21 results about "Spectral ratio" patented technology

To provide an evaluation support device and an evaluation support method for supporting confirmation of the condition of the hard ground where piles are to be installed.SOLUTION: A management device 20 that supports confirmation of the hard ground includes a measurement information storage unit 22 that stores measurement values of the frequency of ground vibration in association with measurement positions of ground vibration, and a control unit 21 connected to a display device. The control unit 21 calculates a frequency distribution of a spectral ratio obtained by dividing the spectrum of a horizontal component by the spectrum of a vertical component from the measurement values recorded in the measurement information storage unit 22, and converts the frequency of the frequency distribution into depth. The control unit 21 outputs to the display device a map that displays depth distribution information for the measurement positions, with the display format changed according to the spectral ratio.SELECTED DRAWING: Figure 1

The invention provides a hyperspectral inversion method for water body sediment concentration and a measuring instrument. The method comprises the following steps: S1, collecting a water body reflection spectrum, a water flow rate and sediment concentration of a test point; s2, pretreating the water body reflection spectrum, the external factors and the sediment concentration; and S3, inputting the preprocessed data into an inversion model to obtain the concentration of the suspended sediment in the water body at the test point. According to the method, spectral ratio characteristics and sediment concentration logarithmic transformation are comprehensively utilized, and weight holding of external auxiliary factors is introduced into the XGBoost gradient tree, so that interference of high-concentration interval spectral saturation and extreme values on model training is relieved, and stability and prediction performance of high-concentration suspended sediment inversion are improved.

The invention relates to the technical field of facility agriculture and environment control, and discloses an intelligent illumination control system for greenhouse plant growth. In order to solve the problems that an existing light supplementing strategy lacks physiological feedback, light damage is easily caused, and shutdown is caused by sensor faults, the system comprises a multi-mode sensing assembly, a central processing unit and a dynamic spectrum execution assembly. The system collects crop non-photochemical quenching coefficients (NPQ) and environmental factors in real time, and dynamically calculates light saturation points by using a multi-factor coupling model; when the NPQ exceeds a threshold value, the spectrum ratio is automatically adjusted to inhibit light stress; three-dimensional canopy scanning is combined to realize gridding differentiation light supplement; when the sensor fails, virtual parameters are reconstructed based on the temperature trend to maintain fault-tolerant operation; in addition, the system estimates stomatal conductance according to air humidity and matrix conductivity, and dynamically corrects target light intensity to avoid aggravation of water deficit; accurate light supply according to needs is achieved, the photosynthetic efficiency and the system reliability are remarkably improved, and the system is suitable for plant factories and multi-span greenhouses.

The invention provides a micro-motion H / V spectrum ratio data processing method and device based on machine learning and a medium, and the method can comprise the steps: obtaining micro-motion H / V spectrum ratio data containing a plurality of curves, recognizing and removing the curves containing abnormal morphological characteristics through a preset curve removing model, and obtaining a candidate data set; classifying peak values of the curves in the candidate data set according to a preset peak value classification model to obtain an effective peak value set; clustering the effective peak value set based on a density clustering algorithm to obtain effective peak value clusters in different frequency intervals; and determining the effective peak cluster with the lowest frequency as a main peak cluster, and rejecting curves of peak values with abnormal frequencies and amplitudes in the main peak cluster to obtain processed micro-motion H / V spectrum ratio data. The method has higher stability and accuracy, the spectrum distribution of the processed curve is more concentrated, the standard deviation curve is more convergent, and the peak value is clearer and more stable.

The invention discloses a ballasted railway ballast bed mechanical state monitoring method based on high-frequency environment noise. The method comprises the steps that S1, three-axis acceleration signals of a ballasted railway under the high-frequency environment noise are collected; s2, integrating the three-axis acceleration signal to obtain a three-axis speed signal, calculating horizontal / vertical power spectral density based on the three-axis speed signal, and calculating the horizontal / vertical power spectral density to obtain an average spectral ratio curve; and S3, constructing an initial basic structure model based on the prior information of the ballast bed and the roadbed, performing inversion on the average spectrum ratio curve by adopting a global inversion algorithm based on the initial basic structure model to obtain the ballast bed shear wave velocity, and judging the mechanical state of the ballast bed according to the ballast bed shear wave velocity. According to the method, the average spectrum ratio curve is established by collecting the signals under the high-frequency environmental noise, the ballast bed shear wave velocity is obtained through inversion, real-time monitoring and long-term tracking of the mechanical state of the ballast bed of the ballast railway are achieved, and the method has remarkable engineering application potential and popularization value.

The present application belongs to the technical field of oil seismic exploration, and discloses a near-surface modeling method and system based on microseismic spectral ratio interface imaging constraint, wherein the method comprises the following steps: collecting continuous microseismic data of a set time length in the whole work area and performing pretreatment; performing spectral ratio calculation on the pretreated microseismic data, smoothing the spectral ratio, and obtaining peak frequency from the smoothed spectral ratio; obtaining the shear wave velocity structure from the microseismic signal inversion, converting the peak frequency under each station into interface depth according to the shear wave velocity structure, and obtaining the interface depth information of the whole work area; taking the interface depth information as a constraint condition, adding the first arrival wave travel time tomography inversion, and completing the near-surface velocity modeling. The present application provides fine lithology interface constraint, makes up for the defect of insufficient micro-logging spatial sampling, improves the vertical resolution and lateral continuity of the near-surface velocity model, and solves the problem of insufficient accuracy of the near-surface model caused by lack of constraint in complex areas.

This invention relates to a method, system, medium, and device for determining the quality factor of intermediate-deep strata, comprising: acquiring source wavelet and receiver wavelet, and performing Fourier transforms on them respectively to obtain the corresponding amplitude spectra; calculating the probability density functions of the wavelet power spectrum before and after attenuation; calculating target parameters based on the probability density functions of the wavelet power spectrum before and after attenuation and the wavelet amplitude spectra before and after attenuation; calculating the centroid frequency difference of the power spectrum based on the probability density functions of the wavelet power spectrum before and after attenuation; and calculating the quality factor of the corresponding layer based on the target parameters and the centroid frequency difference of the power spectrum. This invention constructs a probability density function using the power spectra of the wavelet before and after attenuation, and uses this as a weight to perform a weighted integral on the logarithmic term of the amplitude spectral ratio to construct a new index with a structure similar to Jeffrey divergence, thereby suppressing spectral ratio vibrations caused by noise and achieving the goal of stably and accurately estimating the quality factor of intermediate-deep strata under different actual seismic data conditions.

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.

The invention relates to a Q value estimation method and system based on attenuation function integration, a medium and equipment. The method comprises the following steps: acquiring a reference wavelet and a receiving wavelet; calculating based on the reference wavelet and the receiving wavelet to obtain a reference wavelet amplitude spectrum and a receiving wavelet amplitude spectrum; frequency band selection is carried out based on the reference wavelet amplitude spectrum and the receiving wavelet amplitude spectrum, and a calculation frequency band is obtained; determining a center frequency and an attenuation function frequency based on the computational frequency band; calculating according to the center frequency, the attenuation function frequency and a seismic wave attenuation constant Q model to obtain an expression of an attenuation function about wavelet amplitude spectrums before and after attenuation; an attenuation function integral in a given frequency band range is calculated according to the expression; and performing calculation based on the attenuation function integral to obtain a stratum Q value. Compared with a traditional spectrum ratio method, the method can avoid amplification noise interference, is higher in anti-noise performance, and is remarkably improved in stability.

Embodiments of the present application relate to a kind of near-surface seismic attenuation factor acquisition method, device, equipment and medium, according to the near-surface stratification result of field surface investigation, determine the velocity layer of each excitation point in the excitation well and each receiving point of equidistant arrangement in receiving well;From the multi-channel seismic data corresponding to each excitation point in the corresponding velocity layer, extract the first seismic data corresponding to each receiving point in the corresponding velocity layer and the second seismic data corresponding to any other velocity layer;According to the first seismic data and the second seismic data corresponding to each receiving point, determine the initial seismic attenuation factor corresponding to each receiving point based on spectral ratio method, and then calculate the final seismic attenuation factor;According to the final seismic attenuation factor corresponding to each receiving point in each velocity layer and the depth of receiving point, determine the variation curve of near-surface seismic attenuation factor, can obtain more accurate Q value.

The present invention is applicable to the field of geophysical exploration technology and provides an inversion method for HVSR spectral ratio curves based on the diffusion field theory, including the following steps: construction of a spectral ratio calculation equation based on the diffusion field theory; artificial synthesis of microtremor records with a random seismic source distribution; model setting and microtremor data acquisition; calculation of HVSR spectral ratio curves; construction and optimization of an inversion objective function; and output of inversion results. Based on the diffusion field theory, the present invention significantly reduces the limitations of traditional single-wavefield assumptions by comprehensively considering various wavefield components such as body waves and surface waves, and improves the inversion accuracy. This method shows excellent adaptability under shallow structure and complex medium conditions, and at the same time has strong noise robustness, and is applicable to complex environments such as urban underground space exploration. In addition, this method reduces the dependence on the initial model, avoids the problem of local optimum, and can be extended to fields such as engineering seismic safety assessment and underground water resource exploration, with broad application prospects.

The present application relates to a bolt loosening detection method based on a spectral ratio coefficient method and a bolt loosening degree detection method, comprising the following steps: obtaining a reference amplitude-frequency curve of a healthy structure, obtaining non-healthy amplitude-frequency curves under different bolt loosening degrees, obtaining amplitude-frequency ratio curves of the non-healthy amplitude-frequency curves and the reference amplitude-frequency curve under different bolt loosening degrees, and establishing a fitting linear equation between the bolt loosening degree and the average value of the amplitude-frequency ratio absolute value curves. The present application uses the characteristic that bolt loosening can cause the stiffness of a structure connection to decrease and thus cause the characteristic frequency to shift, uses the amplitude-frequency ratio absolute value curve of a healthy bolt connection structure as a reference, and uses the average value of the amplitude-frequency ratio absolute value curves under different loosening degrees as a bolt loosening degree detection index to identify the loosening state of the bolt, and the detection of the early loosening state of the bolt is more sensitive, thus providing a more intuitive and convenient bolt loosening detection method for a bolt connection structure.

The present application provides a kind of method for identifying liquid inlet hydraulic fracture using microseismic event spectral ratio, comprising the following steps: S1, data acquisition;S2, Fourier transform is carried out to the P wave and S wave obtained, and then the expression in frequency domain is converted into displacement amplitude spectrum;S3, the average value of spectral data in low frequency range is calculated as zero frequency level ω0;S4, Brune stress drop is calculated using the integral of ground velocity square to parameterize, using in the calculation process of stress drop, the integral of ground velocity square is defined as J, which is the second moment of power spectrum;S5, the corner frequency of S wave is calculated;The calculated S wave corner frequency is classified and divided for microseismic event, and low S wave corner frequency is tension event, and high S wave corner frequency is shear event.The present application is helpful to evaluate the distribution of fracturing fluid and understand the stress distribution and change of formation.

This invention relates to a method, system, medium, and device for Q-value estimation based on the attenuation function integral, comprising the following steps: acquiring a reference wavelet and a received wavelet; performing calculations based on the reference wavelet and the received wavelet to obtain the reference wavelet amplitude spectrum and the received wavelet amplitude spectrum; selecting a frequency band based on the reference wavelet amplitude spectrum and the received wavelet amplitude spectrum to obtain a calculation frequency band; determining the center frequency and the attenuation function frequency based on the calculation frequency band; calculating an expression for the attenuation function with respect to the wavelet amplitude spectrum before and after attenuation based on the center frequency, the attenuation function frequency, and a seismic wave attenuation constant Q model; calculating the attenuation function integral within a given frequency band based on the expression; and calculating the formation Q-value based on the attenuation function integral. Compared to the traditional spectral ratio method, this invention avoids amplified noise interference, has higher noise immunity, and significantly enhanced stability.

This invention discloses a method for detecting foreign objects in grain silos based on elastic resonance waves, belonging to the field of grain condition monitoring technology. A low-frequency three-component vibration pickup is selected to collect background vibration noise. Utilizing the resonance characteristics of elastic waves, foreign objects inside the bulk grain in the grain silo are detected. The steps are: S1, selecting a low-frequency three-component vibration pickup; S2, deploying the pickup on the grain surface at designated detection points in the grain silo, adjusting the pickup's orientation and level, setting acquisition parameters, and recording the background vibration signal; S3, removing abnormal vibration noise and calculating the power spectrum of the three vibration components segment by segment; S4, calculating the horizontal and vertical spectral ratio curves; S5, based on the horizontal and vertical spectral ratio curves, performing foreign object identification and calculating burial depth parameters. This method achieves the identification of foreign objects in the grain silo, with a simple data post-processing workflow, minimal impact from human intervention, and stable and reliable processing results.

The invention provides a micro-motion H / V spectrum ratio method three-step stratigraphic inversion method, and relates to the field of geology, and the method comprises the steps: employing an empirical formula, preliminarily estimating the average speed of a peak representative horizon and a sedimentary layer S wave, and carrying out the inversion to obtain an STEP1 average model; combining each layer of the STEP1 average model through a dual-threshold combination to obtain a STEP2 average model; and further narrowing the search range, and carrying out inversion on the STEP2 average model to obtain a shallow shear wave velocity structure below the single station in the research area. The invention develops a'three-step 'inversion method. According to the method, H / V curve characteristics are fully utilized, the approximate range and depth of the underground low-speed layer and the underground high-speed layer are automatically judged, and the inversion model space is gradually obtained and optimized.

The application discloses a seismic frequency-variable Q value estimation method based on a rock physical mechanism, and comprises the following steps: selecting an effective mesoscopic scale rock physical model, determining a Q(f) curve and a velocity dispersion relation in the model; improving the selected mesoscopic scale rock physical model by using a pre-established viscoelastic model, and analyzing attenuation characteristics of the mesoscopic rock physical model in describing a reservoir; and calculating a frequency-variable Q value of the improved mesoscopic scale rock physical model by using a double-parameter spectral ratio method of an SLS model. The above scheme is based on a WIGED multi-scale rock physical model of a fluid and a DKT model of dry rock, and proposes a new frequency-related Q estimation method, i.e. the double-parameter spectral ratio method. Compared with a conventional estimation method, the method establishes a connection among a mesoscopic rock physical model, logging data and seismic data, can give more accurate and reliable seismic data Q value results, and better explains reservoir physical properties.

The application discloses a tailing dam seepage line analysis method and system, and belongs to the technical field of geotechnical engineering monitoring and geophysical exploration. The method first acquires three-component continuous waveform data of a tailing dam observation point, uses a sliding time window to segment and calculate the cross-spectral density between each component, and constructs a horizontal-vertical spectral ratio (HVSR) curve after removing the autocorrelation term; then, using a historical average HVSR curve as a reference template, the single-window HVSR curve is filtered and superimposed and averaged through a global, local or combined amplitude threshold cross-correlation coefficient judgment strategy, and a single-day HVSR curve with high stability is obtained. The application effectively eliminates the redundant amplitude information introduced by environmental noise interference and autocorrelation terms, significantly improves the stability of the HVSR curve and the accuracy of the peak frequency identification, and thus more accurately inverts the position of the wave impedance interface inside the tailing dam, and realizes dynamic monitoring and safety evaluation of the seepage line.

The application belongs to the field of oil seismic exploration, and discloses a method for estimating near-surface Q factor based on VSP data, which comprises the following steps: carrying out wave field separation processing on the vertical component profile after VSP data preprocessing to obtain downgoing wave field containing downgoing direct wave and downgoing multiple wave information under free interface; determining the position of downgoing multiple wave under free interface and the depth point for estimating near-surface Q factor to obtain the amplitude spectrum of downgoing direct wave and downgoing multiple wave under free interface at the depth point; using spectral ratio method to fit binomial to obtain the near-surface Q factor calculated by the data at the depth point; determining other depth points after the same shot in the well, using the data at multiple depth points to calculate multiple near-surface Q factors, and then averaging the multiple near-surface Q factors to obtain the near-surface Q factor at the well point. Downgoing direct wave and downgoing multiple wave under free interface are obtained by using zero well source distance VSP data, and the near-surface Q factor is calculated.

The application discloses a tailing dam seepage line analysis method and system, and belongs to the technical field of geotechnical engineering monitoring and geophysical exploration. The method first acquires three-component continuous waveform data of a tailing dam observation point, uses a sliding time window to segment and calculate the cross-spectral density between each component, and constructs a horizontal-vertical spectral ratio (HVSR) curve after removing the autocorrelation term; then, using a historical average HVSR curve as a reference template, the single-window HVSR curve is filtered and superimposed and averaged through a global, local or combined amplitude threshold cross-correlation coefficient judgment strategy, and a single-day HVSR curve with high stability is obtained. The application effectively eliminates the redundant amplitude information introduced by environmental noise interference and autocorrelation terms, significantly improves the stability of the HVSR curve and the accuracy of the peak frequency identification, and thus more accurately inverts the position of the wave impedance interface inside the tailing dam, and realizes dynamic monitoring and safety evaluation of the seepage line.

This application provides a method for estimating the quality factor of a target stratum by combining distributed acoustic sensing vertical seismic profile data and surface seismic data, belonging to the field of seismic signal processing technology. The method includes: acquiring distributed acoustic sensing vertical seismic profile data, surface seismic data, and a velocity model of the target stratum; performing DAS-VSP first-arrival ray tracing on the velocity model to obtain the propagation path information of the seismic waves; performing local time-frequency transformation on the direct wave information and calculating the logarithmic spectral ratio slope of the direct wave and the source wavelet; calculating the tectonic dip field of the target stratum based on the surface seismic data; constructing a set of quality factor spectral ratio tomographic equations based on the propagation path information and the logarithmic spectral ratio slope; constructing a regularization term for the Seislet transform based on the tectonic dip field, and establishing a quality factor inversion equation based on the regularization term and the quality factor spectral ratio tomographic equations; and solving the quality factor inversion equations to obtain the quality factor field of the target stratum.