12620 results about "Electric generator" patented technology

The present invention relates to the technical field of power system equipment and control. The method of the present invention comprises: installing sensors to acquire data for online real-time monitoring, and constructing a comprehensive condition online monitoring model for comprehensive data analysis; comprehensively evaluating the health condition of a generator on the basis of a comprehensive analysis result, and identifying fault causes; and constructing a generator comprehensive data intelligent monitoring and dynamic early warning model to perform insulation degradation trend analysis and prediction on the generator. In the present invention, by comprehensively monitoring the condition of a turbine generator, various key indicators of the generator are captured in real time, and trends and patterns underlying the data are revealed, providing technical support for accurately evaluating the health condition of the generator; and continuous monitoring for the insulation condition of the generator allows for proactive identification of potential risks, thereby providing decision-making support for preventive maintenance, helping operators take measures promptly, preventing faults, improving the reliability and safety of the generator.

The invention relates to the technical field of fault diagnosis, in particular to a wind driven generator fault diagnosis method and system based on Mamba-ResNet. The method comprises the following steps: carrying out feature extraction and feature fusion by utilizing preprocessed data, namely constructing adaptive window short-time Fourier transform (AW-STFT) to carry out dynamic time-frequency resolution analysis, carrying out parallel feature extraction and constructing a multi-dimensional heterogeneous feature vector, and carrying out a cross-modal adaptive gating fusion mechanism based on a bidirectional cross gating unit; the method comprises the following steps: constructing a Mamba-ResNet hybrid deep network model architecture; performing model training on the constructed network model architecture; and performing fault diagnosis on the wind driven generator by using the trained model architecture. A tedious manual feature design process in a traditional method is avoided, and the automation level and adaptability of a diagnosis system are remarkably improved.

The invention provides a thermoelectric unit intelligent early warning method and system based on an artificial intelligence model. The method comprises the steps that firstly, multi-source operation monitoring information of different operation dimensions of core components such as a turbine, a boiler and a generator of a thermoelectric unit is obtained; performing time sequence correlation analysis on each modal monitoring data, constructing a dynamic correlation matrix, generating a modal conflict correction coefficient, and obtaining a time sequence dependence feature set; inputting the model into a hierarchical evolutionary early warning model, and obtaining an evolutionary fusion early warning feature vector through modal conflict correction and dynamic feature evolution modeling; generating a working condition self-adaptive dynamic early warning threshold value based on the current operation working condition; through comparison and abnormal traceability of the traceability verification module, an abnormal root component and a propagation path are determined, and a targeted traceability early warning instruction is output, so that the early warning accuracy and adaptability of the thermoelectric unit are improved, and safe and stable operation of the unit is guaranteed.

The invention discloses a low sample hydro-generator fault diagnosis method based on transfer learning. The method comprises the following steps: collecting a current signal, a vibration signal, a temperature signal and a voiceprint signal; executing preprocessing; performing label labeling, and dividing the data into a source domain data set and a target domain data set; operating parameters of the hydro-generator are collected, processed and combined into working condition feature vectors; training a source domain base model on the source domain data set to generate a pre-training parameter set; establishing a physical constraint module, and binding the physical constraint module with the parameter updating process of the source domain base model; initializing a transfer learning model, and calling a physical constraint module to apply constraint to generate a physically constrained transfer learning model; performing increment fine adjustment; and outputting a diagnosis result vector through the transfer learning model after increment fine tuning. According to the method, transfer learning and physical constraints are combined, hydro-generator fault diagnosis is optimized through increment fine tuning, and the method has the advantages of high precision, small sample adaptability and physical consistency verification.

A vehicle having a primary mover, a charging system, multiple electric loads, and a controller. The charging system includes a charge storing device and an alternator. The alternator is configured to convert mechanical energy generated by the prime mover into electrical energy to charge the charge storing device. The multiple electrical loads are electrically coupled to the charging system via a power distribution module. The controller is communicably coupled to the charging system and is configured to receive an indication that an electrical output of the charging system is unable to provide sufficient electrical energy to each electrical load in the electrical loads. The controller is also configured to provide a control signal to the power distribution module in response to the indication. The control signal is configured to cause the power distribution module to decouple at least one of the electrical loads from the charging system.

The invention discloses a semi-submersible wave energy-wind energy integrated power generation platform and a damping regulation and control method of a damping regulation and control system of the semi-submersible wave energy-wind energy integrated power generation platform. The platform comprises a semi-submersible wind driven generator platform, a wind driven generator set, a wave energy power generation device, an energy storage system, a sea area detection system and the damping regulation and control system. The wave energy power generation devices are divided into two groups on the inner side and the outer side of the platform, each wave energy power generation device comprises a platform inner side wave energy power generation device and a platform outer side wave energy power generation device, and each wave energy power generation device comprises a swing arm floater, a universal hinge, a connecting arm and a damping adjusting module. The semi-submersible wind power generation device and the wave power generation device are combined, and offshore renewable resources are comprehensively utilized; the six-buoy design is adopted, buoyancy is dispersed, stability and safety are improved, and meanwhile space is provided for a wave power generation device; the floaters are symmetrically arranged in a hexagonal shape and carry a damping regulation and control system, and the whole structure is more easily stabilized by adjusting the damping of the floaters in all directions.

The invention relates to the technical field of micro-grid dispatching, and particularly provides an intelligent dispatching method and system for a photovoltaic-storage-diesel micro-grid, and the method comprises the steps: obtaining the operation data of an energy storage battery, the operation data of a diesel generator, and the global operation data of the micro-grid; evaluating the power response capability of the energy storage battery according to the operation data of the energy storage battery, and evaluating the quick response capability of the diesel generator according to the operation data of the diesel generator; analyzing the stability risk level of the micro-grid according to the global operation data, the power response capability and the quick response capability of the micro-grid; adjusting scheduling optimization target emphasis according to the stability risk level; emphatically acquiring an energy storage battery charging and discharging instruction, a diesel generator starting and stopping instruction and an output instruction according to the adjusted scheduling optimization target, and executing all the acquired instructions; according to the method, the problem that the system stability is sacrificed due to blind pursuit of cost minimization in a traditional strategy can be avoided.

The invention discloses a system and a method for analyzing stability and oscillation transmission of a network-forming converter system, and belongs to the technical field of virtual synchronous generator control, and the system comprises an active power control loop which takes an active power deviation value as input, and outputs a power angle of a VSG system through an active integration part and a feedback part; the reactive power control loop takes the reactive power deviation ratio as input, and outputs the voltage amplitude of the VSG system through an active integration part and a feedback part; according to the analysis method, whether each state variable is stable or not is judged firstly, and then the intensity of oscillation transmission between the state variables is judged. According to the method, the stability of the system can be evaluated more accurately, and the accuracy of system stability analysis under dynamic disturbance is ensured; an oscillation transfer effect function is introduced, and the mutual influence between different state variables is quantitatively analyzed; and the dynamic fluctuation range of each state variable in the system can be accurately evaluated.

The invention belongs to the technical field of permanent magnet synchronous generator demagnetization fault detection, and particularly discloses a permanent magnet motor fault early warning system based on big data, which comprises a high-frequency injection and grid-connected control module, a fault early warning module and a fault early warning module, actively injecting a high-frequency disturbance signal of which the frequency is higher than the fundamental frequency into a control loop of the permanent magnet synchronous generator; the multi-source synchronous acquisition module is used for synchronously acquiring multi-dimensional operation parameters of the permanent magnet synchronous generator and performing time domain alignment and frequency domain separation on the multi-dimensional operation parameters to obtain synchronous acquisition signals; the composite feature extraction module is used for extracting a multi-dimensional demagnetization criterion of the permanent magnet synchronous generator based on the synchronous acquisition signal; the self-adaptive threshold regression prediction module is used for performing fusion evaluation on the multi-dimensional demagnetization criteria by using the demagnetization health index model to generate a demagnetization judgment result of the demagnetization degree of the permanent magnet synchronous generator; the method has the advantages that the demagnetization recognition accuracy is improved, and early warning is achieved.

The invention discloses a pressure storage and heat storage coupled regenerative heat pump power storage system and a regulation and control method thereof. The system is composed of an electric-power generation integrated unit, an energy storage compression and energy release expansion integrated unit, an energy storage expansion and energy release compression integrated unit, a high-temperature heat exchanger, a backheating heat exchanger, a cold energy absorption heat exchanger, a heat storage and cold storage storage tank, a high-pressure gas storage tank and the like. And an energy storage / energy release loop, a heat storage / heat release loop, a cold storage / cold release loop and a pressure heat coupling loop are formed by connecting pipelines. In the energy storage mode, the compressor unit is driven by electric energy to conduct multi-stage compression, and compression heat and expansion cold are stored in the high-temperature storage tank and the low-temperature storage tank correspondingly. In the energy release mode, the heat storage medium and the cold storage medium are sequentially released to supply heat or cold to the circulating working medium, and the expansion unit is driven to drive the generator to generate electricity. According to the method, bidirectional operation of energy storage and energy release is achieved through valve switching and circulation control, and power output and load change are adjusted within a second level through a pressure-heat coupling mechanism.

The invention discloses an electric power control method based on a diesel generator, commercial power and photovoltaic grid connection. The method comprises the following steps: acquiring operation data of commercial power, a diesel generator and photovoltaic-energy storage through an energy management system, constructing a multi-target dynamic optimization model, and distributing power by taking the lowest comprehensive operation cost, the highest power supply reliability and the minimum carbon emission as targets; the power analysis and regulation unit adopts a double-loop mechanism of outer-loop Kalman filtering prediction compensation and inner-loop model prediction control, synchronizes the voltage, frequency and phase of the side to be connected with the grid and the power grid side, and smoothly switches the power change rate of each energy source in the process through a self-adaptive sliding mode control strategy; and the grid-connected switching unit intelligently pre-judges the grid-connected switching opportunity by using a long short-term memory (LSTM) network and fuzzy logic fusion model. According to the invention, the energy utilization efficiency and the power supply stability are improved, multi-energy intelligent dynamic regulation and control are realized, the comprehensive operation cost of the system is effectively reduced, and reliable power supply under complex working conditions is ensured.

The embodiment of the invention provides a digital simulation modeling method and device of a tandem type hybrid electric propulsion system, computer equipment and a medium, and relates to the technical field of simulation modeling, and the method comprises the following steps: constructing a turboshaft prime mover model, constructing a generator model, connecting the turboshaft prime mover model and the generator model in series to generate a generator set, the power generation groups are connected in parallel to construct a turbine power generation system; constructing a propulsion system; constructing a battery energy storage system; constructing a power transmission and distribution system, and respectively connecting the power transmission and distribution system with a turbine power generation system, a propulsion system and a battery energy storage system; and constructing a comprehensive control and energy management system, and outputting a digital simulation modeling result through a turbine power generation system, a power transmission and distribution system and a battery energy storage system. According to the scheme, a simulation modeling method based on multi-physics field coupling double-power-source dynamic response and energy flow regulation and control provides reliable modeling technical support for engineering application of a tandem type hybrid electric propulsion system.

An intelligent energy management system, includes: a drive device including an engine configured to output power to a wheel of the vehicle, a drive motor configured to output power to the wheel, and an electric generator connected to the engine and driven by the engine to generate electricity; a power battery configured to supply electricity to the drive motor and charged with an alternating current outputted from the electric generator or the drive motor; and a control device configured to acquire multi-domain data fusion information, predict, according to the multi-domain data fusion information, a route-specific vehicle energy consumption corresponding to a preset travel route, plan, according to a road section-specific vehicle energy consumption corresponding to each road section, a target SOC corresponding to each road section, and control, according to the target SOC and an actual vehicle demand corresponding to each road section, the drive device.

Disclosed is an explainable method for monitoring a state of a generator of a wind turbine generator system on the basis of a spatio-temporal graph. The method includes: S1: acquiring data collected by a supervisory control and data acquisition (SCADA) system; S2: carrying out data understanding on the SCADA data, selecting features associated with the generator, and carrying out data preparation on the selected feature data, and obtaining valid data; S3: embedding the SCADA data, and forming a directed spatio-temporal graph data sequence; and S4: carrying out modeling of a normal behavior model of the generator on the constructed directed spatio-temporal graph data sequence, computing a full-graph-level residual and a node-level residual, computing a residual through an exponentially weighted moving average (EWMA) control chart method, carrying out full-graph-level state monitoring on the generator, forming a fault information transmission chain relation, and enhancing explainability and robustness of a monitoring result.

The invention discloses a diesel generator turn-to-turn short circuit fault protection method and system based on multi-parameter characteristics, and relates to the technical field of intelligent fault diagnosis of power equipment, and the method comprises the steps: carrying out the feature extraction of operation state monitoring data, carrying out the integration according to a time sequence, and generating a real-time feature sequence set; performing spatio-temporal feature coding and fusion on the real-time feature sequence set to generate a multi-dimensional spatio-temporal feature map; mapping the comprehensive matching score set into fault confidence according to a linear relation, obtaining a fault confidence sequence, judging a fault level in combination with a characteristic amplitude overrun condition, and generating a fault diagnosis result set; and executing hierarchical response based on the fault diagnosis result set, generating a hierarchical protection action execution record, and generating a short-circuit fault protection report in combination with the fault diagnosis result set. According to the method, quantitative similarity analysis of real-time features and standard modes is realized, the fault probability is accurately evaluated through a multi-parameter weighted fusion mechanism, and the reliability and interpretability of a diagnosis result are improved.

The invention relates to the technical field of wind power generation, and particularly discloses a duct double-turbine supercharged windmill which comprises a duct and a blade type rotating structure arranged in the duct. The duct sequentially comprises a first contraction section, a first straight section, a second contraction section and a second straight section in the air flow direction, and the diameter of the first straight section is larger than that of the second straight section. The blade type rotating structure comprises a rotating shaft, a first-stage turbine and a second-stage turbine, the first-stage turbine and the second-stage turbine are arranged on the rotating shaft, the first-stage turbine and the second-stage turbine are correspondingly arranged on the first straight section and the second straight section respectively, and the rotating shaft is connected with the generator through a transmission structure. Structural improvement is carried out through the blade type rotating structure and the duct, the turbofan located at the front end drives the turbofan located at the rear end to rotate, and therefore the wind energy utilization rate is increased.

An electric generator according to the present technology includes a coil element. The coil element includes a magnetic core and two or more windings. The magnetic core causes a magnetic flux change in an axial direction. The two or more windings that are each helically wound around the magnetic core in such a manner that each of the two or more windings is adjacent to the other winding in the axial direction of the magnetic core and are independent windings each capable of being electrically separated from the other winding.

A landing pad receives and stores packages delivered from an aerial vehicle or awaiting pickup from an aerial vehicle. The landing pad can be placed outside of a window and can contain a transmitter for sending out an identification signal via radio frequency to aid aerial vehicles in finding the landing pad. The landing pad contains a landing platform with a trapdoor that leads to a storage compartment. The trapdoor can be configured to only open when it receives a signal from an authorized aerial vehicle. The storage compartment can be accessed via a storage compartment door which can contain a locking mechanism. The storage compartment can be climate controlled. The landing pad can also have a transmitter that emits sounds to discourage animals from nesting on or near the landing pad. The landing pad can also include a solar power generator as a source of electrical energy.

The invention relates to the technical field of wind driven generator monitoring, in particular to a fan fault early warning and diagnosis method fusing multi-modal time sequence data, which comprises the following steps: respectively acquiring vibration time sequence data, current time sequence data and temperature time sequence data of a fan, and respectively calculating a first feature sequence, a second feature sequence and a third feature sequence; generating a fault early warning signal based on a three-state polarity synchronous counting mechanism; calculating a dispersion statistical value, and executing chronic fault diagnosis; when the fan is in a low-load steady-state working condition, active lubrication state detection and feedback are executed; when the first feature sequence is calculated, synchronously executing adjoint oil product pollution diagnosis; and the environment temperature is judged through the temperature time sequence data, and low-temperature working condition adaptability compensation is executed under the low-temperature working condition. The main purpose of the invention is to solve the problems in the prior art that early fault signs cannot be effectively captured due to information loss during fusion processing of multi-modal data, and real faults and external interference are difficult to distinguish.

The invention discloses a fatigue test method for a cabin structural member of an offshore wind power generator. A test piece is subjected to surface treatment, a multi-sensor array is arranged, the test piece is placed in a combined system of a multi-axis dynamic loading unit and a collaborative environment simulation cabin, an intelligent control and analysis platform synchronously applies a multi-axis alternating load, salt spray corrosion and a circulating temperature and humidity environment, and real marine service conditions are simulated; the state of a test piece is evaluated in real time based on criteria such as a strain concentration coefficient and acoustic emission energy, a strengthening test is started for potential damage risks, a load strategy is adjusted to track crack propagation when microcracks are monitored, and after the test is ended, a fatigue life prediction model is established or calibrated by combining failure test piece analysis data. And outputting a life evaluation result and a structure improvement suggestion. Through the multi-factor collaborative simulation and self-adaptive control technology, the authenticity and efficiency of the test are improved, and technical support is provided for design optimization and reliability guarantee of offshore wind power cabin structural parts.

The invention discloses a wind driven generator temperature monitoring method based on a graph space-time attention network, and the method comprises the following steps: carrying out the preprocessing of collected SCADA data, and obtaining a data set; each sensor is used as a node, the top-k neighbor relation of each node is calculated, edge weights among the nodes are calculated through a Gaussian kernel function, a weighted adjacency matrix is constructed based on the neighbor relation and the edge weights of all the nodes, and therefore a multi-sensor time sequence diagram of the wind driven generator is obtained, time sequence characteristics are given to the nodes by time sequence data collected by different timestamps, and a multi-sensor time sequence diagram of the wind driven generator is obtained. Forming a space-time diagram structure, and outputting time sequence characteristics of each sensor; a graph attention network is introduced into wind driven generator temperature state monitoring, and global and connectivity characteristics of a multi-sensor network are modeled. According to the method, the generator temperature prediction precision is remarkably improved by fusing a graph space-time two-dimensional attention mechanism and key variable screening, redundant variables are eliminated by adopting the maximum information coefficient MIC, and noise interference is reduced.

The invention relates to the technical field of wind driven generator driving control, and discloses a wind driven generator rotor turning-over driving control method based on torque and rotating speed cooperation, which comprises the following steps: before operation, controlling a motor to execute forward and reverse quasi-static micro-motion, and collecting an average electromagnetic torque; pure gravity and friction components are separated by using torque arithmetic sum and difference, gravity model gain is corrected, and friction compensation is configured; a feed-forward torque is calculated in combination with a real-time angle, and friction compensation and speed loop feedback are superposed to generate a current instruction; according to the method, gravity and friction are decoupled through physical symmetry, model parameter errors are eliminated, hidden dangers of integral lag and out-of-control rotating speed when the variable polarity load passes through a dead point are avoided, and stability and safety of the turnover process of the hundred-ton rotor are ensured.

The invention discloses a method for detecting surface defects of a blade of a wind driven generator. The method comprises the following steps: acquiring a high-resolution image of the blade of the wind driven generator acquired by an unmanned aerial vehicle; the method comprises the steps of pre-constructing a neural network model based on a deep learning target detection framework, and processing an image; the neural network model comprises a backbone network, a neck network and a detection head; a double-attention mechanism module is embedded in the backbone network and the neck network and is formed by connecting a channel-space attention mechanism and a parallel attention mechanism in series; a multi-scale feature fusion and enhancement operator is introduced into the backbone network, and a detection head operator of an optimization model is adopted to process a feature map output by the neck network; and training the neural network model by using the data set, deploying the neural network model on an unmanned aerial vehicle computing platform after training is completed, and performing real-time defect detection and recognition on an input blade image. According to the method, high-precision recognition of fine and small target defects and high-efficiency operation can be met at the same time, and real-time, accurate and automatic defect detection of the blade image is realized.

The invention discloses a wind power cluster regulation and control method, system and device based on distributed calculation and a medium, and belongs to the technical field of wind power cluster regulation and control, and the method comprises the steps: obtaining the historical wind speed and wind direction data of each wind driven generator in a wind power cluster; calculating a wind condition correlation coefficient between any two wind driven generators; constructing a graph model of a wind power cluster; based on the clustering number, clustering wind power generators in the wind power cluster to obtain a plurality of wind power groups; on the basis of a wind power set, an optimization objective function is constructed in combination with resource constraint conditions of the distributed computing nodes, and a distribution strategy of the distributed computing nodes is determined through an optimization algorithm; and operation regulation and control of the wind power cluster are realized. According to the method, the wind regime correlation coefficient is introduced to construct the graph model, the wind regime correlation degree between the wind driven generators can be accurately reflected, and the physical reasonability of clustering division is improved. The clustering number is determined through graph feature similarity matching, and the problem that parameter setting depends on experience in a traditional clustering method is avoided.

The invention relates to the technical field of ship propulsion power generation system control, in particular to a constant-power rotating speed control method and system for a ship shaft generator, and the method comprises the following steps: obtaining operation state parameters and ship environment parameters of a ship propulsion power generation system; based on the operation state parameters and the ship environment parameters, the influence of the adjusting action of the shaft generator on the rotating speed of a main propulsion diesel engine and the influence of the adjusting action of a main propulsion diesel engine speed adjusting device on the output power of the shaft generator are pre-judged, and an interactive pre-judgment result is obtained; according to the interactive pre-judgment result, jointly deciding and generating a first adjusting instruction for adjusting an axle generator and a second adjusting instruction for adjusting a main propulsion diesel engine speed adjusting device; by introducing an interactive pre-judgment and joint decision-making mechanism, the negative interaction between the shaft generator and the main propulsion diesel engine speed regulation device can be effectively identified and eliminated, and the operation stability and safety of the ship under the severe sea condition are improved.

The invention discloses a synchronous generator excitation method based on mathematical modeling and gain scheduling, and relates to the technical field of synchronous generator control, and the method comprises the steps: building a synchronous generator global dynamic mathematical model comprising the electromagnetic dynamic characteristics of a stator winding, a rotor winding and a damping winding through a modeling module; a discretization simulation platform is constructed in a Matlab / Simulink environment by utilizing a simulation module, model parameters are corrected, dynamic adjustment is realized through a gain scheduling excitation controller, an automatic voltage regulator (AVR) adopts PID (Proportion Integration Differentiation) control and comprises a voltage deviation integral separation strategy, and a power system stabilizer (PSS) dynamically adjusts parameters of a lead-lag compensator based on active power. According to the method, the deviation between a model and an actual system can be reduced by more than 30%, the electromechanical oscillation damping ratio within the rated power range of 10%-150% is increased by 25%-40%, the harmonic content of exciting current is reduced to be lower than 5%, the stability of an electric power system and the electric energy quality are remarkably improved, the engineering practicability is high, and the method is easy to transform and upgrade on an existing synchronous generator.

The invention discloses a blade-free wind power generation device based on vortex-induced vibration and dynamic regulation and control and a regulation and control method. The blade-free wind power generation device comprises an energy capturing mechanism, a support, a dynamic regulation and control system and a power generation mechanism. The energy capturing mechanism, the power generation mechanism and the dynamic regulation and control system are all installed on the support. The energy capturing mechanism is arranged outside the support and is blown by wind to vibrate so that wind energy can be converted into mechanical energy. The power generation mechanism is arranged in the middle of the support and converts mechanical energy into electric energy. And the dynamic regulation and control system is used for regulating and controlling the vibration amplitude of the energy capturing mechanism at different wind speeds, so that the generated power of the energy capturing mechanism is kept stable. Compared with the prior art, the blade-free wind power generation method has the advantages that more stable electric energy output is realized by dynamically regulating and controlling the tightness of the mooring rope, the efficient, stable and environment-friendly blade-free wind power generation device is provided, and the maintenance cost is lower.

The invention discloses a doubly-fed induction generator fault detection method combining a sliding-mode observer and a bilateral cumulative sum algorithm, and the method comprises the following steps: designing a doubly-fed induction generator rotor current sliding-mode observer based on the combination of a novel reaching law and a doubly-fed induction generator state equation; carrying out stability and convergence analysis on the designed novel reaching law by adopting a Lyapunov stability theory; and the fault detection method of the doubly-fed induction generator is designed in combination with the optimized bilateral accumulation sum algorithm. A rotor current sensor fault, an input interference voltage fault, a voltage drop fault and a stator turn-to-turn short circuit fault are introduced. The rotor current tracking performance of the designed sliding-mode observer under different doubly-fed induction generator faults is verified by using a residual value obtained by comparing a doubly-fed induction generator rotor current value estimated by the sliding-mode observer with an actual rotor current output value; and meanwhile, the reliability of the designed doubly-fed induction generator fault detection method based on the optimized bilateral cumulative sum algorithm is verified. The doubly-fed induction generator fault detection method combining the sliding-mode observer and the bilateral cumulative sum algorithm has the advantages of being high in tracking precision and accurate in fault state characterization, meanwhile, weak fault features can be effectively converted into digital signals to be output, and faults of the doubly-fed induction generator are detected.

A grid-connection pre-synchronization method for a virtual synchronous generator parallel system, and an electronic device. The grid-connection pre-synchronization method for the virtual synchronous generator parallel system comprises: after receiving a pre-synchronization instruction, n virtual synchronous generators start to perform grid-connection pre-synchronization, wherein the grid-connection pre-synchronization comprises frequency and phase pre-synchronization, and amplitude pre-synchronization (S110). The frequency and phase pre-synchronization comprises: calculating control amounts for the frequency and phase pre-synchronization; according to the control amounts for the frequency and phase pre-synchronization, calculating a damping power; according to a mechanical power, an electromagnetic power and the damping power, calculating an output angular frequency difference of the virtual synchronous generators; and according to the output angular frequency difference of the virtual synchronous generator sand a rated angular frequency, determining a power angle of the virtual synchronous generators.

The invention discloses a multi-dimensional sensing and AI combined fan blade defect detection system and method, and relates to the technical field of fan blade detection.The system comprises a wind driven generator body and further comprises a multi-dimensional sensing module, an edge calculation module and a cloud AI module, and the wind driven generator body comprises a tower base, a generator head, a flow guide cover and blades; the generator head is installed at the top of the tower base, the flow guide cover is installed at the front end of the generator head, the blade is fixed to the flow guide cover, a fixing bolt is arranged between the blade and the flow guide cover, the multi-dimensional sensing module comprises a voiceprint sensor, an ultrasonic bolt axial force detection sensor and a temperature and vibration integrated sensor, and the voiceprint sensor is installed in the blade and on the tower base. The system has the advantages of multi-dimensional data acquisition, real-time monitoring, automatic cleaning and intelligent diagnosis, and solves the problems of single sensing dimension, poor environmental adaptability, slow fault response and lack of bolt axial force monitoring in the prior art.