458 results about "Wave detection" patented technology

The invention relates to the technical field of power distribution network fault positioning, in particular to a power distribution network fault positioning method based on traveling wave detection, and the method comprises the following steps: S1, distributed detection network construction and signal collection: collecting a three-phase current traveling wave signal in real time; s2, time-frequency joint analysis and feature extraction: extracting time-frequency energy distribution features; s3, intelligent screening of effective fault wave heads: screening out the effective fault wave heads; s4, initial arrival time parameter determination: determining the initial arrival time of each detection point; s5, according to topology self-adaptive error correction, transmission path wave velocity deviation is corrected through line parameter dynamic compensation, and clock errors of the asynchronous detection device are eliminated through adjacent node clock difference estimation; and S6, multi-source data fusion and fault positioning: resolving space coordinates of fault points. According to the invention, the method improves the recognition accuracy of fault features, and solves the problems of poor anti-interference capability and high misjudgment rate of a single feature in a conventional method.

The invention provides a distribution line fault location optimization method based on single-ended traveling wave location, and relates to the technical field of traveling wave detection. The method comprises the following steps: carrying out segmented modeling on a line, calculating the traveling wave propagation speed and wave impedance of each segment, and correcting the traveling wave propagation speed and wave impedance; collecting a voltage / current traveling wave signal of a detection point, and extracting a line mode component; performing wavelet transformation on the line mode component, detecting the wave head position of the initial traveling wave through a modulus maximum search algorithm, and recording the arrival time of the initial traveling wave, a corresponding first energy value and polarity; calculating a reflected wave time window based on segmented modeling parameters, screening reversed polarity waves with qualified energy attenuation, and calculating a fault distance; if no effective reflected wave is detected in the reflected wave time window, triggering a pseudo double-end mode; a result is verified through quadruple constraints; the problems of poor parameter adaptability, low signal processing precision, strong reflected wave dependence and incomplete verification in traveling wave distance measurement of a complex distribution line are solved, and the accuracy and reliability of fault distance measurement are improved.

The invention discloses a distribution network cable fault early warning method and system based on multi-terminal synchronous traveling wave detection, and relates to the technical field of cable fault detection. The method comprises the following steps: deploying at least three synchronous detection ends at each branch end point of a cable, and synchronously triggering a sampling rate; establishing a master-slave synchronous network, and performing frequency spectrum correction on the acquired data; constructing a real-time correction model based on the data of the distributed temperature sensor; extracting early fault features, and constructing a three-dimensional feature tensor; carrying out preliminary diagnosis on edge nodes and carrying out feature classification by adopting a transfer learning optimization network; and in combination with the cable load rate and the environment temperature and humidity, an early warning threshold self-adaptive model based on fuzzy PID (Proportion Integration Differentiation) is established. Through multi-terminal cooperative perception and intelligent analysis, the scheme converts a fault processing mode from passive first-aid repair to active defense, improves the manual inspection efficiency of the distribution network cable, and finds early fault hidden dangers in advance.

The invention discloses a multi-wave detection and imaging system for fish schools, which relates to the field of detection and imaging of fish schools and comprises a metamaterial acoustic emission module, a self-adaptive signal receiving module, a three-dimensional point cloud generation module, an image enhancement and generation module and an intelligent decision control module. According to the multi-wave detection and imaging system for the fish school, clustering parameters can be dynamically adjusted based on the real-time fish school density, the neighborhood radius is automatically expanded in a high-density area to avoid segmentation errors, and the core point judgment threshold is reduced in a low-density area to reduce missing detection; an acoustic attenuation model is constructed in combination with water body environment parameters, emission parameters are calibrated in real time, images can be enhanced, space and time dimension features are fused, the image resolution and definition are improved, accurate recognition of multiple fish species is achieved, the fish species can be better distinguished, meanwhile, a generative network is adopted to directly convert acoustic data into visual images, and the recognition accuracy is improved. Therefore, the generated image can reflect the actual distribution condition of the fish school more truly and accurately.

The invention discloses a fixed area unmanned aerial vehicle countering method and system. The method comprises the steps of obtaining a three-dimensional coordinate of a to-be-identified unmanned aerial vehicle; inputting the obtained spectrum data of the to-be-identified unmanned aerial vehicle into an invasive unmanned aerial vehicle detection model constructed by a deep learning algorithm to generate an invasive unmanned aerial vehicle signal; in response to the invading unmanned aerial vehicle signal, acquiring multispectral imaging data of the invading unmanned aerial vehicle based on the visual image acquisition base station; performing feature-level fusion on the radar wave detection data, the spectrum data and the multispectral imaging data based on a multi-modal fusion algorithm of space-time registration to obtain fusion feature data of the target area; performing feature extraction of different dimensions on the fused feature data, and establishing a threat situation three-dimensional thermodynamic diagram of the invading unmanned aerial vehicle based on the extracted features; and executing a security countering strategy generated based on the threat situation three-dimensional thermodynamic diagram. According to the method, the unmanned aerial vehicle countering requirement in a complex environment is met.

The invention relates to the technical field of power system fault positioning, in particular to a power distribution network fault accurate positioning method, device and system based on the traveling wave principle, and the method comprises the steps: deploying traveling wave detection equipment at two ends of a certain section of line of a power distribution network, and enabling the traveling wave detection equipment to be used for synchronously collecting potential fault traveling wave signals; analyzing based on the acquired potential fault traveling wave signal, and screening out a fault traveling wave; in the time union set of the local time windows at the two ends, marking the fault traveling wave with the maximum peak value in the single end as a direct wave, analyzing the waveform similarity between the direct wave and the fault traveling wave arriving after the direct wave, and screening out a reflected wave according to the peak value difference; and based on the arrival time of the direct waves and the reflected waves at the two ends, calculating the distance from the fault point to the two ends of the line through a positioning formula to position the fault point. The invention aims to improve the positioning precision of the fault point in the power distribution network by analyzing the distribution characteristics of the pseudo traveling wave signal.

The invention relates to the field of power distribution network ground fault accurate judgment, and discloses a power distribution network ground fault accurate positioning method based on traveling wave detection and artificial intelligence, which comprises the following steps: (a) collecting a power distribution network traveling wave voltage signal through a multi-node synchronous sensor array, and generating a preprocessing signal through baseline correction and wavelet threshold denoising; (b) constructing a Gaussian random field model of line resistance, inductance and capacitance, and simulating a traveling wave propagation process in combination with a nonlinear wave equation; and (c) defining Finsler measurement on the traveling wave signal manifold, and separating the aliasing mode by minimizing path integration. According to the invention, the technical scheme of multi-node synchronous signal acquisition and self-adaptive preprocessing is adopted, so that the effect of eliminating coupling of power frequency interference and high-frequency noise is achieved. Compared with a scheme depending on a single sensor and a fixed filtering threshold in the prior art, the method solves the defect that the wave head time difference extraction is not accurate due to asynchronous sampling.

The invention discloses an EEG signal spine wave detection method and system based on KAN feature fusion, and the method comprises the steps: carrying out the preprocessing of electroencephalogram data, and obtaining a training set and a test set; performing parallel feature extraction to obtain multi-KAN parallel features, and performing splicing and dimension reduction to obtain mixed features; performing gating dynamic selection on the obtained mixed features to obtain fusion features of comprehensive multi-scale analysis of the EEG signals; focusing the key period features based on a double attention mechanism to obtain weight fusion features; inputting the obtained weight fusion features into a classifier, and training a prediction model based on a cross entropy loss function; evaluating the performance of the model, and outputting a classification result. The epileptic seizure risk prediction is realized by extracting the electroencephalogram heterogeneous features, and inputting the electroencephalogram heterogeneous features into the classifier after gating dynamic fusion and double attention time sequence compression. The feature expression capability is obviously improved, the focusing capability in a key period is enhanced, and the classification performance is optimized.

The invention relates to the technical field of semiconductors, in particular to an ultrasonic transmitting circuit, a chip and an ultrasonic module. The ultrasonic transmitting circuit comprises a first control circuit and a signal generating circuit. The first control circuit is used for outputting a first control signal; the signal generation circuit is used for outputting a driving signal according to the first control signal; the driving signal is used for driving a first booster circuit to output an excitation signal, and the voltage of the excitation signal is higher than that of the driving signal; the excitation signal is used for exciting the ultrasonic transducer to emit ultrasonic waves. According to the embodiment of the invention, the energy of ultrasonic waves emitted by the ultrasonic transducer can be improved, so that the ultrasonic receiving circuit can receive echoes with higher energy, and the sensitivity and the signal-to-noise ratio of ultrasonic detection are improved.

The invention relates to the technical field of power transmission line safety monitoring, and particularly discloses a self-adaptive calibration method for an ultrasonic wind speed sensor, which comprises the following steps of: arranging an orthogonal ultrasonic probe array at the top of a tower, and compensating probe offset caused by swinging of a tower body in real time through GNSS / IMU (Global Navigation Satellite System / Inertial Measurement Unit) fusion positioning; integrating a temperature, humidity and pressure sensor and vibration spectrum analysis to construct an environmental parameter compensation model; double-frequency ultrasonic waves are adopted to detect the ice accumulation thickness of the protective cover and correct the sound path distance; deploying a lightweight LSTM model at an edge computing unit to realize minute-level dynamic parameter adjustment; electromagnetic interference is suppressed by combining linear frequency modulation spread spectrum and beam forming technologies; and establishing a three-height-layer wind speed gradient model to generate a galloping early warning. The problem of measurement distortion caused by tower deformation, icing and parameter solidification of a traditional sensor is solved, all-working-condition operation from-40 DEG C to 60 DEG C is supported, and the monitoring reliability in a strong electromagnetic environment is remarkably improved.

The invention relates to the technical field of road engineering detection, in particular to a road disease recognition method and system based on electromagnetic waves and photographic imaging, and the method comprises the steps: firstly obtaining electromagnetic wave detection data and photographic imaging data of a road region, then synchronously detecting the distribution position and thickness of a road thin water film, generating a rasterized water film feature map, and finally obtaining a road disease recognition result. Then, according to the water film characteristic pattern, dynamically correcting bimodal data interference, adjusting a reflected wave amplitude value and a time domain delay parameter for electromagnetic wave detection data, compensating a gray difference and an edge gradient value for photographic imaging data by applying a local reflection suppression algorithm, and finally, fusing the corrected data and associating the state of the water film characteristic pattern to eliminate coupling misjudgment. The system comprises a data acquisition unit, a water film detection unit, a double-domain correction unit and a fusion decision unit, the problem of insufficient identification precision caused by a thin water film is solved, the road disease identification precision is improved, and a reliable basis is provided for road maintenance.

The invention discloses a radar-wave-transparent light-emitting vehicle logo lamp, and relates to the field of vehicle lamps. The radar-wave-transparent light-emitting vehicle logo lamp comprises a base, an outer face cover connected to the top of the base, a circuit board fixed between the base and the outer face cover, a light guide plate fixed between the circuit board and the outer face cover and a heating film connected to the surface of the side, away from the base, of the outer face cover. The middle of the base protrudes upwards to form a radar wave-transparent area and a containing groove located in the bottom face of the radar wave-transparent area, and the containing groove is used for containing a millimeter wave radar sensor for emitting radar. The circuit board is provided with a first opening for a radar wave-transparent area to pass through and a plurality of LED lamps arranged at intervals in the circumferential direction. The top face and the bottom face of the light guide plate are attached to the outer face cover and the radar wave-transparent area respectively, and the surface of the side, away from the base, of the light guide plate is provided with a vehicle logo. According to the light-emitting vehicle logo lamp capable of transmitting the radar waves, the radar waves can pass through the light-emitting vehicle logo lamp for detection while the vehicle logo identification is lightened, the influence on radar wave detection is reduced to the maximum extent, and meanwhile the radar wave detection effect can be prevented from being influenced by ice and snow.

The invention discloses a signal countering intelligent monitoring system of an unmanned aerial vehicle, which relates to the technical field of signal countering and comprises a multi-source acquisition module, a dynamic verification module, a decision analysis module, an intelligent communication module, an integrated radar unit, a spectrum analysis unit, an infrared sensing unit and a sound wave detection unit. Multi-source data fusion is realized through the data association evaluation value, the signal countering effect of the unmanned aerial vehicle is improved through the threat evaluation value R, the hierarchical threat response and the precise matching countering strategy, and when the radar signal intensity normalization value S1 conflicts with the infrared feature matching degree S3, the verification value is calculated according to the voiceprint matching degree S4 and the spectrum matching degree S2, so that the reliability of the unmanned aerial vehicle is improved. Or a standby unmanned aerial vehicle signal recognition system is started for synchronous detection, multi-source data contradiction is solved, the misjudgment rate is reduced, satellite, 5G and Mesh network dynamic switching is achieved, the communication performance of the system is guaranteed through a priority strategy, and the data transmission delay rate is reduced.

The invention provides a logarithmic bus bearing roller defect detection method and system based on an ultrasonic technology, and the method comprises the steps: obtaining an ultrasonic detection signal of the surface of a logarithmic bus bearing roller, and carrying out the preprocessing of the ultrasonic detection signal, and obtaining a first echo signal sequence; obtaining an average value sequence, a skewness sequence, a kurtosis sequence and a first high-order cumulant sequence based on the first echo signal sequence; correcting the first high-order cumulant sequence based on the average value sequence to obtain a second high-order cumulant sequence; optimizing the first echo signal sequence based on the dictionary matrix and the signal sparse coefficient vector to obtain a second echo signal sequence; and fusing the sequences to obtain a multi-dimensional feature vector sequence, and comparing the multi-dimensional feature vector sequence with a preset vector threshold to detect whether the logarithmic bus bearing roller has defects or not. According to the method, the problem of beam distortion of traditional ultrasonic waves during detection of the roller defects of the logarithmic bus bearing is solved, and the detection precision is remarkably improved.

The invention discloses a wind wave and surge extraction method and system based on a GNSS and an anemometer. The method comprises the following steps: respectively obtaining water level height data and wind data detected by a buoy for multiple times according to a reference time sequence and a detection time sequence; the buoy water level height data and the wind data are subjected to data preprocessing, the water level height and the wind data are preprocessed, and the preprocessed water level height and the preprocessed wind data are obtained; calculating the water level height and the wind data in unit time by using the preprocessed water level height and the wind data according to a segmented interpolation function, and calculating wave height data under a corresponding detection time sequence according to the water level height and the wind data in the unit time; feature set classification is carried out according to wind speed grades, IFFT is carried out after screening, and final wind wave and surge data are obtained, the water surface wind wave and surge data extraction precision is effectively improved, and low-cost and long-time-efficiency water surface wind wave and surge detection can be achieved.

The invention relates to a long-gap discharge leader development speed measurement method based on radiated electromagnetic wave detection. The method comprises a set of high-frequency antennas and a high-speed oscilloscope and a long-gap discharge leader development speed calculating method. The method adopts a certain antenna arrangement form; long-gap discharge radiated electromagnetic wave pulse time is detected simultaneously through the plurality of antennas; leader head position is positioned according to time difference of a signal arriving at different antennas; and furthermore, the long-gap discharge leader development speed can be calculated. The method can effectively improve the measurement precision of the discharge leader development speed, and resolution reaches the level of 0.1 ns.

The invention relates to a power distribution network fault detection method and system based on distributed traveling wave detection, and relates to the technical field of power distribution network fault detection, and the method comprises the steps: employing a traveling wave detection device which is configured in a power distribution network in a distributed manner for detection, and obtaining a traveling wave parameter and a traveling wave distance; according to the traveling wave distance, a fault position interval is positioned, and a transmission line section is indexed; recovering the traveling wave parameters according to the line maintenance data of the transmission line section, obtaining recovered traveling wave parameters, and obtaining traveling wave consistency parameters through consistency analysis; and based on the traveling wave consistency parameter, positioning in the fault position interval to obtain a fusion fault position, and performing fusion processing to obtain a fusion traveling wave parameter as a fault detection result. According to the method, the problems of large single-point detection error, traveling wave parameter distortion caused by line loss and insufficient multi-source data fusion precision in traditional power distribution network fault detection are solved, the fault positioning precision and the detection reliability are improved, and an efficient solution is provided for power distribution network line fault detection and anomaly positioning.

The invention discloses an automatic grading device for thermal shock cracks of a coating and an application method. Comprising a terahertz wave detection module, a laser ultrasonic excitation and detection module, a high-precision three-dimensional motion control platform, a multi-mode signal synchronous acquisition and processing unit, a crack intelligent grading evaluation unit, an environment simulation and temperature control unit, a protective shell and a human-computer interaction interface. The near-surface dielectric property change of the coating is represented through the terahertz technology, the deep mechanical property evolution is detected through the laser ultrasonic technology, the thermal shock service condition is reproduced in combination with a high-temperature environment simulation unit, and a multi-modal feature fusion algorithm and a physical model and machine learning collaborative inversion model are adopted to obtain the thermal shock resistance of the coating. And automatic quantitative evaluation and severity grading of the depth, density, length and network connectivity of the thermal shock cracks of the thermal barrier coating are realized. The problems that an existing single detection method is insensitive to vertical cracks, poor in high-temperature environment adaptability and low in manual evaluation efficiency are solved.

The invention discloses a breathing and electrocardio information integrated recording and displaying method and system based on overall spatial-temporal characteristics. The method comprises the steps that a high-precision sensor synchronously collects electrocardiogram, phonocardiogram, arterial pulse waveform, venous pulse waveform and breathing wave signals and preprocesses the signals based on different signal characteristics; carrying out multi-cycle electrocardiogram merging by utilizing an R-wave detection algorithm and introducing a variational mode decomposition algorithm; carrying out feature extraction from the multi-mode signal, and carrying out respiratory wave and electrocardiowave conjoint analysis; carrying out feature fusion through a spatial-temporal feature fusion network of a multi-branch attention mechanism, and generating and displaying a combined electrocardiograph distribution diagram; carrying out anomaly detection through an anomaly detection model based on a Transform architecture; synchronously displaying in an integrated display interface; according to the system and the method, efficient acquisition, analysis and visualization of the multi-modal physiological signals are realized by integrating synchronous acquisition, intelligent interpretation and integrated display of various physiological signals, and the efficiency and the accuracy of clinical diagnosis are favorably improved.

The invention discloses an underground cable fault acquisition system and a use method thereof, and particularly relates to the technical field of cable fault detection, and the underground cable fault acquisition system comprises a multi-frequency pulse signal transmitting module, a reflected wave detection array module, a time-frequency joint analysis module, a three-dimensional positioning engine module, an augmented reality terminal and a fault identification module. The multi-frequency pulse signal transmitting module generates a specific excitation signal and injects the signal into a cable. The reflected wave detection array module collects a reflected signal. The time-frequency combined analysis module processes the signal to obtain a characteristic. The three-dimensional positioning engine module calculates a fault point coordinate. The augmented reality terminal maps the fault point coordinate and generates a maintenance path. And the fault identification module judges the fault category. Through cooperative work of multiple modules, accurate positioning, comprehensive analysis and efficient maintenance planning of underground cable faults are achieved, and the system has the advantages of being high in positioning accuracy, accurate in fault diagnosis and high in maintenance efficiency.

The invention discloses a distribution line fault identification and positioning method based on wavelet transform and traveling wave distance measurement technology, and the method comprises the steps: building a three-dimensional digital twin distribution network model, deploying a traveling wave detection device on a distribution line, collecting a traveling wave signal in real time when a fault occurs, and carrying out the fault identification and positioning of the distribution line; the method comprises the following steps: carrying out multi-scale decomposition on an acquired traveling wave signal by using a wavelet transform technology, extracting time-frequency characteristics of fault traveling wave data, and when a line fails, realizing high-precision positioning under a complex branch network by adopting a double-end-B type traveling wave distance measurement algorithm and combining Beidou / GPS time service synchronization and topological parameters; a lightweight convolutional neural network is adopted to construct a fault classification model, and a fault type is quickly identified; and generating a fault positioning report containing three-dimensional coordinates, fault features and historical processing schemes, and marking the specific position of a dynamic fault point on a visual interface. According to the method, the fault positioning precision and the anti-interference capability of the complex power distribution network are remarkably improved, and fault identification-positioning-decision intelligent closed loop is realized.

The invention relates to the technical field of industrial detection, in particular to an electromagnetic ultrasonic double-wave transducer for detecting residual stress of a pipeline. The problems that in the prior art, single-wave detection errors are large, the fitting degree of a sensor and a pipeline curved surface is poor, and impact force affects an internal structure are solved. The invention provides an electromagnetic ultrasonic double-wave transducer. The electromagnetic ultrasonic double-wave transducer comprises a shell, a magnet assembly, a coil and other components. The magnet assembly is composed of a transversely-arranged first magnet, a longitudinally-symmetrical second magnet and a longitudinally-symmetrical third magnet, the included angle between the magnets is adjusted through a hinge, and vertical and horizontal magnetic fields are formed to excite transverse waves and longitudinal waves at the same time. The lower portion of the shell is arc-shaped and attached to the curved surface of the pipeline, and an elastic supporting structure and a flexible buffering layer are arranged at the joint to buffer impact force. In addition, a grounding lead is arranged to improve the signal-to-noise ratio. Through multi-magnet combination, the arc-shaped shell and the grounding wire buffer design, the magnetic field uniformity and the detection signal strength are effectively improved, and transverse and longitudinal wave integrated high-precision residual stress detection is realized.

The invention discloses a shield segment support crack disease impact elastic wave detection method and device based on KNN-BiLSTM. The detection method specifically utilizes impact elastic wave equipment to test a shield segment support, collects the frequency, wave velocity, amplitude, frequency and curve change characteristics of Rayleigh waves propagated from the surface of a structure, and uses a network structure based on KNN-BidirectionalLSTM to carry out data processing on a multi-element elastic wave characteristic and lining disease characteristic mapping model. And obtaining the shield segment support crack depth and water permeability detection result at the detection position. According to the method, the accuracy of crack depth detection is remarkably improved, the over-fitting phenomenon is effectively relieved, the recognition accuracy and speed of the model are improved, meanwhile, the crack depth prediction result can be obtained, the crack water permeability type can be detected, and the method has important practical value and popularization significance.

The invention belongs to the technical field of physiological electric signal detection, and particularly relates to a ratchet wave detection system and epilepsy detection equipment. According to the ratchet wave detection system, the ratchet wave detection unit is used for detecting signal data to obtain the ratchet wave detection result, then the ratchet wave screening unit is used for screening the ratchet wave from the ratchet wave detection result, the waveform of the ratchet wave is displayed in the waveform display area, and finally the preset value of the sensitivity is adjusted to change the displayed waveform of the ratchet wave. The detection error caused by the difference of the ratchet wave forms can be better processed, the ratchet wave forms are combined with the screening threshold value, the universality requirement is met, and the whole system has high adaptability.

The invention belongs to the technical field of magnetic variable measurement, and particularly relates to a power driving compensation method and system for magnetostrictive load characteristic monitoring, and the method comprises the steps: obtaining a reference zero point of magnetic performance evolution in a cold state environment of an electromagnetic system according to the center frequency of the electromagnetic system; calculating a current main frequency impedance module value and a phase difference through an electrical parameter characterization method, and obtaining a thermal drift index reflecting a hysteresis loop distortion degree in combination with a reference zero point; obtaining correction factors of all orders based on the thermal drift index and the average output power at the current moment, and dynamically updating a coefficient vector of the inverse model; and constructing a pre-distortion driving voltage signal capable of counteracting nonlinear interference by using the new coefficient and the ideal guided wave voltage sequence, and inputting the pre-distortion driving voltage signal to a power amplifier to drive the magnetostrictive transducer. According to the invention, the problem of predistortion failure under a variable-temperature working condition in the prior art is solved, and the signal-to-noise ratio of high-power long-distance guided wave detection is remarkably improved.

In an electron tube, the meta-surface emits an electron in response to an incidence of the electromagnetic wave. The first and second electrodes are spaced away from each other, and apply potentials different from each other to the meta-surface. A holder is disposed in the housing and holds the electron emitter. A first conductive line of the meta-surface is electrically connected to the first electrode. A second conductive line of the meta-surface is spaced away from the first conductive line, and is electrically connected to the second electrode. The first conductive line extends from the first electrode to the second conductive line. The second conductive line extends from the second electrode to the first conductive line.

The invention discloses a new energy station line fault detection method based on traveling wave distance measurement, and belongs to the technical field of new energy power line detection, and the method comprises the following steps: obtaining the power performance parameters of each line segment after receiving a line detection signal, carrying out the analysis to obtain the power efficiency index of each line segment, and carrying out the analysis to obtain a fault line segment; traveling wave waveform effect parameters of the fault line section are obtained, traveling wave effect quality indexes are obtained through analysis, and therefore whether traveling wave equipment preset parameter adjustment is carried out or not is judged; and carrying out parameter adjustment on the preset parameters of the traveling wave equipment based on the traveling wave effect quality index, obtaining the adjusted waveform quality parameters, carrying out analysis to obtain the waveform quality index, and carrying out analysis to obtain the line fault position, thereby achieving accurate positioning of the fault point position when the new energy station line has the high-resistance fault. The problem that in the prior art, due to the fact that the wave velocity is not stable, positioning is not accurate when high-resistance fault position positioning is conducted through traveling wave detection is solved.

The embodiment of the invention provides a sea surface wind wave detection method and system based on Beidou reflected signals. The method is applied to the technical field of sea surface wind wave detection, and comprises the following steps: acquiring and processing Beidou direct reflection signals through a double-antenna system to obtain feature and orbit data; calculating reflection point positions and tide correction according to the characteristic orbit data to obtain reflection area characteristics; evaluating sea surface roughness based on the regional features and identifying interference to obtain scattering features; modeling and inverting wind wave parameters according to the scattering characteristics to obtain original data; fusing and screening multi-source observation according to the original data to obtain quality control data; and evaluating and optimizing system parameters by using the quality control data to obtain a storm detection result. According to the invention, interference sources such as land reefs and the like can be effectively identified and processed, and Beidou reflected signal sea surface wind wave detection based on high-precision wind wave parameter inversion is realized.

The invention discloses an ultrasonic double-wave detection and monitoring method and an ultrasonic double-wave transducer, and the ultrasonic double-wave transducer comprises a piezoelectric element which is used for exciting a longitudinal wave signal and a transverse wave signal at the same time under the excitation of a single electric pulse; the backing layer is positioned on the back surface of the piezoelectric element and is used for absorbing longitudinal wave energy radiated to the back surface by the piezoelectric element; the matching layer is arranged between the piezoelectric element and the tested workpiece and is used for acoustic impedance matching; the electrical connection device is used for connecting an external excitation generator and receiving equipment; and the metal shell is used for packaging the piezoelectric element, the backing layer, the matching layer and the electrical connection device and is provided with a structure for applying pre-tightening force. According to the invention, dual-mode excitation is realized through a single piezoelectric plate structure, and the efficiency, precision and reliability of dual-wave ultrasonic detection are improved.

The invention discloses a construction method of an anchoring anchor rod crack defect guided wave detection numerical model, and belongs to the field of anchor rod nondestructive detection.According to the constructed numerical model, finite element-infinite element coupling is adopted for optimizing the surrounding rock stratum boundary, the problem of boundary multi-reflection echoes caused by artificial boundary truncation is solved, and the detection accuracy is improved. The workload of overall grid division is reduced; the method improves the calculation efficiency while guaranteeing the propagation precision, and effectively simulates the guided wave propagation behavior in the infinite boundary of the surrounding rock stratum. The numerical model constructed by the method is used for detecting the crack of the anchor rod under different defect degrees, so that the defect echo amplitude is in an ascending trend along with the increase of the defect degrees, and the bottom echo amplitude is in a descending trend along with the increase of the defect degrees. The numerical model constructed by the method positions the defect position of the anchor rod crack under different defect degrees, the result shows that the change of the defect degree basically does not influence the positioning of the defect position, the defect position can be accurately positioned through the one-way defect echo and the bottom echo, and the error range is less than or equal to 3%.