Method and device for measuring effective area and thickness of corrosion inhibitor coating of oil and gas pipeline

Abstract

The invention relates to the technical field of corrosion inhibitor film coating effect detection, in particular to an oil and gas pipeline corrosion inhibitor film effective area and thickness measuring method and device. The method comprises the steps that first film measuring data and second film measuring data of each testing point position are input into a film thickness comprehensive analysis model; obtaining a final actual film thickness prediction value of the test point position; in combination with the effective thickness of the corrosion inhibitor coating and the actual film thickness predicted value of each test point, failure points are obtained through screening, and the effective area of the corrosion inhibitor coating of the oil and gas pipeline to be tested is determined based on the number of the failure points. According to the invention, deep learning is introduced to construct a film thickness comprehensive analysis model, detection results of a film interference method and a laser ranging method are combined to obtain a final actual film thickness prediction value, and the measurement precision of the film thickness is effectively improved; the effective area of the corrosion inhibitor coating film of the oil and gas pipeline to be detected can be directly determined based on the number of failure point positions, and measures can be taken in time for adjustment when the corrosion inhibitor film fails.

Description

Technical Field

[0001] The invention relates to the technical field of corrosion inhibitor film coating effect detection, in particular to a method and a device for measuring the effective area and thickness of a corrosion inhibitor coating on an oil and gas pipeline. Background Art

[0002] Oil and gas gathering and transportation pipelines often involve complex working conditions such as wet gas transportation and mixed gas and water transportation. The fluids transported in these pipelines are complex in composition, and acidic gases such as H2S, CO2, and SO2, along with highly salinized formation water, pose significant risks of corrosion failure to the pipelines.

[0003] Compared to traditional continuous injection methods, coating significantly improves the inhibitor's effectiveness while reducing agent usage. Therefore, corrosion inhibitor coating is a cost-effective corrosion prevention measure for oil and gas pipelines. The inhibitor adsorbs onto the metal surface to form a protective film, effectively preventing direct contact between the corrosive medium and the metal surface, thereby effectively reducing the corrosion rate. The effectiveness of a corrosion inhibitor coating depends on the duration of its effective adhesion to the metal surface and the size and thickness of its effective area. Therefore, testing the effectiveness of the corrosion inhibitor film coating is necessary when coating the inner surface of oil and gas pipelines.

[0004] The effectiveness testing of existing corrosion inhibitor coatings often relies on various corrosion performance tests and internal testing methods. The existing corrosion inhibitor coating effectiveness testing devices and evaluation methods have the following problems and shortcomings, mainly including:

[0005] (1) Some existing corrosion inhibitor coating effect evaluation methods rely on indoor simulation experiments and closed-loop experiments, which are unable to evaluate the corrosion inhibitor coating effect of on-site oil and gas pipelines. In addition, the real-time monitoring device needs to be directly installed on the oil and gas pipelines and equipment to be tested. In actual application, it will be limited by the installation location, and the maintenance cost is relatively high.

[0006] (2) Existing detection devices require the installation of test samples inside the oil and gas pipeline to obtain the corrosion rate at a specific location or monitor the corrosion current through an electrode probe to determine the effectiveness of the corrosion inhibitor film layer. It is impossible to directly obtain the thickness and effective area of ​​the corrosion inhibitor film layer on the inner surface of the oil and gas pipeline.

[0007] (3) The detection method is single and the corresponding detection accuracy cannot reach the nanometer level, which cannot meet the actual needs of the site. Summary of the Invention

[0008] The present invention provides a method and device for measuring the effective area and thickness of a corrosion inhibitor coating on an oil and gas pipeline, which overcomes the shortcomings of the above-mentioned prior art. It can effectively solve the problems of the existing method for detecting the effect of the corrosion inhibitor film coating on the inner surface of the oil and gas pipeline, namely, the single detection method, which impairs the detection accuracy, and the inability to obtain the effective area of ​​the corrosion inhibitor film.

[0009] One of the technical solutions of the present invention is achieved through the following measures: A method for measuring the effective area and thickness of a corrosion inhibitor coating on an oil and gas pipeline, comprising:

[0010] Obtaining first film measurement data and second film measurement data for each test point on the corrosion inhibitor film on the inner surface of the oil and gas pipeline to be tested, wherein the first film measurement data is the film thickness and the test point position obtained based on the thin film interferometry method, and the second film measurement data is the film thickness and the test point position obtained based on the laser ranging method;

[0011] For each test point, the first film measurement data and the second film measurement data corresponding thereto are input into the film thickness comprehensive analysis model to obtain a final actual film thickness prediction value of the test point;

[0012] Combining the effective thickness of the corrosion inhibitor coating and the predicted value of the actual film thickness at each test point, the failure points are screened out, and the effective area of ​​the corrosion inhibitor coating of the oil and gas pipeline to be tested is determined based on the number of failure points.

[0013] The following are further optimizations and / or improvements to the above technical solutions:

[0014] The construction of the above-mentioned film thickness comprehensive analysis model includes:

[0015] Obtain samples and divide them into a training sample set and a test sample set in proportion, wherein each sample includes first film measurement data, second film measurement data, and corresponding actual film thickness identification information of any test point on the corrosion inhibitor film on the surface of a historical oil and gas pipeline, the first film measurement data being the film thickness and the test point position obtained based on a thin film interferometry method, and the second film measurement data being the film thickness and the test point position obtained based on a laser ranging method;

[0016] A multi-input neural network model is trained using a training sample set, and a training stop condition is introduced during training. When the training stop condition is met, the training is terminated to obtain a comprehensive analysis model of film thickness, wherein the multi-input neural network model includes an input layer, a hidden layer, and an output layer. The input layer receives the first film measurement data and the second film measurement data as input data, the hidden layer introduces nonlinearity through an activation function, and performs feature extraction on the input data, and the output layer outputs a predicted value of the actual film thickness;

[0017] The trained film thickness comprehensive analysis model is tested using the test sample set, the model parameters of the film thickness comprehensive analysis model are optimized, and a film thickness comprehensive analysis model that meets the test evaluation requirements is output.

[0018] The above combined the effective thickness of the corrosion inhibitor coating and the actual film thickness prediction value of each test point to screen out the failure points, including:

[0019] Determine whether the actual film thickness prediction value at a certain test point is less than or equal to the effective thickness of the corrosion inhibitor coating;

[0020] If the response is yes, then the test point is a failure point, and the film thickness loss rate of the test point is calculated by the following formula:

[0021]

[0022] Wherein, η is the thickness loss rate of the corrosion inhibitor film, d1 is the actual film thickness prediction value of the test point, and d0 is the effective thickness of the corrosion inhibitor coating;

[0023] Traverse all test points, repeat the above steps, and filter out all failure points.

[0024] The above-mentioned determination of the effective area of ​​the corrosion inhibitor coating of the oil and gas pipeline to be tested based on the number of failure points is performed by the following formula:

[0025]

[0026] Wherein, δ is the effective area of ​​the corrosion inhibitor coating, x1 is the number of failure points of the oil and gas pipeline to be tested, x0 is the total number of test points, and S is the total surface area of ​​the oil and gas pipeline to be tested.

[0027] The above-mentioned acquisition of the first film measurement data and the second film measurement data of each test point on the corrosion inhibitor film on the surface of the oil and gas pipeline to be tested includes:

[0028] Obtain the time information, light signal emission time, light signal return time, light signal incident angle relative to the inner surface of the oil and gas pipeline to be tested, and the order of interference fringes at a certain test point based on thin film interferometry to determine the film thickness at the test point;

[0029]

[0030] Where d is the film thickness, m is the order of interference fringes, λ is the wavelength of the light source used for the optical signal, n is the refractive index of the corrosion inhibitor film on the surface of the oil and gas pipeline to be tested, and θ is the incident angle of the optical signal relative to the inner surface of the oil and gas pipeline to be tested;

[0031] The first film measurement data is formed by the film thickness of the test point and the position of the test point;

[0032] Obtain the light speed of the light source and the round-trip time difference of the light signal at a certain test point based on the laser ranging method to determine the film thickness at the test point;

[0033]

[0034] Where d is the actual distance between the light source and the inner surface of the oil and gas pipeline to be measured; c is the speed of light from the light source; t is the round-trip time difference of the light signal;

[0035] The second film measurement data is composed of the film thickness of the test point and the position of the test point.

[0036] The second technical solution of the present invention is achieved by the following measures: a device for measuring the effective area and thickness of a corrosion inhibitor coating on an oil and gas pipeline, comprising:

[0037] a test data acquisition unit, which acquires first film measurement data and second film measurement data of each test point on the corrosion inhibitor film on the inner surface of the oil and gas pipeline to be tested, wherein the first film measurement data is the film thickness and the test point position obtained based on the thin film interferometry method, and the second film measurement data is the film thickness and the test point position obtained based on the laser ranging method;

[0038] The film thickness prediction unit inputs the first film measurement data and the second film measurement data corresponding to each test point into the film thickness comprehensive analysis model to obtain a final actual film thickness prediction value of the test point;

[0039] The effective area acquisition unit combines the effective thickness of the corrosion inhibitor coating and the actual film thickness prediction value of each test point to screen out the failure points, and determines the effective area of ​​the corrosion inhibitor coating of the oil and gas pipeline to be tested based on the number of failure points.

[0040] The following are further optimizations and / or improvements to the above technical solutions:

[0041] The above-mentioned film thickness prediction unit includes:

[0042] Model building modules, including:

[0043] The sample acquisition submodule acquires samples and divides them into a training sample set and a test sample set in proportion, wherein each sample includes the first film measurement data, the second film measurement data, and the corresponding actual film thickness identification information of any test point on the corrosion inhibitor film on the surface of the historical oil and gas pipeline. The first film measurement data is the film thickness and the test point position obtained based on the thin film interferometry method, and the second film measurement data is the film thickness and the test point position obtained based on the laser ranging method.

[0044] A training submodule trains a multi-input neural network model using a training sample set, introduces a training stop condition during training, and terminates the training when the training stop condition is met, thereby obtaining a film thickness comprehensive analysis model, wherein the multi-input neural network model includes an input layer, a hidden layer, and an output layer, wherein the input layer receives the first film measurement data and the second film measurement data as input data, the hidden layer introduces nonlinearity through an activation function, performs feature extraction on the input data, and the output layer outputs a predicted value of the actual film thickness;

[0045] The testing submodule uses the test sample set to test the trained film thickness comprehensive analysis model, optimizes the model parameters of the film thickness comprehensive analysis model, and outputs a film thickness comprehensive analysis model that meets the test evaluation requirements;

[0046] The prediction module inputs the first film measurement data and the second film measurement data corresponding to each test point into the film thickness comprehensive analysis model to obtain the final actual film thickness prediction value of the test point.

[0047] The effective area acquisition unit includes:

[0048] The failure point screening module combines the effective thickness of the corrosion inhibitor coating and the actual film thickness prediction value of each test point to screen out the failure points, including:

[0049] Determine whether the actual film thickness prediction value at a certain test point is less than or equal to the effective thickness of the corrosion inhibitor coating;

[0050] If the response is yes, then the test point is a failure point, and the film thickness loss rate of the test point is calculated by the following formula:

[0051]

[0052] Wherein, η is the thickness loss rate of the corrosion inhibitor film, d1 is the actual film thickness prediction value of the test point, and d0 is the effective thickness of the corrosion inhibitor coating;

[0053] Traverse all test points, repeat the above steps, and filter out all failure points;

[0054] The effective area determination module determines the effective area of ​​the corrosion inhibitor coating of the oil and gas pipeline to be tested based on the number of failure points through the following formula:

[0055]

[0056] Wherein, δ is the effective area of ​​the corrosion inhibitor coating, x1 is the number of failure points of the oil and gas pipeline to be tested, x0 is the total number of test points, and S is the total surface area of ​​the oil and gas pipeline to be tested.

[0057] The test data acquisition unit includes a thin film interference test component, a laser ranging component, and a data receiving module;

[0058] A thin film interferometry test assembly, which obtains first film measurement data for each test point on the corrosion inhibitor film on the inner surface of the oil and gas pipeline to be tested. The first film measurement data is the film thickness and test point position obtained based on thin film interferometry. The assembly includes three annular optical probes, each of which includes a light source, an incident optical fiber, a beam splitter, a probe head, a lens, a reflector, a receiving optical fiber, a high-resolution light detector, a high-precision time measurement system, an automatic calibration system, a housing, and a connector.

[0059] A laser ranging component is used to obtain second film measurement data at each test point on the corrosion inhibitor film on the inner surface of the oil and gas pipeline to be tested. The second film measurement data is the film thickness and the test point position obtained based on the laser ranging method. The component includes a light source, a high-resolution light detector, a high-precision time measurement system, and a signal processor.

[0060] The data receiving module receives the first film measurement data and the second film measurement data of each test point on the corrosion inhibitor film on the inner surface of the oil and gas pipeline to be tested.

[0061] The present invention introduces thin film interferometry and laser ranging method to detect the film thickness of each test point on the corrosion inhibitor film on the inner surface of the oil and gas pipeline to be tested, and then introduces deep learning to construct a comprehensive analysis model for film thickness, combines the detection results of thin film interferometry and laser ranging method, and obtains the final actual film thickness prediction value, which effectively improves the measurement accuracy of film thickness, so that the measurement accuracy can reach nanometer level, meeting the actual needs of the field; further, it can combine the effective thickness of the corrosion inhibitor coating and the actual film thickness prediction value of each test point to screen out failure points, and can directly determine the effective area of ​​the corrosion inhibitor coating of the oil and gas pipeline to be tested based on the number of failure points, which is conducive to taking timely measures to adjust when the corrosion inhibitor film fails. Furthermore, the film thickness prediction process of the present invention is less dependent on the physical properties of the film material, and has good adaptability to the situation where the actual corrosion inhibitor film thickness in the oil and gas pipeline to be tested is unevenly distributed and corrosion inhibitors of different components. BRIEF DESCRIPTION OF THE DRAWINGS

[0062] Attachment Figure 1 This is a schematic flow chart of the thickness measurement method provided by the present invention.

[0063] Attachment Figure 2 This is a flow chart of the method for constructing a comprehensive analysis model for film thickness provided by the present invention.

[0064] Attachment Figure 3 This is a schematic flow chart of the method for determining the effective area of ​​the corrosion inhibitor coating provided by the present invention.

[0065] Attachment Figure 4 This is a schematic structural diagram of the thickness measuring device provided by the present invention.

[0066] Attachment Figure 5 This is a schematic diagram of the film thickness prediction unit structure provided by the present invention.

[0067] Attachment Figure 6 This is a schematic diagram of the effective area acquisition unit structure provided by the present invention.

[0068] Attachment Figure 7 This is a structural diagram of the test data acquisition unit provided by the present invention.

[0069] Attachment Figure 8 This is a schematic diagram of the structure of the annular optical probe provided by the present invention.

[0070] The codes in the attached figure are: 1 is the light source, 2 is the beam splitter, 3 is the probe head, 4 is the reflector, 5 is the receiving optical fiber, 6 is the high-resolution light detector, 7 is the high-precision time measurement system, 8 is the housing, and 9 is the connector. DETAILED DESCRIPTION

[0071] The present invention is not limited to the following embodiments, and specific implementation methods can be determined based on the technical solutions of the present invention and actual conditions.

[0072] The present invention will be further described below in conjunction with the embodiments and accompanying drawings:

[0073] Example 1: As shown in the attached Figure 1 As shown, the embodiment of the present invention discloses a method for measuring the effective area and thickness of a corrosion inhibitor coating on an oil and gas pipeline, comprising:

[0074] Step S110, obtaining first film measurement data and second film measurement data of each test point on the corrosion inhibitor film on the inner surface of the oil and gas pipeline to be tested, wherein the first film measurement data is the film thickness and the test point position obtained based on the thin film interferometry method, and the second film measurement data is the film thickness and the test point position obtained based on the laser ranging method;

[0075] Step S120 , for each test point, inputting the corresponding first film measurement data and second film measurement data into a film thickness comprehensive analysis model to obtain a final actual film thickness prediction value of the test point;

[0076] Step S130 , combining the effective thickness of the corrosion inhibitor coating and the actual film thickness prediction value of each test point, screen out failure points, and determine the effective area of ​​the corrosion inhibitor coating of the oil and gas pipeline to be tested based on the number of failure points.

[0077] The present invention discloses a method for measuring the effective area and thickness of a corrosion inhibitor coating on an oil and gas pipeline. The method introduces a thin film interferometry method and a laser ranging method to detect the film thickness of each test point on the corrosion inhibitor film on the inner surface of the oil and gas pipeline to be tested. Then, deep learning is introduced to construct a comprehensive analysis model for the film thickness. The detection results of the thin film interferometry method and the laser ranging method are combined to obtain a final predicted value of the actual film thickness, thereby effectively improving the measurement accuracy of the film thickness, so that the measurement accuracy can reach the nanometer level, meeting the actual needs of the field. Furthermore, the effective thickness of the corrosion inhibitor coating and the predicted value of the actual film thickness of each test point can be combined to screen out failure points, and the effective area of ​​the corrosion inhibitor coating of the oil and gas pipeline to be tested can be directly determined based on the number of failure points, which is conducive to taking timely measures to make adjustments when the corrosion inhibitor film fails.

[0078] Example 2: This embodiment of the present invention is a further optimization of the above embodiment, wherein obtaining first film measurement data and second film measurement data of each test point on the corrosion inhibitor film on the surface of the oil and gas pipeline to be tested includes:

[0079] (1) obtaining first film measurement data of each test point on the corrosion inhibitor film on the surface of the oil and gas pipeline to be tested;

[0080] Obtain the time information, light signal emission time, light signal return time, light signal incident angle relative to the inner surface of the oil and gas pipeline to be tested, and the order of interference fringes at a certain test point based on thin film interferometry to determine the film thickness at the test point;

[0081]

[0082] Where d is the film thickness, m is the order of the interference fringes, λ is the wavelength of light source 1 used for the optical signal, n is the refractive index of the corrosion inhibitor film on the surface of the oil and gas pipeline to be tested, and θ is the incident angle of the optical signal relative to the inner surface of the oil and gas pipeline to be tested, that is, the angle between the incident light and the normal line;

[0083] The first film measurement data is composed of the film thickness of the test point and the position of the test point.

[0084] (2) obtaining second film measurement data at each test point on the corrosion inhibitor film on the surface of the oil and gas pipeline to be tested;

[0085] Obtain the light speed of light source 1 and the round-trip time difference of the light signal obtained by laser ranging method at a certain test point to determine the film thickness at the test point;

[0086]

[0087] Where d is the actual distance between the light source 1 and the inner surface of the oil and gas pipeline to be measured; c is the speed of light of the light source 1; t is the round-trip time difference of the light signal;

[0088] The second film measurement data is composed of the film thickness of the test point and the position of the test point.

[0089] Example 3: As shown in the attached Figure 2 As shown, the embodiment of the present invention is a further optimization of the above embodiment, wherein the construction of the film thickness comprehensive analysis model includes:

[0090] Step S210: Acquire samples and divide them into a training sample set and a test sample set in proportion, wherein each sample includes first film measurement data, second film measurement data, and corresponding actual film thickness identification information of any test point on the corrosion inhibitor film on the surface of the historical oil and gas pipeline, the first film measurement data being the film thickness and the test point location obtained based on the film interferometry method, and the second film measurement data being the film thickness and the test point location obtained based on the laser ranging method;

[0091] Step S230, training the multi-input neural network model using the training sample set, introducing a training stop condition during training, and ending the training when the training stop condition is met to obtain a film thickness comprehensive analysis model, wherein the multi-input neural network model includes an input layer, a hidden layer, and an output layer, wherein the input layer receives the first film measurement data and the second film measurement data as input data, the hidden layer introduces nonlinearity through an activation function to extract features from the input data, and the output layer outputs a predicted value of the actual film thickness;

[0092] The structure of the above multi-input neural network model specifically includes:

[0093] The input layer is provided with two layers, namely input layer 1 and input layer 2, both of which receive two-dimensional data, wherein input layer 1 inputs the first film measurement data, and input layer 2 inputs the second film measurement data, specifically expressed as:

[0094] Input 1: Input 2:

[0095] in, is the first film measurement data, The data for the second film are: and For the test point location, is the film thickness, is the distance obtained by laser ranging, that is, the film thickness.

[0096] The hidden layers include:

[0097] First, for input layer 1 and input layer 2, feature extraction is performed through their respective hidden layers (fully connected layers), specifically expressed as:

[0098]

[0099] in, is the extracted feature vector, W1 and W2 are weight matrices, b1 and b2 are bias terms, and ReLU represents the ReLU activation function;

[0100] Next, after extracting features independently for each input channel, the two feature vectors are concatenated, which can be expressed as follows:

[0101]

[0102] in, is the concatenated feature vector.

[0103] Output layer, the concatenated feature vectors will enter an output layer and output the final actual film thickness prediction value, which is specifically expressed as:

[0104]

[0105] in, is the actual film thickness prediction value, W out is the weight matrix of the output layer, b out is the bias term of the output layer.

[0106] It should also be noted that the training stop conditions include the maximum number of iterations and the loss function, where the loss function can be the mean square error loss, as shown below:

[0107]

[0108] Where n is the total number of sample data; y i is the actual value of the film thickness; is the actual film thickness prediction.

[0109] In step S230 , the trained film thickness comprehensive analysis model is tested using the test sample set, the model parameters of the film thickness comprehensive analysis model are optimized, and the film thickness comprehensive analysis model that meets the test evaluation requirements is output.

[0110] The model parameters of the above-mentioned comprehensive analysis model for optimizing film thickness can be updated by weights W1, b1 and W2, b2 through a back-propagation algorithm.

[0111] Example 4: As shown in the attached Figure 3 As shown, the embodiment of the present invention is a further optimization of the above embodiment, wherein the effective thickness of the corrosion inhibitor coating and the actual film thickness prediction value of each test point are combined to screen out failure points, and the effective area of ​​the corrosion inhibitor coating of the oil and gas pipeline to be tested is determined based on the number of failure points, including:

[0112] Step S310, determining whether the actual film thickness prediction value of a certain test point is less than or equal to the effective thickness of the corrosion inhibitor coating;

[0113] Step S320: If the response is yes, the test point is a failure point, and the film thickness loss rate of the test point is calculated using the following formula;

[0114]

[0115] Wherein, η is the thickness loss rate of the corrosion inhibitor film, d1 is the predicted value of the actual film thickness at the test point, and d0 is the effective thickness of the corrosion inhibitor coating. The effective thickness of the corrosion inhibitor coating here can be obtained through experimental data and experience.

[0116] Step S330, traverse all test points, loop through the above steps, and filter out all failure points;

[0117] Step S340, determining the effective area of ​​the corrosion inhibitor coating of the oil and gas pipeline to be tested based on the number of failure points is performed by the following formula:

[0118]

[0119] Wherein, δ is the effective area of ​​the corrosion inhibitor coating, x1 is the number of failure points of the oil and gas pipeline to be tested, x0 is the total number of test points, and S is the total surface area of ​​the oil and gas pipeline to be tested.

[0120] Example 5: As shown in the attached Figure 4 As shown, the embodiment of the present invention discloses a device for measuring the effective area and thickness of a corrosion inhibitor coating on an oil and gas pipeline, comprising:

[0121] a test data acquisition unit, which acquires first film measurement data and second film measurement data of each test point on the corrosion inhibitor film on the inner surface of the oil and gas pipeline to be tested, wherein the first film measurement data is the film thickness and the test point position obtained based on the thin film interferometry method, and the second film measurement data is the film thickness and the test point position obtained based on the laser ranging method;

[0122] The film thickness prediction unit inputs the first film measurement data and the second film measurement data corresponding to each test point into the film thickness comprehensive analysis model to obtain a final actual film thickness prediction value of the test point;

[0123] The effective area acquisition unit combines the effective thickness of the corrosion inhibitor coating and the actual film thickness prediction value of each test point to screen out the failure points, and determines the effective area of ​​the corrosion inhibitor coating of the oil and gas pipeline to be tested based on the number of failure points.

[0124] Example 6: As shown in the attached Figure 5As shown, the embodiment of the present invention is a further optimization of the above embodiment, wherein the film thickness prediction unit includes:

[0125] Model building modules, including:

[0126] The sample acquisition submodule acquires samples and divides them into a training sample set and a test sample set in proportion, wherein each sample includes the first film measurement data, the second film measurement data, and the corresponding actual film thickness identification information of any test point on the corrosion inhibitor film on the surface of the historical oil and gas pipeline. The first film measurement data is the film thickness and the test point position obtained based on the thin film interferometry method, and the second film measurement data is the film thickness and the test point position obtained based on the laser ranging method.

[0127] A training submodule trains a multi-input neural network model using a training sample set, introduces a training stop condition during training, and terminates the training when the training stop condition is met, thereby obtaining a film thickness comprehensive analysis model, wherein the multi-input neural network model includes an input layer, a hidden layer, and an output layer, wherein the input layer receives the first film measurement data and the second film measurement data as input data, the hidden layer introduces nonlinearity through an activation function, performs feature extraction on the input data, and the output layer outputs a predicted value of the actual film thickness;

[0128] The testing submodule uses the test sample set to test the trained film thickness comprehensive analysis model, optimizes the model parameters of the film thickness comprehensive analysis model, and outputs a film thickness comprehensive analysis model that meets the test evaluation requirements;

[0129] The prediction module inputs the first film measurement data and the second film measurement data corresponding to each test point into the film thickness comprehensive analysis model to obtain the final actual film thickness prediction value of the test point.

[0130] Example 7: As shown in the attached Figure 6 As shown, the embodiment of the present invention is a further optimization of the above embodiment, wherein the effective area acquisition unit includes:

[0131] The failure point screening module combines the effective thickness of the corrosion inhibitor coating and the actual film thickness prediction value of each test point to screen out the failure points, including:

[0132] Determine whether the actual film thickness prediction value at a certain test point is less than or equal to the effective thickness of the corrosion inhibitor coating;

[0133] If the response is yes, then the test point is a failure point, and the film thickness loss rate of the test point is calculated by the following formula:

[0134]

[0135] Wherein, η is the thickness loss rate of the corrosion inhibitor film, d1 is the actual film thickness prediction value of the test point, and d0 is the effective thickness of the corrosion inhibitor coating;

[0136] Traverse all test points, repeat the above steps, and filter out all failure points;

[0137] The effective area determination module determines the effective area of ​​the corrosion inhibitor coating of the oil and gas pipeline to be tested based on the number of failure points through the following formula:

[0138]

[0139] Wherein, δ is the effective area of ​​the corrosion inhibitor coating, x1 is the number of failure points of the oil and gas pipeline to be tested, x0 is the total number of test points, and S is the total surface area of ​​the oil and gas pipeline to be tested.

[0140] Example 8: As shown in the attached Figure 7 As shown, the embodiment of the present invention is a further optimization of the above embodiment, wherein the test data acquisition unit includes a thin film interference test component, a laser ranging component, and a data receiving module;

[0141] The thin film interference test component obtains the first thin film measurement data of each test point on the corrosion inhibitor film on the inner surface of the oil and gas pipeline to be tested. The first thin film measurement data is the film thickness and test point position obtained based on the thin film interferometry method. It includes three annular optical probes, each of which includes a light source 1, an incident optical fiber, a beam splitter 2, a probe head 3, a lens, a reflector 4, a receiving optical fiber 5, a high-resolution light detector 6, a high-precision time measurement system 7, an automatic calibration system, a housing 8 and a connector 9.

[0142] The structure of the annular optical probe can be as shown in the attached Figure 8 shown.

[0143] The thin film interferometry test assembly is used to obtain the first film measurement data of each test point on the corrosion inhibitor film on the inner surface of the oil and gas pipeline to be tested, specifically including:

[0144] (1) Use thin film interferometry to measure the refractive index of various corrosion inhibitors, including:

[0145] (a) Preparation: Drop the corrosion inhibitor to be tested onto the center of the substrate. Set the spin coater speed to 3000 rpm and spin coat for 30 to 60 seconds. Place the substrate in an oven to dry to form a thin film, ensuring the surface is smooth and free of contamination. Use an interferometer for the experiment. Select a monochromatic light source with a known wavelength to improve measurement accuracy. Ensure all interferometer parameters are correctly adjusted before the experiment.

[0146] (b) Interference fringe formation and recording: Light source 1 is irradiated onto the film surface vertically or at a certain angle θ. The light waves are reflected from the upper and lower surfaces of the film. Due to the thinness of the film, the reflected light forms interference fringes with the incident light. After adjusting the experimental setup to make the interference fringes clearly visible, the fringes are observed and recorded in real time using an interferometer.

[0147] (c) By analyzing the position and number of interference fringes, the refractive index of the film to be measured is calculated given the known film thickness. Specifically,

[0148] When light is incident vertically, the optical path difference ΔL between the reflected light and the transmitted light is determined by the thickness and refractive index of the film, as shown in the following formula:

[0149] ΔL=2d(n-1)

[0150] Where d is the film thickness and n is the film refractive index;

[0151] According to the interference principle, when the optical path difference is equal to an integer multiple of the wavelength of light, interference fringes will be generated. The optical path difference and wavelength satisfy the following quantitative relationship;

[0152] ΔL=mλ

[0153] Where m is the order of the interference fringes (an integer), indicating the position of the fringes; λ is the wavelength of the incident light;

[0154] Combining the optical path difference formula with the interference condition formula, we can get the following formula for calculating the refractive index of the thin film:

[0155]

[0156] Where m is the order of interference fringes, λ is the wavelength of the light source used, and d is the film thickness;

[0157] If the light signal is not incident vertically (i.e., the incident angle is θ), the effect of refraction when the optical path difference is different needs to be considered. In this case, the formula should take into account the change in the path of the refracted light. Similarly, the following formula can be obtained:

[0158]

[0159] Where m is the order of the interference fringes, λ is the wavelength of the light source 1 used, d is the film thickness, and θ is the angle between the incident light and the normal.

[0160] (2) The film thickness at each test point on the corrosion inhibitor film on the inner surface of the oil and gas pipeline to be tested, obtained based on the thin film interferometry method, specifically including:

[0161] A corrosion inhibitor film is applied to the surface of the pipeline to be tested using a pre-filmed pig and a guide pig. Three annular optical probes connected to the guide pig and a high-precision time measurement system 7 are used to obtain the time information of the pig passing through the measurement point, the return time of the light signal, and the order of the interference fringes at that point.

[0162] The pre-filming pig, located at the front end of the device, cleans the inner wall of the pipeline, removing oil, rust, and impurities, providing a clean surface for corrosion inhibitor application and enhancing coating adhesion and effectiveness. The rear end is the corrosion inhibitor slug. The guide pig, located after the pre-filming pig and the corrosion inhibitor slug, guides the pig through complex or curved pipelines, controlling its direction and speed to ensure uniform corrosion inhibitor application.

[0163] Light source 1 emits a beam of light of a specific wavelength to illuminate the inner wall of the pipe. An incident optical fiber transmits the light from light source 1 to the probe head 3, where it passes sequentially through a beam splitter 2, a reflector 4, and a lens. Beam splitter 2 splits the incident light into two or more beams, which travel perpendicularly through the exit channel along different paths. These beams then reflect off the upper and lower surfaces of the film and converge, forming interference fringes. The reflector 4 modifies the light's propagation path, adjusting the shape and position of the interference fringes. The lens adjusts the size and distribution of the fringes, while also maintaining a higher resolution for the interference image. Another reflector 4 is located within the probe head 3, allowing light to return to a receiving optical fiber 5. The receiving optical fiber 5 is positioned parallel to the incident optical fiber and receives light reflected from the inner surface of the oil and gas pipeline under test. A light detector is located at the end of the probe, converting the optical signal received by the receiving optical fiber 5 into an electrical signal. Simultaneously, a high-precision time measurement system 7 captures the time the pig passes the current test point and the return time of the optical signal, outputting it as an electrical signal. A signal processor is installed outside the probe and is directly connected to the light detector and high-precision time measurement system 7. Its main function is to process the acquired electrical signal, obtain the time information of the pipe cleaner passing the test point, the return time data of the light signal, and the level of the interference fringes; based on the time data of the light signal return, the relative position of the annular optical probe in the cross section of the pipe is determined, thereby determining the incident angle of the light source 1 on the inner surface of the oil and gas pipeline to be measured; the film thickness at this position is calculated, and the calculated result data is output and stored. The annular optical probe is provided with a housing 8, which can effectively prevent interference from the external environment. Furthermore, an automatic calibration system is provided, and the calibration cycle is set according to the actual usage frequency of the device to meet the actual accuracy requirements of the device.

[0164] The acquired time information is processed by the signal processor inside the annular optical probe. The relative position of the annular optical probe in the cross section of the pipe is determined by the time data of the light signal emission and return, thereby determining the incident angle θ of the light source 1 on the inner surface of the oil and gas pipeline to be measured. The film thickness on the inner surface of the oil and gas pipeline to be measured is calculated by the following formula. After the calculation is completed, the time information of each test point is matched with the film thickness calculation result and the information is stored.

[0165]

[0166] Wherein, d is the film thickness, m is the order of interference fringes, λ is the wavelength of light source 1 used for the optical signal, n is the refractive index of the corrosion inhibitor film on the surface of the oil and gas pipeline to be measured, and θ is the incident angle of the optical signal relative to the inner surface of the oil and gas pipeline to be measured.

[0167] A laser ranging component is used to obtain second film measurement data of each test point on the corrosion inhibitor film on the inner surface of the oil and gas pipeline to be tested. The second film measurement data is the film thickness and the test point position obtained based on the laser ranging method, and includes a light source 1, a high-resolution light detector 6, a high-precision time measurement system 7, and a signal processor;

[0168] The above-mentioned method of obtaining the second film measurement data of each test point on the corrosion inhibitor film on the inner surface of the oil and gas pipeline to be tested based on the laser ranging component specifically includes:

[0169] Emitting light signal: The light source 1 transmits light signal to the inner surface of the pipeline to be tested. The light signal is reflected back after hitting the surface of the corrosion inhibitor film on the inner surface of the oil and gas pipeline to be tested.

[0170] Receive return signal: The high-resolution optical detector 6 receives the light signal reflected from the corrosion inhibitor film on the inner surface of the oil and gas pipeline to be tested, and the high-precision time measurement system 7 can measure the round-trip time of the light signal (i.e. the time from emission to reflection);

[0171] Distance calculation: The time difference of the round trip of the light signal is calculated by the built-in calculation program of the signal processor, and the distance from the light source 1 to the inner surface of the oil and gas pipeline to be tested is calculated by the following formula based on the time difference and the speed of light, thereby reflecting the change in the thickness of the corrosion inhibitor film.

[0172]

[0173] Where d is the actual distance between light source 1 and the inner surface of the oil and gas pipeline to be measured; c is the speed of light of light source 1; and t is the round-trip time difference of the optical signal.

[0174] The data receiving module receives the first film measurement data and the second film measurement data of each test point on the corrosion inhibitor film on the inner surface of the oil and gas pipeline to be tested.

[0175] The above content is only a specific implementation method of the present application, which has strong adaptability and implementation effect, but the protection scope of the present application is not limited to this. Any technician familiar with this technical field can easily think of changes or replacements within the technical scope disclosed in this application, which should be included in the protection scope of the present application. Therefore, equivalent changes made according to the claims of this application are still within the scope covered by this application.

Claims

1. A method for measuring the effective area and thickness of a corrosion inhibitor coating on an oil and gas pipeline, characterized in that: include: Obtaining first film measurement data and second film measurement data for each test point on the corrosion inhibitor film on the inner surface of the oil and gas pipeline to be tested, wherein the first film measurement data is the film thickness and the test point position obtained based on the thin film interferometry method, and the second film measurement data is the film thickness and the test point position obtained based on the laser ranging method; For each test point, the first film measurement data and the second film measurement data corresponding thereto are input into the film thickness comprehensive analysis model to obtain a final actual film thickness prediction value of the test point; Combining the effective thickness of the corrosion inhibitor coating and the predicted value of the actual film thickness at each test point, the failure points are screened out, and the effective area of ​​the corrosion inhibitor coating of the oil and gas pipeline to be tested is determined based on the number of failure points.

2. The method for measuring the effective area and thickness of a corrosion inhibitor coating on an oil and gas pipeline according to claim 1, wherein: The construction of the film thickness comprehensive analysis model includes: Obtain samples and divide them into a training sample set and a test sample set in proportion, wherein each sample includes first film measurement data, second film measurement data, and corresponding actual film thickness identification information of any test point on the corrosion inhibitor film on the surface of a historical oil and gas pipeline, the first film measurement data being the film thickness and the test point position obtained based on a thin film interferometry method, and the second film measurement data being the film thickness and the test point position obtained based on a laser ranging method; A multi-input neural network model is trained using a training sample set, and a training stop condition is introduced during training. When the training stop condition is met, the training is terminated to obtain a comprehensive analysis model of film thickness, wherein the multi-input neural network model includes an input layer, a hidden layer, and an output layer. The input layer receives the first film measurement data and the second film measurement data as input data, the hidden layer introduces nonlinearity through an activation function, and performs feature extraction on the input data, and the output layer outputs a predicted value of the actual film thickness; The trained film thickness comprehensive analysis model is tested using the test sample set, the model parameters of the film thickness comprehensive analysis model are optimized, and a film thickness comprehensive analysis model that meets the test evaluation requirements is output.

3. The method for measuring the effective area and thickness of a corrosion inhibitor coating on an oil and gas pipeline according to claim 1 or 2, characterized in that: The combination of the effective thickness of the corrosion inhibitor coating and the actual film thickness prediction value of each test point is used to screen out the failure points, including: Determine whether the actual film thickness prediction value at a certain test point is less than or equal to the effective thickness of the corrosion inhibitor coating; If the response is yes, then the test point is a failure point, and the film thickness loss rate of the test point is calculated by the following formula: Wherein, η is the thickness loss rate of the corrosion inhibitor film, d1 is the actual film thickness prediction value of the test point, and d0 is the effective thickness of the corrosion inhibitor coating; Traverse all test points, repeat the above steps, and filter out all failure points.

4. The method for measuring the effective area and thickness of a corrosion inhibitor coating on an oil and gas pipeline according to claim 1 or 2, wherein: The effective area of ​​the corrosion inhibitor coating of the oil and gas pipeline to be tested is determined based on the number of failure points by the following formula: Wherein, δ is the effective area of ​​the corrosion inhibitor coating, x1 is the number of failure points of the oil and gas pipeline to be tested, x0 is the total number of test points, and S is the total surface area of ​​the oil and gas pipeline to be tested.

5. The method for measuring the effective area and thickness of a corrosion inhibitor coating on an oil and gas pipeline according to any one of claims 1 to 4, characterized in that: The method of obtaining first film measurement data and second film measurement data of each test point on the corrosion inhibitor film on the surface of the oil and gas pipeline to be tested includes: Obtain the time information, light signal emission time, light signal return time, light signal incident angle relative to the inner surface of the oil and gas pipeline to be tested, and the order of interference fringes at a certain test point based on thin film interferometry to determine the film thickness at the test point; Where d is the film thickness, m is the order of interference fringes, λ is the wavelength of the light source used for the optical signal, n is the refractive index of the corrosion inhibitor film on the surface of the oil and gas pipeline to be tested, and θ is the incident angle of the optical signal relative to the inner surface of the oil and gas pipeline to be tested; The first film measurement data is formed by the film thickness of the test point and the position of the test point; Obtain the light speed of the light source and the round-trip time difference of the light signal at a certain test point based on the laser ranging method to determine the film thickness at the test point; Where d is the actual distance between the light source and the inner surface of the oil and gas pipeline to be measured; c is the speed of light from the light source; t is the round-trip time difference of the light signal; The second film measurement data is composed of the film thickness of the test point and the position of the test point.

6. A device for measuring the effective area and thickness of a corrosion inhibitor coating on an oil and gas pipeline using the method according to any one of claims 1 to 5, characterized in that: include: a test data acquisition unit, which acquires first film measurement data and second film measurement data of each test point on the corrosion inhibitor film on the inner surface of the oil and gas pipeline to be tested, wherein the first film measurement data is the film thickness and the test point position obtained based on the thin film interferometry method, and the second film measurement data is the film thickness and the test point position obtained based on the laser ranging method; The film thickness prediction unit inputs the first film measurement data and the second film measurement data corresponding to each test point into the film thickness comprehensive analysis model to obtain a final actual film thickness prediction value of the test point; The effective area acquisition unit combines the effective thickness of the corrosion inhibitor coating and the actual film thickness prediction value of each test point to screen out the failure points, and determines the effective area of ​​the corrosion inhibitor coating of the oil and gas pipeline to be tested based on the number of failure points.

7. The device for measuring effective area and thickness of corrosion inhibitor coating on oil and gas pipelines according to claim 6, characterized in that: The film thickness prediction unit comprises: Model building modules, including: The sample acquisition submodule acquires samples and divides them into a training sample set and a test sample set in proportion, wherein each sample includes the first film measurement data, the second film measurement data, and the corresponding actual film thickness identification information of any test point on the corrosion inhibitor film on the surface of the historical oil and gas pipeline. The first film measurement data is the film thickness and the test point position obtained based on the thin film interferometry method, and the second film measurement data is the film thickness and the test point position obtained based on the laser ranging method. A training submodule trains a multi-input neural network model using a training sample set, introduces a training stop condition during training, and terminates the training when the training stop condition is met, thereby obtaining a film thickness comprehensive analysis model, wherein the multi-input neural network model includes an input layer, a hidden layer, and an output layer, wherein the input layer receives the first film measurement data and the second film measurement data as input data, the hidden layer introduces nonlinearity through an activation function, performs feature extraction on the input data, and the output layer outputs a predicted value of the actual film thickness; The testing submodule uses the test sample set to test the trained film thickness comprehensive analysis model, optimizes the model parameters of the film thickness comprehensive analysis model, and outputs a film thickness comprehensive analysis model that meets the test evaluation requirements; The prediction module inputs the first film measurement data and the second film measurement data corresponding to each test point into the film thickness comprehensive analysis model to obtain the final actual film thickness prediction value of the test point.

8. The device for measuring effective area and thickness of corrosion inhibitor coating for oil and gas pipelines according to claim 6 or 7, characterized in that: The effective area acquisition unit includes: The failure point screening module combines the effective thickness of the corrosion inhibitor coating and the actual film thickness prediction value of each test point to screen out the failure points, including: Determine whether the actual film thickness prediction value at a certain test point is less than or equal to the effective thickness of the corrosion inhibitor coating; If the response is yes, then the test point is a failure point, and the film thickness loss rate of the test point is calculated by the following formula: Wherein, η is the thickness loss rate of the corrosion inhibitor film, d1 is the actual film thickness prediction value of the test point, and d0 is the effective thickness of the corrosion inhibitor coating; Traverse all test points, repeat the above steps, and filter out all failure points; The effective area determination module determines the effective area of ​​the corrosion inhibitor coating of the oil and gas pipeline to be tested based on the number of failure points through the following formula: Wherein, δ is the effective area of ​​the corrosion inhibitor coating, x1 is the number of failure points of the oil and gas pipeline to be tested, x0 is the total number of test points, and S is the total surface area of ​​the oil and gas pipeline to be tested.

9. The device for measuring effective area and thickness of corrosion inhibitor coating for oil and gas pipelines according to any one of claims 6 to 8, characterized in that: The test data acquisition unit includes a thin film interference test component, a laser ranging component, and a data receiving module; A thin film interferometry test assembly, which obtains first film measurement data for each test point on the corrosion inhibitor film on the inner surface of the oil and gas pipeline to be tested. The first film measurement data is the film thickness and test point position obtained based on thin film interferometry. The assembly includes three annular optical probes, each of which includes a light source, an incident optical fiber, a beam splitter, a probe head, a lens, a reflector, a receiving optical fiber, a high-resolution light detector, a high-precision time measurement system, an automatic calibration system, a housing, and a connector. A laser ranging component is used to obtain second film measurement data at each test point on the corrosion inhibitor film on the inner surface of the oil and gas pipeline to be tested. The second film measurement data is the film thickness and the test point position obtained based on the laser ranging method. The component includes a light source, a high-resolution light detector, a high-precision time measurement system, and a signal processor. The data receiving module receives the first film measurement data and the second film measurement data of each test point on the corrosion inhibitor film on the inner surface of the oil and gas pipeline to be tested.

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