Corrosion rate processing method, device, equipment, storage medium and program product

Abstract

The invention relates to a corrosion rate processing method and device, equipment, a storage medium and a program product. The method comprises the following steps: in response to a corrosion rate prediction request for a target material, acquiring corrosion rate associated data of the target material in a sampling period; wherein the corrosion rate associated data comprises a corrosion rate at each sampling moment and factor data of a key environment factor influencing the corrosion rate at each sampling moment; according to the factor data of the key environment factor at each sampling moment, predicting a factor change trend of the key environment factor in a future time period; and determining a target corrosion rate change trend of the target material in the future time period according to the factor change trend of the key environment factor in the future time period and the corrosion rate of each sampling moment. By adopting the method, the corrosion rate can be accurately determined.

Description

Technical Field

[0001] The present application relates to the technical field of corrosion rate monitoring, and in particular to a corrosion rate processing method, device, equipment, storage medium and program product. Background Art

[0002] Corrosion is the phenomenon of material destruction or deterioration caused by environmental factors. It poses a serious threat to the safe operation of key facilities such as industrial equipment and pipelines. Corrosion not only leads to reduced equipment performance and shortened lifespan, but may also cause serious accidents such as leakage and explosion.

[0003] Therefore, real-time monitoring and evaluation of corrosion rate is of great significance for preventing corrosion accidents and ensuring facility safety. Summary of the invention

[0004] Based on this, it is necessary to provide a corrosion rate processing method, device, equipment, storage medium and program product to accurately determine the corrosion rate in response to the above-mentioned technical problems.

[0005] In a first aspect, the present application provides a corrosion rate processing method, the method comprising:

[0006] In response to a corrosion rate prediction request for a target material, obtaining corrosion rate associated data of the target material within a sampling period; wherein the corrosion rate associated data includes the corrosion rate at each sampling moment and factor data of key environmental factors affecting the corrosion rate at each sampling moment;

[0007] According to the factor data of key environmental factors at each sampling time, predict the factor change trend of key environmental factors in the future period;

[0008] According to the factor change trend of key environmental factors in the future period and the corrosion rate at each sampling time, the target corrosion rate change trend of the target material in the future period is determined.

[0009] In one embodiment, determining the target corrosion rate change trend of the target material in the future period according to the factor change trend of the key environmental factor in the future period and the corrosion rate at each sampling time includes:

[0010] According to the corrosion rate at each sampling moment, the initial corrosion rate change trend of the target material in the future period is determined; the factor change trend of the key environmental factors in the future period is used to adjust the initial corrosion rate change trend to obtain the target corrosion rate change trend of the target material in the future period.

[0011] In one embodiment, the factor change trend of the key environmental factor in the future period is used to adjust the initial corrosion rate change trend to obtain the target corrosion rate change trend of the target material in the future period, including:

[0012] The influence weights of each key environmental factor on the corrosion rate of the target material and the factor change trend in the future period are used to adjust the initial corrosion rate change trend to obtain the target corrosion rate change trend of the target material in the future period.

[0013] In one embodiment, it includes:

[0014] Obtain the standard corrosion rate change trend of the target material; determine the maximum trend difference value between the standard corrosion rate change trend and the target corrosion rate change trend; if the maximum trend difference value is greater than a preset threshold, output corrosion warning information for the target material.

[0015] In one embodiment, the key environmental factors are determined by:

[0016] According to the corrosion rate of the target material at each sample time within the sample period and the factor data of each candidate environmental factor affecting the corrosion rate at each sample time, a correlation analysis is performed between the corrosion rate and each candidate environmental factor to determine the influence weight of each candidate environmental factor on the corrosion rate of the target material; according to the influence weight of each candidate environmental factor on the corrosion rate of the target material, the key environmental factor is selected from each candidate environmental factor.

[0017] In one embodiment, it includes:

[0018] After obtaining the corrosion rate monitoring data for the target material from the monitoring equipment of the target material, a target storage method is selected from database storage method, file storage method, object storage method and block storage method according to the material identification of the target material; according to the target storage method, the corrosion rate monitoring data is processed to obtain corrosion rate associated data, and the corrosion rate associated data is stored.

[0019] In a second aspect, the present application also provides a corrosion rate processing device, the device comprising:

[0020] An acquisition module, configured to acquire, in response to a corrosion rate prediction request for a target material, corrosion rate associated data of the target material within a sampling period; wherein the corrosion rate associated data includes the corrosion rate at each sampling moment and factor data of key environmental factors affecting the corrosion rate at each sampling moment;

[0021] The prediction module is used to predict the factor change trend of the key environmental factors in the future period based on the factor data of the key environmental factors at each sampling time;

[0022] The determination module is used to determine the target corrosion rate change trend of the target material in the future period according to the factor change trend of the key environmental factor in the future period and the corrosion rate at each sampling moment.

[0023] In a third aspect, the present application further provides a computer device, including a memory and a processor, wherein the memory stores a computer program, and when the processor executes the computer program, the following steps are implemented:

[0024] In response to a corrosion rate prediction request for a target material, obtaining corrosion rate associated data of the target material within a sampling period; wherein the corrosion rate associated data includes the corrosion rate at each sampling moment and factor data of key environmental factors affecting the corrosion rate at each sampling moment;

[0025] According to the factor data of key environmental factors at each sampling time, predict the factor change trend of key environmental factors in the future period;

[0026] According to the factor change trend of key environmental factors in the future period and the corrosion rate at each sampling time, the target corrosion rate change trend of the target material in the future period is determined.

[0027] In a fourth aspect, the present application further provides a computer-readable storage medium having a computer program stored thereon, wherein when the computer program is executed by a processor, the following steps are implemented:

[0028] In response to a corrosion rate prediction request for a target material, obtaining corrosion rate associated data of the target material within a sampling period; wherein the corrosion rate associated data includes the corrosion rate at each sampling moment and factor data of key environmental factors affecting the corrosion rate at each sampling moment;

[0029] According to the factor data of key environmental factors at each sampling time, predict the factor change trend of key environmental factors in the future period;

[0030] According to the factor change trend of key environmental factors in the future period and the corrosion rate at each sampling time, the target corrosion rate change trend of the target material in the future period is determined.

[0031] In a fifth aspect, the present application further provides a computer program product, including a computer program, which implements the following steps when executed by a processor:

[0032] In response to a corrosion rate prediction request for a target material, obtaining corrosion rate associated data of the target material within a sampling period; wherein the corrosion rate associated data includes the corrosion rate at each sampling moment and factor data of key environmental factors affecting the corrosion rate at each sampling moment;

[0033] According to the factor data of key environmental factors at each sampling time, predict the factor change trend of key environmental factors in the future period;

[0034] According to the factor change trend of key environmental factors in the future period and the corrosion rate at each sampling time, the target corrosion rate change trend of the target material in the future period is determined.

[0035] The above-mentioned corrosion rate processing method, device, equipment, storage medium and program product provide sufficient data for corrosion rate prediction by obtaining the corrosion rate of the target material at each sampling moment within the sampling period and the factor data of the key environmental factors affecting the corrosion rate at each sampling moment; further, according to the factor data of the key environmental factors at each sampling moment, the factor change trend of the key environmental factors in the future time period is predicted, providing data support for the accurate prediction of the corrosion rate; further, according to the factor change trend of the key environmental factors in the future time period and the corrosion rate at each sampling moment, the target corrosion rate change trend of the target material in the future time period can be determined. This scheme provides ideas for determining the target corrosion rate of the target material by introducing key environmental factors; furthermore, by determining the factor change trend of the key environmental factors in the future time period, it provides a data basis for determining the target corrosion rate situation, and finally accurately determines the target corrosion rate change trend of the target material in the future time period. BRIEF DESCRIPTION OF THE DRAWINGS

[0036] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the related technologies, the drawings required for use in the embodiments or the related technical descriptions are briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0037] FIG1 is an application environment diagram of a corrosion rate treatment method provided in an embodiment of the present application;

[0038] FIG2 is a schematic diagram of a corrosion rate treatment process provided in an embodiment of the present application;

[0039] FIG3 is a schematic diagram of a process for determining a change trend of a target corrosion rate provided in an embodiment of the present application;

[0040] FIG4 is a schematic diagram of a process for determining key environmental factors provided in an embodiment of the present application;

[0041] FIG5 is a schematic flow diagram of another corrosion rate treatment method provided in an embodiment of the present application;

[0042] FIG6 is a structural block diagram of a corrosion rate processing device provided in an embodiment of the present application;

[0043] FIG7 is a structural block diagram of another corrosion rate processing device provided in an embodiment of the present application;

[0044] FIG8 is a diagram of the internal structure of a computer device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0045] In order to make the purpose, technical solution and advantages of the present application more clearly understood, the present application is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application.

[0046] The corrosion rate processing method provided in the embodiment of the present application can be applied in the application environment shown in FIG. 1. Among them, the terminal 102 communicates with the server 104 through the network. The data storage system can store the data that the server 104 needs to process. The data storage system can be integrated on the server 104, or it can be placed on the cloud or other network servers. The terminal 102 can send a corrosion rate prediction request for the target material to the server 104; then, for the received corrosion rate prediction request, the server 104 can obtain the corrosion rate associated data of the target material in the sampling period from the data storage system, and analyze and calculate, and finally determine the target corrosion rate change trend of the target material in the future period; further, the server 104 sends the target corrosion rate change trend of the target material in the future period to the terminal 102, and the terminal 102 displays the target corrosion rate change trend. Among them, the terminal 102 can be, but is not limited to, various personal computers, laptops, smart phones, tablets, Internet of Things devices and portable wearable devices, and the Internet of Things devices can be smart speakers, smart TVs, smart air conditioners, smart car-mounted devices, etc. Portable wearable devices can be smart watches, smart bracelets, head-mounted devices, etc. The server 104 may be implemented as an independent server or a server cluster consisting of multiple servers.

[0047] In an exemplary embodiment, as shown in FIG2 , a corrosion rate processing method is provided, which is described by taking the method applied to the server 104 in FIG1 as an example, and may include the following steps:

[0048] S201 , in response to a corrosion rate prediction request for a target material, obtaining corrosion rate associated data of the target material within a sampling period.

[0049] The target material may be any type of material for which the corrosion rate needs to be determined, such as metals, alloys, and plastics; the sampling period may be the period for which the corrosion rate-related data needs to be obtained, such as the past week; the corrosion rate-related data may include but are not limited to the corrosion rate at each sampling time and the factor data of the key environmental factors affecting the corrosion rate at each sampling time. Optionally, the key environmental factors may be at least two of the factors related to the environment, such as temperature, humidity, corrosive gas concentration, and pH.

[0050] It should be noted that the corrosion rate-related data may be monitored in real time or periodically by sensors, and thus the server 104 may receive the monitored corrosion rate-related data and save it in a data storage system.

[0051] For example, after receiving a corrosion rate prediction request for a target material, the server 104 may obtain corrosion rate-related data of the target material during a sampling period from a data storage system, and perform data cleaning and other operations thereon to eliminate invalid, erroneous or duplicate data.

[0052] S202, predicting the factor change trend of the key environmental factors in the future period based on the factor data of the key environmental factors at each sampling time.

[0053] Among them, the factor change trend can be expressed as a relationship curve between the key environmental factor and time, or it can express the change trend of the key environmental factor, such as increase, decrease and fluctuation, as well as the numerical range of the change.

[0054] Exemplarily, the factor data of the key environmental factors at each sampling moment can be input into the factor prediction model, which analyzes the factor data of the key environmental factors at each sampling moment and predicts the factor change trend of the key environmental factors in the future time period.

[0055] It should be noted that the factor prediction model can be built based on statistical methods or machine learning methods, such as trend line method, vector machine, random forest and neural network, so as to capture the long-term trend, short-term trend and cyclical fluctuation characteristics of the data; further, the built model can be trained based on the factor data of key environmental factors at each sample time during the sample period to optimize the parameters of the model and thus achieve the best prediction effect.

[0056] S203, determining the target corrosion rate change trend of the target material in the future period according to the factor change trend of the key environmental factor in the future period and the corrosion rate at each sampling time.

[0057] Among them, the future time period can represent a period of time from now on, and the length of time can be determined according to the properties of the target material, which can be a few days, weeks or months; the target corrosion rate change trend can be expressed as a curve of the relationship between the corrosion rate and time of the predicted target material in the future period, or it can represent the change trend of the corrosion rate, such as increase, decrease and fluctuation, as well as the range of changing values.

[0058] Exemplarily, the factor change trend of the key environmental factor in the future period and the corrosion rate at each sampling time can be input into the corrosion rate model, and the corrosion rate model analyzes the factor change trend of the key environmental factor in the future period and the corrosion rate at each sampling time, and obtains the target corrosion rate change trend of the target material in the future period. Optionally, the corrosion rate model is obtained by training a machine learning algorithm based on data in the sample period.

[0059] The above corrosion rate processing method provides sufficient data for corrosion rate prediction by obtaining the corrosion rate of the target material at each sampling moment within the sampling period and the factor data of the key environmental factors affecting the corrosion rate at each sampling moment; further, based on the factor data of the key environmental factors at each sampling moment, the factor change trend of the key environmental factors in the future period is predicted, providing data support for the accurate prediction of the corrosion rate; further, the target corrosion rate change trend of the target material in the future period can be determined based on the factor change trend of the key environmental factors in the future period and the corrosion rate at each sampling moment. This scheme provides ideas for determining the target corrosion rate of the target material by introducing key environmental factors; furthermore, by determining the factor change trend of the key environmental factors in the future period, it provides a data basis for determining the target corrosion rate situation, and finally accurately determines the target corrosion rate change trend of the target material in the future period.

[0060] Based on the above embodiment, the present embodiment of the present application explains the above embodiment S203 in detail. Specifically, the process of determining the change trend of the target corrosion rate in the present embodiment of the present application, as shown in FIG3, specifically includes the following steps:

[0061] S301, determining the initial corrosion rate change trend of the target material in the future period according to the corrosion rate at each sampling moment.

[0062] The initial corrosion rate variation trend may represent the initial corrosion rate development trend of the target material determined based on the corrosion rate at each sampling moment.

[0063] Exemplarily, the trend of corrosion rate changes over time at each sampling moment can be visualized through a straight line graph or a scatter plot, and information such as whether the corrosion rate of the target material increases, decreases or remains stable can be preliminarily identified; further, based on the corrosion rate at each sampling moment, statistics such as the mean value and standard deviation of the corrosion rate of the target material in the sampling period can be calculated to understand information such as the overall distribution and degree of discreteness of the data; further, the trend of corrosion rate changes can be modeled through methods such as linear regression, nonlinear regression or time series analysis to determine the initial corrosion rate change trend of the target material in the future period.

[0064] S302, using the factor change trend of the key environmental factor in the future period, adjusting the initial corrosion rate change trend, and obtaining the target corrosion rate change trend of the target material in the future period.

[0065] Among them, the number of key environmental factors is at least two.

[0066] One feasible method is to use the weights of the impact of each key environmental factor on the corrosion rate of the target material and the factor change trend in the future period to adjust the initial corrosion rate change trend and obtain the target corrosion rate change trend of the target material in the future period.

[0067] Optionally, the impact weight can reflect the degree and importance of the key environmental factors on the corrosion rate.

[0068] For example, the weight of each key environmental factor on the corrosion rate can be determined by expert scoring, sensitivity analysis, machine learning and other methods; further, the weight of each key environmental factor on the corrosion rate of the target material, the factor change trend of each key environmental factor in the future period, and the initial corrosion rate change trend can be input into the rate adjustment model, and the rate adjustment model analyzes them and obtains the target corrosion rate change trend of the target material in the future period. Among them, the rate adjustment model can be obtained based on data training in the sample period, and the rate adjustment model can be composed of methods such as multiple linear regression, decision tree or neural network.

[0069] Another possible implementation method is that, for any key environmental factor, the factor change trend of the key environmental factor in the future time period can be multiplied by the weight of the key environmental factor's impact on the corrosion rate to obtain the adjusted factor change trend of the key environmental factor in the future time period; further, for each sampling moment in the future time period, the value of the adjusted key environmental factor at the sampling moment in the factor change trend of the future time period can be multiplied by the value of the initial corrosion rate change trend at the sampling moment to finally obtain the target corrosion rate change trend of the target material in the future time period.

[0070] In the embodiment of the present application, by introducing the target corrosion rate change trend of the target material in the future time period, a data basis is provided for adjusting the initial corrosion rate change trend of the target material in the future time period, laying the foundation for accurately determining the target corrosion rate change trend.

[0071] Based on the above-mentioned embodiments, the embodiments of the present application involve a process of determining corrosion warning information based on the target corrosion rate change trend, specifically including: obtaining the standard corrosion rate change trend of the target material; determining the maximum trend difference value between the standard corrosion rate change trend and the target corrosion rate change trend; if the maximum trend difference value is greater than a preset threshold, outputting corrosion warning information for the target material.

[0072] Among them, the standard corrosion rate change trend can indicate the development of the corrosion rate of the target material in the corresponding environment; optionally, the standard corrosion rate change trend can include the corrosion acceleration stage, the corrosion reduction stage and the corrosion flat stage, etc.; the maximum trend difference value can indicate the value with the largest difference in corrosion rate between the standard corrosion rate change trend and the target corrosion rate change trend; the corrosion warning information may include but is not limited to the target corrosion rate chart, the target corrosion rate change trend analysis chart, the dangerous time point, the dangerous corrosion rate value, the corrosion level, the warning level and the recommended measures, etc.

[0073] Exemplarily, a trend analysis can be performed on the standard corrosion rate change trend and the target corrosion rate change trend through statistical tools or data analysis tools to determine the trend components and trend difference values ​​in the standard corrosion rate change trend and the target corrosion rate change trend; further, the maximum trend difference value can be determined from the trend difference value to reflect the degree of deviation of the corrosion performance of the target material under a specific environment from the standard value; further, a reasonable preset threshold value can be pre-set based on factors such as the purpose, importance and corrosion sensitivity of the target material to reflect the safety performance requirements of the target material under a corrosive environment. If the maximum trend difference value is greater than the preset threshold value, it indicates whether the safety of the target material can be guaranteed, and it is necessary to output corrosion warning information for the target material to remind the staff to take corresponding measures.

[0074] In the embodiment of the present application, by introducing the standard corrosion rate change trend, a reference is provided for determining the degree of change of the target corrosion rate change trend, thereby providing a basis for outputting corrosion warning information.

[0075] Based on the above embodiments, the present application embodiment relates to a process of determining key environmental factors, as shown in FIG4 , which specifically includes the following steps:

[0076] S401, based on the corrosion rate of the target material at each sample time within the sample period and the factor data of each candidate environmental factor affecting the corrosion rate at each sample time, a correlation analysis is performed between the corrosion rate and each candidate environmental factor to determine the influence weight of each candidate environmental factor on the corrosion rate of the target material.

[0077] The candidate environmental factors may represent factors in the environment that may affect the corrosion rate of the target material.

[0078] Exemplarily, the correlation value between each candidate environmental factor and the corrosion rate can be determined based on correlation calculation methods such as the Pearson correlation coefficient or the Spearman rank correlation coefficient; further, the influence of each candidate environmental factor on the corrosion rate can be determined based on the correlation value between each candidate environmental factor and the corrosion rate; further, the correlation value between each candidate environmental factor and the corrosion rate can be calculated based on methods such as multivariate regression analysis, principal component analysis or machine learning algorithms, and the influence weight of each candidate environmental factor on the corrosion rate of the target material can be determined.

[0079] S402, selecting a key environmental factor from each candidate environmental factor according to the influence weight of each candidate environmental factor on the corrosion rate of the target material.

[0080] Exemplarily, each candidate environmental factor can be sorted according to the weight of its influence on the corrosion rate of the target material, such as re-sorting each candidate environmental factor in descending order of influence weight, and screening out the candidate environmental factors that have a greater impact on the corrosion rate, such as determining the top 50% of the candidate environmental factors after sorting as key environmental factors.

[0081] In the embodiments of the present application, by introducing impact weights, a basis is provided for screening key environmental factors from candidate environmental factors, thereby laying a foundation for accurately determining the changing trend of the target corrosion rate.

[0082] Based on the above-mentioned embodiments, the embodiments of the present application involve a process of storing corrosion rate associated data, specifically including: after obtaining corrosion rate monitoring data for a target material from a monitoring device of the target material, selecting a target storage method from database storage method, file storage method, object storage method and block storage method according to the material identification of the target material; processing the corrosion rate monitoring data according to the target storage method to obtain corrosion rate associated data, and storing the corrosion rate associated data.

[0083] Among them, the monitoring equipment is a device for monitoring the corrosion rate of the target material, such as sensors; the material identification can indicate the identification of the target material type, which may include but is not limited to metals, alloys and plastics; the database storage method is responsible for storing and managing various structured or unstructured data; the file storage method is a method of organizing and storing data, and the data is stored in the form of files and folders; the object storage method treats data as objects, each object includes the data itself, metadata and a globally unique identifier; the data in the block storage method is divided into fixed-size storage blocks, each block has a unique identifier.

[0084] Exemplarily, a mapping table or rule table of material identification and storage method can be set in advance; then, after determining the material identification of the target material, the storage method of the material identification corresponding to the target material can be queried in the mapping table or rule table; further, based on the queried storage method of the material identification corresponding to the target material, the corrosion rate associated data is stored.

[0085] In the embodiment of the present application, by setting the correspondence between the material identification and the storage method, convenience is provided for data management, thereby speeding up the data processing speed.

[0086] Based on the above embodiment, this embodiment provides an optional example of a corrosion rate processing method. As shown in FIG5 , the specific implementation process is as follows:

[0087] S501 , in response to a corrosion rate prediction request for a target material, obtaining corrosion rate associated data of the target material within a sampling period.

[0088] The corrosion rate correlation data include the corrosion rate at each sampling time and the factor data of the key environmental factors affecting the corrosion rate at each sampling time.

[0089] S502: predicting the factor change trend of the key environmental factors in the future period based on the factor data of the key environmental factors at each sampling time.

[0090] Among them, the number of key environmental factors is at least two.

[0091] Optionally, the key environmental factors are determined in the following manner: based on the corrosion rate of the target material at each sample moment within the sample period and the factor data of each candidate environmental factor affecting the corrosion rate at each sample moment, a correlation analysis is performed on the corrosion rate and each candidate environmental factor to determine the influence weight of each candidate environmental factor on the corrosion rate of the target material; based on the influence weight of each candidate environmental factor on the corrosion rate of the target material, the key environmental factor is selected from each candidate environmental factor.

[0092] S503, determining the initial corrosion rate change trend of the target material in the future period according to the corrosion rate at each sampling moment.

[0093] S504, using the weights of the impact of each key environmental factor on the corrosion rate of the target material and the factor change trend in the future period, the initial corrosion rate change trend is adjusted to obtain the target corrosion rate change trend of the target material in the future period.

[0094] Optionally, obtain the standard corrosion rate change trend of the target material; determine the maximum trend difference value between the standard corrosion rate change trend and the target corrosion rate change trend; if the maximum trend difference value is greater than a preset threshold, output corrosion warning information for the target material.

[0095] Furthermore, after obtaining the corrosion rate monitoring data for the target material from the monitoring equipment of the target material, a target storage method is selected from database storage method, file storage method, object storage method and block storage method according to the material identification of the target material; according to the target storage method, the corrosion rate monitoring data is processed to obtain corrosion rate associated data, and the corrosion rate associated data is stored.

[0096] The specific process of S501-S504 above can refer to the description of the above method embodiment, and its implementation principle and technical effect are similar, which will not be repeated here.

[0097] It should be understood that, although the various steps in the flowcharts involved in the above-mentioned embodiments are displayed in sequence according to the indication of the arrows, these steps are not necessarily executed in sequence according to the order indicated by the arrows. Unless there is a clear explanation in this article, the execution of these steps does not have a strict order restriction, and these steps can be executed in other orders. Moreover, at least a part of the steps in the flowcharts involved in the above-mentioned embodiments can include multiple steps or multiple stages, and these steps or stages are not necessarily executed at the same time, but can be executed at different times, and the execution order of these steps or stages is not necessarily to be carried out in sequence, but can be executed in turn or alternately with other steps or at least a part of the steps or stages in other steps.

[0098] Based on the same inventive concept, the embodiment of the present application also provides a corrosion rate processing device for implementing the corrosion rate processing method involved above. The implementation scheme for solving the problem provided by the device is similar to the implementation scheme recorded in the above method, so the specific limitations in one or more corrosion rate processing device embodiments provided below can refer to the limitations of the corrosion rate processing method above, and will not be repeated here.

[0099] In an exemplary embodiment, as shown in FIG6 , a corrosion rate processing device 1 is provided, comprising: an acquisition module 10, a prediction module 20 and a determination module 30, wherein:

[0100] An acquisition module 10 is used to obtain corrosion rate associated data of the target material within a sampling period in response to a corrosion rate prediction request for the target material; wherein the corrosion rate associated data includes the corrosion rate at each sampling moment and factor data of key environmental factors affecting the corrosion rate at each sampling moment;

[0101] The prediction module 20 is used to predict the factor change trend of the key environmental factor in the future period according to the factor data of the key environmental factor at each sampling time;

[0102] The determination module 30 is used to determine the target corrosion rate change trend of the target material in the future period according to the factor change trend of the key environmental factor in the future period and the corrosion rate at each sampling time.

[0103] In one embodiment, as shown in FIG7 , the determination module 30 specifically further includes:

[0104] The initial determination unit 31 is used to determine the initial corrosion rate change trend of the target material in the future period according to the corrosion rate at each sampling moment.

[0105] The target determination unit 32 is used to adjust the initial corrosion rate change trend by using the factor change trend of the key environmental factor in the future period, so as to obtain the target corrosion rate change trend of the target material in the future period.

[0106] In one embodiment, the target determination unit 32 is further configured to:

[0107] The influence weights of each key environmental factor on the corrosion rate of the target material and the factor change trend in the future period are used to adjust the initial corrosion rate change trend to obtain the target corrosion rate change trend of the target material in the future period.

[0108] In one embodiment, the corrosion rate processing device 1 further comprises:

[0109] The early warning information determination module is used to obtain the standard corrosion rate change trend of the target material; determine the maximum trend difference value between the standard corrosion rate change trend and the target corrosion rate change trend; if the maximum trend difference value is greater than a preset threshold, output corrosion early warning information for the target material.

[0110] In one embodiment, the corrosion rate processing device 1 further comprises:

[0111] The factor selection module is used to perform a correlation analysis between the corrosion rate and each candidate environmental factor based on the corrosion rate of the target material at each sample time within the sample period and the factor data of each candidate environmental factor affecting the corrosion rate at each sample time, so as to determine the influence weight of each candidate environmental factor on the corrosion rate of the target material; according to the influence weight of each candidate environmental factor on the corrosion rate of the target material, a key environmental factor is selected from each candidate environmental factor.

[0112] In one embodiment, the corrosion rate processing device 1 further comprises:

[0113] The storage module is used to obtain the corrosion rate monitoring data for the target material from the monitoring equipment of the target material, and then select a target storage method from database storage method, file storage method, object storage method and block storage method according to the material identification of the target material; according to the target storage method, the corrosion rate monitoring data is processed to obtain corrosion rate related data, and the corrosion rate related data is stored.

[0114] Each module in the corrosion rate processing device can be implemented in whole or in part by software, hardware, or a combination thereof. Each module can be embedded in or independent of a processor in a computer device in the form of hardware, or can be stored in a memory in a computer device in the form of software, so that the processor can call and execute operations corresponding to each module.

[0115] In an exemplary embodiment, a computer device is provided, which may be a server, and its internal structure diagram may be shown in FIG8. The computer device includes a processor, a memory, an input / output interface (Input / Output, referred to as I / O) and a communication interface. The processor, the memory and the input / output interface are connected via a system bus, and the communication interface is connected to the system bus via the input / output interface. The processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program and a database. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The database of the computer device is used to store corrosion rate associated data. The input / output interface of the computer device is used to exchange information between the processor and an external device. The communication interface of the computer device is used to communicate with an external terminal through a network connection. When the computer program is executed by the processor, a corrosion rate processing method is implemented.

[0116] Those skilled in the art will understand that the structure shown in FIG. 8 is merely a block diagram of a partial structure related to the solution of the present application, and does not constitute a limitation on the computer device to which the solution of the present application is applied. The specific computer device may include more or fewer components than shown in the figure, or combine certain components, or have a different arrangement of components.

[0117] In an exemplary embodiment, a computer device is provided, including a memory and a processor, wherein a computer program is stored in the memory, and when the processor executes the computer program, the following steps are implemented:

[0118] In response to a corrosion rate prediction request for a target material, obtaining corrosion rate associated data of the target material within a sampling period; wherein the corrosion rate associated data includes the corrosion rate at each sampling moment and factor data of key environmental factors affecting the corrosion rate at each sampling moment;

[0119] According to the factor data of key environmental factors at each sampling time, predict the factor change trend of key environmental factors in the future period;

[0120] According to the factor change trend of key environmental factors in the future period and the corrosion rate at each sampling time, the target corrosion rate change trend of the target material in the future period is determined.

[0121] In one embodiment, when the processor executes the computer program, the processor further implements the following steps:

[0122] According to the corrosion rate at each sampling moment, the initial corrosion rate change trend of the target material in the future period is determined; the factor change trend of the key environmental factors in the future period is used to adjust the initial corrosion rate change trend to obtain the target corrosion rate change trend of the target material in the future period.

[0123] In one embodiment, when the processor executes the computer program, the processor further implements the following steps:

[0124] The influence weights of each key environmental factor on the corrosion rate of the target material and the factor change trend in the future period are used to adjust the initial corrosion rate change trend to obtain the target corrosion rate change trend of the target material in the future period.

[0125] In one embodiment, when the processor executes the computer program, the processor further implements the following steps:

[0126] Obtain the standard corrosion rate change trend of the target material; determine the maximum trend difference value between the standard corrosion rate change trend and the target corrosion rate change trend; if the maximum trend difference value is greater than a preset threshold, output corrosion warning information for the target material.

[0127] In one embodiment, when the processor executes the computer program, the processor further implements the following steps:

[0128] According to the corrosion rate of the target material at each sample time within the sample period and the factor data of each candidate environmental factor affecting the corrosion rate at each sample time, a correlation analysis is performed between the corrosion rate and each candidate environmental factor to determine the influence weight of each candidate environmental factor on the corrosion rate of the target material; according to the influence weight of each candidate environmental factor on the corrosion rate of the target material, the key environmental factor is selected from each candidate environmental factor.

[0129] In one embodiment, when the processor executes the computer program, the processor further implements the following steps:

[0130] After obtaining the corrosion rate monitoring data for the target material from the monitoring equipment of the target material, a target storage method is selected from database storage method, file storage method, object storage method and block storage method according to the material identification of the target material; according to the target storage method, the corrosion rate monitoring data is processed to obtain corrosion rate associated data, and the corrosion rate associated data is stored.

[0131] In one embodiment, a computer readable storage medium is provided, on which a computer program is stored, and when the computer program is executed by a processor, the following steps are implemented:

[0132] In response to a corrosion rate prediction request for a target material, obtaining corrosion rate associated data of the target material within a sampling period; wherein the corrosion rate associated data includes the corrosion rate at each sampling moment and factor data of key environmental factors affecting the corrosion rate at each sampling moment;

[0133] According to the factor data of key environmental factors at each sampling time, predict the factor change trend of key environmental factors in the future period;

[0134] According to the factor change trend of key environmental factors in the future period and the corrosion rate at each sampling time, the target corrosion rate change trend of the target material in the future period is determined.

[0135] In one embodiment, when the computer program is executed by a processor, the following steps are also implemented:

[0136] According to the corrosion rate at each sampling moment, the initial corrosion rate change trend of the target material in the future period is determined; the factor change trend of the key environmental factors in the future period is used to adjust the initial corrosion rate change trend to obtain the target corrosion rate change trend of the target material in the future period.

[0137] In one embodiment, when the computer program is executed by a processor, the following steps are also implemented:

[0138] The influence weights of each key environmental factor on the corrosion rate of the target material and the factor change trend in the future period are used to adjust the initial corrosion rate change trend to obtain the target corrosion rate change trend of the target material in the future period.

[0139] In one embodiment, when the computer program is executed by a processor, the following steps are also implemented:

[0140] Obtain the standard corrosion rate change trend of the target material; determine the maximum trend difference value between the standard corrosion rate change trend and the target corrosion rate change trend; if the maximum trend difference value is greater than a preset threshold, output corrosion warning information for the target material.

[0141] In one embodiment, when the computer program is executed by a processor, the following steps are also implemented:

[0142] According to the corrosion rate of the target material at each sample time within the sample period and the factor data of each candidate environmental factor affecting the corrosion rate at each sample time, a correlation analysis is performed between the corrosion rate and each candidate environmental factor to determine the influence weight of each candidate environmental factor on the corrosion rate of the target material; according to the influence weight of each candidate environmental factor on the corrosion rate of the target material, the key environmental factor is selected from each candidate environmental factor.

[0143] In one embodiment, when the computer program is executed by a processor, the following steps are also implemented:

[0144] After obtaining the corrosion rate monitoring data for the target material from the monitoring equipment of the target material, a target storage method is selected from database storage method, file storage method, object storage method and block storage method according to the material identification of the target material; according to the target storage method, the corrosion rate monitoring data is processed to obtain corrosion rate associated data, and the corrosion rate associated data is stored.

[0145] In one embodiment, a computer program product is provided, comprising a computer program, which, when executed by a processor, implements the following steps:

[0146] In response to a corrosion rate prediction request for a target material, obtaining corrosion rate associated data of the target material within a sampling period; wherein the corrosion rate associated data includes the corrosion rate at each sampling moment and factor data of key environmental factors affecting the corrosion rate at each sampling moment;

[0147] According to the factor data of key environmental factors at each sampling time, predict the factor change trend of key environmental factors in the future period;

[0148] According to the factor change trend of key environmental factors in the future period and the corrosion rate at each sampling time, the target corrosion rate change trend of the target material in the future period is determined.

[0149] In one embodiment, when the computer program is executed by a processor, the following steps are also implemented:

[0150] According to the corrosion rate at each sampling moment, the initial corrosion rate change trend of the target material in the future period is determined; the factor change trend of the key environmental factors in the future period is used to adjust the initial corrosion rate change trend to obtain the target corrosion rate change trend of the target material in the future period.

[0151] In one embodiment, when the computer program is executed by a processor, the following steps are also implemented:

[0152] The influence weights of each key environmental factor on the corrosion rate of the target material and the factor change trend in the future period are used to adjust the initial corrosion rate change trend to obtain the target corrosion rate change trend of the target material in the future period.

[0153] In one embodiment, when the computer program is executed by a processor, the following steps are also implemented:

[0154] Obtain the standard corrosion rate change trend of the target material; determine the maximum trend difference value between the standard corrosion rate change trend and the target corrosion rate change trend; if the maximum trend difference value is greater than a preset threshold, output corrosion warning information for the target material.

[0155] In one embodiment, when the computer program is executed by a processor, the following steps are also implemented:

[0156] According to the corrosion rate of the target material at each sample time within the sample period and the factor data of each candidate environmental factor affecting the corrosion rate at each sample time, a correlation analysis is performed between the corrosion rate and each candidate environmental factor to determine the influence weight of each candidate environmental factor on the corrosion rate of the target material; according to the influence weight of each candidate environmental factor on the corrosion rate of the target material, the key environmental factor is selected from each candidate environmental factor.

[0157] In one embodiment, when the computer program is executed by a processor, the following steps are also implemented:

[0158] After obtaining the corrosion rate monitoring data for the target material from the monitoring equipment of the target material, a target storage method is selected from database storage method, file storage method, object storage method and block storage method according to the material identification of the target material; according to the target storage method, the corrosion rate monitoring data is processed to obtain corrosion rate associated data, and the corrosion rate associated data is stored.

[0159] It should be noted that the information (including but not limited to target material information, etc.) and data (including but not limited to data used for analysis, stored data, displayed data, etc.) involved in this application are all information and data fully authorized by all parties, and the collection, use and processing of relevant data must comply with relevant regulations.

[0160] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to the memory, database or other medium used in the embodiments provided in this application can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetoresistive random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. As an illustration and not limitation, RAM can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM). The database involved in each embodiment provided in this application may include at least one of a relational database and a non-relational database. Non-relational databases may include distributed databases based on blockchains, etc., but are not limited to this. The processor involved in each embodiment provided in this application may be a general-purpose processor, a central processing unit, a graphics processor, a digital signal processor, a programmable logic device, a data processing logic device based on quantum computing, etc., but are not limited to this.

[0161] The technical features of the above embodiments may be arbitrarily combined. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0162] The above-described embodiments only express several implementation methods of the present application, and the descriptions thereof are relatively specific and detailed, but they cannot be construed as limiting the scope of the present application. It should be noted that, for a person of ordinary skill in the art, several modifications and improvements can be made without departing from the concept of the present application, and these all belong to the protection scope of the present application. Therefore, the protection scope of the present application shall be subject to the attached claims.

Claims

1. A corrosion rate processing method, characterized in that: The method comprises: In response to a corrosion rate prediction request for a target material, obtaining corrosion rate associated data of the target material within a sampling period; wherein the corrosion rate associated data includes the corrosion rate at each sampling moment and factor data of key environmental factors affecting the corrosion rate at each sampling moment; According to the factor data of the key environmental factor at each sampling time, predict the factor change trend of the key environmental factor in the future period; According to the factor variation trend of the key environmental factor in the future period and the corrosion rate at each sampling moment, the target corrosion rate variation trend of the target material in the future period is determined.

2. The method according to claim 1, characterized in that Determining the target corrosion rate change trend of the target material in the future period according to the factor change trend of the key environmental factor in the future period and the corrosion rate at each sampling time includes: Determine the initial corrosion rate change trend of the target material in the future period according to the corrosion rate at each sampling moment; The factor change trend of the key environmental factor in the future period is used to adjust the initial corrosion rate change trend to obtain the target corrosion rate change trend of the target material in the future period.

3. The method according to claim 2, characterized in that The number of the key environmental factors is at least two; The method of using the factor change trend of the key environmental factor in the future period to adjust the initial corrosion rate change trend to obtain the target corrosion rate change trend of the target material in the future period includes: The initial corrosion rate change trend is adjusted by using the influence weights of each key environmental factor on the corrosion rate of the target material and the factor change trend in the future period to obtain the target corrosion rate change trend of the target material in the future period.

4. The method according to claim 1, characterized in that: The method further comprises: Obtaining a standard corrosion rate variation trend of the target material; Determining a maximum trend difference value between the standard corrosion rate change trend and the target corrosion rate change trend; If the maximum trend difference value is greater than a preset threshold, corrosion warning information for the target material is output.

5. The method according to claim 1, characterized in that The key environmental factors are determined by: According to the corrosion rate of the target material at each sample time within the sample period and the factor data of each candidate environmental factor affecting the corrosion rate at each sample time, a correlation analysis is performed between the corrosion rate and each candidate environmental factor to determine the influence weight of each candidate environmental factor on the corrosion rate of the target material; The key environmental factor is selected from the candidate environmental factors according to the influence weight of each candidate environmental factor on the corrosion rate of the target material.

6. The method according to claim 1, characterized in that The method further comprises: After obtaining the corrosion rate monitoring data for the target material from the monitoring device of the target material, a target storage method is selected from a database storage method, a file storage method, an object storage method and a block storage method according to the material identification of the target material; According to the target storage method, the corrosion rate monitoring data is processed to obtain corrosion rate associated data, and the corrosion rate associated data is stored.

7. A corrosion rate processing device, characterized in that: The device comprises: An acquisition module, configured to acquire, in response to a corrosion rate prediction request for a target material, corrosion rate associated data of the target material within a sampling period; wherein the corrosion rate associated data includes the corrosion rate at each sampling moment and factor data of key environmental factors affecting the corrosion rate at each sampling moment; A prediction module, used to predict the factor change trend of the key environmental factor in a future period according to the factor data of the key environmental factor at each sampling moment; The determination module is used to determine the target corrosion rate change trend of the target material in the future period according to the factor change trend of the key environmental factor in the future period and the corrosion rate at each sampling moment.

8. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 6 are implemented.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 6 are implemented.

10. A computer program product, comprising a computer program, characterized in that When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 6 are implemented.

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