59 results about "Current spectrum" patented technology

The invention relates to the technical field of logistics warehouse storage equipment, in particular to a speed reduction control method for a high-speed motor driven hydraulic system, which comprises the following steps: S1, the output torque of a high-speed motor is transmitted to a gear pump through a motor shaft, a planetary reducer and a planet carrier in sequence to drive the gear pump to work; s2, acquiring a three-phase current instantaneous signal and a direct current bus voltage signal, and performing preprocessing and frequency spectrum conversion to determine a current frequency spectrum; s3, in the current frequency spectrum, extracting an energy value in a preset frequency band with the meshing frequency and harmonic waves of the planetary gear as the center, and calculating to obtain a disturbance characterization value of the planetary gear; s4, determining a torque smooth adjustment coefficient according to the planet wheel disturbance characterization value; and S5, dynamically adjusting a dynamic response parameter of a torque control ring of the high-speed motor according to the torque smooth adjustment coefficient. The problems that in the prior art, a high-rotating-speed motor and a hydraulic pump are not matched in rotating speed, and mechanical disturbance is difficult to restrain are solved.

The invention relates to a heterogeneous insulation interface parameter testing method and device based on broad-spectrum photoelectric emission, and the method comprises the steps: applying metal electrodes with different work functions to to-be-tested samples of two single-layer materials forming heterogeneous insulation, and obtaining a single-layer material photoelectric emission current spectrum; analyzing the photoelectric emission current spectrums of the single-layer materials to obtain parameters of the two single-layer materials forming heterogeneous insulation; applying metal electrodes with different work functions to a heterogeneous insulation composite sample formed by tightly attaching two single-layer materials forming heterogeneous insulation to obtain a total photoelectric emission current spectrum of the heterogeneous insulation composite sample; separating according to the total photoelectric emission current spectrum of the heterogeneous insulation composite sample to obtain an intermediate interface photoelectric emission current spectrum; and analyzing the photoelectric emission current spectrum of the intermediate interface, and calculating to obtain a real contact potential barrier between the two single-layer materials forming the heterogeneous insulation. Compared with the prior art, high-precision measurement of heterogeneous insulation interface parameters is realized.

The invention discloses a household electrical appliance fault diagnosis system based on artificial intelligence, and relates to the technical field of household electrical appliance fault diagnosis and state monitoring. Working condition parameters aligned with a time window are obtained through working condition sensing, and fault features and the working condition parameters are linked in an order form to be converted into a target frequency track; fault characterization is converted into track characterization capable of being continuously tracked along with working conditions from a fixed frequency point, and disturbance to fault positioning in the speed change process is reduced; in order to solve the problem that weak fault components are covered by the same frequency band due to strong dynamic background noise jointly formed by inverter switch harmonic waves, current harmonic waves and load fluctuation, a dynamic noise reference spectrum is output under the current working condition through a condition generation model, and a current spectrum and the dynamic noise reference spectrum form a residual spectrum; the background spectrum base related to the working condition is suppressed, and the separability of the weak fault component in the residual domain is improved from the source.

The invention discloses a motor state monitoring method and device based on a multi-modal sensor, and the method comprises the steps: firstly, carrying out the comprehensive analysis of the current and rotating speed data of a motor, and explicitly constructing a working condition vector which can accurately represent the current load and rotating speed state of the motor; then, self-adaptive adjustment and reconstruction are carried out on original vibration frequency spectrum features and current frequency spectrum features through modes such as an attention mechanism by taking a working condition vector as guidance, so that feature components introduced by working condition changes are stripped, and pure features which are highly related to a fault state and basically irrelevant to a working condition state are extracted; and furthermore, the decoupled pure features are fused to effectively excavate the complementary relationship between vibration and current information, and finally, accurate fault diagnosis is realized. In this way, the accuracy and reliability of motor state monitoring are improved.

The invention discloses a multi-channel LED spectrum adjusting method and system. The method comprises the steps that a light source containing three LED channels is configured; wherein the first LED channel light source outputs short-wave purple light of 400-430 nm, and a purple light chip packaged by packaging glue containing first fluorescent powder is adopted; the second LED channel light source outputs full-wave-band white light of 400-700 nm, and a purple light chip packaged by packaging glue containing second fluorescent powder is adopted; the third LED channel light source outputs long-wave red light of 700-780 nm, and a blue light chip packaged by packaging glue containing third fluorescent powder is adopted; collecting spectral data of a target area through a four-node cross-distributed spectral sensor to obtain a current spectrum; determining a deviation value between the current spectrum and a preset template; and dynamically adjusting the three LED channel light sources according to the deviation value. The radiation intensity of short-wave purple light and long-wave red light can be remarkably improved, the color rendering index is optimized, and the high-precision illumination requirement is met.

The invention relates to the field of fault analysis, and discloses an electrical equipment fault analysis method and system based on big data. The method comprises the following steps: extracting a starting current spectrum and a steady-state current spectrum in a non-salt-fog environment from a historical library, and training corresponding fault diagnosis models by using a one-dimensional convolutional neural network and a two-dimensional convolutional neural network respectively; the method comprises the following steps: acquiring a real-time starting current frequency spectrum, environmental parameters, equipment operation duration, salt mist corrosion characteristic parameters and conductive ion conductivity parameters, compensating the real-time starting current frequency spectrum, eliminating pseudo harmonic peaks and baseline offset distortion caused by corrosion of copper ions by salt mist and corrosion products thereof, and obtaining a compensated starting current frequency spectrum; in the starting stage, the fault probability weight is identified through full-frequency scanning, and FPGA resources are dynamically allocated; and acquiring a steady-state frequency spectrum for fault detection in an operation stage. According to the method, the influence caused by the salt mist environment is eliminated, the fault misjudgment rate is reduced, and the resource occupancy rate is reduced.

The application discloses an electromagnetic detection optimized bipolar SHMPWM transmitting method, which comprises the following steps: S1, by analyzing the influence of the resistive and inductive load on the transmitting current waveform distortion and the transmitting spectrum energy loss, extending the current waveform based on the equal-area principle, compensating for the lost transmitting current spectrum energy, and calculating the current waveform extension time; S2, considering the inductive load and the dead zone effect, establishing a bipolar SHMPWM nonlinear equation set; S3, using the particle swarm algorithm to iteratively operate the bipolar SHMPWM nonlinear equation set, and obtaining the solving result of the switching angle of the half-cycle symmetric SHMPWM. The application adopts the optimized particle swarm algorithm to solve the equation set to obtain the switching angle, and realizes that the frequency domain information of the half-cycle symmetric SHMPWM frequency focusing waveform conforms to the specific harmonic amplitude set by the expectation.

This application discloses a threshold adjustment method, apparatus, device, and medium based on partial discharge data, relating to the field of partial discharge detection technology. The method includes: acquiring the current spectrum type; setting a first adjustment threshold based on the current spectrum type; acquiring effective pulse data and the corresponding number of phase windows based on the first adjustment threshold; calculating the phase window ratio based on the number of phase windows corresponding to the data; if the phase window ratio exceeds a first ratio threshold, clustering the data to obtain a DBI index; if the DBI index is less than a first index and the number of cluster centers is less than or equal to the first threshold, performing an FFT transformation on the data to obtain the frequency point with the highest energy and calculating the energy ratio of that frequency point; if the energy of that frequency point is not within a first range and the energy ratio is less than or equal to a second ratio threshold, adjusting the first adjustment threshold to obtain a second adjustment threshold. This method effectively improves the detection accuracy of partial discharge data.

The present application relates to the technical field of precision manufacturing and numerical control machine tool, and more particularly to a kind of electric spindle thermal-mechanical double hysteresis coupling parameter prediction method.The steps are as follows:S1: collect multi-dimensional operating state signal and process;S2: the vibration time-frequency feature map, current spectrum and temperature gray image after processing are channel superimposed, and three-dimensional feature tensor is formed;S3: construct ResNet-Attention electric spindle thermal-mechanical double hysteresis coupling parameter time series prediction model, input fusion feature vector into trained prediction model, and obtain the optimal thermal-mechanical double hysteresis parameter time series prediction model;S4: the thermal-mechanical double hysteresis parameter time series prediction model is dynamically simulated to obtain predicted value.The electric spindle thermal-mechanical double hysteresis coupling parameter prediction method provided by the present application, by fusing multi-source heterogeneous data, fully excavates the internal relation and complementary information between different data sources, effectively improves the prediction accuracy of the model on electric spindle thermal-mechanical double hysteresis coupling parameter.

The invention discloses a cable tunnel flat spectrum detector, a crack measuring method and a storage medium, and relates to the technical field of tunnel cracks, and the cable tunnel flat spectrum detector comprises a flat spectrum detection module, a signal processing module, a data storage module, a data comparison and analysis module and a display. A plurality of standard crack test pieces with different crack depths or lengths and frequency spectrum characteristic information of crack-free standard test pieces are pre-stored in the data storage module; the signal processing module compares the reference spectrum of the crack-free standard test piece with the spectrum detected by the flat spectrum detection module, screens out a newly added characteristic peak and a frequency deviation peak as characteristic peaks to be detected, and calculates spectrum characteristic information; and the data comparison and analysis module is used for matching the current spectrum characteristic information with the spectrum characteristic information of the standard crack test piece in the crack parameter database to obtain crack parameters. Traditional cable tunnel detection depends on local ultrasonic flaw detection, hysteresis exists, and early-stage tiny cracks are difficult to find; in order to overcome the hysteresis, cracks are found in a full-time monitoring mode through a flat spectrum detection module.

The application provides a rotor eccentric fault diagnosis method and device based on MCU and a vehicle, and the method comprises the following steps: in response to a control instruction, a motor is controlled to operate at a constant rotating speed; a rotating speed signal of the motor is acquired through a position sensor; a rotating speed ripple is extracted according to the rotating speed signal of the motor; a rotating speed ripple amplitude is calculated based on the rotating speed ripple; a rotor eccentricity is acquired according to the rotating speed ripple amplitude; and a diagnosis result is obtained according to the rotor eccentricity. The method can solve the problem that the rotor eccentric fault diagnosis methods commonly used at present, such as current spectrum analysis and back electromotive force analysis, are difficult to apply to the new energy vehicle electric drive system of the embedded permanent magnet synchronous motor using a distributed winding, can effectively diagnose the rotor eccentric fault in real time, and can be directly applied in the vehicle system without additional offline calculation, and is more convenient and fast.

This invention discloses a method and system for offset detection in a wireless power transfer system based on deep learning, comprising the following steps: Step 1: When the output current of the wireless power transfer system is abnormal, the output current on the load is collected; Step 2: The spatiotemporal features of the output current spectrum are extracted and normalized to obtain time-frequency information; Step 3: The time-frequency information obtained in Step 2 is input into the offset detection model to obtain the current offset detection result of the wireless power transfer system; the offset detection result is: the abnormal output current is caused by the offset between the receiving coil and the transmitting coil, or the abnormal output current is not caused by the offset between the receiving coil and the transmitting coil; Step 4: The input voltage is adjusted according to the current offset detection result of the wireless power transfer system.

This invention discloses a multi-agent cooperative anti-interference method based on spectrum data aggregation. First, a multi-agent cooperative anti-interference model based on spectrum data aggregation is established. Second, a joint action is selected based on a greedy strategy. Third, the joint action is executed to obtain a reward, the current spectrum is perceived, the state transitions to the next state, and the experience is stored in the agent's experience pool. Then, random batch sampling is performed from the experience pool, the target Q-value is calculated, the gradient of the loss function is calculated, and the weight values ​​are trained and updated. The algorithm terminates when the maximum number of iterations is reached. This invention features a complete model with clear physical meaning, avoids malicious interference and mutual interference between users, significantly improves the anti-interference performance of ultra-dense networks with incomplete perceptual information, and provides a fairer frequency usage strategy.

The invention discloses an electric power inspection multi-mode large model fine tuning method and device, and the method comprises the steps: carrying out the time series data spectrum preprocessing of a one-dimensional current signal through a Grubrum angle field algorithm, and obtaining a two-dimensional current spectrum; combining the visible light / infrared image and the diagnosis text to construct an instruction fine tuning data set; on the basis of the universal multi-modal backbone model, designing a 1 + N LoRA fine tuning framework comprising a current map encoder and an electrical semantic optimization LoRA module, and obtaining an adjusted model; respectively outputting preliminary diagnosis probability vectors through the visual branch and the current expert branch, and calculating the cosine similarity of the two preliminary diagnosis probability vectors; if the cosine similarity is lower than a preset threshold value or the physical paradox exists, triggering reflection logic; and adjusting the weight of the electrical semantic optimization LoRA module, recalculating a feature fusion result, and outputting a final diagnosis conclusion. The method solves the problems that in the prior art, single-mode sensing is limited, and diagnosis precision is insufficient due to environmental interference.

The application relates to a method for improving the reliability of double-winding motor control based on current spectrum sensing, and the control steps are as follows: a) a main controller receives instructions from a host computer through a bus, controls a main winding, a slave controller receives instructions from the bus, controls a slave winding, and the slave controller receives a main winding current feedback signal; b) the slave controller performs fast Fourier transform (FFT) on the main winding current feedback signal, extracts a fundamental wave, a third harmonic, a fifth harmonic and an even harmonic of the current, judges the running state of the main controller through real-time analysis of the current harmonic in the main winding current feedback signal, and when the current harmonic in the main winding current feedback signal is abnormal and no start instruction is obtained within a set time, the slave controller autonomously starts and controls the slave winding. The method can accurately and timely sense the abnormal condition of the high-voltage side, avoids false detection and missed detection, and greatly improves the reliability of double-winding operation.

This application discloses a controller heat dissipation interface compensation control method, device, and system, belonging to the field of heat dissipation control technology for servo motors. The method includes: acquiring the trigger signal of the acceleration detection unit; resolving the target interface pressure based on the thermal management target of the power device, and calculating the fundamental amplitude and frequency of the disturbance current; sampling, conditioning, and denoising the bus current, and extracting the dynamic fluctuation component to calculate the pressure coefficient; when the pressure coefficient is less than a preset separation threshold, calculating the disturbance amplitude correction based on a model reference adaptive control algorithm, adding it to the fundamental amplitude of the disturbance current; when the energy of the current spectrum exceeds a preset energy threshold within the first offset frequency range of the structural fundamental frequency, superimposing the second offset frequency onto the fundamental frequency, generating a disturbance current signal, and superimposing it onto the motor's current control signal. This method can quickly compensate for interface contact pressure and transiently suppress the rise in target interface thermal resistance.

This invention discloses a method, system, medium, and device for detecting DC arc faults in photovoltaic systems. The method includes: acquiring current data for each time window in the transmission circuit of the photovoltaic system; performing current spectrum calculation to obtain the corresponding current spectrum vector; calculating the edit distance between the real number sequence of the current time window and the real number sequence of a reference time window according to a set characteristic frequency band, obtaining a distance calculation result; setting a threshold and comparing the distance calculation result with the threshold: if the distance calculation result is greater than the threshold, the current time window is marked as a fault time window; otherwise, it is marked as a normal time window; within N consecutive time windows, if the cumulative number of fault time windows reaches a set number M, a DC arc fault is detected. This invention enables accurate and reliable detection of arc faults in photovoltaic systems.

The invention discloses a 5G CPE dynamic spectrum allocation method and system, and relates to the technical field of spectrum allocation, and the method comprises the steps: taking CPE as a spectrum decision main body, and collecting a multi-source state data set associated with the current spectrum use in a preset time window; constructing a frequency spectrum instantaneous state vector representing the operation situation; inputting the frequency spectrum instantaneous state vector into a frequency spectrum state evolution driving model, and executing state evolution direction and evolution strength analysis; constructing a frequency spectrum state feasible evolution domain in an allowable evolution range; and performing CPE dynamic spectrum allocation management according to the optimal spectrum state transition path. The technical problems of insufficient 5G dynamic spectrum allocation adaptability and low operation reliability in the prior art are solved, and the technical effects of accurately screening the optimal spectrum migration path by taking the CPE as a decision subject and improving the 5G dynamic spectrum allocation adaptability and reliability are achieved.

A signal transmitting system, a signal processing system and methods thereof are disclosed. A frequency dependent dynamic range control method is used in a signal transmitting system having a lower impedance in a high frequency region, whereby a current spectrum and a regulation parameter are dynamically estimated to reduce the current in the high frequency region. This method advantageously avoids current overload without using a series resistor as a current limiter.

The application relates to the technical field of industrial automation control and system state monitoring, and discloses a performance evaluation method and system of an industrial internet connector, which comprises the following steps: the method uses the common-mode noise generated in the power supply loop of the device itself as a diagnostic probe in reverse, establishes the intrinsic harmonic spectrum series relationship representing the stability of the noise source itself when establishing the initial frequency spectrum fingerprint baseline, and in the subsequent periodic evaluation, firstly, the spectrum series relationship is pre-checked, and then, based on the drift index of the current frequency spectrum fingerprint relative to the baseline and the change slope in the continuous time window, the performance evolution of the connector is evaluated. The application shifts the focus of evaluation from the apparent correctness of data transmission to the gradual change trend of the physical structure of the bearing connection, and can identify that the irreversible physical state degradation process of the connector is occurring.

The application provides a three-phase inverter DC side leakage fault type discrimination method and electronic equipment, the application carries out frequency spectrum time sequence characteristic analysis on the residual current of the three-phase inverter AC side, further analyzes the change of the residual current amplitude with time under different frequencies, and can understand the fault type of the inverter DC side leakage; through continuous energy monitoring of the residual current signal of the inverter, real-time current monitoring of the inverter is realized, and the sudden change of the leakage fault type or the instantaneous leakage can also be well monitored and discriminated. The application is aimed at the specific characteristics of the inverter leakage current harmonic component, the leakage current spectrum characteristics are different under different fault types, on the basis, the leakage fault type discrimination method based on the harmonic time-frequency feature extraction is proposed, the specific fault type of the inverter can be discriminated under various working conditions, and then the leakage fault position is located, and the problem that the leakage fault type discrimination and positioning are inaccurate in current engineering application is solved.

The present application relates to a kind of laser automatic frequency locking methods based on similarity recognition spectrum, comprising: S1, digital PID feedback controller is to laser output sweep voltage;S2, obtain the spectrum signal of laser output under current sweep voltage;S3, whether there is target spectrum in current spectrum signal based on similarity recognition algorithm is determined, if exists, execute step S4;If target spectrum is not identified, adjust sweep voltage and return to execute step S1;S4, based on the locking point of similarity coefficient peak position determination current characteristic spectrum;S5, after obtaining locking point, based on the frequency locking parameter of locking point determination current characteristic spectrum, control digital PID feedback controller is based on the control amount of the frequency locking parameter and carries out PID control locking.This method can achieve the finding of various spectral characteristic peaks and locking point, wide applicability, small environmental interference and method recognition efficiency is high.

The invention discloses a workpiece quality online analysis and production decision optimization model, and belongs to the field of industrial production management, and the model comprises a spectrum generation module which is used for generating a one-dimensional process energy density spectrum on line, and the process energy density spectrum is formed by dynamically distributing weights for a plurality of process control variables and carrying out nonlinear superposition; the factor construction module is used for calculating a stable factor of each production takt point based on the process energy density spectrum so as to construct a takt characteristic field; the stability factor is determined according to the deviation degree of the current spectrum value relative to the target reference, the spectrum value change gradient of the adjacent beat points and the state logic values of the downstream buffer area and the downstream process; and the instruction splitting module is used for splitting the optimization decision instruction into a plurality of decision quantum packets. Accurate adaptation of the decision instruction and the production takt and dynamic resource allocation can be achieved, resource waste caused by a traditional fixed process is avoided, the utilization efficiency of production resources such as equipment and materials is improved, the production cost is reduced, and the flexibility of production management and control is enhanced.

The invention discloses a communication strategy determination method, a nonvolatile storage medium and electronic equipment. The present invention relates to the technical field of communications, and the method comprises: detecting that there is an interference signal in a current spectrum resource, the current spectrum resource being a spectrum resource for transmitting target data between a current terminal device and a base station; determining the interference type of the interference signal; a communication strategy is determined based on the interference type, the communication strategy comprises an interference avoidance strategy and / or an interference suppression strategy, the interference avoidance strategy indicates that new spectrum resources are selected for transmission of target data, and the interference suppression strategy indicates that subcarriers with interference signals in the current spectrum resources are suppressed. The invention solves the technical problem that the influence of malicious interference signals in wireless communication on the data transmission quality and efficiency cannot be effectively suppressed in the related technology.

The invention provides a spectrum fitting method, which comprises the following steps of: firstly, acquiring a target spectrum chart containing a corresponding relationship between wavelength and radiation power, identifying a target maximum peak wavelength in the target spectrum chart, and selecting a matched chip model from a preset chip data table; identifying a target secondary peak wavelength, and selecting one-to-one corresponding fluorescent powder models from the fluorescent powder data table; then, synthesizing a current spectrogram according to spectrogram data of the chip and the fluorescent powder model, and comparing optical parameters of the current spectrogram with optical parameters of a target spectrogram; if yes, trial matching succeeds; and if not, adjusting the weight of the fluorescent powder model according to a preset rule, and re-synthesizing and comparing. Compared with a traditional mode of relying on artificial experience judgment and repeated physical matching tests, the method has the advantages that the lengthy adaptation period is avoided, the material consumption is reduced, the adaptation cost is reduced, and the product research and development iteration efficiency is improved.

The invention provides an IPWL current spectrum-based power distribution network target impedance evaluation method and system, a product and a terminal, and the method comprises the steps: obtaining a maximum allowable voltage fluctuation threshold and a piecewise linear current waveform of a target chip, and determining the current spectrum distribution of the target chip at different frequencies based on the piecewise linear current waveform; obtaining a target impedance curve of a power supply distribution network for supplying power to the target chip through the maximum allowable voltage fluctuation threshold value and the current spectrum distribution; the method comprises the following steps: constructing a power distribution network simulation model of a target chip, and obtaining an actual impedance curve through frequency domain simulation; and comparing the target impedance curve with the actual impedance curve frequency point by frequency point, and judging whether the power distribution network meets the design requirement or not. Compared with a traditional flat impedance design method, the method achieves the conversion from static constraint to dynamic matching, reduces the redundant design, remarkably improves the design resource utilization efficiency of the power distribution network, and reduces the design cost.

The invention discloses a wafer bonding light source control method, a wafer bonding device and a computer readable storage medium, and relates to the technical field of wafer manufacturing, a target spectrum value and a current spectrum value are compared, a spectrum difference value is obtained, a spectrum threshold value is obtained, under the condition that the spectrum difference value is larger than the spectrum threshold value, a driving part is controlled to drive an optical filter rotating wheel, and the optical filter rotating wheel is driven to rotate. The current spectral value is adjusted by switching the area of the illumination light filtered by the optical filter on the optical filter rotating wheel, and the spectral difference value is made to be smaller than or equal to the spectral threshold value. According to the arrangement, the optical filter can be adjusted, so that the problem of drifting of a central wave band is effectively inhibited, and the spectrum of illumination light irradiated to the wafer to be detected is always kept stable and is highly matched with the process requirement. Therefore, the quality of the acquired mark image can be guaranteed to reach the standard, a reliable basis is provided for accurate identification and positioning of a visual system, the consistency of wafer detection of the same batch is improved, and the process precision and alignment accuracy of wafer bonding are further effectively improved.

This application discloses an automatic laser phase modulation spectrum screening method, apparatus, device, medium, and product, relating to the laser field. The method includes: acquiring the return light values ​​of an initial spectrum under different laser drive currents; selecting the drive current corresponding to the return light values ​​showing differences among the return light values ​​of different initial spectra as a set current value; changing the initial spectrum and reading the return light value under the current spectrum; the return light value under the current spectrum is obtained by applying the drive current to the set current value; selecting the spectrum with return light values ​​below a first set threshold as the preliminary screening result; selecting the preliminary screening result corresponding to the highest drive current value in the self-pulsation phenomenon as the optimal spectrum; the drive current value of the laser drive current increases from the set current value until the self-pulsation phenomenon of the spectrum in the preliminary screening result appears. This application can reduce the laser output power and screening time for spectrum screening.

The application discloses a zero-crossing breaking control method and system based on arc energy transfer prediction and application in ring network cabinet, and relates to the technical field of zero-crossing breaking. Current data and burning images caused by arc energy due to the decay of current data over time are collected. Through Fourier transform, the current data is converted into a current spectrum diagram, which can more accurately reflect the information of the current. Then, a convolutional neural network is used to detect the state of current change. Using an associative neural network, the burning condition of the surface of the contact is combined with the current data, and association and fusion are performed to obtain an arc correlation feature vector. The change of the arc correlation feature vector at multiple time points can more accurately predict the zero-crossing point.

The invention discloses a high-frequency loss characteristic characterization method of a non-closed magnetic core. The method comprises the following steps: constructing a test unit; the test unit comprises an inductor arranged around the non-closed magnetic core; under the condition of high-frequency large signals enabling the non-closed magnetic core to enter a nonlinear working state, a test unit is used for collecting and preprocessing voltage signals and current signals at the two ends of the non-closed magnetic core; performing Fourier transform on the preprocessed voltage signal and current signal to generate voltage frequency spectrum information and current frequency spectrum information; calibrating the parasitic parameters of the test unit and the time delay of the system; calculating inductor coil winding loss parameters; acquiring impedance parameters, inductance parameters and resistance parameters of the inductor at different frequency points according to the ratio of the voltage spectrum information to the current spectrum information; and performing fitting operation and analysis on the impedance parameter, the inductance parameter and the resistance parameter to generate a magnetic core loss characteristic curve under the high-frequency large-signal condition for enabling the non-closed magnetic core to enter a nonlinear working state.