36 results about "Energy matrix" patented technology

The invention relates to the technical field of electrical sensor measurement, and provides a fault test method, system and equipment suitable for a fan converter, and the method comprises the steps: collecting current data in an IGBT module of the fan converter, and taking the current data as an original current signal; screening a plurality of dominant frequencies of the original current signal; decomposing the original current signal to obtain a plurality of component signals, and corresponding to each dominant frequency to obtain a plurality of dominant frequency signals; screening to obtain a reference signal; according to the variation trend difference between each component signal and the reference signal, the variation abnormity of each component signal is obtained; analyzing the energy difference between each component signal and the reference signal in the time-frequency energy matrix to obtain the energy difference index of each component signal; obtaining an anomaly index of each component signal; and performing fault detection on the fan converter based on the anomaly index of each component signal. The invention aims to solve the problem that high-frequency electromagnetic noise affects signal performance of a current sampling loop and covers real fault features.

The invention discloses an irrigation district water distribution scheduling method and device and a medium, belongs to the field of irrigation district management, and aims to solve the problem that accurate irrigation cannot be uniformly and efficiently carried out, and the method comprises the following steps: determining a digital elevation model and a crop planting distribution diagram of an irrigation district; according to the digital elevation model and the crop planting distribution map, determining different irrigation subareas of the irrigation area, and a water delivery energy consumption coefficient, a crop suitability coefficient and a subarea water demand critical period of each irrigation subarea; constructing a water delivery energy matrix of the irrigation area according to the water delivery energy consumption coefficient of each irrigation subarea and the irrigation water demand in the irrigation period; determining a rotation irrigation group of the irrigation area according to the water delivery energy weight combination and the water delivery energy matrix of each irrigation subarea in the current irrigation period; and determining the irrigation time sequence of the rotation irrigation group according to the crop suitability coefficient of each irrigation subarea and the subarea water demand critical period. And water distribution in the irrigated area can be more efficiently and reasonably carried out.

The invention discloses a power distribution feeder fault detection method considering transient frequency response of a distributed power supply, which relates to the technical field of power distribution network fault detection and comprises the following steps: acquiring a voltage traveling wave signal and performing wavelet transformation to obtain a multi-scale wavelet coefficient; calculating wavelet energy entropy and extracting local time-frequency energy characteristics; constructing a time-frequency energy matrix and calculating a norm of the time-frequency energy matrix to judge whether detection is started or not; and after a threshold condition is met, normalizing the energy matrix, screening out invalid data, calculating a non-zero norm, obtaining a distribution proportionality coefficient according to the non-zero norm, and finally completing fault identification. The method has better effects in the aspects of accuracy and applicability.

The invention relates to a hydro-generator partial discharge pulse extraction method based on Taylor-S transformation. The method comprises the following steps: collecting a partial discharge signal of a stator winding of a hydro-generator; preprocessing the partial discharge signal to obtain a preprocessed signal; performing time-frequency transformation on the preprocessed signal to obtain a time-frequency matrix; estimating an instantaneous frequency based on phase information of the time-frequency matrix; synchronously extracting the time-frequency matrix according to the instantaneous frequency to obtain a time-frequency energy matrix; extracting a time-frequency ridge line based on the time-frequency energy matrix, and performing feature optimization on the time-frequency ridge line to obtain an optimized ridge line; and determining starting and ending positions of the partial discharge pulse according to the time-frequency energy matrix and the optimized ridge line. According to the method, Taylor-S transformation is combined with synchronous extraction operation, so that the problems of energy dispersion and serious cross term interference in a strong noise environment of a traditional time-frequency analysis method are effectively solved, and the definition and focusing property of partial discharge pulse time-frequency representation are remarkably improved.

The invention discloses an intelligent energy management system of a photovoltaic-energy storage integrated prefabricated external wall panel. Efficient energy management is realized through a three-layer closed-loop architecture. A data acquisition layer acquires photovoltaic power Ppv, a battery SOC and a temperature Tbatt in real time; the central control layer constructs an energy matrix Ematrix based on an edge computing chip, and executes a three-level scheduling algorithm, and photovoltaic power supplies load preferentially, energy storage and charging are performed, and a surplus feed network is formed; and the communication layer interacts with a power grid through the LoRa module. The system integrates fuzzy PID (Proportion Integration Differentiation) control, LSTM (Long Short Term Memory) prediction, multi-mode dynamic switching (self-sufficiency / power grid assistance / peak shaving / emergency standby) and a safety protection mechanism (thermal runaway blocking and battery health management), and dynamic impedance matching and line loss compensation are combined, so that the energy utilization rate is improved, and the accident rate is reduced.

The invention provides a method for monitoring the motion state of a mask plate workpiece table by exposing an active area, which comprises the following steps of: 1, providing a wafer, performing active area exposure on the wafer, and aiming at the central energy / focal length of a focal length energy matrix test of the exposure, taking the optimal energy / focal length for not performing any registration error compensation on the active area under a corresponding process platform; step 2, determining whether to trigger the fault detection and classification system to work according to the standard deviation of the rotation amount of the mask workpiece table around the Z axis in the movement process generated by different exposure energy values of the focal length energy matrix test; and step 3, after the fault detection and classification system is started to work, checking the mask plate workpiece table. According to the application, the motion state of the mask plate workpiece table can be effectively monitored in real time.

This invention relates to the field of power cable testing technology, and discloses a method and system for detecting cable dimensional parameters based on point cloud feature registration. The method includes: acquiring multispectral image signals; obtaining the light trace energy matrix through physical simulation; constructing an error fingerprint database by combining topological mapping; performing semantic segmentation on the image signals to obtain a probability segmentation mask; calling the fingerprint database to obtain a correction matrix and extracting the original sub-pixel point cloud; performing confidence assessment based on environmental stress parameters to obtain a weighted confidence feature set; performing geometric center alignment to output the cable geometric center set, and then extracting the dimensions to obtain the cable cross-section measurement results. This invention achieves digital decoupling of stress-induced optomechanical coupling pseudo-drift, solves the technical problems of numerical jumps in insulation thickness and deviations in eccentricity calculation, and improves the confidence and measurement accuracy of cable cross-section configuration reconstruction under complex mechanical stress conditions.

The invention provides an energy balancing system and method based on GaN high-frequency multiplexing, and the system comprises a cell group module which is used for storing and supplying energy; the matrix type energy routing module is used for receiving the energy flow decision of the central control module, and a switch matrix adjusts the channel state of an energy transmission channel between the energy storage cell and the GaN-based DC-DC converter according to the energy flow decision; the sensing module is used for collecting state parameters of each energy storage battery cell in the battery cell group module, compensating the state parameters according to a preset calibration database, and transmitting the compensated state parameters to the central control module; and the central control module is used for determining the charge state and the cell health degree of the energy storage cell according to the compensated state parameters, generating an energy flow decision according to the charge state and the cell health degree, and transmitting the energy flow decision to the matrix type energy routing module. And through a charge state and cell health degree two-parameter decision and a matrix type dynamic multiplexing architecture, the energy balance effect is improved while miniaturized integration is realized.

The invention discloses a synthetic aperture radar broadband radio frequency interference detection method and system based on out-of-band signal energy, a storage device and electronic equipment, and the method comprises the following steps: carrying out the range Fourier transform of broadband interference echo data, and converting the data into an azimuth time domain-range frequency domain; extracting signals outside a frequency band to obtain an out-of-band energy matrix only containing noise and radio frequency interference; summing pulse by pulse along the distance direction according to the out-of-band energy matrix to obtain a final energy sequence of which the length is the azimuth sampling number; gaussian weighted moving average filtering is carried out on the energy sequence; calculating the filtered data by using an Otsu algorithm to obtain a self-adaptive threshold value; and segmenting the energy sequence based on a filtering result and an adaptive threshold to obtain an interference detection result. According to the invention, whether the pulse of the synthetic aperture radar echo contains the broadband radio frequency interference can be detected with high precision, so that the interference suppression efficiency is greatly improved, and the interference can be suppressed accurately and effectively subsequently.

The application discloses a kind of ball screw pair fault diagnosis methods based on short-time window energy kurtosis spectrum, current, position and speed and other servo control signals in the running process of ball screw pair are collected, according to position signal and speed signal extract stable running section;Zero-mean processing is carried out to stable running section current signal and short-time Fourier transform is used to construct time-frequency spectrum matrix;According to preset bandwidth, sub-band division is carried out to time-frequency spectrum matrix and the energy of each sub-band in each short-time window is calculated;Further combined with position signal, the energy of sub-band is mapped to lead space, and lead-energy matrix is formed;The kurtosis and / or negative entropy of the energy distribution sequence of each sub-band in the lead direction is calculated, to determine the fault sensitive band;According to the lead energy anomaly corresponding to fault sensitive band, fault diagnosis, fault location and fault degree evaluation are completed;The application has the advantages of strong working condition adaptability, small amount of calculation, good interpretability and easy engineering deployment.

The invention provides a tensegrity module dynamic behavior analysis method based on an energy-preserving matrix perturbation method, which is different from an existing modeling method aiming at a tensegrity structure that a rope and a rod piece are simulated into a rod without considering bending rigidity or both the rope and the rod piece are regarded as beams. The string units are adopted to model the rope, and the actual vibration condition of the structure can be reflected. Taking a three-rod tensegrity structure module unit as an example, firstly, dynamic stiffness matrixes with prestress are established for ropes and rod pieces in the structure respectively; solving the established dynamic stiffness matrix by adopting a W-W algorithm to obtain a structure frequency; and finally, structural response is obtained and verified under the condition of existing frequency, and verification results show that the method has good calculation efficiency on the premise of ensuring accuracy.

The invention relates to the technical field of engine testing, in particular to an aero-engine performance detection method, which comprises the following steps of: acquiring vibration signals mounted on an engine shell and blade tip timing data at the periphery of a gas compressor blade, and performing segmented processing on the continuous vibration signals according to an engine rotating speed period; and calculating time-frequency distribution of each signal segment to obtain a time-frequency energy matrix. According to the method, the vibration signals and the blade tip timing data are synchronously collected and segmented processing is carried out in combination with the rotating speed period, so that the frequency characteristics in different time periods can be completely extracted, and information missing caused by single time domain or frequency domain processing in a traditional method is avoided; furthermore, spectral density is calculated on a frequency domain and a cyclic frequency domain through a time frequency energy matrix, a two-dimensional spectrogram capable of reflecting energy distribution and cyclic characteristics at the same time is constructed, and full expression of characteristic information under multiple dimensions is guaranteed.

The invention discloses a frequency domain-time frequency domain adaptive time-varying filtering method with human-computer interaction characteristics, which comprises the following steps: manually selecting reference data points according to the energy distribution of signals in a time frequency domain, and obtaining an instantaneous frequency curve of a component to be extracted through cubic spline interpolation fitting; based on the short-time Fourier transform energy matrix and the cumulative distribution function, the instantaneous transmission band width at each moment is calculated in a self-adaptive mode; taking the instantaneous frequency as a center frequency and the instantaneous bandwidth as a transmission band boundary, constructing an elliptical digital band-pass filter bank, and forming a self-adaptive time-varying filter; performing time-frequency domain filtering decomposition on the original signal, and performing inverse short-time Fourier transform reconstruction to obtain a pure component signal; order spectrum / envelope order spectrum analysis is carried out on the components, and gear fault features are extracted. The method gives consideration to time domain and frequency domain information, achieves one-time filtering decomposition, is high in calculation efficiency, is high in anti-noise performance, and is suitable for the fault diagnosis of equipment with complex non-stationary signal features.

The application discloses a kind of PCCP pipeline abnormal vibration high frequency automatic identification method, system and equipment, belong to concrete pipeline vibration automatic monitoring field. Including: the modal decomposition is carried out to the broken wire vibration data monitored, and Hilbert spectrum calculation is carried out, obtain time-frequency spectrum;Calculate the vibration energy curve after each filtering with time variation;Curve is normalized, and the one-dimensional vibration energy data after normalization is dimension, form filter threshold-time-filtered energy matrix;Based on energy-time curve before filtering selects key analysis time period, and obtains the corresponding filter threshold-time-filtered energy matrix sub-matrix;To the row (or column) of each filter frequency threshold value corresponding to sub-matrix selects upper quartile and handles, form filter frequency threshold-normalized filtered energy mean curve;According to the maximum on the curve, obtain the highest frequency of PCCP pipeline abnormal vibration.The application can realize automatic identification.

The application relates to the field of electric digital data processing and discloses a metal surface processing quality detection method and system, which comprises the following steps: acquiring a two-dimensional gray data matrix of a surface object to be detected; mapping the matrix into a frequency energy matrix by using a frequency transformation operator and determining an energy decision threshold; extracting a local energy peak value coordinate set and locking a retardation radius according to the radial energy distribution of the local energy peak value coordinate set, so as to generate a dynamic retardation mask matrix; logically point-multiplying the dynamic retardation mask matrix and the frequency energy matrix and rearranging a basic diffuse energy integral value, so as to generate a residual frequency domain matrix; and reconstructing a spatial domain data matrix by using an inverse transformation operator. The application realizes orthogonal decoupling of interference characteristics and target characteristics in the data dimension, relies on a mask generation logic driven by a data stream to cope with working condition fluctuations, and enhances the high-fidelity reconstruction strength for weak abnormal signals.

The application relates to the technical field of electrical sensor measurement, and discloses a fault test method, system and equipment suitable for a fan converter, which comprises the following steps: collecting current data in an IGBT module of the fan converter and taking the current data as original current signals; screening a plurality of main frequencies of the original current signals; decomposing the original current signals to obtain a plurality of component signals and corresponding main frequency signals; screening a reference signal; obtaining variation abnormality of the component signals according to variation trend differences between the component signals and the reference signal; analyzing energy differences between the component signals and the reference signal in a time-frequency energy matrix to obtain energy difference indexes of the component signals; obtaining abnormality indexes of the component signals; and performing fault detection on the fan converter based on the abnormality indexes of the component signals. The application aims to solve the problem that high-frequency electromagnetic noise can affect signal performance of a current sampling loop and cover real fault characteristics.

The invention discloses a broadband stability analysis method of a doubly-fed fan-energy storage combined system, and relates to the field of broadband stability analysis of power systems. The method comprises the following steps: firstly, carrying out preparation work before data acquisition, further carrying out multi-channel synchronous sampling and obtaining four types of features, fusing the four types of features to form a continuous time sequence, and preprocessing the continuous time sequence to obtain a standardized feature set; performing broadband domain wavelet transform on the standardized feature set, and outputting a time-frequency energy matrix and a frequency table; and extracting a core feature set based on the time-frequency energy matrix, and outputting a single-frequency-band stability evaluation value, a double-fed fan-energy storage combined system stability level and a weak-frequency-band positioning result through the optimized broadband stability comprehensive evaluation model. The problems that in stability analysis of a traditional doubly-fed fan-energy storage combined system, broadband disturbance feature coverage is incomplete, a parameter calculation link is fragmented, weight setting is subjective and cannot adapt to dynamic changes of working conditions, and engineering landing performance is poor are solved.

This invention belongs to the field of positioning technology, specifically relating to a transient traveling wave positioning method for broken strand faults in overhead insulated conductors. The method includes: acquiring a single-end transient current signal of the line, obtaining a reconstructed signal through bandpass filtering, and performing an initial time-frequency domain transformation to obtain an initial time-frequency distribution; calculating the power spectrum and constructing a parallel time-varying parameter oscillator array to obtain multiple narrowband enhanced signals; performing a second time-frequency domain transformation on the enhanced signals to construct a fused time-frequency energy matrix; extracting the modulus maxima propagation path from the matrix; determining the arrival times of the initial traveling wave and the reverse polarity fault reflection wave based on the moment when the singularity characteristic index first enters the abrupt change threshold interval; and calculating the fault distance based on the calibrated traveling wave velocity and the single-end traveling wave ranging principle. This method effectively suppresses noise and enhances weak features, significantly improving the accuracy of wavefront identification and the reliability of single-end positioning.

The present application relates to the field of construction engineering structure health monitoring, and particularly relates to a distributed optical fiber intelligent monitoring and early warning system and method for deep foundation pit construction, which comprises the following steps: obtaining an optical fiber strain sequence and differentially extracting a gradient sequence; performing multi-scale space-frequency decomposition to obtain a space-frequency energy matrix; extracting a slowly varying component to construct a background model, calculating a logarithmic domain difference to generate a residual saliency map; statistically quantifying multi-scale gradient direction consistency to quantify edge confidence, and adaptively adjusting a smoothing scale to output refined features; combining feature purity and spatial dispersion to generate a comprehensive atlas through weighted fusion; and constructing an energy function considering spatial adjacent consistency and performing global optimization to solve the problem. The present application effectively improves the weak anomaly detection and early warning accuracy by segmenting physically coherent abnormal areas to trigger early warning.

The embodiment of the invention discloses an energy storage battery dynamic early warning method and device for a typhoon environment. One specific embodiment of the method comprises the following steps: acquiring in-cabin environment parameter information and electrical parameter information of an energy storage battery through a multi-mode sensing network; compensating the temperature information to obtain compensated temperature information; determining a node energy matrix of the target number of sub-bands corresponding to the voltage information; performing feature screening on the energy features of the target number of sub-bands to obtain screened voltage feature information; fusing the compensated temperature information, the humidity information, the air pressure information, the battery impedance information and the screened voltage characteristic information to obtain fused characteristic information; inputting the fused feature information into a pre-trained dynamic boundary model to obtain a dynamic safety boundary temperature value; and determining a risk level to execute a graded early warning operation. According to the embodiment, the early warning accuracy of the energy storage battery in the typhoon environment is improved, and the early warning window period is prolonged.

The application discloses a wind farm line fault identification method and device, a storage medium and an electronic device. The method comprises the following steps: acquiring a fault current value set corresponding to each phase line of each wind turbine, wherein the fault current value set is composed of a plurality of fault current values within each preset time length before and after a wind farm line fault moment; performing data processing on each fault current value set by using a preset time-frequency analysis method to obtain a time-frequency matrix and an energy matrix corresponding to each fault current value set; performing statistical analysis by using a predetermined statistical method based on each time-frequency matrix and each energy matrix to obtain a plurality of fault characteristic values corresponding to each fault current value set; and identifying each fault characteristic value based on a preset fault type identification model and a preset fault branch identification model to obtain a wind farm line fault identification result. The method can improve the identification efficiency of the wind farm line fault.

The application discloses a kind of d-POD and Bi-LSTM-based impeller machine transient flow field fast prediction method. Construct full-cycle flow field snapshot matrix;Through data acquisition code, the physical quantity of flow field area of interest is extracted from simulation data, Hankel augmented matrix is constructed and standardization is completed;The time series augmented original matrix constructed is decomposed by d-POD, and the spatial mode matrix, time coefficient matrix and mode energy matrix are obtained;Bi-LSTM model is trained;The historical time series time coefficient of the predicted working condition is outputed by the model to predict the time coefficient sequence of future time;The physical quantity data reconstructed is matched and bound with the node coordinates and topological structure information of the original flow field grid one by one, to supplement the complete grid information for the restored physical quantity, according to the CFD post-processing standard format.dat File is generated, and the visualization output and subsequent engineering application of predicted flow field are completed.The present application is used to solve the core dilemma that precision and cost are difficult to consider in the prior art.

This invention provides a SEHWS energy prediction method based on double exponential moving average and an SEH wireless sensor, belonging to the field of energy prediction technology for solar energy harvesting wireless sensors. The method includes: collecting and processing historical energy harvesting data, and constructing historical... D Daily Energy Matrix E ; Parameters in the calculation model μ D ( d , n ), B ( d , n ), ω and γ Based on historical data, four parameters are substituted into the DEMA energy prediction model, and the energy collected in the previous time slot is compared with the energy collected in the current time slot. n The weighted calculation is performed by taking the average of the actual energy collected over the past few days, and the result is... n Predicted value of time slot harvesting energy E(—)( d , n The SEH wireless sensor consists of a microcontroller, a data acquisition module, a solar energy collection module, a memory, a wireless communication module, and a power management module.

The application discloses a Doppler-code phase two-dimensional joint search same-frequency multi-target signal detection method and relates to the field of spaceflight measurement and control. The application generates a global energy matrix through two-dimensional joint correlation calculation and incoherent accumulation at a receiving end according to the Doppler frequency shift caused by satellite movement and the code phase offset caused by signal propagation time delay difference, calculates an adaptive threshold, suppresses strong signal sidelobe interference by defining a protection area, and improves weak signal detection probability to more than 90%. The application allocates tracking channels in descending order of energy, and achieves the purpose of efficient detection of multiple targets at the same time. The application is especially suitable for Doppler-code phase two-dimensional joint search same-frequency multi-target signal detection in a low-orbit satellite constellation or a dense satellite network, and solves the problems of low spectrum utilization and complex pseudo code management of traditional frequency division / code division technology.

The invention relates to a storage tank defect detection method and device based on meta transfer learning and frequency dispersion prior, and belongs to the technical field of nondestructive testing. The method comprises the following steps: carrying out continuous wavelet transform on an electromagnetic ultrasonic signal to obtain a time-frequency energy matrix; introducing group velocity frequency dispersion prior, performing nonlinear mapping on a time axis into an equivalent propagation distance axis, and constructing a two-dimensional frequency dispersion compensation feature map and an equivalent distance map; constructing a defect identification network through meta-learning and small sample migration by utilizing data of the source domain and the target domain; and inputting the feature map into the network, calibrating local gain and constraining global physical association by using an equivalent distance map through a built-in space-time attenuation weighted global enhancement module, and finally outputting a defect category. According to the method, physical prior and meta transfer learning are fused, frequency dispersion distortion and far-field attenuation interference are eliminated, the advantages of model cross-domain feature extraction and rapid adaptation are brought into play, and cross-working-condition high-precision defect recognition and adaptive updating are achieved under the small sample condition.

This invention belongs to the field of positioning technology, specifically relating to a transient traveling wave positioning method for broken strand faults in overhead insulated conductors. The method includes: acquiring a single-end transient current signal of the line, obtaining a reconstructed signal through bandpass filtering, and performing an initial time-frequency domain transformation to obtain an initial time-frequency distribution; calculating the power spectrum and constructing a parallel time-varying parameter oscillator array to obtain multiple narrowband enhanced signals; performing a second time-frequency domain transformation on the enhanced signals to construct a fused time-frequency energy matrix; extracting the modulus maxima propagation path from the matrix; determining the arrival times of the initial traveling wave and the reverse polarity fault reflection wave based on the moment when the singularity characteristic index first enters the abrupt change threshold interval; and calculating the fault distance based on the calibrated traveling wave velocity and the single-end traveling wave ranging principle. This method effectively suppresses noise and enhances weak features, significantly improving the accuracy of wavefront identification and the reliability of single-end positioning.

The invention discloses a sound source position and frequency joint characterization method in acoustic imaging, and belongs to the field of microphone array signal processing, and the method comprises the steps: collecting time domain data through a microphone array, converting the time domain data into a plurality of sub-band data through short-time Fourier transform, and constructing an observation model; establishing a sparse Bayesian learning model based on the observation model, performing probability modeling on noise and signals, and setting prior distribution; utilizing array data to iteratively update model parameters until convergence; acquiring a position-frequency energy matrix according to the convergence parameter; a sound source position is determined according to a non-zero line in the position-frequency energy matrix, a frequency sequence is generated for the sound source position, a joint visual graph in a concentric circle or contour line form is constructed, each geometric layer corresponds to a sub-band, and a visual attribute represents an energy amplitude; and finally, superposing the visual graph and the video image. According to the invention, joint visual display of the sound source position and the frequency is realized, and frequency characteristic monitoring and sound source distinguishing are supported.

The invention relates to a fiber bragg grating perimeter intrusion signal processing method based on self-adaptive time-frequency optimization, and belongs to the technical field of sensing application of optical fiber sensors. In the process of the method, firstly, vibration signals caused by multiple types of intrusion events are obtained through a distributed fiber bragg grating sensor array arranged along the perimeter; and signal acquisition is realized through a wavelength demodulator and a computer. In a signal processing flow, firstly, multi-scale decomposition of an intrusion signal is realized by using steady-state wavelet transform, and main vibration characteristics are reserved; then, in a time-frequency analysis stage, frequency band energy of sub-signals subjected to steady-state wavelet transformation is calculated, a mapping relation with a frequency band is established, and a scale energy matrix is solved; and calculating a logarithmic power spectrum matrix of the signal through fast Fourier transform. And establishing a mapping relation between the power spectrum matrix and the scale energy matrix based on taking the scale energy as a prior constraint, and correcting the power spectrum to obtain a self-adaptively optimized time-frequency energy diagram. The purpose of fiber bragg grating perimeter intrusion signal processing is achieved through the fiber bragg grating sensing network.

Embodiments of the present application disclose a downlink precoding method, device, equipment and storage medium. An uplink channel estimation sample is obtained according to an uplink reference signal; a beam energy matrix is determined based on the uplink channel estimation sample; and a downlink precoding matrix is determined based on the beam energy matrix. The downlink precoding method provided by the embodiments of the present application first determines the beam energy matrix based on the uplink channel estimation sample, and then determines the downlink precoding matrix based on the beam energy matrix. The system time-frequency resource overhead can be reduced, and the problems of decoding error on the user equipment side and system performance decline caused by directly using the uplink channel estimation result for downlink precoding can be avoided.

The application relates to a kind of air blower noise positioning imaging method, by the noise data of the surrounding environment of air blower when not running and running is collected, the noise data of the surrounding environment of air blower when running is screened, the region where the decibel value is highest is taken as non-synchronous measurement area, non-synchronous measurement is carried out to the air blower in operation, the non-synchronous measurement data of air blower in multiple positions is obtained, the non-synchronous measurement data of air blower in multiple positions obtained is preprocessed, multiple non-synchronous measurement data of air blower after preprocessing is obtained, the energy spectrum matrix construction is carried out to the non-synchronous measurement data of air blower after preprocessing obtained, multiple energy spectrum matrices are obtained, then based on the space position of each energy spectrum matrix, diagonalization arrangement is carried out, and the energy matrix to be filled is obtained.