Method for identifying corrosion high-risk points in sulfur-containing purification plant

Abstract

The invention discloses a method for identifying corrosion high-risk points in a sulfur-containing purification plant, relates to the technical field of corrosion analysis and protection, and can accurately identify the corrosion high-risk points in a natural gas purification plant by analyzing corrosion monitoring data in historical periods. The problem that in the prior art, the corrosion high-risk point is inaccurately set depending on experience is solved, and stable operation of a purification plant is guaranteed. And CFD analysis is carried out on the regeneration tower and the reboiler, so that the problem of inaccurate analysis caused by special structures and complex internal flow fields of the regeneration tower and the reboiler is avoided, and high-risk corrosion points in the natural gas purification plant can be comprehensively analyzed.

Description

Technical Field

[0001] The invention relates to the technical field of corrosion analysis and protection, and in particular to a method for identifying high-risk corrosion points in a sulfur-containing purification plant. Background Art

[0002] As a high-quality clean energy, the development and utilization of natural gas has received widespread attention from the world. However, natural gas in Sichuan and Chongqing generally contains sulfur, and natural gas needs to be processed in a natural gas purification plant before it can be used. The process flow of purification plants at home and abroad is relatively complex, including desulfurization, sulfur recovery, tail gas treatment, public works and other units; there are many equipment involved, including absorption towers, regeneration towers, reboilers, lean and rich liquid heat exchangers; the corrosion environment of the equipment is changeable, gas, liquid, and solid three-phase coexistence, and there are high temperatures and high pressures at the same time. The highest temperature of the regeneration tower reaches 135°C, and the temperature of the reboiler even exceeds 135°C. The pressure of the absorption tower is greater than 6Mpa. Taking the regeneration tower as an example, the height is more than 20 meters, and there is a large temperature difference between the top and the bottom, with a temperature of 90-105°C at the top and 127-135°C at the bottom. The rich liquid containing acid gas enters the regeneration tower from the top, and the middle rich liquid will continuously parse out acid gas and become semi-lean liquid, and finally become lean liquid at the bottom of the tower, flowing out of the regeneration tower for recycling. The whole process is accompanied by a variety of chemical processes such as acid gas analysis, gas-liquid phase change, temperature change, etc. The material exchange inside the regeneration tower is very complex. Overall, the corrosion environment is relatively harsh, and electrochemical corrosion caused by acid gas, heat-stable salts, and amine liquids, as well as erosion corrosion, are widespread. Since the surface of the purification plant equipment, especially the high-temperature equipment, is covered with an insulation layer, it is difficult to find corrosion leakage points during operation, so corrosion monitoring is required to ensure safe operation. In the actual process, the setting of corrosion monitoring points mostly relies on experience, lacks theoretical and data support, and the pertinence of corrosion monitoring is generally insufficient. It is often discovered only when large corrosion leaks occur, causing the purification plant to stop temporarily, seriously affecting the stable operation of the purification plant. It is urgent to identify the high-risk corrosion points of high-sulfur purification plants, so as to carry out targeted corrosion monitoring and corrosion control to ensure the stable operation of the purification plant. Summary of the invention

[0003] The purpose of the present application is to provide a method for identifying high-risk corrosion points in a sulfur-containing purification plant, which solves the problems existing in the prior art.

[0004] The present invention is achieved through the following technical solutions:

[0005] A method for identifying high-risk corrosion points in a sulfur-containing purification plant, comprising:

[0006] Obtaining corrosion monitoring data of the sulfur-containing purification plant in historical periods, the process flow of the sulfur-containing purification plant, the corrosion environment, and the characteristics of the work object, wherein the corrosion monitoring data of the historical periods, the process flow of the sulfur-containing purification plant, the corrosion environment, and the characteristics of the work object are all pre-stored data;

[0007] According to the process flow, corrosion environment and working object characteristics of the sulfur-containing purification plant, the working objects in the sulfur-containing purification plant are divided into corrosion circuits to obtain multiple corrosion circuits;

[0008] Determine the corrosion influencing factors of each corrosion circuit in its corrosion environment, analyze the corrosion influencing factors, and obtain the corrosion weight values ​​corresponding to different corrosion influencing factors;

[0009] According to the corrosion monitoring data of the sulfur-containing purification plant in the historical period and the corrosion weight values ​​corresponding to the corrosion influencing factors, combined with the real-time monitoring values ​​of the corrosion influencing factors, the high-risk corrosion points in the sulfur-containing purification plant are identified, and the high-risk corrosion point identification results are obtained.

[0010] In a possible implementation, the method further includes: obtaining material characteristics corresponding to all working objects corresponding to the corrosion monitoring data, corrosion mechanisms corresponding to the material characteristics, and corrosion environments.

[0011] In a possible implementation, according to the process flow, corrosion environment and working object characteristics of the sulfur-containing purification plant, the working objects in the sulfur-containing purification plant are divided into corrosion circuits to obtain multiple corrosion circuits, including:

[0012] Determine the material characteristics, the corrosion mechanism corresponding to the material characteristics and the working objects with the same corrosion environment in the sulfur-containing purification plant to obtain a set of working objects; the working object characteristics include the material characteristics and the corrosion mechanism corresponding to the material characteristics;

[0013] All target working objects involved in each process step in the process flow are determined, and the target working objects in the same working object set form a corrosion loop to obtain multiple corrosion loops.

[0014] In a possible implementation, determining the corrosion influencing factors of each corrosion circuit in the corrosion environment in which it is located includes:

[0015] Obtaining the pre-stored corrosion influencing factors of each corrosion circuit in the corrosion environment in which it is located or receiving the corrosion influencing factors input by the staff through human-computer interaction;

[0016] Among them, the corrosion influencing factors are determined according to the process characteristics of the purification plant, and the corrosion influencing factors at least include temperature factors, solution acid gas load factors, flow rate factors, solution concentration factors, heat-stable salt type factors and heat-stable salt content factors.

[0017] In a possible implementation, the corrosion influencing factors are analyzed to obtain corrosion weight values ​​corresponding to different corrosion influencing factors, including:

[0018] For the corrosion influencing factors, at least 4 levels are selected for each factor, and indoor evaluation tests are carried out to obtain the corresponding relationship between the corrosion influencing factors and the corrosion rate, and obtain the corrosion rate curve;

[0019] With the corrosion rate curve as data support, the grey correlation method is used to determine the corrosion weight values ​​corresponding to the corrosion influencing factors corresponding to different corrosion loops.

[0020] In a possible implementation, based on the corrosion monitoring data of the sulfur-containing purification plant in the historical period and the corrosion weight values ​​corresponding to the corrosion influencing factors, combined with the real-time monitoring values ​​of the corrosion influencing factors, the high-risk corrosion points in the sulfur-containing purification plant are identified to obtain the high-risk corrosion point identification results, including:

[0021] Based on the corrosion monitoring data of the sulfur purification plant in the historical period, the points where the sulfur purification plant has experienced corrosion failure in the historical period are determined as the first corrosion high risk points;

[0022] Based on the corrosion monitoring data of the sulfur-containing purification plant in the historical period, the corrosion rate of each point in the sulfur-containing purification plant is determined, and the point whose corrosion rate exceeds the preset corrosion rate threshold is determined as the second corrosion high risk point, or the real-time monitoring value of the corrosion influencing factors of each point in the sulfur-containing purification plant is obtained, and the corrosion rate of each point is predicted using a pre-trained deep learning model, and the point whose corrosion rate exceeds the preset corrosion rate threshold is determined as the second corrosion high risk point;

[0023] The corrosion weight values ​​corresponding to the corrosion influencing factors of each point in the sulfur purification plant are accumulated and calculated to obtain the total corrosion weight value of each point in the sulfur purification plant, and the critical threshold corresponding to the total corrosion weight value is determined according to the second corrosion high risk point, and the point where the total corrosion weight value exceeds the critical threshold is determined as the third corrosion high risk point;

[0024] The first corrosion high risk point, the second corrosion high risk point and the third corrosion high risk point are taken together as the corrosion high risk point identification results in the sulfur-containing purification plant.

[0025] In a possible implementation, it further includes:

[0026] Obtain the corrosion monitoring data of other sulfur-containing purification plants in historical periods, and determine the target points where the corrosion failures in other sulfur-containing purification plants exceed the threshold number of times based on the corrosion monitoring data of other sulfur-containing purification plants;

[0027] The point in the sulfur-containing purification plant with the same corrosion high risk point as the target point is determined as the fourth corrosion high risk point, and the first corrosion high risk point, the second corrosion high risk point, the third corrosion high risk point and the fourth corrosion high risk point are collectively used as the identification results of the corrosion high risk points in the sulfur-containing purification plant.

[0028] In a possible implementation, after identifying high-risk corrosion points in the sulfur-containing purification plant based on the corrosion monitoring data of the sulfur-containing purification plant in the historical period and the corrosion weight values ​​corresponding to the corrosion influencing factors, combined with the real-time monitoring values ​​of the corrosion influencing factors, the method further includes:

[0029] Based on the pre-set update cycle, the corrosion monitoring data of the sulfur-containing purification plant in the historical period, the process flow of the sulfur-containing purification plant, the corrosion environment and the characteristics of the work objects are re-acquired after each update cycle, and the high-risk corrosion points are re-identified based on the corrosion monitoring data of the sulfur-containing purification plant in the historical period and the process flow of the sulfur-containing purification plant, thereby completing the update of the high-risk corrosion point identification results.

[0030] In a possible implementation, it further includes:

[0031] For the regeneration tower in the sulfur purification plant, the CFD simulation analysis method is used to simulate and analyze the flow field distribution diagram of the regeneration tower;

[0032] The area with the largest flow field change in the flow field distribution diagram of the regeneration tower is determined as the target area, and the target area is used as the high-risk corrosion point corresponding to the regeneration tower to obtain the fifth high-risk point; the first high-risk corrosion point, the second high-risk corrosion point, the third high-risk corrosion point, the fourth high-risk corrosion point and the fifth high-risk point are collectively used as the high-risk corrosion point identification results in the sulfur-containing purification plant.

[0033] In a possible implementation, it further includes:

[0034] For the reboiler in the sulfur purification plant, the CFD simulation analysis method is used to simulate and analyze the flow field distribution diagram of the reboiler;

[0035] The area with the largest flow field change in the flow field distribution diagram of the reboiler is determined as the target area, and the target area is used as the high-risk corrosion point corresponding to the reboiler to obtain the sixth high-risk point; the first high-risk corrosion point, the second high-risk corrosion point, the third high-risk corrosion point, the fourth high-risk corrosion point, the fifth high-risk point and the sixth high-risk point are collectively used as the high-risk corrosion point identification results in the sulfur-containing purification plant.

[0036] The present invention provides a method for identifying high-risk corrosion points in a sulfur-containing purification plant. By analyzing the corrosion monitoring data of historical periods, the high-risk corrosion points in the natural gas purification plant can be accurately identified, thereby solving the problem of inaccurate setting of high-risk corrosion points based on experience in the prior art, and ensuring the stable operation of the purification plant. In addition, CFD analysis is performed on the regeneration tower and the reboiler, thereby avoiding the problem of inaccurate analysis due to the special structure and complex internal flow field of the regeneration tower and the reboiler, and the high-risk corrosion points in the natural gas purification plant can be comprehensively analyzed. BRIEF DESCRIPTION OF THE DRAWINGS

[0037] In order to more clearly illustrate the technical solutions of the exemplary embodiments of the present invention, the following briefly introduces the drawings required for use in the embodiments. It should be understood that the following drawings only illustrate certain embodiments of the present invention and should not be regarded as limiting the scope. For those of ordinary skill in the art, other relevant drawings can be obtained based on these drawings without creative work. In the drawings:

[0038] Figure 1 A schematic flow chart of a method for identifying high-risk corrosion points in a sulfur-containing purification plant provided in an embodiment of the present invention. DETAILED DESCRIPTION

[0039] In order to make the objectives, technical solutions and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with embodiments and drawings. The exemplary embodiments of the present invention and their description are only used to explain the present invention and are not intended to limit the present invention.

[0040] Example

[0041] like Figure 1 As shown, an embodiment of the present invention provides a method for identifying high-risk corrosion points in a sulfur-containing purification plant, comprising:

[0042] S1. Obtain corrosion monitoring data of a sulfur-containing purification plant in a historical period, the process flow of the sulfur-containing purification plant, the corrosion environment, and the characteristics of the work object, wherein the corrosion monitoring data of the historical period, the process flow of the sulfur-containing purification plant, the corrosion environment, and the characteristics of the work object are all pre-stored data. For example, the data may be pre-stored in a database, an Excel file, a paper file, or other electronic files.

[0043] In order to facilitate the understanding of this embodiment, this embodiment first introduces the knowledge related to the purification plant and corrosion analysis, as follows: The basic overview of the purification plant includes the processing capacity, the H2S and CO2 content of the raw gas, and the H2S and CO2 content of the product gas. The process flow of a conventional purification plant includes filtration, dehydration, desulfurization, sulfur recovery, and tail gas unit.

[0044] Based on the process flow chart and the process characteristics of each unit, the operating parameters of the key equipment of each unit in the past three years can be sorted out and analyzed, including temperature, pressure, solution acid gas load, flow rate, solution concentration, and the type and content of heat-stable salts.

[0045] The corrosion monitoring data analysis of the purification plant includes: design data of equipment and pipelines, established corrosion probes, corrosion coupons, and ultrasonic thickness measurement data, which can draw a curve of corrosion monitoring and time, as well as various corrosion detection reports and failure statistics reports carried out during overhaul to reflect the corrosion status information of the purification plant operation.

[0046] For example, the basic profile of the purification plant may include: processing capacity: 3 million cubic meters / day. Raw gas H2S: 10%. CO2 content: 8%. Product gas H2S: ≤20mg / m 3 . CO2 content: 2%. The basic process flow is dehydration, alcohol amine solution desulfurization, sulfur recovery, and SCOT tail gas unit.

[0047] Analyzing the operating parameters, taking the desulfurization unit as an example, the process parameter characteristics are as follows:

[0048] Temperature: 40-130℃. Pressure: 0-6Mpa. Solution acid gas load: 0-0.6. Flow rate: 0-2.0m / s. Solution concentration: 40-50%. Types and contents of heat-stable salts: Total salt content: 0-10000mg / L. Hydrochloride: 0-3000mg / L, sulfate: 0-2000mg / L, formate: 0-2000mg / L, acetate: 0-1000mg / L, oxalate 0-2000mg / L, thiosulfate: 0-1000mg / L.

[0049] Optionally, in order to facilitate the implementation of subsequent steps, a corrosion monitoring database can be established first. Based on three years of corrosion monitoring data, a corrosion monitoring database for the purification plant can be formed and stored in chronological order to generate corrosion status charts for key equipment and pipelines to understand the corrosion status of the purification plant.

[0050] S2. According to the process flow, corrosion environment and working object characteristics of the sulfur-containing purification plant, the working objects in the sulfur-containing purification plant are divided into corrosion circuits to obtain multiple corrosion circuits.

[0051] Optionally, the corrosion mechanism, corrosion environment and equipment material can be consistently divided into a corrosion loop to facilitate the analysis of corrosion influencing factors.

[0052] S3. Determine the corrosion influencing factors of each corrosion circuit in its corrosion environment, analyze the corrosion influencing factors, and obtain corrosion weight values ​​corresponding to different corrosion influencing factors.

[0053] For the designated corrosion loops, the corrosion influencing factors of each corrosion loop or process unit are analyzed through indoor evaluation tests, combined with the process parameter characteristics analyzed in the second part. The influence curves of temperature, solution acid gas load, flow rate, solution concentration, type and content of heat-stable salt on the corrosion rate are developed. At least 4 levels are selected for each influencing factor to obtain the influence of the influencing factors on corrosion. According to the actual situation on site, single factor or multi-factor analysis can be carried out. Based on the grey correlation method, the reference data column is determined, the indicator data is dimensionless, the indicator sequence of each evaluated object is calculated, the corrosion weight value of each influencing factor is calculated, and the data value of the corrosion influencing factor of the corrosion loop is obtained.

[0054] At the same time, the corrosion mechanism is further explored. The types and total amount of heat-stable salts in each purification plant are different. They generally include chlorides, sulfates, thiosulfates, formates, acetates, glycolates, oxalates, glycine, etc. Pay special attention to the content of oxalate and glycine. If the analysis data shows that the content of these two salts exceeds 500 mg / L, these two salts need to be listed separately as one of the influencing factors.

[0055] The corrosion mechanism of heat-stable salts is: oxalic acid, glycine, etc. have strong chelating ability with iron, which will destroy the protective film on the metal surface and accelerate the occurrence of corrosion, so they need to be included in the analysis of the corrosion rate curve.

[0056] S4. Based on the corrosion monitoring data of the sulfur-containing purification plant in the historical period and the corrosion weight values ​​corresponding to the corrosion influencing factors, combined with the real-time monitoring values ​​of the corrosion influencing factors, the high-risk corrosion points in the sulfur-containing purification plant are identified to obtain the high-risk corrosion point identification results.

[0057] In a possible implementation, the method for identifying high-risk corrosion points in a sulfur-containing purification plant further includes: obtaining material characteristics corresponding to all work objects corresponding to corrosion monitoring data, corrosion mechanisms corresponding to the material characteristics, and corrosion environments.

[0058] In a possible implementation, according to the process flow, corrosion environment and working object characteristics of the sulfur-containing purification plant, the working objects in the sulfur-containing purification plant are divided into corrosion circuits to obtain multiple corrosion circuits, including:

[0059] The material characteristics, the corrosion mechanisms corresponding to the material characteristics and the working objects with the same corrosion environment in the sulfur-containing purification plant are determined to obtain a set of working objects; the working object characteristics include the material characteristics and the corrosion mechanisms corresponding to the material characteristics, and the working objects are used to characterize the working equipment in the sulfur-containing purification plant.

[0060] All target working objects involved in each process step in the process flow are determined, and the target working objects in the same working object set form a corrosion loop to obtain multiple corrosion loops.

[0061] For example, the corrosion circuits may be divided as shown in Table 1. However, it is worth noting that the corrosion circuits in Table 1 are only used to help those skilled in the art understand the scheme described in this embodiment and are not intended to be limiting. Other corrosion circuits may also be divided.

[0062] Table 1

[0063]

[0064] In a possible implementation, determining the corrosion influencing factors of each corrosion circuit in the corrosion environment in which it is located includes:

[0065] The pre-stored corrosion influencing factors of each corrosion circuit in the corrosion environment in which it is located are obtained, or the corrosion influencing factors input by the staff through human-computer interaction are received.

[0066] Among them, the corrosion influencing factors are determined according to the process characteristics of the purification plant, and the corrosion influencing factors at least include temperature factors, solution acid gas load factors, flow rate factors, solution concentration factors, heat-stable salt type factors and heat-stable salt content factors.

[0067] In a possible implementation, the corrosion influencing factors are analyzed to obtain corrosion weight values ​​corresponding to different corrosion influencing factors, including:

[0068] For the corrosion influencing factors, at least 4 levels are selected for each factor, and indoor evaluation tests are carried out to obtain the corresponding relationship between the corrosion influencing factors and the corrosion rate and obtain the corrosion rate curve.

[0069] With the corrosion rate curve as data support, the grey correlation method is used to determine the corrosion weight values ​​corresponding to the corrosion influencing factors corresponding to different corrosion loops.

[0070] The typical calculation steps of grey correlation method are as follows:

[0071] Assume that there are N independent variables X of dependent variable Y, and the L groups of data obtained from the experiment are as follows:

[0072] Suppose n data sequences form the following matrix:

[0073]

[0074] Among them, m is the number of indicators, X′ i =(x′ i (1), x′ j (2), …, x′i (m)) T , i=1,2,…,n

[0075] 2. Determine the reference data column

[0076] The reference data column should be an ideal comparison standard. The reference data column can be composed of the optimal value (or the worst value) of each indicator, or other reference values ​​can be selected according to the evaluation purpose, which can be recorded as:

[0077] X′0=((x′0(1),x′0(2),…,x′0(m))

[0078] 3. Non-dimensionalize indicator data

[0079] Since the physical meanings of various factors in the system are different, the dimensions of the data may not be the same, which makes it difficult to compare or to get the correct conclusion when comparing. Therefore, dimensionless data processing is generally required when performing grey relational analysis.

[0080] Commonly used dimensionless methods include averaging, initialization, and Transformation, etc.

[0081] The dimensionless data sequence forms the following matrix:

[0082]

[0083] 4. Calculate the absolute difference between the corresponding elements of each evaluated object indicator sequence (comparison sequence) and the reference sequence one by one

[0084] That is |x0(k)-x i (k)|(k=1, ..., m, i=1, ..., n, n is the number of evaluated objects).

[0085] 5. OK and

[0086] 6. Calculate the correlation coefficient

[0087] The correlation coefficients of the corresponding elements of each comparison sequence and the reference sequence are calculated by the following formula:

[0088]

[0089] Usually ρ is taken as 0.5, but the value selected by such definition is subjective, and the scientificity of the calculated correlation still needs to be further improved. This embodiment comprehensively considers the corrosion influencing factors of the purification plant, and combines the characteristics of the center point whitening weight function. After research, ρ is taken as 0.25, which is more suitable for the analysis of the main control factors of corrosion in the purification plant, and the identified weight size is more consistent with the actual monitoring results.

[0090] When the optimal value (or the worst value) of each indicator is used to form a reference data column to calculate the correlation coefficient, an improved and simpler calculation method can also be used:

[0091]

[0092] The improved method can not only omit the third step, making the calculation simpler, but also avoid some negative effects of dimensionless on the index effect.

[0093] 7. Calculate the association order

[0094] For each evaluation object (comparison sequence), the mean of the correlation coefficient between its individual indicators and the corresponding elements of the reference sequence is calculated to reflect the correlation relationship between each evaluation object and the reference sequence, which is called the correlation sequence and recorded as:

[0095]

[0096] 8. If the various indicators play different roles in the comprehensive evaluation, the weighted average of the correlation coefficient can be calculated:

[0097]

[0098] Where W k is the weight of each indicator.

[0099] 9. Based on the correlation sequence of each observed object, the analysis results are obtained.

[0100] For example: select the influencing factors of temperature, solution acid gas load, flow rate, solution concentration, and heat-stable salt, carry out indoor evaluation tests, and obtain the corrosion weight values ​​of each influencing factor through the grey correlation method. Flow rate: 0.9213. Heat-stable salt: 0.9022. Temperature: 0.8256. Acid gas load: 0.7725. Solution amine concentration: 0.5536.

[0101] In a possible implementation, based on the corrosion monitoring data of the sulfur-containing purification plant in the historical period and the corrosion weight values ​​corresponding to the corrosion influencing factors, combined with the real-time monitoring values ​​of the corrosion influencing factors, the high-risk corrosion points in the sulfur-containing purification plant are identified to obtain the high-risk corrosion point identification results, including:

[0102] According to the corrosion monitoring data of the sulfur purification plant in the historical period, the points where the sulfur purification plant has experienced corrosion failure in the historical period are determined as the first corrosion high risk points. For example, the points that have experienced corrosion failure in the past three years during daily operation and overhaul are high corrosion risk points. Table 2 is an example of corrosion rate.

[0103] Table 2

[0104]

[0105] According to the corrosion monitoring data of the sulfur-containing purification plant in the historical period, the corrosion rate of each point in the sulfur-containing purification plant is determined, and the point whose corrosion rate exceeds the preset corrosion rate threshold is determined as the second corrosion high risk point, or the real-time monitoring value of the corrosion influencing factors of each point in the sulfur-containing purification plant is obtained, and the corrosion rate of each point is predicted by the pre-trained deep learning model, and the point whose corrosion rate exceeds the preset corrosion rate threshold is determined as the second corrosion high risk point. For example: Corrosion monitoring in the past three years shows that the corrosion rate exceeds 0.125mm / a. It can be seen from Table 2 that the lower part of the regeneration tower, the semi-lean amine liquid pipeline, the reboiler to the regeneration tower, the semi-lean amine liquid pipeline, the regeneration tower to the reboiler, and the acid gas pipeline at the top of the regeneration tower are all more than 0.125mm / a, so they are high corrosion risk points. By identifying and analyzing historical data, high corrosion risk points can be accurately identified, avoiding the occurrence of inaccurate manual determination.

[0106] Optionally, the pre-trained deep learning model can be set as a BP neural network (Back Propagation), and the BP neural network can be trained by training data containing historical monitoring values ​​and corresponding corrosion rates, that is, historical monitoring values ​​are used as input and corrosion rates are used as true value labels for training. It is worth noting that instantaneous monitoring values ​​may not be representative, so the real-time monitoring value can be the average data within a certain period of time.

[0107] The corrosion rate corresponding to the historical monitoring value can be calculated through subsequent observation data. Therefore, after the deep learning model is trained with historical monitoring values, the deep learning model has the ability to predict the real-time monitoring values, thereby realizing the prediction of the corrosion rate and timely discovering high-risk corrosion points.

[0108] The corrosion weight values ​​corresponding to the corrosion influencing factors of each point in the sulfur purification plant are accumulated and calculated to obtain the total corrosion weight value of each point in the sulfur purification plant. The critical threshold corresponding to the total corrosion weight value is determined according to the second corrosion high risk point, and the point where the total corrosion weight value exceeds the critical threshold is determined as the third corrosion high risk point.

[0109] When the corrosion rate exceeds 0.125mm / a, it can be identified as a high-risk corrosion point. Therefore, the total corrosion weight value of the point can be calculated, which can be used as the critical threshold. In this way, short-term data or real-time data can be directly judged to determine the high-risk corrosion point.

[0110] Taking the lower part of the regeneration tower as an example, its corrosion rate exceeds 0.125mm / a. According to the corrosion weight value of the corrosion influencing factor, the corrosion value is calculated to be 3.2027. Then, according to the operating parameters of other points, the total value of the corrosion weight is calculated. If it is greater than 3.2027, it is determined to be a high-risk point for corrosion.

[0111] The first corrosion high risk point, the second corrosion high risk point and the third corrosion high risk point are taken together as the corrosion high risk point identification results in the sulfur-containing purification plant.

[0112] It is worth noting that the point position in this embodiment is used to represent the work object or a designated monitoring point on the work object.

[0113] This embodiment uses a deep learning model trained based on historical data for identification, and can accurately identify high-risk corrosion points in a sulfur-containing purification plant even if there is little or no historical data record. Compared with identifying high-risk corrosion points in a sulfur-containing purification plant through historical data, it can be implemented without data records, and can detect high-risk corrosion points earlier, so that the staff can deal with the high-risk corrosion points in advance to ensure stable operation.

[0114] The first corrosion high risk point, the second corrosion high risk point and the third corrosion high risk point are taken together as the corrosion high risk point identification results in the sulfur-containing purification plant.

[0115] In a possible implementation, it further includes:

[0116] Obtain the corrosion monitoring data of other sulfur-containing purification plants in historical periods, and determine the target points in other sulfur-containing purification plants where the number of corrosion failures exceeds the threshold based on the corrosion monitoring data of other sulfur-containing purification plants.

[0117] The point in the sulfur-containing purification plant with the same corrosion high risk point as the target point is determined as the fourth corrosion high risk point, and the first corrosion high risk point, the second corrosion high risk point, the third corrosion high risk point and the fourth corrosion high risk point are collectively used as the identification results of the corrosion high risk points in the sulfur-containing purification plant.

[0118] In a possible implementation, after identifying high-risk corrosion points in the sulfur-containing purification plant based on the corrosion monitoring data of the sulfur-containing purification plant in the historical period and the weight factors corresponding to the corrosion influencing factors, combined with the real-time monitoring values ​​of the corrosion influencing factors, the method further includes:

[0119] Based on the pre-set update cycle, the corrosion monitoring data of the sulfur-containing purification plant in the historical period, the process flow of the sulfur-containing purification plant, the corrosion environment and the characteristics of the work objects are re-acquired after each update cycle, and the high-risk corrosion points are re-identified based on the corrosion monitoring data of the sulfur-containing purification plant in the historical period and the process flow of the sulfur-containing purification plant, thereby completing the update of the high-risk corrosion point identification results.

[0120] In view of the special processes and procedures of the purification plant, the regeneration tower, reboiler and other equipment are selected for analysis (it is worth mentioning that other equipment, such as flash tower, gravity separator, etc., can also be used). The regeneration tower plays the role of regenerating the solution. The desulfurized rich liquid that absorbs the acid gas is analyzed into lean liquid in the equipment and then returned to the absorption link for standby. The equipment is generally high, up to 20 meters or more, with a certain temperature difference between the upper and lower parts, the upper temperature is 90-105℃, and the lower temperature is 120-135℃. The internal solution gas-liquid interaction is relatively intense, and it is the key equipment for corrosion analysis of the purification plant. The reboiler includes thermal siphon type and kettle type, which is a shell-and-tube heat exchanger structure. The function of the reboiler is to provide heat to the regeneration tower by steam heat exchange.

[0121] In a possible implementation, the method for identifying high-risk corrosion points in a sulfur-containing purification plant further includes:

[0122] For the regeneration tower in the sulfur-containing purification plant, a CFD (Computational Fluid Dynamics) simulation analysis method is used to perform simulation analysis to obtain the flow field distribution diagram of the regeneration tower.

[0123] The area with the largest flow field change in the flow field distribution diagram of the regeneration tower is determined as the target area, and the target area is used as the high-risk corrosion point corresponding to the regeneration tower to obtain the fifth high-risk point; the first high-risk corrosion point, the second high-risk corrosion point, the third high-risk corrosion point, the fourth high-risk corrosion point and the fifth high-risk point are collectively used as the high-risk corrosion point identification results in the sulfur-containing purification plant.

[0124] In a possible implementation, the method for identifying high-risk corrosion points in a sulfur-containing purification plant further includes:

[0125] For the reboiler in the sulfur purification plant, CFD simulation analysis method is used to perform simulation analysis and obtain the flow field distribution diagram of the reboiler.

[0126] The area with the largest flow field change in the flow field distribution diagram of the reboiler is determined as the target area, and the target area is used as the high-risk corrosion point corresponding to the reboiler to obtain the sixth high-risk point; the first high-risk corrosion point, the second high-risk corrosion point, the third high-risk corrosion point, the fourth high-risk corrosion point, the fifth high-risk point and the sixth high-risk point are collectively used as the high-risk corrosion point identification results in the sulfur-containing purification plant.

[0127] In view of the special structure of the regeneration tower and reboiler, the CFD simulation analysis method is used to perform simulation analysis. Under actual operating conditions, the temperature, pressure, solution composition, and gas composition are obtained, and then the physical properties of the gas phase and the mixed liquid phase are obtained. Then, the numerical simulation calculation method (CFD) is used to establish a model, and the internal flow field distribution law of the full-scale regeneration tower and reboiler is calculated, including the distribution law of temperature distribution, flow rate, and gas-liquid volume fraction. The flow field distribution map inside the entire regeneration tower is calculated, and it is found that the positions with the largest temperature change, the largest flow rate change, and the most drastic gas-liquid change are the parts with the highest corrosion risk of the regeneration tower and reboiler, and the risk analysis of the purification plant is refined into a certain part of the equipment, rather than the entire equipment itself. By obtaining the flow field distribution map inside the tube bundle of the reboiler, it is found that the flow field in the middle of the tube bundle changes most drastically, and the color change in the middle is the most drastic, so the middle of the tube bundle is a high-risk point for corrosion.

[0128] The present invention provides a method for identifying high-risk corrosion points in a sulfur-containing purification plant. By analyzing the corrosion monitoring data of historical periods, the high-risk corrosion points in the natural gas purification plant can be accurately identified, which solves the problem of inaccurate setting of high-risk corrosion points based on experience in the prior art and ensures the stable operation of the purification plant. In addition, CFD analysis is performed on the regeneration tower and the reboiler, which avoids the problem of inaccurate analysis due to the special structure and complex internal flow field of the regeneration tower and the reboiler, and can comprehensively analyze the high-risk corrosion points in the natural gas purification plant.

[0129] The specific implementation methods described above further illustrate the objectives, technical solutions and beneficial effects of the present invention in detail. It should be understood that the above description is only a specific implementation method of the present invention and is not intended to limit the scope of protection of the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the scope of protection of the present invention.

Claims

1. A method for identifying high-risk corrosion points in a sulfur-containing purification plant, characterized in that: include: Obtaining corrosion monitoring data of the sulfur-containing purification plant in historical periods, the process flow of the sulfur-containing purification plant, the corrosion environment, and the characteristics of the work object, wherein the corrosion monitoring data of the historical periods, the process flow of the sulfur-containing purification plant, the corrosion environment, and the characteristics of the work object are all pre-stored data; According to the process flow, corrosion environment and working object characteristics of the sulfur-containing purification plant, the working objects in the sulfur-containing purification plant are divided into corrosion circuits to obtain multiple corrosion circuits; Determine the corrosion influencing factors of each corrosion circuit in its corrosion environment, analyze the corrosion influencing factors, and obtain the corrosion weight values ​​corresponding to different corrosion influencing factors; According to the corrosion monitoring data of the sulfur-containing purification plant in the historical period and the corrosion weight values ​​corresponding to the corrosion influencing factors, combined with the real-time monitoring values ​​of the corrosion influencing factors, the high-risk corrosion points in the sulfur-containing purification plant are identified, and the high-risk corrosion point identification results are obtained.

2. The method for identifying high-risk corrosion points in a sulfur-containing purification plant according to claim 1, characterized in that: Also includes: Obtain the material characteristics corresponding to all working objects corresponding to the corrosion monitoring data, the corrosion mechanism corresponding to the material characteristics, and the corrosion environment.

3. The method for identifying high-risk corrosion points in a sulfur-containing purification plant according to claim 2, characterized in that: According to the process flow, corrosion environment and working object characteristics of the sulfur-containing purification plant, the working objects in the sulfur-containing purification plant are divided into corrosion circuits to obtain multiple corrosion circuits, including: Determine the material characteristics, the corrosion mechanism corresponding to the material characteristics and the working objects with the same corrosion environment in the sulfur-containing purification plant to obtain a set of working objects; the working object characteristics include the material characteristics and the corrosion mechanism corresponding to the material characteristics; All target working objects involved in each process step in the process flow are determined, and the target working objects in the same working object set form a corrosion loop to obtain multiple corrosion loops.

4. The method for identifying high-risk corrosion points in a sulfur-containing purification plant according to claim 1, characterized in that: Determine the corrosion influencing factors of each corrosion circuit in its corrosive environment, including: Obtaining the pre-stored corrosion influencing factors of each corrosion circuit in the corrosion environment in which it is located or receiving the corrosion influencing factors input by the staff through human-computer interaction; Among them, the corrosion influencing factors are determined according to the process characteristics of the purification plant, and the corrosion influencing factors at least include temperature factors, solution acid gas load factors, flow rate factors, solution concentration factors, heat-stable salt type factors and heat-stable salt content factors.

5. The method for identifying high-risk corrosion points in a sulfur-containing purification plant according to claim 4, characterized in that: The corrosion influencing factors are analyzed to obtain the corrosion weight values ​​corresponding to different corrosion influencing factors, including: For the corrosion influencing factors, at least 4 levels are selected for each factor, and indoor evaluation tests are carried out to obtain the corresponding relationship between the corrosion influencing factors and the corrosion rate, and obtain the corrosion rate curve; With the corrosion rate curve as data support, the grey correlation method is used to determine the corrosion weight values ​​corresponding to the corrosion influencing factors corresponding to different corrosion loops.

6. The method for identifying high-risk corrosion points in a sulfur-containing purification plant according to claim 4, characterized in that: According to the corrosion monitoring data of the sulfur purification plant in the historical period and the corrosion weight values ​​corresponding to the corrosion influencing factors, combined with the real-time monitoring values ​​of the corrosion influencing factors, the high-risk corrosion points in the sulfur purification plant are identified, and the high-risk corrosion point identification results are obtained, including: Based on the corrosion monitoring data of the sulfur purification plant in the historical period, the points where the sulfur purification plant has experienced corrosion failure in the historical period are determined as the first corrosion high risk points; Based on the corrosion monitoring data of the sulfur-containing purification plant in the historical period, the corrosion rate of each point in the sulfur-containing purification plant is determined, and the point whose corrosion rate exceeds the preset corrosion rate threshold is determined as the second corrosion high risk point, or the real-time monitoring value of the corrosion influencing factors of each point in the sulfur-containing purification plant is obtained, and the corrosion rate of each point is predicted using a pre-trained deep learning model, and the point whose corrosion rate exceeds the preset corrosion rate threshold is determined as the second corrosion high risk point; The corrosion weight values ​​corresponding to the corrosion influencing factors of each point in the sulfur purification plant are accumulated and calculated to obtain the total corrosion weight value of each point in the sulfur purification plant, and the critical threshold corresponding to the total corrosion weight value is determined according to the second corrosion high risk point, and the point where the total corrosion weight value exceeds the critical threshold is determined as the third corrosion high risk point; The first corrosion high risk point, the second corrosion high risk point and the third corrosion high risk point are taken together as the corrosion high risk point identification results in the sulfur-containing purification plant.

7. The method for identifying high-risk corrosion points in a sulfur-containing purification plant according to claim 6, characterized in that: Also includes: Obtain the corrosion monitoring data of other sulfur-containing purification plants in historical periods, and determine the target points where the corrosion failures in other sulfur-containing purification plants exceed the threshold number of times based on the corrosion monitoring data of other sulfur-containing purification plants; The point in the sulfur-containing purification plant with the same corrosion high risk point as the target point is determined as the fourth corrosion high risk point, and the first corrosion high risk point, the second corrosion high risk point, the third corrosion high risk point and the fourth corrosion high risk point are collectively used as the identification results of the corrosion high risk points in the sulfur-containing purification plant.

8. The method for identifying high-risk corrosion points in a sulfur-containing purification plant according to any one of claims 1 to 7, characterized in that: According to the corrosion monitoring data of the sulfur purification plant in the historical period and the corrosion weight values ​​corresponding to the corrosion influencing factors, combined with the real-time monitoring values ​​of the corrosion influencing factors, after identifying the high-risk corrosion points in the sulfur purification plant, it also includes: Based on the pre-set update cycle, the corrosion monitoring data of the sulfur-containing purification plant in the historical period, the process flow of the sulfur-containing purification plant, the corrosion environment and the characteristics of the work objects are re-acquired after each update cycle, and the high-risk corrosion points are re-identified based on the corrosion monitoring data of the sulfur-containing purification plant in the historical period and the process flow of the sulfur-containing purification plant, thereby completing the update of the high-risk corrosion point identification results.

9. The method for identifying high-risk corrosion points in a sulfur-containing purification plant according to claim 7, characterized in that: Also includes: For the regeneration tower in the sulfur purification plant, the CFD simulation analysis method is used to simulate and analyze the flow field distribution diagram of the regeneration tower; Determine the area with the largest flow field change in the flow field distribution diagram of the regeneration tower as the target area, take the target area as the high-risk corrosion point corresponding to the regeneration tower, and obtain the fifth high-risk point; The first corrosion high risk point, the second corrosion high risk point, the third corrosion high risk point, the fourth corrosion high risk point and the fifth high risk point are taken together as the corrosion high risk point identification results in the sulfur-containing purification plant.

10. The method for identifying high-risk corrosion points in a sulfur-containing purification plant according to claim 8, characterized in that: Also includes: For the reboiler in the sulfur purification plant, the CFD simulation analysis method is used to simulate and analyze the flow field distribution diagram of the reboiler; Determine the area with the largest flow field change in the flow field distribution diagram of the reboiler as the target area, take the target area as the high-risk corrosion point corresponding to the reboiler, and obtain the sixth high-risk point; The first corrosion high risk point, the second corrosion high risk point, the third corrosion high risk point, the fourth corrosion high risk point, the fifth high risk point and the sixth high risk point are taken together as the corrosion high risk point identification results in the sulfur-containing purification plant.

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