10074results about "Resistance/reactance/impedence" patented technology

The invention provides a traveling wave cable measurement sensing method and system based on a time-frequency domain combined reflection principle, and relates to the technical field of measurement, and the method comprises the steps: arranging a high-frequency signal transmitting device and a signal receiving device at one end of a traveling wave cable; establishing a time domain reflection function and a frequency domain reflection function of the traveling wave cable; constructing a time-frequency domain joint reflection model; collecting a reflected signal of the traveling wave cable through the signal receiving device to obtain time domain data and frequency domain data of the reflected signal; carrying out conjoint analysis on the time domain data and the frequency domain data by utilizing a time-frequency domain joint reflection model, and extracting characteristic parameters of a reflected signal; calculating impedance change and signal propagation characteristics along the traveling wave cable based on the characteristic parameters in combination with a time-frequency domain joint reflection model; through analysis of impedance change and signal propagation characteristics, intrusion detection, leakage positioning and fault diagnosis along the traveling wave cable are realized.

The invention discloses a silver paste coating conductive uniformity test system and a test method, particularly relates to the technical field of silver paste coating conductive test, and is used for solving the problem that the silver paste coating conductive uniformity test is inaccurate. Through a high-precision pressure sensor and a camera device, contact state data of a probe are monitored in real time at each measuring point, a contact state matrix is generated to support accurate correction of contact resistance, after collected data are subjected to standardization processing, a support vector regression model is used for capturing a nonlinear relation, and the accuracy of the contact resistance is improved. The method comprises the following steps: optimizing a compensation model through cross validation and parameter tuning, setting an optimal pressure range to stabilize a contact condition and smoothly process data, correcting time deviation by adopting a multi-channel data acquisition and distributed sampling synchronization algorithm, correcting an error in combination with a compensation coefficient, and finally calculating a conductivity uniformity index through a resistance data matrix. Heat map classification evaluation is generated, a low-degree uniform region is repaired, and the consistency and reliability of a conductive uniformity test are remarkably improved.

An interface circuit includes a reference voltage generation circuit to generate a reference voltage, a differential voltage signal generation circuit to convert send data input in sending data into a pair of differential voltage signals and output the pair of differential voltage signals based on the reference voltage generated by the reference voltage generation circuit, a receiver to convert a pair of differential voltage signals input in receiving data and output received data, and a receiver test circuit to perform a sensitivity test of the receiver, the receiver test circuit having a resistance circuit to generate a pair of differential voltage signals having a potential difference being necessary for the sensitivity test of the receiver.

The invention discloses a system for monitoring line loss rate abnormity of a power distribution network station area, and relates to the technical field of power distribution network monitoring. The line loss rate abnormity monitoring system for the power distribution network station area comprises a data acquisition module, a data processing module, a line loss rate calculation module, an abnormity identification and alarm module and an on-site troubleshooting and diagnosis module. Through integrating functions of intelligent electric meter data acquisition, power grid data collection and area division, data processing, line loss rate calculation, abnormity identification and alarm, on-site troubleshooting and diagnosis and the like, comprehensive and real-time monitoring of the line loss rate of the power distribution network station area is realized. And a regional line loss calculation model is established according to the characteristics of the power distribution network of each region, and the line loss rate can be monitored in real time, dynamically calculated and predicted, so that the efficiency and accuracy of line loss management are greatly improved. And the abnormity identification and alarm module can timely discover and give an alarm of line loss abnormity, provides probability analysis of abnormity reasons, and is helpful for operation and maintenance personnel to quickly respond and process.

The invention provides a method for measuring the conductivity and the inner diameter of a pipeline based on sweep frequency eddy current. The method comprises the following steps: establishing an eddy current detection device, designing an absolute eddy current detection coil, placing the coil in a metal pipeline, arranging the coil and the pipeline coaxially, introducing alternating current to excite an alternating magnetic field, and inducing eddy current on the surface and the near surface of the pipeline; establishing a metal pipeline eddy current analysis theoretical model, setting coil geometric parameters, and calculating an analysis expression of coil impedance changing along with excitation frequency; calculating the peak frequency and the corresponding phase value of the impedance phase of the coil in a frequency sweep mode, respectively changing the conductivity and the inner diameter of the pipeline, extracting the corresponding peak frequency and phase value, and constructing an inner diameter relation model based on quadratic curve fitting and a conductivity relation model based on power function fitting; and inverting the inner diameter and the conductivity of the metal pipeline by combining a coil impedance sweep frequency phase measurement result. The method can be used for simultaneously measuring the conductivity and the inner diameter of the pipeline, and is suitable for nondestructive testing and performance evaluation of the metal pipeline.

The invention relates to the technical field of industrial safety, and discloses an electrolytic aluminum short circuit port operation safety early warning system based on multi-parameter collaborative awareness and intelligent diagnosis, and the system comprises a parameter collaborative awareness module, a dynamic diagnosis module, an early warning decision module, and an execution feedback module. By constructing a multi-dimensional parameter collaborative sensing mechanism, fusing temperature field distribution, current balance degree and insulation state multi-source data in real time and dynamically capturing early abnormal symptoms of a short circuit port, the hysteresis problem of traditional single-parameter threshold monitoring is solved, conversion from passive response to active defense is achieved, and the comprehensiveness and timeliness of operation state monitoring are improved; and meanwhile, based on a historical fault database and a real-time evolution model, a health index is generated and a fault path is predicted, so that maintenance personnel can pre-judge a development trend and a time window of potential risks in advance, and sudden equipment accidents are avoided.

The invention discloses a lithium battery health state assessment method and system, and the method comprises the steps: collecting the terminal voltage data and current data of a lithium battery at each moment in a discharge period in real time, so as to obtain a DC impedance estimation value at each moment; obtaining a discharge working condition of the lithium battery at each moment to screen a plurality of direct current impedance effective values, and constructing a plurality of direct current impedance value real-time sequences; calculating a direct-current impedance sequence estimation value of each direct-current impedance value real-time sequence; segmenting the plurality of direct-current impedance sequence estimated values and a preset discharge direct-current impedance data table according to the discharge working condition, and calculating a direct-current impedance average value and a direct-current impedance reference average value in each segment, and determining the health state of the lithium battery according to the DC impedance average value and the DC impedance reference average value, thereby realizing online evaluation of the health state of the lithium battery.

The invention relates to the technical field of storage batteries, in particular to a storage battery monitoring, detection, treatment and evaluation integrated system and a storage battery management method, and the system comprises a plurality of accompanying modules, a collection power distribution control module, a storage battery management capacity checking host and a remote platform; the internal resistance analysis test of the system is based on multi-frequency-point alternating current excitation (0.5 Hz-7. 5kHz), a complex impedance spectrum of not less than 20 frequency points can be constructed, and the internal polarization characteristics of the battery are analyzed; the system adopts a feed network type discharge capacity checking, so that discharge electric energy is fed back to a power grid, and the capacity detection precision is improved to 98%; according to the system, EIS data and an LSTM neural network are fused, and a battery state of health (SOH) prediction model is established; the system is based on a DSP digital power supply technology, and can realize 50A active equalization topology.

The invention discloses a cable oscillation ultralow-frequency withstand voltage and partial discharge integrated test method and system, and relates to the technical field of distribution network cable detection, and the method comprises the steps: applying an oscillation ultralow-frequency voltage signal to a tested cable; the oscillation ultra-low frequency voltage signal is optimized and adjusted through a manifold learning algorithm and is used as a common excitation source for a withstand voltage test, dielectric loss detection and partial discharge detection; acquiring a voltage signal and a current signal of the tested cable under the excitation of the oscillation ultralow-frequency voltage signal, analyzing the deviation degree of the voltage signal and the current signal from the pre-established characteristic manifold, and extracting a dielectric loss characteristic signal and a partial discharge pulse signal; calculating a dielectric loss parameter based on the dielectric loss characteristic signal, determining a partial discharge position based on the partial discharge pulse signal, and generating a cable insulation state diagnosis report according to the dielectric loss parameter and the partial discharge position. According to the invention, the cable testing efficiency is improved, the equipment burden and the testing time are reduced, comprehensive evaluation and accurate fault positioning of the insulation state are realized, and a scientific basis is provided for preventive maintenance of a power system.

The invention relates to a probe contact impedance real-time monitoring and compensating method and device and a storage medium. The method comprises the following steps: acquiring a first measurement data set containing a probe contact resistance value and a contact force, and inputting the first measurement data set into a double-layer deep learning neural network for training to obtain a probe contact resistance monitoring model; performing two-parameter fault detection to obtain a contact state classification result; generating a two-dimensional compensation matrix based on a contact state classification result, and performing nonlinear mapping calculation on the second measurement data set to obtain a compensation coefficient; the compensation coefficient, the original probe structure parameters and the original probe operation parameters are input into a graph attention stacking auto-encoder for parameter prediction, and target probe structure parameters and target probe operation parameters are obtained; cloud model calculation and weighting operation are carried out, a target compensation instruction is obtained, and the target compensation instruction is used for adjusting the probe position parameters and the probe pressure parameters. According to the invention, the probe testing precision of the chip is improved.

The invention relates to the technical field of bushing detection, and discloses a bushing insulation state detection method based on multi-parameter real-time monitoring. The method comprises the following steps: acquiring multi-dimensional monitoring data such as a partial discharge pulse sequence, dielectric loss angle tangent value fluctuation data and surface leakage current density distribution in a bushing operation environment in real time; carrying out insulation defect feature extraction on the data set, and generating an insulation defect distribution map containing a creeping discharge track, an internal air gap position mark and a carbonization channel density index; high-risk and potential defect areas are divided by adopting a dynamic threshold segmentation algorithm, boundary coordinates are determined, and an insulation state evaluation vector containing parameters such as a surface discharge intensity index and the like is constructed according to the boundary coordinates; and inputting the vector into a pre-trained insulation aging prediction model, and outputting a bushing residual insulation life estimated value and a defect development priority sequence. According to the method, all-around accurate monitoring and pre-judgment of the insulation state of the sleeve are achieved, and scientific support is provided for operation and maintenance decision making of the sleeve.

A method includes accessing a material database associating each of a plurality of materials with one or more corresponding resonance frequencies; for each material of at least a subset of the plurality of materials in the material database: transmitting, via an RF transmitter, an RF signal into a target at a first resonance frequency for each material; receiving, via an RF receiver, a response signal from the target; and analyzing the response signal for resonance characteristics that indicate a presence of each material in the target; generating a report of each material in the target indicated by the resonance characteristics; and integrating the report with at least one of: a timestamp; image or video data from a camera; or geolocation data from a geolocation sensor.

A non-invasive liquid integrity monitoring system using dielectric fingerprinting and machine learning to detect and identify contamination in sealed containers is described. The system may employ externally-mounted sensors that measure dielectric properties through electromagnetic interrogation, comparing measurements against baseline signatures to detect deviations indicating contamination, tampering, or degradation. Industry-specific ML models enable identification of specific contaminants with confidence, providing alerts without breaching container integrity.

The invention relates to the technical field of wiring terminals, in particular to an intelligent testing method and system for the contact resistance of a wiring terminal, and the method comprises the following steps: adjusting the resistance testing frequency according to the environment temperature to adapt to different conditions, combining current and voltage data, analyzing the historical change trend of the resistance, predicting the potential change range, and obtaining the contact resistance of the wiring terminal through the current and voltage data. Evaluating the mutual influence with the resistor, judging the abnormal reason of the resistor, adjusting a test scheme according to fault diagnosis, predicting potential faults, and making a test plan. According to the invention, through environment induction and data analysis, the resistance test frequency is adjusted in real time to adapt to environment change, so that the resistance measurement in the test process is more sensitive and accurate, the response speed and data quality of the test process are improved, historical and current resistance data are automatically analyzed, potential faults can be effectively predicted and identified, and the test efficiency is improved. Problems caused by operation errors are reduced, and a prospective fault prediction function enables the adjustment of the test period to be more scientific.

The invention relates to the technical field of electrochemical testing, in particular to an electrochemical impedance spectroscopy testing system based on multi-model combination, which comprises a data acquisition unit, a deep learning analysis unit, a frequency control unit and a feedback regulation unit. The deep learning analysis unit adopts a convolutional neural network and a long-short-term memory network to construct a model, after training, features are extracted, trends are analyzed, and dynamic frequency priority ranking is carried out, the frequency control unit drives the electrochemical workstation to adjust the frequency according to a weight generation strategy, and the feedback adjustment unit calculates predicted and actually measured impedance errors. When the threshold value is exceeded, parameter correction is carried out in each unit, the test frequency is intelligently optimized according to the dynamic change of the electrochemical process, key information is accurately captured, resource waste is avoided, the test efficiency and accuracy are improved, the stability and reliability of the system are ensured through a feedback regulation mechanism, and the research and analysis capability of the electrochemical system is effectively improved.

The invention relates to the technical field of monitoring, in particular to a cable aging monitoring and early warning method and system. The method comprises the following steps: acquiring cable monitoring data, and performing electrical characteristic analysis to obtain electrical characteristic data; performing conductor oxidation analysis based on the electrical characteristic data to obtain conductor oxidation data; cable image feature extraction is carried out according to the cable monitoring data, cable morphology type division is carried out, and curve segment cable data and winding segment cable data are obtained; performing bending fatigue analysis on the curve section cable data to obtain bending fatigue data; performing winding stress analysis on the winding section cable data to obtain winding stress data; performing material damage evaluation according to the bending fatigue data and the winding stress data to obtain material damage data; and carrying out damage position identification according to the material damage data to obtain damage position data. The cable aging monitoring accuracy and the early warning response rate are improved based on the monitoring technology.

The invention belongs to the field of power equipment monitoring, and discloses an electrical signal acquisition system based on intelligent dynamic sampling, which comprises a signal acquisition module, a signal conditioning module, an abrupt change detection module, an impedance calculation module and an upper computer, and is characterized in that the signal acquisition module comprises a first ADC module, a second ADC module, a first MCU module and a second MCU module. Short-circuit impedance real-time calculation and waveform abrupt change detection are adopted for cooperative judgment, and when equipment operates stably, the sampling rate of the system is kept low; when impedance changes or waveform changes suddenly, the sampling rate is improved automatically, important signal changes are recorded accurately, and waveform abrupt change detection is carried out by adopting an edge detection algorithm improved based on an FIR (Finite Impulse Response) filter. The system ensures the time sequence consistency of data under different sampling frequencies through multi-channel data synchronization and timestamp management, and meanwhile, smooth transition is performed by applying an interpolation algorithm during sampling switching, so that the continuity of a data sequence is ensured. The data redundancy is reduced; and the integrity of key information is ensured.

The invention relates to the technical field of integrated circuit testing, in particular to a distance-adjustable probe connector device which comprises an impedance detection unit which comprises a connector fixing part, a connector rotating part, a single connection port, a signal probe and a grounding probe. The impedance data unit is used for determining a characteristic impedance value of the tested microstrip line based on data acquired by the signal probe and the grounding probe; the pressure detection unit is used for determining the contact pressure according to the telescopic displacement of the signal probe and the grounding probe; the control unit determines the allowable range of the contact pressure of the probes based on the line width of the microstrip line to be tested and the distance between the probes, and adjusts the angle between the grounding probe and the surface of the PCB based on the contact pressure difference between the signal probe and the grounding probe and the line width of the microstrip line. And adjusting the contact pressure of the signal probe to obtain the effective characteristic impedance value of the tested microstrip line. According to the invention, the angle and pressure of the grounding probe are intelligently adjusted, and the problem of impedance measurement drift caused by pressure imbalance of double probes is eliminated.

The invention discloses a self-adaptive switching system and method for power supply and distribution, and the system comprises a data collection module, an analysis module, a modeling module, a decision module, an execution module and an early warning module, and the data collection module generates a real-time monitoring signal; the analysis module performs dynamic weighted evaluation according to the real-time monitoring signal and generates an evaluation signal; the modeling module constructs a virtual model of the power supply system and generates an analog signal; the decision signal generates a control signal containing a path selection instruction; the execution module controls the semiconductor device to switch the physical connection state of the power supply according to the control signal and generates a switch feedback signal; and the early warning module forms an equipment health assessment result according to the switch feedback signal and an abnormal arc signal when the execution module switches the connection state and transmits the result to the decision module. The self-adaptive switching system for power supply and distribution can solve the problem that a traditional power supply and distribution switching system depends on a single threshold to judge the state of a power supply and cannot comprehensively evaluate the quality of electric energy.

The invention provides a power distribution network operation risk intelligent identification and early warning method, which comprises the steps of identifying an equipment contact failure probability through an actual wear state, and when the equipment contact failure probability exceeds a safe operation requirement, determining an equipment fault early warning signal through historical fault statistical data, identifying potential equipment failure risk points and extracting risk distribution characteristics; identifying a high-risk equipment node through the equipment fault early warning signal, evaluating whether a cascading fault of adjacent equipment overload is caused after power flow redistribution of a power grid according to the identified high-risk node, extracting a fault propagation path, and determining a system risk level distribution diagram; and carrying out risk area division on the system risk level distribution diagram, identifying key equipment nodes in a high-risk area, extracting a load transfer scheme of the high-risk area, and determining a load distribution path and a power transmission direction.

The invention provides a coal mine underground 3DR electric leakage detection protection method, which comprises the following steps of: constructing an auxiliary star point connected with a system by using three-phase half-waves of a power supply system of a converter substation through a common cathode or common anode connecting wire; a residual current Hall sensor is used for detecting electric leakage residual current of different harmonic waves, and a 3DR electric leakage insulation resistance measurement technology is discriminated based on a Fourier algorithm; according to the harmonic component, the electric leakage resistance, the electric leakage value and the area of the frequency converter of the power supply system of the coal mine mobile converter substation can be judged, and alarm protection is judged; and the harmonic current is dynamically detected, so that selective leakage protection can be realized. According to the invention, through a 3DR electric leakage technology, electric leakage detection and instantaneous protection of the frequency converter are realized; selective earth leakage protection is realized according to the detection of the fundamental component and the harmonic wave; through harmonic leakage current and fundamental wave detection system distributed capacitance, electric leakage protection and capacitive current accurate judgment of power supply equipment in a coal mine power supply system are realized.

An impedance measurement apparatus is provided for measuring impedance of a secondary battery. The impedance measurement apparatus includes a measurement unit and a switching unit. The measurement unit is capable of measuring the impedance of the secondary battery using a plurality of measurement modes differing in measurement condition. The switching unit is configured to switch between the plurality of measurement modes based on a comparison between a correlating parameter, which correlates with the impedance of the secondary battery, and a threshold value.

The invention discloses an aluminum electrolytic capacitor state evaluation method and device, and the method comprises the steps: carrying out the frequency scanning measurement of an electrolyte and oxidation film interface, and obtaining the change data of an interface polarization current phase angle along with the frequency; measuring fluid dynamic characteristics of the electrolyte according to the polarization characteristic parameters, and detecting micro-flow response characteristics; according to the flow distribution data and the evolution data, applying a voltage sequence to carry out ion migration kinetic analysis; carrying out microstructure analysis in a preset temperature change process according to the ion distribution characteristics; and according to the structure change data and the dielectric response data, analyzing the change characteristics of the molecular level, the bubble distribution and the overall performance to obtain a stability evaluation result. According to the technical scheme, through multi-dimensional analysis of the interface polarization characteristic, the fluid dynamic characteristic, the ion migration dynamics and the microstructure change of the electrolyte, effective detection of bubbles and layering phenomena in the electrolyte is realized, and accurate evaluation of the performance state of the capacitor is facilitated.

The invention relates to the technical field of magnetic ring detection, discloses a magnetic ring multi-dimensional nondestructive detection system and method based on multi-frequency composite electromagnetic excitation, and solves the defects of existing magnetic ring detection in the aspects of information acquisition, composite excitation and comprehensive diagnosis. The method comprises the following steps: applying multi-frequency composite excitation, and collecting and preprocessing multi-dimensional response; and extracting features, and carrying out deep learning fusion inversion to obtain magnetic characteristics, material components and defect information. The system comprises a composite excitation module, a multi-mode sensing module, a data acquisition preprocessing module, a data fusion inversion module and a control module. By adopting the technical scheme, comprehensive and efficient nondestructive detection of multi-dimensional electromagnetic information of the magnetic ring is realized, the existing limitation is overcome, and the detection precision and the comprehensive diagnosis capability are remarkably improved.

The invention provides a 110V transformer winding insulation resistance absorption ratio detection method, which belongs to the technical field of transformer windings, and is characterized in that transformer operation state parameters and environmental influence factors are acquired through a multi-channel synchronous acquisition system, and thermodynamic and electrical models are established. The research adopts methods of principal component analysis, numerical integration and the like, an insulation resistance change rule is analyzed under a standard test voltage, a weight coefficient matrix is constructed in combination with an operation state and an environmental factor, a measured value is corrected through multiple linear regression and a correction coefficient method, and finally, the insulation resistance is obtained through statistical average and standard deviation analysis. The accurate evaluation of the insulation resistance absorption ratio of the transformer winding is realized; according to the method, the influence of the complex working environment and the operation state of the transformer on the insulation performance is fully considered, and the problem that various complex factors in the operation process of the transformer cannot be comprehensively considered and compensated in the prior art is solved by adopting the means of mathematical modeling, data correction, statistical analysis and the like; therefore, the technical problem of large deviation of the measurement result is solved.

The invention discloses a single storage battery internal resistance on-line measurement method, which relates to the technical field of battery detection and comprises the following steps: S1, establishing a dynamic load disturbance model of a storage battery; s2, extracting effective voltage drop component data from the noise signal by adopting an adaptive filtering method; s3, calculating equivalent internal resistance by using a complex impedance calculation method; s4, performing multi-scale internal resistance evolution analysis based on the calculated equivalent internal resistance; and S5, based on multi-scale internal resistance evolution analysis, performing fault early warning on internal resistance abnormity. According to the on-line measurement method for the internal resistance of the single storage battery, high-precision on-line measurement of the internal resistance of the single storage battery is realized through construction of a dynamic load disturbance model, multi-scale internal resistance evolution analysis and fault early warning based on the internal resistance. Compared with the prior art, the method can accurately capture the influence of the load change on the internal resistance, utilizes the multi-scale internal resistance evolution analysis to early warn the internal resistance abnormity in advance, and improves the health management capability in combination with the multi-scale analysis.

The invention discloses a dynamic on-resistance test circuit based on a gallium nitride transistor and a test method thereof. Belongs to the technical field of power electronics. The circuit comprises a DPT test circuit, a switch state switching circuit and a clamping circuit, the test method comprises the following steps: monitoring the voltage between test points on the clamping circuit and the current on the coaxial resistor to obtain the on resistance of the to-be-tested tube; the switching between the hard switching test and the soft switching test is realized by changing the switch interface. According to the invention, a gallium nitride transistor and a clamping circuit are introduced into a traditional double-pulse test circuit, and a dynamic on-resistance test function in a soft switching mode and a hard switching mode is integrated. Compared with a traditional testing circuit, the clamping circuit can capture the dynamic on-resistance within nanosecond time delay, meanwhile, the peak of the clamping voltage is greatly reduced, the testing precision is improved, and rapid and accurate measurement of the dynamic on-resistance is achieved.

The invention discloses a multi-condition simulation capacitance detection relay life prediction method, system, equipment and medium, and relates to the technical field of relays, and the method comprises the steps: applying a plurality of simulation conditions to a relay through a programmable driving power supply, simulating the complex conditions in actual operation, and collecting the multi-dimensional parameters of the relay in real time in the execution process of the simulation conditions, extracting characteristic parameters from the collected multi-dimensional parameters, carrying out data preprocessing on the characteristic parameters, constructing a life prediction model, carrying out prediction calculation and reliability grade evaluation on the residual life of the relay by utilizing the life prediction model, and carrying out reliability grade evaluation on the residual life of the relay by monitoring capacitance change between contacts of the relay. And early performance degradation early warning is carried out in combination with a prediction result. According to the invention, through fusion of multi-working-condition simulation, hybrid modeling and capacitance detection, full-chain optimization from data acquisition, accurate prediction to early warning is realized, and the accuracy, timeliness and engineering application value of relay life prediction are improved.

The invention relates to the technical field of electrical property detection, and discloses a graphene film surface property detection device, which comprises a data acquisition module used for acquiring electrical property data of the surface of a graphene film through a multi-point array electrode probe; the vector grid modeling module is used for constructing a vector grid model for representing the surface performance of the graphene film according to the electrical characteristic data; the iterative inversion calculation module is used for performing iterative inversion calculation on the vector grid model to determine the surface performance distribution of the graphene film; the parallel optimization fusion module is used for performing parallel processing and optimization fusion on the multi-scale performance data through a distributed computing framework; the three-dimensional visualization module is used for generating a three-dimensional visualization model of the surface performance of the graphene film according to the optimized and fused performance data; the problems of insufficient precision and low efficiency of a traditional detection method in graphene film performance detection are solved.

The invention discloses a detection method of a high-speed connector and a related device, and the method comprises the steps: carrying out the plugging motion control of the high-speed connector, injecting a pulse sequence carrying a displacement mark into a differential signal pair in the process, and obtaining the initial reflection data containing a plugging displacement-time index; space-time boundary information of a gap coupling section, an initial touch deformation section and a full-insertion steady-state section is analyzed and determined in a segmented mode through reflection characteristics. And generating a mutual excitation pulse pair in the initial touch deformation section, and executing differential sampling processing by using a thermal-electric coupling effect to obtain a thermally induced group delay sequence and a geometrically induced impedance differential sequence. A dynamic zero-reflection anchor point is generated based on double-sequence fusion, and real-time reference plane migration processing is realized to obtain a calibration impedance curve. And repeating the processes of insertion and extraction, generating an elastic difference curve through displacement-time coaxial difference processing of a bidirectional calibration impedance curve, and positioning an irreversible abnormal section of the impedance. According to the method, the plugging transient impedance change can be continuously monitored, and the early failure risk of the high-speed connector can be evaluated in time.