Methods, systems, storage media, and electronic equipment for developing inspection plans for pressure equipment

Abstract

This invention relates to the field of non-destructive testing and physicochemical analysis technology in the special equipment industry, and in particular to a method and system for formulating inspection plans for pressure equipment. The method converts relevant technical regulations and basic parameter data of pressure pipelines into a database and a logic operation library for logical operations. Then, a data import unit obtains the basic parameter data of the pressure pipeline to be inspected. By calling the database and logic operation library, corresponding parameters can be matched to obtain a preliminary inspection plan for the pressure pipeline. Finally, the preliminary inspection plan is revised based on the on-site operating conditions of the pressure pipeline to obtain the final optimal inspection plan. This embodiment allows for the periodic formulation of pressure pipeline inspection plans, greatly reducing manual intervention, thereby improving inspection efficiency, avoiding omissions, missed inspections, and incorrect inspections caused by human factors, and improving inspection quality.

Description

Technical Field

[0001] This invention relates to the field of non-destructive testing and physicochemical analysis technology in the special equipment industry, and in particular to a method and system for formulating inspection plans for pressure equipment. Background Technology

[0002] Pressure equipment, such as pressure pipelines, is classified as special equipment. According to the "Special Equipment Safety Law of the People's Republic of China," the "Regulations on Safety Supervision of Special Equipment," and the "Technical Supervision Regulations for Pressure Pipelines," pressure pipelines must pass periodic inspections before being put into use. Pressure pipelines are characterized by their large number, long lengths, and complex media and operating conditions. In particular, the pressure pipelines in petrochemical companies' catalytic cracking units, delayed coking units, coal-to-hydrogen purification units, PDH units, and PP units typically number in the thousands and range in length from tens to hundreds of kilometers. Before the periodic inspection work begins, an inspection plan needs to be developed for each pressure pipeline based on parameters and technical requirements such as media characteristics, operating pressure, operating temperature, and relevant standards and specifications. Traditionally, pressure pipeline inspection plans are developed by inspection personnel analyzing the media characteristics and operating conditions of each pressure pipeline and then formulating plans according to relevant specifications and standards.

[0003] Currently, the method of manually developing periodic inspection plans for pressure pipelines by inspection personnel has the following potential problems:

[0004] First, a single petrochemical plant typically has over a thousand pressure pipelines, ranging in length from tens to hundreds of kilometers. Manually handling the inspection of such a large number of pressure pipelines would be labor-intensive and inefficient.

[0005] Secondly, inspectors need to comprehensively refer to standards and technical specifications such as "Classification of Occupational Exposure to Toxic Substances" GBZ 230-2010, "List of Hazardous Chemicals - 2015 Edition", "Code for Fire Protection Design of Petrochemical Enterprises" GB 50160-2018, "Code for Fire Protection Design of Buildings" GB 50016-2014, "Code for Construction and Acceptance of Steel Pipelines for Toxic and Flammable Media in Petrochemical Industry" SH3501-2011, "Damage Mode Recognition of Pressure Equipment" GB / T 30579-2014, "Non-destructive Testing of Pressure Equipment" NB / T 47013-2015, "Pressure Pipeline Specification - Industrial Pipeline" GB / T20801-2020, "Rules for Periodic Inspection of Pressure Pipelines - Industrial Pipelines" TSGD7005-2018, and "Safety Technical Supervision Regulations for Pressure Pipelines - Industrial Pipelines" TSG D0001-2009 to formulate inspection plans. This results in high workload and low efficiency.

[0006] Third, the differences in the inspection capabilities, understanding of standards and specifications, and tolerance for workload of different inspection personnel will also affect the quality and accuracy of the inspection plan. Summary of the Invention

[0007] This invention addresses the problems of existing technologies by providing a method and system for developing inspection plans for pressure equipment. In the inspection of pressure pipelines, it helps inspectors to develop inspection plans, reduces their workload, minimizes the impact of human factors during inspection, and improves inspection efficiency and quality.

[0008] To address the aforementioned technical problems, the present invention provides a method for developing an inspection plan for pressure equipment, the method comprising:

[0009] S1. The database unit transforms relevant technical specifications into a database and a logic operation library, which can be searched, extracted, and used for logical operations.

[0010] S2. The data import unit acquires the relevant parameter data of all pressure-bearing equipment to be inspected, and classifies the acquired relevant parameter data according to the data category attributes based on the database;

[0011] S3. The data processing unit calls upon and, based on the requirements of the database and the underlying logic library, classifies, analyzes, judges, and recommends preliminary verification schemes for the relevant parameter data obtained by the data import unit.

[0012] S4. The on-site working condition verification unit, in conjunction with the location of the pressure equipment, modifies the preliminary inspection plan provided by the data processing unit and formulates the optimal inspection plan;

[0013] S5. The solution output unit provides the best inspection solution to the inspection personnel.

[0014] Preferably, the database unit in S1 converts relevant technical specifications into a database and a logic operation library, including the following methods:

[0015] S11. The database unit establishes a media database and a material database to classify various media and materials according to different standards;

[0016] S12. The database unit establishes an inspection regulation library, combines the inspection rules specified in relevant technical regulations, extracts the basic data of pressure pipelines as the rules for matching the inspection regulation library; and extracts the inspection methods and testing ratios from the inspection rules specified in relevant technical regulations as the results of the inspection regulation library matching.

[0017] S13. The database unit establishes an optimal solution library by scanning the inspection rule library and summarizing the highest detection rate of various non-destructive or physicochemical methods in the inspection rules specified in various relevant technologies, thus forming the optimal solution library.

[0018] Preferably, method S2 includes the following:

[0019] S21. The data import unit obtains the pressure equipment information to be matched, forms the initial attribute dictionary A of the pressure equipment, establishes the extended attribute dictionary C of the pressure equipment, directly adds the attributes in the initial attribute dictionary A except for the medium and material to the extended attribute dictionary C, and creates medium and material elements in the extended attribute dictionary C. The type of the element value is a list, and the initial element of the list is the value of medium and material in dictionary A.

[0020] S22. After establishing the initial attribute dictionary A and the extended attribute dictionary C, perform the following processing on each pressure-bearing device:

[0021] The material of the pressure equipment is deconstructed into the basic attributes of the material database record and added to the attribute list of the material in the extended attribute dictionary C; the category name and alias to which the material of the pressure equipment belongs are added to the extended attribute dictionary C. If it belongs to multiple categories or has multiple aliases, all categories and aliases are added to the attribute list of the material in the extended attribute dictionary C.

[0022] The device's media is deconstructed into the basic attributes of the media database records and added to the media attribute list in the extended attribute dictionary C. The category name and alias to which the device's media belongs are added to the extended attribute dictionary C. If it belongs to multiple categories or has multiple aliases, all category names and aliases are added to the media attribute list in the extended attribute dictionary C.

[0023] Preferably, method S3 includes the following:

[0024] S31. Establish an attribute combination set D. From the extended attribute dictionary C, extract combinations of 1 element, combinations of 2 elements up to combinations of N elements in sequence, and add them to the attribute combination set D, where N is equal to the total number of elements in the extended attribute dictionary C.

[0025] S32. Match each combination in the attribute combination set D with the inspection code library. If a match is found, it means that the pressure equipment needs to undergo this type of inspection.

[0026] Preferably, each combination in the attribute combination set D is matched with the inspection rule library, and the data processing unit optimizes the matching process, specifically including:

[0027] By using multi-threaded concurrency, multiple devices can be matched in parallel, reducing computation time;

[0028] By using pruning techniques to optimize the algorithm, when a non-destructive or physicochemical detection reaches the optimal solution recorded in method S13, the matching of that non-destructive or physicochemical detection is stopped, thus reducing the amount of computation.

[0029] By using caching technology, each combination of attribute combination set D and its matching results are cached. When performing a new match, the results are first queried from the cache. The initial attribute dictionary A and the final matching results of each device are cached. When matching devices with the same initial attributes, the matching results can be obtained directly.

[0030] Preferably, during caching, the initial attributes of each combination or device in the attribute combination set D are sorted in lexicographical order and combined into a string, which is used as the index of the hash table. The value is the matching result and stored in the hash table. During matching caching, the attribute combinations to be matched are sorted in lexicographical order and combined into a string L. The index of the string L that matches is searched in the hash table. If it is found, its value is directly obtained from the hash table as the matching result.

[0031] The second aspect of this invention discloses a system for formulating inspection plans for pressure equipment, including a data import unit, a database unit, a data processing unit, a field working condition confirmation unit, and a plan output unit;

[0032] The data import unit is used to obtain the basic parameters of the storage pressure-bearing equipment;

[0033] The database unit is used to store the database of relevant technical specifications and standards for establishing periodic inspections of pressure equipment, and to convert the relevant technical specifications and standards into a low-level logic library that can be searched, extracted and logically operated.

[0034] The data processing unit is used to classify, analyze, judge, and recommend the best verification scheme based on the requirements of the database and underlying logic library established by the database unit.

[0035] The on-site working condition verification unit is used to modify the inspection plan recommended by the data processing unit based on the on-site working conditions of the equipment.

[0036] The scheme output unit is used to provide the inspection scheme, which has been modified by the on-site working condition confirmation unit, to the inspection personnel.

[0037] Preferably, the database unit includes a media database, a corrosivity database, a material database, a logic operation library, a testing and regulation library, and an optimal solution library. The media database includes a media toxicity database and a fire hazard database.

[0038] The media database is used to store data on commonly used media in pressure equipment;

[0039] The material database is used to classify and store the materials used in pressure equipment according to their chemical elements and uses, in accordance with technical specifications.

[0040] The medium toxicity database is used to establish a database of commonly used media in pressure equipment according to their toxicity levels, namely, extremely hazardous, highly hazardous, moderately hazardous, slightly hazardous, and non-toxic fluids, in accordance with technical specifications.

[0041] The fire hazard database is used to establish databases of commonly used media in pressure equipment according to their fire hazard, namely Class A flammable gases, Class B flammable gases, Class A flammable liquids, Class B flammable liquids, Class C flammable liquids and non-flammable fluids, in accordance with technical regulations.

[0042] The inspection regulation library is used to extract basic data of pressure equipment and on-site environment as rules for matching inspection regulations, extract inspection methods and testing ratios of inspection rules in technical specifications, and form the inspection regulation library as the result of inspection regulation matching.

[0043] The optimal solution library is used to summarize the highest detection rate of various non-destructive or physicochemical methods in the various technically specified detection rules by scanning the inspection rule library.

[0044] The third aspect of the present invention discloses a computer storage medium storing computer instructions, which, when invoked, are used to execute the pressure equipment inspection scheme formulation method described above.

[0045] A fourth aspect of the present invention provides an electronic device, wherein the electronic device comprises:

[0046] A processor; and a memory arranged to store computer-executable instructions, which, when executed, cause the processor to perform the pressure equipment inspection scheme formulation method described above.

[0047] The beneficial effects of this invention are:

[0048] 1. This invention enables the data-driven and intelligent application of the method for formulating periodic inspection plans for pressure pipelines;

[0049] 2. This invention can simultaneously input thousands of basic parameters of pressure pipelines and process the data to formulate a periodic inspection plan, which can greatly reduce the inspection time.

[0050] 3. This invention can avoid omissions, missed inspections, and incorrect inspections caused by human factors, thereby improving the quality of inspection. Attached Figure Description

[0051] Figure 1 This is a flowchart of the method of the present invention;

[0052] Figure 2 This is a logic diagram for the transformation of the periodic inspection rules for pressure pipelines in this invention;

[0053] Figure 3This is a system flowchart of the present invention;

[0054] Figure 4 This is a basic data table for the routine inspection of a pressure pipeline according to the present invention;

[0055] Figure 5 The conclusion diagram after importing basic data into the system of this invention;

[0056] Figure 6 A general process card for magnetic particle testing was obtained by importing basic data into the system of this invention;

[0057] Figure 7 A general metallographic analysis process card derived from importing basic data into the system of this invention;

[0058] Figure 8 A general process card for Leeb hardness testing was obtained by importing basic data into the system of this invention.

[0059] Figure 9 This is a schematic diagram of an electronic device structure according to Embodiment 5 of the present invention. Detailed Implementation

[0060] To facilitate understanding by those skilled in the art, the present invention will be further described below with reference to embodiments and accompanying drawings. The content mentioned in the embodiments is not intended to limit the present invention. The present invention will be described in detail below with reference to the accompanying drawings.

[0061] Example 1:

[0062] This embodiment provides a method for developing an inspection plan for pressure-bearing equipment, such as... Figure 1 ,include:

[0063] S1. The database unit transforms relevant technical specifications into a database and a logic operation library, which can be searched, extracted, and used for logical operations.

[0064] The database includes a media database (which includes a media toxicity database and a fire hazard database) and a material database. The logic operation library includes the "TSG D0001 database", "TSG D7005 database", and "GB / T30579 database".

[0065] S2. The data import unit acquires the relevant parameter data of all pressure-bearing equipment to be inspected, and classifies the acquired relevant parameter data according to the data category attributes based on the database;

[0066] The first step in developing a periodic inspection plan is to collect basic parameters for each pressure pipeline in the petrochemical plant, including pipeline number, diameter, wall thickness, length, material, design pressure, design temperature, working pressure, working temperature, and medium, and list them in an Excel spreadsheet. The data import unit can directly import all pipeline data from the Excel spreadsheet at once, while retaining Excel's filtering and sorting functions. The imported data is then linked to the database unit and the data processing unit, participating in subsequent logical operations.

[0067] S3. The data processing unit calls upon and, based on the requirements of the database and the underlying logic library, classifies, analyzes, judges, and recommends preliminary verification schemes for the relevant parameter data obtained by the data import unit.

[0068] In this step, the data processing unit imports the basic parameters collected by the data import unit. Based on the relationship between the database and the logic operation library established by the database unit, it determines the fire hazard level, toxicity level, pressure pipeline level, and damage mode of the medium in the pressure pipeline, and formulates an inspection plan. Using the medium parameters imported by the data import unit, and based on the "Fire Hazard Database" and "Medium Toxicity Level Database" in the medium database of the database unit, the fire hazard level and toxicity level of the medium can be determined. Using the pressure, temperature, and medium parameters imported by the data import unit, and based on the "TSGD0001 Database" and the determined fire hazard level and toxicity level of the medium, the pressure pipeline level is determined. Using the medium, material, and temperature parameters imported by the data import unit, and based on the "GB / T 30579 Database," the possible damage modes of the pressure pipeline are determined. Based on the determined toxicity level of the medium, pressure pipeline level, and possible damage modes, and based on the "TSG D7005 Database," a preliminary inspection plan is formulated, determining the required non-destructive testing items and inspection ratios. Finally, by confirming the on-site operating conditions of the pressure pipeline, a preliminary inspection plan is formulated based on the "TSG D7005 database".

[0069] S4. The on-site working condition verification unit, in conjunction with the location of the pressure equipment, modifies the preliminary inspection plan provided by the data processing unit and formulates the optimal inspection plan;

[0070] S5. The solution output unit provides the best inspection solution to the inspection personnel;

[0071] The on-site condition verification unit and the solution output unit can be selected as human-computer interaction units. Pressure pipelines may encounter various on-site conditions, such as insulation layer damage leading to rainwater infiltration, long-term exposure to alternating loads, previously identified hazardous defects, or the first periodic inspection. These on-site conditions need to be combined with the preliminary periodic inspection plan. The data processing unit then modifies the plan based on the on-site conditions to develop the final periodic inspection plan. The solution output unit allows the system to output the periodic inspection plan in formats such as Excel, Word, and PDF to the inspection personnel's terminals, such as mobile phones and computers.

[0072] Specifically, this embodiment uses a pressure pipeline in a pressure-bearing device as an example. Relevant technical specifications and basic parameter data of the pressure pipeline are converted into a database and a logic operation library for logical operations. Then, the basic parameter data of the pressure pipeline to be inspected is obtained through a data import unit. By calling the database and logic operation library, corresponding parameters can be matched to obtain a preliminary inspection plan for the pressure pipeline. Then, combined with the on-site operating conditions of the pressure pipeline, the preliminary inspection plan is revised to obtain the final optimal inspection plan. This embodiment allows for the periodic development of pressure pipeline inspection plans, greatly reducing manual intervention, thereby improving inspection efficiency, avoiding omissions, missed inspections, and incorrect inspections caused by human factors, and improving inspection quality.

[0073] More specifically, the inspection plan formulation method in this embodiment includes the following steps:

[0074] Establish relevant databases, including:

[0075] S11. Database Unit: Establish Media Database and Material Database; This is the data preparation process. Prepare the media database (including media toxicity database and fire hazard database), material database, and logic operation library in advance to classify various media and materials according to different standards. For example, materials can be classified into cast iron, carbon steel, alloy steel, stainless steel, etc., based on carbon content, trace elements, etc. The media database is classified according to media toxicity, fire hazard, corrosiveness, etc.

[0076] S12. The database unit establishes a regulatory code library, and extracts basic data of pressure pipelines, such as diameter, wall thickness, design pressure, design temperature, medium, material, commissioning date and site environment, as the rules for matching the regulatory codes, in conjunction with the inspection rules of relevant technical regulations; and extracts the inspection methods and inspection ratios in the inspection rules of relevant technical regulations as the result of matching the regulatory code library, such as the regulation description of "TSG D7005-2018 Periodic Inspection Rules for Pressure Pipelines - Industrial Pipelines" 2.4.2.3(4) "Surface defect detection shall adopt NB / T The detection method in 47013. Magnetic particle testing should be given priority for the surface defect detection of ferromagnetic material pipelines. The requirements for surface defect detection are as follows: (4) Carbon steel, low alloy steel low temperature pipelines, Cr-Mo steel pipelines, low alloy steel pipelines with a standard tensile strength lower limit greater than or equal to 540MPa, pipelines subjected to significant alternating loads for a long period of time, and GC1 grade pipelines undergoing their first periodic inspection, should have their external surface non-destructive testing randomly checked at welded joints and stress concentration areas. The sampling ratio should not be less than 5% of the number of welded joints, and not less than 2. The description in this inspection regulation has parallel situations, so it is converted into 8 matching rules, such as Figure 2 As shown.

[0077] S13. The database unit establishes an optimal solution library. By scanning the inspection code library, it summarizes the highest detection ratio of various non-destructive or physical and chemical methods in the inspection rules of various relevant technical regulations, and forms an optimal solution library. For example, in the inspection code "TSG D7005-2018 Periodic Inspection Rules for Pressure Pipelines - Industrial Pipelines", the highest detection ratio of the MT test method is 10%, so the detection ratio of 10% is the optimal solution of the MT test method in this inspection code.

[0078] Furthermore, the basic parameter data of the pressure pipeline to be inspected is collected and imported to facilitate data matching and querying of inspection plans, specifically including:

[0079] S21. The data import unit obtains the pressure equipment information to be matched, forms the initial attribute dictionary A of the pressure equipment, establishes the extended attribute dictionary C of the pressure equipment, directly adds the attributes in the initial attribute dictionary A except for the medium and material to the extended attribute dictionary C, and creates medium and material elements in the extended attribute dictionary C. The type of the element value is a list, and the initial element of the list is the value of medium and material in dictionary A.

[0080] S22. After establishing the initial attribute dictionary A and the extended attribute dictionary C, perform the following processing on each pressure-bearing device:

[0081] The material of the pressure equipment is deconstructed into the basic attributes recorded in the material database and added to the attribute list of the material in the extended attribute dictionary C;

[0082] Add the category name and alias of the material to which the pressure equipment belongs to the extended attribute dictionary C. If it belongs to multiple categories or has multiple aliases, add all categories and aliases to the attribute list of the material in the extended attribute dictionary C.

[0083] The device's media is deconstructed into the basic attributes of the media database records and added to the media attribute list in the extended attribute dictionary C;

[0084] Add the category name and alias of the device's media to the extended attribute dictionary C. If the device belongs to multiple categories or has multiple aliases, add all category names and aliases to the media's attribute list in the extended attribute dictionary C.

[0085] After establishing the database and collecting the basic parameter data of the pressure pipeline to be tested, it is necessary to match the basic parameter data of the pressure pipeline with the database and perform logical operations, including:

[0086] S31. Establish an attribute combination set D. From the extended attribute dictionary C, extract combinations of 1 element, combinations of 2 elements up to combinations of N elements in sequence, and add them to the attribute combination set D, where N is equal to the total number of elements in the extended attribute dictionary C.

[0087] S32. Match each combination in the attribute combination set D with the inspection code library. If a match is found, it means that the pressure equipment needs to undergo this type of inspection.

[0088] The matching process is optimized using various techniques to reduce system runtime. Specific optimizations are as follows:

[0089] ① By using multi-threaded concurrency, multiple devices can be matched in parallel, reducing computation time;

[0090] ② The algorithm is optimized by pruning. When a non-destructive or physical-chemical test reaches the optimal solution in the optimal solution library, the matching of that non-destructive or physical-chemical test is stopped, reducing the amount of computation.

[0091] ③ By using caching technology, each combination of attribute combination set D and its matching results are cached. When performing a new match, the results are first queried in the cache. The initial attribute dictionary A and the final matching results of each device are cached. When matching devices with the same initial attributes, the matching results can be obtained directly.

[0092] The specific logic of the cache is as follows: For each combination or device in the attribute combination set D, the initial attributes are sorted lexicographically and combined into a string. This string serves as the index of the hash table, and the value is the matching result, stored in the hash table. (A hash table is a current technology; a hash table is a data structure that allows direct access based on a key value. That is, it accesses records by mapping the key value to a location in the table to speed up the search. This mapping function is called a hash function, and the array storing the records is called a hash table. Given a table M, there exists a function f(key). For any given key value key, if substituting it into the function yields the address of a record containing that key in the table, then table M is called a hash table, and function f(key) is called a hash function.) When matching the cache, the attribute combinations to be matched are sorted lexicographically and combined into a string L. The index of the matching string L is searched in the hash table. If it exists, its value is directly retrieved from the hash table as the matching result.

[0093] After obtaining the inspection plan through the above methods, and considering the on-site working conditions, the pressure pipeline may encounter situations such as insulation layer damage, rainwater infiltration, long-term alternating load, previously discovered dangerous defects, and the first periodic inspection. It is necessary to combine the on-site working conditions with the preliminary periodic inspection plan, and the data processing unit will make corrections based on the on-site working conditions to formulate the final periodic inspection plan. The periodic inspection plan will then be output to the inspection personnel's terminal in the form of Excel, Word, PDF, etc.

[0094] The pressure equipment inspection plan formulation method in this embodiment only requires collecting the basic parameter data of the pressure pipeline to be inspected, and then performing data matching and querying to obtain the relevant inspection plan. Compared with manual inspection, it can greatly reduce the inspection time, efficiently inspect pressure pipelines, and improve the quality of inspection, reducing omissions and errors.

[0095] Example 2:

[0096] This embodiment provides a system for developing inspection plans for pressure-bearing equipment, such as... Figure 3 It includes a data import unit, a database unit, a data processing unit, a field condition confirmation unit, and a solution output unit;

[0097] The system comprises the following components: a data import unit for acquiring and importing basic parameters of the pressure equipment; a database unit for storing relevant technical specifications and standards for establishing periodic inspections of the pressure equipment, and converting these specifications and standards into a low-level logic library capable of searching, extracting, and performing logical operations; a data processing unit for classifying, analyzing, judging, and recommending the best inspection plan based on the requirements of the database and low-level logic library established by the database unit; a field condition verification unit for modifying the inspection plan recommended by the data processing unit based on the field conditions of the equipment; and a plan output unit for providing the modified inspection plan to the inspection personnel.

[0098] Specifically, the system in this embodiment mainly consists of five parts: a data import unit, a database unit, a data processing unit, a field condition verification unit, and a scheme output unit. The data import unit acquires and imports the main design parameters (including design pressure, design temperature, pipeline length, design diameter, wall thickness, commissioning date, design medium, and pipeline class) of all pressure pipelines in the petrochemical plant into the system, converting them into machine language to provide basic data for the formulation of inspection schemes (here, basic data refers to the design parameters of the pressure pipelines). The database unit converts the technical specifications, standards, and other technical regulations related to the formulation of inspection schemes (such as "Periodic Inspection Rules for Pressure Pipelines—Industrial Pipelines" TSG D7005-2018, "Damage Pattern Recognition of Pressure Equipment" GB / T 30579, "Pressure Pipeline Specifications—Industrial Pipelines" GB / T 20801, etc.) into a low-level logic library that can be searched, extracted, and logically operated. The data processing unit classifies, judges, analyzes, and recommends the best inspection scheme based on the medium, material, temperature, and pressure in the basic data according to the requirements of the technical specifications and database. The on-site condition verification unit allows inspectors to select and verify specific situations encountered on the pressure pipeline, such as insulation damage leading to rainwater infiltration, long-term exposure to alternating loads, previously identified hazardous defects, or the first periodic inspection. After verification, the system will re-analyze and recommend a final inspection plan. The plan output unit provides the system-recommended inspection plan to the inspectors in PDF, Word, or other formats.

[0099] More specifically, the specific principle of this embodiment is as follows:

[0100] Database Units: The database units include the "Media Database (including the Media Toxicity Degree Database and Fire Hazard Database)," "Material Database," "Corrosivity Database," "TSG D0001 Database," "TSG D7005 Database," and "GB / T 30579 Database." The "Fire Hazard Database" is established according to the provisions of the "Code for Fire Protection Design of Petrochemical Enterprises" GB50160-2018, the "Code for Fire Protection Design of Buildings" GB 50016-2014, the "List of Hazardous Chemicals," the "Safety Technical Supervision Regulations for Pressure Pipelines—Industrial Pipelines" TSG D0001-2009, and the "Code for Construction and Acceptance of Steel Pipelines for Toxic and Flammable Media in Petrochemical Industry" SH3501-2011. It categorizes commonly used media in pressure pipelines according to their fire hazard into Class A flammable gases, Class B flammable gases, Class A flammable liquids, Class B flammable liquids, Class C flammable liquids, and non-flammable fluids. The "Media Toxicity Database" is established based on the provisions of GBZ 230-2010 "Classification of Occupational Exposure to Toxic Substances," TSG D0001-2009 "Safety Technical Supervision Regulations for Pressure Pipelines—Industrial Pipelines," and SH3501-2011 "Construction and Acceptance Specifications for Steel Pipelines for Toxic and Flammable Media in Petrochemical Industry." It categorizes commonly used media in pressure pipelines according to their toxicity levels, classifying them into extremely hazardous, highly hazardous, moderately hazardous, slightly hazardous, and non-toxic fluids. The "Media Database" summarizes the molecular formulas, physical properties, and chemical properties of commonly used media in pressure pipelines. The "Material Database" is established based on the provisions of GB / T 20801-2020 "Pressure Pipeline Specifications—Industrial Pipelines," classifying the materials used in pressure pipelines according to different chemical elements and applications, including carbon steel, low-temperature steel, alloy steel, stainless steel, and heat-resistant steel. The "TSG D0001 Database" is a logic operation library established based on the "Safety Technical Supervision Regulations for Pressure Pipelines—Industrial Pipelines" (TSG D0001-2009). It establishes a correspondence between the pressure pipeline medium, temperature, pressure, and other parameters imported into the data import unit and the pressure pipeline's classification level. The "TSG D7005 Database" is a logic operation library established based on the "Periodic Inspection Rules for Pressure Pipelines—Industrial Pipelines" (TSG D7005-2018). It establishes a correspondence between the pressure pipeline medium, temperature, pressure, and other parameters imported into the data import unit and the non-destructive and physicochemical tests required for the pressure pipeline. The "GB / T 30579 Database" is a logic operation library established based on "Damage Pattern Recognition of Pressure Equipment" (GB / T30579-2014). It establishes a correspondence between the pressure pipeline medium, temperature, pressure, and other parameters imported into the data import unit and potential environmental cracking and material degradation that may occur in the pressure pipeline.

[0101] Data Import Unit: Developing a periodic inspection plan requires collecting basic parameters for each pressure pipeline in the petrochemical plant, including pipeline number, start and end points, diameter, wall thickness, length, corrosion allowance, material, design pressure, design temperature, operating pressure, operating temperature, and medium, listed in an Excel spreadsheet. The data import unit can directly import all pipeline data from the Excel spreadsheet into the system at once, retaining Excel's filtering and sorting functions. Matching the Excel data categories with the system's data categories (e.g., database categories) completes the basic data import. The imported data then establishes a connection with the system's database and data processing units, participating in subsequent logical operations.

[0102] Data Processing Unit: The data processing unit receives the basic parameters imported by the data import unit. Based on the database and logic operation library established by the database unit, it determines the fire hazard level, toxicity level, pressure pipeline class, and damage mode of the medium in the pressure pipeline, and formulates an inspection plan. Using the medium parameters imported by the data import unit, and based on the "Fire Hazard Database," "Medium Toxicity Database," and "Medium Database" of the database unit, the fire hazard level and toxicity level of the medium can be determined. Using the pressure, temperature, and medium parameters imported by the data import unit, and based on the "TSGD0001 Database" and the determined fire hazard level and toxicity level of the medium, the pressure pipeline class is determined. Using the medium, material, and temperature parameters imported by the data import unit, and based on the "GB / T 30579 Database," the possible damage modes of the pressure pipeline are determined. Based on the determined toxicity level of the medium, pressure pipeline class, and possible damage modes, and based on the "TSG D7005 Database," a preliminary inspection plan is formulated, determining the required non-destructive testing, physicochemical testing items, and testing ratios. Finally, by confirming the on-site operating conditions of the pressure pipeline, a final inspection plan is formulated based on the "TSG D7005 database".

[0103] On-site operating condition confirmation and output unit: This unit can be a human-computer interaction unit. Through data processing by the data import unit, database unit, and data processing unit, a preliminary periodic inspection plan has been developed based on the basic data provided by the pressure pipeline user. However, on-site conditions may include insulation layer damage leading to rainwater infiltration, long-term alternating loads, previously discovered hazardous defects, or the first periodic inspection. In these cases, the on-site operating conditions need to be re-input into the system. The data processing unit then modifies the plan based on these conditions to develop the final periodic inspection plan. The output unit allows the system to output the periodic inspection plan to the inspection personnel's terminal in formats such as Excel, Word, and PDF.

[0104] This embodiment realizes the data-driven and intelligent application of the method for formulating periodic inspection plans for pressure pipelines. In current periodic inspection work for pressure pipelines, for example, the basic data for periodic inspection of a pressure pipeline includes... Figure 4 As shown, the inspection process is as follows:

[0105] ① According to GB 5044-1985, the medium "saturated vapor" is not considered a toxic medium. Therefore, according to section 2.4.2.9 of TSGD7005-2018, this pipeline does not require a recommended leak test. However, according to TSGD0001-2009, based on the pipeline's design pressure ≥4.0 MPa and design temperature ≥400℃, it is classified as GC1. (When the pipeline class determined by the medium and the combined pressure and temperature differs, the higher classification takes precedence. GC1 > GC2).

[0106] ②Since the material of the pipeline is 12Cr5Mo1, according to GB / T20801.2-2020 "Pressure Piping Specification - Industrial Piping", the material is a magnetic alloy steel Cr-Mo material. According to 2.4.2.3(4) in TSG D7005-2018, the pressure pipeline needs to be tested for surface magnetic particle, and the number of welded joints should not be less than 5% and not less than 2.

[0107] ③ Since the design temperature of this pipeline is 400℃ and the material is 12Cr5Mo1, according to GB / T 30579 "Damage Mode Recognition of Pressure Equipment", this pressure pipeline is at risk of high temperature creep. It is recommended to conduct physical and chemical analysis using either metallographic or hardness analysis.

[0108] ④ After determining that the pressure pipeline requires magnetic particle testing and metallographic or hardness testing during periodic inspections, the inspector needs to develop a magnetic particle testing process card based on NB / T 47013-2015 "Non-destructive Testing of Pressure Equipment", a metallographic process card based on GB / T 13298-2015 "Metallographic Replication Technology for Non-destructive Testing of Surfaces" and GB / T 17566-2008, or a hardness testing process card based on GB / T 17394.1-2014 "Metallic Materials - Leeb Hardness Test - Part 1: Test Methods" and GB / T 17395.2-2012 "Metallic Materials - Leeb Hardness Test - Part 2: Inspection and Calibration of Hardness Testers".

[0109] like Figure 5 As shown, this is the test plan obtained after importing the basic data.

[0110] like Figures 6 to 8As shown, these are general process cards for magnetic particle testing, metallographic analysis, and Leeb hardness testing, derived from the imported basic data.

[0111] The pressure equipment inspection plan development system in this embodiment can simultaneously input and process thousands of basic pressure pipeline parameters to develop a periodic inspection plan. The entire process is reduced from a month's work time using traditional methods to within a day. Currently, during normal shutdowns and maintenance at large petrochemical projects, the downtime is extremely limited, leaving very little time for inspection agencies. Furthermore, large petrochemical companies typically have thousands of pressure pipelines, often requiring inspection agencies to work on thousands of pipelines at a time. When inspection agencies receive such orders, they usually need to organize a team of inspectors to be stationed on-site for several months in advance, spending a month developing the inspection plan. The development steps for each pipeline inspection plan are the same as in point one above, creating a significant workload for on-site inspectors in terms of standard review. However, using the system in this embodiment, the required non-destructive testing and physicochemical analysis plan can be developed in just a few minutes.

[0112] In addition, this embodiment has a powerful media database and material database, which can provide inspection and testing personnel with fast and accurate search and reference, improving the efficiency and accuracy of data processing and reducing the labor intensity of inspection personnel in finding standards, regulations and inspection rules.

[0113] Furthermore, this embodiment can avoid omissions, missed inspections, and incorrect inspections caused by human factors. Due to differences in the understanding of standards by inspection personnel, incorrect inspections and missed inspections often occur when formulating plans. The system and method of this embodiment can effectively avoid such risks.

[0114] Example 3:

[0115] This embodiment discloses a computer storage medium that stores a computer program for electronic data exchange, wherein the computer program causes a computer to execute some or all of the steps in the pressure equipment inspection scheme formulation method described in Embodiment 1.

[0116] Example 4:

[0117] This embodiment discloses a computer program product, which includes a non-transitory computer-readable storage medium storing a computer program, and the computer program is operable to cause a computer to perform some or all of the steps in the pressure equipment inspection scheme formulation method described in Embodiment 1.

[0118] Example 5:

[0119] Please see Figure 9 , Figure 9This invention discloses an electronic device comprising:

[0120] Processor 41; and memory 42 arranged to store computer-executable instructions (program code), which may be an electronic memory such as flash memory, EEPROM (Electrically Erasable Programmable Read-Only Memory), EPROM, hard disk, or ROM. Memory 42 has storage space 43 for storing program code 44 for performing any method steps in the embodiments. For example, storage space 43 for program code may include various program codes 44 for implementing the various steps in the methods above. This program code can be read from or written to one or more computer program products. These computer program products include program code carriers such as hard disks, CDs, memory cards, or floppy disks. Such computer program products are typically the computer-readable storage medium of Embodiment 4. The computer-readable storage medium may have the same characteristics as... Figure 9 The memory 42 in the electronic device is a storage unit such as a storage segment or storage space. The program code can be compressed, for example, in a suitable form. Typically, the storage unit stores program code for performing the steps of the method according to the invention, i.e., program code that can be read by a processor such as 41, which, when run by the electronic device, causes the electronic device to perform the various steps of the method described above.

[0121] The above description is merely a preferred embodiment of the present invention and is not intended to limit the present invention in any way. Although the present invention has been disclosed above with reference to preferred embodiments, it is not intended to limit the present invention. Any person skilled in the art can make some changes or modifications to the above-disclosed technical content to create equivalent embodiments without departing from the scope of the present invention. Any simple modifications, equivalent changes, and modifications made to the above embodiments based on the present invention without departing from the scope of the present invention are within the scope of the present invention.

Claims

1. A method for formulating an inspection plan for pressure equipment, characterized in that, The method includes: S1. The database unit transforms relevant technical specifications into a database and a logic operation library, which can be searched, extracted, and used for logical operations. S2. The data import unit acquires the relevant parameter data of all pressure-bearing equipment to be inspected, and classifies the acquired relevant parameter data according to the data category attributes based on the database; S3. The data processing unit calls upon and, based on the requirements of the database and the underlying logic library, classifies, analyzes, judges, and recommends preliminary verification schemes for the relevant parameter data obtained by the data import unit. S4. The on-site working condition verification unit, in conjunction with the location of the pressure equipment, modifies the preliminary inspection plan provided by the data processing unit and formulates the optimal inspection plan; S5. The solution output unit provides the best inspection solution to the inspection personnel; The database unit in S1 transforms relevant technical specifications into a database and a logic operation library, including the following methods: S11. The database unit establishes a media database and a material database to classify various media and materials according to different standards; S12. The database unit establishes an inspection regulation library, combines the inspection rules specified in relevant technical regulations, extracts the basic data of pressure pipelines as the rules for matching the inspection regulation library; and extracts the inspection methods and testing ratios from the inspection rules specified in relevant technical regulations as the results of the inspection regulation library matching. S13. The database unit establishes an optimal solution library by scanning the inspection rule library and summarizing the highest detection rate of various non-destructive or physicochemical methods in the inspection rules specified in various relevant technical regulations to form an optimal solution library. The method S2 includes the following approaches: S21. The data import unit obtains the pressure equipment information to be matched, forms the initial attribute dictionary A of the pressure equipment, establishes the extended attribute dictionary C of the pressure equipment, directly adds the attributes in the initial attribute dictionary A except for the medium and material to the extended attribute dictionary C, and creates medium and material elements in the extended attribute dictionary C. The type of the element value is a list, and the initial element of the list is the value of medium and material in dictionary A. S22. After establishing the initial attribute dictionary A and the extended attribute dictionary C, perform the following processing on each pressure-bearing device: The material of the pressure equipment is deconstructed into the basic attributes recorded in the material database and added to the attribute list of the material in the extended attribute dictionary C; Add the category name and alias of the material to which the pressure equipment belongs to the extended attribute dictionary C. If it belongs to multiple categories or has multiple aliases, add all categories and aliases to the attribute list of the material in the extended attribute dictionary C. The device's media is deconstructed into the basic attributes of the media database records and added to the media attribute list in the extended attribute dictionary C; Add the category name and alias of the device's media to the extended attribute dictionary C. If it belongs to multiple categories or has multiple aliases, add all category names and aliases to the media's attribute list in the extended attribute dictionary C. The method S3 includes the following approaches: S31. Establish an attribute combination set D. From the extended attribute dictionary C, extract combinations of 1 element, combinations of 2 elements up to combinations of N elements in sequence, and add them to the attribute combination set D, where N is equal to the total number of elements in the extended attribute dictionary C. S32. Match each combination in the attribute combination set D with the inspection code library. If a match is found, it means that the pressure equipment needs to undergo this type of inspection. Each combination in the attribute combination set D is matched with the inspection rule library. The data processing unit optimizes the matching process, specifically including: By using multi-threaded concurrency, multiple devices can be matched in parallel, reducing computation time; By using pruning techniques to optimize the algorithm, when a non-destructive or physicochemical detection reaches the optimal solution recorded in method S13, the matching of that non-destructive or physicochemical detection is stopped, thus reducing the amount of computation. By using caching technology, each combination of attribute combination set D and its matching results are cached. When performing a new match, the results are first queried from the cache. The initial attribute dictionary A and the final matching results of each device are cached. When matching devices with the same initial attributes, the matching results can be obtained directly.

2. The method for formulating an inspection plan for pressure-bearing equipment according to claim 1, characterized in that: During caching, the initial attributes of each combination or device in the attribute combination set D are sorted in lexicographical order, combined into a string, and used as an index for the hash table. The value is the matching result and stored in the hash table. When matching the cache, the attributes to be matched are sorted in lexicographical order and combined into a string L. The index of the string L that matches is searched in the hash table. If it is found, its value is directly retrieved from the hash table as the matching result.

3. A pressure equipment inspection plan formulation system based on the pressure equipment inspection plan formulation method according to any one of claims 1-2, characterized in that: It includes a data import unit, a database unit, a data processing unit, a field condition verification unit, and a solution output unit; The data import unit is used to obtain the basic parameters of the storage pressure-bearing equipment; The database unit is used to store the database of relevant technical specifications and standards for establishing periodic inspections of pressure equipment, and to convert the relevant technical specifications and standards into a low-level logic library that can be searched, extracted and logically operated. The data processing unit is used to classify, analyze, judge, and recommend the best verification scheme based on the requirements of the database and underlying logic library established by the database unit. The on-site working condition verification unit is used to modify the inspection plan recommended by the data processing unit based on the on-site working conditions of the equipment. The scheme output unit is used to provide the inspection scheme, which has been modified by the on-site working condition confirmation unit, to the inspection personnel.

4. The pressure equipment inspection plan formulation system according to claim 3, characterized in that: The database unit includes a media database, a corrosivity database, a material database, a logic operation library, a testing and regulation library, and an optimal solution library. The media database includes a media toxicity database and a fire hazard database. The media database is used to store data on commonly used media in pressure equipment; The material database is used to classify and store the materials used in pressure equipment according to their chemical elements and uses, in accordance with technical specifications. The aforementioned medium toxicity database is used to establish a database of commonly used media in pressure equipment according to their toxicity levels, namely, extremely hazardous, highly hazardous, moderately hazardous, slightly hazardous, and non-toxic fluids, in accordance with technical specifications. The fire hazard database is used to establish databases of commonly used media in pressure equipment according to their fire hazard, namely Class A flammable gases, Class B flammable gases, Class A flammable liquids, Class B flammable liquids, Class C flammable liquids, and non-flammable fluids, in accordance with technical regulations. The inspection regulation library is used to extract basic data of pressure equipment and on-site environment as rules for matching inspection regulations, extract inspection methods and testing ratios of inspection rules in technical specifications as the result of inspection regulation matching and form the inspection regulation library; The optimal solution library is used to summarize the highest detection rate of various non-destructive or physicochemical methods in the various technically specified detection rules by scanning the inspection rule library.

5. A computer storage medium storing computer instructions, wherein the computer storage medium, when invoked, is used to execute the pressure equipment inspection scheme formulation method as described in any one of claims 1-2.

6. An electronic device, wherein, The electronic device includes: Processor; and, A memory configured to store computer-executable instructions, which, when executed, cause the processor to perform the pressure equipment inspection scheme formulation method as described in any one of claims 1-2.

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