633results about "Digital technique network" patented technology

The invention relates to the technical field of equipment full-life-cycle management, in particular to an equipment full-life-cycle tracing and management and control system based on digital threads. Comprising a digital thread generation unit which is used for generating a dynamic digital thread penetrating through the whole life cycle of technical improvement purchasing, operation maintenance and decommissioning of equipment; a full life cycle data integration unit; and a business process management and control unit. According to the method, a dynamic digital thread which runs through the whole life cycle of technical improvement purchasing, operation overhaul and decommissioning of equipment is constructed, and a multi-dimensional data anchoring algorithm fused with weighted Bayesian estimation is combined, so that probabilistic association matching between heterogeneous physical data in each stage and a corresponding physical scene is realized; and a unique device identifier is bound to form dynamic association of physical state-data record-time node, so that the problems of fragmentation of data in the whole life cycle of the device and lack of association between the data and a physical scene in the prior art are solved.

The invention relates to the technical field of charging pile operation and maintenance systems, and particularly discloses a charging pile operation unmanned inspection and automatic operation and maintenance system which comprises a data acquisition module, a state initial judgment module, a fault diagnosis module and an automatic operation and maintenance module. An unmanned three-dimensional inspection network is constructed through an unmanned aerial vehicle and an Internet of Things sensor, accurate fault diagnosis is realized in combination with multi-modal feature fusion, a dynamic operation and maintenance priority is generated and a differential strategy is formulated based on a machine learning model, and a complete operation and maintenance closed loop of acquisition, diagnosis, execution, feedback and optimization is formed at the same time. According to the method, the inspection real-time performance and the fault recognition accuracy are greatly improved, the operation and maintenance resource configuration efficiency is optimized, the operation and maintenance cost is reduced, the equipment downtime can be shortened, the charging experience of a user is improved, the operation and maintenance capability can be continuously iteratively optimized through data accumulation, and powerful support is provided for stable and reliable operation of a charging pile network.

The invention belongs to the technical field of multivariable measurement and data analysis, and relates to a multi-source data joint measurement and analysis method based on a physical consistency relationship, which comprises the following steps of: 1, acquiring and preprocessing multi-source data; 2, modeling physical characteristics; 3, constructing a physical consistency relationship; 4, multi-source joint feature extraction; 5, carrying out consistency evaluation and abnormity identification; and 6, result fusion and dynamic updating. According to the method, collaborative analysis and consistency feature extraction of different types of measurement signals are realized by establishing a physical constraint model among multi-source sensor data, so that the reliability and precision of a multivariable measurement system are improved, the robustness of the system to measurement errors, noise and abnormity under complex working conditions is effectively enhanced, and the measurement accuracy of the system is improved. The method is suitable for the fields of intelligent driving, industrial monitoring, multi-sensor fusion measurement and the like.

The invention discloses a mixing parameter regulation and control method and system for an SBS-T modified asphalt mixture and a terminal. The method comprises the following steps: analyzing a modification mechanism through a scanning electron microscope and X-ray photoelectron spectroscopy combined technology, dividing three stages of rapid melting and the like, and establishing a temperature-viscosity model; constructing a multi-scale capture system by using an atomic force microscope, a Fourier transform infrared spectrum and a dynamic shear rheometer; designing a five-factor three-level test matrix by adopting a response surface method, and establishing a road performance prediction model in combination with a BP neural network; mixing parameters are optimized in a multi-objective mode based on a genetic algorithm, and dynamic correction is achieved through an Internet of Things sensor and Kalman filtering. The system comprises a mechanism analysis module, a multi-scale detection module, a terminal integrated storage unit, a processing unit and a man-machine interaction unit. According to the scheme, the limitation of traditional single-factor analysis is broken through, microscopic and macroscopic collaborative optimization and dynamic parameter regulation and control are achieved, and the construction adaptability and precision are improved.

The invention relates to the technical field of data processing, in particular to a coal mine environment data monitoring method and system based on the Internet of Things, and the method comprises the steps: obtaining an environment data sequence of each type of sensors in a coal mine; constructing a target window for any type of sensors, obtaining a covariance matrix through a Kalman filtering algorithm, and obtaining the data change degree of the target window; any type of sensors in a coal mine serve as target sensors, the overall window similarity is obtained, window length adjustment is conducted on target windows corresponding to the target sensors, a new target window is obtained, a preset number of sliding windows are constructed, and according to data of the new target window and data of each sliding window, a preset number of sliding windows are obtained. The sampling frequency of the target sensor at the current moment is adjusted to obtain the self-adaptive sampling frequency of the target sensor at the future moment, so that the self-adaptive sampling frequency of the target sensor at the future moment is more adaptive to change characteristics of different environmental factors, and the requirement for efficient and intelligent monitoring of coal mine environmental data is met.

The invention relates to the technical field of electronic circuits, in particular to a filter circuit, a voltage filter control circuit, a chip and electronic equipment. The filter circuit comprises a counter, a first data selector, a digital operation circuit and a register, the counter is used for receiving the counting enable signal, outputting a counting mark value to the first data selector, determining a corresponding current logic operation mode according to the current counting mark value, and performing logic operation on the intermediate input parameter according to the current logic operation mode to obtain a first voltage error value after filtering processing; by adopting the filter circuit provided by the invention, required logical operation can be completed by virtue of the first data selector and the digital operation circuit, so that the first voltage error value is output, and the filtered voltage signal is adjusted according to the first voltage error value, so that the set frequency component in the output voltage signal is filtered out; in this way, complex filter coefficients do not need to be configured, a processor with higher computing power does not need to be used, and hardware cost is saved.

The invention relates to the technical field of radio frequency signal processing, and discloses a digital filtering repair method and system for signal distortion, and the method comprises the steps: obtaining a frequency domain amplitude-frequency response and a phase response; constructing a phase compensation amount by adopting piecewise polynomial fitting and a phase inversion mechanism; a complex number logarithm domain mapping mechanism is adopted to execute composite frequency response inversion; constructing a switchable hybrid digital filter with an amplitude path and a phase path coupled in parallel; multi-band adaptive scheduling is executed; and outputting the radio frequency baseband signal stream. The technical problems that in the prior art, frequency response nonlinear distortion in a broadband range cannot be dealt with by adopting a fixed template or a single-path filter, and particularly, a high-precision and low-delay dynamic compensation effect cannot be realized in a scene that multi-band coupling interference exists in a radio frequency ADC channel with the bandwidth exceeding 800MHz are solved. Due to the fact that the switchable hybrid digital filter is constructed, accurate modeling and flexible recovery of distortion characteristics in broadband signals are achieved.

There is provided a phase shifter circuit of an optical encoder. The phase shifter circuit receives a first signal, a second signal, a third signal and a fourth signal sequentially having a 90-degree phase shift, and includes a first cascaded resistor string, a second cascaded resistor string, a third cascaded resistor string and a fourth cascaded resistor string. The first, second, third and fourth cascaded resistor strings respectively delay the first, third, second and fourth signals by selecting a switch connected at a tap-out node of the first, second, third and fourth cascaded resistor strings to correct phase deviations between incremental signals and an index signal and / or between incremental signals.

The invention provides a control system for suppressing peak of output voltage and current of a power amplifier. The system comprises a PS signal processing module, a PL signal processing module and a high-voltage power circuit, wherein the PS is configured to receive a bus signal issued by an upper computer, execute digital Gaussian filtering processing on the bus signal and then transmit the bus signal to the PL signal processing module; meanwhile, relevant data of the power amplifier are collected and uploaded; the PL signal processing module is configured to receive a signal which is issued by the PS and is subjected to digital Gaussian filtering processing, and pre-process the signal; and transmitting the processed signal to a high-voltage power circuit to control the high-voltage power circuit to execute power conversion operation on the load. According to the method provided by the invention, smooth transition is realized at the phase jump position of the signal by adjusting the parameters of the digital Gaussian filter, so that the peak of the output voltage and current of the power amplifier is inhibited, the stress of a post-stage high-voltage power circuit device is reduced, the post-stage output power is effectively improved, and the stability of the power amplifier is improved.

The invention discloses a crystal oscillator taming system based on Kalman filtering and adaptive PID, and relates to the technical field of time-frequency equipment. Comprising a crystal oscillator time frequency module used for generating a local time frequency signal, a reference module used for receiving an external reference time frequency signal, an error measurement module used for measuring the phase deviation between the local time frequency signal and the reference time frequency signal, and a Kalman filtering estimation module used for performing Kalman filtering estimation based on the phase deviation. The Kalman filtering module is used for outputting phase deviation estimation and covariance estimation and adaptively adjusting PID parameters according to the phase deviation estimation, the position deviation estimation and the covariance estimation; the control feedback module is used for superposing the voltage-controlled voltage adjustment quantity to the crystal oscillator time frequency module to adjust the output frequency of the crystal oscillator; according to the method, the crystal oscillator taming parameters are dynamically adjusted through Kalman filtering in combination with self-adaptive PID, high-precision and robust taming of the crystal oscillator is achieved, and the long-term frequency stability and the time synchronization precision of the crystal oscillator are improved.

The invention discloses a radar system clutter background modeling and adaptive suppression method and system, and relates to the technical field of radar signal target detection. The radar system clutter background modeling and adaptive suppression method comprises the following steps of covariance matrix construction, clutter model construction, clutter adaptive suppression and adaptive suppression processing optimization. According to the method, covariance matrix stability evaluation is carried out through the constructed covariance matrix, whether covariance matrix correction is carried out is judged, then the initial clutter model is established according to the covariance matrix and the preset probability distribution model, then clutter model adaptability evaluation is carried out, whether clutter model optimization is carried out is judged, and clutter model optimization is carried out. According to the method, the radar signal is subjected to self-adaptive suppression processing, and finally the judgment result of self-adaptive suppression processing optimization is obtained based on the signal-to-noise ratio of the radar signal after self-adaptive suppression processing, so that the clutter suppression effect in the radar signal is improved, and the problem of poor clutter suppression effect in the radar signal in the prior art is solved.

The invention relates to the technical field of servo control, in particular to a servo driving current harmonic compensation method and system for electromagnetic interference suppression. The method comprises the following steps: extracting common-mode and differential-mode interference by using current and voltage sampling and combining differential measurement, and configuring a multi-stage passive filter according to spectrum characteristics to construct a suppression channel; establishing a digital interference cancellation mechanism, generating a reverse compensation signal by adopting self-adaptive trapped wave and a DSP (Digital Signal Processor), and injecting the reverse compensation signal into a control loop to form a software-defined multi-channel suppression architecture; after interference suppression, a high-order tensor model is constructed for the purified three-phase current, and an alternating least square method is adopted for decomposition so as to separate multi-band harmonic waves; a graph neural network is introduced, harmonic coupling is represented, and dominant and residual harmonic decoupling is realized through message passing; according to a grading progressive strategy, dominant harmonic waves are firstly subjected to coarse compensation, then residual harmonic waves are finely adjusted, and a compensation sequence is adaptively optimized through iterative feedback, so that high-robustness closed-loop control of servo driving is realized.

The invention discloses a lithium battery broadband impedance online measurement system and method without an additional circuit, and relates to the technical field of lithium battery state monitoring. The system comprises a power DC-DC converter, a driving circuit, a sampling module and a digital controller, the digital controller comprises a converter control module and an impedance calculation and output module, the output end of the driving circuit is connected with the control end of a switching device of the power DC-DC converter, and the output end of the power DC-DC converter is connected with the input end of the sampling module. The output end of the sampling module is connected with the input end of the converter control module and the input end of the impedance calculation and output module. The output end of the converter control module is connected with the input end of the drive circuit. According to the invention, no extra hardware circuit is needed, and online, high-precision and low-cost measurement of the broadband impedance of the lithium battery is realized.

The invention provides a new energy automobile high-voltage accident grading response and emergency rescue operation guiding method and system, and is applied to the technical field of data processing. Multi-source data of voltage, current and battery states of a high-voltage system are collected, a standardized association sequence is generated after denoising, then the standardized association sequence is converted into a three-dimensional risk map, electric leakage, overvoltage and thermal runaway scenes are analyzed and subdivided through a fault tree, and a classified accident grading model is constructed. Extracting hazard weight factors to establish a dynamic evaluation matrix, and cooperatively calculating multi-source data to obtain key response indexes; parameters are extracted according to accident stages, response levels are divided, and a feature matrix is generated; real-time data and historical data are compared, and correction factors are generated by means of the accident curve slope. And in combination with vehicle types, architecture and environment grouping, key factors are screened by using a support vector machine, a personalized rescue model is established by fusing multiple constraints, and finally, a real-time graded response instruction and scene-divided rescue guidance are output.

A monorail hoist positioning method combining rail joint beacons and inertial navigation. An odometry kinematic model for a monorail hoist is established by means of an encoder on the monorail hoist, and an extended Kalman filter is used to fuse a heading angle obtained from a kinematic model solution and a heading angle obtained from a strapdown inertial navigation solution. Beacons are arranged at rail joints for the monorail hoist, and vibration signals are acquired by a vibration sensor. By combining a strapdown inertial navigation system, the encoder, and a rail installation diagram, a rail joint determination model is constructed to perform filtering, so as to obtain impact signals at rail joint beacons that meet a requirement. Beacon identifiers are used to match the identified rail joint beacons against specific beacon coordinates in the rail installation diagram, so as to obtain a time-position coordinate sequence for the monorail hoist arriving at the rail joints. A combined positioning model integrating rail joint beacons and strapdown inertial navigation is constructed to realize integration of local relative positioning and global absolute positioning of the monorail hoist. The method can improve the positioning accuracy of the monorail hoist while reducing positioning costs.

The invention provides a learning enhanced Kalman filtering method for forest emergency positioning and a related device. The method comprises the following steps: acquiring time sequence measurement data of an unmanned aerial vehicle and a ground target node; inputting time sequence measurement data into an error compensation network, and outputting a ranging error compensation amount and an observation noise covariance matrix; performing distance measurement compensation on the time sequence distance measurement data, feeding back the distance measurement data subjected to error compensation and a state error of the ground target node to a state prediction network, and outputting a state transition matrix and a process noise covariance matrix; state prediction is carried out based on a state transition model and a process noise covariance matrix, Kalman filtering fusion is carried out on a prediction state, compensated distance measurement data and an observation noise covariance matrix, three-dimensional position estimation of a ground target node is determined, combined improvement of measurement correction and prior prediction precision is realized, and the accuracy of measurement correction and prior prediction is improved. On the basis of keeping the optimality of traditional filtering, modeling is carried out on time-varying noise and non-linear motion, and the positioning precision in a forest complex environment is improved.

The invention discloses a pollution emission monitoring and early warning method based on physical prior and information value driving, and relates to the technical field of environment monitoring and pollution control, and the method comprises the following steps: collecting production side certificate data, executing time alignment and self-calibration drift removal, and constructing a standardized multi-source database; judging whether a heat island effect occurs or not, and if yes, collecting volume heat capacity, solar irradiance and heat island intensity data of a single building; according to the method, the heat island effect is introduced to judge and generate a new time-space diagram network, real-time heat island intensity changes caused by building materials and solar irradiation can be dynamically captured, and building wind field and plume data are accurately corrected. The problem that a conventional method cannot adapt to irregular fluctuation of vertical wind shear caused by the real-time heat island effect is solved, the pollution plume low-altitude compression phenomenon caused by the heat island effect is effectively corrected, and the monitoring direction is always aligned with the real diffusion path of pollutants.

The invention relates to the technical field of interference suppression, in particular to an electromagnetic compatibility optimization method and system for a ship shaft frequency converter, and the method comprises the steps: carrying out the term-by-term judgment of sensitive interference energy, current errors and switching loss after the discretization and jump limitation based on a frequency sequence, and screening out a boundary-crossing sequence, the genetic algorithm executes cross combination and amplitude superposition in the residual sequence, a new frequency set is formed through transformation and rearrangement, frequency points are distributed in a plurality of intervals to be reorganized, the switch state is predicted and updated one by one through Kalman filtering, observation residual errors are corrected in real time, and the frequency points are reorganized. The harmonic distortion rate, the radiation intensity and the instruction change amplitude are synchronously output by taking the time index as a sequence, the deviation is compensated at the amplitude and phase level, the harmonic index and the radiation index are controlled in an agreed range, the switching loss and the instruction change are within threshold values, and a complete closed loop covering frequency generation, harmonic correction and sequence updating is formed.

The invention provides a self-adaptive calculation method and system for a coal mine separation layer grouting hole arrangement pitch. The method comprises the following steps: constructing a three-dimensional geomechanical model of a target mining area; in the advancing process of the coal face, a layered settlement monitoring system is adopted to monitor dynamic development of overlying strata separation in real time, and settlement time sequence data of all strata interfaces are obtained; dynamically correcting the three-dimensional geomechanical model based on real-time monitoring data; performing simulation prediction based on the corrected three-dimensional geomechanical model to obtain a dynamic evolution rule of the spatial form, volume and position of separation layer development in a period of time in the future; and according to the dynamic evolution law of the separation layer, calculating and outputting the current optimal hole spacing of the grouting material in combination with the flow characteristics of the grouting material. According to the method, on the basis of simulation, adverse separation layer development conditions such as sudden increase or rapid closing of the separation layer can be predicted, and a precious time window is provided for adjusting a grouting strategy in advance and avoiding water inrush or ground surface settlement risks.

The invention relates to the technical field of aeronautical manufacturing and robot assembly, and discloses an aeronautical landing gear cable teleoperation collaborative assembly system and method, and the system comprises a master end interaction subsystem, a slave end assembly subsystem and a central control processing subsystem. The method comprises the following steps: acquiring multi-modal data through an environment monitoring camera, a six-dimensional force sensor and a touch sensor, and realizing space-time registration and state estimation by using Kalman filtering; and planning an optimal path by using a genetic algorithm based on the digital twinborn model and providing augmented reality guidance. And the system calculates visual confidence in real time, and adaptively switches a vision dominant control mode according to the visual confidence: when the vision is limited, the rigidity of the mechanical arm is automatically reduced, the force feedback weight is enhanced, and an operator is assisted to complete compliant operation in a blind area. According to the invention, the problems of sensing shielding and precise control of flexible cable assembly in a narrow cabin are solved, and the safety and efficiency of assembly operation are improved.

The application belongs to the technical field of power distribution network automation, and particularly relates to a power distribution transformer intelligent regulation and control method and system based on energy efficiency evaluation, which comprises the following steps: collecting the low-voltage side current, rated current, no-load loss and load loss of a power distribution transformer, and calculating the load rate; obtaining the fluctuation intensity according to the standard deviation of the load rate in a sliding window, and obtaining the change gradient by subtracting the load rates at adjacent time points; obtaining the direction consistency index according to the consistent degree of the directions of the change gradient in a preset number of steps; calculating the noise covariance according to the fluctuation intensity and the direction consistency index, and obtaining the smoothed load rate by substituting the Kalman filter equation; dynamically determining the threshold step number according to the direction consistency index, calculating the smoothed total loss, and determining the preset energy efficiency threshold according to the no-load loss and the load loss. The application reduces the tap changer regulation frequency and prolongs the service life of the contact.

The invention provides a segmented adaptive SG filtering method and device based on cosine weight transition. The method comprises the following steps: obtaining a noisy fault signal of a power distribution network; extracting local feature indexes of the signals, wherein the local feature indexes comprise an average gradient representing the change frequency of the signals and a composite feature index representing the noise level; dynamically determining a window length and a polynomial order of SG filtering based on the local feature indexes; the transient stage is the first 1 / 2 period of the post-fault signal, the steady-state stage is the subsequent part of the post-fault signal, an overlapping region is arranged at the junction of the transient stage and the steady-state stage, the overlapping region is a 1 / 2 period following the transient stage, and a cosine weight function is adopted to perform weighted fusion on filtering results of the two stages in the overlapping region; and splicing the filtering results of the non-overlapping region and the overlapping region of the transient stage and the non-overlapping region of the steady stage, and outputting a filtered fault feature signal.

The invention relates to the technical field of equipment state monitoring, and particularly discloses a combustor fault prediction and health management system. Comprising nine core modules including a multi-modal sensor fusion module, a sensor verification and recovery module, an intelligent feature extraction module, a digital twinborn simulation module, a health state evaluation module, a remaining useful life prediction module, a risk perception decision module, an uncertainty quantification and management module and an adaptive control module. Comprehensive monitoring and accurate prediction of the state of the combustor are realized through a method of combining multi-source data fusion, a physical model and data driving; and carrying out risk perception decision-making by adopting distributed reinforcement learning, verifying a maintenance strategy through a digital twin platform, and realizing closed-loop optimization in combination with adaptive control. According to the invention, through the adaptive weighting algorithm of the multi-modal sensor fusion module, the state perception comprehensiveness is improved; through a dual-path network of the intelligent feature extraction module, collaborative analysis can be carried out on multi-dimensional features.

The invention belongs to the technical field of charging pile load scheduling, and provides a power distribution network measurement data fusion driven ultrafast charging load flexible regulation and control method and system, and the method comprises the steps: firstly processing multi-source data through a multi-source measurement data fusion module by employing a self-adaptive weighted fusion and Kalman filtering algorithm, and forming a high-fidelity data pedestal; the load is predicted through a charging load accurate prediction module in combination with wavelet transform, an LSTM-GNN model and a variational mode decomposition algorithm; then, a dynamic regulation and control strategy generation module generates a regulation and control strategy through marginal cost pricing and deep reinforcement learning according to prediction; the source-load collaborative optimization module integrates related systems and optimizes scheduling by means of a particle swarm optimization algorithm; the real-time monitoring and feedback module monitors and corrects the strategy in real time; and the security protection module ensures data and system security. During use, the above module processes are operated in sequence, and flexible regulation and control of the ultrafast charging load are realized.

The invention discloses a lithium battery SOC (State of Charge) and SOH (State of Health) joint estimation method based on dual-high-order volume Kalman filtering. The method comprises the following steps: firstly, based on a second-order RC equivalent circuit model of a lithium battery; equivalent circuit parameters are identified through a pulse power characteristic experiment, and an OCV-SOC relation curve is fitted through an open-circuit voltage experiment; constructing a dual-high-order volume Kalman filter, wherein the dual-high-order volume Kalman filter comprises an SOC estimation filter and an SOH estimation filter which are parallel to each other; the SOC filter operates in real time according to a sampling period; and finally, taking the SOC estimation value as an observed quantity of an SOH filter, using the SOH estimation value to correct a battery capacity parameter in the SOC filter, and introducing a time scale transformation factor. The method can effectively improve the precision and the real-time performance of battery state estimation, the operation efficiency is remarkably improved compared with an existing method, and the method is suitable for application scenes such as electric automobiles and energy storage power stations with high requirements for the battery state monitoring precision and the real-time performance.

Devices and methods may include receiving a square wave having a frequency at an input of a harmonic-cancellation (HC) sine-wave generator; receiving a clock signal having a clock frequency at a clock input of the HC sine-wave generator; generating one or more delayed square waves based on the received square wave and the clock signal using one or more delay components of the HC sine-wave generator; and amplitude-scaling the square wave and the one or more delayed square waves using a plurality of taps of the HC sine-wave generator to produce a plurality of amplitude-scaled square waves. The method may include adding the plurality of amplitude-scaled square waves using summing circuitry of the HC sine-wave generator to produce a sine wave having tone at the frequency with suppressed signal strength at selected harmonics of the frequency of the square wave at an output terminal of the HC sine-wave generator.

This down-converter device (21, 22, 23) comprises a band limiting filter (32, 43, 53) and a Farrow structure filter (33, 44, 54). The band limiting filter (32, 43, 53) suppresses the frequency bands of a portion of an input signal. The Farrow structure filter (33, 44, 54) converts the sample rate of a signal output from the band limiting filter (32, 43, 53). The band limiting filter (32, 43, 53) suppresses at least a portion of the frequency bands excluding a frequency band to be extracted.

The application belongs to the field of aero-engines, and particularly relates to a real-time correction and repair calculation method for dynamic temperature data of an aero-engine. The method comprises the following steps: step one, correcting the dynamic temperature data, including: S1.1, performing digital filtering processing on the dynamic temperature data; S1.2, performing dynamic error correction on the dynamic temperature data; and step two, repairing bad point data in the dynamic temperature data. The real-time correction and repair calculation method for the dynamic temperature data of the aero-engine not only solves the problem of real-time correction of the dynamic temperature data in an experimental site, but also solves the problem of repairing damaged temperature measuring points through an algorithm.

The invention relates to the technical field of power system automation, in particular to a new energy box-type substation state estimation, regulation and control method, which comprises the following steps of: injecting a multi-frequency electrical excitation signal into a box-type substation, acquiring a voltage signal and a current signal, establishing a digital twin model based on primary wiring topology and grounding grid topology, performing combined state estimation and parameter estimation to obtain a comprehensive feature vector representing a degradation state, and inputting the comprehensive feature vector into a fault diagnosis and life evaluation model to obtain a risk index; and constructing a risk weighting objective function taking active output, reactive output and current as independent variables, and solving to obtain a control quantity vector for adjusting power output, reactive compensation and an electric protection device action constant value, thereby reducing the operation risk and prolonging the service life of equipment while ensuring the grid-connected requirement.

The invention belongs to the technical field of EMI (Electro-Magnetic Interference) suppression, and relates to an EMI filtering method based on dual-frequency spread spectrum and dual-frequency recombination common-mode noise cancellation waveform, which comprises the following steps of: selecting a frequency as a composition frequency; enabling the EUT to work normally by taking a selected frequency as a switching PWM frequency, and obtaining common-mode noise amplitude data of multiple times of the frequency; acquiring a common-mode voltage amplitude, and calculating an amplitude transformation ratio and an amplitude of an injected offset waveform; acquiring a common-mode voltage amplitude, and calculating the phase of the injected offset waveform; injection offset waveform data is obtained through calculation, and the common-mode voltage is offset; according to the invention, common-mode noise is taken as a main scene, and common-mode suppression can be realized while the size is reduced.