281 results about "Frequency coupling" patented technology

The invention discloses a self-adaptive filtering and intelligent separation method for a multi-mode partial discharge signal, and relates to the technical field of insulation state monitoring and signal processing of power equipment, and the method comprises the following steps: S1, collecting the partial discharge signal of the power equipment in real time, and synchronously obtaining an equipment operation parameter and an environment noise signal; according to the adaptive filtering and intelligent separation method for the multi-modal partial discharge signal, the problems of modal aliasing and feature distortion caused by signal and noise time-frequency coupling in a dynamic noise environment in a traditional method are effectively solved through a cooperative mechanism of dynamic coupling degree modeling and dual-channel adversarial decoupling. The dynamic coupling path sensing module quantifies interaction characteristics of noise and signals in real time, and realizes accurate suppression of high-frequency transient interference and low-frequency periodic noise in combination with a double-channel architecture of complex field phase sensitive filtering and vibration trajectory matched filtering.

The invention discloses an electrical fire monitoring method based on inherent residual current automatic compensation, and relates to the technical field of electrical safety monitoring, and the method comprises the following steps: S100, collecting a residual current signal, executing multi-component time-frequency deconstruction processing, extracting an energy distribution characteristic through wavelet packet transformation, and extracting a mutability index in combination with short-time spectrum entropy analysis, and constructing a preliminary distribution map of higher harmonic interference, and determining boundary features of interference signals in a time domain and a frequency domain. According to the method, high-frequency interference signals are accurately positioned through time-frequency deconstruction, wavelet packet analysis and spectral entropy indexes, non-fault harmonic components are effectively eliminated in combination with amplitude-frequency coupling recognition and a recursive rejection strategy, closed-loop control is constructed by introducing an adaptive compensation and stability backtracking mechanism, accurate recognition and dynamic correction of real electric leakage risks are achieved, and the method is suitable for large-scale popularization and application. The identification precision and the safety reliability of the monitoring system in a complex industrial environment are obviously improved, and the method has good engineering adaptability.

The invention discloses a motor rotating speed measuring method, system and equipment based on electromagnetic induction, and belongs to the field of motors. According to the embodiment of the invention, firstly, a magnetostriction resonance signal and an electromagnetic induction signal of a motor rotating shaft are obtained; performing frequency domain conversion on the magnetostrictive resonance signal to obtain magnetostrictive resonance frequency domain characteristics; performing frequency domain conversion on the electromagnetic induction signal to obtain electromagnetic induction frequency domain characteristics; frequency domain energy spectrum fusion reconstruction is carried out on the magnetostriction frequency domain characteristics and the electromagnetic induction frequency domain characteristics based on the frequency band matching relation between the magnetostriction frequency domain characteristics and the electromagnetic induction frequency domain characteristics, and a dual-frequency coupling energy spectrum is generated; and finally, determining the rotating speed of the motor rotating shaft according to the frequency position and amplitude distribution of the energy peak in the dual-frequency coupling energy spectrum, thereby improving the measurement precision of the rotating speed of the motor in a complex environment.

The invention relates to an electroencephalogram classification method fusing phase amplitude coupling characteristics, and belongs to the field of electroencephalogram signal processing and deep learning. The method comprises the following steps: collecting electroencephalogram signal data, and carrying out channel selection and preprocessing; performing Hilbert transform on the EEG signal of each channel, and extracting instantaneous phase and amplitude information; calculating the coupling degree of phases and amplitudes between different frequency bands, and generating a phase-amplitude coupling characteristic matrix for representing the cross-frequency coupling strength; and the PAC features and the original EEG time sequence features are jointly input into an improved Transform classification network, a self-attention mechanism is utilized to effectively model a time sequence dependence and frequency coupling relationship, multi-scale time domain, frequency domain and space features are extracted, fusion calculation is performed, and a final classification result is output. According to the method, the dependence of a traditional electroencephalogram classification method on a single frequency spectrum feature is overcome, the modeling capability of an electroencephalogram activity cross-frequency cooperation mechanism is enhanced, and the accuracy and generalization performance of electroencephalogram classification are improved.

The invention discloses a digital control uninterruptible power supply parallel operation phase locking method, which relates to the technical field of digital phase locking, and comprises the following steps of: in each analysis period, acquiring an output voltage waveform signal and a current frequency disturbance control parameter of each uninterruptible power supply, and respectively executing short-time Fourier transform to obtain an output voltage waveform signal and a current frequency disturbance control parameter of each uninterruptible power supply; and converting the time domain signal into a multi-dimensional dynamic spectrum matrix, extracting frequency and amplitude parameters of a disturbance signal, and constructing a corresponding uninterruptible power supply disturbance parameter set. According to the invention, through dynamic spectrum analysis and frequency domain coupling tensor modeling, accurate extraction of UPS modulation signal features and dynamic evaluation of resonance risk indexes are realized, in combination with a risk-driven frequency intervention mechanism, frequency coupling is broken, the frequency diversity and disturbance decoupling capability of the system are improved, and the reliability of the system is improved. The stability, the anti-interference performance and the intelligent response capability of the parallel system are obviously enhanced, and early warning and active suppression of lock point resonance are realized.

The invention discloses a detection method for judging the quality of a cable-stayed pipe, relates to the technical field of cable-stayed pipe quality detection, and is used for solving the problem of poor cable-stayed pipe quality detection precision. The optical fiber sensors are arranged on the surface of the cable-stayed pipe to collect strain data, a continuous space-time strain field is constructed, local gradient changes are extracted, identification of a micro-damage area is achieved, a node response frequency spectrum is obtained in combination with a multi-frequency-band acoustic excitation means, nonlinear energy and frequency coupling characteristics are extracted, and the micro-damage area is identified. Calculating a nonlinear display probability to locate a potential nonlinear response concentration area of the structure, constructing a topological graph model of the structure, reflecting a mechanical connection relation between nodes and monitoring abnormal response, when an abnormal structure behavior is detected, carrying out topological structure state analysis on the area where the abnormal structure behavior is located, extracting key information such as structure coupling and state propagation capability, and carrying out state analysis on the abnormal structure behavior; and high and low risk signals are generated according to a judgment result, so that the accurate identification and intelligent regulation and control of the quality change of the cable-stayed pipe are realized.

The invention relates to an intelligent sleep adjusting method and system based on closed-loop acousto-optic brain wave entrainment, electroencephalogram (EEG) signals are collected and preprocessed in real time through a wireless dry electrode, and high-precision sleep staging is achieved through a deep learning model. The system adopts a fuzzy PID (Proportion Integration Differentiation) controller to dynamically adjust acousto-optic synergistic stimulation: an acoustic module generates binaural beat signals, an optical module outputs blue light (470nm) and amber light (590nm) pulses, and the brain wave entrainment efficiency is enhanced through phase synchronization (the phase difference is less than or equal to 10 degrees) and golden section frequency coupling (fL is equal to 1.618 fA). Parameters are updated every 30 seconds through closed-loop feedback, the sound pressure level (30-50 dB) and the light intensity (10-100 lux) are adjusted according to the Weber-Fechner law, and the response delay is lt; the time is 200 ms. A three-level safety mechanism monitors gamma wave abnormity, epilepsy sample discharge and impedance overrun in real time, and triggers graded protection (alarming, cutting off light stimulation and shutdown). Clinical verifications show that the entrainment success rates of the delta wave and the theta wave respectively reach 71% and 68%, the sleep improvement effect is good, and a safe and efficient intervention scheme is provided for sleep disorders.

The invention discloses a transcranial magnetic navigation and curative effect evaluation system based on electroencephalogram power spectrum analysis, particularly relates to the technical field of electroencephalogram signal processing, and is used for solving the technical problem that existing transcranial magnetic stimulation treatment lacks interference evaluation and stimulation path optimization on a cortical collaborative area. According to the method, electroencephalogram signals of a testee in a resting state and a task state are collected, phase-amplitude coupling indexes between frequency bands are extracted, a frequency-crossing coupling matrix is constructed, a nested chain structure with modulation direction consistency is identified, a stable resonance channel group is extracted from a channel intersection set to form a collaborative active region, and the collaborative active region is constructed. And after mapping to a standard brain map, carrying out space matching with a TMS target spot, evaluating an interference risk level, formulating a stimulation avoidance strategy, recording side reactions during treatment, and constructing a curative effect scoring window in a normalization manner, so as to realize synchronous optimization of stimulation planning and curative effect evaluation.

The invention belongs to the technical field of comprehensive utilization of ocean renewable energy sources, and particularly relates to a pilot frequency coupling-based wind wave energy multi-degree-of-freedom broadband control method, which comprises the following steps of: performing frequency domain identification on wind wave environment characteristics, and constructing a wind wave pilot frequency energy coupling model; based on the motion response characteristics of the multi-degree-of-freedom floating platform, designing a pilot frequency energy regulation and conversion mechanism; a full-working-condition dynamic optimization control strategy is adopted, and cooperative operation and energy flow self-adaptive distribution of the wind energy conversion unit and the wave energy conversion unit are achieved. Aiming at the significant difference and relevance of wind energy and wave energy in frequency characteristics, time scale and spatial distribution, a pilot frequency wind wave coupling dynamic model is established, and broadband capture of low-frequency wind-induced and high-frequency wave-induced coupling energy is realized under complex sea conditions through multi-degree-of-freedom motion decoupling and state observation, so that the wind-induced and high-frequency wave-induced coupling energy is obtained. The energy utilization rate, the attitude stability and the structural safety of the system are effectively improved, and good robustness and engineering adaptability are achieved.

The invention relates to the field of gear vibration signal analysis and fault diagnosis, in particular to a gearbox gear fault detection method which comprises the steps that gear vibration signals are collected, all initial extreme points are screened, and the product of the amplitude deviation degree of the initial extreme points and local accumulated energy serves as the amplitude sudden change degree; extracting the instantaneous frequency and the instantaneous phase of each initial extreme point, and fusing the frequency consistency and the phase consistency through a geometric averaging method to obtain a time-frequency coupling index; determining the effectiveness of the initial extreme point according to the product of the time-frequency coupling index and the amplitude abrupt change degree, screening the real extreme point according to the effectiveness, extracting the inherent rotation component of the vibration signal based on the real extreme point, combining to form a feature vector, and matching the feature vector with a fault feature library to realize the fault diagnosis of the gear. According to the method, the influence of noise interference and pseudo extreme points is suppressed, and the accuracy of fault detection is improved.

The invention provides a switch cabinet dual-frequency coupling partial discharge type dynamic identification method and system and a storage medium, and the method comprises the steps: obtaining a potential partial discharge point position set of a target switch cabinet, and presetting a dual-frequency monitoring array according to the potential partial discharge point position set; deploying a synchronous acquisition system; executing dual-frequency coupling cooperative acquisition through the dual-frequency monitoring array and the acquisition system to obtain a dual-frequency signal pair array; performing space-time-frequency domain multi-dimensional feature dynamic fusion on the dual-frequency signal pair array; inputting the partial discharge characteristic parameter array fused with the space-time-frequency domain multi-dimensional characteristics into a preset partial discharge characteristic decision forest for discharge type discrimination; and carrying out dynamic weight adjustment on a discharge type judgment result. According to the invention, the space-time correlated dual-frequency monitoring array and acquisition system are deployed, and a three-level dynamic trigger mechanism is constructed, so that the cooperative capture capability of transient pulses and intermittent discharge is significantly enhanced, and the problem of leak detection of a single sensor on weak discharge signals is effectively solved.

The invention relates to the technical field of power battery health state evaluation and anomaly recognition, in particular to a remote health state analysis and anomaly recognition method for an electric bicycle battery, which comprises the following steps of: under an access working condition, applying small-signal active excitation and synchronously acquiring to form an opportunity diagnosis excitation data window; time-frequency coupling modeling including equivalent impedance modeling, harmonic wave and intermodulation fingerprint modeling, Koopman operator modeling and entropy coefficient difference is carried out, and a spectral measurement geometric distance is constructed through optimal transmission to generate a multi-domain response packet, a physical invariant vector and an uncertainty matrix; according to the geometric distance and consistency score gating and hierarchical standardization, obtaining a health state estimation record and an abnormal event set by adopting a shape-limited health mapping model; and in combination with mapping Jacobian and dual potential, generating an opportunity diagnosis incentive plan of a next period by adopting D-optimal test design, and updating a group health manifold, thereby realizing cross-environment, cross-equipment and traceable remote health assessment and early anomaly recognition.

The invention discloses an LSTM (Long Short Term Memory)-based harmonic frequency coupling model optimization method for a network construction type converter, which considers the influence of a dead zone and establishes a converter model controlled by a virtual synchronous generator based on a harmonic state space method. In the power electronic modeling process, due to approximate simplification, switch neglecting and other nonlinear relations, the model is not accurate enough, meanwhile, in the harmonic state space model modeling process, system state variable parameters need to be considered, and the precision of the model affects harmonic transmission characteristics and coupling analysis, so that the modeling efficiency is greatly improved. Errors caused by power electronic modeling are reduced through an LSTM neural network algorithm, the harmonic amplitude estimation difference is reduced, state variable parameter values in a system model are accurately estimated, the model precision is further improved, and then the harmonic coupling condition under the dead zone influence is effectively and accurately analyzed.

The invention is suitable for the technical field of data processing, and provides a new energy station voltage and frequency coupling cooperative control performance online evaluation method, which comprises the following steps: acquiring a three-phase voltage signal, a frequency signal, a unit output power signal and a power grid dispatching instruction signal of a new energy station grid-connected point, and calculating a voltage and frequency coupling characteristic matrix; performing collaborative quantitative analysis to generate a collaborative parameter matrix; performing control performance evaluation on the collaborative parameter matrix based on the collaborative evaluation network structure to generate collaborative evaluation parameters; constructing a dynamic coupling constraint function, and calculating to obtain a collaborative stability boundary representing the operation state of the station; and dynamically correcting the collaborative evaluation parameters to generate a station control performance optimization sequence. And the safety, the stability and the electric energy quality of the operation of the new energy station are effectively improved.

The invention relates to the technical field of harmonic wave evaluation, and particularly discloses a follow-up network parallel system harmonic wave anti-interference evaluation method and system considering frequency coupling, and the method comprises the steps: obtaining grid-connected current data of a GFL converter and a GFM converter under different background harmonic waves, calculating the harmonic wave coupling admittance matrix of the GFL converter and the GFM converter, and calculating the harmonic wave coupling admittance matrix of the GFL converter and the GFM converter; obtaining a harmonic coupling admittance matrix of the parallel system at the common coupling point; calculating a power grid side harmonic coupling admittance matrix based on the harmonic coupling admittance matrix of the parallel system at the common coupling point and the power grid line impedance; and based on the power grid side harmonic coupling admittance matrix, calculating an evaluation index of the anti-background harmonic interference capability of the parallel system, and realizing evaluation of the harmonic anti-interference capability of the parallel system. According to the method, harmonic mutual impedance is introduced, the influence of harmonic coupling is fully considered, and the harmonic anti-interference capability evaluation precision is effectively improved in part of scenes.

The invention relates to a DC power transmission system oscillation suppression method based on a matrix passivity theory. The method comprises the following steps: firstly, establishing a converter admittance matrix under a frequency coupling effect; then, constructing a stability criterion of the direct-current power transmission system based on the admittance matrix of the converter in combination with a matrix passivity theory; and finally, based on the stability criterion of the direct-current power transmission system, adding active damping and passive damping, adjusting corresponding parameters, and suppressing medium-high frequency oscillation of the direct-current power transmission system. The method can solve the problem of dependence on power grid side impedance modeling, constructs the stability criterion of the DC power transmission system by directly analyzing the admittance matrix characteristics of the converter, adapts to the complex situation when the AC grid side operation condition changes, and can completely suppress the medium-high frequency oscillation of the DC power transmission system. An unstable interval of a direct current system is transferred to a high frequency band through active damping, strict stability of the direct current power transmission system in middle and high frequency bands is achieved through passive damping, and the strategy cost is reduced.

The invention relates to the technical field of water turbine frequency modulation control, in particular to a water turbine primary frequency modulation control method based on an intelligent optimization algorithm, and the method comprises the steps: obtaining actual operation parameters of all collection moments in the operation process of a water turbine, and analyzing the difference degree between the high-frequency information of all actual operation parameters in the operation process of the water turbine; calculating the high-frequency coupling degree at each acquisition moment according to the random change degree of the high-frequency information of each actual operation parameter; according to the method, abnormal rotating speeds are extracted, the abnormal deviation degree of each abnormal rotating speed is obtained through the local water turbine rotating speed change dispersion degree of each abnormal rotating speed, then a rotating speed dead zone optimization value at the current collection moment is obtained, whether the opening degree of a guide vane in the water turbine is adjusted or not is judged, and optimal control parameters of a PID controller are obtained through an intelligent optimization algorithm. Therefore, primary frequency modulation control of the water turbine is realized. The stability of water turbine frequency modulation control can be guaranteed.

The invention relates to the technical field of machine learning, and discloses a transformer operation state intelligent identification method based on machine learning, which is applied to a 110kV-500kV transformer and an edge-cloud collaborative architecture of an online monitoring system of the 110kV-500kV transformer. According to the method, multi-modal features are extracted based on multi-channel cleaning data, a modal enhancement TCN model fusing kernel feature mapping and a Koopman operator is introduced, and time-frequency coupling modeling and hidden space state representation are achieved. The model realizes online recursion and working condition adaptive tracking through a Sherman-Morrison incremental updating mechanism, outputs an operation state identification result and a risk score, realizes millisecond alarm linkage through an IEC 61850 GOOSE protocol, and provides high-precision and traceable technical support for intelligent monitoring and operation and maintenance of a transformer of a transformer substation.

In a general aspect, a quantum state transferring process is performed in a computing network. In some implementations, a method of transferring a quantum state between nodes in a computing network includes receiving a signal at a first node transmitted on a transmission line from a second node. The first node includes a superconducting quantum processing circuit including a tunable-frequency coupler device with a superconducting circuit loop and a first resonator device having a tunable linewidth. The first resonator device is capacitively coupled to the tunable-frequency coupler coupled to the transmission line. The second node includes a second resonator device having a fixed linewidth coupled to the transmission line. The method includes modifying the tunable linewidth of the first resonator device over time while the signal transfers a quantum state to the first resonator device from the second resonator device, by varying a magnetic flux pulse applied to the superconducting circuit loop.

The invention discloses a building electrical circuit arc fault multi-dimensional detection and positioning method and system. The method comprises the following steps: injecting a low-amplitude broadband excitation signal into a key node of a power distribution loop through an electromagnetic excitation and sensing device, collecting a line response waveform and establishing a steady-state electromagnetic response baseline; performing self-correlation operation and spectral analysis based on the baseline, extracting formant frequency, energy distribution and bandwidth characteristics, and generating an electromagnetic modal characteristic fingerprint; through constructing a time-frequency coupling resonance matrix, formant frequency shift amount and energy gradient change are monitored in real time, and an abnormal resonance state of a line is identified. After abnormality is detected, establishing a spatial positioning equation according to multi-node phase distribution, and determining the position of an arc or a breakdown source by adopting a phase inversion algorithm; calculating a line stability coefficient by combining a positioning result and time sequence resonance data, and predicting an arc risk level; when the risk level exceeds a threshold value, an electromagnetic compensation module is activated, an opposite-phase suppression signal is generated and injected into an abnormal area, and active protection closed-loop control is achieved.

The invention discloses a network construction converter equivalent sequence impedance modeling method considering frequency coupling and time delay, and belongs to the technical field of power electronics. The network construction converter equivalent sequence impedance modeling method can accurately establish a complete and comprehensive network construction converter equivalent sequence impedance model with clear physical significance; and a basis for improving broadband interaction stability problem analysis and impedance matching optimization of the power grid is provided. Based on the model, the application of the network construction type converter in the micro-grid is promoted, the influence characteristic of digital delay on the output impedance of the converter is determined, and a theoretical basis is provided for optimizing the high-frequency stability of the network construction converter. The method can be applied to various scenes such as new energy power generation grid connection, distributed power supply access and a micro-grid, and provides technical support and a solution for stable operation of a modern power system.

The invention discloses a dual-frequency positive-sequence impedance modeling method for a network-building type energy storage converter considering frequency coupling. The method comprises the following steps: 1, injecting a dual-frequency positive-sequence disturbance voltage signal at a grid-connected point of the network-building type energy storage converter based on a virtual synchronous machine; 2, establishing a linearized small signal model for each control link of an active-frequency loop, a reactive-voltage loop, a virtual impedance-containing voltage and current double closed loop and the like to form a multi-frequency signal model; and 3, according to the multi-frequency coupling relationship between the current and the voltage, constructing a frequency coupling impedance matrix, and reducing a coupling term into output impedance to obtain the positive sequence output impedance and the negative sequence output impedance of the converter considering the frequency coupling, thereby simplifying the model stability analysis. According to the method, dual-frequency positive sequence disturbance is introduced, the coupling effect between different frequency components is effectively described, the defect that a traditional single-frequency modeling method cannot reflect the multi-frequency interaction characteristic is overcome, and the accuracy and applicability of the impedance model of the network construction type energy storage converter under the multi-frequency disturbance scene are remarkably improved.

The invention discloses a holosymmetric four-mass MEMS gyroscope which comprises four sensitive mass block coupling structures which are arranged in a central symmetry manner, and four first U-shaped beams, four n-shaped beams and a cross-shaped coupling structure which are arranged in a central symmetry manner and are connected with the four sensitive mass block coupling structures, compared with the prior art, the four sensitive mass block coupling structures are designed compactly and symmetrically, so that the sensitivity can be effectively improved, and thermally induced drift can be effectively reduced. The driving mode and the working mode are separated through the specific coupling mechanism, so that frequency coupling is avoided, and environmental vibration interference is reduced. And meanwhile, the symmetry of the structure is beneficial to uniform distribution of thermal stress or mechanical stress, so that zero drift caused by temperature change is inhibited.

The invention relates to the technical field of cable insulation detection engineering, in particular to a cable insulation damage detection method, device and equipment based on adaptive optimal kernel function design and a storage medium. The method comprises the following steps: injecting a detection signal based on time-frequency coupling into a to-be-detected cable, and collecting an echo signal generated by the to-be-detected cable based on the detection signal; constructing a self-adaptive optimal kernel function corresponding to the echo signal, and solving echo signal time-frequency distribution of the echo signal based on the self-adaptive optimal kernel function; and solving detection signal time-frequency distribution of the detection signal, and determining a cable insulation damage monitoring result of the to-be-detected cable based on the detection signal time-frequency distribution and the echo signal time-frequency distribution. By adopting the scheme, the problem of cable insulation defect detection can be solved.

In a general aspect, a multi-qubit quantum logic gate for a multi-qubit hardware-efficient stabilizer measurement is performed. In some implementations, a superconducting quantum processing unit includes a stabilizer check qubit device and two or more data qubit devices operably coupled to the stabilizer check qubit device through respective tunable-frequency coupler devices. A method includes applying a multi-qubit quantum logic gate on the stabilizer check qubit device and the two or more data qubit devices. Applying the multi-qubit quantum logic gate includes evolving the stabilizer check qubit device and the two or more data qubit devices under an interaction Hamiltonian with a plurality of terms. Each of the plurality of terms corresponding to an interaction between the stabilizer check qubit device and a respective one of the two or more data qubit devices, includes a phase combined with a Pauli operator applied to the stabilizer check qubit device and the Pauli operator applied to the respective one of the two or more data qubit devices.

The invention provides a grid-connected inverter impedance modeling method and system in a multivariable control mode. The method comprises the following steps: firstly, carrying out two-port equivalence on a to-be-analyzed and modeled grid-connected inverter to obtain a main circuit core equation; secondly, after disturbance is added, a harmonic linearization method is used for modeling a phase-locked loop under current response of voltage disturbance to obtain a corresponding phase-locked loop model considering coupling, coupling components of all frequency bands are fully considered, and the frequency coupling rule of the inverter is revealed; and finally, based on a multivariable control mode, introducing different control parameters to obtain grid-connected inverter impedance models in different control modes. Compared with a traditional inverter impedance modeling method, the grid-connected inverter impedance modeling method not only considers coupling response mechanisms under various frequencies, but also considers the impedance model under the influence of different control variables, and improves the precision and accuracy of the grid-connected inverter impedance model.

The invention discloses a sequential active frequency support method for an offshore wind power flexible direct current sending-out system, and the method comprises the steps: constructing a dynamic coupling relation between the frequency of an onshore alternating current system and the direct current voltage at a receiving end converter station through a direct current voltage synchronous control technology; the grid-connected power of a receiving end converter station is adjusted in real time according to the frequency change of an onshore alternating-current power grid by setting a proper direct-current voltage and frequency coupling coefficient. In a sending end converter station, additional control based on direct current voltage-frequency is added. And according to the fluctuation of the direct-current voltage, the frequency given value of the offshore alternating-current collection system is adjusted in real time, so that the stored energy of the sub-module capacitor of the sending-end converter station is released, and short-time frequency support is realized. In addition, the control strategy of the offshore wind turbine generator is improved, and fan virtual inertia control and primary frequency modulation control are introduced; and the frequency modulation function is realized by fully releasing the DC capacitor of the wind turbine generator and the stored energy of the rotor. The frequency change of the alternating current system can be quickly responded, and the stability is enhanced.

The invention provides a multi-input and multi-output frequency coupling admittance modeling method for a follow-up network fan, and belongs to the technical field of large-scale follow-up network type and follow-up network type fan frequency coupling admittance modeling. The technical problem that a network following type GFL and network constructing type GFM doubly-fed fan series-parallel system in a wind power plant lacks an accurate small-signal modeling and analysis method is solved. According to the technical scheme, the method comprises the following steps: S1, establishing an open-loop doubly-fed motor self admittance considering stator and rotor flux linkage dynamics; s2, obtaining frequency domain multiple-input multiple-output admittances of the following network type doubly-fed fan and the constructed network type doubly-fed fan; s3, obtaining a unified multiple-input multiple-output admittance frequency domain model containing a closed loop interconnection system formed by the following network type doubly-fed fan admittance YGFL and the construction network type doubly-fed fan admittance YGFM; and S4, quantitatively evaluating a phase-locked loop parameter and a virtual synchronous control parameter. According to the invention, accurate determination of frequency coupling oscillation is realized.

The invention discloses an impedance modeling method, system and equipment for a network-constructed converter and a medium, and relates to the field of modeling of the network-constructed converter. The objective of the invention is to solve the problem that a chain-type network-constructing converter lacks an accurate and effective impedance model and cannot support stability analysis and controller design. According to the network construction type converter impedance modeling method, system and equipment considering the multiple harmonic characteristics and the medium, the influence of multiple harmonic components on small signals and the frequency coupling effect brought by nonlinearity of a control loop can be considered, and accurate modeling of a chain type network construction type converter is achieved; and a model foundation is laid for researching the system stability of the chain-type network-constructing converter.

The invention relates to the field of laser shock peening, and particularly discloses a laser shock peening black adhesive tape damage monitoring method based on sound signals, which comprises the following steps: collecting laser shock discrete sound signals, obtaining a discrete sound signal sequence, and carrying out Hilbert envelope extraction on the discrete sound signal sequence to obtain envelope signals; performing weighting processing on the extracted envelope signal to obtain a weighted envelope, and constructing a loudness index based on the weighted envelope; short-time window frequency analysis is adopted, a dominant frequency sequence with the dominant frequency changing along with time is extracted, and the dominant frequency stability offset is calculated according to the dominant frequency sequence; and constructing a loudness-frequency coupling damage scoring criterion, and calculating a damage score. According to the method, the damage identification sensitivity is remarkably improved, the real-time online monitoring of the laser shock process is realized, the environmental adaptability is high, the engineering deployment is simple and convenient, the consistency of the laser shock peening quality is remarkably improved, and meanwhile, the method has good expandability and universality.