549 results about "Impedance spectrum" patented technology

The invention discloses a lithium ion battery internal short circuit fault detection method based on time-frequency fusion, and the method comprises the steps: firstly constructing a fractional order equivalent circuit model fused with an electrochemical aging mechanism, and simulating the paths of conductivity reduction, active material loss and lithium inventory reduction in combination with an aging empirical formula; joint modeling of the aging process and the random internal short circuit is achieved, and multi-cycle voltage and current and electrochemical impedance spectroscopy data are obtained; secondly, extracting time domain features by using a time domain attention enhanced long-short-term memory network, and analyzing frequency domain information by using a multi-scale frequency sensing convolutional neural network; and then weighting and screening two types of modal features through a dynamic gating fusion module, introducing a cross attention mechanism to establish dependency mapping between time-frequency domain features, and finally outputting an internal short circuit fault detection result. The method can solve the problems that in the lithium ion battery aging process, due to lithium dendrite growth, the internal short circuit early fault is high in concealment, and single time-frequency characteristics are difficult to detect, and early high-precision recognition of the internal short circuit fault can be achieved.

The invention provides a battery health state evaluation method, device and equipment and a medium, and the method comprises the steps: collecting multi-source parameters of a power battery in a charge-discharge cycle process, the multi-source parameters comprising voltage, current, temperature and electrochemical impedance spectroscopy; performing feature engineering processing on the multi-source parameters based on a battery aging mechanism, and extracting key feature parameters; the key characteristic parameters are input into a multi-physics field coupling model to simulate thermoelectric coupling behaviors of the battery under a dynamic load, lithium ion concentration distribution and temperature distribution in the battery are obtained, and the multi-physics field coupling model is used for representing a coupling relation between an electrochemical field and a thermal field of the battery; and fusing the key characteristic parameters with data output by the multi-physics field coupling model, and determining a health state evaluation result of the power battery. According to the invention, the accuracy of power battery health state evaluation is improved.

The invention belongs to the crossing field of artificial intelligence and process control, particularly relates to an intelligent coupling control strategy for chlorine production through seawater electrolysis based on digital twinning, and aims to solve the problems of response lag, weak disturbance suppression and lack of electrode aging early warning in a traditional control method. According to the strategy, a high-fidelity digital twin fusing electrochemistry, fluid and thermodynamics is constructed, characteristics of current, temperature, impedance spectroscopy and the like are collected and fused at high frequency through a multi-source sensor, a state space model driven by a deep recurrent neural network is established, and current efficiency and electrode aging coupling evolution recognition is achieved; when salinization or flow mutation is detected, the twinborn body predicts and dynamically calibrates the current density and the voltage set value in advance, and the safety process window is synchronously scaled. According to the strategy, the chlorine gas yield fluctuation is reduced by 60%, the energy consumption standard deviation is reduced by 45%, the fault early warning is advanced by 2-5 hours, the fault-free operation time of the system is prolonged by 50%, and high-precision, self-adaptive and preventive intelligent control of the electrolysis process is realized.

The invention relates to the technical field of lithium ion battery testing, and discloses a lithium ion battery life loss evaluation method and device, a medium and equipment, and the method comprises the following steps: S1, collecting multi-modal dynamic data of a lithium ion battery in a charge-discharge cycle process; s2, performing time-frequency domain conjoint analysis on the multi-modal dynamic data, and extracting a battery aging sensitive feature set; s3, constructing a multi-scale coupling model of battery life loss; by constructing a multi-modal data fusion mechanism and a dynamic feature extraction system, during lithium ion battery life loss evaluation, change trends of electrochemical impedance spectroscopy and heat distribution key parameters are captured in real time based on time-frequency domain conjoint analysis, sensor signal distortion and drift problems can be identified, the extraction precision of aging sensitive features is improved, and the accuracy of lithium ion battery life loss evaluation is improved. The problem of characteristic errors caused by signal interference in traditional evaluation is solved, and the accuracy and reliability of life loss evaluation are ensured.

The invention discloses an online EIS battery pack performance parameter estimation algorithm, and relates to the technical field of battery management, and the algorithm comprises the steps: generating a basic frequency conversion excitation signal through a digital signal generator, and loading the basic frequency conversion excitation signal to a working battery pack through a self-adaptive frequency sweeping strategy; acquiring a response signal, analyzing an impedance real part and an imaginary part of the battery pack at each frequency point through a digital orthogonal synchronous demodulation technology, and constructing an electrochemical impedance spectrum; extracting multi-dimensional health features from the electrochemical impedance spectrum, inputting the multi-dimensional health features into a fusion deep learning model, and estimating the state of charge and the state of health of the battery; and generating a system optimal control signal based on the estimated state of charge and state of health. According to the algorithm, portable, online and real-time detection of the performance parameters of the battery system in the working state is realized, and the application scene limitation of traditional EIS equipment is broken through; and through the optimized signal processing and intelligent algorithm, the detection stability and response speed are improved.

The invention relates to the technical field of aircraft part processing, testing or inspection and the like, and provides an aircraft aluminum alloy plate aging evaluation method based on an equivalent circuit model, and the method comprises the following steps: collecting electrochemical impedance spectrums of samples with different exposure age limits, and extracting electrochemical impedance spectrum characteristics of the samples; establishing an equivalent circuit model comprising solution resistance, coating resistance, coating capacitance, Warburg impedance, anodic oxide film charge transfer resistance, interface capacitance, aluminum alloy matrix charge transfer resistance, interface electric double-layer capacitance, inductance and corresponding resistance of the inductance based on the characteristics, wherein the equivalent circuit model comprises the solution resistance, the coating resistance, the coating capacitance, the Warburg impedance, the anodic oxide film charge transfer resistance, the interface capacitance, the aluminum alloy matrix charge transfer resistance and the interface electric double-layer capacitance; and analyzing a resistance curve and a capacitance curve obtained by fitting the model to complete the evaluation of the corrosion and aging degree. According to the method, systematicness and accuracy of aging evaluation are improved, an electrochemical mechanism in the corrosion process can be disclosed, time correlation modeling of the aging process can be achieved, and the method is suitable for long-term service performance monitoring and service life prediction of the aviation aluminum alloy structure.

The invention discloses a power cable insulation state evaluation method and system based on a broadband impedance spectrum, relates to the technical field of cable insulation, and is used for solving the problem that a defect grading result deviates from a real aging process of a cable. The method comprises the following steps: extracting broadband reflection data, calling a corresponding insulation aging type, converting a phase sequence in the broadband reflection data into a phase deviation coefficient for region screening, extracting a reflection peak value based on a reflection coefficient amplitude sequence, calling a corresponding impedance variation reference according to the insulation aging type, and performing region screening. The method comprises the following steps: generating impedance variation characteristics in combination with a reflection coefficient peak value, judging whether a defect grading mechanism is entered, detecting discharge pulse count and insulation recovery time of a marked division region, generating marked division defect grades according to a detection result, and distinguishing impedance variation modes corresponding to different aging forms in judgment. And the defect grading result better conforms to the actual aging process of the cable.

The invention provides an intelligent battery sorting method integrating impedance characteristics and deep learning. The method comprises the following steps: acquiring battery impedance data through an electrochemical workstation, drawing an electrochemical impedance spectroscopy (EIS), and extracting impedance characteristics of a medium-frequency region; a 25-dimensional impedance coupling feature space is innovatively constructed, a dual-network differentiated feature selection strategy (IC-GRU) is adopted, a main network selects 12 features with the highest correlation, a boundary expert network selects 10 features with the highest correlation and additionally constructs 5 boundary sensitive features, and finally, the main network selects 12 features with the highest correlation. And establishing an impedance coupling sensing gating circulation unit network to realize accurate prediction of the state of health (SOH). And performing four-stage sorting on the SOH result predicted by the IC-GRU through a random forest algorithm (RF). According to the method, more accurate SOH prediction is realized through deep learning guided by a physical mechanism, the battery pack health state sorting precision and consistency are improved, and an intelligent solution is provided for new energy automobile battery life management.

The invention discloses a lithium battery solid electrolyte interface film forming quality evaluation method. The method comprises the following steps: in a lithium battery formation stage or a circulation process, applying an alternating current disturbance signal with an amplitude of 1-20mV, and collecting full-band electrochemical impedance spectroscopy data in real time; a relaxation time distribution method is adopted to decouple the electrochemical impedance spectrum of the intermediate frequency region; constructing an equivalent circuit model containing SEI film characteristics, and fitting the decoupled electrochemical impedance spectrum curve by the equivalent circuit model; the compactness index of the SEI film is calculated according to the SEI film resistance and the film capacitance, and whether the compactness of the SEI film reaches the standard or not is judged according to the compactness index; and calculating a lithium ion diffusion coefficient by combining the charge transfer resistance and the Warburg diffusion impedance, and evaluating the SEI membrane ion transmission efficiency. According to the invention, non-destructive monitoring is supported, quantitative evaluation of SEI membrane compactness, ionic conductivity and short circuit faults in the module can be realized, and the cycle life and safety of the lithium battery are improved.

The invention specifically relates to a standardized fuse fault monitoring and diagnosis system, and relates to the technical field of power system protection equipment monitoring. A signal processing and impedance spectrum calculation module; an intelligent diagnosis and state evaluation module; and a benchmark management and personalized tracking module. According to the invention, controllable micro test signals are actively injected to obtain frequency domain impedance fingerprints, and accurate capture of microscopic degradation is realized; non-intrusive coupling and signal injection are adopted, the topology of a main loop does not need to be changed, the inherent protection characteristic of the fuse is guaranteed, and power frequency interference can be penetrated; the recognition amount of budding faults such as contact oxidation and melt corrosion is improved in advance, and power failure accidents caused by fault expansion are avoided.

The invention provides a new energy station grid-connected oscillation risk assessment method and device, and relates to the field of new energy grid-connected control. The method comprises the following steps: constructing a dynamic equivalent model based on new energy station operation parameters; based on the dynamic equivalent model, obtaining impedance spectrum feature domains in different control modes; calibrating an impedance spectrum feature domain based on a semi-physical simulation platform; inputting the calibrated impedance spectrum feature domain into a grid-connected oscillation risk assessment model, and outputting oscillation damping ratio predicted values of the new energy station in different control modes based on the grid-connected oscillation risk assessment model; and constructing a self-adaptive threshold, and evaluating the grid-connected oscillation risk of the new energy station based on the magnitude relationship between the oscillation damping ratio predicted value and the self-adaptive threshold in different control modes. The method solves the problems that when different control modes are switched or external operation conditions are changed, a prediction result of a traditional method is prone to distortion, and the real oscillation risk of the new energy station is difficult to reflect accurately.

The invention discloses a single-hole pressure adjusting method, device and equipment for a water curtain test of an underground water-sealed cave depot and a storage medium, and relates to the technical field of geological engineering.The method comprises the steps that firstly, a rock mass acoustic impedance spectrum is collected, intrinsic mode decomposition is carried out to extract geologic feature components, and the rock mass acoustic impedance spectrum is obtained; processing the target pressure value, the current pressure value and the geologic feature component by using a pressure-opening coupling model based on acoustic feature extraction, time sequence dynamic analysis and physical constraint decoding to obtain a reference valve opening; then, a water curtain hole valve is adjusted according to the reference valve opening degree, and the pressure change acceleration is monitored in real time; calculating an opening compensation increment and a damping attenuation coefficient based on the pressure change acceleration, and further generating a target valve opening; and finally, the valve is adjusted to the target opening degree, so that the water curtain hole reaches the target pressure value. According to the invention, high-precision self-adaptive adjustment of the pressure of a single water curtain hole can be realized in the water curtain test of the underground water-sealed cave depot.

The invention belongs to the technical field of energy storage system state monitoring, and provides a lithium ion energy storage system abnormal state identification method and system based on impedance spectrum analysis, and the method comprises the steps: carrying out the decoupling of voltage response data and current response data through employing an excitation-response decoupling algorithm under a dynamic working condition, and obtaining an impedance spectrum; obtaining a voltage response component and a current response component; obtaining the total impedance spectrum of the lithium ion energy storage system under the current working condition; constructing a system-level impedance cloud picture; calculating a difference value between the current impedance spectrum and the weighted moving average baseline spectrum based on the system-level impedance cloud atlas to obtain an enhanced difference cloud atlas; and performing non-uniform segmentation and feature extraction on the enhanced difference cloud picture by using a visual Transform model oriented to electrochemical prior to obtain a multi-dimensional abnormal probability vector, and obtaining an abnormal state type of the lithium ion energy storage system based on the multi-dimensional abnormal probability vector. According to the technical scheme, the accuracy, timeliness and reliability of abnormal state recognition of the energy storage system are remarkably improved.

The invention relates to the field of chip detection, and discloses a high-efficiency chip detection system and method, which are used for realizing long-term performance degradation detection of a chip. Comprising the following steps: synchronously acquiring power pin electric signals and chip surface thermal imaging data to generate an electrothermal coupling characteristic data set in a working state of a to-be-tested chip, and extracting impedance and heat conduction characteristic parameters through impedance spectroscopy analysis and thermal time constant calculation. And analyzing an internal signal transmission path based on impedance characteristic parameters to obtain path characteristic parameters, establishing a mathematical model of dynamic current and working voltage of the chip by combining the two, generating a system identification result, and finally generating a chip detection result and fault positioning information by integrating various parameters. According to the invention, system benchmark testing and environmental interference monitoring and compensation are carried out, and high precision and high robustness of a detection result are realized.

The invention relates to the technical field of electrochemical water treatment, and discloses a high-salt waste liquid electric flocculation hardness removal and electrodialysis resourceful treatment method and a high-salt waste liquid electric flocculation hardness removal and electrodialysis resourceful treatment system. The method comprises the following steps: collecting water quality parameters of the high-salt waste liquid and initial electrochemical impedance spectroscopy parameters of a polar plate; calculating the initial current density according to the hardness and the conductivity, carrying out electric flocculation treatment, monitoring impedance spectrum change in real time, identifying the scaling type, and predicting the residual operation time of the polar plate; the current density is optimized according to the prediction time, and the residual hardness is calculated; and adjusting electrodialysis parameters by taking the residual hardness as a feedforward signal for concentration, and performing bipolar membrane electrodialysis on the concentrated solution to obtain acid-alkali liquor. The problems that in the electrochemical treatment process of the high-salt waste liquid, the state of a polar plate cannot be monitored in real time, consequently, operation parameters are adjusted blindly, and energy consumption is high and the recycling efficiency is low due to the fact that parameters of a pretreatment unit and parameters of a pretreatment unit are not linked are solved.

The invention discloses a cable high-frequency impedance characteristic analysis method based on bipolar trapezoidal wave excitation, and belongs to the technical field of power equipment state monitoring and fault diagnosis. In order to solve the problems of low test efficiency, insufficient high-frequency parameter modeling precision and weak anti-interference capability in cable high-frequency impedance characteristic analysis of a traditional sine wave excitation method, the method comprises the following steps: generating an odd-symmetry bipolar trapezoidal wave excitation signal with specific frequency and amplitude, and injecting the signal into the head end of a cable to be tested through a coupling device after power amplification; synchronously acquiring a high-frequency response signal of the key position of the cable under the excitation of the bipolar trapezoidal wave by using a data acquisition system; preprocessing the high-frequency response signal, converting the high-frequency response signal into a frequency domain through Fourier transform, calculating input impedance of the cable under different harmonic frequencies, and synthesizing a broadband impedance spectrum; based on the broadband impedance spectrum, the amplitude-frequency characteristic and the phase-frequency characteristic of impedance are analyzed, and cable state evaluation, partial discharge detection, insulation defect diagnosis or fault point positioning are realized. The method is used for an electric power system.

The invention provides an intelligent dust remover control method and system based on electrostatic adsorption. The method comprises the following steps: acquiring dust concentration, temperature and humidity and particulate matter impedance spectrum data of a working environment, screening key measurement points, applying an alternating electric field to obtain an impedance phase difference map, performing frequency spectrum consistency verification on the impedance phase difference map and the impedance spectrum data after temperature and humidity compensation, and calculating conductivity discrimination parameters of dust with different particle sizes; deploying a parallel metal plate adsorption array containing an insulating dielectric layer, and adjusting the plate spacing to change the electric field intensity; generating a resistivity space distribution thermodynamic diagram based on the conductivity discrimination parameters, and cooperating with drive board spacing adjustment and voltage output according to the resistance gradient change of the insulation and conductive dust gathering area and the migration path; and a measurement point location screening strategy is updated in combination with the spacing adjustment amplitude and the voltage change rate, and the impedance spectrum precision is optimized. Precise identification of insulation and conductivity multi-mode dust and dynamic electric field self-adaptive adsorption are achieved, the dust removal efficiency of a complex environment is improved, and energy consumption is reduced.

The embodiment of the invention provides a photovoltaic power station fault rapid positioning method and system, and belongs to the technical field of electrical measurement and fault detection. The method comprises the following steps: acquiring electrical parameter data of each group string of a photovoltaic power station, performing normalization processing in combination with an environmental condition, generating baseline data, and screening suspicious group strings based on the baseline data; applying a preset power perturbation signal to the suspicious string and collecting corresponding voltage and current responses to form dynamic response data; determining impedance spectrum features based on the dynamic response data, extracting dynamic response fingerprints, and constructing feature vectors for representing the electrical state of the string; and comparing the feature vector with a health template, executing phase coupling analysis, generating a fault judgment result, and outputting corresponding string positioning information. According to the scheme of the invention, accurate identification and rapid positioning of the cascade fault of the photovoltaic power station group are realized, and high-robustness and high-confidence diagnosis effects can still be maintained under complex working conditions.

The invention belongs to the technical field of lithium ion batteries, and particularly relates to a preparation method of a silicon negative electrode composite SEI membrane based on electrochemical impedance spectroscopy in-situ regulation and control. Comprising the following steps: S1, constructing a battery system, and adding an electrochemical active organic precursor and a film-forming additive into an electrolyte; s2, in-situ monitoring: carrying out in-situ electrochemical impedance spectroscopy (EIS) scanning on the battery, and capturing the growth dynamic state of an SEI film in real time; s3, carrying out feature recognition, analyzing the EIS spectrogram in real time, and obtaining a moment when the RSEI growth rate RSEI / t has an inflection point or tends to be stable as an induction trigger point; s4, dynamic induction: applying an electrochemical induction signal of constant potential and high-frequency pulse to carry out dynamic induction; and S5, completing first circle formation to obtain the composite SEI film. The composite SEI film of the inorganic base layer and the organic flexible layer is constructed through combination of EIS real-time monitoring and dynamic induction, the problem that the SEI film is prone to cracking is effectively solved, intelligent and controllable preparation of the composite SEI film is achieved, the cycle life of a silicon negative electrode battery is prolonged, and the consistency of the silicon negative electrode battery is improved.

The invention discloses a method, a device and equipment for predicting a loss function of an electrochemical impedance spectroscopy, and a medium, and relates to the technical field of electrochemical analysis, and the method comprises the steps: obtaining the electrochemical impedance spectroscopy of a to-be-predicted material and all equivalent circuit models of the to-be-predicted material; and determining relative error parameters and spectrogram reconstruction parameters for each equivalent circuit model and the electrochemical impedance spectroscopy; determining a parameter relative error loss according to the relative error parameter, and determining a spectrogram reconstruction loss according to the spectrogram reconstruction parameter; the loss function of the to-be-predicted material is determined according to the parameter relative error loss and the spectrogram reconstruction loss, and the prediction accuracy of the loss function of the electrochemical impedance spectroscopy is improved.

The invention belongs to the technical field of energy storage batteries, and discloses an energy storage battery state evaluation method based on a generated impedance spectrum and a related device. The method comprises the following steps: acquiring impedance data of a to-be-evaluated energy storage battery; equivalent circuit fitting is carried out based on the impedance data of the energy storage battery to be evaluated, and equivalent element parameters are obtained; the correlation degree between the equivalent element parameters and the battery health state is calculated, and parameters with the correlation degree larger than a threshold value are selected as characteristic parameters; and inputting the characteristic parameters into a pre-established energy storage battery SOH evaluation model based on the generative impedance spectroscopy to obtain the health state of the energy storage battery to be evaluated. According to the invention, the test speed of the AC impedance spectroscopy and the interpretability of the evaluation model are considered; a full-spectrum alternating-current impedance spectrum is generated by using an adversarial neural network through a few points in different frequency ranges, so that the problems that full-spectrum testing time is long and engineering application is not facilitated are solved; and performing equivalent circuit analysis by using the generated full spectrum, and performing health state evaluation of the energy storage battery.

An electrochemical impedance spectroscopy prediction method of an echelon utilization battery comprises the following steps that an echelon utilization battery data set is collected and preprocessed, and the data set comprises charging curve data and electrochemical impedance spectroscopy data under the corresponding cycle index; generating charging voltage-time data according to the charging curve data; constructing an attention model for representing a mapping relationship between the charging voltage-time data and the electrochemical impedance spectroscopy data; the attention model comprises a bidirectional LSTM encoder and an LSTM decoder; the LSTM decoder comprises an attention module which introduces an aging factor weight matrix and is used for dynamically adjusting attention weights of different aging states according to the number of cycles; training an attention model by using the preprocessed echelon utilization battery data set; and predicting the electrochemical impedance spectrum of the echelon utilization battery by using the trained attention model. According to the method, efficient and accurate EIS prediction can be realized without traditional EIS test equipment, and support is provided for echelon battery screening, health monitoring and safety early warning.

The invention provides a decoupling analysis method of a battery medium-high frequency impedance spectroscopy and a battery health diagnosis method, and the decoupling analysis method comprises the steps: building a battery medium-high frequency RQ model, the battery medium-high frequency RQ model comprises at least one RQ link, each RQ link is used for representing an electrochemical process or a conduction characteristic of the battery in a middle-high frequency band in a decoupling manner, and comprises a CPE element and a resistor element which are connected in parallel; and carrying out RQ-DRT transformation on the medium-high frequency impedance spectrum of the battery by using the medium-high frequency RQ model of the battery, and solving to obtain at least one electrochemical process or a characteristic parameter corresponding to a conduction characteristic of the battery in a medium-high frequency band. According to the method used by the invention, the electrochemical process or the conduction characteristic of the high frequency band in the battery impedance spectrum can be quantitatively analyzed in a decoupling manner and can be used as a basis for health diagnosis of the battery.

The embodiment of the invention discloses a cable defect positioning and defect aging state detection method and equipment, belongs to the technical field of cable defect detection, and solves the problem that cable defects are difficult to reliably position during cable defect diagnosis in the prior art. Comprising the steps of constructing an integral transformation kernel function based on cable initial characteristic parameters; based on the integral transformation kernel function, constructing an integral transformation function corresponding to the cable head end impedance spectrum data, obtaining a cable defect diagnosis function, and determining cable defect positioning information through the cable defect diagnosis function; inputting the obtained cable defect positioning information into a cable impedance spectrum calculation model containing a local defect section, and outputting an impedance spectrum calculation value; optimizing a difference value objective function corresponding to the impedance spectrum calculation value and the impedance spectrum measurement value through a particle swarm algorithm to obtain characteristic parameters of the defect section of the cable; and determining the aging state of the local defect of the cable based on a preset cable aging characteristic parameter threshold and the characteristic parameters of the defect section of the cable.

The invention relates to the field of lithium battery performance detection, in particular to a lithium battery performance detection method and system for lithium battery production, and the method comprises the steps: obtaining the surface temperature and electrochemical impedance spectrum of a qualified lithium battery at each collection moment in the single charging and discharging process; after preprocessing, obtaining a first comprehensive temperature sequence corresponding to a single charging and discharging process and a first complex impedance sequence of each frequency, and similarly obtaining a second comprehensive temperature sequence of the lithium battery to be measured and a second complex impedance sequence of each frequency; and calculating the performance score of the to-be-tested lithium battery, if the performance score is smaller than a preset qualified threshold value, stopping the charge-discharge cycle, judging whether the total number of charge-discharge cycles is greater than a preset number of times, and judging that the performance of the to-be-tested lithium battery is qualified when the total number of charge-discharge cycles is greater than the preset number of times. According to the method, the medium-high frequency irregularity and the low frequency irregularity of the complex impedance value distribution in the charging and discharging process of the lithium battery to be tested can be considered, and the confidence coefficient of lithium battery performance evaluation is improved.

The invention relates to the technical field of alarm, in particular to a hydrogen-cooled generator manhole door hydrogen leakage prevention intelligent early warning system, which comprises a signal acquisition module for applying a measurement current to a manhole door sealing ring where a hydrogen-cooled generator is located through an electrode array, obtaining an original time domain signal, calculating to obtain a frequency domain response vector, and calculating a hydrogen leakage early warning value based on the frequency domain response vector; and extracting a complex impedance real part and imaginary part combination of each frequency point to generate impedance spectrum data. The method comprises the following steps of: applying alternating-current measurement current to a manhole door sealing ring, acquiring frequency domain response vector and impedance spectrum data, extracting relaxation characteristic frequency points from an impedance spectrum, closely associating the relaxation characteristic frequency points with current state parameters such as temperature and pressure of a hydrogen-cooled generator, and establishing reference characteristic parameters of an initial state; therefore, the real-time characteristics of the sealing ring in a dynamic environment are reflected.

The invention provides a lithium ion battery health state estimation method and system based on an electrochemical impedance spectrum. The method comprises the following steps: firstly, acquiring impedance data of the lithium ion battery in different aging states through electrochemical impedance spectroscopy measurement equipment; secondly, an improved equivalent circuit model is put forward, the double-electric-layer effect under low-frequency excitation is effectively represented by connecting a capacitor to a warburg impedance in parallel, and the fitting precision of impedance data is remarkably improved; performing parameter identification on the impedance data based on the improved model, and extracting equivalent circuit element parameters highly related to battery aging; and finally, in combination with a Gaussian process regression algorithm, taking the extracted parameters as input, and constructing a battery SOH estimation model. According to the method, the improved equivalent circuit model and the data driving method are combined, the defects that generalization is poor and the data driving method has high requirements for input characteristics are overcome, high-precision and unsupervised estimation of the SOH of the lithium ion battery is achieved, and the method is suitable for battery health management of an electric automobile and an energy storage system.

The invention relates to the technical field of power transmission line safety monitoring, discloses a power transmission line safety assessment method based on grounding electrode current, and aims to solve the problem of low assessment reliability caused by the fact that the prior art is susceptible to far-field interference and environmental factors, and the method comprises the following steps: synchronously collecting instantaneous current and potential signals of a target and a reference monitoring position; calculating respective original impedance spectrums; performing spatial difference on the target original impedance spectrum and the average reference impedance spectrum of the reference position to obtain a differential impedance spectrum to suppress common mode influence; carrying out time difference on the differential impedance spectrum and a dynamic health baseline spectrum based on real-time environmental parameter prediction to obtain a diagnosis residual spectrum so as to remove environmental changes; and finally, performing safety evaluation and fault diagnosis based on the diagnosis residual spectrum. According to the method, local fault features can be accurately extracted through space-time dual difference, the accuracy and anti-interference capability of evaluation are improved, and quantitative evaluation and graded early warning of health states and identification of specific fault modes can be realized.

The invention discloses a visual intelligent electrical loop automatic test system and a test method thereof, and belongs to the technical field of circuit testing, and the system comprises a main control unit, a multipath signal acquisition unit, a broadband impedance spectroscopy analysis unit, an automatic switching circuit unit, a communication unit and a man-machine interaction unit. The multi-path signal acquisition unit is connected with the main control unit and is used for synchronously acquiring voltage and current signals of a ring main unit control loop, a remote signaling loop and a remote measuring loop; the multipath signal acquisition unit comprises a voltage detection unit, a current detection unit and a control loop disconnection detection unit. The broadband impedance spectroscopy analysis technology is applied to loop fault positioning, millimeter-level accurate positioning of faults such as poor contact and short circuit can be achieved, the pain point that problems are difficult to find is fundamentally solved, and for complex faults such as motor stalling, double criteria of a current curve and a rotating speed signal are adopted, so that accurate positioning of the faults is achieved. Misjudgment possibly caused by single current detection is effectively avoided, and the diagnosis result is more reliable.

A method for battery authentication includes, at a battery controller of a battery subsystem, measuring a test electrochemical impedance spectroscopy (EIS) response of one or more battery cells connected to the battery controller. The test EIS response is compared to a historical EIS response stored in a storage subsystem, wherein the historical EIS response corresponds to one or more authentic battery cells associated with the battery controller. Based at least in part on a measured similarity between the test EIS response and the historical EIS response, the battery controller outputs an authenticity determination for the one or more battery cells connected to the battery controller.