An online monitoring and evaluation method for automobile corrosion test of fusion corrosion monitoring plate

Abstract

The application discloses a kind of automobile corrosion test online monitoring evaluation methods of fusion corrosion monitoring board, it is related to material corrosion test technical field, including arrangement N monitoring board in test box, and construct the multichannel galvanic switching matrix with N channels;According to the preset sampling period control multichannel galvanic switching matrix connects to form galvanic couple in turn with any two monitoring board, measures the galvanic current, mixed potential and coupling resistance of each galvanic couple, constructs galvanic current matrix, mixed potential matrix and coupling resistance matrix, and establishes quantitative relationship equation set using galvanic corrosion theory, obtains the corrosion potential and polarization resistance of each monitoring board and so on step.The application solves the problem that corrosion monitoring board cannot be monitored online in real time and multiple board data is isolated, realizes the construction of corrosion electrochemical potential field and polarization resistance field and the online real-time acquisition of corrosion state.

Description

Technical Field

[0001] This invention relates to the field of material corrosion testing technology, specifically to an online monitoring and evaluation method for automotive corrosion testing that integrates a corrosion monitoring panel. Background Technology

[0002] Current automotive corrosion testing uses a standard corrosion monitoring board as the core reference, obtaining corrosion levels offline through pre-test cleaning, drying, and weighing, and post-test rust removal, drying, and weighing. In recent years, resistance probe and electrochemical probe methods have been introduced into the corrosion monitoring field, respectively calculating mass loss through resistance changes and characterizing electrochemical properties through polarization resistance. However, neither of these technologies has transformed the standard corrosion monitoring board from a passive test piece into an active sensing node, nor has it achieved multi-board interconnection measurement and spatial field construction.

[0003] Existing technologies suffer from the following problems: Standard corrosion monitoring plates are passive during the test cycle, only capable of offline weighing and unable to acquire corrosion status online in real time, resulting in inefficient and undynamically adjustable test parameters; even when multiple monitoring plates are deployed simultaneously, their data remain isolated and parallel, allowing only simple numerical comparisons and failing to construct a spatial distribution field of corrosion status, let alone reveal spatial gradient characteristics. These issues limit the online monitoring capabilities and spatial assessment accuracy of corrosion tests. Summary of the Invention

[0004] The purpose of this invention is to propose an online monitoring and evaluation method for automotive corrosion testing that integrates a corrosion monitoring board. This method solves the problems of corrosion monitoring boards being unable to perform real-time online monitoring and the isolated parallel data from multiple boards. It also addresses the issue of existing technologies being unable to distinguish whether spatial non-uniformity is driven by the environment or caused by material anomalies.

[0005] This application provides an online monitoring and evaluation method for automotive corrosion testing that integrates a corrosion monitoring panel, including the following steps:

[0006] N monitoring boards are placed inside the test chamber, and a multi-channel thermocouple switching matrix with N channels is constructed.

[0007] According to the preset sampling period, the multi-channel thermocouple switching matrix is ​​controlled to connect any two monitoring boards in sequence to form a thermocouple pair. The thermocouple current, mixed potential and coupling resistance of each thermocouple pair are measured. The thermocouple current matrix, mixed potential matrix and coupling resistance matrix are constructed. The quantitative relationship equation system is established by using the thermocouple corrosion theory, and the corrosion potential and polarization resistance of each monitoring board are obtained by solving it.

[0008] The monitoring boards are arranged according to their spatial positions, and corrosion electrochemical potential field and polarization resistance field are constructed respectively based on the spatial distribution of corrosion potential and polarization resistance.

[0009] Gradient analysis of the corrosion electrochemical potential field was performed to determine environment-driven inhomogeneities; anomaly detection of the polarization resistance field was performed to determine anomalous material inhomogeneities.

[0010] Based on corrosion potential and polarization resistance, the local environmental parameters at each monitoring board are inferred.

[0011] Monitoring was repeated at a fixed sampling period to obtain the time series sequences of corrosion electrochemical potential field, polarization resistance field, and local environmental parameters, and the corrosion rate and mass loss were calculated.

[0012] The test endpoint is predicted based on mass loss, corrosion rate, and target mass loss.

[0013] Output the determination results of environment-driven inhomogeneity, material anomaly-type inhomogeneity, and test endpoint, and generate online monitoring and evaluation results.

[0014] In one embodiment, N monitoring boards are arranged inside the test chamber, and a multi-channel thermocouple switching matrix with N channels is constructed, including:

[0015] N standard corrosion monitoring boards are arranged inside the test chamber and suspended inside the test chamber by insulating brackets;

[0016] A multi-channel thermocouple switching matrix is ​​constructed. The multi-channel thermocouple switching matrix consists of a microcontroller, a relay array or solid-state switch array, a thermocouple current measurement circuit and a voltage follower. The multi-channel thermocouple switching matrix has N channels, and each channel is connected to a monitoring board through a shielded wire.

[0017] In one embodiment, a multi-channel thermocouple switching matrix is ​​used to sequentially connect any two monitoring boards to form thermocouple pairs according to a preset sampling period. The thermocouple current, mixed potential, and coupling resistance of each thermocouple pair are measured to construct a thermocouple current matrix, a mixed potential matrix, and a coupling resistance matrix, including:

[0018] The multi-channel thermocouple switching matrix is ​​controlled to perform the measurement cycle according to the preset sampling period. In each sampling period, all monitoring board combinations are traversed, and any two monitoring boards are connected as thermocouple pairs in turn, while the remaining monitoring boards are placed in a high-impedance open circuit state.

[0019] For each thermocouple pair, the thermocouple current is measured by a thermocouple current measuring circuit, and the mixed potential is measured by a voltage follower.

[0020] The coupling resistance is calculated by applying a known constant current between the couplers using the four-wire method and measuring the potential difference.

[0021] After traversing all the combinations of electric couples, the measured electric couple current, mixed potential and coupling resistance are filled into the symmetric matrix to construct the electric couple current matrix, mixed potential matrix and coupling resistance matrix respectively.

[0022] In one embodiment, a set of quantitative equations is established using galvanic corrosion theory to solve for the corrosion potential and polarization resistance of each monitoring board, including:

[0023] Establish a set of equations relating the galvanic current, mixed potential, corrosion potential, polarization resistance, and coupling resistance;

[0024] The objective function is constructed using the least squares method, and the minimum value of the objective function is obtained by iterative optimization algorithm to obtain the corrosion potential and polarization resistance of each monitoring board.

[0025] In one embodiment, gradient analysis of the corrosion electrochemical potential field is performed to determine environment-driven inhomogeneities, including:

[0026] Centered on each monitoring board, a set of monitoring boards spatially adjacent to it is selected, and the spatial partial derivative of the corrosion potential is calculated by differential approximation.

[0027] The corrosion potential gradient magnitude at each monitoring board location is calculated based on spatial partial derivatives.

[0028] Calculate the mean corrosion potential gradient across the entire field, compare the magnitude of the corrosion potential gradient with the mean corrosion potential gradient across the entire field, and identify the locations where the magnitude of the corrosion potential gradient is higher than the mean corrosion potential gradient across the entire field as environmentally driven inhomogeneities.

[0029] In one embodiment, anomaly detection of the polarization resistance field is performed to determine abnormal material inhomogeneities, including:

[0030] Calculate the mean and standard deviation of the polarization resistance across the entire field;

[0031] The polarization resistance deviation of each monitoring board is calculated based on the mean and standard deviation of the polarization resistance across the entire field.

[0032] By comparing the polarization resistance deviation with the anomaly judgment threshold, the position where the polarization resistance deviation exceeds the preset anomaly judgment threshold is judged as a material anomaly type inhomogeneity.

[0033] In one embodiment, local environmental parameters at each monitoring board are derived by back-calculation based on corrosion potential and polarization resistance, including:

[0034] A first equation is established relating corrosion potential to local oxygen concentration, salt concentration, pH, and temperature.

[0035] A second equation is established relating polarization resistance to liquid film conductivity, liquid film thickness, and local oxygen concentration.

[0036] Solve for the inverse functions of the first and second equations, substitute the corrosion potential and polarization resistance of each monitoring plate, and then deduce the local oxygen concentration, salt concentration, liquid film thickness, and liquid film conductivity at each monitoring plate.

[0037] In one embodiment, monitoring is repeatedly performed at a fixed sampling period to obtain a time series sequence of corrosion electrochemical potential field, a time series sequence of polarization resistance field, and a time series sequence of local environmental parameters, including:

[0038] During the test period, the steps of measuring the electrode pairs, solving the electrochemical parameters, determining the environment-driven inhomogeneity, determining the material anomaly inhomogeneity, and inferring the local environmental parameters were repeated at a fixed sampling period.

[0039] The corrosion potential, polarization resistance, local oxygen concentration, salt concentration, and liquid film thickness of each monitoring board obtained from each sampling are arranged in chronological order to form the corrosion electrochemical potential field time series, polarization resistance field time series, and local environmental parameter time series, respectively.

[0040] In one embodiment, calculating the corrosion rate and mass loss includes:

[0041] Calculate the environmental correction coefficient for each sample based on the time series of local environmental parameters;

[0042] Based on the corrosion electrochemical potential field time series, polarization resistance field time series and environmental correction coefficient, the corrosion rate corresponding to each sampling is calculated;

[0043] Based on the corrosion rate and a fixed sampling period, the mass loss of the monitoring board at the current sampling time is obtained by cumulative calculation.

[0044] In one embodiment, the test endpoint is predicted based on mass loss, corrosion rate, and target mass loss, including:

[0045] Determine whether the current sampling quality loss reaches the target quality loss;

[0046] If the target is not reached, the predicted test endpoint time is calculated by linear extrapolation based on the corrosion rate at the time of sampling.

[0047] The beneficial effects of this invention are:

[0048] (1) This invention constructs a multi-channel galvanic switching matrix and establishes a quantitative relational equation set based on galvanic corrosion theory, transforming the traditional passive corrosion monitoring board that can only be weighed offline into an active sensing node for online real-time monitoring. This solves the problems of corrosion monitoring board being unable to monitor online in real time and data isolation of multiple boards, and realizes the construction of corrosion electrochemical potential field and polarization resistance field and the online real-time acquisition of corrosion state.

[0049] (2) This invention determines environmentally driven inhomogeneity by performing gradient analysis on the corrosion electrochemical potential field and determines material abnormal inhomogeneity by performing anomaly detection on the polarization resistance field. This solves the problem of existing technologies being unable to distinguish whether spatial inhomogeneity is caused by environmental drive or material abnormality, and realizes the identification of the root cause of spatial inhomogeneity.

[0050] (3) This invention calculates corrosion rate and mass loss based on corrosion electrochemical potential field time sequence, polarization resistance field time sequence and local environmental parameter time sequence by repeatedly performing monitoring according to a fixed sampling period, and then predicts the test endpoint. This solves the problem of low efficiency caused by the inability to dynamically adjust test parameters and the unpredictability of test endpoint in existing corrosion tests, and realizes online prediction of test endpoint and improves test efficiency. Attached Figure Description

[0051] The accompanying drawings are provided to further illustrate the invention and form part of the specification. They are used in conjunction with embodiments of the invention to explain the invention and do not constitute a limitation thereof. In the drawings:

[0052] Figure 1 This is a schematic diagram of the overall process of the online monitoring and evaluation method for automotive corrosion testing based on the integrated corrosion monitoring board proposed in this invention;

[0053] Figure 2 This is the matrix heatmap proposed in this invention;

[0054] Figure 3 The convergence curve of the iterative optimization algorithm proposed in this invention;

[0055] Figure 4 This is a graph showing the time-series accumulation of mass loss and the predicted endpoint of the experiment proposed in this invention;

[0056] Figure 5 This is a schematic diagram of the structure of the online monitoring and evaluation system for automotive corrosion testing that integrates a corrosion monitoring board, as proposed in this invention. Detailed Implementation

[0057] The present invention will now be described in further detail with reference to the accompanying drawings. These drawings are simplified schematic diagrams, illustrating only the basic structure of the invention, and therefore only show the components relevant to the invention.

[0058] In current automotive corrosion testing, standard corrosion monitoring boards can only be removed and weighed after the test. Throughout the entire testing cycle, the testers are completely unaware of the corrosion status. This offline detection mode results in the inability to dynamically adjust test parameters, leading to low efficiency and poor repeatability. Even when multiple monitoring boards are deployed, the data from each board are isolated, and the system can only perform simple numerical comparisons, failing to form a spatial distribution field, let alone reveal spatial gradient characteristics. When the corrosion rate at a certain location is high, existing methods cannot determine whether it is due to harsh environmental conditions or abnormalities in the test sample material, resulting in a lack of traceability. Furthermore, existing methods only focus on the corrosion rate as a result indicator, ignoring the two fundamental driving forces of corrosion potential and polarization resistance, and spatial assessment also lacks electrochemical and physical constraints.

[0059] In view of this, this application provides an online monitoring and evaluation method for automotive corrosion testing that integrates a corrosion monitoring board. The corrosion monitoring board is transformed from a passive test piece into an active sensing node. Multi-board interconnection measurement is achieved through a galvanometer switching matrix. Based on the galvanometer corrosion theory, the corrosion potential and polarization resistance are inverted to construct an electrochemical potential field and a polarization resistance field. This enables the tracing of spatial non-uniformity, the inference of local environmental parameters, and the prediction of the test endpoint, ultimately generating online monitoring and evaluation results.

[0060] The following is combined with Figure 1 This document describes the overall process of this application. Figure 1 The main steps of the method are illustrated. This method is applied to the monitoring terminal of the corrosion test chamber. The monitoring terminal can be an embedded industrial control computer, a single-chip microcomputer system, or a host computer software platform.

[0061] like Figure 1 As shown, the method includes the following steps S10 to S90.

[0062] S10. Arrange N monitoring boards inside the test chamber and construct a multi-channel thermocouple switching matrix with N channels. This step, through insulating suspension and matrix construction, transforms the traditional passive test piece into an active sensing node capable of online switching measurement, providing a hardware foundation for the construction of the corrosion electrochemical potential field and polarization resistance field.

[0063] Specifically, N standard corrosion monitoring plates are arranged inside the test chamber. The value of N is determined based on the volume of the test chamber and the evaluation accuracy, and is generally not less than 5. Each monitoring plate is suspended inside the test chamber by a ceramic or PTFE insulating bracket, ensuring complete electrical insulation between the monitoring plate and the metal wall of the test chamber and other monitoring plates. The monitoring plates are arranged to cover key locations such as directly below the spray nozzle, side walls, corners, upper layer, lower layer, center, and edges to capture spatial non-uniformity.

[0064] A multi-channel thermocouple switching matrix is ​​constructed, which consists of a microcontroller, a relay array or solid-state switch array, a high-precision microampere-level thermocouple current measurement circuit, and a high-input-impedance voltage follower. The matrix has N channels, each of which is connected to a corresponding monitoring board via a shielded wire. The microcontroller controls the relay array or solid-state switch array to connect any two monitoring boards corresponding to any two channels into a thermocouple pair according to a preset timing sequence, while placing the remaining monitoring boards in a high-impedance open-circuit state. The shielding layer of the shielded wire is grounded at one end to suppress electromagnetic interference in the salt spray environment.

[0065] S20. Following a preset sampling period, the multi-channel thermocouple switching matrix sequentially connects any two monitoring boards to form thermocouple pairs. The thermocouple current, mixed potential, and coupling resistance of each thermocouple pair are measured, constructing thermocouple current matrices, mixed potential matrices, and coupling resistance matrices. This step traverses all thermocouple pairs to complete matrix measurements, acquiring raw thermocouple corrosion data to provide input for subsequent inversion calculations, thus transforming the corrosion status acquisition from offline weighing to online real-time acquisition.

[0066] Specifically, the multi-channel thermocouple switching matrix is ​​controlled to execute the measurement cycle according to the preset sampling period P; within each sampling period, the microcontroller sequentially traverses all the parameters that satisfy the preset sampling period P. The monitoring board combination generated a total of There are several thermocouple pairs; for each thermocouple pair, the microcontroller controls the multi-channel thermocouple switching matrix to monitor the board. and monitoring board The connection is made to measure the thermocouple current through a high-precision microampere-level thermocouple current measurement circuit. Measuring the mixed potential using a high input impedance voltage follower After the measurement is completed, disconnect the thermocouple pair and continue measuring the next pair until all combinations have been measured.

[0067] During each thermocouple current measurement, the monitoring board was measured using the four-wire method. With monitoring board Coupling resistance between The specific method is as follows: on the monitoring board With monitoring board A known constant current is applied between them Measure the potential difference between the two monitoring boards The coupling resistance is then calculated using the following formula:

[0068] ;

[0069] In the formula, The constant test current applied, in amperes (A). The measured potential difference is expressed in V. For monitoring board With monitoring board The coupling resistance between the two monitoring boards is measured in Ω. This coupling resistance is determined by the conductivity of the salt spray film and the geometric distance between the two monitoring boards, reflecting the degree of electrical coupling formed between the two monitoring boards through the salt spray film.

[0070] After traversing all the thermocouple pair combinations, the measured thermocouple currents are... Arranged into an N-order square matrix according to the monitoring board numbers, denoted as the thermocouple current matrix, its nth order... Line 1 Column elements are The matrix is ​​a symmetric matrix, satisfying The diagonal elements are zero; the measured mixed potential Arranged in the same manner into an N-order square matrix, denoted as the mixed potential matrix, its elements are: The matrix is ​​a symmetric matrix, satisfying The diagonal elements are zero; the measured coupling resistance Arranged in the same manner into an N-order square matrix, denoted as the coupling resistance matrix, its elements are... The matrix is ​​a symmetric matrix with zero elements on its diagonal.

[0071] like Figure 2 As shown, the thermocouple current matrix, the mixed potential matrix, and the coupling resistance matrix are respectively derived from... The three matrices are composed of square matrices of order 1. The row and column numbers of the three matrices correspond to the monitoring board numbers. The matrix elements are the measured values ​​of the thermocouple current, mixed potential and coupling resistance of the corresponding monitoring board combination. All three matrices are symmetric matrices. The diagonal elements are zero, and the off-diagonal elements represent the value according to the gray level. The dark background corresponds to the larger absolute value of the value, and the light background corresponds to the smaller absolute value of the value.

[0072] S30. A quantitative set of equations is established using the theory of galvanic corrosion, and the corrosion potential and polarization resistance of each monitoring plate are obtained by solving the equations. This step obtains the fundamental driving force parameters through inversion of the overdetermined equations, overcoming the limitation of existing technologies that can only obtain offline weighing results, and realizing online real-time analysis of corrosion potential and polarization resistance.

[0073] Specifically, based on the theory of galvanic corrosion, galvanic current With monitoring board corrosion potential Monitoring board corrosion potential Monitoring board polarization resistance Monitoring board polarization resistance and coupling resistor The following relationship exists between them:

[0074] ;

[0075] This formula originates from the equivalent circuit analysis of galvanic corrosion; the two monitoring boards are considered as two electrodes, each with a corrosion potential and polarization resistance. The two electrodes form a closed loop through the coupling resistance of the salt spray liquid film, and the loop current is determined by the ratio of the potential difference between the two electrodes to the total resistance of the loop; in the formula, and monitoring board With monitoring board The corrosion potential, in V; and monitoring board With monitoring board The polarization resistance, in Ω; This is the coupling resistance, in Ω; This is the thermocouple current, measured in amperes (A).

[0076] Simultaneously, mixed potential The parameters mentioned above satisfy the following relationship:

[0077] ;

[0078] This formula originates from the mixed potential theory; when two monitoring boards are short-circuited to form a couple, the mixed potential of the system is obtained by weighted averaging of the corrosion potentials of the two electrodes according to their respective polarization resistances, with the weights being inversely proportional to the polarization resistances; the definitions and units of each parameter in the formula are the same as above.

[0079] For N monitoring boards, the two sets of equations above provide a total of N(N-1) independent equations, with N corrosion potentials as the unknowns. and N polarization resistors There are a total of 2N unknowns; when N is not less than 5, the number of equations is at least 20, which is much greater than the number of unknowns (10), making the system of equations overdetermined; the objective function is constructed using the least squares method. :

[0080] ;

[0081] In the formula, The weighting coefficients for the mixed potential term, in units of A. 2 / V 2 This is used to balance the contributions of thermocouple current measurement error and mixed potential measurement error to the inversion results, so that the objective function... The two dimensions are unified as A. 2 ; The value is determined based on the accuracy of the thermocouple current measurement circuit. With voltage follower accuracy according to Determined, generally taken 0.5A 2 / V 2 Up to 2.0A2 / V 2 Objective function The dimension of A 2 It has the same dimensions as the square of the dipole current and conforms to the least squares construction principle.

[0082] The objective function is solved using the Levenberg-Marquardt iterative optimization algorithm. The minimum value is used to obtain the corrosion potential of each monitoring board. and polarization resistance This algorithm combines the advantages of gradient descent and Gauss-Newton methods. Gradient descent is used to ensure convergence in the early stages of iteration, and Gauss-Newton method is automatically switched to improve the convergence speed when the optimal solution is close. The initial iteration value is the arithmetic mean of the measured potentials of each monitoring board in the open circuit state as the initial value of the corrosion potential iteration. The statistical mean of the polarization resistance measured by the monitoring boards of the same material under standard salt spray conditions in the pre-test stage is taken as the initial value of the polarization resistance iteration. The iteration termination condition is that the relative change of the objective function value between two adjacent iterations is less than 0.000001.

[0083] like Figure 3 As shown, the objective function The iteration number k decreases exponentially, and the vertical axis is plotted on a logarithmic scale; the initial value is approximately 5.99 × 10⁻⁶. -6 A 2 After 25 iterations, it converged to 3.5 × 10⁻⁶. -9 A 2 The iteration terminates when the relative change in the objective function value between two adjacent iterations is less than 0.000001 below the threshold. This curve shows that the inversion of the overdetermined equation system has numerical stability, and the Levenberg-Marquardt algorithm has good convergence efficiency in the inversion of corrosion electrochemical parameters.

[0084] S40. Arrange the monitoring boards according to their spatial positions, and construct the corrosion electrochemical potential field and polarization resistance field respectively based on the spatial distribution of corrosion potential and polarization resistance. This step transforms discrete point data into a continuous physical field, providing a field basis for subsequent spatial inhomogeneity tracing.

[0085] Specifically, the monitoring boards are arranged according to their spatial coordinates within the test chamber; the monitoring boards are set up... Spatial coordinates are , , Unit: m; Corrosion potential is distributed according to the spatial position after arrangement. This forms a corrosion electrochemical potential field, which reflects the distribution of the thermodynamic driving force for metal corrosion at each location; the polarization resistance is distributed according to the spatial position after arrangement. This forms a polarized resistance field, which reflects the kinetic resistance distribution of corrosion reactions at various locations.

[0086] S50. Perform gradient analysis on the corrosion electrochemical potential field to determine environment-driven inhomogeneity; perform anomaly detection on the polarization resistance field to determine material-anomalous inhomogeneity. This step, through gradient analysis and anomaly detection, distinguishes between environment-driven and material-anomalous inhomogeneity, achieving accurate identification of the root cause of spatial inhomogeneity.

[0087] Specifically, gradient analysis was performed on the corrosion electrochemical potential field to calculate the corrosion potential gradient magnitude at each monitoring plate location. ; with each monitoring board Centered on a set of spatially adjacent monitoring panels The adjacentness determination criterion is that the spatial Euclidean distance is less than a preset distance threshold, or the distance is selected according to the geometric topology of the test chamber and the monitoring board. The spatial partial derivatives are approximated by using the difference approximation method, taking at least three coplanar monitoring panels that are closest to each other as the adjacent set.

[0088] ;

[0089] ;

[0090] ;

[0091] In the formula, The number of adjacent monitoring panels, dimensionless; , , For adjacent monitoring boards The spatial coordinates; the above difference formula is derived from the discrete approximation of the partial derivatives of multivariable functions. When the distance between adjacent monitoring boards approaches zero, the difference approximation approaches the continuous partial derivatives.

[0092] The magnitude of the corrosion potential gradient is calculated based on the above spatial partial derivatives:

[0093] ;

[0094] In the formula, For monitoring board The corrosion potential gradient magnitude at the location, in V / m.

[0095] Calculate the mean corrosion potential gradient across the entire field:

[0096] ;

[0097] In the formula, This represents the average corrosion potential gradient across the entire field, expressed in V / m.

[0098] If a certain monitoring board location is located at Higher than This indicates the presence of a strong environmental gradient in the area, suggesting the existence of environment-driven inhomogeneity. This determination is based on the fact that environment-driven inhomogeneity is caused by uneven environmental distribution within the test chamber, manifesting as drastic spatial changes in corrosion potential. A gradient modulus value higher than the overall average indicates an abnormal environmental gradient.

[0099] Anomaly detection is performed on the polarization resistance field, and the average polarization resistance across the entire field is calculated. and standard deviation :

[0100] ;

[0101] ;

[0102] In the formula, This is the average polarization resistance across the entire field, in Ω. This represents the standard deviation of the global polarization resistance.

[0103] Calculate the polarization resistance deviation of each monitoring board. :

[0104] ;

[0105] In the formula, This refers to the polarization resistance deviation.

[0106] Set anomaly detection threshold , The value is based on statistics The criteria are determined, and generally the following are adopted: The value is between 2.0 and 3.0; if Greater than If the material inhomogeneity is found to be abnormal, the monitoring board is determined to have material abnormalities. This determination is made because material abnormalities are caused by defects in the materials of the monitoring board itself or abnormalities in its processing. They are manifested as a significant deviation of the polarization resistance from the statistical law of the entire field. If the deviation exceeds a threshold, it indicates a material abnormality.

[0107] S60. Based on corrosion potential and polarization resistance, the local environmental parameters at each monitoring board are derived. This step reverses the electrochemical parameters into local environmental parameters, further revealing the causes of inhomogeneity and providing environmental dimension support for tracing the source of spatial inhomogeneity.

[0108] Specifically, a quantitative relationship is established between corrosion potential, polarization resistance, and local environmental parameters. According to the mixed potential theory, the corrosion potential is jointly determined by the cathodic oxygen reduction reaction and the anodic metal dissolution reaction, and satisfies the following multivariate linear relationship with local oxygen concentration, salt concentration, pH, and ambient temperature:

[0109] ;

[0110] In the formula, For the first Local oxygen concentration at each monitoring panel, in mg / L; Salt concentration, in g / L; pH level; Ambient temperature, in °C; For the intercept term, the unit is V; , , , The regression coefficients are given in units of V·L / mg, V·L / g, V, and V / ℃, respectively. The model was determined through pre-experiment calibration: calibration monitoring plates were arranged in a standard salt spray test chamber, and the corrosion potential of each monitoring plate, as well as the oxygen concentration, salt concentration, pH, and temperature at its location, were measured simultaneously. At least 50 sets of sample data were collected, and the coefficients were obtained using multiple linear least squares regression fitting. to .

[0111] The polarization resistance is related to ion transport and oxygen diffusion processes in the liquid film, and satisfies the following multivariate linear relationship with the liquid film conductivity, liquid film thickness, and local oxygen concentration:

[0112] ;

[0113] In the formula, Liquid film conductivity, in S / m; The liquid film thickness is expressed in mm. This is the intercept term, in Ω; , , The regression coefficients are given in units of Ω·m / S, Ω / mm, and Ω·L / mg, respectively. The model was also determined through pre-experiment calibration: polarization resistance, liquid film conductivity, liquid film thickness, and oxygen concentration were simultaneously measured on each monitoring plate within a standard salt spray test chamber. At least 50 sets of sample data were collected, and the coefficients were obtained using multiple linear least squares regression fitting. to .

[0114] The corrosion potential of each monitoring board obtained in step S40 and polarization resistance Substitute into the two equations above;

[0115] Due to the salt concentration in the salt spray test The test chamber salt spray supply system is set to known test conditions, and the liquid film conductivity is... With salt concentration satisfy ,in The molar conductivity coefficient of ions, in units of S·m² / g, is determined by referring to a table based on the composition of the test medium. In this application, temperature and pH sensors are placed near each monitoring board inside the test chamber to directly measure the ambient temperature. and pH Substituting this as a known quantity into the corrosion potential equation and the polarization resistance equation, the unknowns in the two equations are reduced to the liquid film thickness. and oxygen concentration The local oxygen concentration and liquid film thickness at each monitoring plate are obtained by solving the two equations simultaneously. Then, the liquid film conductivity is calculated using the known relationship between salt concentration and liquid film conductivity.

[0116] S70. Repeatedly perform monitoring at a fixed sampling period to obtain the time series sequences of corrosion electrochemical potential field, polarization resistance field, and local environmental parameters, and calculate the corrosion rate and mass loss. This step obtains corrosion kinetic data through time series evolution analysis, providing a computational basis for predicting the experimental endpoint.

[0117] Specifically, within the experimental period, a fixed sampling period is followed. Repeat steps S20 to S60; after After the second sampling, we obtained Group corrosion potential data, Group polarization resistance data and Group local environmental parameter data; for the first Each monitoring board will The corrosion potentials from the subsequent samples are arranged in chronological order to form a time sequence of corrosion electrochemical potential fields. ;Will The polarization resistances sampled in each sample are arranged in chronological order to form a polarization resistance field time sequence. ;Will Local oxygen concentration in the second sample Salt concentration Liquid film thickness Liquid film conductivity and pH Arranged in chronological order, forming a time series of local environmental parameters. , , , and ;wherein the liquid film conductivity The salt concentration from this sampling according to The calculated pH value is... The pH value was directly measured by the pH sensor during this sampling. This represents the time corresponding to the nth sampling, in hours (h). The value range is 1 to .

[0118] Based on the time series of local environmental parameters, calculate the first... Environmental correction coefficient corresponding to the next sample This coefficient is used to quantify the overall impact of the local environment on the corrosion rate, and is defined as:

[0119] ;

[0120] In the formula, For reference oxygen concentration, the unit is mg / L, and the measured value of oxygen concentration under standard salt spray test conditions is taken; For reference salt concentration, the unit is g / L, and the measured value of salt concentration under standard salt spray test conditions is taken; For reference liquid film thickness, in mm, the measured value of liquid film thickness under standard salt spray test conditions is used; The coefficient is dimensionless. The numerator reflects the oxygen and salt supply capacity of the current environment relative to the reference environment, and the denominator reflects the correction of mass transfer resistance by the liquid film thickness.

[0121] Based on the corrosion electrochemical potential field time series, polarization resistance field time series, and environmental correction coefficients, the first... Corrosion rate corresponding to the second sample According to the mixed potential theory and corrosion kinetics, the corrosion rate is directly proportional to the overpotential, inversely proportional to the polarization resistance, and modulated by the environmental correction factor.

[0122] ;

[0123] In the formula, This is the kinetic proportionality constant, in g / The determination is made through preliminary calibration. The specific method is as follows: an offline weighing test is conducted on a monitoring plate of the same material under standard salt spray conditions, and the electrochemical parameters are recorded simultaneously. The results are then calculated using the above formula. And take the average value of multiple tests; The equilibrium potential of the monitoring plate material in the test medium is expressed in V and can be found in an electrochemical handbook or determined in a preliminary test. The corrosion potential at the nth sampling time, in V; For the first Polarization resistance at the time of the next sampling, in Ω; The value represents the corrosion rate, expressed in g / h.

[0124] Based on the corrosion rate and a fixed sampling period, the monitoring board is calculated through cumulative calculation. In the Mass loss during the second sampling :

[0125] ;

[0126] In the formula, Cumulative mass loss, in grams; The sampling period is fixed, in hours.

[0127] S80. Predict the test endpoint based on mass loss, corrosion rate, and target mass loss. This step predicts the test endpoint by linear extrapolation based on the current corrosion rate, solving the problem of unpredictable test endpoints and improving test efficiency.

[0128] Specifically, the following endpoint prediction is performed on each monitoring board: determine the quality loss at the current sampling time. Has the preset target quality loss been achieved? If not reached, then based on the corrosion rate at the time of sampling. Perform linear extrapolation to calculate the predicted test endpoint time of the monitoring board. The arithmetic mean of the predicted end times of the experiment from all monitoring boards is taken as the final predicted end time of the experiment. :

[0129] ;

[0130] In the formula, The target mass loss is defined in grams and is determined by the test standards or process requirements. For the first The time corresponding to each sampling, in hours; To predict the end time of the experiment, the unit is hours. Assuming the subsequent corrosion rate remains constant at the current level, dividing the remaining mass to be lost by the current rate gives the remaining time required. Adding this to the time already elapsed gives the predicted end time.

[0131] like Figure 4 As shown, the corrosion rate v remains constant within each sampling period, represented by a bar chart; mass loss It accumulates in a step-like manner over time, represented by a broken line; the current sampling time. Mass loss at 10h =2.20g, target mass loss =5.00g is marked with a horizontal dashed line; based on the current corrosion rate. Linear extrapolation was performed at a concentration of 0.24 g / h to predict the experimental endpoint. =21.67h, marked at the intersection of the dashed line of the target quality loss level and the vertical line of the predicted endpoint.

[0132] S90 outputs the judgment results for environment-driven inhomogeneity, material anomaly-type inhomogeneity, and the test endpoint, generating online monitoring and evaluation results. This step integrates all monitoring and prediction results to form a complete online monitoring and evaluation report, supporting dynamic adjustment of test parameters.

[0133] Specifically, the conclusions of environmentally driven inhomogeneity and material anomaly inhomogeneity are read, and the corrosion potential gradient modulus is read. and polarization resistance deviation Read local environmental parameters, including local oxygen concentration. Salt concentration Liquid film thickness Liquid film conductivity and pH Read quality loss Corrosion rate and predicting the end time of the experiment The above data are linked and integrated according to the monitoring board number and spatial location to generate online monitoring and evaluation results that include non-uniformity type determination, non-uniformity spatial distribution, local environmental parameter distribution, and test endpoint prediction.

[0134] The following uses a set of simulation data to illustrate the specific calculation process of this application; assuming the test chamber is arranged as follows: =6 monitoring boards, sampling period =2h, target mass loss .

[0135] In one sampling, the polarization resistances of the six monitoring boards were measured as follows: , , , , , ;

[0136] Calculate the average value of the global polarization resistance according to step S50:

[0137] ;

[0138] Calculate the standard deviation:

[0139] ;

[0140] Calculate the deviation of each plate:

[0141] , , , , , ;

[0142] Take the anomaly detection threshold =2.0, then If the value is greater than 2.0, it is determined that monitoring board 4 has material inhomogeneity.

[0143] Assuming that the corrosion potentials of the six monitoring boards are obtained through step S40, respectively , , , , , The adjacent monitoring boards of monitoring board 1 are boards 2 and 5, with spatial coordinate differences of respectively. , The corrosion potential gradient magnitude at monitoring board 1 is calculated as follows:

[0144] ;

[0145] ;

[0146] .

[0147] Assuming the mean gradient of the entire field ,but Greater than It was determined that there was environmentally driven non-uniformity near monitoring board 1.

[0148] In step S70, a fixed sampling period is set. =2h, after =5 samples, the corrosion rate of a certain monitoring board is as follows: , , , , The cumulative mass loss is:

[0149] .

[0150] Set target quality loss At present Current corrosion rate Then predict the endpoint of the experiment:

[0151] .

[0152] The above calculation examples demonstrate that the formulas and algorithms involved in this application are clearly operable, and those skilled in the art can implement the solutions of this invention according to the above description.

[0153] This application also provides an online monitoring and evaluation system for automotive corrosion testing that integrates a corrosion monitoring panel, referring to... Figure 5This system is used to perform any embodiment of the aforementioned online monitoring and evaluation method for automotive corrosion testing using a fused corrosion monitoring panel.

[0154] Specifically, the system includes a monitoring data acquisition module, an electrochemical parameter inversion module, a spatial inhomogeneity tracing module, a time-series monitoring and endpoint prediction module, and an online monitoring and evaluation result generation module.

[0155] The monitoring data acquisition module is used to arrange N standard corrosion monitoring boards in the test chamber, insulate and suspend them and construct a multi-channel thermocouple switching matrix. According to the preset sampling period, the control matrix connects any two monitoring boards to form a thermocouple pair, measures the thermocouple current, mixed potential and coupling resistance of each thermocouple pair, and constructs the thermocouple current matrix, mixed potential matrix and coupling resistance matrix.

[0156] The electrochemical parameter inversion module is used to establish a set of quantitative relationship equations between galvanic current, mixed potential and corrosion potential, polarization resistance and coupling resistance using galvanic corrosion theory. The objective function is constructed using the least squares method and solved by iterative optimization algorithm to obtain the corrosion potential and polarization resistance of each monitoring board. Then, the monitoring boards are arranged according to their spatial positions to construct the corrosion electrochemical potential field and polarization resistance field.

[0157] The spatial non-uniformity tracing module is used to perform gradient analysis on the corrosion electrochemical potential field to obtain the corrosion potential gradient magnitude, and to perform anomaly detection on the polarization resistance field to obtain the polarization resistance deviation. Based on the corrosion potential gradient magnitude and polarization resistance deviation, it determines the environment-driven non-uniformity and the material anomaly non-uniformity, and based on the corrosion potential and polarization resistance, it inversely calculates the local environmental parameters at each monitoring board.

[0158] The timing monitoring and endpoint prediction module is used to repeatedly perform monitoring according to a fixed sampling period to obtain the timing sequence of corrosion electrochemical potential field, polarization resistance field and local environmental parameters, calculate the environmental correction coefficient, corrosion rate and mass loss, and predict the test endpoint based on mass loss, corrosion rate and target mass loss.

[0159] The online monitoring and evaluation result generation module is used to read the judgment results of environment-driven non-uniformity, the judgment results of material abnormal non-uniformity, and the test endpoint, and integrate them according to the monitoring board number and spatial location to generate online monitoring and evaluation results.

[0160] It should be noted that those skilled in the art can clearly understand that the specific implementation process of each module of the above system can be referred to the corresponding description in the foregoing method embodiments. For the sake of convenience and brevity, it will not be repeated here.

[0161] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any person skilled in the art can easily conceive of various equivalent modifications or substitutions within the technical scope disclosed in this application, and these modifications or substitutions should all be covered within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of protection of the claims.

[0162] In conclusion, the above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A method for online monitoring and evaluation of automotive corrosion testing integrating a corrosion monitoring panel, characterized in that, Includes the following steps: N monitoring boards are placed inside the test chamber, and a multi-channel thermocouple switching matrix with N channels is constructed. According to the preset sampling period, the multi-channel thermocouple switching matrix is ​​controlled to connect any two monitoring boards in sequence to form a thermocouple pair. The thermocouple current, mixed potential and coupling resistance of each thermocouple pair are measured. The thermocouple current matrix, mixed potential matrix and coupling resistance matrix are constructed. The quantitative relationship equation system is established by using the thermocouple corrosion theory, and the corrosion potential and polarization resistance of each monitoring board are obtained by solving it. The monitoring boards are arranged according to their spatial positions, and corrosion electrochemical potential field and polarization resistance field are constructed respectively based on the spatial distribution of corrosion potential and polarization resistance. Gradient analysis of the corrosion electrochemical potential field was performed to determine environment-driven inhomogeneities; anomaly detection of the polarization resistance field was performed to determine anomalous material inhomogeneities. Based on corrosion potential and polarization resistance, the local environmental parameters at each monitoring board are inferred. Monitoring was repeated at a fixed sampling period to obtain the time series sequences of corrosion electrochemical potential field, polarization resistance field, and local environmental parameters, and the corrosion rate and mass loss were calculated. The test endpoint is predicted based on mass loss, corrosion rate, and target mass loss. Output the determination results of environment-driven inhomogeneity, material anomaly-type inhomogeneity, and test endpoint, and generate online monitoring and evaluation results.

2. The online monitoring and evaluation method for automotive corrosion testing using a fused corrosion monitoring board according to claim 1, characterized in that, N monitoring boards are placed inside the test chamber, and a multi-channel thermocouple switching matrix with N channels is constructed, including: N standard corrosion monitoring boards are arranged inside the test chamber and suspended inside the test chamber by insulating brackets; A multi-channel thermocouple switching matrix is ​​constructed. The multi-channel thermocouple switching matrix consists of a microcontroller, a relay array or solid-state switch array, a thermocouple current measurement circuit and a voltage follower. The multi-channel thermocouple switching matrix has N channels, and each channel is connected to a monitoring board through a shielded wire.

3. The online monitoring and evaluation method for automotive corrosion testing using a fused corrosion monitoring board according to claim 1, characterized in that, According to the preset sampling period, the multi-channel thermocouple switching matrix sequentially connects any two monitoring boards to form thermocouple pairs. The thermocouple current, mixed potential, and coupling resistance of each thermocouple pair are measured, and thermocouple current matrices, mixed potential matrices, and coupling resistance matrices are constructed, including: The multi-channel thermocouple switching matrix is ​​controlled to perform the measurement cycle according to the preset sampling period. In each sampling period, all monitoring board combinations are traversed, and any two monitoring boards are connected as thermocouple pairs in turn, while the remaining monitoring boards are placed in a high-impedance open circuit state. For each thermocouple pair, the thermocouple current is measured by a thermocouple current measuring circuit, and the mixed potential is measured by a voltage follower. The coupling resistance is calculated by applying a known constant current between the couplers using the four-wire method and measuring the potential difference. After traversing all the combinations of electric couples, the measured electric couple current, mixed potential and coupling resistance are filled into the symmetric matrix to construct the electric couple current matrix, mixed potential matrix and coupling resistance matrix respectively.

4. The online monitoring and evaluation method for automotive corrosion testing using a fused corrosion monitoring board according to claim 1, characterized in that, A set of quantitative equations was established using the theory of galvanic corrosion, and the corrosion potential and polarization resistance of each monitoring board were obtained by solving them, including: Establish a set of equations relating the galvanic current, mixed potential, corrosion potential, polarization resistance, and coupling resistance; The objective function is constructed using the least squares method, and the minimum value of the objective function is obtained by iterative optimization algorithm to obtain the corrosion potential and polarization resistance of each monitoring board.

5. The online monitoring and evaluation method for automotive corrosion testing using a fused corrosion monitoring board according to claim 1, characterized in that, Gradient analysis of the corrosion electrochemical potential field was performed to determine environment-driven inhomogeneities, including: Centered on each monitoring board, a set of monitoring boards spatially adjacent to it is selected, and the spatial partial derivative of the corrosion potential is calculated by differential approximation. The corrosion potential gradient magnitude at each monitoring board location is calculated based on spatial partial derivatives. Calculate the mean corrosion potential gradient across the entire field, compare the magnitude of the corrosion potential gradient with the mean corrosion potential gradient across the entire field, and identify the locations where the magnitude of the corrosion potential gradient is higher than the mean corrosion potential gradient across the entire field as environmentally driven inhomogeneities.

6. The online monitoring and evaluation method for automotive corrosion testing using a fused corrosion monitoring board according to claim 1, characterized in that, Anomaly detection of the polarization resistance field is used to determine anomalous inhomogeneities in the material, including: Calculate the mean and standard deviation of the polarization resistance across the entire field; The polarization resistance deviation of each monitoring board is calculated based on the mean and standard deviation of the polarization resistance across the entire field. By comparing the polarization resistance deviation with the anomaly judgment threshold, the position where the polarization resistance deviation exceeds the preset anomaly judgment threshold is judged as a material anomaly type inhomogeneity.

7. The online monitoring and evaluation method for automotive corrosion testing using a fused corrosion monitoring board according to claim 1, characterized in that, Based on corrosion potential and polarization resistance, the local environmental parameters at each monitoring board are derived, including: A first equation is established relating corrosion potential to local oxygen concentration, salt concentration, pH, and temperature. A second equation is established relating polarization resistance to liquid film conductivity, liquid film thickness, and local oxygen concentration. Solve for the inverse functions of the first and second equations, substitute the corrosion potential and polarization resistance of each monitoring plate, and then deduce the local oxygen concentration, salt concentration, liquid film thickness, and liquid film conductivity at each monitoring plate.

8. The online monitoring and evaluation method for automotive corrosion testing using a fused corrosion monitoring board according to claim 1, characterized in that, Monitoring was repeated at a fixed sampling period to obtain time series sequences of corrosion electrochemical potential field, polarization resistance field, and local environmental parameters, including: During the test period, the steps of measuring the electrode pairs, solving the electrochemical parameters, determining the environment-driven inhomogeneity, determining the material anomaly inhomogeneity, and inferring the local environmental parameters were repeated at a fixed sampling period. The corrosion potential, polarization resistance, local oxygen concentration, salt concentration, and liquid film thickness of each monitoring board obtained from each sampling are arranged in chronological order to form the corrosion electrochemical potential field time series, polarization resistance field time series, and local environmental parameter time series, respectively.

9. The online monitoring and evaluation method for automotive corrosion testing using a fused corrosion monitoring board according to claim 1, characterized in that, Calculations of corrosion rate and mass loss include: Calculate the environmental correction coefficient for each sample based on the time series of local environmental parameters; Based on the corrosion electrochemical potential field time series, polarization resistance field time series and environmental correction coefficient, the corrosion rate corresponding to each sampling is calculated; Based on the corrosion rate and a fixed sampling period, the mass loss of the monitoring board at the current sampling time is obtained by cumulative calculation.

10. The online monitoring and evaluation method for automotive corrosion testing using a fused corrosion monitoring board according to claim 1, characterized in that, The test endpoint is predicted based on mass loss, corrosion rate, and target mass loss, including: Determine whether the current sampling quality loss reaches the target quality loss; If the target is not reached, the predicted test endpoint time is calculated by linear extrapolation based on the corrosion rate at the time of sampling.

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