583 results about "Impedance parameters" patented technology

The invention provides a self-adaptive impedance matching method and system of a microwave frequency band. The method comprises the following steps: performing initial impedance measurement on a plurality of microwave component ports to obtain a complex impedance parameter as a matching reference; in the operation process, a current impedance state and a reflection coefficient are collected through a reflection monitoring mechanism, and a dynamic impedance state vector is constructed; inputting the state information into an adaptive algorithm module, generating a matching parameter vector and configuring an adjustable device to realize real-time adjustment of a matching network; calculating a matching error according to the current reflection state and a target reference value, and driving parameters to be iteratively updated; after the matching precision requirement is met, the final parameters are loaded to the controller to complete actual configuration; meanwhile, the system periodically collects environmental parameters and matching effects, and dynamically judges whether rematching is needed or not so as to maintain long-term stable operation of the system. The method has the capabilities of automatic sensing, closed-loop optimization and environmental change adaptation, and can improve the matching efficiency and signal transmission quality of a microwave system under multi-band and high-dynamic working conditions.

The invention provides a power system optimization control method and device based on power market transaction. The method comprises the following steps: acquiring real-time electricity price fluctuation data, load demand prediction data and dynamic topology connection data between power grid nodes; generating a simplified network structure adaptive to a transaction scene based on the data, and adjusting an equivalent impedance parameter of a key transmission path in real time; a node voltage amplitude and a phase angle are cooperatively regulated and controlled through a multi-stage regulation mechanism of the solid-state transformer, and a power distribution scheme is formed; monitoring operation data of the solid-state transformer in real time by utilizing an edge computing node, and generating a local control instruction by combining the current equivalent impedance parameter; and carrying out space-time mapping matching on the local instruction and the electricity price fluctuation data, generating a combined control strategy through collaborative priority ranking, and dynamically adjusting a power distribution scheme. According to the technical scheme provided by the invention, collaborative optimization of economical operation and physical transmission performance of the power system is realized.

The invention relates to the technical field of energy storage battery diagnosis, and discloses an energy storage battery fault diagnosis method and system based on a data fusion algorithm. The method comprises the following steps: acquiring historical operation data and real-time operation data of an energy storage battery in a preset operation period, and generating a historical fault data set according to the historical operation data; performing multi-source feature fusion processing on the historical fault data set to generate a fusion feature parameter set integrating voltage, current, temperature and impedance parameter joint change features; a multi-dimensional fault space is constructed based on the parameter set, coordinate axes of the multi-dimensional fault space correspond to different parameter dimensions, and spatial position coordinates represent parameter change characteristic values; calculating the fault correlation degree of the historical fault event in the multi-dimensional fault space, and determining a fault early warning index set; and extracting real-time characteristic parameters based on the real-time operation data to form a state vector, carrying out space mapping correlation calculation on the state vector and the fault early warning index set in a multi-dimensional fault space, and outputting a real-time fault correlation factor.

The invention discloses a line loss treatment method based on low-voltage power grid multi-source data fusion, and belongs to the technical field of information, and the method comprises the steps: reconstructing a power supply path based on a power grid topological structure and a changed power access point; extracting reverse power flow characteristics of the frequency points for correcting a node impedance matrix of the current power supply path to obtain a power supply access point impedance parameter set; updating a power transmission path through the reverse power flow characteristic to obtain a power distribution characteristic; and a power grid topological structure, a current power supply path, a power supply access point impedance parameter set and power distribution characteristics are fused to construct a line loss distribution prediction model and identify a line loss abnormal region, and the line loss abnormal region is treated. Through implementation of the method and the device, the problem that the line loss treatment effect is poor due to the fact that the influence of factors such as transformer area topological structure change, power access point change and load fluctuation on the line loss is not considered in the prior art, and the predicted line loss distribution has a large error compared with the actual situation can be solved.

The invention relates to the technical field of electromagnetic shielding compensation, and discloses an electromagnetic shielding compensation method and system for an FPC high-performance computing chip interface, and the method comprises the steps: carrying out the impedance signal collection of the FPC high-performance computing chip interface, obtaining a time domain signal and a second-order change rate curve, a time domain signal is acquired by applying an alternating current excitation signal between a signal layer and a grounding layer; performing feature extraction on the time domain signal and the second-order change rate curve to obtain a feature vector; inputting the feature vector into a support vector machine model to perform electromagnetic interference classification identification to obtain an electromagnetic interference mode type; performing weighted fusion analysis on the time domain signal to obtain an electromagnetic interference state parameter; according to the method, a layered compensation controller is constructed, the impedance parameters of the shielding layer are adjusted through a self-adaptive backstepping control algorithm, compensation control parameters are obtained, accurate adjustment of the impedance parameters of the shielding layer is achieved, and stability and effectiveness of electromagnetic shielding compensation are guaranteed.

The invention discloses a power distribution network planning method and system considering distributed energy uncertainty, and relates to the technical field of power grid planning, and the method comprises the steps: collecting distributed energy node data, compensating space-time migration in combination with meteorological data, and carrying out the time sequence alignment through a dynamic time warping algorithm; constructing an improved Wasserstein generative adversarial network to generate a conventional scene, and injecting Gaussian noise through potential spatial disturbance to generate an extreme scene deviating from training distribution; inputting the mixed scene set into a mixed integer nonlinear programming model, and adopting a graph neural network to establish a topology-power flow agent model to accelerate solution; updating line impedance parameters through a Kalman filter, and collecting and checking actual output; and decomposing the corrected planning scheme into cloud global optimization and edge local control, and carrying out cloud-edge collaboration. According to the method, the adaptability of a power distribution network planning scheme in a complex and uncertain environment is improved by combining spatial-temporal feature alignment, adversarial network scene enhancement, a graph neural network and cloud edge collaborative optimization.

The invention relates to the technical field of robot control, in particular to a force control method and system based on an impedance model for a rope-driven robot. Comprising the steps of system dynamics modeling and parameter identification, real-time axial compression sensing and model updating, Cartesian space impedance model design, adaptive impedance parameter adjustment, inner ring position control based on feedback linearization, force error compensation and expected trajectory generation, real-time control circulation and anti-interference processing and experimental verification and iterative optimization. According to the method, through real-time axial compression sensing and equivalent Young modulus dynamic updating, the problem of model mismatch caused by material rigidity sudden change in the phase change process of the hyperelastic material is solved. Specifically, a traditional method depends on static material parameter calibration, and real-time compensation of the nonlinear characteristic of the material is achieved through online estimation of the axial compression amount of the main beam and iterative correction of the Young modulus.

The present disclosure discloses a seismic inversion method based on joint constraint of a physical model and priori information. The method includes: extracting seismic wavelets based on seismic data, and determining an amplitude scaling factor of the wavelets; counting priori information of impedance parameters; establishing an initial impedance parameter model by using seismic structural interpretation information and logging data; obtaining a simplified approximate equation based on an interface weak elasticity difference hypothesis, forward modeling a seismic gather by using the simplified equation, and calculating an inversion residual; rewriting an objective function into a function related to the impedance parameters by using a generalized linear inversion idea, solving the impedance parameters by using an iterative reweighted least squares algorithm, and updating the impedance parameters; and repeating the above steps until the inversion residual reaches the requirements or reaches the maximum number of iterations, and outputting a final processing result.

The invention relates to a robot dynamic grabbing control method based on visual sense and tactile sense depth fusion. The method comprises the following steps that firstly, based on visual information, surface geometric features of a target object are extracted, grabbing adaptability scores are calculated, an optimal grabbing point is selected, and a collision-free approaching track is planned; secondly, in a contact establishment stage, detecting a contact event through a touch sensor, fusing vision and touch data to unify a coordinate system, calculating a vision-touch consistency score, and applying an initial grabbing force; and thirdly, in the stable holding stage, slip detection is conducted through wavelet packet energy entropy and pressure gradient, and the grabbing force and impedance parameters are dynamically adjusted in combination with self-adaptive impedance control. According to the method, intelligent control over the whole process from approaching to contact to stable holding is achieved, and the adaptability, stability and safety of robot grabbing in the dynamic environment are improved.

The invention provides a flexible control method and device of a mechanical arm, a storage medium and a computer program product. The flexible control method comprises the following steps: a contact force calculation step: calculating the contact force between the charging plug and the charging socket according to state information by using a contact dynamic model; a track correction step: using an admittance controller to correct the original expected track according to the contact force between the charging plug and the charging socket to obtain a corrected reference track; a track control step: calculating a joint torque according to the corrected reference track by using a mechanical arm dynamic model so as to drive the mechanical arm to track the corrected reference track; and a parameter optimization step: according to the real-time state of the end effector of the mechanical arm and the contact force between the charging plug and the charging socket, the impedance parameter of the admittance controller is optimized through a reward function of a reinforcement learning algorithm. The flexible control method provided by the invention has higher precision, stronger adaptability and continuous optimization capability.

The invention discloses a power network parameter-based power flow system ill-conditioned evaluation method and system, and mainly relates to the technical field of data calculation of a power system. Comprising the following steps: generating a multi-dimensional evaluation index set comprising a network topology structure index, an admittance matrix characteristic index and branch impedance parameter statistics according to basic network parameters of a power system; through comprehensive analysis of the generated multi-dimensional evaluation index set, traditional Jacobian matrix singular value calculation is replaced, and the ill-conditioned condition number of power flow calculation of the power system is evaluated; according to the power grid type and the operation scene, dynamically adjusting the judgment threshold value of each index, and outputting the ill-conditioned risk level and the optimization suggestion. The method has the advantages that calculation independent of Jacobian matrix singular values is achieved, dynamic quantitative evaluation is carried out on bad operation conditions of the system, and meanwhile the load flow calculation stability evaluation precision of a large-scale power grid is remarkably improved.

The invention provides a netlike inverter indifference control and PCC point voltage drop optimization system and method, a reactive power error feedback module generates a reactive power compensation amount according to received reactive power reference information and collected reactive power information, and combines proportional integral control to eliminate a steady-state error so as to realize static indifference control of reactive power; the PCC point voltage drop feedforward compensation module dynamically adjusts the output voltage amplitude of the inverter according to the deviation between the theoretical reference voltage and the actual voltage of the PCC point, and directly counteracts the voltage drop caused by the line impedance; the dynamic impedance compensation module dynamically adjusts an integral coefficient of a PI controller according to an impedance parameter of a multi-machine parallel circuit, adapts to different impedance scenes, and ensures reactive power equalization and voltage balance under multi-machine parallel connection; through cooperation of closed-loop feedback and feed-forward compensation, static indifference control is realized, power grid disturbance is resisted, and system reliability is improved.

The invention discloses a communication fault diagnosis method and device based on a power system, equipment and a medium. The method comprises the following steps: S1, collecting and outputting multi-source data; s2, preprocessing the multi-source data; s3, performing topological constraint attention mechanism weighting processing on the data matrix; s4, performing dynamic threshold calculation on the fusion feature matrix; s5, positioning the abnormal node list; s6, calculating to obtain a posterior probability; s7, matching the rule base to obtain a standardized disposal instruction; according to the method, the communication traffic is collected through the compressed sensing collection algorithm, the line impedance parameters are integrated into the observation matrix in combination with the topological parameters, key node data are collected preferentially, and the effective data acquisition rate is increased; the accuracy of switch false alarm identification is improved by outputting a time-space unified fusion feature matrix; the computing resources are focused to the abnormal nodes and neighborhoods thereof through the abnormal node mask matrix, so that the positioning precision of the aged equipment is improved, and the judgment omission rate caused by switch aging is prevented from being improved.

The invention relates to the technical field of industrial process measurement, and discloses a high-precision liquid level measurement anti-interference calibration method, which comprises the following steps of: 1, synchronously acquiring a liquid level signal, a mechanical vibration signal, an electromagnetic field intensity signal and a temperature distribution signal through a multi-mode sensor array to form multi-physical field data; 2, constructing a hypergraph adjacency tensor based on the coupling relationship of the multi-physics field data, and generating a Laplacian matrix constraint; step 3, performing CP tensor decomposition with hypergraph constraint on an original signal tensor formed by the multi-physical field data, and separating a liquid level signal kernel from an interference kernel; and step 4, inputting the decomposed signal kernel characteristics and the sensor impedance parameters into a depth deterministic strategy gradient algorithm to realize hardware acceleration of a processing flow. A multi-physics field coupling relation is constructed through a hypergraph adjacency tensor and a Laplacian matrix, and the limitation of a traditional binary correlation model is broken through.

The invention provides a power grid connection disturbance observer feedback control method, which belongs to the technical field of power grid connection, and comprises the following steps: detecting power grid impedance parameters by using a multi-frequency harmonic injection technology, designing a disturbance observer algorithm to establish a state equation set, and constructing a nominal inverter model by using a low-pass filter; the total disturbance amount is estimated in real time by comparing the difference value between the actual current output and the nominal model output, a feedback control strategy is constructed, the disturbance estimation value serves as a feedforward compensation signal to be superposed to the current controller output, and disturbance components in different frequency ranges are processed in a classified mode according to disturbance types. A disturbance observer bandwidth parameter and a filter cut-off frequency are set, a disturbance estimation value is compensated to a current control loop in real time through a feedforward compensation signal to suppress the influence of power grid disturbance on the grid-connected current, and the technical problem that it is difficult to accurately estimate and compensate the influence of power grid disturbance on the grid-connected inverter in real time is solved.

The invention discloses a live-line measurement method and device for zero-sequence distribution parameters of a double-circuit line with double ends sharing a bus, and the method comprises the steps: measuring the power parameters of the double-circuit transmission line with double ends sharing the bus, and enabling the power parameters to be used for at least indicating the operation state of the double-circuit transmission line with double ends sharing the bus; a line impedance parameter matrix and an admittance parameter matrix are constructed based on the electric power parameters of the double-circuit power transmission line with the double ends sharing the bus, the line impedance parameter matrix is used for indicating impedance characteristics of the double-circuit power transmission line with the double ends sharing the bus, and the admittance parameter matrix is used for indicating admittance characteristics of the double-circuit power transmission line with the double ends sharing the bus; zero-sequence parameters, including at least one of zero-sequence resistance, zero-sequence inductance and zero-sequence capacitance, of the double-circuit transmission line sharing the bus at the two ends are determined based on the line impedance parameter matrix and the admittance parameter matrix. According to the invention, live-line measurement of line zero-sequence distribution parameters of double-circuit transmission lines on the same tower or different towers with double ends sharing buses can be effectively realized.

The invention belongs to a robot control method, and provides a human-guided robot-environment interaction self-adaptive control method and a related device for solving the technical problems that an existing human-guided robot-environment interaction control method is insufficient in motion stability, low in human operator safety and low in control precision. And estimating an optimal impedance parameter through a state space model, and learning a human-guided reference trajectory through a neural network in combination with the optimal impedance parameter. Then, in combination with a robot Jacobian matrix and a human-guided reference trajectory, a reference joint speed and an estimated acceleration of a joint space are obtained through closed-loop inverse kinematics, then network parameters of a robot dynamic model are obtained through approximation of an uncertain dynamic model, and finally, the robot dynamic model is obtained through combination with the reference joint speed and the network parameters of the joint space. And the mechanical arm control torque is obtained through the offset width fuzzy neural network. Accurate and compliant control under uncertain motion and dynamics conditions is realized.

The invention discloses an insulation resistance and capacitance measuring circuit and method based on monopulse double-edge analysis, and relates to the related field of the electrical insulation online monitoring technology, and the circuit comprises a detected object and an insulation detection circuit. The insulation detection circuit comprises a controlled pulse voltage source, a coupling resistance network, a current sensor, a switch control module, a signal modulation circuit and a processor. The measurement method implemented based on the circuit comprises the following steps: injecting a common-mode voltage pulse into a transmission line of the power transmission system by adopting a pulse transmitter; pulse current response is collected in real time, a current oscillogram is drawn, and a three-point sampling method is introduced to record a current value for insulation impedance parameter calculation; according to a load condition, a double-edge verification method is applied based on a pulse current attenuation characteristic, and insulation impedance parameters including a resistive component and a capacitive component are independently calculated by analyzing a pulse current rising edge and a pulse current falling edge. According to the invention, non-intrusive synchronous monitoring of resistive and capacitive components of line-to-ground impedance is realized, and the detection precision is improved.

The invention discloses a boundary-preserving seismic wave impedance inversion method, device, equipment and medium, and relates to the technical field of geological prospecting. Historical seismic data of a target area and logging curve data including logging impedance parameters are acquired, and seismic wavelet data are extracted from the historical seismic data; carrying out data processing on the seismic wavelet data to obtain target seismic wavelet data, constructing an initial impedance parameter model according to the logging curve data, carrying out forward modeling on the initial impedance parameter model, constructing a composite objective function comprising a boundary preserving constraint term and a prior information constraint term, and carrying out the forward modeling on the initial impedance parameter model based on the composite objective function. And the initial impedance parameter model is updated to obtain the target impedance parameter model, and the output impedance parameter inversion curve is obtained through the target impedance parameter model, so that the inversion precision and efficiency are improved, and the inversion stability and the geological reduction capability are improved.

The invention relates to the technical field of industrial control, in particular to an industrial stacker intelligent control system based on machine vision, and the system comprises a state resolving module which is used for carrying out the feature region decoupling of original observation data, and resolving a position deviation matrix and a deformation state variable for a rigid subspace and a flexible subspace respectively; the dynamic modeling module is used for identifying the first-order inherent frequency and the damping ratio of the mechanical structure on line and establishing a second-order impedance contact model; the impedance control module is used for generating an expected speed based on the position deviation and adaptively adjusting an impedance parameter according to a deformation state so as to carry out compliant modulation on a speed vector; and the estimation shaping module is used for correcting system time lag by using a Kalman observer and inhibiting residual vibration in combination with a zero-vibration input shaper. Through multi-dimensional physical field fusion and dynamic modeling, the problem that a rigid control model is mismatched with a flexible operation object is solved, and self-adaptive compliant control and vibration-free accurate operation of the stacking machine in the unstructured environment are achieved.

The invention relates to the field of lithium battery intelligent monitoring, in particular to a low-temperature-resistant lithium battery BMS monitoring method and system based on cooperative sensing. The method comprises the following steps: acquiring surface temperature distribution, environment temperature and electrochemical parameters of the low-temperature tolerant lithium battery, and constructing a multi-source state characteristic matrix through space-time alignment and data fusion; applying a composite current excitation signal, and combining impedance analysis and spectrum analysis to extract impedance parameters, nonlinear distortion components and electrochemical stress factors to form a multi-dimensional feature vector; obtaining a state monitoring result by utilizing decision level fusion; through multi-sensor fusion and multi-dimensional feature fusion, the special internal state of the low-temperature tolerant lithium battery is comprehensively represented, early risk identification and early warning are carried out aiming at unique electrochemical behavior features of the low-temperature tolerant lithium battery, and compared with a common lithium battery monitoring method, the method has the advantages that the safety is high; and the accuracy, the robustness and the real-time performance of monitoring the state of the low-temperature tolerant lithium battery in the low-temperature environment are remarkably improved.

The invention relates to the technical field of unmanned aerial vehicle control, in particular to an aerial work six-degree-of-freedom mechanical arm and a self-adaptive anti-interference control method and system.The self-adaptive anti-interference control method comprises the steps that a mechanical arm structure is manufactured through an arm body designed in a carbon fiber topological optimization mode and a joint shell provided with a flow guide groove; constructing a dynamic disturbance observer based on a DDPG algorithm, outputting a dynamic compensation amount through the dynamic disturbance observer, calculating a wind power disturbance value in combination with a disturbance compensation algorithm, and integrating the wind power disturbance value to a control law of the unmanned aerial vehicle; adjusting impedance parameters on line based on a TD3 algorithm; and generating a real-time obstacle avoidance path based on an optimized multi-target PPO path planning algorithm, and executing a path planning task of the corresponding real-time obstacle avoidance path. The unmanned aerial vehicle has the advantages that the wind disturbance resistance is remarkably enhanced, the load sudden change stability is remarkably optimized, the task energy consumption is remarkably reduced, the narrow space adaptability is remarkably improved, and the light weight is achieved.

The invention relates to the technical field of community new energy control, and discloses an orderly and rapid charging new energy control method, which comprises the following steps: collecting photovoltaic output data, power grid voltage / current data, user charging behavior data and battery state parameters in real time; generating a dynamic charging strategy based on the power grid load data, the time-of-use electricity price information, the photovoltaic output fluctuation range and the battery health state evaluation result; generating a corresponding local optimization strategy based on the operation state data of each charging pile; an economic index and a technical index are calculated, and when any index exceeds a preset threshold value, a strategy adjustment instruction is triggered, and a charging mode switching threshold value is updated; an equipment health index is generated by combining inverter temperature, coil coupling efficiency and insulation impedance parameters with historical fault data, and maintenance early warning is triggered when the health index is lower than a safety threshold value. According to the invention, the electricity cost of the user can be reduced on the basis of improving the multi-energy collaborative optimization capability of the charging facility in the residential area.

The invention discloses a distribution-micro collaborative operation simulation optimization method, which belongs to the technical field of simulation optimization, and comprises the steps of preprocessing grid-connected point voltage data, tie line power data and communication time delay data, constructing a power distribution network power flow physical network following a Kirchhoff's law, outputting a source load power prediction curve by using a long short-term memory network algorithm, and calculating the distribution-micro collaborative operation according to the source load power prediction curve. And a distribution-micro collaborative simulation optimization model is obtained based on residual error rolling correction tie line impedance parameters, a delay penalty term is set in a target function in combination with the preprocessed communication delay data, a power regulation instruction is obtained by using a particle swarm optimization algorithm, and a dynamic simulation video stream is generated. According to the invention, through rolling correction of the tie line impedance parameters and setting of the delay penalty term positively correlated with the time delay, the problem of control failure caused by physical deviation caused by model parameter solidification and communication time delay accumulation is solved, and the defects of voltage deviation calculation distortion and inaccurate network loss evaluation are eliminated. And the simulation precision and the operation stability of distribution-micro cooperation are improved.

The invention relates to the technical field of robots and intelligent control, and discloses a robot trajectory control method, device and equipment based on multiple modalities and a medium, and the method comprises the steps: obtaining a natural language instruction, environment visual information and current state information of a robot, carrying out the fusion of visual and language features, and generating a fusion feature, generating a track sequence through a track generation model according to the fusion features and the robot state information, collecting a contact force signal of the tail end of the robot in contact with the target surface, adaptively adjusting impedance parameters by using the contact force signal, and generating a control instruction; and based on the contact force signal, feedback correction is carried out on the track generation model to drive the tail end of the robot to move, and multi-mode sensing and force control feedback cooperative control is achieved. According to the invention, track and force control cooperation is realized through multi-modal fusion and contact force feedback, so that the robot keeps stable fitting and adaptive motion in a complex contact scene, and the track generation precision and the imaging quality are improved.

The invention relates to the field of power grid simulation, and particularly discloses a control method of an alternating-current power grid broadband oscillation simulation device based on a component physical model, which realizes broadband domain oscillation simulation of an alternating-current power grid based on the component physical model and a notch filter. Specifically, according to the control method of the alternating-current power grid broadband oscillation simulation device based on the element physical model, an adjustable element physical model type and a corresponding impedance parameter serve as input conditions, and a dynamic voltage compensation component excited by power grid impedance is calculated in combination with an adjustable notch filter; and a power grid simulation reference signal is constructed in real time through superposition of an original input reference voltage value and a dynamic voltage compensation component excited by power grid impedance, so that oscillation simulation in a wide frequency domain of the alternating-current power grid is realized.

The invention relates to a robot polishing online flutter suppression method based on reinforcement learning, and relates to the technical field of robot vibration control and regulation, and the method comprises the following steps: starting from a vibration signal and a force error signal in a robot polishing process, performing discrete wavelet transform, energy entropy calculation and statistical feature extraction to obtain a vibration signal and a force error signal; the method comprises the following steps: constructing a multi-source feature vector with high identification degree, normalizing the multi-source feature vector, performing feature fusion and dimensionality reduction by adopting a convolutional neural network and a multi-head attention module to obtain low-dimensional feature representation, constructing a time sequence enhanced strategy model through a DDPG framework embedded with LSTM, and outputting impedance parameters based on a time sequence state by an Actor network in the strategy model to obtain a time sequence enhanced strategy model; and the Critic network realizes stable updating of a strategy by minimizing a loss function and combining entropy regularization so as to regulate and control an end effector of the robot, real-time suppression and efficient control of a complex flutter mechanism in the process of polishing the thin-walled workpiece by the robot are realized, and the self-adaptability and the control precision of the system are remarkably improved.

The invention provides a core wire decoupling method for online monitoring of insulation damage of a multi-core cable and a signal electromagnetic coupling injection device, and the method comprises the steps: modulating a cable insulation damage monitoring signal in a time-frequency domain; injecting the modulated monitoring signal into a multi-core cable through an electromagnetic coupling method; reflection signals generated by the core wires at the cable insulation impedance discontinuous points are received respectively; calculating a system propagation coefficient according to the received reflection signal, analyzing the discontinuity degree of the cable insulation impedance, and obtaining a cable insulation impedance parameter group; if the impedance discontinuity degree is not greater than the given threshold value, injecting the modulated monitoring signal again after a given time interval; and if the impedance discontinuity degree is greater than a given threshold value, decomposing the distribution parameters of the insulation impedance through a multi-core impedance decoupling method, identifying the core wire with insulation damage, and positioning the position of the core wire. According to the invention, positioning and mode identification can be realized for conventional cable insulation damage, and the problems of positioning and damage condition identification of cable insulation damage monitoring are solved.

The invention provides a grid-connected inverter impedance detection method based on an L-shaped filter, and belongs to the technical field of grid-connected inverter impedance detection. A multi-frequency-point disturbance signal is injected into a preset grid-connected inverter working point, time domain data of inverter side current and common coupling point voltage are collected, fast Fourier transform analysis is carried out on the collected data, amplitude and phase information corresponding to each injection frequency point is extracted, and a frequency domain feature vector matrix is established; and establishing a frequency compensation matrix model to compensate and correct high-frequency band measurement data based on a frequency characteristic attenuation vector, calculating to obtain optimal estimated values of power grid impedance and grid-connected inverter output impedance, performing error analysis and precision verification on an impedance detection result, and outputting a verified impedance parameter value. The technical problem of insufficient power grid impedance detection precision caused by high-frequency band attenuation of the L-shaped filter is solved.

The invention relates to the technical field of electric energy quality management of an electric power system, and discloses an industrial power grid voltage fluctuation suppression method and system, and the method comprises the steps: firstly building a system-level voltage and current forward transmission model composed of a power unit, a filter circuit and power grid impedance which are cascaded; reversely constructing a feedforward controller based on a voltage and current forward transfer model, and generating a main compensation voltage instruction according to the power grid disturbance quantity detected in real time; state parameters of each power unit are obtained, a differential equation is constructed, and a comprehensive real-time health degree index is obtained through fuzzy reasoning; dynamically correcting an equivalent impedance parameter in the forward transfer model by using the index, and calculating a voltage distribution weight of each unit; and decomposing the total compensation voltage instruction into each unit modulation signal according to the weight. Through systematic modeling, intelligent state evaluation and dynamic fault-tolerant distribution, high-speed, accurate and high-reliability suppression of the voltage fluctuation of the industrial power grid is realized.