9 results about "Correlation curve" patented technology

The invention discloses a biological characteristic sample quality threshold determination method and device and a biological characteristic recognition method and device, and belongs to the field of biological characteristic recognition. According to the method, the mismatching rate is counted under the set mismatching rate level and different discarding rates, the relation between discarded low-quality biological characteristic sample pairs and the biological characteristic recognition performance is established, namely, the correlation curve of the discarding rate and the mismatching rate is established, and the sample quality threshold value under the set mismatching rate level is obtained according to the correlation curve. And a method for quantifying the quality intensity by the biological characteristic sample is provided. The sample quality threshold value is determined according to the parameters of the biological feature recognition performance and is related to the mismatching rate and the mismatching rate, and compared with a manually set sample quality threshold value, the sample quality threshold value has better reasonability and reliability.

This invention relates to the field of data monitoring technology, specifically to an intelligent monitoring method for injection and pressure during groundwater remediation processes. The method involves: obtaining the degree of suspected anomalies based on the differences between data points and adjacent data points in a monitoring data sequence, and the discrete characteristics of the data points; identifying suspected anomaly points in the monitoring data sequence based on the degree of suspected anomalies; obtaining different continuous trend segments based on the temporal distribution characteristics and local data change characteristics of the suspected anomaly points in the monitoring data sequence; obtaining flow-pressure correlation curves based on the correspondence between flow and pressure in the continuous trend segments; and obtaining the degree of regularity in the distribution of flow and pressure based on the differences in the flow-pressure correlation curves of different continuous trend segments. This invention determines the recent flow and pressure status during groundwater remediation based on the degree of regularity in the distribution of flow and pressure, improving monitoring accuracy and reducing the impact on the groundwater remediation process.

A signal synchronization method includes sequence interpolation correlation synchronization, detecting the position of the maximum peak and the maximum value R xy (max); selecting correlation sample values on both sides of the maximum peak, linearly fitting the points on both sides, and the intersection of the two fitted straight lines as the predicted optimal synchronization point; selecting points on both sides of the predicted position as target synchronization position candidate points, cutting the target signal for channel estimation, calculating the channel equivalent SNR of different target positions; selecting the position with the maximum SNR as the final synchronization position; the above signal synchronization method is based on the shape of the correlation curve to predict the synchronization position, the sequence interpolation correlation synchronization method finds the approximate position of the peak, the left and right data of the correlation curve are linearly fitted, the intersection of the two fitted straight lines is the predicted optimal synchronization position, and then within a small range on both sides of the predicted position, the best synchronization point is further selected based on the quality of the channel response, which can improve the synchronization effect by 3-4 times.

The invention discloses a symbol synchronization position estimation method and system. The method comprises the following steps: generating a noiseless reference parabolic curve model under reference symbol deviation by using matlab simulation; generating an actual parabolic curve model according to the reference parabolic curve model; acquiring the acquired signals, and performing cross-correlation on the acquired signals and a local sequence to obtain a correlation curve; obtaining a peak value and a secondary peak value of a correlation peak in the correlation curve, respectively substituting the peak value and the secondary peak value of the correlation peak into the actual parabolic curve model, and establishing a quadratic function about the sampling deviation; and solving the quadratic function, and adding the solution of the sampling deviation and the reference symbol deviation to obtain a symbol synchronization position estimation value. According to the invention, only two sampling points are needed to realize the same performance as the existing method.

The invention discloses a division method suitable for a temper mill strip shape preset layer table. The division method comprises the steps that a rolled piece roller system integrated simulation model is constructed based on the structure of a four-roller temper mill; actual production data of the four-roller temper mill are obtained, simulation calculation is conducted on the basis of the actual production data and the rolled piece roller system integrated simulation model, and simulation big data are obtained; a correlation curve of each strip steel parameter and the secondary convexity of the strip steel cross section is obtained based on simulation big data analysis; and obtaining an optimal division scheme of the preset layer table based on the correlation curve of the strip steel parameters and the secondary convexity of the strip steel cross section. The problem that in the prior art, the plate shape presetting control precision of a temper mill unit is poor is solved, and therefore the plate shape quality of plate strip steel products is remarkably improved.

This invention discloses a method for dividing a pre-set layer table for strip shape in a leveling mill, comprising: constructing an integrated simulation model of the rolling mill roll system based on the structure of a four-roll leveling mill; acquiring actual production data of the four-roll leveling mill; performing simulation calculations based on the actual production data and the integrated simulation model of the rolling mill roll system to obtain simulation big data; analyzing the simulation big data to obtain the correlation curves between various strip parameters and the secondary crown of the strip cross-section; and obtaining the optimal division scheme of the pre-set layer table based on the correlation curves between strip parameters and the secondary crown of the strip cross-section. This invention solves the problem of poor control accuracy of pre-set strip shape in the prior art, thereby significantly improving the strip shape quality of strip products.

The application provides a beam displacement regulation method and a beam displacement device. The method is applied to the beam displacement device, the beam displacement device comprises a plurality of cell structures which are sequentially and spacedly distributed along the same direction, and the method comprises the following steps: obtaining structure data of the cell structure and a working frequency of the cell structure; determining a transmittance and a transmission phase corresponding to the cell structure based on the structure data and the working frequency; determining a correlation curve between the incident angle, the transmittance and the transmission phase based on each incident angle, each transmittance and each transmission phase; and determining a transverse displacement corresponding to a preset adjustment mode of the incident wave in the cell structure by setting the cell structure as a second type of boundary condition for finite element simulation calculation based on the correlation curve and the incident wave of a preset incident wavelength incident to the cell structure of the preset adjustment mode. The complexity and cost of the regulation method are reduced, the regulation efficiency of the beam displacement is improved, and the transverse displacement is increased.

A method of characterizing a reservoir by automatic depth alignment of petrophysical logs, including: receiving a first and second correlation logs in a depth-domain; transforming, using a Fast Fourier Transform (FFT), the first correlation log in the depth-domain into a first frequency-domain log; transforming, using the FFT, the second correlation log in the depth-domain into a second frequency-domain log; determining, using the first and second frequency-domain logs, a correlation curve of the first and second correlation logs; determining, using the correlation curve, a correlation metric of the first and second correlation logs; determining, using the correlation curve, an alignment shift for the first and second correlation logs and a depth-corrected second correlation log by applying the alignment depth shift to the second correlation log; updating and evaluating the correlation metric after applying the alignment shift; and outputting the depth-corrected second correlation log to a subsequent process of reservoir characterization.

The present application relates to the porosity calculation method based on natural gamma spectrum and three porosity curves, belongs to the unconventional shale gas exploration and development technical field. The specific steps are as follows: step 1: using data statistics 'one' regression method, through the cross analysis of the porosity data of core analysis and acoustic time difference, density, neutron, uranium logging curves in the research area, the good correlation curve is selected as the modeling parameter; step 2: through the comparative analysis of the porosity modeling method of multiple combination modes; step 3: considering the differences of different structural belt reservoir burial depth and the differences of main evaluation parameters such as physical property, brittleness and gas content, the research area is further optimized and partitioned; step 4: using core data to scale logging curve, the porosity interpretation model based on natural gamma spectrum and three porosity curves is finally established. The method can effectively improve the porosity precision, and has important guiding significance for efficient development of shale gas.