40 results about "Distortion analysis" patented technology

The invention relates to the technical field of high-frequency signal modulation, and discloses a high-frequency carrier synchronization signal modulation system. A carrier distortion compensation module of the system constructs a model based on a historical transmission data set, captures a phase jitter parameter, a spectrum leakage component and a modulation pulse sequence of a transmitting end carrier in real time, and outputs a reconstructed baseband parameter; the multi-dimensional distortion analysis module compares the reconstructed baseband parameter with a receiving end demodulation baseband parameter through composite difference detection, and generates a channel-level distortion coefficient tensor; the topological positioning network module is used for positioning signal out-of-step physical nodes and generating a probability distribution thermodynamic diagram by combining impedance characteristics of transmission nodes and signal path delay information; and the adaptive modulation strategy module starts a multi-band carrier injection mode for the high-probability out-of-step nodes according to the abnormal probability gradient of the thermodynamic diagram, and applies a phase disturbance test to adjacent transmission links. The system can improve the adaptability and accuracy of high-frequency carrier signal synchronous modulation.

The invention discloses a GIS partial discharge on-line monitoring method, and relates to the technical field of power equipment monitoring and fault diagnosis, and the method comprises the following steps: a detection system carries out the real-time collection of an electrical signal caused by a partial discharge phenomenon in the operation process of GIS equipment through a high-frequency sensor disposed on the GIS equipment, therefore, a data basis for subsequent distortion analysis and positioning is obtained. Partial discharge signals are collected in real time through the high-frequency sensor, signal distortion is evaluated in combination with a machine learning model, the time domain and the frequency domain of the signals are accurately corrected by adopting a dynamic time warping algorithm and a frequency compensation means, and the real characteristics of the signals are recovered. According to the method, the signal positioning precision is improved, the GIS equipment fault detection capability is enhanced, potential risks are warned in advance, equipment faults and safety accidents are reduced, and the safety and stability of a power system are remarkably improved.

The invention belongs to the technical field of power monitoring, and discloses a detection method for monitoring the state of a primary and secondary fusion circuit breaker, which comprises the following steps: acquiring state data of the circuit breaker, including electromagnetic waveform data, harmonic response characteristics and temperature distribution gradient; obtaining circuit breaker electric field distribution fingerprints through nonlinear segmented harmonic analysis, constructing a multi-dimensional permeation characteristic matrix, and establishing a micro-scale electrothermal coupling map; performing impedance distortion analysis to obtain a nonlinear region situation table, performing multi-frequency response analysis to obtain a harmonic penetration curve, and constructing a high-frequency harmonic penetration path spectrum; a micro-region diagnosis algorithm is established, nonlinear impedance calibration is carried out, and a multi-level protection instruction sequence is generated; adjusting the operation state of the circuit breaker to obtain a circuit breaker medium steady-state index, and performing risk analysis to obtain a harmonic penetration early warning report; according to the invention, accurate identification and early warning of the abnormal-state area in the circuit breaker are realized, and the safe and stable operation capability of the primary and secondary fusion circuit breaker is improved.

The invention relates to the technical field of size detection, in particular to a component size detection system based on machine vision, which comprises an interference area identification module, an edge repair module, a structure clustering module, a distortion analysis module and an attitude restoration module. According to the method, the gray level change trend of each pixel and the adjacent points in the image is obtained, the high-reflection suspected interference area is identified, the edge response cancellation processing is executed, and linear interpolation compensation is carried out by combining the effective edge response values of the adjacent areas; after a continuous contour trend is constructed, clustering and sub-grouping division are carried out according to an included angle difference trend between contour geometric vectors, a three-axis direction response linear array variation amplitude is extracted to construct a distortion curvature mapping table, existence of non-equal-interval deformation is judged, reverse angle compensation is applied, and a three-axis intersection point convergence process is completed through a nonlinear optimization algorithm; and according to the three-dimensional coordinates, calculating a geometric dimension and outputting a detection result, thereby realizing self-adaptive detection of different postures and surface interference component dimensions.

According to the laser confocal scanning microscope, the scanning image distortion correction method and the acquisition card provided by the invention, the transflective mirror is fixedly arranged between the resonance galvanometer and the galvanometer galvanometer, and the monitoring light path and the second detector are arranged in the transmission direction of the transflective mirror. The acquisition card is respectively connected with the first detector and the second detector; the confocal signal and the grating signal which are synchronously acquired by the acquisition card in an isochronous manner are twin images in time and space, and the grating image formed by the grating signal depicts the movement of the resonance galvanometer in the scanning process, so that distortion correction can be performed on the twin object plane image of the grating image through distortion analysis on the grating image, and the distortion correction accuracy is improved. Therefore, the correction accuracy is effectively improved, and the method is not easily influenced by factors such as environment, service life and optical path deviation. Moreover, in the distortion correction process, correction is carried out through the odd-numbered line sub-graphs and the even-numbered line sub-graphs, so that the distortion correction accuracy is further improved.

The invention discloses a supply chain material inventory control method and system, and the method comprises the steps: carrying out the demand distortion analysis of the demand signal data of each node in a target supply chain, and obtaining the demand signal distortion amplitude of each node; if the demand signal distortion amplitude exceeds a preset distortion amplitude threshold, performing distortion degree classification prediction on the demand signal distortion amplitude to obtain a real-time demand prediction result of each node; performing sensitivity analysis on the real-time demand prediction result, and generating a safety inventory parameter of each node; generating a collaborative inventory distribution scheme of the target supply chain according to the safety inventory parameters and the information sharing evaluation indexes; and performing cooperative control on the material inventory of each node in the target supply chain according to the cooperative inventory distribution scheme. The flexibility and cooperation efficiency of the supply chain to adapt to the market change can be improved through the cooperation inventory distribution scheme, so that the risk resistance capability is enhanced, and the capability of the supply chain to cope with the market demand fluctuation complex scene is improved.

The invention provides a tree ring structure distortion intelligent analysis system based on a convolutional neural network, which belongs to the technical field of tree ring distortion analysis and comprises an image acquisition module, a preprocessing module, a feature extraction module, a distortion analysis module and an output module. Wherein the image acquisition module is used for acquiring a high-resolution scanning image of a cross section of a tree ring; wherein the preprocessing module carries out deblurring, normalization and environmental perception data enhancement processing on an image; wherein the feature extraction module is used for extracting multi-scale features of an annual ring based on an improved residual convolutional neural network (ResNet-FPN). According to the system, through multi-dimensional fusion of a deep learning technology and environmental science, an efficient and accurate tree ring distortion intelligent analysis platform is constructed, key bottlenecks of a traditional method in the aspects of feature extraction, environment correlation modeling and scene adaptability are solved, and reliable technical support is provided for ecological monitoring, climate research and forestry management.

The invention relates to the field of image data processing and generation, in particular to a numerical control machine tool part state visual online evaluation method, which comprises the following steps: acquiring high-frequency visual image data; and carrying out pixel-level enhancement on the image data by utilizing a combined image enhancement algorithm, and generating multi-modal image data through a multi-channel image fusion technology. And performing frequency domain transformation operation on the multi-modal image data, and constructing a structural topology hash. And generating a baseline hash based on a historical image, performing image feature comparison with the structure topology hash obtained in the current detection period, and generating a risk probability signal and a fine diagnosis signal. And responding to the fine diagnosis signal, generating and reconstructing a multi-modal three-dimensional point cloud image through structured light projection and distortion analysis, and carrying out geometric and texture analysis on the point cloud image to generate a part state evaluation report. According to the method provided by the invention, visual, online and multi-mode state evaluation of the numerical control machine tool part can be realized, and the detection efficiency and accuracy are remarkably improved.

The invention belongs to the field of near-eye light field display equipment, and discloses a region-based imaging correction method and system, and the method comprises the steps: obtaining an original display image from the near-eye light field display equipment, and carrying out the preprocessing of the original image; dividing the display image into a plurality of sub-regions according to the structure of the lens array; distortion analysis is carried out on each sub-region, and geometric and chromatic aberration distortion characteristics of the region are identified; creating a distortion model for each sub-region based on a distortion analysis result; designing a correction algorithm suitable for each sub-region to correct geometric and chromatic aberration distortion of the sub-region; applying the correction algorithm to each sub-region of the original display image to generate a corrected image; and loading the corrected image back to the near-eye light field display device for display. The method has strong robustness, can cope with errors caused by mechanical errors, is wide in applicability, is suitable for various different near-eye light field display devices, and provides reliable technical support for improving image quality and user experience.

This invention relates to the field of laser processing technology, and discloses a method and system for femtosecond laser three-dimensional surface processing based on adaptive optics. The method includes: spatial topology reconstruction of the original point cloud data of the workpiece to be processed to obtain a three-dimensional digital surface; row spacing planning and optimization of the three-dimensional digital surface to obtain a spatial processing trajectory, and point wavefront mapping of the spatial processing trajectory to obtain pre-compensated phase distribution data; optical field distortion analysis of the surface reflected light signal of the workpiece to be processed to obtain the actual wavefront phase; encoding the pre-compensated phase distribution data into an initial wavefront control command for a beam shaping device, and iteratively optimizing the initial wavefront control command to obtain a wavefront supplement signal; and updating the spatial processing trajectory by combining the real-time contour data of the workpiece to be processed. This invention can improve the efficiency of femtosecond laser three-dimensional surface processing based on adaptive optics.

The present application belongs to the technical field of power monitoring, and discloses a detection method for monitoring the state of primary-secondary fusion circuit breaker, comprising: obtaining circuit breaker state data, including electromagnetic waveform data, harmonic response characteristics and temperature distribution gradient; obtaining circuit breaker electric field distribution fingerprint through nonlinear segmented harmonic analysis, constructing a multi-dimensional penetration feature matrix, and establishing a micro-scale electric-thermal coupling atlas; obtaining a nonlinear region situation table through impedance distortion analysis, obtaining a harmonic penetration curve through multi-frequency response analysis, and constructing a high-frequency harmonic penetration path spectrum; establishing a micro-region diagnosis algorithm, performing nonlinear impedance calibration, and generating a multi-level protection instruction sequence; adjusting the operating state of the circuit breaker, obtaining the circuit breaker medium steady-state index, and performing risk analysis to obtain a harmonic penetration early warning report; the present application realizes accurate identification and early warning of abnormal regions inside the circuit breaker, and improves the safe and stable operation ability of the primary-secondary fusion circuit breaker.

The embodiment of the invention provides a wall flatness detection method and system based on projection image distortion analysis, and the method comprises the steps: obtaining a plurality of groups of standard template images and a plurality of groups of deformation images of a to-be-detected wall under the condition that the perpendicularity self-calibration of detection equipment is completed; wherein the number of the plurality of groups of deformation images is consistent with that of the plurality of groups of standard template images, and the plurality of groups of deformation images are images formed on the surface of the to-be-detected wall by the plurality of groups of standard template images; based on the plurality of groups of standard template images and the plurality of groups of deformation images, performing pairing to obtain a plurality of groups of image pairs; feature extraction and fusion are carried out on the multiple groups of image pairs through a convolutional neural network to obtain a wall surface flatness map; based on the wall flatness map, flatness index quantitative calculation and compliance judgment are carried out, and a wall flatness detection result is obtained. According to the scheme, the accuracy and efficiency of wall flatness detection can be improved.

The invention discloses a multi-channel video real-time processing method and a multi-channel video real-time processing system based on an embedded computer platform, and relates to the technical field of multi-channel video processing. Obtaining rotation dynamic distortion analysis information in a video collected by a camera in the state in real time, and respectively generating a rotation track deviation index and an edge contour distortion coefficient; constructing a rotation distortion prediction model for the generated rotation track deviation index and the edge contour distortion coefficient, and generating a rotation distortion prediction coefficient; and performing prediction analysis based on the generated rotation distortion prediction coefficient, and predicting the distortion degree of the image in the video collected by the camera when the target rotates at a high speed and the rotation direction changes nonlinearly. According to the method, the problem of image distortion caused by nonlinear change of a high-speed rotating target is solved, and the image quality and the processing efficiency are improved through real-time prediction and dynamic optimization of a motion compensation strategy.

A method for characterizing single-phase grounding faults in a distribution network that takes into account nonlinear arc resistance includes: constructing a discretized computer simulation model of the arc model; determining fault arc model parameters for the discretized computer simulation model constructed under different conditions based on measured data of arcs generated when a distribution conductor passes through concrete, asphalt pads, gravel patches, or grassy areas when a single-phase grounding fault occurs; inputting the fault arc model parameters into the discretized computer simulation model of the arc model, integrating them with the normal operation model of the distribution network to form a discretized computer simulation model of the distribution network single-phase grounding fault; and performing characterization analysis of the distribution network single-phase grounding fault characteristics including nonlinear arc resistance based on zero-sequence current harmonic extraction and distortion analysis. The present invention implements electromagnetic transient simulation of arc faults occurring on distribution lines on grass, gravel, concrete, asphalt roads, or trees, meeting the needs of arc fault detection for single-phase grounding faults in distribution networks.

The invention relates to the technical field of transformer detection, in particular to an intelligent state detection system for a dry-type transformer, and the system comprises a data obtaining module which is used for obtaining the environment parameters and operation parameters of the dry-type transformer; the load type determination module is used for determining the operation load type of the dry-type transformer based on the operation parameters; the potential fault positioning module is used for responding to a low load type and positioning a potential fault position based on the operation parameters; the detection path planning module is used for determining a detection path based on the potential fault position and the three-dimensional structure model; and the path adjustment module is used for determining a fault influence area corresponding to the detection position based on the fault detection result, and adjusting a subsequent detection path based on the fault influence area. According to the method, through the technical means of combining iron core vibration distortion analysis under the low-load working condition with dynamic path planning and adjustment, the beneficial effects of accurately positioning potential faults in the low-load period and adaptively optimizing the detection path are achieved.

The application discloses a kind of based on multimodal feature fusion's ultra-high-definition video AI repair method, it is related to video repair technical field, for solving the structure drift after reference frame pollution cannot be accurately identified, and the structure misplacement of repair area appears in continuous playing process Problem, by executing code rate fluctuation detection and adjacent frame jitter analysis to the video stream to be measured, to identify structure distortion state, video stream is decoded and extracted coding structure information, the frame level dependency graph corresponding to video frame is constructed, motion vector amplitude is collected and distortion intensity is generated in combination with frame distortion analysis result, the initial frame weight is dynamically regulated, to evaluate the propagation trend of distortion in reference frame link, fusion audio feature data and visual feature data execute consistency determination, in combination with distortion propagation trend mark candidate distortion area, and utilize AI image repair model to execute different reconstruction repair to candidate distortion area, avoid the structure misplacement problem caused by traditional local enhancement.

The present application belongs to the field of unmanned driving, and proposes a point cloud distortion correction method based on dynamic vehicle detection in an unmanned driving scene, which comprises the following steps: step 1, point cloud distortion analysis and data generation; step 2, point cloud global distortion correction based on laser radar motion analysis; step 3, point cloud local distortion correction based on vehicle motion analysis; and step 4, point cloud distortion correction in an unmanned driving scene. The method of the present application improves the accuracy of three-dimensional reconstruction and three-dimensional positioning in unmanned driving, and effectively overcomes the safety hazards of intelligent motion behavior of unmanned driving.

The present application relates to the technical field of size detection, in particular to a component size detection system based on machine vision, which comprises an interference area identification module, an edge repair module, a structure clustering module, a distortion analysis module and a posture restoration module. In the present application, by obtaining the gray level change trend of each pixel and its adjacent points in the image, the high reflection suspected interference area is identified and the edge response is invalidated, the linear interpolation compensation is performed in combination with the effective edge response value of the adjacent area, the continuous contour trend is constructed, the clustering and sub-grouping division are implemented according to the difference trend of the angle between the contour geometric vectors, the three-axis direction response line array change amplitude is extracted to construct a distortion curvature mapping table and judge the existence of non-equal interval deformation, the reverse angle compensation is applied, and the three-axis intersection point convergence process is completed through a nonlinear optimization algorithm, the geometric size is calculated according to the three-dimensional coordinates, and the detection result is output, so that the adaptive detection of the size of components with different postures and surface interference is realized.

The invention provides an arch wire recommendation method and device, electronic equipment and a storage medium. The method comprises the following steps: acquiring a tooth image of an object body acquired by image acquisition equipment; performing distortion analysis on the tooth image according to the to-be-corrected parameters corresponding to the key process nodes of the tooth correction to obtain to-be-corrected parameter information of a tooth distortion part; the to-be-corrected parameter information comprises tooth alignment parameter information and tooth leveling parameter information; according to the tooth alignment parameter information and the tooth leveling parameter information, comparing the tooth alignment parameter information and the tooth leveling parameter information with a corresponding reference datum, and generating correction reference information of a reference scheme corresponding to the tooth alignment parameter information and the tooth leveling parameter information; the correction reference information of the reference scheme comprises an arch wire model and a single use cycle of the arch wire; and displaying correction reference information of the reference scheme on a display interface. Therefore, manual consideration for obtaining the correction reference information of the reference scheme is reduced, and manpower is saved.

The invention discloses a hidden perception spoofing attack detection method based on self-diagnosis space consensus. The method comprises the following steps: acquiring a state vector set reported by all user equipment based on own received signals; the state vector set comprises a state vector corresponding to each user equipment; the state vector comprises a position estimator, a speed estimator and a power measurement index; dividing the state vector set into a plurality of clusters by adopting a consensus clustering algorithm based on a kernel function; calculating a consistency metric for each cluster to determine an initial attack cluster; and carrying out feature structure distortion analysis and RCS consistency verification based on the initial attack cluster, thereby providing a detection method capable of effectively identifying hidden perception spoofing attacks such as cross-UE space collaborative spoofing, parameter adaptive time sequence camouflage and high-simulation physical layer signal replication.

The invention discloses an energy-saving water pump parameter adaptive scheduling method and system, and relates to the technical field of water pump control, and the method comprises the steps: collecting active power data of a frequency converter, pipeline pressure data, pipeline flow data and motor rotation speed data; performing time alignment processing; response feature extraction is carried out on the water pump operation condition data after time alignment processing, and dynamic response features are obtained; performing dynamic behavior distortion analysis according to a dynamic response reference model and the dynamic response characteristics to obtain a dynamic behavior distortion analysis result; and if the dynamic behavior distortion analysis result is that behavior distortion exists, cancelling the modification of the multiplicative correction coefficient on the water pump parameters. According to the method, behavior distortion can be analyzed in combination with water pump operation condition data and dynamic response characteristics, and water pump parameter modification is canceled, so that water pump parameter adaptive scheduling is realized, accuracy and stability are improved, and energy consumption per unit water volume is reduced.

The invention discloses a self-adaptive control method and system for an inverter. The method comprises the following steps: acquiring current operation sampling data, working condition parameters and device rated parameters of an arc load in real time; performing fast Fourier transform to obtain spectral characteristic data; based on the arc load model library, optimization parameter adjustment is carried out, and preliminary control parameters are obtained; inputting the current operation sampling data into a pre-trained support vector machine model to obtain a target control parameter; performing load adjustment based on a fuzzy logic control algorithm to obtain adjusted current operation sampling data; distortion analysis is carried out to obtain an adjustment result, and the initial control parameters are adjusted to obtain initial control parameters; working condition analysis and adjustment are carried out according to the environment temperature, the device rated parameters and the initial control parameters, and final control parameters are obtained. According to the method, self-adaptive control of the inverter on the arc load is realized, and sensitive and accurate control of stable combustion of the arc is realized.

The invention discloses a UWB space positioning method and system, and relates to the technical field of wireless communication positioning navigation.The high-precision positioning is achieved through a UWB label, multiple base stations, an intelligent temperature control clock module and a data processing center, the distance is calculated through the TWR technology, and the intelligent temperature control clock module is connected with a temperature sensor through a phase-locked loop circuit and a constant-temperature control unit; dynamically compensating the temperature drift to synchronize the clock frequency; the positioning method comprises the following steps: receiving base station distance data and signal characteristics, realizing multi-modal NLOS identification through signal distortion analysis, obstacle detection and motion continuity judgment in combination with environment perception and motion trail data, and screening candidate base stations; selecting a base station with the lowest NLOS probability as a reference, compensating and correcting distance data through Kalman filtering motion prediction, and fusing results of multiple base stations to determine a target position; and virtual reference points can be set to optimize positioning, so that the positioning precision and stability in a complex environment are effectively improved.

The invention belongs to the technical field of valve sealing performance testing, aims to solve the problems that in the prior art, microscopic symptoms of flow state transition cannot be captured in the extremely early stage of leakage development, and the essential type of a fault cannot be further deconstructed from the coupling relation of multi-source data, and particularly relates to a valve sealing performance testing system based on multi-source data fusion. Comprising an operation parameter acquisition module, a dynamic feature extraction module, a mapping analysis module, a distortion analysis module and a state evaluation module. According to the method, a reference coordinate system with a pressure zero crossing point as a time anchor point is constructed, a flow zero crossing point is mapped into the coordinate system, and traditional macroscopic magnitude comparison is converted into microstructure analysis of a pressure-flow coupling relation; the fundamental transformation of leakage early warning from'macroscopic threshold triggering 'to'microstructure distortion capturing' is realized, and the timeliness of early detection of leakage is remarkably improved.

The invention belongs to the technical field of information management, and provides an intelligent information service management system, which comprises the following steps of: acquiring full-link data of information transmission in a historical period by adopting an Flink stream processing framework, and constructing a full-link information analysis library; based on the full-link information analysis library, content distortion and aging distortion analysis is carried out on the distortion degree of information transmission in work, and the distortion degree of full-link data in work is evaluated; if the working full-link data distortion is serious, performing quantitative deviation analysis on all works with serious full-link data distortion in a historical period, evaluating hierarchical distortion risks in the works, identifying serious distortion hierarchies, and requiring a processor of the serious distortion hierarchies to re-check and supplement original information; according to the method, the serious distortion level in the whole link is positioned, and the risk is quantified by fusing the double dimensions of the distortion occurrence frequency and the severity, so that targeted rectification and level process optimization are realized.

This invention discloses a supply chain inventory control method and system. The method includes performing demand distortion analysis on demand signal data at each node in the target supply chain to obtain the distortion amplitude of the demand signal at each node; if the distortion amplitude exceeds a preset distortion amplitude threshold, classifying and predicting the distortion degree to obtain the real-time demand forecast result for each node; performing sensitivity analysis on the real-time demand forecast result to generate safety stock parameters for each node; generating a collaborative inventory allocation scheme for the target supply chain based on the safety stock parameters and information sharing evaluation indicators; and collaboratively controlling the inventory of materials at each node in the target supply chain according to the collaborative inventory allocation scheme. This collaborative inventory allocation scheme can improve the flexibility and efficiency of the supply chain in adapting to market changes, thereby enhancing its risk resistance capabilities and improving its ability to cope with complex scenarios of fluctuating market demand.

The invention discloses an electrolysis cooperative control method and system based on electrochemical state feedback, and relates to the technical field related to electrolysis control, and the method comprises the steps: monitoring a steady-state operation signal of an electrolysis unit, applying controlled perturbation excitation, synchronously collecting an unsteady-state response signal, and carrying out distortion analysis, transient impedance spectrum extraction and phase drift analysis on the unsteady-state response signal, so as to obtain an unsteady-state response signal; obtaining a dynamic feature set; in combination with the steady-state reference features, the combined features are mapped to a unified projection space for electrochemical state inversion, and a state feedback quantity is generated; and extracting state evolution characteristics and judging an evolution interval, and generating a cooperative control strategy according to the evolution interval to execute electrolysis cooperative control management. The technical problems that in the prior art, electrochemical state sensing is lagged and one-sided, dynamic information utilization is lacked, and multi-unit cooperative control is extensive are solved, and the technical effects that the state sensing real-time performance of the electrolysis process, cooperative control accuracy and foresight and the overall energy efficiency and service life of cooperative operation of multiple electrolysis units are improved are achieved.

The invention provides a 5G NR signal modulation distortion intelligent analysis method, and relates to the technical field of signal processing. The method comprises intelligent synchronous detection, carrier synchronization, channel estimation and equalization, reference signal generation and modulation distortion analysis, and the intelligent synchronous detection comprises PSS detection, SSS detection, determination of the maximum sending number Lmax of SS / PBCH in a burst set period, half-frame number detection, determination of SS / PBCH patterns and the burst set period and frame synchronization. According to the modulation distortion analysis, error vector amplitude is calculated, and original point offset, orthogonal error and gain imbalance evaluation are adopted in a matched mode for modulation distortion analysis and evaluation. According to the method, complex parameter configuration of 5G NR signal analysis is reduced through intelligent synchronous detection, high-precision modulation distortion analysis of 5G NR signals is achieved through the provided 5G NR signal modulation distortion test analysis method in a matched mode, the modulation performance of 5G equipment is analyzed on the basis of multiple dimensions, and a foundation is laid for comprehensive index testing of the 5G equipment.

The application discloses an adaptive control method and system of an inverter, and the method comprises the following steps: acquiring current operation sampling data, working condition parameters and device rated parameters of an arc load in real time; performing fast Fourier transform to obtain frequency spectrum characteristic data; based on an arc load model library, performing optimization parameter adjustment to obtain preliminary control parameters; inputting the current operation sampling data into a pre-trained support vector machine model to obtain target control parameters; performing load adjustment based on a fuzzy logic control algorithm to obtain adjusted current operation sampling data; performing distortion analysis to obtain an adjustment result, and adjusting the preliminary control parameters to obtain initial control parameters; and performing working condition analysis and adjustment according to the environmental temperature, the device rated parameters and the initial control parameters to obtain final control parameters. The method realizes adaptive control of the inverter on the arc load, and realizes sensitive and accurate control of arc stable combustion.