9 results about "Frequency curve" patented technology

This invention relates to the field of aquatic environmental ecological risk assessment technology, and specifically discloses a method for assessing the risk of anthropogenic heavy metal accumulation based on zonal background and baseline values. The method includes the following steps: Step 1, Zoning and sample collection of the study area: Zonal sampling and multi-element determination: Obtaining representative sediments and determining the content of the target heavy metals; Step 2, Calculation of zonal background values: Automatically identifying the curvature abrupt change points of the cumulative frequency curves of each zone using the curvature extreme value method, and using these as the theoretical upper limit of the background element concentration; Step 3, Calculation of zonal baseline values, representing the natural background content of the area that is unaffected or minimally affected by human interference. This method for assessing the risk of anthropogenic heavy metal accumulation based on zonal background and baseline values ​​fully considers the spatial heterogeneity within lakes by constructing background and baseline values ​​through zoning, avoiding errors caused by using a single background value, and making the calculation of anthropogenic contributions closer to the actual situation.

This invention belongs to the technical field of hydrometeorological extreme value theory, and provides an unbiased estimation method for rainfall probability distribution based on least squares fitting. Existing parameter estimation methods are numerous, each with its own specific applicable scope and advantages and disadvantages. The choice of method significantly affects the accuracy of generalized extreme value distribution parameter estimation. This invention comprehensively considers the advantages of five parameter estimation methods: Bayesian, GMLE, L-moments, MLE, and MPS. Based on least squares fitting, it determines the optimal weight coefficients of a single method, establishing an unbiased and efficient ensemble parameter estimation framework. By integrating multiple parameter estimation methods, the bias and variance of individual methods can be reduced, improving the robustness and reliability of parameter estimation, and providing a reference for accurately determining the rainfall frequency curve and design rainfall.

The application discloses a shallow sea heavy mineral sand mine resource exploration method and related equipment, and the method comprises the following steps: obtaining pre-research data of a target shallow sea area, predicting an exploration scheme based on the pre-research data, and arranging a bottom seismograph in the target shallow sea area based on the exploration scheme; collecting passive source micro-motion data by using the bottom seismograph, and extracting original data from the passive source micro-motion data based on a preset data quality standard; constructing a horizontal and vertical spectral ratio curve based on the original data, performing frequency spectrum separation on the horizontal and vertical spectral ratio curve, and obtaining a low-frequency curve of a bedrock resonance peak; constructing a palaeotopographic map through bedrock surface depth inversion based on the low-frequency curve; obtaining a regional geological model of the target shallow sea area, superimposing and analyzing the palaeotopographic map and the regional geological model, and obtaining an evaluation result of heavy sand mine resource potential. The application can effectively improve the exploration directivity and the accuracy of resource potential evaluation by identifying the change of ore-controlling landforms, and can be widely applied to the technical field of data processing.

This invention discloses a frequency-domain modal method for determining the stability of vehicle-to-grid oscillations in new energy systems, applicable to converter impedance measurement. Specifically, it involves: acquiring the topology and component parameters of an electrified railway traction power supply system; performing frequency scanning on the single-input single-output frequency-domain impedance obtained through measurement or mathematical modeling in the frequency band to be analyzed, forming the system frequency-domain node admittance matrix at each frequency; performing eigenvalue decomposition to obtain the amplitude-frequency curve of the modal admittance or modal impedance; determining the oscillation frequency based on the extreme values ​​of the curve; determining the system stability based on the real and imaginary parts of the modal admittance or impedance at the oscillation frequency; and calculating the participation factor of each node in the unstable oscillation mode. This invention is applicable to low-frequency oscillation stability analysis of traction power supply systems with arbitrary topologies that do not contain three-phase converters. The SISO frequency-domain impedance of the single-phase voltage source converter interface power supply and locomotive load can be directly measured through impedance scanning without the need for dq-domain conversion.

The application discloses a target motion parameter estimation method and system based on a bistatic Doppler time-frequency curve; a plane rectangular coordinate system is established with a receiver position as an origin, a transmitter position is a known fixed coordinate, and a target is assumed to be a uniform linear motion; according to analytical expressions of distances between the transmitter and the target and between the receiver and the target, a bistatic equivalent path length is constructed, and an analytical expression of Doppler variation with time is derived based on a Doppler physical model; a target Doppler time-frequency curve is sampled at multiple time points to obtain a Doppler measurement vector, and outputs of the analytical model at corresponding time points are combined to form a model vector, so that an observation equation with target motion parameters as unknown quantities is formed; and a nonlinear least square algorithm is used to estimate the target motion parameters. The application has the advantages of not needing distance measurement, complete theoretical basis, high estimation precision and easy engineering implementation, and can be used for multi-station radar target trajectory matching and information fusion.

The application relates to a power equipment fault detection method and system based on sound feature analysis. The method comprises the following steps: determining a deviation coefficient of a voiceprint segment according to the difference between the amplitude of a sampling point in the voiceprint segment and a preset amplitude; determining a maximum value gathering coefficient according to the distance between the maximum value corresponding frequency value and other frequency values in a frequency curve, the amplitude corresponding to the other frequency values, and the similarity between the frequency curves according to the difference between the maximum value gathering coefficient and the corresponding maximum value gathering coefficient; determining a time sequence degradation coefficient of the voiceprint segment according to the deviation coefficient of the voiceprint segment in a voiceprint sequence to which the voiceprint segment belongs and the similarity between the corresponding frequency curves; determining a fault weight of the voiceprint segment according to the deviation coefficient of the voiceprint segment, the time sequence degradation coefficient of the voiceprint segment and the deviation coefficient of a target voiceprint segment; and inputting the fault weight of the voiceprint segment and the voiceprint segment with a fault type label into a conditional GAN model to generate a new voiceprint sequence. The method can improve the fault judgment accuracy.

This invention belongs to the field of signal processing technology, specifically relating to a method for enhancing the stochastic resonance of variable frequency signals. The method includes setting the fault characteristic frequency of interest as the target frequency; calculating the target frequency curve based on the rotational frequency and the fault characteristic order; dividing the vibration signal into multiple sub-signals according to the target frequency curve, with each sub-signal's target frequency decomposed and grouped into the same node; performing envelope demodulation on each sub-signal to obtain multiple envelope sub-signals; performing multi-scale noise adjustment on each envelope sub-signal to obtain multiple reconstructed envelope sub-signals, which are then input into a normalized stochastic resonance system to obtain multiple output sub-signals, which are then combined; and performing time-frequency analysis or order analysis on the combined signal to determine whether a fault exists in the variable speed equipment. This invention can solve the problem of segmented signal processing when the frequency variation range is large, greatly enhancing the target frequency, eliminating noise influence, and thus achieving accurate detection of minor faults in rotating machinery.

This invention discloses a method, apparatus, equipment, and medium for analyzing the frequency characteristics of engine components, relating to the field of rocket engine testing technology, to solve the problems of low accuracy and time-consuming nature of existing frequency characteristic analysis methods. The method for analyzing the frequency characteristics of engine components includes: acquiring exciter parameters and pressure time-domain signals at measuring points during dynamic characteristic testing; selecting a corresponding transformation method to transform the pressure time-domain signals to obtain a three-dimensional time-frequency chromatogram based on a comparison between the sweep rate and a preset rate threshold; obliquely slicing the three-dimensional time-frequency chromatogram to obtain a target three-dimensional time-frequency chromatogram; generating amplitude-frequency curves corresponding to each measuring point based on the target three-dimensional time-frequency chromatogram; and determining the frequency characteristics of the engine component based on the amplitude-frequency curves corresponding to each measuring point. The engine component frequency characteristic analysis method provided by this invention improves the accuracy of engine component frequency characteristic analysis.

This invention discloses a current signal fault diagnosis method based on window parameter adaptive complementary synchronous extraction transform, belonging to the field of fault diagnosis and signal processing technology. The method constructs an adaptive complementary weight matrix by referencing the instantaneous current frequency curve and candidate instantaneous current frequency curves; establishes a window parameter-based adaptive complementary synchronous extraction transform framework to obtain the accurate instantaneous current frequency. Then, after resampling the accurate instantaneous current frequency and performing detrending term processing, the instantaneous frequency fluctuation order spectrum is obtained; finally, it is compared with the theoretical fault characteristic order to determine the fault type. This invention overcomes the limitations of traditional synchronous extraction transform in processing strongly time-varying signals, such as being limited by the uncertainty principle, having subjective window parameter selection, and being sensitive to noise, significantly improving the accuracy of instantaneous frequency extraction. This greatly enhances the reliability of fault diagnosis under time-varying operating conditions.