205 results about "Echo time" patented technology

The invention relates to a magnetic resonance imaging method and device and a storage medium, and the method comprises the steps: scanning a target region through employing a first magnetic resonance sequence, setting a plurality of echo times, and collecting a plurality of spin echo images; recording a plurality of echo times and corresponding dispersion sensitivity coefficients according to the first magnetic resonance sequence; scanning the target area by using the second magnetic resonance sequence to obtain an apparent dispersion coefficient; and according to the plurality of spin echo images, the plurality of echo times, the dispersion sensitivity coefficient and the apparent dispersion coefficient, fitting to obtain a transverse relaxation time constant quantitative image for correcting the dispersion influence. According to the method and the device, the problem of dispersion when a magnetic resonance transverse relaxation time constant quantitative image is obtained through a variable echo time spin echo method in the prior art is solved, and the beneficial effect of effectively improving the quantitative accuracy is achieved.

The invention provides an electromagnetic ultrasonic bolt stress detection system based on a space-time complementation algorithm, and the system comprises the steps: carrying out the multi-channel ultrasonic signal collection of a to-be-detected bolt, and obtaining a multi-channel echo signal group; performing time-varying attenuation compensation and adaptive entropy weight denoising on the multi-channel echo signal group to obtain a denoised echo signal group; extracting echo time-domain features from the de-noised echo signal group, performing segmented time-frequency feature extraction on the de-noised echo signal group based on a short-time sliding window to obtain echo time-frequency features, and fusing the echo time-domain features and the echo time-frequency features into ultrasonic time-frequency features; performing wave field reconstruction on the de-noised echo signal group to obtain a spatial ultrasonic energy diagram, and extracting ultrasonic spatial features of the spatial ultrasonic energy diagram based on a self-attention map convolutional network; performing correlation detection and space-time complementary modeling on the ultrasonic time-frequency features and the ultrasonic space features to obtain ultrasonic space-time joint features, and performing stress analysis on the ultrasonic space-time joint features to obtain bolt stress data.

The invention relates to the technical field of water level online measurement, and discloses a water level measurement method and system based on ultrasonic waves. According to the invention, a variable time-sharing amplification circuit with a dynamic range is adopted, and the amplification times of echoes with different distances are automatically changed, so that the amplitude of an echo signal is kept to be more than five times of that of noise, and the influence of the noise on the measurement precision is effectively avoided; the method comprises the following steps of: receiving an echo signal, carrying out digital shaping on the echo signal according to a standard echo waveform near an echo peak value, and taking time corresponding to a waveform vertex after shaping as echo time, so that the influence of the measurement accuracy of echo waveform distortion is eliminated through the technology; meanwhile, the method that optimization is carried out after continuous three times of measurement is adopted, and the accidental phenomena of no echo and measurement value jumping can be effectively eliminated.

The invention discloses a current transformer oil level monitoring system based on ultrasonic echo detection, which relates to the technical field of electric power monitoring and comprises the following steps: acquiring original echo time sequence data; calculating the distance between the transmitting end and the top of the metal expander by combining the propagation velocity of the ultrasonic waves in the air; and when the oil level height value is lower than a set threshold value, an alarm signal is triggered. According to the invention, the problems of easy clamping stagnation, complex installation, large temperature drift and environmental interference and the like of the traditional float-type, pressure-type and window observation methods are effectively overcome, remote uploading and local acousto-optic prompt are supported, and intelligent inspection and fault pre-warning identification under unattended operation are realized; and the operation safety, the monitoring reliability and the operation and maintenance intelligent level of the oil-immersed current transformer are remarkably improved.

The invention discloses a sonar target motion identification method based on a low-frame-rate bright spot structure sequence. The sonar target motion identification method comprises the steps of 1, roughly intercepting a bright spot structure; 2, accumulating a bright spot structure, sonar platform information and tracking information; step 3, motion compensation of the sonar platform; 4, accurately intercepting a bright spot structure; and 5, searching the optimal radial speed. According to the method, target radial motion parameters are extracted by means of distance steep motion of a sonar target among multiple frames of echoes, and a speed estimation loss function based on bright spot structure global optimal estimation is innovatively designed for the problems that the time interval between adjacent echoes of a low-frame-rate sonar target is long and the bright spot structure fluctuates greatly. According to the method, the global similarity between input period bright spot structures is fully utilized, the distance steep motion measurement precision is improved, the radial speed of the sonar target can be given at the same time, and the motion identification precision and stability of the sonar target are improved.

The invention belongs to the field of ocean wave feature extraction, and particularly relates to a sea wave feature inversion method based on reverse echo measurement, which comprises the following steps of: acquiring an echo signal from a seabed to an ocean surface, and performing adaptive time window smoothing processing on the echo signal to obtain an echo signal; carrying out abnormal value identification and missing data filling on the smoothed data; removing abnormal values by adopting an improved Tukey method, and filling missing data by adopting a segmented cubic spline interpolation method; through high-pass filtering and detrending processing, sea wave echo signals with low-frequency trends removed are obtained; and selecting a proper time window to calculate the dispersion of echo time, establishing a mathematical relationship between the dispersion and the significant wave height through a regression algorithm, and substituting observation data into an equation to obtain an inversion result of the significant wave height. According to the method, the sea waves are subjected to feature inversion based on the reverse echo measurement technology, the precision of sea wave feature extraction is effectively improved, the field measurement cost is reduced, and the stable and low-cost sea wave measurement method is provided.

The invention discloses an audio-based information hidden transmission method, an audio decoding method and electronic equipment, which are applied to the field of communication. The audio-based information hidden transmission method comprises the following steps: acquiring to-be-embedded original information; generating symbol information according to the original information; obtaining a time delay corresponding to each symbol in the symbol information, obtaining an original audio carrier, and sequentially embedding the time delay corresponding to each symbol into the original audio carrier to generate an echo frame; and combining the echo frame and the original audio carrier to obtain a target audio. The original information to be embedded is embedded into the original audio carrier in the form of echo time delay, so that the confidentiality and security of the communication process are improved, and even if the target audio is accidentally recorded by third-party recording equipment, the embedded original information can still be analyzed from the recorded audio so as to trace the leakage source.

The embodiment of the invention provides a natural gas leakage detection method and device, electronic equipment and a storage medium. The natural gas leakage detection method comprises the steps that all leakage areas of natural gas in a station are recognized; directionally transmitting an ultrasonic detection signal to each leakage area, and calculating the position information of each leakage area according to the echo time of the ultrasonic detection signal in each direction; calculating the natural gas concentration of the corresponding leakage area according to the gas temperature and the gas molecular weight of each leakage area; and displaying the position information and the natural gas concentration of each leakage area in a detection map of the station. According to the embodiment of the invention, through automatic and remote monitoring technologies, the exposure time of personnel on site is reduced, the safety risk is remarkably reduced, and powerful support is provided for emergency rescue work through accurate monitoring and visualization means.

The invention discloses a bolt pre-tightening force prediction method based on ultrasonic echo time-frequency characteristics, and the method comprises the steps: S1, carrying out the ultrasonic excitation of a target bolt, obtaining an ultrasonic echo signal generated by the bolt, and carrying out the time-frequency analysis, and forming an initial time-frequency characteristic matrix; s2, according to a bolt material characteristic database, determining characteristic parameters of ultrasonic echo propagation corresponding to a target bolt material, and performing weighting processing on the initial time-frequency characteristic matrix to obtain a weighted time-frequency characteristic matrix; s3, extracting a time-frequency characteristic index through the weighted time-frequency characteristic matrix, and forming a target characteristic vector; and S4, inputting the target feature vector into the trained double-branch prediction model, outputting a pre-tightening force energy feature value and a pre-tightening force state change value, inputting the pre-constructed neural network model, and outputting a bolt pre-tightening force prediction value. According to the method, the bolt pre-tightening force can be predicted with high precision and high reliability, and the technical problems of low prediction precision and great environmental influence are solved.

The invention provides a method and a system for identifying environment abnormity in a direct-current battery swap station. The method comprises the following steps: fusing multi-source images acquired by the direct-current battery swap station; determining at least one suspected abnormal region based on the fused image; constructing a three-dimensional structure model of an object in the suspected abnormal area based on reflection deformation information of structured light projected into the suspected abnormal area for multiple times; determining reflection change information of the object in the suspected abnormal area based on reflection echo intensity and reflection echo time of the obtained ultrasonic wave on the surface of the object in the suspected abnormal area; and performing logic correlation analysis based on the three-dimensional structure model and the reflection change information, and determining a target abnormal region in the to-be-identified direct-current battery swap station. According to the method and the system, the capability of identifying tiny and hidden abnormal objects of the direct-current battery swap station is greatly improved, missed judgment is effectively reduced, the accuracy and the reliability of environment abnormity identification in the direct-current battery swap station are improved, and stable operation of the battery swap station is guaranteed.

A method for acquiring a magnetic resonance image dataset of a field-of-view using a gradient-echo imaging protocol includes acquiring additional k-space lines within a central region of k-space at intervals throughout the imaging protocol, wherein the additional k-space lines are used for estimating motion parameters of the field-of-view. The imaging protocol has been amended by inserting additional gradient blips after at least some of the RF excitations, such that at least one additional gradient echo is generated, allowing the acquisition of at least one additional k-space line during one echo time.

The invention relates to the technical field of ultrasonic wind measurement, in particular to a high-precision wind measurement system and method based on double-frequency ultrasonic waves, and the method comprises the steps: deploying an orthogonal double-frequency ultrasonic transducer array in a horizontal plane, capturing an echo timestamp, and solving the wind speed through the dynamic changes corresponding to the high and low frequency characteristics; according to the forward and reverse wind round-trip time difference of the double-frequency ultrasonic waves on the X axis and the Y axis, the real-time temperature obtained through temperature compensation is combined, the wind speed components of the high-frequency ultrasonic waves and the low-frequency ultrasonic waves are calculated according to a forward and reverse wind formula, the X-axis final wind speed component and the Y-axis final wind speed component are obtained through weighted averaging, the wind direction angle is calculated according to an arc tangent function, and wind speed and direction results are output after quadrant correction; the wind speed and direction data obtained through calculation are preprocessed, and finally the processed data are stored in an internal storage. Double-frequency ultrasonic waves are adopted, high frequency is used for capturing rapid wind speed changes, low frequency is used for long-distance propagation to reduce environmental noise influences, the wind speed is solved in combination with a sound velocity formula, temperature compensation and a propagation equation, and high-precision measurement can be achieved.

The invention discloses a submarine topography surveying and mapping method and system based on an underwater robot, relates to the technical field of underwater robots, and provides reliable basic data for measurement based on an original measurement point sound wave data set S, and extracts a multipath disturbance feature set F of each sonar scanning point; the multi-path interference in the underwater environment is effectively identified and represented, data are clustered through density clustering analysis, dense clusters and discrete points are successfully identified, then a disturbance residual Cc is obtained and compared with a preset interference judgment threshold Omap, each sonar scanning point is endowed with a multi-path label, and the multi-path interference in the underwater environment is effectively identified and represented. According to the method, the time sequence and the amplitude sequence of sonar scanning points are combined, the main path echo time of each measuring point is accurately obtained, the continuity of landforms is effectively judged, and high precision and stability of underwater topographic survey are ensured, especially in the aspects of multi-path interference elimination, main path reconstruction judgment and final accurate topographic reflection.

The invention provides a water quality pollution tracing method and system applied to a wave radar sea area, and the method comprises the steps: firstly obtaining a sea area polarization echo time sequence set captured by a wave radar and a sea area pollutant characteristic set measured synchronously, and then carrying out the polarization characteristic deconstruction processing of the sea area polarization echo time sequence set; a polarization characteristic parameter set of each sea area block is obtained, then a pollutant molecular structure and a polarization reflection coefficient in the sea area pollutant characteristic set are associated and adapted with the polarization characteristic parameter set to generate a pollution polarization association map, and a polarization-driven pollution traceability model is constructed based on the pollution polarization association map. The method comprises the steps of inputting a pollution polarization correlation map and preset sea area ocean current parameters, outputting a traceability path set of pollutants and an initial pollution area boundary, finally analyzing an original diffusion starting point of the pollutants according to a polarization-driven pollution traceability model, and generating a pollution traceability report containing information such as coordinates of the initial pollution area. Therefore, a sea water quality pollution source can be accurately positioned.

The invention discloses an ultrasonic imaging system and method based on a heart surface, a medium and a product, the system comprises an ultrasonic detection assembly and an imaging terminal which are in communication connection, an ultrasonic transducer is packaged at the head end of an attached ultrasonic probe in the ultrasonic detection assembly, and an acoustic window on the ultrasonic transducer is planar; the ultrasonic transducer is used for being attached to the surface of the heart or the aorta, and the plane of the ultrasonic transducer is parallel to the plane of the acoustic window; and the imaging terminal is used for generating a sound velocity mask pattern according to the reference ultrasonic image, determining echo time delay data according to the sound velocity mask pattern, synthesizing and reconstructing the radio frequency signal data according to the echo time delay data to obtain an ultrasonic image, performing motion compensation on the image sequence, performing multi-modal fusion on the ultrasonic image subjected to motion compensation, and obtaining a final ultrasonic image. The problem of acoustic interference of anatomical structures such as the chest wall and the esophagus in a traditional echocardiography technology is solved, and real-time and high-quality image support is provided for cardiac surgery.

The invention relates to a magnetic resonance imaging electromagnetic parameter distribution scanning and calculation method, which comprises the following steps that a fast spin echo sequence I is adopted to scan a target body, parameters are (alpha1, TE0, TR0 and Bw1), alpha is a deflection angle, TE is echo time, TR repetition time and Bw receiving bandwidth; scanning a target body by adopting a fast spin echo sequence II, wherein parameters are (alpha2, TE0, TR0 and Bw1); scanning a target body by adopting a fast spin echo sequence III, wherein parameters are (alpha2, TE0, TR0 and Bw2); and scanning the homogeneous water model by adopting the fast spin echo sequences I, II and III. And under the condition that the magnetic vector precession meets the conditions that the amplitudes are comparable when the phases are the same and the phases are differentiable when the amplitudes are the same, each magnetic field and electric field parameter is calculated based on the homogeneous water model data. According to the invention, decoupling of the proton density and the sensitive field of the signal is realized, so that magnetic resonance weighted quantization imaging becomes possible.

The invention discloses a radar target detection method based on graph node dual-channel feature attention fusion, and belongs to the technical field of radar signal detection, and the method comprises the following steps: 1, carrying out the graph node division of received frame radar echo data; 2, respectively extracting time domain amplitude and time frequency characteristics from echo time sequence data corresponding to each graph node; step 3, establishing a feature preprocessing sub-network; step 4, constructing a node feature fusion sub-network; 5, constructing a signal classification graph neural sub-network; 6, connecting the feature preprocessing sub-network, the node feature fusion sub-network and the signal classification graph neural sub-network in series to form a radar target detection neural network; and 7, inputting the test set into the trained radar target detection neural network, and outputting a dichotomy result of which the corresponding node is a target or clutter signal. Through the scheme, the target detection capability of the radar in the clutter environment can be improved.

The present invention belongs to the technical field of maritime target detection, and particularly relates to a two-dimensional constant false alarm target detection method and detector based on dual-observation-channel data. The method includes: obtaining the echo time series transmitted on each observation channel and received on each range cell; the observation channels include two observation channels of the cell to be detected and two observation channels of the reference cell; respectively performing square-law detection on the received echo time series to obtain detection statistics; calculating the estimated values of the clutter power levels of the two observation channels respectively based on the samples after square-law detection of the echo data of the reference cell; calculating the normalization factor according to the preset false alarm probability; and performing target detection according to the detection statistics, the estimated values of the clutter power levels, and the normalization factor, in combination with the two-dimensional constant false alarm adaptive decision criterion. It reduces the missed detection or misjudgment caused by the limitation of single-channel information, and improves the accuracy of judging the presence or absence of a target.

Embodiments of the present invention provide a method for measuring the time-of-flight of a low-signal-to-noise ratio ultrasonic echo signal, relating to the field of measurement technology. The method comprises the steps of acquiring an echo signal; performing noise reduction and reconstruction on the acquired echo signal using an empirical wavelet transform to obtain a reconstructed echo signal; obtaining a preset reference echo peak value and a reconstructed echo peak value, and calculating the echo characteristic peak of the echo signal using a preset characteristic peak location algorithm; obtaining echo characteristic points of the echo; and measuring the echo time-of-flight based on the obtained echo characteristic points according to a preset measurement algorithm. This method can achieve higher-precision time-of-flight measurements of ultrasonic echo signals using a simpler calculation method.

The invention belongs to the technical field of sonar echo processing, and discloses an underwater active sonar echo time-frequency tensor feature fusion method based on sub-beam filling. According to the method, firstly, a receiving array element is divided into a plurality of sub-beams, each sub-beam is independently subjected to beam forming, and the delay difference between the sub-beams is calculated to achieve time alignment. Then, short-time Fourier transform, continuous wavelet transform and smooth pseudo Wigner-Ville distribution analysis are respectively carried out on the echo signal of each sub-beam, and a corresponding time-frequency feature tensor is generated; thirdly, performing frequency domain weighting on the time-frequency characteristics by adopting a Gaussian distribution weighting function so as to highlight target frequency band characteristics; and finally, performing normalization processing on the weighted time-frequency features, and splicing feature tensors of different time-frequency transformations in a frequency dimension to form a fused feature tensor. The method effectively solves the problem of spatial information loss of a traditional method, and has a wide application prospect.

A polyacrylic acid (salt)-based super absorbent polymer has a T2 relaxation time of 1.85×10−5 seconds or less, as derived by exponential fitting of the TD-NMR measurement results of the super absorbent polymer through regression analysis using the following Equation 1:y=y⁢0+A×e-(xt)wherein, y represents a signal intensity obtained through TD-NMR analysis, x represents an echo time determined from specified experimental parameters: first duration; last duration; and a data point, t represents a T2 relaxation time derived by exponential fitting, A represents a signal intensity value derived by exponential fitting, and y0 represents an offset constant derived through regression analysis.

The present invention discloses a method for identifying the type of radar interference signal based on a convolutional neural network model, comprising: obtaining an echo time domain sequence and performing time-frequency conversion to obtain an echo frequency domain sequence; performing hierarchical quantization on the echo time domain sequence and the echo frequency domain sequence, respectively, and generating first and second real matrices based on the hierarchical quantization results; concatenating the first and second real matrices and converting them into grayscale images; inputting the grayscale images into a pre-trained convolutional neural network model so that the convolutional neural network model outputs a radar interference signal type identification result; wherein the convolutional neural network model is trained based on multiple sample grayscale images and the radar interference signal type corresponding to each sample grayscale image. Based on the convolutional neural network model, the present invention uses image classification and recognition methods to intelligently identify the type of radar interference signal, and has high generalization ability and recognition accuracy.

The invention provides a runner chamber wall thickness and void synchronous detection method, and relates to the technical field of hydro-power engineering nondestructive testing, S1, modular calibration: preparing a combined simulation block of a metal standard plate and an organic material plate, establishing a concrete water content inversion model and a void depth model segmented according to the thickness of a steel lining, and outputting calibration parameters; s2, field data acquisition: arranging measuring lines along a vertical welding seam and a longitudinal rib plate of the runner chamber, acquiring ultrasonic echo time and a thermal neutron counting rate, correcting the wall thickness in combination with the temperature of a steel lining, performing secondary verification on an abnormal measuring point, and outputting an original data set S = {}; and S3, machine learning signal processing: performing wavelet packet decomposition to extract energy ratio characteristics, and calculating thermal neutron counting rate fluctuation characteristics. Precise collaborative detection of the wall thickness and the void is realized through a link-by-link process of modular calibration, field data acquisition, machine learning signal processing, segmented collaborative modeling and Internet of Things data management.

The invention discloses a waveform feature extraction method and system for irregular waveforms of a hyperspectral laser radar, and aims at solving the problem that asymmetric waveforms, weak echoes and overlapped echoes in multi-channel full-waveform laser radar signals are difficult to accurately decompose, modeling full-waveform signals collected by multiple spectral channels into superposition of echo components and background noise. A multi-channel waveform is preprocessed through noise threshold and pulse width combined constraint, the waveform position is determined by adopting a gravity center discrimination method, and time synchronization calibration of each channel signal is realized in combination with a multi-echo quality index. The method further utilizes a cubic B-spline function to carry out modeling on transmitted waveforms of all spectrum channels, carries out weighted accumulation on multi-channel echo signals to enhance weak echo signals, and adopts a multi-channel interconnection decomposition optimization strategy to realize accurate extraction of irregular waveform features under the constraint condition of keeping time parameters of sub-echoes of all the channels consistent.

The invention provides a radar data processing method and device, electronic equipment and a vehicle, and the method comprises the steps: comparing the echo time corresponding to an echo signal of a reversing radar with the pre-obtained echo time of a license plate after the vehicle is powered on, and when the echo time corresponding to the echo signal of the reversing radar is smaller than or equal to the echo time of the license plate, starting the reversing radar; and discarding the echo signal of the reversing radar corresponding to the echo time. When the echo time corresponding to the echo signal of the reversing radar of the vehicle is smaller than or equal to the echo time of the license plate, the echo signal of the reversing radar corresponding to the echo time is discarded, so that the echo signal generated by the license plate can be effectively filtered, and the influence of the echo signal generated by the license plate on the detection result of the reversing radar is avoided; in addition, a radar data processing strategy does not need to be changed along with the change of the size of the license plate, and therefore the development cost is prevented from being increased, and a large amount of manpower and material resources are prevented from being consumed.

A magnetic resonance imaging device (100) according to the present invention comprises a sequence control unit (120), a first calculation unit (150d), a range selection unit (150h), a second calculation unit (150e), and a display control unit (150c). The sequence control unit (120) executes a pulse sequence and collects data from an imaging target. On the basis of the data, the first calculation unit (150d) calculates a first map indicating an amount corresponding to volume magnetic susceptibility. On the basis of an echo time (TE) value and a phase change value of the first map, the range selection unit (150h) determines a selection range for a phase slope value. On the basis of the first map and the selection range, the second calculation unit (150e) calculates a second map indicating a feature amount of a voxel value of the first map or a region of a part of the first map. The display control unit (150c) displays an image on a display unit on the basis of the second map.

The invention discloses a gynaecology and obstetrics intelligent visual midwifery system based on an ultrasonic technology, and relates to the technical field of ultrasonic midwifery, the system constructs a two-dimensional coordinate system and extracts ultrasonic echo total time and respiratory phase data, and fetal membrane structure data and fetal physiological data are generated through dimensionless processing and data analysis. And constructing an amniotic sac thickness gradient index dyn according to the thickness gradient change to evaluate the structural stability of the amniotic sac. And if the fetal respiratory phase drift index psh is evaluated to be unstable, calculating the fetal respiratory phase drift index psh, and jointly constructing a comprehensive parturition risk index Rco with the amniotic sac thickness gradient index dyn to reflect the potential parturition risk of coupling of the fetal stress level and the membrane structure variation. And the system generates different types of intervention instructions according to the evaluation result of the comprehensive parturition risk index Rco. Multi-dimensional data mapping and layer display are achieved, linkage display of a risk thermodynamic diagram and a breathing phase curve is supported, and a visual and traceable dynamic midwifery decision basis is provided for medical staff.

The present invention provides a method, system, electronic device, and medium for magnetic resonance imaging of the lungs. The method includes: applying a gradient magnetic field in a layer direction to a target to be imaged; when the gradient of the gradient magnetic field begins to climb, hard pulse excitation is performed on the target to be imaged, and the hard pulse is frequency modulated based on a preset frequency modulation range to generate a magnetic resonance signal; when the hard pulse excitation is stopped, spiral acquisition is performed on the magnetic resonance signal to obtain raw imaging data of the target to be imaged; based on preset reconstruction rules, the raw imaging data is reconstructed to obtain target imaging. The method, system, electronic device, and medium for magnetic resonance imaging of the lungs provided by the present invention can effectively shorten the echo time and imaging time, and have a high signal-to-noise ratio and high resolution.

Described are various embodiments of a system and method for minimizing a storage mode dephasing error caused by a reset of the auxiliary qubit. In one embodiment, the method comprises the steps of performing on the auxiliary qubit a first ηge pulse causing a |g↔|e transition in said auxiliary qubit, waiting for a designated echo time duration; and performing on the auxiliary qubit a second ηge pulse. The method may further comprise performing a f0g1 reset on the auxiliary qubit.

This invention discloses a phased array ultrasonic defect intelligent identification and data analysis system, relating to the field of PAUT (Polymerization and Angiography). It includes: an acquisition module for driving a phased array ultrasonic sensor array to perform weld seam scanning according to preset scanning rules, simultaneously acquiring and outputting ultrasonic echo time-series data across the entire depth range of the weld seam; and a preprocessing module for receiving the ultrasonic echo time-series data, performing data correction, noise filtering, and initial screening of effective signals, while simultaneously receiving feature anchoring parameters output by a mapping module, refining the signals in the corresponding regions, and outputting the results. This invention enables continuous, blind-zone-free scanning across the entire thickness and width range of the weld seam, simultaneously completing accurate echo signal correction and defect feature extraction, improving defect identification accuracy through closed-loop adaptive processing, accurately determining defect types and calculating their spatial location, size, and other core parameters, and simultaneously completing defect data statistical analysis and welding process correlation.