388 results about "Correlation function" patented technology

The invention relates to the technical field of anomaly detection, and discloses a context-aware-driven multi-dimensional anomaly detection early warning method. The method comprises the following steps: collecting real-time context data in a target monitoring scene, and generating an initial feature set containing an environment parameter sequence and a behavior pattern map; a first detection model and a second detection model matched with the scene type are constructed according to the scene types, the first model comprises a dynamic correlation function of environment indexes and abnormal probabilities, and the second model comprises a nonlinear mapping rule of behavior characteristics and risk levels; and based on the real-time context deviation degree and the characteristic fluctuation coefficient, a target model is triggered to generate a dynamic early warning instruction, and the dynamic early warning instruction is pushed to an execution module to adjust a trigger threshold of an abnormal response strategy or a priority of a risk disposal process. According to the method, multi-dimensional data is combined, the adaptability and accuracy of anomaly detection are improved through dynamic model triggering and response strategy adjustment, and the method is suitable for various monitoring scenes.

The invention relates to the technical field of data processing, in particular to a standardized detection result calibration method based on multi-modal fusion, which comprises the following steps of: performing high-precision space-time synchronization and standardization on different modal data, performing dynamic compensation by utilizing timestamp alignment, a cross-correlation function and an IMU (Inertial Measurement Unit), and performing dynamic parameter adjustment by adopting a local abnormal factor algorithm. Carrying out cross validation by utilizing inherent relevance of multi-modal data, constructing and continuously optimizing a high-confidence system state representation model, and realizing real-time identification and self-adaptive calibration of model parameters by adopting a Bayesian online learning framework; the method further comprises the steps that closed-loop recalibration is conducted through multi-sensor cross validation and residual analysis, an optimal action sequence is generated through a reinforcement learning agent, accurate prediction of key indexes of a monitored object is achieved, instant calibration and situational prediction can be conducted according to a specific event, and the intelligent level and maintenance efficiency of system monitoring are comprehensively improved.

The invention belongs to the technical field of underwater acoustic engineering and digital signal processing, and particularly relates to a fractional delay FIR (Finite Impulse Response) phase calibration method and system of a multichannel sonar system. Comprising the steps of signal acquisition and reference channel selection; high-precision relative delay estimation; calculating a cross-correlation function of other channel signals and the reference channel signal, performing coarse estimation by searching a peak point of the amplitude of the cross-correlation function, and performing fine estimation on the peak position by using a parabola interpolation method to obtain the delay time of each channel relative to the reference channel; designing an FIR fractional delay filter; digital filtering and phase calibration; verifying a calibration effect; and calculating the phase of each channel signal at the target frequency point after calibration, and counting the standard deviation of each channel signal so as to evaluate the improvement degree of phase consistency. The method aims at overcoming the defect that traditional integral multiple sampling delay correction precision is insufficient, high-precision phase compensation of a sub-sampling point level is achieved, and therefore the performance of algorithms such as beam forming of a multi-channel sonar system is remarkably improved.

The invention relates to the technical field of data center dynamic modeling, and discloses a twin model dynamic modeling method for a data center DCIM platform, which comprises the following steps: constructing a discrete state space model containing a thermal coupling matrix and a system matrix, collecting real-time power and temperature time sequence data, and calculating a cross-correlation function to lock hot air dynamic transmission lag time; calculating cut-off frequency based on physical attributes of the cabinet and decomposing data into high and low frequency components by using a complementary filter; according to the method, the model parameters are made to return to a physical source through a frequency domain decoupling mechanism, the problem of aliasing of airflow coupling and structural thermal inertia parameters in a traditional single-scale identification method is solved, and the method is suitable for large-scale identification. And the physical authenticity and prediction robustness of the twin model under a complex working condition are improved.

The invention relates to the technical field of process control, and discloses a multiple cyclic utilization process control method of regenerated polyethylene for tailing seepage prevention, which comprises the following steps: synchronously acquiring melt pressure, screw driving motor current and a control input sequence, calculating a cross-correlation function of the current and the pressure, and identifying physical transmission lag time; monitoring an uncommanded residual component of the current in real time, deducing an impending pressure fluctuation amplitude based on a cross-correlation function, and generating an inertia feedforward compensation amount; according to the method, a dual-time scale model is utilized to update parameters online and construct a disturbance observer to generate a feedback compensation control quantity, feedforward and feedback compensation are superposed to a basic output quantity to generate a final driving instruction, a heterogeneous signal time sequence correlation mechanism is utilized, reverse adjustment is carried out before pressure fluctuation is transmitted to a machine head through a screw, and the pressure fluctuation is reduced. And a control blind area caused by physical transmission lag is avoided.

The invention relates to the technical field of bridge engineering structure health monitoring, in particular to a service life prediction method and system for a bridge connection part, and the method comprises the steps: collecting the strain of a grouting sleeve, a reinforcement-grouting interface ultrasonic reflection signal and environment temperature and humidity data through a distributed sensor array; a three-dimensional dynamic void rate model is generated through fusion of a spatial topological mapping algorithm, a correlation function of load circulation and void expansion is established, the dynamic void rate is input into a bond strength coupling degradation model, after strength attenuation is quantized in combination with steel bar corrosion data and bond failure early warning is triggered, stress redistribution is calculated through multi-physics coupling simulation, and the dynamic void rate is obtained. Early warning is taken as a starting node, the actual load spectrum and temperature and humidity data are combined, Monte Carlo sampling is adopted to simulate rigidity degradation and output the residual life probability, the system comprises a multi-source collaborative sensing unit, a micro-void evolution analysis unit and a life prediction decision unit, and the safety control precision of bridge connection parts is improved.

The invention discloses a distributed OFDR sensing signal demodulation method and system based on local ridge line tracking, relates to the technical field of optical fiber sensing, and is used for solving the problem that a traditional cross-correlation algorithm is difficult to consider robustness and real-time performance at the same time. The method comprises the following steps: respectively processing a reference beat frequency signal of a sensing optical fiber to be measured in a strain-free state and a measurement beat frequency signal of the sensing optical fiber to be measured in a strain state to obtain a reference complex Rayleigh scattering signal and a measurement complex Rayleigh scattering signal containing a plurality of sensing positions along the optical fiber; calculating a cross-correlation function based on the two signals; stacking the cross-correlation functions corresponding to all sensing positions along a distance domain, and constructing a two-dimensional cross-correlation thermodynamic diagram matrix; performing filtering processing and weighting processing on the two-dimensional cross-correlation thermodynamic diagram matrix to obtain an optimal frequency drift distance; and demodulating based on the optimal frequency drift amount to obtain strain distributed along the to-be-measured sensing optical fiber. According to the invention, high-robustness and rapid demodulation of the signal in an application scene with extremely high real-time requirement can be realized.

The invention discloses an intelligent identification method for an electricity larceny prevention behavior of an electric energy metering box, which relates to the technical field of electricity larceny behavior identification and comprises the following steps: continuously acquiring data of the metering box, calculating a difference value between metering energy and estimated energy, extracting a symbol direction to generate a metering deviation accumulation index and determining an abnormal starting moment; taking the moment as an anchor point to extract a current ripple phase and a zero-sequence current direction, calculating a correlation function of a differential symbol sequence, and determining a characteristic response time delay and a coupling weight search range through combined evaluation of time delay peak sharpness and time delay peak stability to construct a coupling projection signal; traversing a search range in a verification window to calculate forward and reverse cumulants, and solving a self-consistent coupling weight and an abnormal effective moment; a coupling projection is constructed by using the self-consistent coupling weight and the time delay, and a verification accumulation index is generated; when the overlap ratio of the verification accumulation index and the metering deviation accumulation index falls into a preset credible interval, determining that an electricity stealing behavior exists; according to the invention, the accuracy and reliability of electricity stealing behavior identification are improved.

The invention relates to the technical field of power systems, and discloses a cable defect positioning method, system and device, a medium and a product, and the method comprises the steps: taking a Gaussian envelope linear chirp signal as an initial incident signal for frequency domain reflection, optimizing the signal characteristic parameter of the initial incident signal, obtaining an incident signal, and carrying out the positioning of a cable defect. The method comprises the following steps: exciting a target cable through an incident signal, obtaining a reflection signal on a preset measuring point of the target cable, respectively carrying out time-frequency conversion on the incident signal and the reflection signal to obtain an incident time-frequency domain signal and a reflection time-frequency domain signal, and obtaining a time-frequency domain signal and a reflection time-frequency domain signal on the basis of a cross-correlation function. The peak position of a cross-correlation function is determined through the incident time-frequency domain signal and the reflected time-frequency domain signal, the signal propagation defect time delay of the target cable is determined according to the peak position of the cross-correlation function, and the defect position of the target cable is determined according to the signal propagation defect time delay and the propagation speed of the incident signal. Therefore, surrounding signal interference can be filtered out, and the accuracy of cable defect positioning is improved.

The invention discloses a temperature measurement calibration method and system for an infrared temperature measurement thermal imager, a medium and a product, and the method comprises the steps: uniformly selecting a plurality of temperature points in a temperature measurement range, and building a first mapping relation between a response value and a temperature measurement value of the infrared temperature measurement thermal imager through a least square method; based on the acquired environment temperature, establishing a first correlation function of the shutter response value and the environment temperature; based on the environment temperature, establishing a second correlation function of the blackbody response value of the middle reference temperature and the environment temperature; on the basis of a preset three-item calibration model, the first correlation function and the second correlation function are combined, and the response value of the temperature measurement thermal imager is calibrated; based on the calibrated response value of the temperature measurement thermal imager and the first mapping relation, temperature data after pixel difference calibration, temperature drift calibration and additional radiation calibration are calculated; according to the invention, the temperature measurement precision of the infrared temperature measurement thermal imager is improved, the calibration process is simplified, the implementation difficulty is reduced, and the calibration cost is reduced.

The invention discloses an underwater sound environment sensing method based on multi-array-element sparse channel estimation. An underwater sound receiving end receives signals transmitted through an underwater sound multipath channel through a multi-array-element array; performing Hilbert transform on the receiving signal of each array element to obtain an analysis signal, and calculating a cross-correlation function of the analysis signal and the transmitting signal; based on the cross-correlation function, sparse channel parameters, including path amplitude and time delay, of each array element are estimated by adopting an orthogonal matching pursuit algorithm combined with a constant false alarm detection dynamic threshold value; the method comprises the following steps: constructing an array response vector by using sparse channel parameters of a multi-array element array, and searching and estimating angles of arrival, including a direction angle and a pitch angle, of a multipath signal through a spatial spectrum peak value; and based on the arrival angles, amplitudes and time delays of the direct path and the reflection path, inverting an underwater environment structure through a ray acoustic theory, including a reflection point distance and a reflection surface normal vector, so as to realize three-dimensional perception of the underwater reflector. According to the invention, multipath resolution can be improved, and false alarm and missing detection can be effectively reduced.

The invention discloses a feature point identification method of a river hydrodynamic condition. The method comprises the following steps: S1, hydrological data collection; s2, dividing flow levels and simulating a flow field of each flow level; s3, arranging alternative control sections; s4, determining a target control section; and S5, constructing a correlation function to determine a target feature point. According to the method, historical hydrological and geographic data of a to-be-monitored river reach are utilized, hydraulic engineering simulation software is combined, a target control section is selected and determined by calculating section similarity indexes, relevancy values of all nodes in the target control section are calculated and selected through a constructed relevancy function, and the flow velocity of the nodes is combined; determining alternative feature points, and finally rejecting points influencing navigation, namely target feature points; the identified feature points are optimal monitoring points for arranging the river flow velocity monitoring device, a scientific basis is provided for reasonably arranging flow velocity monitoring points, only the water flow velocity of a limited number of feature points can be monitored, and the hydrodynamic change condition of the whole river can be mastered.

The invention discloses an intelligent monitoring method and device for operation energy efficiency of a transformer. The method comprises the following steps: acquiring multi-dimensional time sequence data such as iron loss and copper loss of the transformer; generating a cross-domain influence factor or a cross-domain influence matrix for quantifying the cross-domain correlation strength of the iron loss and the copper loss by calculating a cross-correlation function between related time sequences of the iron loss and the copper loss; and the correlated quantitative features are fused with the standardized loss trajectory and the working condition parameters, and a machine learning prediction model is constructed, so that a hidden fault mode of'iron loss-copper loss cross-domain correlated degradation 'in which the copper loss is driven to abnormally increase by iron loss deterioration is identified and early warned. According to the method, the defect of isolated analysis of loss in the traditional technology is overcome, early warning and traceability of a specific composite fault can be realized, and the safety and reliability of operation of the transformer are remarkably improved. The invention further provides a device for executing the method.

The invention discloses a configuration acquisition method and system for realizing a maximum violation five-setting CHSH measurement device, and relates to the technical field of quantum information processing, and the method comprises the steps: S1, obtaining the probability amplitude of the pure state of a pair of two-dimensional non-maximum entangled particle A and particle B, and calculating the concurrency; s2, constructing an incidence matrix based on the concurrency, and mapping the measurement vector of the particle B from the Bloch spherical surface to the ellipsoid surface by using the incidence matrix; s3, taking five points on the same plane on the ellipsoid as vertexes of a five-pointed star, wherein a perimeter formula of the five-pointed star is equivalent to a correlation function maximum value formula; s4, traversing vertex positions of the five-pointed star to obtain a maximum perimeter value; s5, obtaining the measurement vector of the particle B and the measurement vector of the particle A to obtain the optimal measurement configuration; and S6, configuring a quantum measurement device to measure the particles A and B. According to the method, the problem of setting the maximum value of the CHSH correlation function is converted into the problem of solving the maximum value of the perimeter of the ellipsoid inscribed five-pointed star, and the optimal measurement scheme is obtained through simple numerical fitting.

The invention provides a vehicle fault identification and driving behavior early warning method based on multi-modal feature fusion, and relates to the field of vehicle fault diagnosis and safe driving, and the method comprises the steps: collecting a vibration signal, an acoustic signal and a driving operation signal, extracting a fault feature and a behavior feature, calculating a time delay cross-correlation function to obtain a time delay influence spectrum, and carrying out the early warning of a driving behavior. And performing recursive calculation to obtain an evolution trajectory curve, calculating a fault-behavior coupling risk index by detecting the deviation of the evolution trajectory curve from a preset stable region, and generating a multi-modal early warning signal of a corresponding intensity level according to the risk index. The method has the advantages that correlation analysis of faults and driving behaviors is achieved, and the accuracy and timeliness of early warning are improved.

The invention provides a public signal assisted RSMA ISAC system sensing method. The method comprises the following steps: transmitting a sensing signal, a public signal and a private signal through a base station; obtaining a covariance matrix of the transmitted signal by accumulating the transmitted beam forming vectors of the common signal and the sensing signal; constructing a cross-correlation function of any two sensing target directions; traversing the cross-correlation function to obtain a sensing target angle corresponding to the peak value of the reflected signal; calculating the distance from the sensing target to the base station according to the time delay of back-and-forth propagation of the target transmitting signal; calculating the position of the sensing target relative to the base station according to the sensing target angle and distance; according to the invention, the common signal is incorporated into the sensing signal to improve the sensing performance, so that the sensing capability of the RSMA ISAC system is improved.

The invention provides a cable fault early warning method and system, a storage medium and a program product, and relates to the technical field of electrical variable measurement. And calculating the absolute value of the amplitude difference under adjacent sampling points, comparing the absolute value with the relative change value, and screening out signal parts which are really changed and possibly predict faults. Waveform segments in a preset time window before and after the traveling wave starting point are extracted to generate a front-end feature segment and a rear-end feature segment; carrying out discretization, Fourier transform and other operations on the characteristic fragments, converting a complex waveform of a time domain into a frequency domain for analysis, calculating time delay by searching a peak position in a time domain cross-correlation function sequence through correlation calculation of the frequency domain, and comparing with a traveling wave theoretical propagation time difference calculated by detecting the length of a cable between groups; if the difference value is greater than the threshold value, the fault hidden danger is judged and early warning is triggered, the cable section with the fault hidden danger is positioned, the fault repair efficiency is improved, and the normal power supply order and the normal operation of the power utilization unit are ensured.

An example computer-implemented method for determining patient-specific tumor dynamics is described herein. The method includes receiving an image of a tissue sample that includes a distribution of tumor cells and non-tumor cells; applying a spatial correlation function to the image; and obtaining a power spectral density of the spatial correlation function of the image. The method also includes fitting the power spectral density of the spatial correlation function of the image to the power spectrum of a reaction-diffusion model; and inferring a patient-specific tumor-dynamic coefficient based on the reaction-diffusion model of cancer.

The present invention relates to the field of metal powder processing, and in particular to a method and system for intelligently controlling the sintering process of powder metallurgy metal materials. The method comprises: obtaining a temperature curve of the powder metallurgy sintering process, determining the offset of each curve using a cross-correlation function and aligning them, determining the segment length based on the segment suitability of the local area, analyzing the abnormality reference degree based on the correlation between the Mahalanobis distance of each segment and the sintering quality, obtaining the overall abnormality degree of each curve through normalization processing and weighted calculation, determining whether an abnormal temperature curve exists based on the overall abnormality degree and a preset abnormality degree threshold, and if the abnormality degree exceeds the preset threshold, issuing an early warning of abnormal sintering process and prompting adjustment of control. The present invention optimizes temperature control by accurately detecting local abnormalities, reducing production costs, and improving product quality and production efficiency.

The invention discloses a water conservancy project full life cycle operation and maintenance management method and platform, and relates to the technical field of water conservancy project management.The weir crest water level Hw, the gate flow Qo, the gate opening and closing pressure Pg, the structure dip angle Gq and the iron concentration cFe are accurately collected through a multi-source physical sensing unit; and the sensor type, the arrangement position and the acquisition condition corresponding to each parameter highly accord with the operation characteristics of the water conservancy project, so that the data source is stable, the coverage is wide, and a high-frequency real-time data sensing system is formed. The mechanism breaks through the problem of low credibility of previous parameters, and lays a high-quality data foundation for subsequent operation state modeling and situation map construction. A structural stability correlation function constructed based on a water conservancy physical mechanism is introduced as an evaluation index, sliding window recognition and inversion repair are performed on abnormal fluctuation in original data, and different from a conventional statistical elimination method or an interpolation filling method, reasonable traceability correction can be performed by using a known physical relationship of a system.

The invention relates to the technical field of ultrasonic measurement, and discloses a wind speed and humidity combined measurement method, device and equipment and a storage medium, and the method comprises the steps: constructing a transducer system, and carrying out the pre-calibration of the transducer system; collecting reciprocity measurement data by using the transducer system, and performing cross-correlation operation by combining a preset Golay sequence to obtain a cross-correlation function; performing wind speed calculation and humidity inversion based on the cross-correlation function to obtain wind speed data and humidity data; constructing a joint estimation model, and performing parameter calculation by using the joint estimation model to obtain a calculation result; performing exception processing on the resolving result to obtain a wind speed and humidity measurement result; the integrated detection of the wind speed and the humidity is realized by constructing a transducer system, pre-calibrating, collecting reciprocity measurement data, carrying out signal processing, extracting propagation time difference and dispersion characteristics, respectively calculating the wind speed and the inversion humidity, and further constructing a joint estimation model to carry out fusion data resolving.

The invention discloses a detection method, equipment and medium for a new energy high-power direct-current charging pile, and relates to the technical field of charging pile stability detection, and the method comprises the steps: controlling a direct-current electronic load to generate a load disturbance signal at N characteristic working points, collecting instantaneous value change data through a broadband data collection center, and calculating the stability of the charging pile according to the instantaneous value change data; and based on the dynamic load disturbance signal and the instantaneous value change data, calculating the pulse response characteristics of the to-be-tested DC charging pile at the N characteristic working points through a correlation function analysis method, constructing a dynamic impedance characteristic model, and based on the safe working area three-dimensional boundary map, the electric energy quality indexes of the N characteristic working points and the dynamic impedance characteristic model, calculating the dynamic impedance characteristic of the to-be-tested DC charging pile. And evaluating and diagnosing the comprehensive performance of the direct current charging pile to be tested. According to the direct current charging pile comprehensive performance detection method based on dynamic load disturbance, accurate physical examination of the overall performance of the charging pile is achieved, and the detection depth, precision and predictability are improved.

The invention discloses a seismic wave velocity change analysis method under a hydraulic fracturing condition, and belongs to the technical field of seismic wave propagation analysis. The method comprises the following steps: S1, acquiring data by using a plurality of seismic stations and removing transient signals by using a long and short window method; s2, calculating a cross-correlation function between the two stations; s3, extracting a tail wave signal and estimating relative velocity change by using mobile window cross-spectrum analysis; s4, extracting a group velocity frequency dispersion curve based on a cross-correlation function, and constructing a two-dimensional velocity model before and after fracturing; and S5, generating a speed image through inversion, and calculating a difference image to reveal speed change characteristics. According to the method, the tail wave sensitivity and the moving window cross-spectrum analysis are combined, the speed change and the anisotropy characteristics of the speed change are accurately quantified, the method is suitable for the complex geological environment, and a new interpretation framework is provided for the influence of hydraulic fracturing on the underground structure.

The invention discloses a regional wind speed meteorological reference station representativeness evaluation method based on a correlation function field, a medium and a program product. The regional wind speed meteorological reference station representativeness evaluation method comprises the following steps: collecting multi-year day-by-day wind speed data of a high-density meteorological observation station in a target region and environment information of the observation point; selecting an independent sample of day-by-day wind speed data in each same time period in the region; establishing a correlation function field between every two stations, and fitting a relation model of correlation functions and distances; estimating a standardized observation random mean square error; calculating the relative standard deviation generated by replacing the target point wind speed truth value data with the reference station wind speed observation data; and evaluating the excellent grade of the spatial distance range represented by the wind speed of the reference station. The method can achieve the good representative evaluation of the reference station in the distance range, and has important practical values for the selection of a reliable meteorological reference station in the climate feasibility demonstration of wind power development site selection, urban and rural construction planning and the like, the evaluation of extreme climate risks and the calculation of the accuracy of engineering meteorological parameters.

The invention discloses a large-scale unstructured data joint processing method and system. The method comprises the steps that S1, large-scale unstructured data is collected, and a metadata feature library containing dynamic updating and index retrieval optimization is constructed; s2, constructing a federated index based on the dynamic metadata feature library, constructing a cross-domain joint index on the basis of the federated index, and performing layered federated architecture optimization to obtain a cross-domain joint optimization index; s3, constructing a global correlation matrix based on the cross-domain joint optimization index to perform cross-domain correlation modeling, and obtaining a global correlation function through cross-domain correlation modeling; and S4, carrying out joint optimization solution based on the global correlation function to realize unstructured data joint processing, uniformly optimizing tasks such as clustering, label prediction and correlation rule mining by fusing a processing target function, and enabling the tasks to cooperate with each other, so that the whole data processing process is more intelligent and efficient, and the accuracy of a data processing result is improved.

The invention relates to the technical field of physical quantity measurement, and discloses a multi-physical quantity measurement method and device for a passive multi-parameter optical fiber sensing unit, and the method comprises the steps: synchronously collecting temperature, humidity, air pressure and inclination angle four-parameter optical signals, calculating a time sequence cross correlation function in real time, and quantifying the parameter coupling strength and causal conduction time delay; constructing an initial weighted causal map based on the time sequence causal index, automatically detecting a chain enhancement path, positioning an initial abnormal node, and iteratively predicting a subsequent fault probability; drawing a dynamic arrow chain along an enhanced path in the three-dimensional digital twin model by taking the initial abnormal node as a starting point, and rendering according to a fault probability; according to the method, discrete multi-physical-quantity abnormal signals are converted into topological and visual causal chains, full-link transparent mapping of abnormal sources-propagation paths-potential fault nodes is achieved, and the pre-judgment precision and operation and maintenance decision timeliness of the state evolution trend of a complex structure are remarkably improved.

The invention relates to a method (200) for calibrating a conversion chain (12) of an analogue signal receiver (10), which method comprises: - generating (205) a pseudo-random sequence (S) of states used for the formation (210) of a frequency-modulated analogue calibration signal (ANA_cal,mod); - injecting (215) this calibration signal into the conversion chain (12); - forming a digital signal to be processed (NUM_BB) by demodulating (220) an intermediate digital signal (NUM_int) received in response to the modulated analogue calibration signal (ANA_cal,mod); - determining (225) a correlation function R(NUM_BB,S) between the digital signal to be processed (NUM,BB) and the pseudo-random sequence (S); - determining (230) a transfer function (H) of the conversion chain based on the correlation function R(NUM_BB,S); and - where necessary, determining (235) a parameter (Ci) of a processing step at the output based on the transfer function (H).

A calculation method of karst underground reservoir capacity curve based on hydrogeological parameters, including the following steps: hydrogeological exploration, determination of karst underground water reservoirs scope, determination of water storage space, determination of relevant hydrogeological parameters based on hydrogeological tests, and underground reservoir capacity analysis. The invention uses the unit water permeability and the borehole line karst rate that are very easily obtained through the borehole pressure (injection) water test and combines it with a small amount of water pumping test, thereby obtaining a correlation function relationship through regression analysis between the specific yield and the karst rate that are difficult to obtain and the unit water permeability or the permeability coefficient; the underground storage capacity at the corresponding elevation is calculated according to the specific yield or the karst rate and the underground storage capacity curve is obtained, which can improve accuracy and reduce errors.

A method and an apparatus for transmitting a physical layer protocol data unit (PPDU) are provided. The method includes: generating a synchronization header field based on a first sequence or a third sequence, where a side lobe of a periodic cross-correlation function of the first sequence and a second sequence is a constant value, the first sequence is a binary sequence consisting of 1 and 0, the second sequence is a binary phase shift keying sequence corresponding to the first sequence, a side lobe of a periodic autocorrelation function of the third sequence is a constant value, and the third sequence is a binary phase shift keying sequence consisting of 1 and −1; and sending the PPDU on a target channel, where the PPDU includes the synchronization header field.

The invention discloses an osmotic pressure analysis method and device fusing model optimization and physical inversion and a medium, and the method comprises the steps: calculating correlation coefficients of a specified reservoir water level and osmotic pressure under different time lags based on cross-correlation function analysis, and recognizing a differential nonlinear feature corresponding to the maximum correlation coefficient; aiming at the differentiated nonlinear characteristics of different dam types, constructing a plurality of corresponding diagnosis prediction models in parallel, and establishing a model selection decision rule to select an optimal diagnosis model; according to delay parameters obtained through cross-correlation analysis, a permeability coefficient is reversely deduced through a pore medium heat transfer diffusion theoretical formula; according to the regression slope and the theoretical value attenuation factor of the optimal model, a permeability coefficient is reversely deduced in combination with a correction diffusion equation, credibility evaluation and weighted fusion are performed on the permeability coefficient, and a comprehensive permeability coefficient is calculated; and diagnosing the soil type and the permeability characteristic grade. According to the method, the propagation delay characteristic of reservoir water level change in the pore medium can be accurately quantified, and the inversion precision of the permeability coefficient and the engineering applicability are improved.