41 results about "Corrosion morphology" patented technology

The invention discloses a scanning electrochemical microscope in-situ stress corrosion testing device and method, and belongs to the technical field of material stress corrosion testing, and the device comprises a base, a power transmission module, a clamping module, a corrosion module, a signal acquisition module and a scanning electrochemical microscope module. Slow strain rate stretching of a sample is achieved through a servo motor, a planetary gear speed reducer and a transmission mechanism, the clamping module is integrated with a force sensor to monitor loads in real time, the corrosion module provides a temperature-controllable corrosion environment, and the scanning electrochemical microscope module achieves electrochemical scanning of the surface of the sample. The device can synchronously obtain a load-deformation curve, corrosion morphology and microcell electrochemical information under stress-corrosion-temperature multi-field coupling, and provides an effective technical means for deeply researching a stress corrosion mechanism of a material. The method comprises the steps of sample installation, corrosion solution preparation, electrode arrangement, tensile test, electrochemical scanning and the like, and has the advantages of simplicity and convenience in operation, comprehensive data, high precision and the like.

The invention belongs to the technical field of vehicle-mounted controller heat dissipation evaluation, and particularly discloses a vehicle-mounted controller salt fog environment heat dissipation evaluation method and system, and the method comprises the steps: initial heat distribution data collection, salt fog environment dynamic simulation, thermal performance evaluation parameter calculation and heat dissipation capability comprehensive evaluation. Through multi-source heat distribution data acquisition and gridding processing, the limitation of a single temperature measurement mode is overcome; establishing a multi-dimensional mapping model of the salt mist sedimentation rate, the airflow velocity and the thermal resistance increment value, and dynamically adjusting test conditions; the influence of salt spray corrosion on the heat dissipation performance is analyzed and quantified in combination with corrosion morphology, and key index weight configuration is optimized. According to the invention, the accuracy and dynamic adaptability of the evaluation result can be improved, and reliable support is provided for the heat dissipation performance test of the vehicle-mounted controller.

An old well corrosion oil casing safety evaluation and life dynamic prediction method is characterized in that based on old well basic parameters and a well bore structure, pipe mechanics, thermodynamics and electrochemical experiments are carried out, and a corrosion rate model is established; then, on the basis of the pipe corrosion morphology / contour, utilizing SOLIDWORKS to establish a three-dimensional geometric model of the casing containing corrosion damage, importing ABAQUS finite element simulation software, simulating the corrosion depth, the time-varying strength and the residual life of the casing under different service conditions, and establishing a prediction model of the corrosion depth of the casing, the time-varying strength of the corroded casing and the residual life of the corroded casing; in combination with on-site underground service conditions and casing damage detection data, an isolation forest method and a data cleaning technology are adopted to preprocess original data, then required parameters are input into a prediction model for dynamic prediction, and the method provides a basis for petroleum engineers to predict the residual life of the casing with corrosion defects according to the on-site service conditions. The method is suitable for the technical field of petroleum and natural gas drilling engineering.

The invention discloses an anchor rod corrosion morphology three-dimensional reconstruction method and system based on three-dimensional laser scanning. The method comprises the following steps: acquiring anchor rod surface point cloud data through three-dimensional laser scanning and preprocessing the anchor rod surface point cloud data; performing serialized slicing processing on the point cloud, and establishing a local coordinate system axially aligned with the anchor rod; adopting an improved RANSAC (Random Sample Consensus) algorithm with adjacent slice continuity constraint, fitting the contour of the non-rusted reference circle piece by piece, and reconstructing a reference geometric shape; the corrosion degree is quantified by calculating the corrosion deviation value of the actual contour point and the reference circle, and is converted into polar coordinates to analyze circumferential distribution; and on the basis of the corrosion deviation value, a three-dimensional morphology cloud picture and a polar coordinate expansion picture are generated through bidirectional dynamic color mapping, and multi-dimensional visualization of the corrosion morphology is achieved. According to the method, the limitation that original contour data cannot be obtained through a traditional method is overcome, accurate quantification and reconstruction of anchor rod corrosion under the standard-free condition are achieved, and high robustness and engineering applicability are achieved.

The invention relates to the technical field of high-temperature experimental equipment, in particular to a monitoring system for a high-temperature corrosion test of a tubular furnace. Comprising the following steps: a heating unit is mounted in a ceramic fiber hearth to perform high-temperature heating on a tubular furnace; the image acquisition unit is provided with an observation window for forming a gradient heat resistance mechanism, and penetrates into a hearth to record a surface image of an object to be detected in the furnace at high temperature in real time; the cooling unit comprises a circulating water pipeline which penetrates into the image acquisition unit to reduce the temperature and improve the image acquisition definition; the main control unit is connected with the heating unit and the temperature acquisition unit so as to regulate and control the test environment temperature; and extracting local features of the corrosion morphology based on the recorded surface image of the to-be-detected object, and matching the local features with a pre-established database to obtain a matching result. Through innovative structural design and intelligent control of the image acquisition unit and the cooling unit, visualization of the corrosion process, monitoring precision and analysis automation are realized.

The invention discloses a method and system for predicting the atmospheric corrosion life of an aluminum alloy based on a corrosion image, and the method comprises the steps: carrying out the image processing and feature extraction based on an obtained aluminum alloy corrosion image, and obtaining the fractal dimension of the current time; calculating based on the fractal dimension of the current time in combination with a pre-constructed aluminum alloy corrosion life prediction model to obtain the residual corrosion life of the aluminum alloy and the maximum corrosion pit depth of the current time; wherein the aluminum alloy corrosion life prediction model is constructed and obtained by determining a function relation between the maximum corrosion pit depth and the corrosion time on the basis that fractal dimensions serve as intermediary variables of the corrosion time and the maximum corrosion pit depth; the fractal dimension is used as an intermediary variable, so that the problem that the traditional corrosion pit depth is difficult to directly associate with the exposure time is solved; the service life prediction model can predict the corrosion service life of the aluminum alloy more accurately; according to the box counting method, the corrosion morphology complexity can be quantified, and the traditional pitting rate parameter sensitivity is improved by 40%.

The invention relates to the technical field of machine learning, and particularly discloses a remote intelligent control method for a gas pipeline multi-branch safety valve based on an AI model, and the method comprises the following steps: obtaining original flow data and pipeline inner wall image data of a plurality of branches of a gas pipeline; inputting the original flow data and the pipeline inner wall image data into a pre-trained flow correction model to obtain corrected flow data of each branch; based on the corrected flow data, a control instruction of each branch safety valve is calculated through a control algorithm, and the control instruction comprises the specific adjustment amount of the opening degree of the safety valve; and sending the control instruction to a safety valve execution device of a corresponding branch through a communication network. The negative influence of the corrosion form on the stability of the flow field is effectively eliminated, precise control over gas conveying under the non-uniform flow field condition is achieved, and the safety of a gas pipeline system and the gas supply stability are guaranteed.

The application discloses a kind of prediction methods of high-strength steel wire high temperature creep behavior of rust, belong to bridge cable safety assessment technical field.The method is first obtained by test the material intrinsic material parameters of rust high-strength steel wire test piece and un-rust high-strength steel wire test piece;Then three-dimensional scanning quantization corrosion morphology is used, the maximum pit depth of rust high-strength steel wire surface and the pit root radius of pit bottom are extracted, and then the stress concentration coefficient and the effective bearing area decay function after net section loss are calculated, and the corrosion damage index is introduced;On this basis, the creep strain rate prediction model considering local stress concentration, section loss and material damage is established.The prediction method of the application realizes the quantitative prediction from pit micro-morphology to macro creep behavior, and has great engineering application value for evaluating the safety and residual life of in-service bridge cable.

The invention discloses a chloride ion concentration driven corrosion evolution probability type cellular automaton simulation method, and relates to the field of metal corrosion evolution simulation, and the method comprises the following steps: S1, setting a cellular space size and a cellular size, and constructing a three-dimensional cellular space; s2, cell types are defined, and initial distribution of various types of cells is completed in a three-dimensional cell space; s3, setting a reaction mechanism of a model iteration process, and judging a conversion rule among various types of cells according to a corrosion probability Pa, a passivation probability Pb and a passivation film fracture probability Pd; s4, a chloride ion concentration matrix, a probability enhancement coefficient and an attenuation coefficient are introduced, the cellular transformation probability in the iteration process is corrected through the real-time concentration value of chloride ions, and aggravation of the local corrosion process is achieved; and S5, comparing test and simulated corrosion morphology results under the same mass loss rate. According to the method, local corrosion difference can be effectively reduced on the basis of comprehensive corrosion, and support is provided for durability evaluation of the steel structure.

The invention provides a method for determining a silicon surface and a carbon surface of a 3C-SiC single crystal wafer, which comprises the following steps of: (1) immersing the 3C-SiC single crystal wafer into molten alkali for corrosion treatment; (2) taking out the corroded 3C-SiC single crystal wafer and observing the surface appearance of the 3C-SiC single crystal wafer; if the surface only shows the stacking fault characteristic, judging that the surface is a (C) surface; and if the surface has the characteristics of stacking fault and dislocation corrosion pits at the same time, determining that the surface is a (111) Si surface. According to the invention, the inherent difference of molten alkali on the corrosion morphology of the (111) Si surface and the (C) surface of the 3C-SiC single crystal is found and utilized for the first time: the (111) Si surface can present stacking fault and dislocation corrosion pits at the same time, and only the (C) surface has stacking fault. By observing the obvious morphology comparison, the two crystal faces can be quickly and accurately distinguished.

The application discloses a method for evaluating the residual strength of a pipeline with corrosion defects under blasting vibration, and belongs to the technical field of oil and gas pipeline safety evaluation. In view of the problem that the traditional method only considers the corrosion geometric thinning and ignores the material dynamic performance degradation and spatial non-uniform distribution, leading to distorted evaluation, the application reconstructs the corrosion morphology based on detection data, constructs a corrosion damage variable, calibrates the damage-strain rate-material parameter mapping relationship through a mechanical test, establishes an explicit dynamic model of a pipeline-defect-soil-blast source, realizes non-uniform assignment of material performance in the corrosion area by using the UMAT subprogram of LS-DYNA, obtains stress, strain and damage state through nonlinear dynamic analysis, and completes the residual strength evaluation. The application couples the geometric defects and material degradation effect for the first time, greatly improves the evaluation accuracy and engineering applicability, and provides support for the safety control of pipeline blasting construction.

The invention discloses a finite element shell element model modeling method and system considering metal surface corrosion random morphology. The method comprises the following steps: obtaining metal surface corrosion morphology three-dimensional point cloud data of a corroded component through three-dimensional laser scanning; performing dimension reduction on the three-dimensional point cloud data, judging whether the corrosion form of the metal surface is uniform corrosion or not, if so, calculating a physical regression equation based on the expanded point cloud data, and constructing a corrosion random morphology model based on superposition of a corresponding uniform corrosion depth on a corrosion texture generating a corresponding weight loss ratio; if not, constructing a corrosion random morphology model based on the learned corrosion texture; generating a corrosion morphology by using the corrosion random morphology model; performing regular grid division and numbering operation on the corrosion random morphology model; material attribute endowing is completed based on grid partitioning and numbering, and grid encryption division is carried out; and based on the shell element geometric model with the given thickness, parameter setting is completed, and a finite element shell element model is obtained.

The present application relates to the technical field of machine learning, and specifically discloses a remote intelligent control method for a gas pipeline multi-branch safety valve based on an AI model, comprising the following steps: obtaining original flow data and pipeline inner wall image data of multiple branches of a gas pipeline; inputting the original flow data and pipeline inner wall image data into a pre-trained flow correction model to obtain corrected flow data of each branch; based on the corrected flow data, calculating control instructions for safety valves of each branch through a control algorithm, wherein the control instructions include specific adjustment amounts of safety valve opening degrees; and sending the control instructions to safety valve execution devices of corresponding branches through a communication network. The present application effectively eliminates the negative impact of corrosion patterns on the stability of the flow field, realizes accurate control of gas transportation under non-uniform flow field conditions, and ensures the safety and gas supply stability of the gas pipeline system.

The application discloses a kind of chloride ion concentration driven corrosion evolution probability type cellular automaton simulation method, it is related to metal corrosion evolution simulation field, including the following steps: S1: setting cell space size and cell size, construct three-dimensional cell space;S2: definition cell type and in three-dimensional cell space complete the initial distribution of each type cell;S3: set the reaction mechanism of model iteration process, to corrosion probability P a , passivation probability P b , passivation film rupture probability P d Determine the conversion rule between each type of cell;S4: introduce chloride ion concentration matrix and probability enhancement coefficient, attenuation coefficient, by the real-time concentration value of chloride ion to the cell conversion probability in iteration process is modified, realize the aggravation of local corrosion process;S5: compare the corrosion morphology results of test and simulation under the same mass loss rate.This application can effectively reduce the difference of local corrosion on the basis of general corrosion, provide support for steel structure durability evaluation.

The invention relates to a method for detecting electrochemical corrosion and durability of a PET (Polyethylene Terephthalate)-based adhesive tape in an electrolyte in the field of intelligent manufacturing, which comprises the following steps: acquiring initial surface topography data of a material in an electrochemical environment, and determining microstructure characteristics according to the initial surface topography data; acquiring electric field distribution data in the electrochemical environment, and determining ion migration characteristics according to the electric field distribution data; determining the initial corrosion state of the surface of the material according to the ion migration characteristics and an electrochemical impedance spectroscopy measurement value; obtaining corrosion morphology evolution data according to the surface corrosion initial state; determining corrosion-dissolution associated parameters according to the corrosion morphology evolution data and the concentration data of the dissolved matter in the electrolyte; according to the corrosion-dissolution associated parameters, analyzing the dynamic relationship between the microscopic change of the surface of the material and the concentration of the dissolved substance to obtain the tolerance degradation trend of the material; and predicting a durability evaluation result of the material in a long-term electrochemical environment according to the tolerance degradation trend of the material.

The invention discloses an ion thruster acceleration gate downstream pit-groove corrosion morphology prediction method, which comprises the following steps: establishing a computational domain, and determining boundary conditions of the computational domain; ions are injected from the left boundary of the computational domain, charges carried by all the ions are mapped to grid nodes of the computational domain through a weight distribution method, and space charge density distribution is obtained; solving three-dimensional potential distribution and three-dimensional electric field distribution in a computational domain based on space charge density distribution and set boundary conditions; pushing the ions to move based on the three-dimensional electric field distribution, and updating the positions and speeds of all the ions; simulating a charge exchange collision process of ions and neutral atoms based on the updated ion position and speed, and updating the state of the collided ions; counting information of charge exchange ions impacting the downstream surface of the acceleration gate within a set time; and calculating the three-dimensional corrosion morphology of the downstream surface of the acceleration gate based on charge exchange ion information in combination with a sputtering yield model and gate material attributes.

This invention discloses a method for establishing a high-temperature alloy hot corrosion model based on image recognition, comprising: preparing a sample and conducting a hot corrosion test; photographing and recording the surface morphology of the sample after hot corrosion during the test, and preprocessing the images; performing grayscale analysis on the preprocessed results to calculate the mean grayscale G and grayscale distribution of the surface images after hot corrosion; calculating the fractal dimension D of the corrosion morphology of different sample surfaces using the box-ring method; and establishing a high-temperature alloy hot corrosion model based on the mean grayscale G and the fractal dimension D of the corrosion morphology. This invention can infer the hot corrosion temperature and time based on the surface morphology characteristics of the high-temperature alloy after hot corrosion, providing a technical basis for rapidly determining the hot corrosion temperature and time in engineering practice.

The invention relates to the technical field of automobile heat exchanger corrosion, and discloses an automobile aluminum heat exchanger corrosion depth prediction method comprising the following steps: cleaning and drying a test sample; a test sample piece is placed on a salt mist box supporting plate; preparing a salt solution; adding a salt solution into a salt mist box liquid storage tank, and carrying out an external corrosion test; after the external corrosion test is finished, carrying out an air tightness test on the test sample piece; cleaning and drying the test sample piece passing the air tightness test again; sampling a test sample radiating tube, analyzing the corrosion morphology and the corrosion mechanism, and measuring the corrosion depth by using a metallographic microscope; and simulating the maximum possible corrosion depth after the external corrosion test of the automobile aluminum heat exchanger based on the Gunn's distribution theory. According to the method for predicting the corrosion depth of the automobile aluminum heat exchanger, test reproducibility is ensured through strict preprocessing specifications, simulation of research of the automobile aluminum heat exchanger in the field of external corrosion is achieved, and the prediction precision of the corrosion depth is greatly improved.

The invention discloses an in-situ electrochemical and corrosion monitoring device and an in-situ electrochemical and corrosion monitoring method for researching marine microorganism adhesion and metal corrosion behaviors under high-flux simulated seawater flowing conditions. The device comprises a flow cell, an industrial camera and a data analysis system, flowing seawater and a three-electrode system externally connected with an electrochemical workstation are arranged in the flowing pool, and a working electrode in the three-electrode system is metal attached with marine microorganisms and used for researching corrosion behaviors; the industrial camera is used for shooting to obtain the working electrode corrosion condition; the data analysis system is used for acquiring data of the electrochemical workstation, processing the data by using a distribution relaxation time dissociation algorithm, acquiring high-throughput microbial corrosion electrochemical data of the electrochemical workstation, taking a time sequence as a variable, acquiring an image shot by the industrial camera, and performing image processing and feature extraction; and establishing an electrochemical-image cross validation mechanism, and generating a comprehensive analysis report containing a distribution relaxation time dissociation result, corrosion morphology statistics and a time evolution trend.

The invention relates to the field of modeling methods, and particularly discloses an SAC305 lead-free solder viscoplastic corrosion fracture phase field modeling method, which comprises the following steps: determining SAC305 material viscoplastic constitutive model parameters based on stress-strain data of a uniaxial tensile experiment; carrying out a corrosion experiment on the SAC305 material, and determining a corrosion morphology evolution rule of the SAC305 material; and establishing a corrosion-fracture phase field model, and calibrating phase field model parameters. According to the scheme, constitutive model parameters of SAC305 are calibrated according to a uniaxial tensile experiment, corrosion boundary conditions of the model are confirmed according to a corrosion experiment result, and a corrosion-fracture phase field model is constructed, so that corrosion-induced strength attenuation, crack initiation and expansion paths can be accurately simulated; the method can be used for reliability evaluation, design optimization and service life prediction of SAC305 welding spots in electronic packaging, and provides a basis for engineering application of key interconnection parts in a corrosion environment.

The invention relates to a method for establishing a finite element model of cold-formed thin-walled steel with comprehensive corrosion coupled with pitting corrosion. According to the method, the corrosion field is constructed through the combination of the power spectral density constraint and the pitting statistical distribution function based on the corrosion index parameters and the corrosion random field theory, so that the comprehensive corrosion trend and the overall thinning characteristic of the component can be described, and the scale change and the space randomness of the local pitting pit can be represented; and the cold-formed thin-walled steel rusted surface topography conforming to the statistical law can be generated in batches in a computer environment. And on the basis of the generated corrosion surface topography data, continuous mapping and entity reconstruction from a corrosion disturbance field to a component geometric domain are achieved through a Python program, and a three-dimensional entity model containing corrosion fluctuation and pitting depression is formed. According to the method, the problem that the random corrosion morphology is difficult to accurately generate on the component scale and is difficult to automatically convert into the finite element geometric model in the existing research is solved.

The invention discloses a method for predicting the residual bearing capacity of an anchor rod containing non-uniform corrosion, and relates to the technical field of geotechnical engineering structure safety assessment, and the method comprises the following steps: S1, reconstructing a three-dimensional corrosion morphology model of the anchor rod through a three-dimensional laser scanning device, S2, carrying out cross section division and extracting corrosion parameters, S3, carrying out non-uniform quantification on the corroded anchor rod, and S4, calculating the residual bearing capacity of the anchor rod containing non-uniform corrosion. The method comprises the following steps of S1, selecting a corrosion type, S4, establishing a corresponding geometric generalization model for each corrosion type, S5, carrying out mechanical property analysis on the corroded anchor rod by adopting a micro-section method, S6, establishing a linear relation model between the residual bearing capacity and the section corrosion rate, and S7, carrying out model verification and practical engineering application. According to the method, the real morphology of the naturally rusted anchor rod is reconstructed by adopting a high-precision three-dimensional laser scanning technology, the function of high reconstruction precision is realized, the manual measurement error and the form difference between the accelerated corrosion test and natural corrosion are overcome, and a reliable data basis is provided for subsequent analysis.

The application discloses a method for improving the morphology of corrosion, which comprises the following steps: S1, first, checking the equipment state before corrosion, ensuring that there is no abnormality, then adjusting the process, adopting a mechanical chemical corrosion process to perform chemical thinning on a semiconductor silicon wafer, preparing auxiliary materials required in the process, and adjusting process parameters such as the rotating speed of a mechanical arm of a corrosion machine, the nitrogen path in an acid tank, the temperature of a corrosion ice machine and the nitrogen flow; S2, then, adjusting the concentration and temperature of a liquid medicine to determine the removal rate of corrosion, thereby affecting the corrosion morphology of the final corrosion, and ensuring that the position setting of the moving nitrogen pipe in the acid tank is consistent with the actual moving position. The application adjusts the concentration of mixed acid, the moving position of the nitrogen pipe and the nitrogen flow and the like to improve the uniformity of the surface corrosion of the silicon wafer in the corrosion process, achieves the purpose of improving the morphology of the silicon wafer, and better improves the process capacity and reduces the product parameter failure rate.

The invention discloses a multi-dimensional quantitative detection method for microbial corrosion resistance of Cr-containing steel. The method comprises the following steps: a microbial challenge test: inoculating sulfate reducing bacteria into a culture medium, and exposing a sample in a microbial environment; performing quantitative analysis on corrosion products: performing ultrasonic rust removal on the sample by using an acid pickling solution, then calculating a weightlessness corrosion rate, and quantifying the adhesion amount of microorganisms on the surface of the sample; multi-mode electrochemical testing: monitoring the open-circuit potential and linear polarization resistance of the sample, and performing electrochemical impedance spectroscopy and potentiodynamic polarization curve testing to obtain corrosion current density and polarization resistance; surface analysis: analyzing the corrosion morphology and element distribution of the sample through a scanning electron microscope and an energy disperse spectroscopy, and determining the chemical state of the chromium element by adopting X-ray photoelectron spectroscopy to obtain the stability and the sulfur content of a passive film; and evaluating the corrosion degree: establishing a coupling model of the corrosion current density, the polarization resistance, the passivation film stability, the microorganism adhesion amount and the sulfur content, and calculating the corrosion degree.

The application provides a corrosion degradation prediction method of a marine engineering structure, and relates to the field of marine engineering structures, and comprises the following steps: constructing a finite element model representing the three-dimensional random corrosion morphology of the marine engineering structure; establishing a surrogate model with material parameters as input and multi-order dynamic responses as output; for each candidate statistical characteristic quantity, generating multiple sets of material parameter samples to input the surrogate model, and obtaining a set of multi-order dynamic response prediction values; taking the relative error between the mean value of each order dynamic response prediction value and the mean value of the target response distribution of each order dynamic response target value as an optimization target, and obtaining a Pareto non-dominated solution set; calculating the KL divergence between the joint prediction distribution of the multi-order dynamic response corresponding to each candidate solution in the Pareto non-dominated solution set and the target response distribution, and selecting the candidate solution with the minimum KL divergence as the optimal solution. The method takes into account the efficiency, accuracy and calculation cost of the corrosion degradation prediction of the marine engineering structure.

The invention discloses a method and a device for determining the external corrosion type of a steel pipe based on computer vision. The method comprises the following steps: acquiring external corrosion failure image data and external corrosion working condition data of a to-be-identified pipeline; according to the external corrosion failure image data of the to-be-identified pipeline, using the trained machine learning model to identify whether the external corrosion morphology type of the to-be-identified pipeline is local corrosion or comprehensive corrosion; if the corrosion is local corrosion, determining the corrosion type of the to-be-identified pipeline based on a pre-constructed multi-modal identification model according to a first group of specified parameters in the external corrosion working condition data of the to-be-identified pipeline; and if the corrosion is comprehensive corrosion, determining the corrosion type of the to-be-identified pipeline based on a pre-constructed multi-modal identification model according to a second group of specified parameters in the external corrosion working condition data of the to-be-identified pipeline. The external corrosion type of the steel pipe can be quickly, accurately and effectively identified, the identification efficiency is high, the cost is low, and accurate data support is provided for steel pipe risk management and control.

The invention relates to the technical field of civil engineering health monitoring, in particular to a method for quantitatively monitoring the three-dimensional non-uniform corrosion state of a reinforcing steel bar based on distributed optical fibers. According to the method, the distributed optical fiber sensors are spirally and annularly arranged on the surface of the steel bar, and the distributed optical fiber sensors are annularly arranged on the surface of the concrete, so that the corrosion expansion effect generated by corrosion of the steel bar is monitored, and the corrosion distribution and the accumulated corrosion degree are further evaluated. The method overcomes the technical defects that longitudinal and transverse distribution of corrosion morphology is difficult to obtain through grating fiber monitoring in the prior art and the corrosion area range cannot be judged through an electrochemical method in the prior art.

The present application relates to the technical field of pipeline corrosion detection and data analysis, and provides a pipeline corrosion defect database construction method for artificial intelligence training, wherein a multi-scene corrosion experiment platform is constructed to simulate typical corrosion environments that the pipeline may encounter during service, real corrosion defects with different morphologies are prepared on pipeline steel samples through accelerated corrosion experiments; then high-precision three-dimensional measurement technology is adopted to obtain fine morphology data of the corrosion pits, and standard magnetic flux leakage detection equipment is used to collect magnetic flux leakage signals corresponding to the defects; finally, the corrosion environment parameters, corrosion pit geometric characteristic parameters and magnetic flux leakage detection signal data are uniformly and structurally processed to form a queryable and extensible associated database. The database can truly reflect the internal relationship between the corrosion morphology and the magnetic flux leakage signals, and provide key data support for subsequent quantitative evaluation of pipeline corrosion defects, optimization of detection models and research on intelligent inversion algorithms.

This invention relates to the field of monitoring corrosion morphology and pH dynamic distribution in steel, and particularly to a rapid and intelligent monitoring method and system for in-situ monitoring of pitting morphology and surrounding pH dynamic distribution during electrochemical testing of steel pitting corrosion. First, an in-situ steel test sample with an observation surface is prepared and encapsulated, and then horizontally mounted in an adjustable electrolytic cell. Next, a methyl orange calibration solution with a pH gradient of 1-7 is prepared, and images of the sample at different pH values ​​are captured and imported into the system for calibration, establishing a quantitative mapping relationship between pH and the Lab values ​​of the calibrated images. Finally, in-situ electrochemical testing is conducted in a colorless salt test solution containing the same concentration of methyl orange, simultaneously monitoring the morphology of pitting initiation and development, as well as the dynamic evolution of the surrounding pH. This system can achieve millisecond-level dynamic in-situ monitoring of the spatial distribution of pH around pitting corrosion during the corrosion growth process, and can continuously capture real-time pH evolution information during the initiation and expansion of pitting corrosion.

A supporting frame for engineering plastic cleaning comprises a rectangular bottom frame, a plurality of pairs of backup plates are welded to the rectangular bottom frame, each backup plate is rotationally provided with an inner shaft, the inner shafts are rotationally arranged on the rectangular bottom frame, the inner shafts are eccentrically provided with pressing wheels, the inner shafts are provided with swing arms, strip-shaped holes are formed in the swing arms, and moving rods are arranged in the strip-shaped holes in a penetrating mode. The upper ends of the moving rods located on the same side are connected with moving arms through threads, one side of each pair of backup plates makes contact with one side of a sample, the other side of the sample is tightly attached to the pressing wheel, and therefore when the pressing wheel rotates, the peripheral side of the pressing wheel can act on the sample, the requirement for fixing the sample is met, gaps exist between the fixed samples, and the sample fixing efficiency is improved. The problem that the corrosion morphology of the sample is damaged due to collision and the like is avoided. Moreover, when the support frame is used for cleaning the sample, the support frame with the sample is placed in a cleaning tank, and then the sample is cleaned in a flushing manner, so that the corrosion appearance can be prevented from being damaged by flushing, and the cleaning operation can be quickly completed conveniently.