiography data, are processed by an image segmenter implemented as a convolutional neural network to generate a lumen mask identifying vessel lumen within the volumetric image data. In implementations, the image segmenter predicts binary masks on multiple two-dimensional slices extracted from the volumetric image data along different axes and / or angles, and the predicted masks are combined by voting, averaging, and / or nonlinear filtering to form a three-dimensional lumen segmentation. A three-dimensional segmented vessel model is formed from the lumen segmentation, a narrowing region is detected, and dimensional parameters of the narrowing region are computed, including at least stenosis length, stenosis thickness, and minimum lumen cross-sectional area. The dimensional parameters are output in a machine-readable format. Optionally, computational flow parameters and classification outputs may be generated.

The application provides an electrical layer fault time determination method adopting multi-value discriminant comparison, and is used for a height measurement system adopting four kinds of measurement devices, namely, inertial components, radio altimeter, diaphragm capsule barometric altimeter and GPS height measurement device, for redundancy fusion measurement; four kinds of signals, namely, inertial height, radio height, diaphragm capsule barometric height and GPS height, are respectively subjected to nonlinear filtering transformation, and then four kinds of filtering speed signals and filtering signals are obtained; the inertial components are independently measured, the interference probability is small, therefore, the relative error data and the absolute error data are obtained by comparing the latter three with the inertial components; the threshold valve is set to judge the time when the fault occurs, and the component causing the fault is further judged according to the mutation of the filtering speed signal; the method has the advantages of accurate judgment and simple implementation.

The application discloses a wireless charging communication data packet real-time decoding method and system for a smart tire, relates to the technical field of wireless power supply and charging monitoring of a tire inner unit of a smart tire, and comprises the following steps: high-frequency sampling of the differential voltage at both ends of the transmitting coil of a wireless charging transmitting end; extracting a peak value point according to a carrier cycle; performing nonlinear filtering on the peak value sequence to obtain a filtered peak value sequence, segmenting according to a time window, generating a dynamic decision threshold corresponding to the time window, and detecting a level flip point of a high-low level sequence; performing bit decision according to the duration between adjacent level flip points; when the detected duration does not satisfy the bit decision condition, performing abnormal reset; performing preamble synchronization in the bit stream obtained in the bit decision, analyzing a header and an information field according to an asynchronous serial byte structure, performing check, and obtaining a real-time decoding result of the wireless charging communication data packet; and the application can realize real-time monitoring and reliable decoding of a communication packet on the transmitting end side.

The super-resolution image enhancement system and method of the variational modal decomposition algorithm of the application, the system comprises an adaptive decomposition module, an enhancement processing module, a fusion module and an optimization module. The adaptive decomposition module receives a low-resolution image signal, generates a modal component signal containing different frequency band characteristics, and outputs a modal number parameter signal according to the image frequency energy distribution. The enhancement processing module comprises a high-frequency enhancement unit and a low-frequency reconstruction unit, and generates a high-frequency enhancement signal and a low-frequency reconstruction signal. The fusion module receives the modal number parameter signal, the high-frequency enhancement signal and the low-frequency reconstruction signal, and performs spatial adaptive weighted fusion on the high-frequency and low-frequency signals through a dynamic weight coefficient to generate an initial high-resolution signal. The optimization module performs adaptive nonlinear filtering processing on the initial high-resolution signal. The super-resolution image enhancement system of the variational modal decomposition algorithm of the application can solve the problem that the prior art is difficult to adapt to complex image structures.