936 results about "Multiple frequency" patented technology

This disclosure describes systems, methods, and devices for configuring sounding reference signal resources across multiple frequency locations for device positioning. A device may encode for transmission a sounding reference signal (SRS) including a first set of SRS resources for a first transmission by a user equipment (UE) device to the node B network device at a first time and a second set of SRS resources for a second transmission by the UE device to the node B network device at a second time; decode the first transmission received from the UE device using the first set and a first bandwidth at the first time; decode the second transmission received from the UE device using the second set and a second bandwidth at the second time; and combine the first transmission and the second transmission for a device positioning estimation based on the first bandwidth and the second bandwidth.

The invention discloses an electroencephalogram signal automatic feature extraction method based on a convolutional neural network, which comprises the following steps of: acquiring original electroencephalogram signal data, and performing adaptive artifact suppression and channel amplitude dynamic re-calibration based on a channel spectrum curvature change rate; executing frequency band deformation reconstruction, determining a frequency band boundary according to the frequency spectrum curvature change rate sequence, and constructing a frequency deformation mapping function to generate a plurality of frequency band component tensors; inputting the frequency band component tensor into an improved ConvNeXt model, and extracting a multi-dimensional electroencephalogram feature tensor; cross-frequency-domain attention fusion is executed, and a fused electroencephalogram feature vector is constructed; performing task reasoning, and outputting an electroencephalogram task response result; and performing feature feedback reconstruction according to the frequency deformation consistency index and the prediction offset degree, and jointly updating deformation convolution kernel parameters. According to the method, the accuracy and stability of electroencephalogram feature extraction are improved, and the method is suitable for various electroencephalogram intelligent processing scenes such as cognitive state recognition and medical auxiliary analysis.

The invention provides a dark crack detection method of an ultrahigh-strength steel plate stamping part for a new energy automobile, and relates to the technical field of stamping part detection, and the dark crack detection method comprises the following steps: obtaining a detection area and a reference area of a to-be-detected stamping part; injecting a group of same multi-frequency alternating-current excitation signals into the detection area and the reference area of the to-be-detected stamping part at the same time, and synchronously acquiring a first electrical response signal of the detection area under the multi-frequency alternating-current excitation signals and a second electrical response signal of the reference area under the multi-frequency alternating-current excitation signals; based on the first electrical response signal and the second electrical response signal, calculating a conductivity difference value of the detection area and the reference area at the same frequency point, and obtaining a conductivity difference value-frequency curve comprising a plurality of frequency points; and based on the conductivity difference-frequency curve, whether dark cracks exist in the detection area is judged. According to the detection method, the defect degree can be quantitatively evaluated, and the strict requirement of the new energy automobile industry for quality consistency is met.

The invention relates to the technical field of water treatment equipment, in particular to an ultrasonic water treatment equipment control method and system based on variable-frequency vibration waves. According to the method, based on preset fluid working condition parameters, ultrasonic frequency conversion vibration wave signals covering multiple frequency bands are dynamically generated, and a vibrator array is driven to generate a composite sound field; a cavitation effect and an activation effect are synchronously excited in a fluid medium through variable-frequency vibration wave signals, so that physical form depolymerization and surface charge distribution change of scale forming substances occur; a shearing effect is formed on a fluid-pipe wall boundary layer, an attached state biological membrane structure is stripped, and the microscopic binding force of a crystallized scale body is loosened; monitoring the dispersion degree of scale-forming substances in the fluid and the state of a boundary layer, and adjusting the frequency band combination and energy distribution of variable-frequency vibration waves to maintain scale inhibition; and continuously optimizing the frequency conversion strategy and the sound field intensity according to the feedback data of the scale inhibition maintenance state. Through intelligent multi-band frequency conversion control of the ultrasonic water treatment equipment, efficient and environment-friendly water treatment and scale prevention effects are realized.

The invention discloses a gas pipeline leakage source positioning method, and relates to the field of gas leakage detection. According to the method, acceleration signals and sound wave signals are collected through sensors arranged at detection points, peak value extraction is carried out in respective corresponding frequency domain complex spectrums through data preprocessing, and main frequency signals and frequency multiplication signals are obtained; distinguishing real leakage and interference signals according to the stable frequency integral multiple relation characteristic and time sequence consistency of the two signals; the phase difference is calculated by extracting the phase of the dominant frequency signal and the phase of the corresponding frequency multiplication signal, and the position of the leakage source relative to the detection point is calculated by combining the path sound velocity. The method can capture small distance differences, effectively improves the precision and robustness of leakage positioning, and is suitable for online leakage monitoring and diagnosis of gas or liquid medium pipelines.

Disclosed herein is an optical frequency comb generator for a distributed acoustic anomaly detection system. The system can include a continuous wave frequency modulated laser source configured to generate a laser signal. The system can include an acousto-optical modulator configured to modulate the laser signal by altering an amplitude and / or frequency of the laser signal based on an RF drive signal applied to the AOM, and to output an optical pulse with multiple frequency sidebands based on the modulation. The output can form an optical frequency comb usable detecting and locating acoustic anomalies within a structure under observation.

The invention discloses a power system frequency risk quantification and coordination control method and system, and belongs to the technical field of power systems and automation thereof. The method comprises the following steps: collecting power grid online operation data and system working conditions; frequency response curves of the system after different faults are obtained through fault simulation; dividing the frequency into different frequency bands according to a binary criterion formed by a plurality of frequency threshold values and corresponding duration time, and distributing an initial weight coefficient for each frequency band; obtaining a dynamic weight coefficient of each frequency band by combining the frequency change rate in the frequency band and a preset weight gain coefficient; based on the dynamic weight coefficient of each frequency band, performing time integration on the frequency deviation value in each frequency band to obtain a transient frequency risk assessment value; and judging the system stability and the risk level, and giving a corresponding frequency control strategy according to the risk level so as to coordinate and control resources. According to the method, the short-time power disturbance and the permanent power disturbance can be effectively distinguished, and a basis is provided for on-line and off-line safe and stable control.

The invention provides a motor multi-band vibration suppression method and a motor multi-band vibration suppression device based on electromagnetic-mechanical cooperative regulation and control. According to the method, vibration signals are collected in real time, and spectral analysis is carried out to identify vibration frequency distribution; dividing the vibration signal into a low-frequency band, a middle-frequency band and a high-frequency band according to a spectral analysis result, and respectively corresponding to a mechanical vibration source, an electromagnetic excitation source and a structural noise source; a control strategy is dynamically selected based on a vibration frequency band, a low-frequency band triggers a mechanical regulation and control module to output a reverse force to perform vibration suppression, a middle-frequency band triggers an electromagnetic control module to optimize a current waveform and a PWM modulation mode, and a high-frequency band starts a cooperative control strategy of the electromagnetic and mechanical control module; through real-time communication between the controller and each module, vibration feedback signals are continuously monitored, and control parameters are dynamically adjusted according to working condition changes so as to maintain the vibration suppression effect. According to the invention, through cooperative adjustment of electromagnetic control and a mechanical structure, active suppression of vibration of the motor in multiple frequency bands is realized.

The invention discloses an atmosphere and ocean integrated atmosphere temperature and humidity profile inversion method based on multiple sources and multiple frequency bands. The method comprises the following steps: S1, acquiring multi-source collaborative observation data, and preprocessing the acquired data; s2, constructing an integrated state vector and coupling forward model, and obtaining an integrated state vector X; s3, performing optimal estimation based on the preprocessed data and the integrated state vector X, and performing joint inversion to realize integrated inversion solution; and S4, outputting an inversion result and theoretical uncertainty output. According to the method, integrated cooperative inversion is carried out through a physical model and an optimal estimation theory, and the inversion precision of the atmosphere temperature and humidity profile in the clear sky and in the presence of clouds, especially in the air above the ocean, is remarkably improved.

The invention discloses a robot joint hidden fault detection method and system based on artificial intelligence, and relates to the technical field of robot fault diagnosis, and the method comprises the steps: collecting a vibration signal data sequence of a robot joint; performing frequency domain decomposition on the vibration signal data sequence to obtain vibration components of a plurality of frequency bands; generating a vibration spectrum based on the vibration component, calculating an energy mean value of each frequency band in the vibration spectrum, and determining a characteristic frequency band; counting time points with abnormal energy in the characteristic frequency band, and analyzing probability distribution characteristics of a time interval sequence of the time points to obtain a fault characteristic probability; and according to the change trend of the fault feature probability, determining that the robot joint has a hidden fault risk and outputting fault risk early warning information. According to the method, the abnormal energy distribution rule of the vibration signal characteristic frequency band is analyzed, the robot joint hidden fault is early warned, the equipment fault can be effectively prevented, and the equipment operation reliability is improved.

The invention provides a soil stress monitoring method based on a distributed echo wall optical fiber cavity array, which innovatively utilizes a plurality of echo wall structures to realize distributed multi-point monitoring of soil stress in the same optical fiber, and accurately reflects the spatial distribution of the soil stress by monitoring the resonant frequency change of the echo wall structures; the method comprises the following steps: testing connection; monitoring the resonant frequency of the echo wall of the optical fiber echo wall array sensor; a wide-spectrum light source is adopted to excite an optical fiber to generate an optical signal, after the optical signal is transmitted by the optical fiber, when the optical signal passes through echo wall structures with different diameters of the optical fiber echo wall array sensor, the optical signal resonates at resonant frequencies of the echo wall structures, so that resonant trapped waves on multiple frequencies appear in a transmitted spectrum measured by a spectrograph; monitoring the resonant frequency change of the echo wall structure caused by the soil stress, and obtaining the spatial distribution information of the soil stress.

The invention discloses a non-stationary time sequence prediction method and system based on layered wavelet attention. The invention provides a refined prediction normal form of decomposition-independent modeling-adaptive fusion. The method comprises the following steps: firstly, effectively separating dynamic characteristics of endogenous time sequence data into a plurality of frequency scales through small waveguide number transformation, strengthening non-stationary components such as abrupt change and the like, carrying out layered independent modeling by adopting an independent time sequence encoder for each frequency scale, and then, carrying out self-adaptive scale fusion through a self-adaptive scale fusion mechanism; weighted fusion is dynamically performed on the coded features of all frequency scales at each time point, so that the model can focus on the current most critical dynamic information. According to the method, the problem of complex dynamic modeling in a non-stationary time sequence is fundamentally solved, and the accuracy and robustness of prediction are remarkably improved.

The invention provides a structured light projector calibration method and system and a medium, and the method comprises the steps: projecting a multi-frequency stripe pattern to a target region based on an MEMS micromirror array module, obtaining a distorted image sequence, and carrying out the phase decoding, and obtaining a phase diagram corresponding to each frequency; resolving the phase diagram based on a phase shift method and an optical path triangulation principle to obtain a preliminary three-dimensional point coordinate; constructing a neural network model and a calibration sample set, obtaining a real three-dimensional coordinate by using a standard calibration plate or a known curved surface, and calculating the deviation between the initial three-dimensional point coordinate and the real three-dimensional coordinate to obtain a training sample set; and training the neural network model according to a training sample set based on an Euclidean distance loss function, outputting a three-dimensional offset compensation amount according to the neural network model, correcting the initial three-dimensional point coordinates, and realizing an end-to-end error self-compensation mechanism through the neural network model, so that deviation compensation is effectively performed on the three-dimensional point coordinates, and the accuracy of the three-dimensional point coordinates is improved. And the three-dimensional reconstruction precision is improved.

The invention discloses a frequency safety target construction method, system and equipment for multi-element frequency modulation resource frequency response characteristic analysis, and a medium, and belongs to the technical field of power system scheduling, and the method comprises the steps: collecting the operation parameters of a thermal power generating unit, an energy storage device and a new energy inverter; establishing dynamic frequency response models including constraints such as response delay, power climbing, charge and discharge rate, energy capacity and virtual inertia, and uniformly coupling the models to form a system overall equivalent frequency response model; calculating the frequency offset, the frequency recovery time and the oscillation attenuation rate, constructing a frequency safety objective function in combination with an electric power system operation safety standard, inputting the frequency safety objective function into an electric power system dispatching optimization model, and realizing coordinated distribution of the thermal power generating unit, the energy storage device and the new energy inverter through optimization solution. According to the invention, collaborative optimization scheduling of multi-element frequency modulation resources is realized, the accuracy and safety of system frequency control are improved, and stable operation of a power system under a high-proportion new energy access condition is ensured.

The invention discloses a power supply output control method and system based on adaptive pulse width adjustment, and relates to the technical field of power supply control, and the method comprises the steps: collecting an analog envelope signal for preprocessing, and generating a probability that an amplitude falls into an interval; establishing a shortest undistorted pulse width reference model, calculating the shortest undistorted pulse width in combination with the probability that the amplitude falls into the interval, correcting the shortest undistorted pulse width, obtaining an adaptive reference pulse width, carrying out pulse edge detection, calculating an integer frequency reduction multiple and a fractional multiple correction factor, and carrying out fractional multiple frequency reduction on effective pulses to obtain a target output frequency; on the basis of the target output frequency, allocation division and allocation verification of the pulse edge are executed, and on the basis of an allocation verification result, weighting operation is executed to generate a voltage value of a step waveform; according to the invention, the distortion rate of the output waveform is reduced, and the frequency division precision and the balance of pulse distribution are remarkably improved, so that the overall energy efficiency and reliability of power supply output control are improved.

The invention relates to the technical field of leakage detection, in particular to a drainage pipe network leakage area AI identification method and system, and the method comprises the following steps: collecting sound pressure changes through an acoustic collection device, extracting candidate leakage sections, collecting images through an inspection robot, screening training samples, analyzing brightness and profile changes, adjusting the training weight, and identifying the leakage position. And calculating a boundary coincidence area ratio, and adjusting model parameters in combination with a pipe section material. According to the method, leakage candidate sections are compared and screened based on continuous fluctuation of a sound pressure multi-frequency channel, the problem of frequent occurrence of misrecognition under noise interference is avoided, a complexity index is constructed by combining a texture direction and a span in an image, and sample screening is performed; the gray-scale curved surface constructed in the non-abnormal area in the image is compared with the profile trend of the abnormal area to identify the abnormal structure, the extraction capability of irregular leakage features is enhanced, the leakage boundary and material coding data are superposed to evaluate the identification interference degree of the mixed section, and the adaptability and stability of model parameters under different materials are guaranteed.

The invention relates to the technical field of insulation degradation detection, and discloses an on-line detection method and system for insulation degradation of electric control equipment, and the method comprises the steps: obtaining and decomposing broadband dielectric response data of the electric control equipment, and obtaining a feature sequence of a plurality of frequency components; according to the energy distribution of the high-frequency component in the feature sequence, determining a potential degradation area of the electric control equipment and extracting a degradation feature component, applying pulse excitation to the degradation feature component by adopting a time domain reflection algorithm, and obtaining a time difference sequence of a reflected signal; comparing the time difference sequence with a preset delay reference, determining the initial point position of degradation invasion, and analyzing the continuous change of the time difference sequence to obtain the boundary contour information of the insulation degradation area of the electric control equipment; three-dimensional coordinate mapping of the insulation degradation path of the electric control equipment is generated based on the boundary point set, the three-dimensional coordinate mapping is optimized, a final path map of insulation degradation of the electric control equipment is generated, and the detection precision of insulation degradation of the electric control equipment is improved.

The invention provides a load balance control system of a converter tilting device and a control method thereof, and belongs to the field of converter control. The control system comprises a plurality of motors including a first motor and a second motor; the plurality of feedback encoders, the plurality of controllers and the plurality of frequency converters correspond to the plurality of motors; the motor feedback encoders are arranged on rotating shafts of all the motors and used for obtaining the first rotating speed and the second rotating speed; the master controller is used for generating an integral component and a first control reference value, and the slave controller is used for generating a second control reference value; the frequency converters are in data communication connection, the main frequency converter is used for synchronizing integral components to the driven frequency converter, and the main frequency converter and the driven frequency converter are respectively used for controlling the first motor and the second motor to execute first and second control reference values. The method is mainly used for solving the problems of overload, reverse dragging, unstable control and the like caused by non-uniform load distribution when the converter is driven by multiple motors to tilt, the tilting stability is improved, and the wear rate of equipment is reduced.

The invention discloses a wind power generation fault on-line detection method and system based on multi-frequency-converter cooperation, and relates to the technical field of frequency converters, and the method comprises the steps: connecting U frequency converters, and collecting real-time operation parameters; obtaining a first connection state sequence of each wind power generation assembly corresponding to a first frequency converter in the U frequency converters; traversing the U frequency converters to obtain U connection state sequences, combining with historical fault examples, setting fault feature vectors, constructing a fault diagnosis model, and performing fault reasoning; based on the fault diagnosis model, in the wind power generation topological graph, setting V health state evaluation nodes, uploading real-time operation parameters, and carrying out optimal configuration; and configuring a fault diagnosis mechanism of the U frequency converters by using the V health state evaluation nodes. The technical problems of low efficiency and poor accuracy of frequency converter fault diagnosis in the prior art are solved, and the technical effect of improving the efficiency and accuracy of fault diagnosis is achieved by monitoring and analyzing the operation state of the frequency converter in real time.

The invention discloses an industrial AGV navigation method based on visual BEV representation and hierarchical asynchronous control, and the method comprises the steps: collecting a multi-view perspective view of AGV navigation, and achieving an intermediate-frequency visual odometer and a high-frequency wheel type odometer through a prediction cost map and 3-DoF relative pose transformation in a BEV space; hierarchical asynchronous self-adaptive navigation based on multiple frequencies: a parameter tuning network operates at a low frequency and adaptively tunes planner parameters based on a local cost map and a relative target point provided by a planner; the local planner runs at an intermediate frequency, and generates a local track and a feed-forward speed based on the optimized planner parameters; the controller operates at a high frequency and predicts a feedback speed based on a local track, a feed-forward speed, a robot state and a local cost map, the feedback speed and the feed-forward speed are superposed and then used for controlling AGV navigation, and a complete navigation solution with low cost, high precision and high adaptability is provided.

The invention discloses a power distribution network small current grounding fault diagnosis positioning method and system based on edge calculation, and belongs to the field of power system automation, and the method comprises the steps: extracting and recognizing transient features, if a suspected grounding fault is detected, carrying out the multi-source feature fusion analysis through a regional main node, and constructing a transient response time sequence map; a weighted fuzzy clustering algorithm is combined with a multi-channel criterion to determine a fault channel, and a specific fault branch is further positioned through a topology tracking algorithm; introducing a multi-scale wavelet packet energy analysis method into the regional main node, performing energy inversion calculation on the transient current signal under multiple frequency bands, and identifying an energy concentration region near the grounding point through an energy distribution gradient; and constructing a robustness data redundancy model based on the historical data of the edge nodes and the topological relation, and identifying and eliminating abnormal feature data containing noise or distortion. According to the method, transient characteristics are rapidly extracted and preliminary judgment is made after a fault occurs, so that the real-time performance of fault response is greatly improved.

The invention discloses a coordinated regulation and control method for a comprehensive energy system to participate in multiple frequency modulation services of a power grid, and the method comprises the steps: collecting the operation state data of four resources, carrying out the preprocessing of the operation state data, obtaining the original data of the resources, constructing four resource virtualization energy storage models, and bringing the original data of the resources into the four models. The method comprises the following steps: respectively obtaining adjustable energy and power boundaries, constructing a virtual energy storage model, uniformly mapping four resources into a virtual energy storage data set through the virtual energy storage model, substituting the virtual energy storage data set into a multi-frequency modulation collaborative optimization model, obtaining an optimal scheduling result, and realizing model flexibility. And the coordination control between each subsystem in the IES and the power grid is realized, and the coordination operation mechanism of multiple auxiliary service markets is perfected.

This document describes techniques for flexible frequency band pairing for satellite communications. In aspects, a non-terrestrial communication system uses multiple frequency bands for a wireless link between a user equipment, UE, and a satellite of the non-terrestrial communication system. The non-terrestrial communication system determines to utilize two different frequency bands the wireless link between the satellite and the UE, the two different frequency bands being defined by a governing entity. In response, the non-terrestrial based communication system selects a first defined frequency band for downlink communications from the satellite to the UE and a second defined frequency band for uplink communications from the UE to the satellite. The non-terrestrial communication system then directs the satellite and the UE to communicate via the wireless link by using the first defined frequency band for the downlink communications and the second defined frequency band for the uplink communications.

The invention relates to a Beidou / GNSS full-frequency-point clock difference and signal deviation estimation system and method, and the system comprises a full-frequency-point pseudo-range deviation estimation module which is used for estimating pseudo-range deviation products on a plurality of frequency points and / or a plurality of signals of a Beidou / GNSS system; the double-frequency phase clock / phase deviation estimation module is used for estimating a phase clock / phase deviation product on the reference double frequency of the Beidou / GNSS system; the full-frequency-point phase deviation estimation module is used for estimating phase deviation products on frequencies except the reference frequency of the Beidou / GNSS system; and the full-frequency-point phase clock / phase deviation alignment module is used for aligning the clock deviation reference of the product with the clock deviation reference of the product in the previous day based on the product, so as to maintain the day boundary continuity of the product. Therefore, the problem that due to the fact that precision products have diversity and lack a unified modeling framework on the whole, effective information sharing and combined processing are difficult to achieve between different precision products, and the positioning precision is affected is solved.

The invention provides a multi-frequency distributed nested array DOA estimation method based on low-rank constraint, and the method comprises the steps: S1, building a receiving signal model of a distributed nested array, and obtaining a receiving signal based on the receiving signal model; s2, calculating a covariance matrix of the received signal, and performing vectorization processing on the covariance matrix to obtain a first virtual array corresponding to the distributed nested array; s3, extrapolating sub-arrays in the first virtual array to fill part of holes existing under the long baseline condition to obtain a second virtual array; s4, zero elements are inserted into the remaining hole positions to obtain a third virtual array, and the rank of the covariance matrix corresponding to the third virtual array is recovered; s5, establishing a matrix reconstruction model combining the low-rank constraint and the sparsity constraint, and solving to obtain a complemented covariance matrix; and S6, carrying out characteristic decomposition on the complemented covariance matrix to obtain a final DOA estimation value.

The invention discloses a tissue broadband domain impedance characteristic test system and method, and belongs to the technical field of medical detection. The system comprises a signal acquisition and control unit, a radio frequency power amplifier module, a protective resistor, a bipolar scalpel, two voltage probes and a sampling resistor module, an electrode of the bipolar scalpel is in contact with a biological tissue to be subjected to impedance characteristic test; the signal acquisition and control unit outputs a broadband excitation voltage signal, the broadband excitation voltage signal is amplified by the radio frequency power amplifier module, and the amplified signal sequentially passes through the protective resistor, the sampling resistor module and the electrode to be input into biological tissue; the two voltage probes are respectively used for sampling voltage signals of the electrode and the sampling resistor module in real time and feeding back the voltage signals to the signal acquisition and control unit; and the signal acquisition and control unit obtains impedance amplitudes and impedance phases of the biological tissue under various frequencies through Fourier transform, and impedance characteristic testing is completed. Data support can be provided for the design of the energy surgical instrument.

The invention relates to the technical field of power systems, and provides a power carrier signal adaptive separation method, device and equipment and a medium, and the method comprises the steps: sampling a power carrier signal, and decomposing the power carrier signal to obtain a multi-mode signal; dividing an interference component in the multi-mode signal into a plurality of frequency modes, and dynamically adjusting each frequency mode based on the intra-mode parameters to obtain a decoupling mode; performing time shift compensation on disturbance in the decoupling mode based on the time compensation coefficient and the frequency scale adjustment coefficient to obtain a steady-state feature; and adaptively calculating the modal energy of each interference modal in the steady-state characteristics, and dynamically adjusting the contribution proportion of each interference modal to obtain a multi-modal mask so as to realize the adaptive separation of the power carrier signals. According to the invention, high-precision and robust separation and dynamic recovery of the power line carrier signal can be realized, and the method is suitable for a complex power line channel environment.

The invention relates to a hybrid energy storage system energy optimization distribution method and system based on model prediction control, and specifically, the method comprises the steps: decomposing a total demand power prediction sequence into a multi-band sub-sequence, and then in each control period, based on a battery SOC track feature, a model mismatch residual error and a disturbance estimation state, carrying out the optimization of the multi-band sub-sequence; in combination with the current energy storage unit health state and the power subsequence kurtosis value, the battery life attenuation cost weight and the power boundary constraint are updated, the operation cost, the battery life attenuation cost and the super-capacitor state maintenance cost serve as optimization targets, the model is solved in a rolling mode, and a power distribution reference value is obtained; a real-time power instruction is obtained by calculating a model mismatch residual error of an actual operation state and a predicted value and combining a current Lyapunov exponent to update a model mismatch observer, outputting a compensation control quantity and superposing the compensation control quantity with a reference value, and energy optimization distribution is realized.

Disclosed are a communication method and apparatus, a terminal device, a network device, and a chip, which relate to the field of communication technology. The method includes the following. Physical uplink shared channel (PUSCH) is sent on a first PUSCH resource; and the PUSCH is sent on a second PUSCH resource, where the second PUSCH resource is obtained by performing frequency hopping on the first PUSCH resource. A frequency-domain starting position of the first PUSCH resource and a frequency-domain starting position of the second PUSCH resource are both located in an available frequency-domain resource, an available frequency-domain resource in a time unit is an uplink frequency-domain resource among multiple frequency-domain resources in the time unit, the plurality of frequency-domain resources comprise at least one uplink frequency-domain resource and at least one downlink frequency-domain resource.

The application provides a kind of active and passive intention recognition method and system based on electroencephalogram signal: the method comprises: obtaining the electroencephalogram signal of test personnel;Extract the electroencephalogram feature of multiple frequency bands based on electroencephalogram signal;And based on the electroencephalogram signal power spectrum density of preset frequency band in the electroencephalogram feature of multiple frequency bands, obtain active feature and passive feature;Multiple frequency bands of electroencephalogram feature, active feature and passive feature are input into pre-trained active and passive intention recognition model, and the active and passive intention categories of test personnel are obtained by identification;Active and passive intention recognition model is trained based on the electroencephalogram signal obtained from active intention experiment and passive intention experiment.The application solves the problem that the processing of electroencephalogram signal in the prior art does not consider the influence of active and passive intention, resulting in poor accuracy of control instruction output by brain-computer interface.