326 results about "Waveform distortion" patented technology

The invention provides a multi-target tracking and interference cooperation method and system based on a millimeter wave radar. The method comprises the following steps: firstly, acquiring an original detection signal in real time by using a millimeter-wave radar carried by an unmanned aerial vehicle, establishing a track correlation sequence of each moving target, extracting interference waveform characteristics formed by signal coupling among a plurality of moving targets in the original detection signal, and then, according to a spatial distribution parameter of the interference waveform characteristics, determining a track correlation sequence of each moving target; correcting the space-time continuity judgment rule of the trajectory correlation sequence, and finally outputting an anti-interference cooperative tracking result based on the corrected space-time continuity judgment rule. According to the technical scheme provided by the invention, the industry pain point that waveform distortion interference of the millimeter wave radar in a dense target scene cannot be eradicated is solved, and the error correlation rate in a dense formation scene is also reduced.

The invention discloses a power transmission channel risk early warning evaluation method and system, and relates to the technical field of power transmission channel abnormal condition early warning, and the method comprises the steps: analyzing the current waveform distortion degree caused by a nonlinear load in a power transmission line through monitoring the voltage harmonic distortion rate, and evaluating the influence of harmonic waves on the insulation aging and heating loss of the line and equipment; the real-time gradient of the temperature of the wire is analyzed, abnormal heating conditions of different sections of the wire are judged, and the abnormal rising degree of the temperature of the wire and potential thermal damage accumulation caused by overload and poor contact factors are evaluated; by monitoring and analyzing multi-dimensional indexes such as the voltage harmonic distortion rate, the lead temperature real-time gradient, the sag dynamic deviation rate and the corona discharge intensity, the defect of a traditional monitoring means in the aspect of abnormal heating risk assessment is overcome.

The invention relates to the technical field of electric power monitoring analysis, and discloses an intelligent analysis system for electric power monitoring data based on a mutual inductor. The system comprises a mutual inductor data acquisition and structuring module which acquires a current waveform, a voltage waveform and a harmonic component in real time, and generates a standardized monitoring data unit through preprocessing, field mapping and association identification establishment; the theoretical monitoring value calculation module constructs a dynamic calculation model according to historical power data, and an input standard data unit outputs a theoretical value; the rule conformity verification module is used for matching the equipment type with the operation rule and generating single compliance judgment; a multi-dimensional difference analysis module compares a theoretical value with a measured value from time domain deviation, frequency domain deviation and waveform distortion, and generates an equipment-level difference coefficient matrix; the association network construction module is used for constructing a multi-monitoring-point association map according to the equipment identifier and the position information; and the anomaly positioning and strategy generation module combines the map, compliance judgment and a difference matrix, calculates a risk score, generates an anomaly probability distribution map, positions anomaly and matches a monitoring strategy.

The invention belongs to the technical field of semiconductor testing, and discloses a novel automatic detection system and method for the electrostatic protection performance of a power device. A distributed parasitic parameter network model is constructed by acquiring packaging structure parameters of a to-be-tested power device and physical layout data of a test fixture, key parasitic parameter distribution is identified in combination with a time domain reflection measurement technology, a waveform distortion coefficient is calculated, and a spatio-temporal evolution model of electrostatic pulse propagation is constructed. Based on the model, a compensatory predistortion waveform is generated to counteract the parasitic effect of a transmission path, a device port response signal is collected in real time, an energy dissipation characteristic spectrum is extracted through wavelet packet decomposition, and quantitative evaluation of the electrostatic protection performance is achieved. According to the invention, the test precision and repeatability are improved, and the method is suitable for electrostatic protection tests of various novel power devices, especially high-frequency wide-band gap devices.

The invention discloses a modular reclosing circuit breaker protection system based on intelligent electrical cloud coordination, particularly relates to the technical field of intelligent power distribution network relay protection, and is used for solving the problems that fault diagnosis is delayed and a protection strategy cannot be generated in a fault clearing time window due to resource competition in a cloud coordination protection system. A dynamic preemption priority is generated based on power grid topology vulnerability and associated circuit breaker collaborative requirements by monitoring the load state of cloud computing node resources in real time; credibility attenuation control is carried out in combination with a fault current waveform distortion rate; when the resource preemption necessity exceeds a threshold value, freezing a periodic task thread and releasing computing resources, and opening up a high-priority communication channel at the same time; sending a fault recording compression instruction to a target circuit breaker terminal to obtain an edge preprocessing feature vector; and protection strategy optimization is executed in the released resources to generate reclosing parameters, and the reclosing parameters are issued and executed through a high-priority channel, so that quick response of a fault diagnosis task is realized.

The invention relates to a weak current cable fault positioning method and system, and the method comprises the steps: preliminarily locking a fault region through monitoring the axial stress change in real time, injecting a low-frequency pulse signal in a target section, analyzing the reflection waveform characteristics, and extracting the waveform distortion characteristics in a reflection signal; dynamically adjusting the output impedance based on the amplitude attenuation and time delay relationship, and if the dynamically adjusted output impedance cannot enable the output impedance of the injected low-frequency pulse signal to be synchronous with the impedance change trend of the cable, marking as an impedance mismatch point; after an impedance mismatch point is identified, other interferences are eliminated through multi-band signal attenuation difference analysis, and the position of a fault point is determined; the system is used for implementing the method. According to the method and system, stress monitoring and electric signal detection are combined, the detection range is remarkably shortened, the positioning precision and the detection accuracy are improved, and the method and system are suitable for weak current cable fault diagnosis in a complex environment.

The invention relates to the technical field of power distribution networks, and discloses a power distribution network fault self-recovery method and system based on machine learning, and the method comprises the steps: collecting the multi-source fault feature data of a power distribution network in real time, including the voltage and current waveform distortion feature, the load sudden change feature and the equipment temperature anomaly feature; and inputting the multi-source fault feature data into a multi-stage classification model for processing, and by setting a pseudo fault filtering module, establishing a typical interference feature library and setting dynamic filtering thresholds for different working conditions during real-time fault detection of the power distribution network, so that the recognition accuracy of various interference signals is ensured, and the fault detection accuracy of the power distribution network is improved. Meanwhile, similarity comparison is carried out on real-time collected data and pseudo fault features, whether the problems of signal distortion and noise pollution occur at the fault positioning position of the power distribution network or not can be detected in real time, the accuracy of fault type recognition is ensured, the misjudgment risk is reduced, and when strategy adaptation is abnormal, the matching degree of the self-healing strategy and the actual state of the power grid is ensured.

The invention provides an abnormal blood sampling inspection data evaluation processing method and system of a blood sampling system. Wherein the diffusion track dynamic state of an anticoagulant-blood contact surface in a blood sampling tube is tracked in real time, dielectric response waveform distortion characteristics on the two sides are synchronously collected through a capacitance sensor array, and diffusion form parameters are generated; curvature sudden change is analyzed to trigger an acoustic fluid device to modulate audio frequency and flow velocity, and a composite disturbance field is formed; performing capacitance axial scanning on the disturbed mixed fluid, extracting phase angle offset and gradient abrupt change point coordinates, and constructing a dielectric anomaly three-dimensional map; matching a standard dielectric model, positioning a coordinate set of a concentration gradient imbalance area and a coordinate set of an eddy current attenuation area, and generating an anticoagulant abnormal index and a mixed defect matrix in combination with phase angle offset difference; and establishing a data anomaly degree evaluation function based on the anomaly index and the defect matrix, dynamically associating a clinical error threshold, and outputting a test evaluation result. According to the invention, anticoagulant diffusion can be monitored in real time, and the mixing quality error can be accurately evaluated.

The invention relates to the technical field of intelligent decision making, can be applied to business system platforms of financial science and technology, medical health and the like, and discloses an equipment adaptive control method and device, equipment and a medium, and the method comprises the following steps: obtaining a multi-modal signal of an equipment detection target, and constructing a dynamic reference system according to the multi-modal signal; performing space-time alignment optimization on the multi-modal signal according to the dynamic reference system to obtain a space-time alignment signal, and performing dynamic calibration on the space-time alignment signal to obtain a calibration signal; performing transient waveform distortion feature extraction on the calibration signal to obtain a signal distortion feature; performing feature space mapping on the signal distortion features to obtain a feature mapping result; and generating an equipment early warning grade parameter according to the feature mapping result and a preset safety boundary distance, and dynamically adjusting a preset equipment control parameter according to the equipment early warning grade parameter. By analyzing the multi-mode signal, the dynamic adjustment of the equipment control parameters is realized, and the equipment detection precision is improved.

The invention relates to a multi-modal fusion pipeline damage positioning method, which comprises the following steps of: uniformly arranging piezoelectric transducer arrays along the circumferential direction of a pipeline, generating non-frequency dispersion L (0, 2) and T (0, 1) guided waves respectively excited by 70kHz sine pulses as excitation signals, and unidirectionally spreading the excitation signals along the pipeline; the method comprises the following steps: acquiring reflection echoes at a to-be-measured section of a pipeline, and performing matched filtering, omega-k domain filtering and circumferential modal decomposition on the reflection echoes to obtain two modal components in an L (0, 2) mode and a T (0, 1) mode; performing back propagation and focusing imaging on each modal component to obtain imaging results under two modals L (0, 2) and T (0, 1); and fusing the imaging results in the two modals to obtain a multi-modal fusion pipeline damage image. Compared with the prior art, the method has the advantages that the problem that sensitivity of different defect types is difficult to consider due to single-mode optimization and the problems of signal waveform distortion and energy dispersion existing in multi-mode signals are solved.

The invention relates to a wireless power transmission system parameter identification method based on a time domain differential model, and belongs to the technical field of wireless power transmission system control. The method comprises the following steps: establishing a parameterized time domain dynamic physical model; collecting system dynamic response data; constructing an optimization target based on a time domain residual error; and performing optimal parameter estimation based on iterative optimization. According to the method, a time domain dynamic physical model of a wireless power transmission system is constructed, and unknown parameters are solved through an iterative optimization algorithm with a minimum waveform matching error as a target. According to the algorithm, in an iteration process, a physical model is called to carry out forward differential equation solution, a time domain residual error between a model solution current and a real measurement current is used to drive a parameter estimation value to converge, and finally high-precision and high-robustness wireless power transmission system parameter identification under any working frequency is realized. The problem that in the prior art, due to static stiffness and sensitivity to waveform distortion of a theoretical model, the identification precision is insufficient is effectively solved.

The invention discloses a power transformation cabinet temperature and humidity remote monitoring and alarming method and system, and relates to the technical field of power transformation cabinet temperature and humidity monitoring and alarming, and the method comprises the following steps: a temperature and humidity monitoring system carries out the continuous monitoring of the temperature and humidity in a power transformation cabinet at a preset sensitivity, and monitors the temperature and humidity fluctuation; and any abnormal condition exceeding a safety range can be found and alarmed in time. By introducing the deep learning model to predict the load change trend, the response capability of the temperature and humidity monitoring system is remarkably improved. A traditional system depends on a fixed alarm threshold value and cannot deal with load fluctuation and rapid change in time, and a deep learning model intelligently predicts a load aggravation trend and generates an abnormal fluctuation index based on parameters such as real-time current waveform distortion and load response time. When the load is abnormal, the system automatically adjusts the alarm sensitivity, quickly captures the temperature and humidity change and triggers the alarm, thereby avoiding the temperature and humidity abnormity problem caused by the load fluctuation, and ensuring the safe operation of the equipment.

The invention relates to the technical field of power system court management, and particularly discloses a court identification and user binding method based on a special transformer acquisition terminal, which comprises the following steps: separating harmonic interference generated by start and stop of an electric welding machine through a kurtosis index and time-frequency energy entropy fusion detection method, and extracting a fundamental voltage and a pure power signal; constructing a dynamic time bending model containing phase consistency and gradient feature constraint based on the fundamental wave voltage, and calculating voltage track similarity to judge electrical coupling; for the users with electrical coupling, dynamic weight power cross-correlation analysis is fused to generate a comprehensive decision value, and a space-time diagram neural network is utilized to update a transformer area topology structure online in combination with a historical topology change event, so that the dynamic determination of the transformer area to which the users belong is realized; through multi-dimensional feature fusion and anti-interference algorithm design, the problems of phase deviation and waveform distortion caused by electric welding machine harmonic waves are reduced, and the transformer area identification accuracy and real-time performance are improved.

The invention relates to the field of crystal detection, and discloses a multifunctional comprehensive scintillation crystal and semiconductor material energy spectrum test system, which comprises a crystal adaptation module for judging the type and size of a placed crystal through an optical identification and parameter matching mechanism, and a signal acquisition module for amplifying, filtering and digitally processing an acquired signal, the signal correction module is used for correcting waveform distortion and baseline drift through a dynamic gain adjustment algorithm of a low-noise pre-amplifier and a multi-channel pulse analyzer; the data analysis module is used for generating an energy spectrum curve according to input signals and calculating energy resolution, counting rate, light attenuation time or carrier mobility, and the environment calibration module is used for dynamically evaluating shading degree, environment light, temperature and electromagnetic interference through an optical sensor and a temperature and humidity detector in the camera obscura and outputting updated calibration parameters. The method has the advantages of improving the detection efficiency, precision and consistency.

The invention discloses an intelligent diagnosis system for power utilization abnormal information acquisition, particularly relates to the technical field of power system monitoring, and is used for solving the problems of waveform distortion and broadening caused by transmission line distribution parameters in the long-distance wired transmission process of an existing system. The system collects abnormal characteristic waveform data through a distributed intelligent terminal, selects a characteristic harmonic component in the power frequency voltage of a power line to construct an inherent test signal, extracts the envelope form similarity of a response signal and the test signal through envelope analysis as a first distortion evaluation index, and obtains a second distortion evaluation index after statistical significance judgment. Performing instantaneous frequency stability analysis on the signal with significant distortion to obtain a second distortion evaluation index, and finally generating a corresponding waveform compensation parameter based on double indexes to realize real-time compensation correction; the integrity of the abnormal characteristic waveform in the transmission process is effectively maintained, and the accuracy and reliability of power consumption abnormity diagnosis are remarkably improved.

The invention discloses a composite voltage generation device and a cable insulation performance evaluation system and method, and relates to the technical field of high-voltage insulation testing. The composite voltage generating device comprises a synchronous controller, a direct current source, an impact source, an IGBT active protection unit and a magnetic isolation coupler, and by means of the excellent characteristics of the IGBT and the magnetic isolation coupler, the superposition time sequence accuracy of direct current and impact voltage is improved, and waveform distortion is reduced. The IGBT active protection unit comprises a first IGBT and a second IGBT, and direct-current voltage polarity switching can be realized through selective conduction of the IGBTs; the RC circuit is connected in parallel between the collector electrode of the first IGBT and the emitter electrode of the second IGBT, reverse current flowing back to the direct current source direction can be discharged through the RC circuit, the risk of energy flowing back is reduced, meanwhile, the magnetic isolation coupler can completely block direct current, and an impact source is protected against the influence of direct current voltage; according to the invention, the authenticity and reliability of cable insulation performance evaluation can be effectively improved.

The invention relates to the technical field of electronic exploder control, in particular to an anti-electromagnetic interference dynamic threshold control system and method for an electronic exploder, and aims to solve the problem that the electronic exploder is easily interfered in a complex electromagnetic environment to cause false triggering or missing detection. According to the system and the method, surrounding electromagnetic signals are acquired, time domain, frequency domain, waveform distortion and interference source features are extracted and fused to generate clustering feature vectors, and the signals are divided into pure interference, pure detonation control and superposed signals by using an improved K-means algorithm; and based on the clustering result and the interference intensity, adjusting an identification threshold in real time through a staged dynamic threshold adjustment formula, introducing a multi-dimensional reference factor of historical interference data after the interference is weakened, and stably recovering the threshold to a normal level by adopting a staged adaptive recovery mechanism. According to the system and the method, the anti-interference capability of the electronic detonator in a complex electromagnetic environment can be remarkably improved, and the safety and the accuracy of detonation operation are ensured.

The invention relates to the technical field of electronic component parameter optimization, in particular to an electronic component parameter optimization method and system, and the method comprises the following steps: collecting high-frequency measurement data of an electronic component; performing preliminary interference separation on the high-frequency measurement data to identify and suppress continuous waveform distortion caused by impedance mismatching of the transmission line and accidental transient electromagnetic pulses caused by reduction of shielding capability of the transmission line, and obtaining data after preliminary interference separation; performing purity evaluation on the data after the preliminary interference separation to quantify the degree of residual interference in the data after the preliminary interference separation to obtain a purity evaluation result; and dynamically adjusting an optimization strategy and a data weight of an electronic component parameter optimization program according to a purity evaluation result so as to carry out electronic component parameter optimization. The accuracy and efficiency of parameter optimization of the electronic component can be improved.

The invention discloses a power distribution network equipment fault regulation and control system based on traveling wave distance measurement, relates to the technical field of power distribution networks, and solves the problem that distortion signals of this kind cannot be acquired in a mode of changing sampling frequency in real time according to the change condition of signal frequency. The highest amplitude point, the lowest amplitude point and related wave bands are analyzed and processed through a unique algorithm, the frequency to be modulated is accurately locked, and the problems of waveform distortion, information loss and the like caused by insufficient sampling frequency are effectively solved; the regulation and control center adjusts the sampling frequency in real time according to the to-be-regulated frequency to ensure that the characteristics of the transient traveling wave signals can be fully acquired, the accuracy and integrity of signal acquisition are remarkably improved, the fault positioning precision is further improved, the troubleshooting time is shortened, and the operation reliability and stability of the power distribution network are enhanced. And a powerful guarantee is provided for safe and efficient operation of a power system.

The invention relates to the technical field of intelligent control of power electronic converters and induction heating, in particular to an intelligent control system of a medium-frequency power supply, which comprises a data acquisition module configured to acquire end-side voltage data and end-side current data of power conversion hardware in real time; the feature extraction module is configured to receive the end-side voltage data and the end-side current data and extract broadband waveform distortion features; the state evaluation module is configured to receive the broadband waveform distortion characteristics and calculate a model trust entropy value based on the broadband waveform distortion characteristics; the self-adaptive control module is configured to receive the model trust entropy value, trigger a second control mode to generate a second switch instruction and send the second switch instruction to the power conversion hardware; the model trust entropy represents a prediction deviation degree of a preset robust control model to the current real physical state of the power conversion hardware; according to the invention, the problem of insufficient perception of fine-grained service parameters in the background technology is solved.

The invention discloses an intelligent prediction and maintenance method and system for a power grid auxiliary control system, and relates to the technical field of power grid management and control, and the method comprises the steps: obtaining the electromagnetic field intensity and voltage waveform of a power grid in real time, building a standard library, carrying out Fourier transform and modeling, and obtaining an abnormal coefficient through abnormal processing and discontinuous point detection; high-frequency electromagnetic wave influence is predicted according to the coefficient, and a voltage waveform is fitted through a cubic spline interpolation method in case of abnormality, so that the system is ensured to be normal. According to the method, the electromagnetic field intensity is collected in real time, library establishment and comparison are performed, voltage waveform Fourier transform and discontinuity point detection are combined, the abnormal coefficient is comprehensively calculated, high-frequency interference is pre-judged, and waveform distortion is avoided; for abnormal waveforms, cubic spline interpolation is used for fitting discontinuous intervals, continuous functions and derivatives are met, signal self-repairing is achieved, and cost reduction and stability maintaining are achieved.

The invention discloses a laser radar multi-target ranging method and system based on adaptive waveform matching, and relates to the technical field of laser ranging, and the technical scheme is characterized in that the adaptive waveform matching mechanism proposed by the invention dynamically adjusts convolution kernel sampling points through a deformable convolutional network (DCN), and the adaptive waveform matching is realized; various nonlinear waveform distortions caused by electric field interference and complex target reflection characteristics can be actively adapted, and a customized matching template is generated for each input waveform. Equivalently, the system is endowed with the capability of eliminating counterfeit and keeping true in a strong electromagnetic interference environment, so that the robustness to special working conditions of ultra-high voltage hot-line work is fundamentally improved.

The invention discloses a distribution line fault detection method and device, equipment and a storage medium, and relates to the technical field of electric power inspection, hidden danger features are extracted through LSTM time sequence analysis, time sequence modeling is performed on current and voltage waveforms, harmonic distortion rate, waveform distortion and other features are extracted, and early abnormality of the equipment can be accurately identified through quantitative analysis of the features, so that the fault detection accuracy is improved. Early warning before a fault is achieved, and the passive situation that an existing system can only conduct positioning after the fault occurs is changed. The fault type is subjected to weighted fusion judgment by using the random forest + SVM algorithm, and the advantages of the two algorithms are integrated, so that the possible misjudgment condition of a single algorithm is greatly reduced, and the accuracy of fault judgment is improved. Secondly, waveform correction is introduced into a traditional double-end positioning formula, local spectrum analysis of edge nodes is combined, traveling wave propagation speed errors are corrected, dependence on clock synchronization of equipment at the two ends is reduced, and the fault positioning precision is improved.

The invention discloses a fault symptom rapid identification method, a fault symptom rapid identification device, a fault symptom rapid identification device and a computer readable storage medium for a converter transformer valve side external construction frequency resonance test, and the method comprises the steps: firstly, carrying out the real-time synchronous collection of multi-dimensional parameters, such as voltage, current, local discharge amount and waveform distortion; on the basis, a multi-parameter comprehensive criterion system is established, and fault type priorities are configured, so that accurate classification and identification of different types of fault symptoms are realized; a preset linkage disposal operation sequence is automatically triggered according to an identification result, and an automatic closed loop from monitoring and early warning to active protection is formed; and finally, through whole-process data recording and report generation, the traceable management of the fault information is perfected. According to the whole scheme, multi-source information fusion and intelligent decision control are combined, and systematic technical support is provided for early warning and quick response of faults in the test process.

The invention relates to a low-quality data identification method for strong vibration records, and belongs to the technical field of earthquake monitoring data processing. The method solves the problems of low manual identification efficiency and high omission ratio. According to the technical scheme, the method comprises the steps of firstly obtaining three-component acceleration time history data of strong vibration records; then constructing a multi-dimensional dynamic quality evaluation index system including data integrity, a signal-to-noise ratio dynamic range, a waveform anomaly index, a frequency response offset degree and a polarity consistency coefficient; performing real-time quality scoring on the data based on the system, and marking the data as low-quality data when the score is lower than a dynamic threshold value; and finally, adopting a self-adaptive classification algorithm to identify the abnormal type of the marked data, wherein the abnormal type comprises at least one of waveform distortion, baseline drift, polarity reversal and field response abnormity. The method is mainly used for improving the reliability and engineering application value of strong vibration observation data.

The invention belongs to the technical field of underground pipeline positioning and classification, and discloses an automatic underground pipeline identification and classification system. According to the method, a multi-parameter evaluation system of pipeline contour integrity, pipeline diameter volatility, waveform distortion degree and hyperbola deformation condition is constructed, so that the covering condition is comprehensively judged; the covering condition caused by factors such as pipeline overlapping and medium interference is effectively identified, and leak detection of deep or shielded pipelines is avoided; according to the method, the convex hull filling rate is used as a judgment basis, the area lower than the threshold value is judged as a misrecognition cavity through quantitative calculation of three-dimensional data processing software, the situation that an underground cavity is misjudged as a pipeline is avoided, and the data authenticity is improved; according to the method, inclined secondary scanning is carried out on the suspected covering area, two inclined scanning paths are designed, directional detection of the deep covered pipeline is achieved, the view angle limitation of traditional vertical scanning is broken through, and the detection success rate in a complex laminated pipeline scene is remarkably improved.

The invention provides a solar inverter grid-connected protection method, device and equipment and a storage medium. The method comprises the following steps: collecting power grid state data in real time through a virtual synchronous machine of a grid-connected inverter; according to a power grid supporting capability index of the power grid state data and historical waveform data, determining a voltage extreme value and a waveform distortion feature vector in a future preset duration, and generating a dynamic protection threshold set; when any threshold in the dynamic protection threshold set is triggered, generating a hash value according to the current fault waveform data, performing row distributed verification in the block chain node network, and outputting a verification result identifier; and performing multi-mode protection on the grid-connected inverter according to the fault level of the verification result identifier. Through the implementation of the scheme of the invention, the protection strategy can be adaptively adjusted according to the real-time state and waveform trend of the power grid, and the accuracy and response speed of fault recognition are remarkably improved.

The invention relates to the technical field of integrated photoelectron and electro-optical modulation, in particular to a thin-film lithium niobate electro-optical modulator structure and a preparation method of the thin-film lithium niobate electro-optical modulator structure. The buried layer is located on the upper surface of the substrate; the partially-etched thin film lithium niobate layer comprises a partially-etched thin film lithium niobate flat plate layer and a thin film lithium niobate ridge waveguide, the partially-etched thin film lithium niobate flat plate layer is located on the upper surface of the buried layer and exposes a part of the buried layer, and the thin film lithium niobate ridge waveguide is located on the partially-etched thin film lithium niobate flat plate layer; the partially-etched buffer layer is located on the partially-etched thin film lithium niobate layer, and the side wall of the partially-etched thin film lithium niobate flat plate layer is exposed; and the metal electrode is in electric contact with the side wall of the partially etched thin film lithium niobate flat plate layer. Therefore, the problems of low-frequency modulation waveform distortion, direct-current bias point drift and the like caused by electro-optical relaxation and electric field shielding of a related thin-film lithium niobate electro-optical modulator are solved.

The invention discloses a track irregularity dynamic detection method based on inertial navigation and non-filtering, which belongs to the field of railway track detection, and comprises the following steps: based on an inertial measurement unit, performing global integrated navigation solution by combining zero-speed information, a speed sensor and a GNSS positioning result to obtain a global reference navigation state sequence; point cloud registration and key point extraction are carried out on the two-dimensional point cloud obtained by scanning the surface of the track to be detected, and key point coordinates are obtained; performing mechanical arrangement of the sliding window inertial navigation system by taking the target chord length as the window length to obtain a bogie motion trail; and performing three-dimensional dynamic lever arm position compensation based on the global reference navigation state sequence, the key point coordinates and the bogie motion trail to obtain a track shape trail: calculating track irregularity parameters, and completing track irregularity dynamic detection. According to the method, track irregularity dynamic detection is realized, band-pass filtering processing is not needed, information loss is less, and waveform distortion can be avoided.

The invention relates to a material damage online monitoring method and system based on ultrasonic multi-feature fusion, and the method comprises the steps: obtaining a reference ultrasonic echo signal and a current ultrasonic echo signal in a current state, and carrying out the parallel calculation of a first damage index and a second damage index, wherein the first damage index is used for quantitatively representing ultrasonic signal energy attenuation characteristics caused by material plastic deformation; the second damage index is used for quantitatively representing ultrasonic signal waveform distortion characteristics caused by material microscopic damage; determining the weight of each damage index based on the data inherent statistical characteristics of the first damage index and the second damage index in the whole monitoring time sequence; and carrying out weighted fusion on each damage index by adopting the corresponding weight, and constructing a comprehensive damage index to quantitatively characterize the damage state of the material. Compared with the prior art, the method has the advantages of realizing accurate, dynamic and quantitative characterization of the damage degree of the material in the whole life cycle and the like.