20 results about "Curve matching" patented technology

The invention relates to the technical field of power communication network fault diagnosis, in particular to a power communication network fault intelligent diagnosis method based on dynamic topology simulation. The electric power communication network fault intelligent diagnosis scheme is implemented by six steps: firstly, collecting physical layer, protocol layer and topological data, and constructing an equipment-time-performance index three-dimensional matrix; decomposing the matrix to calculate a stability index, and primarily judging an abnormal time period and an abnormal area; mapping a physical topology, and accurately positioning a fault area by using a dynamic convex hull and a ray algorithm; extracting historical data to generate a characteristic curve, and matching a sample library to identify a fault type; the theoretical and actual parameters are iteratively compared to verify the reliability; and finally generating a report and matching a repair strategy. Rapid positioning, accurate identification and reliable diagnosis of faults are achieved, the defects of static analysis, data splitting and verification deficiency in the prior art are overcome, and the operation and maintenance efficiency and the safety level of an electric power communication network are improved.

The invention discloses an anomaly detection method and device for a service system, electronic equipment and a storage medium, and relates to the field of operation and maintenance monitoring, and the method comprises the steps: obtaining a first quantity curve reflecting a mapping relation between a detection moment and an abnormal data quantity in a first time period; obtaining a first fitting curve matched with the first quantity curve and a first confidence interval through a time sequence model; according to the first confidence interval and the first quantity curve, determining quantity abnormal moments in the first time period; and obtaining an anomaly detection result of the business system in the first time period according to the actual anomaly number, the fitting anomaly number, the fitting anomaly upper limit and the fitting anomaly lower limit at the number anomaly moment. According to the technical scheme of the embodiment of the invention, the anomaly detection result not only adapts to data fluctuation and data periodical change, but also avoids missing report and false report of the abnormal state of the service system, improves the accuracy of the anomaly detection result, and improves the anomaly detection efficiency.

This invention proposes a method for extracting the dynamic envelope of spacecraft parameters based on curve matching search, comprising the following steps: reading telemetry parameter files to obtain parameter sequence curves as templates for matching search; reading historical telemetry data to obtain historical parameter sequence curves as objects for traversal and retrieval; traversing the historical parameter sequence curves, with a window length equal to the number of values ​​in the template sequence and the initial point of the window sequence as the initial matching point, and calculating the matching vector and matching value between each window sequence and the parameter sequence curve; sorting the matching values ​​in ascending order and correspondingly sorting the matching starting points; optimizing the matching starting points for interference reduction based on distance boundaries; extracting the optimized matching starting points based on matching thresholds and performing curve positioning to form a curve set; and calculating the upper and lower dynamic envelopes of the spacecraft telemetry parameters based on the maximum and minimum values ​​of the curve points in the curve set.

The invention discloses a reflection amplitude characteristic matched simple calibration-free dielectric constant measurement method, which comprises the following steps of: outputting a continuous wave with continuously changing frequency through a signal generator, enabling the continuous wave to enter a rectangular waveguide in which a sample to be measured is placed through a power divider, and enabling the sample to be measured and an electromagnetic field to interact to generate a reflection signal; the reflected signals are transmitted to a detector after passing through a power divider, the reflected signals are collected, and a reflection amplitude actual measurement curve is obtained; a reflection amplitude theoretical curve is generated through the NRW transmission theory based on the dispersion model, curve matching optimization is conducted through a search algorithm, the Euclidean distance between a reflection amplitude actual measurement curve and the reflection amplitude theoretical curve is calculated iteratively, and an optimal parameter combination is obtained; and substituting the optimal parameter combination into the dispersion model to obtain the dielectric constant of the tested sample.

The present invention discloses a method for identifying pile foundation defects based on feature curve matching of low-strain curves, including: Step 1: Generate corresponding defect feature curves for each pile foundation defect type; Step 2: Convert the defect feature curves of each different pile foundation defect type into corresponding text files; Step 3: Slide and intercept the data on the actual low-strain curve, calculate the matching accuracy between the intercepted data and the defect feature curve to construct a matching accuracy curve, and find the maximum value of the matching accuracy exceeding the preset threshold in advance on the matching accuracy curve; Step 4: Calculate the classification probability of the defect type on the actual low-strain defect according to the matching accuracy; Step 5: Determine the level of the defect type. The present invention can realize the automatic identification of pile foundation defects in low-strain curves, greatly improve the efficiency and accuracy of pile foundation detection, and reduce the probability of misjudgment and missed judgment of pile foundation defects caused by manual judgment of low-strain curves.

The application discloses a multi-channel track detection data adaptive mileage correction and evaluation method, relates to the track detection field, and comprises the following steps: S1, acquiring reference data X and to-be-repaired data Y of a track; S2, extracting special points in the reference data and the to-be-repaired data as base points; S3, adopting digital curve matching of a local section to obtain optimal correction points; S4, correcting mileage error of to-be-repaired data between adjacent base points according to the optimal correction points; and S5, comprehensively evaluating correction results according to the precision of mileage deviation correction of the to-be-repaired data and the change of waveforms before and after correction. According to the track reference data X, the to-be-repaired data Y is accurately corrected in terms of mileage error, higher-precision mileage information is obtained, original data features of track detection data such as track orientation and height, track gauge, level, twist, curvature of left and right tracks are reserved, and the quality of mileage correction is evaluated by using scientific and faithful statistical indexes, so that the real geometric state of the track can be more accurately mastered.

The invention provides an evaluation method and device for anti-load capability and electronic equipment, and the method comprises the steps: receiving a training data stream from multi-path collection equipment, carrying out the format conversion, writing the data stream into a cache and a database at the same time, reading index data from the cache, and carrying out the waveform display; updating a waveform view in real time and superposing a test curve matched with a training item type by adopting a dual-channel refreshing mechanism of a bottom-layer thread callback and user interface timer polling shared queue; matching the real-time waveform with a preset standard curve for the guidance training item, and determining a guidance quantitative score; packaging whole-course index data into an evaluation file containing time, personnel and project attributes, and supporting data browsing and index statistics; and the cycle score is generated according to the training cycle, and the test single item, the training process and the comprehensive capability evaluation report are formed in combination with the evaluation file, so that stable display and differentiated evaluation of multi-path high-frequency data are realized, and the comprehensiveness and accuracy of evaluation are improved.

The invention relates to the field of data analysis, in particular to a classroom energy-saving risk early warning method fusing student behaviors and energy consumption twinning, and the method comprises the steps: obtaining a supply and demand side unified feature sequence through multi-source twinning data collection and standardization processing; analyzing the student spatial distribution information entropy to obtain a space-time thermal entropy coupling lag potential energy factor; performing conjoint analysis on the short-time power spectrum of the supply and demand side and the time domain trend to obtain a frequency spectrum energy dissipation mismatch factor; performing fusion calculation on the numerical distance and the two types of physical constraint factors to obtain a mixed local distance under the physical constraint; the energy-saving operation risk early warning and self-adaptive regulation and control result is obtained by performing dynamic planning and attribution analysis on the mixed local distance under the physical constraint, so that the problem of energy-saving risk early warning missing report caused by neglecting the thermotechnical physical time delay constraint and frequency domain response difference in the existing standard DTW-based supply and demand curve matching is solved.

The invention relates to the technical field of cells, and discloses a method for analyzing perovskite solar cell performance influence factors based on numerical simulation, and the method comprises the following steps: S1, obtaining experimental cell parameters, and obtaining a J-V curve and output parameters of an actual perovskite solar cell; s2, constructing a physical model of the solar cell, and constructing a physical numerical relationship between voltage and current of the solar cell by adopting an equivalent circuit theory according to the principle of the solar cell; s3, performing numerical simulation analysis; s4, curve matching is carried out, and programming software is utilized; and S5, influence factor analysis. According to the method, a numerical fitting method is adopted, a theoretical J-V curve is matched with an actual cell J-V curve, the sizes of Jsrh, Jsurf, juug and Je, series resistance Rs and parallel resistance Rsh are clarified, influences of the Jsrh, Jsurf, juug and Je, the series resistance Rs and the parallel resistance Rsh on the conversion efficiency of the perovskite solar cell are calculated, limiting factors of the actual perovskite solar cell performance are clarified, and on the basis of a simulation result, the actual performance of the perovskite solar cell is calculated. And a strategy for reducing corresponding loss is provided.

The invention belongs to the technical field of electric digital data processing, and particularly relates to an automatic matching method of an oil and gas production decline curve, electronic equipment and a storage medium. According to the method, mathematical characteristics of a double logarithmic space are utilized, a complex curve matching problem is converted into a linear translation optimization problem, automatic alignment of data points is achieved in combination with an interpolation algorithm, the single well analysis time is shortened to be within 1 minute from 1-2 hours of a traditional method, and efficiency is improved by two orders of magnitude; a numerical optimization algorithm is adopted to replace manual visual matching, and by establishing a centroid initialization-based least square optimization model, an optimal translation parameter is automatically calculated, and deviation caused by human factors is eliminated, so that the parameter inversion precision is greatly improved; an overlap ratio quantitative evaluation mechanism is introduced, a matching result is objectively evaluated by setting a scientific threshold value, the problem that a traditional method lacks a quality judgment standard is solved, and high-precision and high-efficiency automatic matching of oil and gas well production data and a theoretical curve is achieved.

The present invention provides a data separation method and a separation system, wherein the data separation method comprises the following steps: obtaining a full-cycle processing curve during workpiece processing, wherein the full-cycle processing curve comprises a plurality of single-cycle processing curves; selecting one of the single-cycle processing curves in the full-cycle processing curve as a template curve, and the other single-cycle processing curves as processing curves to be matched; determining a standard sample curve in the template curve; judging whether the standard sample curve matches each processing curve to be matched; judging whether to update the standard sample curve based on the matching results between n adjacent processing curves to be matched that match the standard sample curve and the standard sample curve; and separating the template curve before the update and all processing curves to be matched that match the standard sample curve in the template curve.

The present application belongs to the technical field of electric digital data processing, and particularly relates to an automatic matching method of oil and gas production decline curve, an electronic device and a storage medium. The method utilizes the mathematical characteristics of double logarithmic space to convert the complex curve matching problem into a linear translation optimization problem, and realizes the automatic alignment of data points in combination with an interpolation algorithm, so that the single well analysis time is shortened from 1-2 hours of the traditional method to within 1 minute, and the efficiency is improved by two orders of magnitude. A numerical optimization algorithm is adopted to replace artificial visual matching, an optimal translation parameter is automatically calculated by establishing a least square optimization model based on centroid initialization, and the deviation caused by human factors is eliminated, so that the parameter inversion accuracy is greatly improved. A coincidence quantitative evaluation mechanism is introduced, the matching result is objectively evaluated by setting a scientific threshold, the problem of lacking quality evaluation standard in the traditional method is solved, and the high-precision and high-efficiency automatic matching of oil and gas well production data and theoretical curve is realized.

The present application discloses a method and system for identifying new energy consumption boundaries based on time series characteristics, the method comprising: obtaining a data set of a source domain and a data set of a target domain, the data set of the source domain comprising power generation data and meteorological data of the source domain within a set period, the data set of the target domain comprising meteorological data of the target domain within a set period and no power generation data of the target domain within the set period; determining source domain common features corresponding to the data set of the source domain and target domain common features corresponding to the data set of the target domain; generating a new energy output time series curve matching the target domain based on the source domain common features and the target domain common features; determining an optimization model based on the new energy output time series curve, power generation data of the source domain, meteorological data of the source domain and meteorological data of the target domain; and using the optimization model to identify the new energy consumption boundary corresponding to the target domain based on meteorological features extracted from the meteorological data of the target domain, thereby accurately identifying the new energy consumption boundary of the area to be identified.

The present application relates to the technical field of statistical analysis, in particular to a bridge monitoring method and system based on big data analysis, which collects multi-component monitoring sequences and compares differences in time sequence, generates a response grading baseline according to wave threshold identification of abnormalities, constructs a jump distribution map based on amplitude grading and space-time law, identifies dense inflection points and generates a consistency curve by comparison and linkage, matches the trend of pier support to determine the stable response area, merges sequences to extract statistical characteristics and mark, and generates a bridge monitoring operation state characteristic set. The present application establishes a grading baseline based on the frequency and direction of monitoring data, forms a jump inflection point system in combination with multi-dimensional time sequence, draws a structure jump map, uses linkage identification to depict component consistency, dynamically captures local stable response, integrates trend law to complete characteristic merging, constructs state characteristic layered mapping, establishes a cross-component aggregated response chain, realizes information space-time high correlation extraction, and clearly presents the structure evolution law.

The application discloses a waveform curve matching method and device, which cuts a first waveform curve into a plurality of first waveform segments, cuts a second waveform curve into a plurality of second waveform segments, and calculates matching degrees between the plurality of first waveform segments and the plurality of second waveform segments to obtain the matching degrees of the first waveform curve and the second waveform curve; that is, the first waveform curve and the second waveform curve are both cut into waveform segments, and then each waveform segment is compared to exclude matching of redundant waveform segments and missing segments, so that an accurate matching result can be found, the matching accuracy is improved, and the precision of calculating the similarity of the first waveform curve and the second waveform curve is improved.

The application provides a map matching design method, a matching method and a system based on a SylixOS operating system, and solves the technical problem that the real-time performance of the existing map matching cannot fully utilize the real-time performance of the operating system. The method comprises the following steps: in the map matching process, a main thread is set, which is used for responding to a map matching request of a hard interrupt; a serial port thread is set, which is used for responding to a data bidirectional serial transmission request of a first soft interrupt; a search thread is set, which is used for responding to a map database search request of a second soft interrupt; a matching thread is set, which is used for responding to a curve matching map matching request of a third soft interrupt; and data synchronization and / or data sharing are performed among the serial port thread, the search thread and the matching thread according to a synchronization semaphore. The real-time high-frequency response of a positioning data request of an external inertial device through a serial port, the map database search efficiency and the curve matching map matching accuracy are ensured.

This invention relates to the field of deep learning technology, specifically disclosing a method for optimizing the energy efficiency of AI computing devices based on deep learning. The method includes the following steps: allocating a dedicated hardware computing partition for the AI ​​computing task to be executed and initiating the acquisition of real-time power consumption sensor data streams; acquiring the processor frequency sequence and the performance throughput sequence reflecting the task progress of the hardware computing partition; calculating a real-time energy efficiency ratio sequence based on the real-time power consumption sensor data stream and the performance throughput sequence; matching the processor frequency sequence and the real-time energy efficiency ratio sequence to construct a coordinate point sequence; retrieving a benchmark energy efficiency curve matching the current computing task and the current running stage from a pre-built task energy efficiency benchmark library; determining the target frequency adjustment value based on the coordinate point sequence and the benchmark energy efficiency curve, and generating a frequency adjustment command. This invention can achieve a better balance between performance and energy consumption.

The present invention relates to the technical field of blood vessel detection, and specifically relates to a blood vessel matching method, device, equipment and storage medium based on a topological graph. According to the curve information in the topological graph, the present invention classifies curves with different information in the same topological graph, and layers the topological graph according to the classification results, that is, the curves on the same layer have the same information, and the curves on different layers have different information. When performing curve matching, the curves on the corresponding topological layered graph are matched, and the matching of the curves is the matching of the blood vessels corresponding to the curves. Laying the topological graph by the present invention can not only improve the blood vessel matching speed, but also reduce the degree of incorrect matching of blood vessels. Only by correctly matching the blood vessels can it help doctors view the changes of the same blood vessel for the diagnosis of patients.

The application discloses a kind of v optimal reference iteration-based blade repair area surface reconstruction algorithm.For the cross section of preprocessed point cloud data, the reference cross section point cloud set is obtained, and the reference cross section curve is obtained by fitting the reference cross section point cloud set;After that, the reference cross section curve group is adopted Gaussian weighting discrete, and the v direction curve group is obtained by fitting in v direction;Based on the optimal principle in v direction, the optimal cross section of repair area is selected, the optimal cross section is intersected with the v direction curve group, the cross section curve of repair area is obtained, the cross section curve of repair area is added to the reference cross section curve group after ICP matching, then the v direction curve group is recalculated, all repair area cross sections are fitted in the form of step-by-step iteration, and the reference cross section curve group is added to the reference cross section curve group, finally, the reference cross section curve group is lofted to obtain the blade repair surface.The accuracy of the repair surface is greatly improved by the iterative method.

The invention discloses a spatial point string and curve matching method, system and device based on double-endpoint normal constraint and a medium, and the method comprises the steps: obtaining a spatial point string and a theoretical curve, and constructing two motion guide rails at the endpoints of the theoretical curve; taking the movement of the space point string starting point along the first movement guide rail as a variable to obtain the position of the space point string ending point on the second movement guide rail; establishing a fixed connection coordinate system, and converting the spatial point string to the fixed connection coordinate system to obtain a conversion point set; an optimization model with the rotation angle around the z axis as a variable is established under the fixedly connected coordinate system, and the optimal rotation angle is solved by minimizing the shortest distance from each conversion point to the theoretical curve; and moving the starting point positions of the spatial point string along the first motion guide rail, solving the final point position and the rotation angle for each starting point position, and determining the globally optimal starting point, final point and rotation angle through one-dimensional search to obtain the optimal matching pose. According to the method, the practicability of the registration result in self-adaptive finish machining of the air inlet and outlet edges of the blade is improved.