53 results about "Filter analysis" patented technology

The invention discloses an information acquisition and transmission system of track control equipment, which relates to the technical field of track traffic intelligent monitoring and comprises an intelligent sensing terminal, an edge intelligent analysis node, a safety communication module, a central control platform, a digital twin diagnosis center and a predictive maintenance engine. According to the invention, the intelligent sensing terminal integrates various sensors, adopts a permalloy shielding cavity to isolate external electromagnetic interference, is equipped with a three-stage lightning protection circuit to realize microsecond-stage lightning surge protection, can stably collect parameters of track control equipment in a severe environment, is internally provided with a lightweight LSTM model, carries out preliminary filtering analysis on original data, and is used for monitoring the parameters of the track control equipment. The device operation state can be dynamically identified, the sampling strategy can be adjusted, the basic sampling frequency is maintained in the stable state to reduce power consumption, the sampling frequency is improved by 10 times and the sensor gain is enhanced in the early warning or emergency state, all analysis decisions are completed at the local millisecond level without depending on the cloud, and the real-time performance and accuracy of data processing are effectively improved.

The invention relates to the technical field of mutual inductor tests, and provides a mutual inductor test abnormal data automatic filtering analysis method and system, and the method comprises the steps: obtaining magnetic field data, electric field data and thermal field data, respectively carrying out the feature extraction and weighted fusion, and obtaining a multi-physical field fusion feature vector; constructing an electromagnetic induction chain type propagation graph, calculating the weight of an edge in the graph, constructing a magnetic flux conservation constraint graph convolutional neural network, learning propagation and evolution modes of transformer test abnormity, and obtaining a coupling abnormity feature vector; the coupling anomaly feature vectors are classified, normal data, single physical field abnormal data and multi-physical field coupling abnormal data are recognized, and corresponding data are judged as abnormal data and filtered; and carrying out physical mechanism analysis on the filtered abnormal data to obtain an abnormal detection report. According to the invention, high-precision automatic identification, filtering analysis and physical mechanism traceability diagnosis of transformer test abnormal data are realized.

The invention relates to a big language model enhanced knowledge adaptive learning planning system, and belongs to the field of intelligent education. The system comprises a knowledge center module, a learner portrait module, a path planning module and an intelligent learning guiding module, and the knowledge center module extracts entities and relationships from a multi-modal data source by using a large language model to construct a knowledge graph; the learner portrait module collects multi-dimensional learning data of the user and maps the multi-dimensional learning data to corresponding nodes of a knowledge graph, and dynamically deduces a learner portrait through a Bayesian knowledge tracking model; the path planning module generates an initial learning path based on the knowledge graph and the learner portrait, establishes a collaborative filtering analysis model, predicts and optimizes the expected effect of the current learner following the initial learning path in combination with a Bayesian knowledge tracking model, and finally generates a target learning path; and the intelligent learning guiding module generates a standardized knowledge card for each knowledge node on the target learning path through a security retrieval enhancement generation technology.

The invention relates to the technical field of mechanical equipment fault diagnosis, and discloses a fault diagnosis method and system for an automatic tensioning control valve of a scraper conveyor. The method comprises the following steps: acquiring pressure and flow data of a main flow channel and an auxiliary flow channel through a sensor array, and extracting frequency domain characteristics to obtain a standardized frequency spectrum; detecting parameter coupling abnormity based on the spectrum cross correlation coefficient and generating an abnormal index; environment interference and medium viscosity data are fused, and non-linear feature distribution and correction deviation representing the mechanical state are obtained through classification and filtering analysis; matching the correction deviation with a preset fault mode, determining a fault type, and generating a fault positioning coordinate in a three-dimensional space by using an optimization algorithm; and finally, performing fluid dynamic simulation through the high-fidelity virtual model to verify the coordinate stability, and outputting accurate early warning when conditions are met. Through cooperation of multi-source information fusion and an intelligent algorithm, the accuracy of early-stage internal fault diagnosis of the complex double-flow-channel valve is improved.

The invention relates to the technical field of image processing, and discloses an underwater image enhancement method based on a Retinex algorithm, and the method comprises the steps: firstly obtaining an underwater original image, and extracting multi-dimensional feature information through a preprocessing module (including a histogram analysis unit, a filtering analysis unit and the like); and multi-scale processing is supported, a target processing scale is detected during multi-scale simultaneous processing, and the feature confidence is calculated to screen the optimal feature. The Retinex algorithm processing unit adopts a multi-branch fusion structure (color correction, contrast adjustment and detail recovery branch), generates coefficients and fuses the coefficients to realize enhancement, and can dynamically adjust weights and parameters according to coefficient differences. The method comprehensively extracts features, performs adaptive multi-scale processing, balances the enhancement effect, improves the underwater image quality, and is suitable for underwater image optimization.

The invention discloses a metal plate defect imaging method based on laser ultrasound and surface wave number filtering analysis, and aims to position defect positions and invert defect shapes by using metal plate surface wave echoes. The position of detection light of a laser vibration meter is determined on the surface of a fixed metal plate, and multiple groups of ultrasonic data are obtained by performing field scanning on the surface of the same side of the metal plate through a field scanning system. Performing wavelet transform on the obtained surface wave data to remove a low-frequency component in the signal, and performing Fourier transform on a time component to obtain a frequency spectrum; and then extracting signal data of a specific frequency and carrying out two-dimensional Fourier transform to obtain a wave number spectrum. And finally, filtering and inverse Fourier transform are carried out on the wave number spectrum to obtain a defect image, and defect positioning and defect shape imaging are realized.

The embodiment of the invention provides a high-precision temperature field real-time monitoring method and device based on multi-sensor fusion, and the method and device achieve the effective collection of data through the innovative design of a sensor deployment system and the arrangement of an optimization and calibration mechanism. And a fusion processing mechanism is constructed, and reliable temperature estimation is established in combination with filtering analysis and weight calculation. And reconstruction optimization is introduced, and monitoring comprehensiveness is ensured through an interpolation algorithm and a compensation function. According to the method, the defects of the traditional technology in the aspects of sensor deployment, data fusion, temperature field reconstruction and the like are effectively overcome, and technical guarantee is provided for temperature field monitoring.

The invention belongs to the technical field of frequency converter supervision, and particularly relates to an operation monitoring method and system for a frequency converter, and the system comprises a server, a power fault detection module, a cooling operation monitoring module, a filter screen analysis module and a remote monitoring early warning module. According to the invention, the power fault detection module monitors the power of the frequency converter and identifies the power fault of the frequency converter, the power risk of the frequency converter can be gradually and comprehensively analyzed and early warned in time, and the cooling operation monitoring module reasonably analyzes the operation performance of the cooling fan in the frequency converter and accurately feeds back the operation performance. And when a cooling operation qualified signal is generated, a filter screen analysis module is used for carrying out inspection emergency analysis on a filter screen at an air inlet in the frequency converter, so that background management personnel can take corresponding treatment measures in time, safe and stable operation of the frequency converter is ensured, the management difficulty of the frequency converter is remarkably reduced, and the intelligent level is high.

The embodiment of the invention provides an unknown cross-site script security detection method and device generated based on a test script, and intelligent construction of the test script is realized through innovatively constructing a script generation mechanism driven by a Markov chain and through atomic element sequence analysis and a random walk strategy. And designing a DOM tree difference-based filtering analysis mechanism, and establishing a filtering rule identification strategy in combination with multi-dimensional mark extraction and node positioning. And a matrix iterative optimization mechanism is introduced, and self-adaptive optimization of the test script is realized through dynamic updating and convergence calculation of a state transition matrix. According to the method, the defects of the traditional technology in the aspects of script generation, filtering analysis, optimization adjustment and the like are effectively overcome, and the unknown cross-site script detection effect is remarkably improved.

This invention discloses a metal plate defect imaging method based on laser ultrasound and surface wave wavenumber filtering analysis. Its purpose is to use surface wave echoes from the metal plate to locate the defect position and inversely interpret the defect shape. The method determines the position of a laser vibrometer's detection light on the surface of a fixed metal plate and uses a field scanning system to scan the surface on the same side of the metal plate to obtain multiple sets of ultrasonic data. The obtained surface wave data is then subjected to a wavelet transform to remove low-frequency components from the signal, and the time component is Fourier transformed to obtain a frequency spectrum. Subsequently, signal data at specific frequencies is extracted and subjected to a two-dimensional Fourier transform to obtain a wavenumber spectrum. Finally, the wavenumber spectrum is filtered and inverse Fourier transformed to obtain a defect image, achieving defect location and defect shape imaging.

The invention provides a weld joint feature point extraction method and device and a storage medium, and belongs to the technical field of weld joint extraction, and the method comprises the steps: carrying out the image collection of a to-be-extracted light strip through a calibrated gray camera, and obtaining a plurality of original light strip images; preprocessing each original light strip image to obtain a preprocessed light strip image; performing filtering analysis on each preprocessed light strip image through a filtering network to obtain a filtered light strip image; and performing center point extraction and analysis on all the filtered light strip images to obtain a plurality of target center point coordinates. According to the method, the light strip noise can be effectively removed, and the light strip center extraction precision is greatly improved, so that high-precision weld joint feature point extraction is realized, and the problem that the light strip center with strong reflection interference is difficult to extract is solved.

A method of operating an encoder or a decoder. The method includes receiving an analysis signal of an audio signal and a filtered analysis signal, combining the filtered signal with the analysis signal to generate a combined signal using a max function that provides at least one of a maximum positive value at each index i of the combined signal and a maximum negative value at each index i of the combined signal. The method includes identifying a wide peak and a narrow peak of the combined signal.

The application relates to the technical field of computing data processing, and discloses a multi-dimensional power transmission and distribution equipment operation data acquisition and edge computing processing system, which comprises a data compression module, the data compression module comprises an edge node configured at an equipment side, carries out filtering analysis and compression on collected data of power transmission and distribution equipment, and establishes a ring-shaped original buffer area used for storing uncompressed original data for a short time before the data is compressed. The application realizes the pre-simulation of the decompression data result of the data center at the edge node by decompressing the compression package in the data simulation area in a consistent logical manner with the data center, compares the original sample in the ring-shaped original buffer area, can pre-quantify the data distortion caused by filtering and compression in the edge node without affecting the front-end collection and uploading, and does not need to wait until the data is used in the data center to expose the problem.

The application discloses a decision knowledge base construction method and a data center intelligent regulation and control method and device. The decision knowledge base construction method comprises the following steps: obtaining an initial decision corresponding to a preset moment from an initial knowledge base constructed based on historical experience of a target scene and executing; obtaining key execution data corresponding to each collection period in an evaluation window after waiting for an evaluation delay; generating a candidate knowledge item set; performing serial filtering analysis on the item set according to objective indexes; obtaining an objective passing item set and an objective passing rate; when the objective passing rate is greater than a threshold value, performing subjective analysis on the objective passing item set to obtain a subjective passing item set; then performing timeliness analysis on the item set; storing a knowledge item meeting a condition to the initial knowledge base; and taking the updated initial knowledge base as a decision knowledge base. The method can obtain safe, reliable, stable and not outdated knowledge, realize effective reuse of the knowledge and effectively improve the intelligence and accurate regulation and control of the system.

A design method for a lumped narrowband IPD filter based on N+2 coupling theory is presented. This invention addresses the problems of existing methods for calculating transmission zero locations being difficult to apply to IPD processes and for quickly providing component values. The design method comprises: 1. Performing bandpass frequency transformation on the admittance matrix equation; 2. Setting the cross-coupling factor between resonators i and k in the coupled filter network as M. ik The cross-coupling factor M is characterized by a PI-type capacitor network. ik ; 3. When M ik When it is positive, it belongs to magnetic coupling, M ik When the value is negative, it indicates electrical coupling. Fourth, the designed narrowband IPD filter circuit undergoes evolution and simplification processing, including source impedance transformation, narrowband approximation of magnetic coupling, and negative capacitance narrowband approximation, to solve for the component values ​​of each element in the circuit structure. This invention starts from the topology of the coupled filter and utilizes various narrowband filter analysis methods to achieve the evolution and simplification of the circuit structure.

The invention relates to the technical field of biomedicine, in particular to a method for detecting ctDNA without obtaining a lymphoma tissue sample and application. Comprising the following steps: 1, collecting a blood sample; 2, constructing a hybrid library; 3, bioinformatics analysis; the blood sample is derived from peripheral blood. On the basis of a next-generation sequencing technology, a tumor tissue sample does not need to be obtained, the ctDNA content of the sample can be detected and determined only by collecting a peripheral blood sample of a lymphoma patient, and the treatment effect of the patient can be predicted by combining the ctDNA content value and the equivalent value multiple change in the treatment process. Plasma cfDNA and leukocyte genome DNA are collected, and UDI and UMI molecular tags are adopted for NGS sequencing library construction. After sequencing, cfDNA sample sequencing data and leukocyte genome DNA sample sequencing data are combined for filtering analysis, and the ctDNA equivalent of the sample can be accurately calculated.

The invention relates to the technical field of chemical process simulation, in particular to a gas-solid two-phase flow inter-phase heat transfer calculation method, system and equipment, and solves the problem that current accurate fine grid numerical simulation can only be limited to laboratory scale calculation and cannot be used for large-scale calculation through filtering analysis and fitting to obtain a gas-solid two-phase flow inter-phase heat transfer calculation model. In the process of amplifying to the industrial scale, the calculation cost cannot be borne by using fine grid simulation; and meanwhile, the problem that a high-precision mesoscale gas-solid interphase heat transfer model is lacked in coarse grid calculation is solved, and the calculation precision is ensured while the calculation efficiency is improved.

The application discloses a kind of integrated characterization method and system for ceramic microstructure, comprising: sampling and cutting of the ceramic sample to be measured;Metallographic grinding and surface polishing processing of the ceramic sample to be measured;Positioning mark of the ceramic sample to be measured;High-precision collection of surface three-dimensional topography height information of the ceramic sample to be measured region;Surface three-dimensional topography height information result filtering analysis;Surface three-dimensional topography height information display setting;Surface three-dimensional topography height information image recognition;Microstructure quantitative analysis based on image recognition result;Analysis result display obtains different microstructure quantitative analysis.The application is based on the collection of surface three-dimensional topography height information of the metallographic polishing surface of ceramic material, combined with filtering analysis and image recognition software and quantitative analysis algorithm, to obtain the integrated quantitative analysis of ceramic and ceramic matrix composite microstructure based on three-dimensional surface topography height information collection and image recognition analysis.

The application relates to the technical field of mechanical equipment fault diagnosis, and discloses a fault diagnosis method and system of an automatic tension control valve of a scraper conveyor; the method comprises the following steps: collecting pressure and flow data of a main flow channel and an auxiliary flow channel through a sensor array, extracting frequency domain features to obtain a standardized frequency spectrum; detecting parameter coupling abnormalities and generating abnormal indexes based on a frequency spectrum cross-correlation coefficient; fusing environmental interference and medium viscosity data, obtaining nonlinear feature distribution and correction deviation representing mechanical states through classification and filtering analysis; matching the correction deviation with a preset fault mode, determining a fault type, and generating fault positioning coordinates in a three-dimensional space by using an optimization algorithm; finally, verifying the stability of the coordinates through fluid dynamics simulation of a high-fidelity virtual model, and outputting a precise early warning when the conditions are met; the application improves the accuracy of early internal fault diagnosis of a complex double-flow valve through multi-source information fusion and intelligent algorithm cooperation.

The invention provides a laser micro-nano machining control method and system for coping with complex structure design, and relates to the technical field of laser micro-nano machining, and the method comprises the steps: firstly obtaining a discrete point cloud cluster of a target complex micro-nano structure and a set texture feature constant, expanding discrete point cloud, carrying out topological distance filtering analysis, and generating a vein persistence graph; analyzing the venation nodes based on a preset processing strategy to obtain a venation affiliation result, and calculating the complex saturation to judge the processing difficulty; if the point is the source structure point, planning a smooth benchmarking guide map according to the surface element size and the normal vector of the one-class discrete point cloud, and controlling processing; and if the structural points are derivative structural points, evaluating second-class discrete point clouds to obtain difficulty coefficient freeze-frame, disassembling and searching a global common track, and controlling processing. According to the method, smooth processing of the source complex pattern and rapid communication processing of the derivative complex pattern can be correspondingly executed according to different complex saturation conditions, so that the stability of the complex micro-nano structure is improved.

The invention provides a multi-source information fusion-based key point extraction method for medical and invasive resources, and belongs to the technical field of key point extraction of medical and invasive resources. On the basis of multi-source heterogeneous data acquired by multiple parties, an original medical and invasive resource database is constructed, and medical and invasive resource statements are sorted according to an execution sequence of database operation statements to support efficient sorting and rapid screening analysis of data in the database by a user, so that the efficiency of subsequent data processing and information extraction is improved, and the user experience is improved. Core information is subjected to cross validation and complementary enhancement, structured integration of medical and invasive resources is realized, general rules, consensus cognition and core challenges in the field can be summarized on the basis of a constructed medical and invasive resource fusion model, and advantages and disadvantages of the medical and invasive resources in a database are deeply mined, so that a medical and invasive resource fusion model is established. The accuracy, adaptability and practicability of key point extraction of the medical and invasive resources under the background of multi-source information fusion are remarkably improved.

The invention discloses a decision knowledge base construction method and a data center intelligent regulation and control method and device. The decision knowledge base construction method comprises the steps of obtaining an initial decision corresponding to a preset moment from an initial knowledge base constructed based on historical experience of a target scene, executing the initial decision, after waiting for evaluation delay, obtaining key execution data corresponding to each collection period in an evaluation window, generating a candidate knowledge item set, performing serial filtering analysis of objective indexes on the item set to obtain an objective passing item set and an objective passing rate, performing subjective analysis on the objective passing item set to obtain a subjective passing item set when the objective passing rate is greater than a threshold value, then performing timeliness analysis on the item set, storing knowledge items meeting conditions into an initial knowledge base, and obtaining an objective passing item set; and taking the updated initial knowledge base as a decision knowledge base. According to the method, safe, reliable, stable and timely knowledge can be obtained, effective reuse of the knowledge is realized, and intelligent and accurate regulation and control of the system are effectively improved.

This application provides a method and apparatus for detecting unknown cross-site scripting (XSS) based on test script generation. It innovatively constructs a Markov chain-driven script generation mechanism and achieves intelligent construction of test scripts through atomic element sequence analysis and random walk strategies. A filtering analysis mechanism based on DOM tree difference is designed, combining multi-dimensional tag extraction and node localization to establish a filtering rule recognition strategy. A matrix iterative optimization mechanism is introduced, achieving adaptive optimization of the test script through dynamic updating and convergence calculation of the state transition matrix. This method effectively addresses the shortcomings of traditional techniques in script generation, filtering analysis, and optimization adjustment, significantly improving the detection effect of unknown XSS.

The present application relates to the technical field of mutual inductor test, and provides a mutual inductor test abnormal data automatic filtering analysis method and system, which comprises the following steps: acquiring magnetic field data, electric field data and thermal field data, respectively performing feature extraction and weighted fusion to obtain a multi-physical field fusion feature vector; constructing an electromagnetic induction chain type propagation graph, calculating the weight of the edges in the graph, constructing a magnetic flux conservation constraint graph convolutional neural network, learning the propagation and evolution mode of the mutual inductor test abnormality, and obtaining a coupled abnormal feature vector; classifying the coupled abnormal feature vector, identifying normal data, single physical field abnormal data and multi-physical field coupled abnormal data, determining the corresponding data as abnormal data and filtering; and performing physical mechanism analysis on the filtered abnormal data to obtain an abnormality detection report. The present application realizes high-precision automatic identification, filtering analysis and physical mechanism tracing diagnosis of mutual inductor test abnormal data.

The present invention discloses a method and system for detecting illegal buildings by oblique photography based on superpixels and morphology, and the method comprises: obtaining first surface height image data, first surface orthophoto image data of a target area in a first time period, and second surface height image data and second surface orthophoto image data of a second time period; calculating height change image data of the target area; performing superpixel segmentation processing on the height change image data to obtain superpixel units; performing object clustering and filtering analysis on the superpixel units using architectural morphology indexes to obtain vector data of the target area. The present invention obtains height change image data based on surface height image data of different time periods, and performs post-processing on the height change image data through superpixel segmentation and architectural morphology analysis, thereby solving the problems of recognition accuracy and algorithm efficiency, and thus realizing accurate detection of urban building changes.

The invention provides an anti-crawling application method and system based on ELK log collection, and the method comprises the steps: 1, a request receiving step: carrying out the log cleaning in Logstash after a flow request forwarded by a gateway is received; 2, a flow analysis step: accurately analyzing the peak period and the valley period of the flow in the current time period according to the number of requests in the whole time period, and dynamically adjusting an anti-crawling strategy; 3, an anti-crawling filtering analysis step: intercepting User-Agent, Referer and cookie fields in the request header, comparing the fields with a standard request header in a database, analyzing whether an access path and a flow of the Referer header conform to reasonable user portrait information in the database, and determining whether all interception or partial interception is performed according to a time period; 4, an open customization step: the request is issued to an interface of the airline to enter different modules of the airline according to the type of the request; and 5, a timed pushing step: storing the identified problem IP in a cache, and regularly pushing crawler behavior IP data to an alarm center. Compared with anti-climbing tools in the market, the anti-climbing application method and system adopted by the invention are more flexible, low in deployment cost and easier to maintain.

The invention discloses a method for evaluating the storage stability of modified emulsified asphalt, and belongs to the field of road engineering regeneration. According to the evaluation method, an ultraviolet lamp is utilized to excite the modifier to generate a fluorescence effect, and the storage stability of the modified emulsified asphalt is evaluated by observing the distribution change condition of the modifier. Preparing modified emulsified asphalt by adopting an external doping method, and placing the modified emulsified asphalt in a container for standing; in the standing period, modified emulsified asphalt samples are extracted from different depths of the container respectively, the samples are observed through a fluorescence microscope, binary images of an emulsified asphalt phase and a modifier phase are obtained after filtering analysis and segmentation treatment, and the content of the modified emulsified asphalt is calculated by comparing the fluorescence area difference. And analyzing the distribution change condition of the modifier phase in the emulsified asphalt phase along with the change of the storage time so as to evaluate the storage stability of the modified emulsified asphalt. Compared with a traditional method, the problem that the storage stability of the modified emulsified asphalt cannot be quantitatively evaluated is solved, and a solid foundation is laid for follow-up research on the technical performance of the modified emulsified asphalt.

The invention belongs to the technical field of collaborative filtering algorithms, and discloses a method which utilizes multi-modal data and a deep learning technology and integrates a standardized traditional Chinese medicine diagnosis index system and objective medical data to keep the essence of the traditional Chinese medicine theory and construct a clear scientific verification mechanism. Carrying out multi-modal data acquisition; step 2, data preprocessing; step 3, constructing a multi-modal deep fusion model; 4, performing model training and scientific verification; and step 5, outputting personalized health-care guidance. According to the method, the traditional Chinese medicine theory and the modern data science and technology are integrated, and the accuracy and robustness of health risk assessment are effectively improved through standardized preprocessing and multi-modal deep fusion of multi-source data, so that the assessment result not only reflects the traditional Chinese medicine physique characteristics, but also has objective modern medical data support; therefore, a more personalized and refined health management scheme is provided for the user.

The invention provides a calculation method and system for the activity rate of an oil reservoir group level fault. The calculation method comprises the steps that natural gamma curves of all oil reservoir groups of a preset target layer are sampled at equal intervals; performing spectral analysis on the selected natural gamma curve, and determining that the natural gamma curve has Mie astronomical cycle information; performing filtering analysis on the selected natural gamma curve to obtain a filtering result of the Mie's astronomical cycle information, and calculating the deposition time limit of the stratum of the corresponding oil reservoir group; obtaining the stratum apparent thickness with stable hanging wall and footwall near the fault, performing dip angle correction on the stratum apparent thickness to obtain the true thickness of the hanging wall and footwall stratum of the fault, and calculating the fall of the true fault; and based on the obtained true fault fall and the stratum deposition time limit of the corresponding oil reservoir group, calculating the activity rate of the oil reservoir group level fault. According to the method, the activity of the fault corresponding to a higher-level stratum is analyzed, the calculation precision of the activity rate of the fault is improved, and a higher-level and finer technical method is provided for the analysis of the fracture activity of an oil field.

The invention provides a flowmeter rapid in-situ calibration processing method and system based on a weighing method and a medium. A data acquisition module is used for receiving a flow detection signal sent by a flowmeter sensor and a weight detection signal sent by a weight sensor, and forwarding the signals to a filtering analysis calculation module; the weight detection signal and the flow detection signal are subjected to Kalman filtering processing through a filtering analysis module, and an accurate predicted flow detection signal and an accurate predicted weight detection signal are obtained; and respectively carrying out preorder differential processing on the obtained predicted flow detection signal and the predicted weight detection signal by using an in-situ calibration analysis module, carrying out iterative fitting processing according to flow differential data and weight differential data obtained by the preorder differential processing until a first convergence condition is met, and then carrying out iterative fitting processing according to the flow differential data and the weight differential data obtained by the preorder differential processing. And the final iteration fitting processing result is used as the target in-situ calibration data, so that the obtained target in-situ calibration data is more accurate, and the in-situ calibration of the flowmeter sensor by using the target in-situ calibration data is more accurate.