102 results about "Harmonic analysis" patented technology

The invention relates to the technical field of elevator operation and maintenance, and discloses a multi-source data fusion method and system for elevator fault localization, and the method comprises the steps: carrying out the noise filtering and data alignment of multi-source monitoring data of an elevator during operation, and obtaining a monitoring data set; performing time-frequency analysis on acceleration sensor data in the monitoring data set to obtain vibration mode characteristics; performing harmonic analysis on the motor current data to obtain current distortion characteristics; performing space-time correlation on the vibration mode characteristics, the current distortion characteristics and the safety loop state in the monitoring data set to obtain a comprehensive fault characteristic vector; according to the comprehensive fault feature vector, specific components and types when the elevator breaks down are determined, so that fault positioning information is obtained; the fault positioning information is transmitted to an elevator monitoring terminal, and the elevator is maintained according to the fault positioning information; according to the invention, the fault positioning efficiency can be improved.

The invention relates to the technical field of optical current transformer detection, and provides an optical current transformer real-time calibration and health diagnosis method and system, and the method comprises the steps: carrying out the harmonic analysis of an initial digital signal sequence obtained through the conversion of a continuous modulation optical signal of a target optical current transformer, and obtaining harmonic component data; physical state evaluation is carried out according to the higher harmonic component data and preset health state baseline data to generate a physical state evaluation result, nonlinear disturbance compensation is carried out according to an error control signal generated based on the higher harmonic component data, and after a linear working point is reached, nonlinear disturbance compensation is carried out; and calculating an electrical measurement value according to the output target fundamental component data, and performing comprehensive analysis according to the physical state evaluation result and the electrical measurement value to generate a diagnosis report. According to the invention, through a measurement calibration and state diagnosis mechanism based on harmonic analysis, while the electrical performance measurement precision is effectively improved, reliable quantitative diagnosis and accurate traceability of different physical faults in the equipment are realized.

The invention belongs to the technical field of grid-connected inverter harmonic analysis, and particularly discloses a grid-connected inverter harmonic closed-loop transmission analysis method and system considering broadband coupling. The method comprises the following steps: respectively establishing a harmonic component transfer function of each module; based on the harmonic component transfer function of the sampling module, calculating to obtain harmonic active power and harmonic reactive power input to the power outer loop control module; based on a harmonic component transfer function of the power outer loop control module, calculating to obtain a harmonic current component in a reference current signal output by a power outer loop; based on a harmonic component transfer function of a current inner loop control module, obtaining a three-phase modulation voltage harmonic component and an inverter port voltage harmonic component through coordinate inverse transformation; on the basis of the inverter port voltage harmonic component, a main circuit harmonic transfer equation is combined, and a grid-connected point harmonic current component is obtained through calculation; the method overcomes the defects that a traditional analysis method cannot consider the control of a whole loop by a closed loop, and the broadband coupling is insufficiently considered.

The invention relates to the technical field of motor diagnosis, and discloses a motor eccentricity fault diagnosis method and system based on current harmonic analysis, and the method comprises the steps: carrying out the power frequency component extraction of a three-phase stator current signal, obtaining a residual current signal, carrying out the complex analysis envelope transformation of the residual current signal, and obtaining an envelope analysis signal; performing synchronous interpolation resampling on the envelope analysis signal to obtain a complex envelope signal; performing frequency spectrum estimation on the complex envelope signal to obtain a discrete frequency spectrum of a module value sequence; performing equalization processing on the order spectral line amplitude in the discrete spectrum to obtain a whitened spectrum, and performing inverse transformation on the whitened spectrum to reconstruct an angular domain amplitude signal of the target motor; performing cyclostationary analysis on the angular domain amplitude signal to obtain a third-order cyclic cumulant of the angular domain amplitude signal at a specific cyclic frequency; according to the third-order cycle cumulant, the type and severity level of the eccentric fault are judged; the accuracy of motor eccentricity fault diagnosis can be improved.

The invention discloses a rotor turn-to-turn short circuit diagnosis method based on an exciting current-shaft voltage harmonic nonlinear correlation coefficient. The method comprises the following steps: synchronously collecting parameters, and preprocessing the collected parameters through wavelet threshold denoising and temperature normalization; extracting harmonic analysis according to the shaft voltage harmonic characteristics; identifying magnetic saturation, temperature and load nonlinear factors and calculating corresponding coefficients; performing dynamic correction on the Pearson's correlation coefficient through the nonlinear correction coefficient, and combining with fuzzy logic weighting to obtain fuzzy logic weighting; defining a working condition feature vector, and constructing a working condition adaptive dynamic model comprising a linear regression basic model and an LSTM neural network; and calculating a dynamic threshold value based on the basic threshold value and the nonlinear factor, and judging the turn-to-turn short circuit trend of the rotor according to the comparison of the correlation coefficient and the dynamic threshold value and a prediction result. According to the invention, through combination of the nonlinear correction correlation coefficient and the LSTM neural network, dynamic compensation of nonlinear factors is realized, and the accuracy and reliability of rotor turn-to-turn short circuit fault diagnosis are improved.

The invention provides a data processing method and device for an intelligent acquisition terminal, and the method comprises the steps: determining whether a current signal is in a smooth or linear change stage or a rapid change stage according to the ratio of the first-order difference to the absolute value of a preset signal change rate threshold value; according to the method, a sampling interval is dynamically adjusted according to a change condition of a signal, so that the collected data can reflect a waveform change condition of the signal, then key feature point data collected within a preset sampling duration is determined, and a data packet of a key moment where a key feature point is located is constructed; the key feature point data can reflect the amplitude and the key time domain of the signal waveform, and the characteristics of the signal waveform can be restored through the amplitude and the key time domain, so that the relatively accurate signal waveform is obtained, the distortion condition during subsequent harmonic analysis is reduced, and the accuracy of power grid state judgment is improved.

The invention discloses a broadband harmonic voltage measuring system and method based on an improved CVT, and the system comprises a first current sensor which is used for measuring the first current of a high-voltage capacitor of the CVT; the broadband harmonic wave acquisition device is used for sampling the first current to obtain first current sampling data; and the broadband harmonic analysis device is used for determining an amplitude frequency spectrum of the first current based on the first current sampling data and determining each frequency component of the system voltage based on the amplitude frequency spectrum of the first current. On the basis of a large number of CVTs used in a power system, the broadband harmonic voltage measurement function within the range of hundreds of kHz is achieved by improving the CVT, the original power frequency measurement function of the CVT is not changed, the operation reliability of the CVT is not reduced, and effective broadband, high-precision and low-cost harmonic voltage measurement can be achieved.

The invention relates to a power distribution network harmonic analysis method and system, and the method comprises the steps: constructing a digital twinborn model of a power distribution network region, and selecting transformers in the region as analysis objects one by one; for each analysis object, various working conditions are simulated by changing the transformation ratio of the analysis object in a digital twin model, and voltage and current waveforms are collected and subjected to Fourier decomposition to obtain harmonic phasors; thirdly, performing phase reduction on the phasor data, separating a real part from an imaginary part to construct a matrix, and solving a harmonic coefficient matrix by using a least square method to realize error minimization; separating linear and nonlinear parts of the harmonic current, and calculating a harmonic emission capability parameter and a harmonic current risk parameter for quantitative evaluation; according to the method, all transformers are traversed and analyzed, and systematic harmonic evaluation of the whole power distribution network area is finally realized.

The present application relates to a kind of Fourier transform-based ATSE power harmonic analysis method, comprising the following steps: collecting each AD data, each AD value is processed by central axis zeroing;After each AD value processed by central axis zeroing, Fourier transform calculation is carried out, and the harmonic content of each waveform is obtained;According to each harmonic content, total harmonic content is obtained;According to total wave effective value and total harmonic content, further obtain fundamental effective value;Through the fundamental effective value and each harmonic content, control logic analysis power state is assisted.The present application is based on Fourier transform harmonic analysis method, helps automatic transfer switch to analyze the harmonic content of current power, so that controller more comprehensive analysis power state, more suitable switching mode is selected according to load condition, further improve the safety and reliability of dual power automatic transfer switch, maintain the normal operation of entire power system, protect electrical equipment and reduce power loss.

This invention belongs to the field of electrical digital data processing technology, specifically relating to a multi-objective optimization method for improving motor torque performance. The method includes: establishing a parameterized model of the motor; extracting geometric harmonic prior features based on the harmonic analysis principle of the motor's air gap magnetic flux density, and using these as a screening criterion to obtain an initial high-quality sample set; constructing a Kriging surrogate model reflecting the mapping relationship between design variables and performance response, introducing an energy efficiency boundary risk function during the construction process; based on the Kriging surrogate model, using a multi-objective optimization algorithm to search for a Pareto front solution set, selecting potential sample points from the Pareto front solution set for simulation verification, and then adaptively updating the Kriging surrogate model until the stopping criterion is met, at which point the target motor design parameters are output. This invention can achieve accurate optimization of electromagnetic parameters by screening samples through geometric harmonic prior features and utilizing the energy efficiency boundary risk function.

The present application relates to the technical field of fault monitoring, in particular to a wind turbine transmission chain fusion perception monitoring system, the system comprising a perception deployment module, a data synchronization module, a structure extraction module, a state identification module and a fusion monitoring module. In the present application, multi-source signal fusion analysis is carried out in multiple transmission components, unified time alignment and multi-parameter synchronous sampling are carried out after the attribution of each node signal channel is determined, periodic joint fragments are constructed in combination with multi-parameter characteristics in the harmonic analysis window, the parameter change trend of different components is associated and analyzed, the cross-deconstruction and directional deviation identification of multi-dimensional characteristics such as strain, temperature and vibration are carried out, the fine-grained classification result of the running state of each transmission component is obtained, the accuracy of abnormal sign identification and the response ability of trend change perception are significantly improved, the fusion monitoring and abnormal identification of each component in the transmission chain under the unified framework are realized, and the ability of the monitoring data to express the real state evolution process is ensured.

The invention discloses a tide level correction applicability evaluation method and system for a tide station, and belongs to the technical field of machine learning processing under tide harmonic analysis, and the method comprises the steps: carrying out the unified time reference alignment and preprocessing of an actually measured tide level time sequence; respectively constructing a physical error sequence and a machine learning error sequence; obtaining a physical side performance characteristic index and a machine learning side performance characteristic index; according to the tide level correction applicability evaluation method and system of the tide station, eight novel performance indexes are respectively calculated by constructing an error sequence of an actually measured tide level, a physical tide level and a machine learning tide level, so that a quantitative judgment result whether machine learning correction is recommended or not is given under the constraint of a physical mechanism.

The invention provides a method for quantifying tidal non-stationarity, and belongs to the technical field of natural science research based on nonlinear data analysis. Firstly, hour-by-hour tide observation data with the observation duration not less than one month in a target sea area are obtained; separating non-tidal low-frequency and high-frequency tidal changes in the data by using an empirical mode decomposition method, and extracting a tidal component; returning the tide component through a classical harmonic analysis CHA model to obtain CHA return tide; then calculating a correlation coefficient, a mean absolute error and a root-mean-square error of the tidal component and the CHA, and respectively dividing the mean absolute error and the root-mean-square error by an average value of the observation absolute values to obtain a normalized index; finally, (1, 0, 0) is used as a reference point, (CC, NMAE, NRMSE) is used as an observation point, and the tidal non-stationarity index NS is calculated according to a two-point distance formula. The device can be widely applied to global sea areas and is suitable for sea areas of different tide types and sea areas of different tidal ranges.

The present application belongs to the technical field of power monitoring, and discloses a detection method for monitoring the state of primary-secondary fusion circuit breaker, comprising: obtaining circuit breaker state data, including electromagnetic waveform data, harmonic response characteristics and temperature distribution gradient; obtaining circuit breaker electric field distribution fingerprint through nonlinear segmented harmonic analysis, constructing a multi-dimensional penetration feature matrix, and establishing a micro-scale electric-thermal coupling atlas; obtaining a nonlinear region situation table through impedance distortion analysis, obtaining a harmonic penetration curve through multi-frequency response analysis, and constructing a high-frequency harmonic penetration path spectrum; establishing a micro-region diagnosis algorithm, performing nonlinear impedance calibration, and generating a multi-level protection instruction sequence; adjusting the operating state of the circuit breaker, obtaining the circuit breaker medium steady-state index, and performing risk analysis to obtain a harmonic penetration early warning report; the present application realizes accurate identification and early warning of abnormal regions inside the circuit breaker, and improves the safe and stable operation ability of the primary-secondary fusion circuit breaker.

The invention discloses a GPS / GLONASS inter-frequency clock deviation modeling and forecasting method and device, and the method comprises the steps: obtaining positioning data received by a receiver from a satellite, and constructing a geometric-free ionosphere-free phase combination observation value according to the positioning data; an inter-epoch difference method is adopted to remove ambiguity constants absorbing phase hardware delay time invariants in the geometry-free ionosphere-free phase combinations, and a single observation station ionosphere-free combination IFCB is obtained; integrating observation data of multiple observation stations, and calculating a final IFCB deviation by adopting a multi-station weighted average mode; according to the IFCB data, carrying out harmonic analysis by adopting fast Fourier transform to obtain an accurate period of an IFCB sequence, and proposing an IFCB model based on a third-order polynomial and a seven-period harmonic function; and performing experiment forecasting according to the IFCB time sequence model, extracting and comparing periodic characteristics of IFCB deviation, and calculating an optimal forecasting period. According to the method, the observation data of the GPS / GLONASS system can be corrected in real time, so that the positioning result is accurately corrected to improve the positioning accuracy.

The utility model provides a kind of ground impedance detection device based on harmonic analysis, belong to ground impedance detection technical field, including main frame assembly, the inner wall of main frame assembly is connected with ground impedance detector, the outer wall of main frame assembly is fixedly connected with limiting component, the outer wall of main frame assembly is provided with honing component, the outer wall of main frame assembly is provided with side support component, the outer wall of main frame assembly is provided with take-up assembly;The utility model is provided with take-up assembly, in use, by take-up motor driving take-up rod rotation, and then realize the orderly winding of the wire connected with probe or ground electrode test point, avoid multiple wires between each other cross each other, improve the accurate detection of ground impedance detector in field use;By the setting of limiting component, in use, start and control rotary motor use, drive press plate rotation, so that multiple spring barrels are above ground impedance detector.

This invention belongs to the field of energy efficiency management technology. It discloses an integrated system for oil well power metering and energy efficiency analysis based on the Internet of Things (IoT). The system includes: real-time acquisition and fusion processing of parameter data through an IoT sensing layer to obtain a corresponding basic energy consumption dataset; generation of standardized power metering data using harmonic analysis and phase compensation algorithms; multi-scale pattern mining and load decomposition of the standardized power metering data to construct a power load characteristic model; analysis of the relationship between production status and energy consumption to establish an energy efficiency evaluation index system and energy consumption baseline; real-time evaluation and benchmarking analysis using group clustering and anomaly detection algorithms to form an energy efficiency optimization strategy knowledge base; output of intelligent control decision sequences through multi-objective optimization; execution of the intelligent control decision sequences and adoption of a closed-loop feedback mechanism to achieve adaptive and precise equipment control and collaborative energy consumption management, effectively solving the problems of traditional oil well power management.

Described are various technologies pertaining to identifying a dominant frequency in an acquired signal, such as a frequency corresponding to a human heartbeat in an acquired video signal. In connection with identifying the dominant frequency, a sub-signal of the acquired signal is extracted from the acquired signal, where the sub-signal includes Nsamples number of samples (frames). A looped signal is generated by looping the sub-signal. Nsamples is incremented, and the process is repeated until Nsamples is equivalent to a predefined threshold; accordingly, numerous looped signals are formed. The dominant frequency is identified based upon the looped signal and presented with the corresponding uncertainty based on harmonic analysis.

The application relates to a power distribution network harmonic index data evaluation, transmission method and system, the method comprising: after obtaining harmonic index data, directly judging whether a harmonic abnormal event occurs in real time according to the harmonic index data, so that the uploaded harmonic abnormal event has real-time performance. The harmonic index data is fitted to obtain fitting coefficients and is uploaded, so that a superior terminal such as a harmonic analysis platform can restore the harmonic index data at any time according to the fitting coefficients. Meanwhile, the application also screens the to-be-transmitted data in the harmonic index data, and only uploads the to-be-transmitted data, thereby reducing the data transmission amount and enabling the superior terminal to verify the restored harmonic index data through the to-be-transmitted data.

The invention provides a medical equipment power distribution monitoring method and system based on artificial intelligence, relates to the technical field of medical equipment power management, and solves the technical problems that the detection precision is insufficient and potential risks are lack of intelligent prediction in the existing medical equipment power distribution monitoring process. The method comprises the following steps: acquiring power supply data and resolving the power supply data to obtain power supply parameters; pre-processing the power supply parameters through a pre-processing algorithm to obtain pre-processed data; performing harmonic analysis on the preprocessed data through an FFT algorithm to obtain harmonic parameters; performing anomaly detection on the preprocessed data and the harmonic parameters based on threshold comparison to obtain a real-time anomaly result; inputting the preprocessed data and the harmonic parameters into a pre-trained risk prediction model to obtain a prediction risk result; and performing weighted fusion decision on the real-time abnormal result and the prediction risk result to generate an abnormal alarm signal. The method is used in the medical equipment power management process.

This invention discloses a method and apparatus for detecting and demagnetizing residual magnetism in the core of an electromagnetic current transformer, comprising: acquiring current and voltage signals; performing harmonic analysis on the current signal; performing integration processing on the voltage signal; performing phase decomposition on the even-order harmonic components based on the fundamental phase of the magnetic flux to extract the residual magnetism-related components; determining the normalized residual magnetism index based on the residual magnetism-related components and the odd-order harmonic components; using a controllable current source connected in parallel with the secondary circuit of the electromagnetic current transformer; and adjusting the polarity and amplitude of the controllable DC component using the normalized residual magnetism index as a closed-loop feedback signal to make the normalized residual magnetism index approach zero. This invention can detect the presence and level of residual magnetism in the core online without shutting down the electromagnetic current transformer or interrupting its metering and protection functions, and automatically implement closed-loop active demagnetization when the detected residual magnetism exceeds a safety threshold, restoring the core to a symmetrical magnetization working state without residual magnetism.

The application belongs to the technical field of circulation mixing coefficient estimation, and discloses a global estimation method, system, device and terminal of a wave-induced turbulent mixing model, the global estimation method of the wave-induced turbulent mixing model comprising: estimating the global three-dimensional structure of the internal tide-induced turbulent mixing coefficient based on the wave-induced turbulent mixing coefficient, the internal tide information extracted by the satellite altimeter and the WOA13 temperature and salinity data; determining the structure of the global internal wave spectrum; and estimating the distribution characteristics of the global annual average internal wave-induced turbulent mixing coefficient BVIW. The internal tide information extraction comprises: obtaining, processing and filtering satellite along-track sea surface height anomaly data, performing tidal harmonic analysis on the filtered data, and obtaining the internal tide harmonic constant of the global ocean tidal frequency M2. According to the derived mixing coefficient, new mixing is not created, but a mixing process that is not available under the existing framework and is rich in physical connotation is created, and the important significance of wave mixing to the circulation is given.

The application relates to the technical field of motor diagnosis, and discloses a motor eccentric fault diagnosis method and system based on current harmonic analysis. The method comprises the following steps: extracting a power frequency component of a three-phase stator current signal to obtain a residual current signal, and performing complex analytic envelope transformation on the residual current signal to obtain an envelope analytic signal; performing synchronous interpolation resampling on the envelope analytic signal to obtain a complex envelope signal; performing spectrum estimation on the complex envelope signal to obtain a discrete spectrum of a modulus sequence; performing equalization processing on the order spectrum line amplitude in the discrete spectrum to obtain a whitened spectrum, and inversely transforming and reconstructing the whitened spectrum into an angular domain amplitude signal of a target motor; performing cyclic stationary analysis on the angular domain amplitude signal to obtain a third-order cyclic cumulative quantity of the angular domain amplitude signal at a specific cycle frequency; and determining the type and severity level of the eccentric fault according to the third-order cyclic cumulative quantity. The application can improve the accuracy of motor eccentric fault diagnosis.

The invention discloses an electric power verification non-contact anti-electricity-stealing detection method and system, and relates to the technical field of electric power detection, and the method comprises the steps: collecting a voltage signal and a current signal of a to-be-detected electric power circuit through a portable voltage non-contact anti-electricity-stealing detector non-contact voltage clamp and a portable voltage non-contact anti-electricity-stealing detector non-contact current clamp; performing real-time harmonic analysis on the collected current signal to obtain a harmonic component effective value and a fundamental current effective value; performing dynamic error correction on the current measurement value according to the effective value of the harmonic component and the effective value of the fundamental current; the actual electric energy error of the electric energy meter is determined according to the voltage value and the corrected current value, and whether the electricity stealing behavior exists or not is judged based on the actual electric energy error, so that the harmonic component condition caused by the power grid environment can be overcome, and harmonic waves caused by the electricity stealing load can be accurately identified and identified; the electricity larceny recognition efficiency and precision are improved, and meanwhile the high quality and high precision of current data are guaranteed.

The invention provides a high-precision troposphere delay modeling method, device and equipment under a sparse GNSS (Global Navigation Satellite System) site, and belongs to the technical field of spatial scientificity, and the method comprises the steps: calculating an initial ZTD (Zero Time Division) value of a real GNSS site through a first preset empirical model, constructing a ZTD residual time sequence by combining a GNSS actually measured ZTD value, analyzing a periodic signal, constructing a residual model to obtain a ZTD residual, and calculating the ZTD residual according to the ZTD residual. Further obtaining a ZTD improved value of the GNSS real station; based on a second preset empirical model in which an error correction term is introduced, virtual sites are arranged in the sparse region, and ZTD values of the virtual sites are generated; performing weighted fusion on the real and virtual ZTD values through a variance component estimation method to obtain a unified ZTD observation data set; and adopting spherical crown harmonic analysis to solve the adaptation coefficient, constructing a continuous ZTD model, outputting full-region data, and generating a high-resolution and high-precision ZTD map. According to the method, the defect that sparse GNSS station data coverage is insufficient is effectively overcome, and troposphere delay modeling precision, space continuity and area coverage integrity are remarkably improved.

The invention relates to a UPQC adaptive harmonic suppression method and system based on an intelligent terminal, and the method comprises the steps: collecting the multi-node electrical quantity of a medium-voltage transformer area through the intelligent terminal, and carrying out the sequential decoupling, thereby obtaining positive, negative and zero-sequence components; carrying out harmonic analysis, counting the content ratio, the phase and the power direction of each order of harmonic, forming a harmonic portrait containing the harmonic source intensity, the impedance resonance risk and the interphase coupling coefficient, identifying dominant and cross harmonics according to the harmonic portrait, and generating a UPQC parallel unit target compensation current instruction and a series unit reference voltage instruction on line; and the parallel side of the UPQC executes selective harmonic injection and dynamic damping, and the series side is matched to perform voltage compensation so as to realize combined suppression. The terminal continuously senses environment change and capacitor switching, and dynamically adjusts a sampling window and inhibits bandwidth. According to the method and the system, accurate perception is realized by constructing a harmonic portrait, and adaptive decision and control are carried out, so that the combined suppression effect and the system stability of the UPQC in a complex harmonic environment can be improved.

The embodiment of the application provides a kind of vector control method and system based on multidimensional space, it is related to the technical field of motor technology.The method comprises: obtaining the real-time current error signal of the current loop of motor controller;Based on the real-time current error signal, selective harmonic analysis is performed on the preset key frequency point to construct the multi-dimensional vibration vector representing the vibration state of the system, wherein the key frequency point covers the audible frequency range of human ear;The multi-dimensional vibration vector is first processed to calculate the perceived vibration energy value;According to the deviation between the perceived vibration energy value and the preset target energy value, generate proportional-integral parameter adjustment amount;Based on the proportional-integral parameter adjustment amount, dynamically update the proportional-integral controller parameters of the current loop.Through the application, the problem of low motor control sensing accuracy is solved, and the sensing accuracy is improved.

The invention relates to the technical field of household appliance control, and discloses an intelligent frequency conversion temperature control method and system of a high-rotating-speed double-frequency hair drier. The method comprises the following steps: collecting multi-modal operation data; constructing a current harmonic model related to the rotating speed of the motor; self-adaptive signal separation is conducted on original temperature data through the model, and the real air outlet temperature is extracted; pre-judging a temperature change trend in a frequency conversion process by combining a thermal dynamic prediction model; calculating a heating power compensation amount; and a heating and frequency conversion control instruction is generated through an intelligent temperature control decision algorithm. The system comprises a multi-modal data acquisition module, a harmonic analysis module, a signal separation module, a thermal prediction module, a power compensation module, a temperature control decision module and an execution control module. According to the technical scheme, the temperature control precision, the response speed and the use safety are improved.

A live-line verification device and method for high-voltage instrument transformers are disclosed. The device includes a signal acquisition module, a signal processing module, a data transmission module, a control module, and a display module, all electrically connected in sequence. The signal acquisition module employs a voltage divider voltage sensor and a Rogowski coil current sensor to accurately acquire secondary-side voltage and current signals. The signal processing module uses second-order RC low-pass filtering, adjustable-gain instrument amplification, and high-sampling-rate analog-to-digital conversion to achieve interference filtering and signal optimization. The control module incorporates an error calculation algorithm and a Fourier harmonic analysis algorithm to accurately calculate the ratio difference and angle difference. The method, based on the aforementioned device, achieves live-line verification of high-voltage instrument transformers through standardized connection, acquisition, processing, calculation, and display steps.