CN112633540A

CN112633540A - Intelligent corrosion early warning method and early warning system for oil refining static equipment

Info

Publication number: CN112633540A
Application number: CN201910895157.8A
Authority: CN
Inventors: 陈文武; 韩磊; 屈定荣
Original assignee: China Petroleum and Chemical Corp; Sinopec Qingdao Safety Engineering Institute
Current assignee: China Petroleum and Chemical Corp; Sinopec Qingdao Safety Engineering Institute
Priority date: 2019-09-20
Filing date: 2019-09-20
Publication date: 2021-04-09

Abstract

The invention relates to the technical field of petrochemical corrosion protection, and discloses an intelligent corrosion early warning method and an intelligent corrosion early warning system for oil refining static equipment, wherein the corrosion early warning method comprises the following steps: acquiring corrosion related data of a plurality of static oil refining equipment, drawing a dynamic corrosion loop diagram of the static oil refining equipment according to the corrosion related data, and marking corrosion parts of the static oil refining equipment in the dynamic corrosion loop diagram; establishing a corrosion prediction model aiming at each corrosion part of the oil refining static equipment; processing the corrosion-related data based on a corrosion prediction model to obtain corrosion prediction data for each corrosion site; and correlating the corrosion prediction data corresponding to each corrosion part with the corresponding corrosion part to carry out corrosion early warning. The method and the device can acquire relevant data of the plurality of oil refining static devices in real time, draw a dynamic corrosion loop diagram of the oil refining static devices, mark corrosion positions, establish a corrosion model and perform corrosion early warning, and can effectively improve the accuracy and timeliness of the corrosion early warning of the oil refining static devices.

Description

Intelligent corrosion early warning method and early warning system for oil refining static equipment

Technical Field

The invention relates to the technical field of petrochemical corrosion protection, in particular to an intelligent corrosion early warning method and an intelligent corrosion early warning system for oil refining static equipment.

Background

In recent years, the import of crude oil processed in the petrochemical industry of China is greatly increased, the crude oil is continuously degraded, and heavy, high-sulfur and high-acid crude oil becomes a main oil type processed by an oil refining device. Feedstock degradation presents a significant corrosion risk to the primary refinery equipment. The static oil refining equipment is equipment which is in a static state after being installed (namely, equipment which does not need power transmission in the production operation process), is widely applied to various process processes such as mass transfer, heat transfer, medium heating, chemical reaction and the like in production and stored materials, is easily corroded by the influence of high temperature, high sulfur, high acid, dew point and the like, accounts for a large proportion in five types of oil refining devices (atmospheric and vacuum, catalytic cracking, delayed coking, hydrofining and hydrocracking devices), and the five types of devices are oil refining devices with the highest corrosion risk in the oil refining devices, so that the corrosion risk early warning of the static oil refining equipment is very important, the static oil refining equipment can be well controlled in corrosion risk, and the equipment corrosion risk of oil refining enterprises can be basically guaranteed to be controllable.

Although the anticorrosion technology of the oil refining equipment is greatly developed in recent years, the anticorrosion technology of the oil refining static equipment is also greatly improved, the corrosion early warning of the equipment usually depends on a single data source and a simple fixed threshold range to carry out corrosion early warning on the equipment, and the problems that the acquisition of physical and chemical parameters for corroding the oil refining device is not comprehensive enough and has weak pertinence, a plurality of single-point technologies exist, a plurality of information islands exist and the like exist. Particularly for the oil refining static equipment, the corrosion protection related work of the oil refining static equipment is completed mainly by depending on a large amount of technical reserves and rich experience of equipment maintenance personnel.

Disclosure of Invention

In order to solve the technical problems and at least partially solve the technical problems, an embodiment of the invention provides an intelligent corrosion early warning method for oil refining static equipment.

According to a first aspect of the embodiment of the invention, an intelligent corrosion early warning method for oil refining static equipment is provided, and the intelligent corrosion early warning method for oil refining static equipment comprises the following steps: acquiring corrosion related data of a plurality of oil refining static equipment; drawing a dynamic corrosion loop diagram of the static oil refining equipment according to the corrosion related data, and marking a corrosion part of the static oil refining equipment in the dynamic corrosion loop diagram; establishing a corrosion prediction model aiming at each corrosion part of the oil refining static equipment; processing the corrosion-related data based on the corrosion prediction model to obtain corrosion prediction data for each corrosion site; and correlating the corrosion prediction data corresponding to each corrosion part with the corrosion part marked by the dynamic corrosion loop diagram to carry out corrosion early warning.

Preferably, the corrosion-related data includes equipment basic data and production analysis data of the oil refining static equipment; wherein the device grounding data comprises one or more of the following parameters: equipment design temperature, equipment design pressure, equipment original wall thickness, equipment off-line thickness measurement data and equipment material; and the production analysis data comprises production data of the oil refining static equipment, analysis data of a laboratory information management system and corrosion on-line monitoring data.

Preferably, the step of marking the corrosion site of the oil refining static equipment in the dynamic corrosion loop diagram comprises the following steps: determining the equipment type of the oil refining static equipment, and dividing the dynamic corrosion loop diagram into a plurality of corrosion loops based on corrosion mechanisms corresponding to different equipment types; marking corrosion positions of the refining static equipment in the corrosion loop according to a first characteristic and a second characteristic, wherein the equipment categories comprise an atmospheric and vacuum distillation unit, a catalytic cracking unit, a delayed coking unit, a hydrofining unit and a hydrocracking unit; the first characteristic is used for indicating corrosion mechanisms corresponding to different corrosion loops, and the second characteristic is used for indicating corrosion related data of each corrosion part.

Preferably, the processing the corrosion-related data based on the corrosion prediction model to obtain corrosion prediction data for each corrosion site comprises: if the part in the corrosion loop is a high-temperature part which has a temperature higher than a preset temperature and has a high-temperature sulfur and naphthenic acid corrosion mechanism, inputting production analysis data of the oil refining static equipment corresponding to the high-temperature part into a high-temperature sulfur and naphthenic acid corrosion prediction model to obtain high-temperature prediction data; if the part in the corrosion loop is an atmospheric tower top part with an ammonium salt crystallization corrosion mechanism, inputting production analysis data of the oil refining static equipment corresponding to the atmospheric tower top part into an ammonium salt crystallization corrosion prediction model to obtain atmospheric tower top prediction data; if the part in the corrosion loop is a fractionating tower top part with a low-temperature dew point corrosion mechanism, inputting the production analysis data of the oil refining static equipment corresponding to the fractionating tower top part into a fractionating tower top low-temperature corrosion prediction model to obtain fractionating tower top prediction data; if the part in the corrosion loop is a sulfur-containing part with a sulfur-containing sewage erosion corrosion mechanism, inputting production analysis data of the oil refining static equipment corresponding to the sulfur-containing part into a sulfur-containing sewage erosion prediction model to obtain prediction data corresponding to the part; and if the part in the corrosion loop is the high-temperature part, the atmospheric tower top part, the fractionating tower top part and other parts except the sulfur-containing part, inputting the production analysis data of the oil refining static equipment corresponding to the part into a corrosion prediction model matched with the mechanism of the part to obtain corrosion prediction data aiming at the part.

Preferably, the associating the corrosion prediction data corresponding to each corrosion site with the corrosion site marked by the dynamic corrosion loop diagram to perform corrosion early warning includes: setting an alarm threshold of the corrosion part of the oil refining static equipment according to the corrosion prediction model, and dividing the corrosion risk grade of the oil refining static equipment according to the set alarm threshold; determining the corrosion risk level of the corrosion position marked in the dynamic corrosion loop diagram according to the divided corrosion risk level, the corrosion related data of the oil refining static equipment corresponding to the corrosion position marked in the dynamic corrosion loop diagram and the corrosion prediction data; and marking a corrosion position of the oil refining static equipment in the corrosion loop by using a third characteristic so as to carry out corrosion early warning on the oil refining static equipment according to the determined corrosion risk level, wherein the third characteristic is used for indicating the corrosion risk level of the corrosion position.

According to a second aspect of the embodiments of the present invention, there is provided an intelligent corrosion early warning system for oil refining static equipment, the intelligent corrosion early warning system for oil refining static equipment includes: the acquisition unit is used for acquiring corrosion related data of a plurality of oil refining static equipment; the marking unit is used for drawing a dynamic corrosion loop diagram of the static oil refining equipment according to the corrosion related data and marking a corrosion part of the static oil refining equipment in the dynamic corrosion loop diagram; the modeling unit is used for establishing a corrosion prediction model aiming at each corrosion part of the oil refining static equipment; a prediction unit for processing the corrosion-related data based on the corrosion prediction model to obtain corrosion prediction data for each corrosion site; and the early warning unit is used for associating the corrosion prediction data corresponding to each corrosion part with the corrosion part marked by the dynamic corrosion loop diagram so as to carry out corrosion early warning.

The corrosion related data comprises equipment basic data and production analysis data of the oil refining static equipment; wherein the device grounding data comprises one or more of the following parameters: equipment design temperature, equipment design pressure, equipment original wall thickness, equipment off-line thickness measurement data and equipment material; and the production analysis data comprises the production data of the oil refining static equipment, analysis data of a laboratory information management system and corrosion on-line monitoring data.

The labeling unit includes: the loop dividing subunit is used for determining the equipment type to which the oil refining static equipment belongs and dividing the dynamic corrosion loop diagram into a plurality of corrosion loops based on corrosion mechanisms corresponding to different equipment types; and a labeling subunit, configured to label, in the corrosion loop, a corrosion site of the quiet oil refining equipment according to a first characteristic and a second characteristic, where the equipment categories include an atmospheric and vacuum distillation unit, a catalytic cracking unit, a delayed coking unit, a hydrorefining unit, and a hydrocracking unit; the first characteristic is used for indicating corrosion mechanisms corresponding to different corrosion loops, and the second characteristic is used for indicating corrosion related data of each corrosion part.

The prediction unit includes: an etching mechanism confirming subunit for confirming that a position in the etching loop is one of the following: a high temperature part with a temperature above a preset temperature and a high temperature sulfur and naphthenic acid corrosion mechanism; an atmospheric overhead portion having an ammonium salt crystallization corrosion mechanism; a fractionation overhead portion having a low temperature dew point corrosion mechanism; a sulfur-containing site having a mechanism of scouring corrosion of sulfur-containing wastewater; and said high temperature portion, said atmospheric overhead portion, said fractionation overhead portion, and other portions other than said sulfur-containing portion; the prediction subunit is used for inputting the production and analysis data of the oil refining static equipment corresponding to the high-temperature part into a high-temperature sulfur and naphthenic acid corrosion prediction model to obtain high-temperature prediction data when the part in the corrosion loop is determined to be the high-temperature part with the temperature above the preset temperature and a high-temperature sulfur and naphthenic acid corrosion mechanism; when the part in the corrosion loop is determined to be an atmospheric tower top part with an ammonium chloride crystallization and dew point corrosion mechanism, inputting production analysis data of the oil refining static equipment corresponding to the atmospheric tower top part into an ammonium chloride crystallization and dew point corrosion prediction model to obtain atmospheric tower top prediction data; when the part in the corrosion loop is a fractionating tower top part with a low-temperature dew point corrosion mechanism, inputting the production analysis data of the oil refining static equipment corresponding to the fractionating tower top part into a fractionating tower top low-temperature corrosion prediction model to obtain fractionating tower top prediction data; when the part in the corrosion loop is a sulfur-containing part with a sulfur-containing sewage erosion corrosion mechanism, inputting production analysis data of the oil refining static equipment corresponding to the sulfur-containing part into a sulfur-containing sewage erosion prediction model to obtain prediction data corresponding to the part; and inputting the production analysis data of the refinery static equipment corresponding to the part into a corrosion prediction model matched with the part to obtain corrosion prediction data aiming at the part when the part in the corrosion loop is confirmed to be the high-temperature part, the atmospheric tower top, the fractionating tower top and other parts except the sulfur-containing part.

Preferably, the early warning unit includes: the corrosion risk classification subunit is used for setting an alarm threshold of a corrosion part of the oil refining static equipment according to the corrosion prediction model and performing corrosion risk classification on the oil refining static equipment according to the set alarm threshold; a corrosion risk determining subunit, configured to determine, according to the divided corrosion risk levels, the corrosion related data of the oil refining static equipment corresponding to the corrosion site marked in the dynamic corrosion loop diagram, and the corrosion prediction data, a corrosion risk level of the corrosion site marked in the dynamic corrosion loop diagram; and the early warning subunit is used for marking a corrosion part of the oil refining static equipment in the corrosion loop by using a third characteristic so as to carry out corrosion early warning on the oil refining static equipment according to the determined corrosion risk level, wherein the third characteristic is used for indicating the corrosion risk level of the corrosion part.

According to a third aspect of the embodiments of the present invention, there is provided a machine-readable storage medium, on which instructions are stored, the instructions being configured to enable the machine-readable storage medium to execute the above-mentioned smart corrosion early warning method for oil refining static equipment.

According to the technical scheme, the dynamic corrosion loop diagram of the static oil refining equipment is drawn according to the acquired relevant data of the plurality of static oil refining equipment, the corrosion positions of the static oil refining equipment are labeled, a corrosion prediction model for each corrosion position is established, and the accuracy of equipment corrosion early warning is continuously improved through data comparison among the plurality of equipment.

Additional features and advantages of embodiments of the invention will be set forth in the detailed description which follows.

Drawings

The accompanying drawings, which are included to provide a further understanding of the embodiments of the invention and are incorporated in and constitute a part of this specification, illustrate embodiments of the invention and together with the description serve to explain the embodiments of the invention without limiting the embodiments of the invention.

Fig. 1 is a flowchart of an intelligent corrosion early warning method for oil refining static equipment according to an embodiment of the present invention;

FIG. 2 is a schematic diagram of a dynamic corrosion loop of a hydrogenation apparatus according to an embodiment of the present invention;

FIG. 3 is a schematic diagram of a dynamic corrosion loop of an atmospheric and vacuum distillation apparatus according to an embodiment of the present invention;

FIG. 4 is a dynamic corrosion loop diagram of a catalytic cracking unit according to an embodiment of the present invention;

FIG. 5 is a schematic diagram of a delayed coker dynamic corrosion loop according to one embodiment of the present invention;

fig. 6 is an intelligent corrosion early warning matrix diagram of the oil refining static equipment provided by the second embodiment of the invention;

FIG. 7 is a block diagram of an intelligent corrosion warning system for oil refining static equipment according to a third embodiment of the present invention;

FIG. 8 is a block diagram of a labeling unit of the intelligent corrosion warning system for oil refining static equipment according to the fourth embodiment of the present invention;

FIG. 9 is a block diagram of a prediction unit of the intelligent corrosion warning system for oil refining static equipment according to the fifth embodiment of the present invention;

FIG. 10 is a block diagram of an early warning unit of the intelligent corrosion early warning system for oil refining static equipment according to a sixth embodiment of the present invention;

fig. 11 is a network architecture diagram of an intelligent corrosion early warning system for oil refining static equipment according to a seventh embodiment of the present invention; and

fig. 12 is an architecture diagram of an application example of the intelligent corrosion early warning system for oil refining static equipment according to an eighth embodiment of the present invention.

Description of the reference numerals

1. Acquisition unit 2 and labeling unit

3. Modeling unit 4 and prediction unit

5. Early warning unit 21 and loop dividing subunit

22. Standard subunit 41 and corrosion mechanism confirming subunit

42. Prediction subunit 51, corrosion risk partitioning subunit

52. Corrosion risk confirming subunit 53 and early warning subunit

Detailed Description

The following detailed description of embodiments of the invention refers to the accompanying drawings. It should be understood that the detailed description and specific examples, while indicating embodiments of the invention, are given by way of illustration and explanation only, not limitation.

Example one

Fig. 1 is a flowchart of an intelligent corrosion early warning method for oil refining static equipment according to an embodiment of the present invention, and as shown in fig. 1, the method may include the following steps:

s100, obtaining corrosion related data of a plurality of oil refining static devices.

In particular, the oil refining static equipment is widely applied to various process procedures such as mass transfer, heat transfer, medium heating, chemical reaction and the like in production and stored materials, so that the equipment is influenced by various factors such as temperature, pH value and the like in the production process. Therefore, in order to warn the corrosion of the refinery equipment, the basic data of the equipment and the data in the production process need to be comprehensively analyzed.

In addition, because corrosion of the oil refining static equipment in the actual production process is influenced by various factors, most of the corrosion early warning systems for the oil refining static equipment in the prior art directly set a corrosion early warning threshold value for a certain oil refining static equipment according to equipment corrosion parameters in national or industrial standards (such as API571-2003 oil refining equipment damage mechanism), do not comprehensively consider production analysis data of the oil refining static equipment in the actual production process, do not comprehensively analyze data for monitoring and analyzing the oil refining static equipment by utilizing various ways (such as production data of the oil refining static equipment, LIMS (Laboratory Information Management System) analysis data and corrosion on-line monitoring data), and do not comprehensively analyze data of a plurality of oil refining static equipment among a plurality of companies in an enterprise or among a plurality of companies in the same industry, therefore, the early warning method for analyzing the corrosion of the equipment and setting the corrosion early warning threshold only aiming at the data and the national or industrial standard in the production process of a certain oil refining static equipment has great limitation. Therefore, the factors are comprehensively considered in the embodiment of the invention, the corrosion early warning model which is more matched with the actual production condition of the static oil refining equipment is constructed by acquiring the corrosion related data of the static oil refining equipment of a plurality of branch companies of an enterprise and processing the data, the corrosion early warning is carried out on the static oil refining equipment, and the timeliness and the accuracy of the corrosion early warning on the static oil refining equipment are improved.

Preferably, the corrosion-related data includes equipment basic data and production analysis data for each refinery apparatus. Wherein the device grounding data comprises one or more of the following parameters: equipment design temperature, equipment design pressure, equipment off-line thickness measurement data and equipment material. The production analysis data includes production data of the refinery static equipment, LIMS (Laboratory Information Management System) analysis data, and corrosion on-line monitoring data.

For example, the basic data of the equipment is determined when the equipment leaves the factory, and may be imported into the intelligent corrosion risk early warning system of the oil refining static equipment in a form of a table, for example, the machine account data of the equipment including a large amount of information (such as the number of the equipment pipeline included in the equipment, the design/operation temperature, the pressure, the specification and size, the material, the commissioning time, and the like) is directly imported into the system.

The production analysis data is obtained in real time through a developed isomerization interface, and the developed isomerization interface is mainly used for synchronously obtaining data monitored by a plurality of branch companies of an enterprise or a plurality of monitoring devices among different enterprises and obtaining the production analysis data aiming at a plurality of oil refining static devices in real time through different ways. The production data of the oil refining static equipment mainly refers to data such as real-time temperature of the equipment, pH value of stored materials in the equipment, pressure in the equipment and the like in the production process. The LIMS is an information management tool that combines an information technology with a database as a core and a laboratory management requirement, and LIMS analysis data refers to a result obtained by analyzing data for a plurality of oil refining static devices. The corrosion on-line monitoring data is obviously that the oil refining static equipment is monitored on line to obtain data such as real-time wall thickness of the equipment.

Preferably, although corrosion of the refinery equipment is a relatively serious problem, the corrosion degree of the equipment will not change greatly in a moment in general, and the corrosion process is a day-by-day and month-by-month process, so that production analysis data of the refinery equipment can be obtained at certain time intervals (for example, 5 minutes, 30 minutes, 1 hour, 2 hours, etc.), but production analysis data of the refinery equipment can also be obtained in real time for timeliness and accuracy of corrosion early warning, which is not limited in the embodiment of the present invention.

And S200, drawing a dynamic corrosion loop diagram, and marking a corrosion part.

Specifically, a dynamic corrosion loop diagram of the oil refining static equipment is drawn according to the corrosion related data, and the corrosion position of the oil refining static equipment is marked in the dynamic corrosion loop diagram.

Preferably, the equipment type of the oil refining static equipment is determined firstly, and the dynamic corrosion loop diagram is divided into a plurality of corrosion loops based on corrosion mechanisms corresponding to different equipment types; marking the corrosion part of the static oil refining equipment in a corrosion loop according to a first characteristic and a second characteristic, wherein the equipment comprises an atmospheric and vacuum distillation unit, a catalytic cracking unit, a delayed coking unit, a hydrofining unit and a hydrocracking unit; the first characteristic is used for indicating corrosion mechanisms corresponding to different corrosion loops, and the second characteristic is used for indicating corrosion related data of each corrosion part.

Specifically, a plurality of corrosion loops are drawn according to corrosion mechanisms on the flow chart of the oil refining static equipment device, and the corresponding corrosion mechanisms (such as high-temperature oxidation, high-temperature vulcanization, ammonium chloride corrosion and naphthenic acid corrosion) are noted. The corrosion loop of the device and the pipeline is embedded into the corrosion flow analysis, a high corrosion risk part is calibrated for a refining enterprise, a corrosion monitoring and detecting scheme is provided for the part, and the method has great practical significance.

For example, a corrosion loop is a localized region of a plant (e.g., a hydrotreater, an atmospheric and vacuum unit, a catalytic cracker, a delayed coker) having the same or similar materials, process conditions, and media environments, and thus having the same corrosion mechanism. After the corrosion loop is divided, the corrosion loop can be uniformly processed by adopting the same corrosion model or evaluation method, and the specific pipeline or equipment in the loop is not processed independently. For example: fig. 2 is a dynamic corrosion loop diagram of a hydrogenation unit provided in an embodiment of the present invention, fig. 3 is a dynamic corrosion loop diagram of an atmospheric and vacuum distillation unit provided in an embodiment of the present invention, fig. 4 is a dynamic corrosion loop diagram of a catalytic cracking unit provided in an embodiment of the present invention, and fig. 5 is a dynamic corrosion loop diagram of a delayed coking unit provided in an embodiment of the present invention.

When the corrosion loop is divided, firstly, the dynamic corrosion loop diagram is divided according to a corrosion mechanism determined by API571-2003 refinery equipment damage mechanism. 66 damage mechanisms are divided in API571-2003 refinery equipment damage mechanism, and 26 damage mechanisms closely related to delaying corrosion of static refining equipment are screened out in the embodiment of the invention and are used as bases for dividing a corrosion loop according to the corrosion mechanism, so that the corrosion loop is divided. Secondly, marking the relevant corrosion data of each part in the oil refining corrosion loop,

specifically, different numbers may be used to mark the possible corrosion mechanism (e.g. represented by circled number characters (i.e. 101, 102, 201, 202) and the corresponding corrosion related data (e.g. represented by pure numbers including no letters, special symbols, etc.) at a certain position or corrosion loop. The corrosion mechanism and the corrosion related data corresponding to each corrosion part are based on data which are needed for analyzing the corrosion risk of the part and can be obtained in a practical and feasible mode (such as importing or online obtaining), the obtained data are imported into the intelligent corrosion early warning system in a table form, and then the corrosion mechanism and the related data corresponding to each part of the oil refining static equipment are obtained in an automatic table look-up mode.

For example: the circled numeric characters marked in fig. 2-5 indicate the corrosion mechanism of each part in the corrosion loop. The pure numbers marked in fig. 2-5, which do not contain letters, special symbols, etc., represent the corresponding corrosion-related data for the corrosion site of the corrosion loop. The corrosion mechanism and the corrosion related data of each part can be obtained by looking up the table according to the number marked in the corrosion loop diagram.

Table 1 shows the 26 damage mechanisms screened out in the present example that are closely related to the retardation of refinery quiet plant corrosion. For example: "I, high temperature Sulfur Corrosion" means that the part marked with "I" has a high temperature Sulfur Corrosion mechanism.

It should be noted that, in the embodiment of the present invention, a table representing the corrosion mechanism of different types of apparatuses in the static oil refining equipment (for example, a hydrogenation apparatus, an atmospheric and vacuum apparatus, a catalytic cracking apparatus, a delayed coking apparatus, and the like) may be selected according to characteristics of the apparatuses, respectively, damage closely related to the apparatuses may be drawn, a general table representing the corrosion mechanism of the static oil refining equipment may be drawn according to various apparatuses, and other suitable manners may also be adopted, which is not limited in this respect.

Taking the data related to corrosion of each part of the dynamic corrosion loop diagram of the hydrogenation device as an example, the data related to corrosion of each part of the hydrogenation device is shown in table 2, wherein the data listed in table 2 is determined according to one actual hydrogenation device, and the data items and alarm limit values in the tables determined by different hydrogenation devices are different. As shown in table 2, the significance of the numerical designation of each corrosion-related data is shown in table 2, for example, the site with site number 102, the site name "D103 entry" (indicating a specific site of the hydrogenation apparatus), the item name "temperature" (indicating the temperature of the site), the data unit "temperature", the alarm value (LL) "ammonium chloride crystallization temperature" (indicating that a low alarm is given when the temperature of the site reaches the ammonium chloride crystallization temperature), the alarm value (L) "ammonium chloride crystallization temperature + 15" (indicating that a low alarm is given when the temperature of the site exceeds the ammonium chloride crystallization temperature by 15 ℃), and both the alarm value (H) and the alarm value (HH) are empty, indicating that a high alarm and a high alarm temperature are not set for the site. Fig. 4 is a dynamic corrosion loop diagram of a catalytic cracking unit provided in an embodiment of the present invention, and fig. 5 is a dynamic corrosion loop diagram of a delayed coking unit provided in an embodiment of the present invention. The data related to corrosion of each part in the dynamic corrosion loop diagram of the atmospheric and vacuum distillation unit, the dynamic corrosion loop diagram of the catalytic cracking unit and the dynamic corrosion loop diagram of the delayed coking unit provided in the embodiment of the present invention may be listed as the data related to corrosion of each part in the dynamic corrosion loop of the hydrogenation unit provided in the embodiment of the present invention shown in table 2.

TABLE 1

TABLE 2

S300, establishing a corrosion prediction model.

Specifically, a corrosion prediction model for each corrosion site of the oil refining plant is established. For example, a high-temperature sulfur and naphthenic acid corrosion prediction model is established for a high-temperature part with a high-temperature sulfur and naphthenic acid corrosion mechanism above 240 ℃, and NH is contained₄NH is established at the top part of the atmospheric tower by Cl crystallization and dew point corrosion mechanism₄Cl crystallization and dew point corrosion prediction model. The specific construction process is mainly to draw a corrosion curve (mainly used for reflecting the corrosion rates of the static refining equipment under different conditions) for a specific part of the static refining equipment according to the corrosion-related data of the static refining equipment acquired in the step S100 and by combining with corrosion-prevention-related management regulations of the static refining equipment (for example, the regulations of API571-2003 refinery equipment damage mechanism). And for general corrosion parts, alarm threshold value setting is mainly carried out according to technical documents such as China petrochemical refining process anti-corrosion management regulations, API571-2003 refinery equipment damage mechanisms, API581-2008 risk-based inspection basic resource documents, NACE 34109 + 2009 crude oil distillation unit tower top system corrosion numbers and the like, and specific setting of the alarm threshold values for each part is taken as a corrosion early warning model of the corresponding part and is led into the intelligent corrosion early warning system of the refining static equipment.

S400, processing the corrosion related data to obtain corrosion prediction data.

Specifically, the corrosion-related data is processed based on a corrosion prediction model to obtain corrosion prediction data for each corrosion site.

Preferably, if the part in the corrosion loop is a high-temperature part which has a temperature higher than a preset temperature and has a high-temperature sulfur and naphthenic acid corrosion mechanism, inputting production analysis data of the oil refining static equipment corresponding to the high-temperature part into a high-temperature sulfur and naphthenic acid corrosion prediction model to obtain high-temperature prediction data; if the part in the corrosion loop is the normal pressure tower top part with an ammonium salt crystallization corrosion mechanism, inputting production analysis data of the oil refining static equipment corresponding to the normal pressure tower top part into an ammonium salt crystallization corrosion prediction model to obtain normal pressure tower top prediction data; if the part in the corrosion loop is a fractionating tower top part with a low-temperature dew point corrosion mechanism, inputting production analysis data of the oil refining static equipment corresponding to the fractionating tower top part into a fractionating tower top low-temperature corrosion prediction model to obtain fractionating tower top prediction data; if the part in the corrosion loop is a sulfur-containing part with a sulfur-containing sewage scouring corrosion mechanism, inputting production analysis data of the oil refining static equipment corresponding to the sulfur-containing part into a sulfur-containing sewage scouring prediction model to obtain prediction data corresponding to the part; and if the part in the corrosion loop is a high-temperature part, an atmospheric tower top part, a fractionating tower top part and other parts except a sulfur-containing part, inputting the production analysis data of the oil refining static equipment corresponding to the part into a corrosion prediction model matched with the mechanism of the part to obtain corrosion prediction data aiming at the part.

For example, for a fractionating tower top part of a certain static oil refining equipment with a low-temperature dew point corrosion mechanism, inputting production analysis data of the static oil refining equipment corresponding to the fractionating tower top part into a fractionating tower top low-temperature corrosion prediction model to obtain fractionating tower top prediction data, and obtaining corrosion prediction data of the fractionating tower top part: the corrosion rate was predicted to be 2mm/30 days.

And S500, correlating the corrosion prediction data with the corrosion part, and carrying out corrosion early warning.

Specifically, corrosion prediction data corresponding to each corrosion part is associated with the corrosion part marked by the dynamic corrosion loop diagram, so as to perform corrosion early warning.

Preferably, an alarm threshold value of the corrosion part of the oil refining static equipment is set according to the corrosion prediction model, and the corrosion risk grade of the oil refining static equipment is divided according to the set alarm threshold value; determining the corrosion risk grade of the corrosion part marked in the dynamic corrosion loop diagram according to the divided corrosion risk grade, and the corrosion related data and the corrosion prediction data of the oil refining static equipment corresponding to the corrosion part marked in the dynamic corrosion loop diagram; and marking the corrosion position of the oil refining static equipment in the corrosion loop by using a third characteristic so as to carry out corrosion early warning on the oil refining static equipment according to the determined corrosion risk level, wherein the third characteristic is used for indicating the corrosion risk level of the corrosion position.

For example, for a high-temperature part with a high-temperature sulfur and naphthenic acid corrosion mechanism at the labeled temperature above 240 ℃, an alarm threshold is set for the labeled part according to the high-temperature sulfur and naphthenic acid corrosion prediction model in step S400, for example: it is shown in the high-temperature sulfur and naphthenic acid corrosion prediction model that, when the service life of the corresponding refinery static equipment is 2 to 2.5 years, the corrosion rate is 1mm/30 days, it is set that if the corrosion rate calculated from the corrosion-related data of the refinery static equipment is 0.8mm/30 days or less, the corrosion risk level is low risk, when the calculated corrosion rate is 0.8 to 1.1mm/30 days, the corrosion risk level is medium risk, and when the calculated corrosion rate is 1.1mm/30 days or more, the corrosion risk level is high risk.

Example two

Further, in the embodiment of the invention, the corrosion risk of the refinery static equipment is early warned according to the corrosion risk level and the equipment importance of the refinery static equipment determined in the above manner. The alarm level and the related parameters of the marked part of the corresponding oil refining static equipment which gives out the alarm can be displayed more intuitively by using the form of a matrix diagram.

Fig. 6 is an intelligent corrosion early-warning matrix diagram of the static oil refining equipment according to the second embodiment of the present invention, and as shown in fig. 6, the importance of the static oil refining equipment may be divided according to the status of the static oil refining equipment in the total flow of the equipment operation of an oil refining enterprise, the corrosion risk level may be divided according to the deviation degree between the operation parameter of the static oil refining equipment and the alarm threshold, and the corrosion risk early-warning may be performed on the static oil refining equipment by combining the importance of the static oil refining equipment and the corrosion risk level. The early warning level can be divided into no warning, low warning and high warning from low to high. The above is only an exemplary description of the corrosion risk early warning manner provided by the embodiment of the present invention, and the classification of the equipment importance and the corrosion risk level may be divided into more levels according to needs, and the early warning level may also be subjected to a more detailed warning level, which is not limited by the present invention.

For example, if a user clicks a corresponding alarm level in an intelligent corrosion early warning matrix diagram in the intelligent corrosion early warning system for the static oil refining equipment, information of the static oil refining equipment corresponding to the alarm level is popped up, and the information may include corrosion related data of the static oil refining equipment, a corrosion part giving an alarm, and the like.

In addition, in practical application, different alarm levels can be displayed by pictures with different colors so as to play a warning role, and alarm reminding can be displayed in other suitable modes or in a voice mode.

In a preferred embodiment of the invention, the intelligent corrosion early warning method for the oil refining static equipment further comprises the step of automatically generating a corrosion prevention report of the oil refining static equipment at preset time intervals. The preset time may be set to the beginning of the month, the middle of the month, and the end of the month, and the time range of the preset time may include 15 to 45 days. The anti-corrosion report can comprise a recently updated dynamic corrosion loop diagram, corrosion risk early warning aiming at each corrosion part, corrosion control strategy suggestions given by an intelligent corrosion early warning system of the oil refining static equipment, corrosion information inquiry and the like.

EXAMPLE III

Fig. 7 is a block diagram of an intelligent corrosion early-warning system for static oil refining equipment provided in the third embodiment of the present invention, and as shown in fig. 7, the intelligent corrosion early-warning system for static oil refining equipment includes: the device comprises an acquisition unit 1, a data acquisition unit and a data processing unit, wherein the acquisition unit is used for acquiring corrosion related data of a plurality of oil refining static equipment; the marking unit 2 is used for drawing a dynamic corrosion loop diagram of the static oil refining equipment according to the corrosion related data and marking the corrosion part of the static oil refining equipment in the dynamic corrosion loop diagram; the modeling unit 3 is used for establishing a corrosion prediction model aiming at each corrosion part of the oil refining static equipment; a prediction unit 4 for processing the corrosion-related data based on a corrosion prediction model to obtain corrosion prediction data for each corrosion site; and the early warning unit 5 is used for associating the corrosion prediction data corresponding to each corrosion part with the corrosion part marked by the dynamic corrosion loop diagram so as to carry out corrosion early warning.

The corrosion related data comprises equipment basic data and production analysis data of the oil refining static equipment; wherein the device infrastructure data comprises one or more of the following parameters: equipment design temperature, equipment design pressure, equipment off-line thickness measurement data and equipment material; and the production analysis data comprises production data of the oil refining static equipment, analysis data of a laboratory information management system and corrosion on-line monitoring data.

Example four

Fig. 8 is a block diagram of a labeling unit of the intelligent corrosion early warning system for oil refining static equipment according to the fourth embodiment of the present invention, and as shown in fig. 8, the labeling unit 2 includes: the loop dividing unit 21 is used for determining the equipment type to which the oil refining static equipment belongs, and dividing the dynamic corrosion loop diagram into a plurality of corrosion loops based on corrosion mechanisms corresponding to different equipment types; and a labeling subunit 22, configured to label, in the corrosion loop, a corrosion site of the refinery plant with a first characteristic and a second characteristic, where the plant categories include an atmospheric and vacuum distillation unit, a catalytic cracking unit, a delayed coking unit, a hydrorefining unit, and a hydrocracking unit; the first characteristic is used for indicating corrosion mechanisms corresponding to different corrosion loops, and the second characteristic is used for indicating corrosion related data of each corrosion part.

EXAMPLE five

Fig. 9 is a block diagram of a prediction unit of the intelligent corrosion early warning system for oil refining static equipment according to the fifth embodiment of the present invention, and as shown in fig. 9, a corrosion mechanism confirmation subunit 41 is configured to confirm that a part in a corrosion loop is one of the following: a high temperature part with a temperature above a preset temperature and a high temperature sulfur and naphthenic acid corrosion mechanism; an atmospheric overhead portion having an ammonium salt crystallization corrosion mechanism; a fractionation overhead portion having a low temperature dew point corrosion mechanism; a sulfur-containing site having a mechanism of scouring corrosion of sulfur-containing wastewater; and a high temperature portion, an atmospheric overhead portion, a fractionation overhead portion and other portions other than the sulfur-containing portion; the prediction subunit 42 is configured to, when it is determined that the portion in the corrosion loop is a high-temperature portion that is at a temperature above a preset temperature and has a high-temperature sulfur and naphthenic acid corrosion mechanism, input production and analysis data of the oil refining static equipment corresponding to the high-temperature portion into a high-temperature sulfur and naphthenic acid corrosion prediction model to obtain high-temperature prediction data; when the part in the corrosion loop is determined to be the normal pressure tower top part with the ammonium chloride crystallization and dew point corrosion mechanism, inputting the production analysis data of the oil refining static equipment corresponding to the normal pressure tower top part into an ammonium chloride crystallization and dew point corrosion prediction model to obtain normal pressure tower top prediction data; when the part in the corrosion loop is a fractionating tower top part with a low-temperature dew point corrosion mechanism, inputting production analysis data of the oil refining static equipment corresponding to the fractionating tower top part into a fractionating tower top low-temperature corrosion prediction model to obtain fractionating tower top prediction data; when the part in the corrosion loop is a sulfur-containing part with a sulfur-containing sewage scouring corrosion mechanism, inputting production analysis data of the oil refining static equipment corresponding to the sulfur-containing part into a sulfur-containing sewage scouring prediction model to obtain prediction data corresponding to the part; and inputting the production analysis data of the oil refining static equipment corresponding to the part into a corrosion prediction model matched with the part to obtain corrosion prediction data aiming at the part when the part in the corrosion loop is determined to be a high-temperature part, an atmospheric tower top, a fractionating tower top part and other parts except a sulfur-containing part.

EXAMPLE six

Fig. 10 is a block diagram of an early warning unit of the intelligent corrosion early warning system for oil refining static equipment according to the sixth embodiment of the present invention, and as shown in fig. 10, the early warning unit 5 includes: the corrosion risk classification subunit 51 is configured to set an alarm threshold of a corrosion portion of the oil refining static equipment according to the corrosion prediction model, and perform corrosion risk classification on the oil refining static equipment according to the set alarm threshold; the corrosion risk determining subunit 52 is configured to determine a corrosion risk level of the corrosion site marked in the dynamic corrosion loop diagram according to the divided corrosion risk level, and the corrosion related data and the corrosion prediction data of the oil refining static equipment corresponding to the corrosion site marked in the dynamic corrosion loop diagram; and an early warning subunit 53, configured to mark, in the corrosion loop, a corrosion site of the oil refining static equipment with a third feature, so as to perform corrosion early warning on the oil refining static equipment according to the determined corrosion risk level, where the third feature is used to indicate the corrosion risk level of the corrosion site.

Other specific embodiments and beneficial effects of the intelligent corrosion early warning system for the oil refining static equipment refer to the intelligent corrosion early warning method for the oil refining static equipment, and are not described herein again.

The following describes a specific implementation of the intelligent corrosion early warning system for oil refining static equipment in the embodiment of the invention by using a specific application example.

EXAMPLE seven

Fig. 11 is a network architecture diagram of the intelligent corrosion early-warning system for oil refining static equipment according to the seventh embodiment of the present invention, as shown in fig. 11, the intelligent corrosion early-warning system for oil refining static equipment is denoted by a remote corrosion monitoring center, and is generally set in units of enterprises, so as to obtain corrosion-related parameters of oil refining static equipment of multiple subsidiaries of the enterprises, perform analysis and processing, compare data among the subsidiaries, and then refer to each other according to the equipment operation and management modes of the subsidiaries, which is beneficial to improving the management level and further prolonging the service life of the equipment.

Example eight

Fig. 12 is an architecture diagram of an application example of the intelligent corrosion early-warning system for oil refining static equipment according to the eighth embodiment of the present invention, and as shown in fig. 12, a remote corrosion data center server in an enterprise is built, and the intelligent corrosion early-warning system for oil refining static equipment is placed therein.

Specifically, basic data such as equipment pipeline off-line thickness measurement data and equipment pipeline wall thickness material data are imported into a remote corrosion data center server in an enterprise. And secondly, acquiring enterprise production real-time data, LIMS analysis data and corrosion on-line monitoring data of the oil refining static equipment in real time by using the developed isomerization interface, and transmitting the data to an enterprise remote corrosion data center server. Furthermore, according to the obtained real-time production data, LIMS analysis data and corrosion online monitoring data of the static oil refining equipment, a corrosion loop diagram of the static oil refining equipment is drawn, and corrosion loop division is performed according to a corrosion mechanism determined by API571-2003 refinery equipment damage mechanism, for example, the corrosion loop diagram is divided into an atmospheric and vacuum device dynamic corrosion loop diagram, a catalytic cracking device dynamic corrosion loop diagram, a delayed coking device dynamic corrosion loop diagram, a hydrofining device dynamic corrosion loop diagram and a hydrocracking device dynamic corrosion loop diagram.

Aiming at a specific part of oil refining static equipment, a corrosion prediction model constructed according to corrosion related data is built in a software system, for example, a high-temperature part with a high-temperature sulfur and naphthenic acid corrosion mechanism at the temperature of more than 240 ℃ and a high-temperature sulfur and naphthenic acid corrosion prediction model are built; for the atmospheric tower top part with an ammonium salt crystallization corrosion mechanism, an ammonium salt crystallization and corrosion prediction model is built in a software system; for the top part of the fractionating tower with a low-temperature dew point corrosion mechanism, a fractionating tower top low-temperature corrosion prediction model is arranged in a software system; for sulfur-containing parts with a sulfur-containing sewage erosion corrosion mechanism, a sulfur-containing sewage erosion corrosion prediction model is built in a software system; and setting alarm threshold values for the parts in the corrosion loop, namely the high-temperature part, the normal-pressure tower top part, the fractionating tower top part and other parts except the sulfur-containing part according to technical documents such as China petrochemical refinery process anticorrosion management regulations, API571-2003 refinery equipment damage mechanism and the like, and constructing an alarm threshold loop as a corrosion prediction model of the corresponding part.

And correlating the obtained corrosion related data to the determined constructed corrosion prediction model, and comparing the corrosion related data with basic data such as the wall thickness of a pipeline of the oil refining static equipment led into the data center server, the material of the equipment and the like to realize online risk early warning of the oil refining static equipment.

The intelligent corrosion early warning matrix diagram of the refinery quiet equipment as shown in fig. 6 can be drawn to perform corrosion risk early warning on the corresponding refinery quiet equipment, the alarm number is displayed in the graphical range of no alarm, low alarm, high alarm and the like as shown in fig. 6, and after the alarm number is clicked, the detailed information (for example, displayed in the form of a pop-up list) of the refinery quiet equipment corresponding to the alarm of the corresponding level is displayed.

In addition, the anti-corrosion monthly report can be automatically generated, and the anti-corrosion weekly report can be automatically generated by simply modifying the system setting. And the corrosion risk of the refinery static equipment can be automatically pushed to corresponding managers, such as: and sending short messages, WeChats and the like to mobile terminals such as mobile phones of equipment managers managed correspondingly so that the managers can take appropriate measures (such as maintenance or replacement of equipment parts and the like) in time.

Through the technical scheme, the common corrosion parts are marked, data groups such as key operating parameters, analysis data, corrosion on-line monitoring parameters and the like of each part are defined, and the prediction model is integrated with a high-temperature sulfur and naphthenic acid corrosion prediction model and a fractionating tower top low-temperature corrosion prediction model (NH)₄Cl salt, a water dew point model), a corrosion warning threshold value and other corrosion warning core technology modules are subjected to correlation calculation, a corrosion risk warning value is output, an anti-corrosion monthly report is automatically generated, and the reliability, the accuracy and the real-time performance of corrosion risk warning of the oil refining static equipment are effectively improved.

Although the embodiments of the present invention have been described in detail with reference to the accompanying drawings, the embodiments of the present invention are not limited to the details of the above embodiments, and various simple modifications can be made to the technical solutions of the embodiments of the present invention within the technical idea of the embodiments of the present invention, and the simple modifications all belong to the protection scope of the embodiments of the present invention.

It should be noted that the various features described in the above embodiments may be combined in any suitable manner without departing from the scope of the invention. In order to avoid unnecessary repetition, the embodiments of the present invention do not describe every possible combination.

Those skilled in the art will understand that all or part of the steps in the method according to the above embodiments may be implemented by a program, which is stored in a storage medium and includes several instructions to enable a single chip, a chip, or a processor (processor) to execute all or part of the steps in the method according to the embodiments of the present application. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk or an optical disk, and other various media capable of storing program codes.

In addition, any combination of various different implementation manners of the embodiments of the present invention is also possible, and the embodiments of the present invention should be considered as disclosed in the embodiments of the present invention as long as the combination does not depart from the spirit of the embodiments of the present invention.

Claims

1. An intelligent corrosion early warning method for oil refining static equipment is characterized by comprising the following steps:

acquiring corrosion related data of a plurality of oil refining static equipment;

drawing a dynamic corrosion loop diagram of the static oil refining equipment according to the corrosion related data, and marking a corrosion part of the static oil refining equipment in the dynamic corrosion loop diagram;

establishing a corrosion prediction model aiming at each corrosion part of the oil refining static equipment;

processing the corrosion-related data based on the corrosion prediction model to obtain corrosion prediction data for each corrosion site; and

and correlating the corrosion prediction data corresponding to each corrosion part with the corrosion part marked by the dynamic corrosion loop diagram to carry out corrosion early warning.

2. The intelligent corrosion early warning method for oil refining static equipment according to claim 1, wherein the corrosion related data comprises equipment basic data and production analysis data of the oil refining static equipment;

wherein the device grounding data comprises one or more of the following parameters: equipment design temperature, equipment design pressure, equipment original wall thickness, equipment off-line thickness measurement data and equipment material; and

the production analysis data comprises production data of the oil refining static equipment, analysis data of a laboratory information management system and corrosion online monitoring data.

3. The intelligent corrosion early warning method for oil refining static equipment according to claim 1, wherein the step of marking the corrosion position of the oil refining static equipment in the dynamic corrosion loop diagram comprises the following steps:

determining the equipment type of the oil refining static equipment, and dividing the dynamic corrosion loop diagram into a plurality of corrosion loops based on corrosion mechanisms corresponding to different equipment types; and

marking the corrosion part of the oil refining static equipment in the corrosion loop by using a first characteristic and a second characteristic,

wherein the equipment category comprises an atmospheric and vacuum distillation unit, a catalytic cracking unit, a delayed coking unit, a hydrofining unit and a hydrocracking unit;

the first characteristic is used for indicating corrosion mechanisms corresponding to different corrosion loops, and the second characteristic is used for indicating corrosion related data of each corrosion part.

4. The intelligent corrosion early warning method for oil refining static equipment according to claim 1, wherein the processing the corrosion related data based on the corrosion prediction model to obtain corrosion prediction data for each corrosion site comprises:

if the part in the corrosion loop is a high-temperature part which has a temperature higher than a preset temperature and has a high-temperature sulfur and naphthenic acid corrosion mechanism, inputting production analysis data of the oil refining static equipment corresponding to the high-temperature part into a high-temperature sulfur and naphthenic acid corrosion prediction model to obtain high-temperature prediction data;

if the part in the corrosion loop is an atmospheric tower top part with an ammonium salt crystallization corrosion mechanism, inputting production analysis data of the oil refining static equipment corresponding to the atmospheric tower top part into an ammonium salt crystallization corrosion prediction model to obtain atmospheric tower top prediction data;

if the part in the corrosion loop is a fractionating tower top part with a low-temperature dew point corrosion mechanism, inputting the production analysis data of the oil refining static equipment corresponding to the fractionating tower top part into a fractionating tower top low-temperature corrosion prediction model to obtain fractionating tower top prediction data;

if the part in the corrosion loop is a sulfur-containing part with a sulfur-containing sewage erosion corrosion mechanism, inputting production analysis data of the oil refining static equipment corresponding to the sulfur-containing part into a sulfur-containing sewage erosion prediction model to obtain prediction data corresponding to the part; and

and if the part in the corrosion loop is the high-temperature part, the atmospheric tower top part, the fractionating tower top part and other parts except the sulfur-containing part, inputting the production analysis data of the oil refining static equipment corresponding to the part into a corrosion prediction model matched with the mechanism of the part to obtain corrosion prediction data aiming at the part.

5. The intelligent corrosion early warning method for oil refining static equipment according to claim 1, wherein the associating the corrosion prediction data corresponding to each corrosion site with the corrosion site marked by the dynamic corrosion loop diagram for corrosion early warning comprises:

setting an alarm threshold of the corrosion part of the oil refining static equipment according to the corrosion prediction model, and dividing the corrosion risk grade of the oil refining static equipment according to the set alarm threshold;

determining the corrosion risk level of the corrosion position marked in the dynamic corrosion loop diagram according to the divided corrosion risk level, the corrosion related data of the oil refining static equipment corresponding to the corrosion position marked in the dynamic corrosion loop diagram and the corrosion prediction data; and

marking the corrosion part of the static oil refining equipment in the corrosion loop according to a third characteristic so as to carry out corrosion early warning on the static oil refining equipment according to the determined corrosion risk level,

wherein the third characteristic is indicative of a corrosion risk level of the corrosion site.

6. The intelligent corrosion early warning system for the oil refining static equipment is characterized by comprising:

the acquisition unit is used for acquiring corrosion related data of a plurality of oil refining static equipment;

the marking unit is used for drawing a dynamic corrosion loop diagram of the static oil refining equipment according to the corrosion related data and marking a corrosion part of the static oil refining equipment in the dynamic corrosion loop diagram;

the modeling unit is used for establishing a corrosion prediction model aiming at each corrosion part of the oil refining static equipment;

a prediction unit for processing the corrosion-related data based on the corrosion prediction model to obtain corrosion prediction data for each corrosion site; and

and the early warning unit is used for associating the corrosion prediction data corresponding to each corrosion part with the corrosion part marked by the dynamic corrosion loop diagram so as to carry out corrosion early warning.

7. The intelligent corrosion early warning system for oil refining static equipment according to claim 6, wherein the corrosion related data comprises equipment basic data and production analysis data of the oil refining static equipment;

the production analysis data comprises production data of the oil refining static equipment, analysis data of a laboratory information management system and corrosion on-line monitoring data.

8. The intelligent corrosion early warning system for oil refining static equipment according to claim 6, wherein the labeling unit comprises:

the loop dividing subunit is used for determining the equipment type to which the oil refining static equipment belongs and dividing the dynamic corrosion loop diagram into a plurality of corrosion loops based on corrosion mechanisms corresponding to different equipment types; and

a marking subunit, configured to mark a corrosion site of the oil refining static equipment in the corrosion loop according to a first characteristic and a second characteristic,

9. The intelligent corrosion early warning system for oil refining static equipment according to claim 6, wherein the prediction unit comprises:

an etching mechanism confirming subunit for confirming that a position in the etching loop is one of the following: a high temperature part with a temperature above a preset temperature and a high temperature sulfur and naphthenic acid corrosion mechanism; an atmospheric overhead portion having an ammonium salt crystallization corrosion mechanism; a fractionation overhead portion having a low temperature dew point corrosion mechanism; a sulfur-containing site having a mechanism of scouring corrosion of sulfur-containing wastewater; and said high temperature portion, said atmospheric overhead portion, said fractionation overhead portion, and other portions other than said sulfur-containing portion;

the prediction subunit is used for inputting the production and analysis data of the oil refining static equipment corresponding to the high-temperature part into a high-temperature sulfur and naphthenic acid corrosion prediction model to obtain high-temperature prediction data when the part in the corrosion loop is determined to be the high-temperature part with the temperature above the preset temperature and a high-temperature sulfur and naphthenic acid corrosion mechanism;

when the part in the corrosion loop is determined to be an atmospheric tower top part with an ammonium chloride crystallization and dew point corrosion mechanism, inputting production analysis data of the oil refining static equipment corresponding to the atmospheric tower top part into an ammonium chloride crystallization and dew point corrosion prediction model to obtain atmospheric tower top prediction data;

when the part in the corrosion loop is a fractionating tower top part with a low-temperature dew point corrosion mechanism, inputting the production analysis data of the oil refining static equipment corresponding to the fractionating tower top part into a fractionating tower top low-temperature corrosion prediction model to obtain fractionating tower top prediction data;

when the part in the corrosion loop is a sulfur-containing part with a sulfur-containing sewage erosion corrosion mechanism, inputting production analysis data of the oil refining static equipment corresponding to the sulfur-containing part into a sulfur-containing sewage erosion prediction model to obtain prediction data corresponding to the part; and

and when the parts in the corrosion loop are confirmed to be the high-temperature part, the normal-pressure tower top, the fractionating tower top and other parts except the sulfur-containing part, inputting the production analysis data of the oil refining static equipment corresponding to the parts into a corrosion prediction model matched with the parts to obtain the corrosion prediction data aiming at the parts.

10. The intelligent corrosion early warning system for oil refining static equipment according to claim 6, wherein the early warning unit comprises:

the corrosion risk classification subunit is used for setting an alarm threshold of a corrosion part of the oil refining static equipment according to the corrosion prediction model and performing corrosion risk classification on the oil refining static equipment according to the set alarm threshold;

a corrosion risk determining subunit, configured to determine, according to the divided corrosion risk levels, the corrosion related data of the oil refining static equipment corresponding to the corrosion site marked in the dynamic corrosion loop diagram, and the corrosion prediction data, a corrosion risk level of the corrosion site marked in the dynamic corrosion loop diagram; and

the early warning subunit is used for marking the corrosion part of the static oil refining equipment in the corrosion loop according to a third characteristic so as to carry out corrosion early warning on the static oil refining equipment according to the determined corrosion risk level,

11. A machine-readable storage medium, wherein the machine-readable storage medium has instructions stored thereon, and the instructions are used for enabling the machine-readable storage medium to execute the intelligent corrosion early-warning method for oil refining static equipment according to any one of claims 1 to 5.