4 results about "Deconvolution filter" patented technology

The invention relates to the technical field of nondestructive testing, in particular to a copper bar coating lower substrate defect nondestructive testing device based on terahertz waves, which comprises a terahertz scanning acquisition module used for controlling a transmitting and receiving unit to perform two-dimensional scanning so as to acquire an original waveform; the flight time dynamic correction module is used for resolving the local coating thickness and carrying out dynamic time axis alignment; the substrate roughness deconvolution module is used for calling the reference model to carry out deconvolution filtering so as to strip background scattering noise; the interface dielectric feature analysis module is used for extracting a dielectric feature vector reflecting an interface dielectric constant mutation state; the defect risk assessment imaging module is used for constructing a three-dimensional chromatography map and outputting a detection result; according to the method, the physical characteristic decoupling of the signal source is realized, the coating thickness fluctuation and the real defect are effectively distinguished, the misjudgment rate is obviously reduced, and the evaluation accuracy is ensured.

Systems and methods are disclosed. The method includes, for each of a plurality of spatial partial differential equations (sPDEs) within a wave equation, determining a linear system of equations using an approximate solution at a plurality of grid nodes. The linear system of equations includes an inverse matrix, a first vector, and a second vector. The method further includes, for each of the plurality of sPDEs, evaluating the inverse matrix by evaluating a first portion of the inverse matrix using a first deconvolution filter and evaluating a second portion of the inverse matrix using a second deconvolution filter. The method further still includes, for each of the plurality of sPDEs, evaluating the first vector using the evaluated inverse matrix and the second vector as well as determining the wavefield using the evaluated first vector for each of the plurality of sPDEs, a velocity model, and the wave equation.

A method for deblurring distortion-corrected images, includes: obtaining a video-see-through (VST) image of a real-world environment; determining a given region of the VST image, based on at least one of: a distortion profile of a camera lens of at least one VST camera, blur characteristics of the camera lens, a scaling ratio between a resolution of the at least one VST camera and a resolution of a display whereat the VST image is to be displayed; and performing an undistortion deblurring operation on the given region of the VST image, by utilising at least one of: (i) a deblurring deconvolution filter, (ii) at least one neural network, based on locations of pixels of the given region, to generate an output image.

The invention discloses a gear fault diagnosis method and system based on maximum CGGI deconvolution filtering, and relates to the technical field of mechanical fault diagnosis, and the method comprises the steps: collecting a vibration signal of a gear transmission system; performing generalized envelope spectrum transformation on the vibration signal to obtain multiple groups of generalized envelope spectrums, constructing a weight coefficient based on Gini indexes corresponding to the generalized envelope spectrums, and performing weighted summation on the multiple groups of generalized envelope spectrums to obtain a generalized weighted envelope spectrum; calculating a generalized Gini index based on the generalized weighted envelope spectrum, and rewriting the generalized Gini index into a cyclic embedding generalized Gini index based on a cyclic embedding sparsity measurement method; and taking the maximized cyclic embedding generalized Gini index as an objective function of blind deconvolution filtering, solving a filter coefficient by adopting a feature vector algorithm, performing deconvolution on the vibration signal, and outputting an optimal deconvolution filtering signal. The stability and consistency of a deconvolution result are improved, and a clearer feature expression basis is provided for gear fault recognition.