Petrochemical equipment tank health state assessment method based on multi-dimensional data

Abstract

The invention relates to the technical field of petrochemical equipment tank health state evaluation, in particular to a petrochemical equipment tank health state evaluation method based on multi-dimensional data. The method comprises the following steps: acquiring original data of the petrochemical equipment tank, including information such as structure, material, use environment and the like of the equipment tank, and performing acquisition of the petrochemical equipment tank structure and construction of a simulation model based on the data to obtain simulation model data of the petrochemical equipment tank; identifying an abnormal area of the equipment tank through the simulation model, carrying out overlay analysis, evaluating the structural stability and fracture probability of the equipment tank, calculating the fracture probability of the equipment tank according to abnormal overlay data and structural stability attenuation data of the equipment tank, and carrying out health state abnormity evaluation on the equipment tank based on fracture probability data; according to the evaluation result, the petrochemical equipment tank is repaired; according to the method, the petrochemical equipment tank health state evaluation is optimized, so that the petrochemical equipment tank health state identification is more accurate.

Description

Technical Field

[0001] The present invention relates to the technical field of health status assessment of petrochemical equipment tanks, and particularly to a method for assessing the health status of petrochemical equipment tanks based on multi-dimensional data. Background Art

[0002] The health status of petrochemical equipment tanks is crucial for production safety and environmental protection. The health status assessment of petrochemical equipment tanks directly affects the maintenance cycle, operation cost and accident prevention efficiency of the equipment. The long-term action of high pressure, high temperature and corrosive substances will cause different degrees of damage and attenuation to the equipment tanks. Problems such as deformation, corrosion, cracks, and pitting on the inner and outer walls of the equipment will affect the load-bearing capacity and sealing performance of the tank body, leading to serious safety accidents such as equipment rupture and leakage. The method for assessing equipment health based on multi-dimensional data has gradually emerged. These methods can use sensors to monitor the operating status of petrochemical equipment tanks in real time, and through data fusion and analysis, comprehensively evaluate the health status of the equipment. Especially by collecting a large amount of real-time data, such as the temperature, pressure, vibration, and corrosion conditions of the tank body, combined with modern simulation modeling technology and data analysis algorithms, the dynamic monitoring and prediction of the health status of petrochemical equipment tanks can be realized. However, the traditional method for assessing the health status of petrochemical equipment tanks based on multi-dimensional data has problems of inaccurate prediction of external corrosion of petrochemical equipment tanks and inaccurate calculation of the rupture probability of petrochemical equipment tanks. Summary of the Invention

[0003] Based on this, it is necessary to provide a method for assessing the health status of petrochemical equipment tanks based on multi-dimensional data to solve at least one of the above technical problems.

[0004] To achieve the above object, a method for assessing the health status of petrochemical equipment tanks based on multi-dimensional data includes the following steps:

[0005] Step S1: Obtain petrochemical equipment tank data; collect the structure of the petrochemical equipment tank according to the petrochemical equipment tank data, so as to obtain petrochemical equipment tank structure data; construct a simulation model of the petrochemical equipment tank based on the petrochemical equipment tank data and the petrochemical equipment tank structure data to obtain petrochemical equipment tank simulation model data;

[0006] Step S2: Analyze the deformation trend of the inner wall of the petrochemical equipment tank according to the petrochemical equipment tank simulation model data to obtain petrochemical equipment tank inner wall deformation trend data; detect the damage of the outer wall of the petrochemical equipment tank according to the petrochemical equipment tank simulation model data to obtain petrochemical equipment tank outer wall damage data; perform abnormal superposition analysis on the petrochemical equipment tank based on the petrochemical equipment tank inner wall deformation trend data and the petrochemical equipment tank outer wall damage data to obtain petrochemical equipment tank abnormal superposition data;

[0007] Step S3: Conduct an analysis of the attenuation of the structural stability of the equipment tank based on the abnormal superimposed data of the petrochemical equipment tank to obtain the data on the attenuation of the structural stability of the equipment tank; calculate the rupture probability of the petrochemical tank based on the data on the attenuation of the structural stability of the equipment tank to obtain the data on the rupture probability of the petrochemical equipment tank;

[0008] Step S4: Conduct an abnormal assessment of the health status of the petrochemical equipment tank based on the data on the rupture probability of the petrochemical equipment tank to obtain the abnormal data on the health status of the petrochemical equipment tank; repair the petrochemical equipment tank based on the abnormal data on the health status of the petrochemical equipment tank to obtain the repair data of the petrochemical equipment tank.

[0009] The petrochemical equipment tank health status evaluation method based on multi-dimensional data of the present invention can achieve comprehensive equipment monitoring and accurate health prediction, greatly improving the intelligent level of equipment management. By obtaining multi-dimensional data of petrochemical equipment tanks, including information such as structure, material, and usage environment, and combining with the simulation model of the equipment, the physical state and load-bearing capacity of the equipment are comprehensively analyzed. By constructing a simulation model and based on data analysis, potential hidden dangers of the equipment are discovered in advance, avoiding the subtle problems overlooked by traditional inspection methods, and improving the comprehensiveness and accuracy of the evaluation. Secondly, based on the analysis of the inner wall deformation trend and the detection of the outer wall damage, the abnormal superposition analysis can comprehensively consider various influencing factors, not only being able to identify single defects, but also revealing the complex problems of the mutual influence and superposition between the inner and outer walls. This comprehensive analysis method can more accurately judge the operation of the equipment in a complex environment, identify the key factors leading to equipment failures in advance, and provide more powerful data support for subsequent safety evaluation and preventive measures. Further, through the analysis of the attenuation of the equipment structure stability, combined with the deformation and damage conditions of the inner and outer walls of the equipment, the probability of equipment rupture is obtained. This probability calculation not only helps to evaluate the current health status of the equipment, but also provides an important basis for the maintenance and replacement of the equipment. Through accurate prediction of the rupture probability, preventive measures are effectively formulated in advance, avoiding the occurrence of sudden accidents and ensuring the continuity and safety of production. Finally, based on the rupture probability data of petrochemical equipment tanks, the health status abnormality evaluation is carried out, which helps to comprehensively evaluate the operation risk of the equipment, identify the abnormal state of the equipment, and take repair measures in time. This process not only improves the accuracy and efficiency of equipment repair, avoids resource waste, but also improves the intelligent level of equipment maintenance through data-based health evaluation, reducing the risk of human judgment errors. Overall, this evaluation method starts from the operation data of the equipment, comprehensively considers factors such as damage, stress, and corrosion of the inner and outer walls, and can scientifically predict the health status of the equipment. Therefore, the present invention is an optimization of the traditional petrochemical equipment tank health status evaluation method based on multi-dimensional data, solving the problems of inaccurate prediction of external corrosion of petrochemical equipment tanks and inaccurate calculation of the rupture probability of petrochemical equipment tanks existing in the traditional petrochemical equipment tank health status evaluation method based on multi-dimensional data, and improving the accuracy rate of external corrosion prediction of petrochemical equipment tanks and the accuracy rate of rupture probability calculation of petrochemical equipment tanks.

[0010] Preferably, step S1 includes the following steps:

[0011] Step S11: Obtain petrochemical equipment tank data;

[0012] Step S12: Collect the petrochemical equipment tank structure according to the petrochemical equipment tank data, so as to obtain petrochemical equipment tank structure data;

[0013] Step S13: Obtain the petrochemical equipment tank material based on the petrochemical equipment tank data, so as to obtain the petrochemical equipment tank material data;

[0014] Step S14: Construct a petrochemical equipment tank simulation model based on the petrochemical equipment tank material data and the petrochemical equipment tank structure data to obtain the petrochemical equipment tank simulation model data.

[0015] By obtaining the relevant data of the petrochemical equipment tank, the present invention comprehensively grasps the actual operating status and potential risks of the equipment. The obtained petrochemical equipment tank data provides a basis for subsequent structural analysis and material evaluation, ensuring the authenticity and comprehensiveness of the data. Based on these data, the equipment structure is collected, which can accurately describe the structural characteristics of the equipment such as its shape, size, and design parameters, laying a solid foundation for subsequent simulation modeling. In this process, the collection of structural data not only ensures the reflection of the actual operating conditions of the equipment but also provides objective data support for subsequent evaluation, avoiding hidden problems ignored by traditional inspection methods. Further, obtaining the petrochemical equipment tank material data can comprehensively understand the material composition, physical properties, and corrosion resistance of the equipment, providing an accurate basis for material strength and durability analysis. This link is crucial for analyzing the reliability of the equipment during long-term operation and its ability to withstand the external environment. By combining the material data and the structural data to construct a petrochemical equipment tank simulation model, a model reflecting the actual working conditions can be created, providing an important basis for various engineering simulations and performance evaluations. The simulation model can reproduce the performance of the equipment under different working conditions in a virtual environment, predicting problems that may occur in advance, such as deformation and fatigue damage, so as to provide scientific decision-making support for the maintenance and optimization of the equipment.

[0016] Preferably, step S14 includes the following steps:

[0017] Step S141: Conduct a petrochemical equipment tank material strength test based on the petrochemical equipment tank material data to obtain the petrochemical equipment tank material strength data;

[0018] Step S142: Measure the external diameter of the tank body according to the petrochemical equipment tank structure data to obtain the petrochemical equipment tank external diameter data;

[0019] Step S143: Calculate the internal storage capacity according to the petrochemical equipment tank structure data to obtain the petrochemical equipment tank internal storage capacity data;

[0020] Step S144: Calculate the storage load-bearing capacity of the petrochemical equipment tank according to the petrochemical equipment tank internal storage capacity data and the petrochemical equipment tank material strength data to obtain the petrochemical equipment tank storage load-bearing capacity data;

[0021] Step S145: Construct a spatial rectangular coordinate system for the petrochemical equipment tank based on the internal storage capacity data and the external diameter data of the petrochemical equipment tank to obtain the spatial rectangular coordinate system data of the petrochemical equipment tank;

[0022] Step S146: Construct a simulation model of the petrochemical equipment tank based on the spatial rectangular coordinate system data and the storage and bearing capacity data of the petrochemical equipment tank to obtain the simulation model data of the petrochemical equipment tank.

[0023] In the present invention, by performing material strength detection on the petrochemical equipment tank, the actual strength data of the equipment material is accurately obtained, thereby evaluating its ability to withstand pressure and external environmental impacts, providing a basis for the long-term stability and safety of the equipment. Measuring the external diameter of the tank body and calculating the internal storage capacity can provide key parameters for the usage ability and structural safety of the equipment, and support for subsequent bearing capacity and risk assessment. Combining the material strength and storage capacity data to calculate the storage and bearing capacity of the petrochemical equipment tank helps to evaluate whether the equipment can withstand the expected load, thereby reducing the risk of overloading and accidents. In addition, constructing a spatial rectangular coordinate system to transform the geometric characteristics of the equipment into a mathematical model helps to accurately simulate the three-dimensional structure of the equipment and provide real simulation data support. The simulation model constructed based on the above data can effectively predict various problems that occur in the actual operation of the petrochemical equipment tank, help formulate scientific maintenance and optimization plans, and ensure the safety and stability of the equipment operation.

[0024] Preferably, step S2 includes the following steps:

[0025] Step S21: Analyze the deformation trend of the inner wall of the petrochemical equipment tank based on the simulation model data of the petrochemical equipment tank to obtain the deformation trend data of the inner wall of the petrochemical equipment tank;

[0026] Step S22: Detect the damage to the outer wall of the petrochemical equipment tank based on the simulation model data of the petrochemical equipment tank to obtain the damage data of the outer wall of the petrochemical equipment tank;

[0027] Step S23: Calculate the thickness attenuation of the outer wall of the petrochemical equipment tank based on the damage data of the outer wall of the petrochemical equipment tank to obtain the thickness attenuation data of the outer wall of the petrochemical equipment tank;

[0028] Step S24: Perform abnormal superposition analysis on the petrochemical equipment tank based on the deformation trend data of the inner wall of the petrochemical equipment tank and the thickness attenuation data of the outer wall of the petrochemical equipment tank to obtain the abnormal superposition data of the petrochemical equipment tank.

[0029] Through the analysis of the deformation trend of the inner wall of the petrochemical equipment tank, the deformation conditions occurring during the use of the inner wall can be timely detected, providing an important basis for predicting equipment failures or malfunctions in advance. The detection of damage to the outer wall of the petrochemical equipment tank helps to identify external damage, prevent more serious damage caused by external wall corrosion or crack propagation, and ensure the integrity and safety of the equipment. Combining the damaged data of the outer wall for thickness attenuation calculation can accurately evaluate the durability and service life of the outer wall of the equipment, helping to formulate maintenance or replacement plans. By performing abnormal superposition analysis on the inner wall deformation trend and the outer wall thickness attenuation data, the mutual influence and potential safety hazards between the inner and outer walls are revealed, providing a scientific basis for subsequent safety assessments and decision-making, thereby optimizing the maintenance strategy, extending the service life of the equipment, and reducing the accident risk.

[0030] Preferably, step S21 includes the following steps:

[0031] Step S211: Simulate the condition of overfilling of petroleum based on the simulation model data of the petrochemical equipment tank to obtain the overfilling data of the petrochemical equipment tank;

[0032] Step S212: Estimate the increase in the internal pressure of the petrochemical equipment tank based on the overfilling data of the petrochemical equipment tank to obtain the internal pressure increase data of the petrochemical equipment tank;

[0033] Step S213: Analyze the stress increase of the inner wall of the petrochemical equipment tank according to the internal pressure increase data of the petrochemical equipment tank and the overfilling data of the petrochemical equipment tank to obtain the inner wall stress increase data of the petrochemical equipment tank;

[0034] Step S214: Analyze the deformation trend of the petrochemical equipment tank based on the inner wall stress increase data of the petrochemical equipment tank and the internal pressure increase data of the petrochemical equipment tank to obtain the deformation trend data of the petrochemical equipment tank.

[0035] The present invention effectively identifies the overload conditions occurring in the petrochemical equipment tank by simulating the overfilling condition of petroleum, thereby providing a basis for preventing safety hazards caused by overfilling. Estimating the increase in internal pressure based on the overfilling data of petroleum can predict the change trend of the pressure in the tank under abnormal operating conditions, helping to take measures in advance to avoid the tank from bearing excessive pressure. Combining the pressure increase data with the overfilling situation for inner wall stress increase analysis can accurately evaluate the stress conditions borne by the petrochemical equipment tank under specific operations, further identifying potential structural risks. Analyzing the deformation trend based on the inner wall stress increase and pressure data provides detailed warning information for equipment maintenance and safety inspections, helping to timely detect deformations and potential rupture points, reducing the risk of accidents, and ensuring the safe operation of petrochemical equipment.

[0036] Preferably, step S213 includes the following steps:

[0037] Analyze the pressure state of the inner wall connection points based on the internal air pressure growth data of the petrochemical equipment tank to obtain the pressure state data of the inner wall connection points;

[0038] Detect the local stress concentration of the inner wall connection points for the pressure state data of the inner wall connection points to obtain the local gravitational concentration data of the inner wall connection points;

[0039] Measure the oil height according to the overfilling data of the petrochemical equipment tank to obtain the oil height data of the petrochemical equipment tank;

[0040] Obtain the stored oil density data; calculate the bottom liquid pressure of the petrochemical equipment tank based on the oil height data of the petrochemical equipment tank and the stored oil density data to obtain the bottom liquid pressure data of the petrochemical equipment tank;

[0041] Conduct an analysis of the stress growth of the inner wall of the petrochemical equipment based on the bottom liquid pressure data of the petrochemical equipment tank and the local gravitational concentration data of the inner wall connection points to obtain the stress growth data of the inner wall of the petrochemical equipment.

[0042] By analyzing the internal air pressure growth data of the petrochemical equipment tank and conducting an analysis of the pressure state of the inner wall connection points, this invention deeply understands the pressure situation faced by the inner wall connection points of the tank, thereby identifying the weak links prone to failure. The detection of the local stress concentration of the inner wall connection points further reveals the risk of local stress concentration caused by these pressure points, providing a basis for the reinforcement of local weak points. Measuring the oil height in combination with the overfilling data of the oil can accurately grasp the actual height of the liquid in the petrochemical equipment tank, laying a foundation for subsequent liquid pressure calculations. Obtaining the oil density data and calculating the bottom liquid pressure helps to accurately evaluate the pressure exerted by the bottom liquid, avoiding equipment damage caused by excessive pressure. Conducting an analysis of the inner wall stress growth based on the bottom liquid pressure and local gravitational concentration data helps to timely discover potential structural fatigue points, optimize the maintenance strategy, and ensure the long-term stable operation of the equipment.

[0043] Preferably, step S22 includes the following steps:

[0044] Step S221: Obtain the storage environment data of the petrochemical equipment tank; collect the humid environment of the storage environment according to the storage environment data of the petrochemical equipment tank to obtain the humid data of the storage environment of the petrochemical equipment tank;

[0045] Step S222: Calculate the generation probability of the corrosion medium for the humid data of the storage environment of the petrochemical equipment tank based on the simulation model data of the petrochemical equipment tank to obtain the generation probability data of the outer wall corrosion medium;

[0046] Step S223: Calculate the pitting probability of the outer wall for the generation probability data of the outer wall corrosion medium to obtain the pitting probability data of the outer wall of the equipment tank;

[0047] Step S234: Based on the pitting corrosion probability data of the outer wall of the equipment tank, estimate the corrosion diffusion to obtain the corrosion diffusion data of the outer wall of the equipment tank;

[0048] Step S235: Measure the temperature fluctuation of the storage environment data of the petrochemical equipment tank to obtain the temperature fluctuation data of the tank storage environment;

[0049] Step S236: Calculate the growth trend of the thermal stress on the outer wall of the equipment tank according to the temperature fluctuation data of the storage environment to obtain the growth trend data of the thermal stress on the outer wall of the equipment tank;

[0050] Step S237: Based on the growth trend data of the thermal stress on the outer wall of the equipment tank and the corrosion diffusion data of the outer wall of the equipment tank, conduct damage detection on the outer wall of the petrochemical equipment tank to obtain the damage data of the outer wall of the petrochemical equipment tank.

[0051] By obtaining the storage environment data of the petrochemical equipment tank and collecting the humid environment, the present invention can accurately master the humidity of the storage environment and provide key data support for the generation of corrosive media. Calculate the generation probability of corrosive media for the humid environment data to effectively evaluate the corrosion risk encountered by the outer wall. Calculate the pitting corrosion probability through the generation probability data of the corrosive media on the outer wall, which helps to identify potential corrosion points on the outer wall and provide a basis for subsequent treatment. Based on the pitting corrosion probability of the outer wall, estimate the corrosion diffusion to predict in advance the expansion trend of the corrosion area, and then guide the maintenance measures. The combination of the measurement of the temperature fluctuation of the storage environment and the calculation of the growth trend of the thermal stress can deeply analyze the growth of the thermal stress on the outer wall caused by temperature changes, identify the areas that cause cracks or structural problems, and combine the growth trend of the thermal stress and the corrosion diffusion data to conduct damage detection on the outer wall, which helps to achieve early detection of damage to the outer wall of the equipment, reduce the failure risk, and improve the safety and durability of the equipment.

[0052] Preferably, step S24 includes the following steps:

[0053] Step S241: Based on the deformation trend data of the inner wall of the petrochemical equipment tank, count the deformation positions of the inner wall of the petrochemical equipment tank to obtain the deformation position data of the inner wall of the petrochemical equipment tank;

[0054] Step S242: Detect the defect overlapping area of the petrochemical equipment tank according to the deformation position data of the inner wall of the petrochemical equipment tank and the thickness attenuation data of the outer wall of the petrochemical equipment tank to obtain the defect overlapping area data of the petrochemical equipment tank;

[0055] Step S243: Calculate the local stress superposition of the defect overlapping area data of the petrochemical equipment tank to obtain the local stress superposition data of the petrochemical equipment tank;

[0056] Step S244: Based on the defect overlapping area data of the petrochemical equipment tank and the local stress superposition data of the petrochemical equipment tank, estimate the rigidity attenuation of the petrochemical equipment tank to obtain the rigidity attenuation data of the petrochemical equipment tank;

[0057] Step S245: Perform abnormal superposition analysis on the petrochemical equipment tank based on the rigid attenuation data and the local stress superposition data of the petrochemical equipment tank to obtain the abnormal superposition data of the petrochemical equipment tank.

[0058] The present invention accurately identifies the weak areas of the inner wall of the equipment tank by statistically analyzing the deformation position based on the deformation trend data of the inner wall of the petrochemical equipment tank, providing specific position support for subsequent analysis. Combining the inner wall deformation position data with the outer wall thickness attenuation data to detect the defect overlapping area helps to discover the areas where potential overlapping problems exist between the inner and outer walls, which is crucial for early identification of structural risks. Calculating the local stress superposition of the defect overlapping area data can effectively reveal the additional stress borne by these areas, helping to evaluate the structural stability of the equipment tank. Based on the local stress superposition data and the defect overlapping area data, predicting the rigid attenuation can predict the rigid decline trend of the equipment tank in advance, and then evaluate the risk of the decline of its bearing capacity. Combining the rigid attenuation and the local stress superposition data for abnormal superposition analysis can comprehensively understand the comprehensive abnormal conditions of the equipment tank, provide a scientific basis for equipment maintenance decisions, improve the operational safety of the equipment, and extend the service life.

[0059] Preferably, step S3 includes the following steps:

[0060] Step S31: Perform analysis on the accumulation of material damage to the petrochemical equipment tank based on the abnormal superposition data of the petrochemical equipment tank to obtain the data on the accumulation of material damage to the petrochemical equipment tank;

[0061] Step S32: Estimate the structural fatigue condition of the petrochemical equipment tank based on the data on the accumulation of material damage to the petrochemical equipment tank to obtain the structural fatigue data of the petrochemical equipment tank;

[0062] Step S33: Perform analysis on the attenuation of the structural stability of the equipment tank based on the structural fatigue data and the data on the accumulation of material damage to the petrochemical equipment tank to obtain the data on the attenuation of the structural stability of the equipment tank;

[0063] Step S34: Calculate the rupture probability of the petrochemical tank based on the structural fatigue data and the data on the attenuation of the structural stability of the equipment tank to obtain the rupture probability data of the petrochemical equipment tank.

[0064] By analyzing the accumulation of material damage based on the abnormal superimposed data of petrochemical equipment tanks, the present invention can effectively track the damage process of materials during long-term operation, timely reveal the fatigue points of the materials, and provide a basis for subsequent preventive maintenance. Using the damage data to estimate the structural fatigue condition helps to clarify the fatigue problems that occur during the high-load and long-term use of the equipment tank, and identify potential structural risks in advance. By combining the structural fatigue data and the material damage data to analyze the attenuation of the equipment structure stability, an in-depth understanding of the stability decline trend of the equipment under different working conditions can be obtained, providing a scientific prediction for optimizing the maintenance cycle and avoiding sudden failures. Calculating the rupture probability based on the structural fatigue and stability attenuation data provides a basis for evaluating the rupture risk of the equipment tank in advance, ensuring the safe operation of the petrochemical equipment tank, preventing uncontrollable equipment damage or accidents, and maximizing the long-term stability and safety of the equipment.

[0065] Preferably, step S4 includes the following steps:

[0066] Step S41: Calculate the leakage probability of the petrochemical equipment tank based on the rupture probability data of the petrochemical equipment tank and the structural fatigue data of the petrochemical equipment tank to obtain the leakage probability data of the petrochemical equipment tank;

[0067] Step S42: Conduct a safety risk assessment of the petrochemical equipment tank based on the leakage probability data of the petrochemical equipment tank and the rupture probability data of the petrochemical equipment tank to obtain the safety risk data of the petrochemical equipment tank;

[0068] Step S43: Conduct an abnormal assessment of the health status of the petrochemical equipment tank based on the safety risk data of the petrochemical equipment tank and the leakage probability data of the petrochemical equipment tank to obtain the abnormal health status data of the petrochemical equipment tank;

[0069] Step S44: Repair the petrochemical equipment tank according to the abnormal health status data of the petrochemical equipment tank to obtain the repair data of the petrochemical equipment tank.

[0070] By calculating the leakage probability based on the rupture probability data and the structural fatigue data of the petrochemical equipment tank, the present invention can effectively predict the probability of leakage during the long-term operation of the equipment, timely identify potential risks, and thus take preventive and repair measures in advance. Combining the leakage probability and the rupture probability for safety risk assessment can comprehensively understand the safety hazards of the petrochemical equipment tank under various extreme working conditions, providing a scientific basis for optimizing safety management. Conducting an abnormal assessment of the health status based on the safety risk data and the leakage probability can accurately judge whether there are abnormal changes during the operation of the equipment tank, timely detect the deviation of the equipment health status, and avoid accidents. Repairing the tank according to the abnormal health status data ensures that the equipment tank can be repaired in time when problems occur, thereby improving the safety, reliability and service life of the equipment, and reducing the impact of equipment failures on production safety.

[0071] The present invention lies in that the method for evaluating the health status of petrochemical equipment tanks based on multi-dimensional data can achieve comprehensive equipment monitoring and accurate health prediction, greatly improving the intelligent level of equipment management. By obtaining the multi-dimensional data of petrochemical equipment tanks, including information such as structure, material, and usage environment, and combining with the simulation model of the equipment, the physical state and load-bearing capacity of the equipment are comprehensively analyzed. By constructing a simulation model and based on data analysis, potential hidden dangers of the equipment are discovered in advance, avoiding the subtle problems overlooked by traditional inspection methods, and improving the comprehensiveness and accuracy of the evaluation. Secondly, based on the analysis of the inner wall deformation trend and the detection of the outer wall damage, the abnormal superposition analysis can comprehensively consider various influencing factors, not only identifying single defects but also revealing the complex problems of mutual influence and superposition between the inner and outer walls. This comprehensive analysis method can more accurately judge the operation of the equipment in a complex environment, identify the key factors leading to equipment failures in advance, and provide more powerful data support for subsequent safety assessment and preventive measures. Further, through the analysis of the attenuation of the equipment structure stability, combined with the deformation and damage conditions of the inner and outer walls of the equipment, the probability of equipment rupture is obtained. This probability calculation not only helps to evaluate the current health status of the equipment but also provides an important basis for the maintenance and replacement of the equipment. Through accurate prediction of the rupture probability, preventive measures are effectively formulated in advance, avoiding the occurrence of sudden accidents and ensuring the continuity and safety of production. Finally, based on the rupture probability data of petrochemical equipment tanks, the abnormal health status assessment is carried out, which helps to comprehensively evaluate the operation risk of the equipment, identify the abnormal status of the equipment, and take repair measures in a timely manner. This process not only improves the accuracy and efficiency of equipment repair, avoids resource waste, but also improves the intelligent level of equipment maintenance through data-based health assessment, reducing the risk of human judgment errors. Overall, this evaluation method starts from the operation data of the equipment, comprehensively considers factors such as damage, stress, and corrosion of the inner and outer walls, and can scientifically predict the health status of the equipment. Therefore, the present invention makes an optimization treatment for the traditional method for evaluating the health status of petrochemical equipment tanks based on multi-dimensional data, solves the problems of inaccurate prediction of external corrosion of petrochemical equipment tanks and inaccurate calculation of the rupture probability of petrochemical equipment tanks existing in the traditional method for evaluating the health status of petrochemical equipment tanks based on multi-dimensional data, and improves the accuracy rate of predicting external corrosion of petrochemical equipment tanks and the accuracy rate of calculating the rupture probability of petrochemical equipment tanks. Description of the Drawings

[0072] Figure 1 It is a schematic diagram of the step flow of a method for evaluating the health status of petrochemical equipment tanks based on multi-dimensional data;

[0073] Figure 2 is Figure 1 a detailed implementation step flow diagram of step S2 in

[0074] Figure 3 For Figure 1 the detailed implementation step flow schematic diagram of step S3 in

[0075] The realization, functional features and advantages of the object of the present invention will be further described in conjunction with the embodiments with reference to the accompanying drawings. Specific implementation manners

[0076] The technical method of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are part of the embodiments of the present invention, rather than all of the embodiments. All other embodiments obtained by those skilled in the art within the scope of the present invention without creative work based on the embodiments of the present invention belong to the scope of protection of the present invention.

[0077] In addition, the accompanying drawings are only schematic diagrams of the present invention and are not necessarily drawn to scale. The same reference numerals in the drawings denote the same or similar parts, and thus repeated descriptions thereof will be omitted. Some of the block diagrams shown in the drawings are functional entities and do not necessarily correspond to physically or logically independent entities. The functional entities can be implemented in software form, or implemented in one or more hardware modules or integrated circuits, or implemented in different networks and / or processor methods and / or microcontroller methods.

[0078] It should be understood that although the terms "first", "second", etc. may be used here to describe various units, these units should not be limited by these terms. These terms are only used to distinguish one unit from another. For example, without departing from the scope of the exemplary embodiments, the first unit may be referred to as the second unit, and similarly the second unit may be referred to as the first unit. The term "and / or" used here includes any and all combinations of one or more of the listed associated items.

[0079] To achieve the above object, please refer to Figures 1 to 3 , a petrochemical equipment tank health status evaluation method based on multi-dimensional data, comprising the following steps:

[0080] Step S1: Obtain petrochemical equipment tank data; collect the petrochemical equipment tank structure according to the petrochemical equipment tank data, so as to obtain petrochemical equipment tank structure data; construct a petrochemical equipment tank simulation model based on the petrochemical equipment tank data and the petrochemical equipment tank structure data to obtain petrochemical equipment tank simulation model data;

[0081] Step S2: Analyze the deformation trend of the inner wall of the petrochemical equipment tank based on the petrochemical equipment tank simulation model data to obtain the deformation trend data of the inner wall of the petrochemical equipment tank; detect the damage of the outer wall of the petrochemical equipment tank based on the petrochemical equipment tank simulation model data to obtain the damage data of the outer wall of the petrochemical equipment tank; perform abnormal superposition analysis on the petrochemical equipment tank based on the deformation trend data of the inner wall of the petrochemical equipment tank and the damage data of the outer wall of the petrochemical equipment tank to obtain the abnormal superposition data of the petrochemical equipment tank;

[0082] Step S3: Analyze the attenuation of the structural stability of the equipment tank based on the abnormal superposition data of the petrochemical equipment tank to obtain the attenuation data of the structural stability of the equipment tank; calculate the rupture probability of the petrochemical tank based on the attenuation data of the structural stability of the equipment tank to obtain the rupture probability data of the petrochemical equipment tank;

[0083] Step S4: Evaluate the abnormal health status of the petrochemical equipment tank based on the rupture probability data of the petrochemical equipment tank to obtain the abnormal health status data of the petrochemical equipment tank; repair the petrochemical equipment tank based on the abnormal health status data of the petrochemical equipment tank to obtain the repair data of the petrochemical equipment tank.

[0084] In the embodiment of the present invention, refer to Figure 1 As shown, it is a schematic diagram of the step flow of a method for evaluating the health status of a petrochemical equipment tank based on multi-dimensional data according to the present invention. In this example, the method for evaluating the health status of a petrochemical equipment tank based on multi-dimensional data includes the following steps:

[0085] Step S1: Obtain petrochemical equipment tank data; perform petrochemical equipment tank structure acquisition according to the petrochemical equipment tank data to obtain petrochemical equipment tank structure data; construct a petrochemical equipment tank simulation model based on the petrochemical equipment tank data and the petrochemical equipment tank structure data to obtain petrochemical equipment tank simulation model data;

[0086] In the embodiment of the present invention, when obtaining petrochemical equipment tank data, a real-time sensor device is used to comprehensively monitor the physical state of the petrochemical equipment tank, including parameters such as temperature, pressure, humidity, and vibration. The sensor data is transmitted to the data acquisition system through a wireless transmission device, and the system records and stores the data in real time. Through data cleaning and preprocessing, noise and abnormal data are removed. Subsequently, based on the collected data, high-precision scanning of the external and internal parts of the equipment tank is performed using a laser scanner or three-dimensional structure scanning technology to obtain the geometric shape and structure data of the equipment. These structure data include the thickness of the tank body, material strength, wall thickness change, and the connection conditions of each joint. Then, these structure data are combined with the physical performance data of the petrochemical equipment tank, and a simulation model of the petrochemical equipment tank is constructed through finite element analysis software or a custom calculation tool.

[0087] Step S2: Analyze the deformation trend of the inner wall of the petrochemical equipment tank based on the petrochemical equipment tank simulation model data to obtain the deformation trend data of the inner wall of the petrochemical equipment tank; detect the damage of the outer wall of the petrochemical equipment tank based on the petrochemical equipment tank simulation model data to obtain the damage data of the outer wall of the petrochemical equipment tank; perform abnormal superposition analysis on the petrochemical equipment tank based on the deformation trend data of the inner wall of the petrochemical equipment tank and the damage data of the outer wall of the petrochemical equipment tank to obtain the abnormal superposition data of the petrochemical equipment tank;

[0088] In the embodiment of the present invention, the deformation trend of the inner wall of the petrochemical equipment tank is analyzed according to the simulation model data. By analyzing the pressure fluctuation and temperature change data experienced by the tank body during actual use, combining the material parameters and external conditions in the model, and using the finite element analysis method to calculate stress and deformation, the deformation trend data of the inner wall of the petrochemical equipment tank is obtained. Immediately afterwards, an external detection device such as an ultrasonic detector or infrared scanning technology is used to detect the damage of the outer wall of the petrochemical equipment tank. During the detection process, by analyzing the cracks, corrosion and wear conditions of the outer wall, the damage data of the outer wall of the equipment tank is obtained. According to the deformation trend data of the inner wall and the damage data of the outer wall, using the data fusion technology, the two data are fused and abnormal superposition analysis is performed to identify potential fatigue points and safety hazards in the structure of the equipment tank, and the abnormal superposition data of the petrochemical equipment tank is obtained.

[0089] Step S3: Analyze the attenuation of the structural stability of the equipment tank according to the abnormal superposition data of the petrochemical equipment tank to obtain the attenuation data of the structural stability of the equipment tank; calculate the rupture probability of the petrochemical tank according to the attenuation data of the structural stability of the equipment tank to obtain the rupture probability data of the petrochemical equipment tank;

[0090] In the embodiment of the present invention, the obtained abnormal superposition data of the petrochemical equipment tank is used to analyze the attenuation of the structural stability of the equipment. This analysis process comprehensively evaluates the material strength, wall thickness and historical stress conditions of the equipment tank, and uses a life prediction model to analyze the attenuation of the structural stability of the equipment tank to judge the recession rate of the tank body under different working conditions. The attenuation analysis combines the effects of corrosion rate, fatigue load and temperature change, and calculates the current stability of the equipment tank through a mathematical model and obtains the corresponding attenuation data. Subsequently, based on these attenuation data, using the stress-strain relationship and material failure theory, the rupture probability of the petrochemical equipment tank is calculated. Through the calculated rupture path and the remaining strength of the equipment tank material, the rupture probability data of the equipment tank under specific use conditions is obtained.

[0091] Step S4: Based on the rupture probability data of the petrochemical equipment tank, evaluate the abnormal health status of the petrochemical equipment tank to obtain the abnormal health status data of the petrochemical equipment tank; repair the petrochemical equipment tank data according to the abnormal health status data of the petrochemical equipment tank to obtain the repair data of the petrochemical equipment tank.

[0092] In the embodiment of the present invention, based on the obtained petrochemical equipment tank rupture probability data, the health status of the petrochemical equipment tank is evaluated for anomalies. This evaluation process combines the rupture probability with the service life, operating environment, and historical failure data of the equipment tank, and uses multi-dimensional data analysis methods to comprehensively evaluate the health status of the equipment tank. By setting a threshold for health status evaluation, it is identified whether the equipment tank is currently in an abnormal state, providing a basis for subsequent maintenance decisions. Then, based on the health status anomaly data, repair operations for the petrochemical equipment tank are carried out. The repair operations determine whether partial reinforcement or replacement of some damaged materials is required according to the anomaly evaluation results. In actual operation, through advanced welding techniques, reinforcing materials, and repair methods, the load-bearing capacity and structural integrity of the petrochemical equipment tank are restored.

[0093] Preferably, step S1 includes the following steps:

[0094] Step S11: Obtain petrochemical equipment tank data;

[0095] Step S12: Collect the structure of the petrochemical equipment tank according to the petrochemical equipment tank data, so as to obtain petrochemical equipment tank structure data;

[0096] Step S13: Obtain the material of the petrochemical equipment tank according to the petrochemical equipment tank data, so as to obtain petrochemical equipment tank material data;

[0097] Step S14: Based on the petrochemical equipment tank material data and the petrochemical equipment tank structure data, construct a simulation model of the petrochemical equipment tank to obtain petrochemical equipment tank simulation model data.

[0098] In the embodiments of the present invention, when acquiring the data of the petrochemical equipment tank, a set of high-precision sensors are used to comprehensively monitor the petrochemical equipment tank. The sensors include a temperature sensor, a pressure sensor, a humidity sensor, a vibration sensor, a flow sensor, etc. Each sensor is fixed at different positions of the equipment tank to monitor various environmental parameters inside and outside the tank in real time. The output data of all sensors are uploaded to the central data management system through a wireless transmission module. The data management system records and stores the collected raw data in real time and preliminarily screens the abnormal data. After the data of the petrochemical equipment tank is collected, a three-dimensional laser scanner is used to perform a detailed scan on the geometric structure of the petrochemical equipment tank. The laser scanner can obtain the surface and internal geometric information of the equipment tank within a short time, with an accuracy up to the millimeter level. Through the laser scan of the surface of the equipment tank, the external contour of the equipment tank is obtained, including important parameters such as wall thickness, joints, and support points. At the same time, combined with the measurement data of the internal structure, the internal dimensions and support structure of the tank body are detected by special sensors. These data are subjected to three-dimensional modeling through data processing software to generate the three-dimensional structure data of the petrochemical equipment tank. When obtaining the material of the petrochemical equipment tank, non-destructive testing techniques such as X-ray flaw detection, ultrasonic thickness measurement, and magnetic particle testing are required to obtain the material information on the surface and inside of the equipment tank. An ultrasonic thickness gauge can be used to measure the actual thickness of the tank body and material defects without damaging the equipment. Then, by taking on-site samples or referring to the material specifications of the equipment, the specific material types used for the petrochemical equipment tank are determined, such as stainless steel, carbon steel, etc. The chemical composition analysis of the material sample is carried out to confirm its chemical composition and physical properties, such as tensile strength, yield strength, hardness, etc. Combining the on-site data with the material certification documents, the complete material data of the petrochemical equipment tank is obtained. After completing the acquisition of the structure and material of the petrochemical equipment tank, the construction of the simulation model of the petrochemical equipment tank begins. Using the obtained structure data and material data, the finite element analysis (FEA) method is used to model the equipment tank. The finite element model needs to accurately reflect the geometric shape, material properties, and working environment of the equipment tank. The CAD software is used to perform geometric modeling of the equipment tank, and this model is imported into the finite element analysis software. The physical properties of each part are set according to the material data, such as elastic modulus, Poisson's ratio, etc. Subsequently, the simulation conditions, such as pressure, temperature, external load, etc., are set, and mechanical simulation calculations are performed on the equipment tank to analyze the stress, strain, temperature distribution, and deformation of the tank body under various working conditions. The simulation results will generate the simulation model data of the petrochemical equipment tank, including the stress distribution diagram, deformation trend, and rupture point of the equipment tank under different working conditions.

[0099] Preferably, step S14 includes the following steps:

[0100] Step S141: Perform petrochemical equipment tank material strength detection according to the petrochemical equipment tank material data to obtain petrochemical equipment tank material strength data;

[0101] Step S142: Measure the external diameter of the tank according to the petrochemical equipment tank structure data to obtain the petrochemical equipment tank external diameter data;

[0102] Step S143: Calculate the internal storage capacity according to the petrochemical equipment tank structure data to obtain the petrochemical equipment tank internal storage capacity data;

[0103] Step S144: Calculate the storage bearing capacity of the petrochemical equipment tank according to the petrochemical equipment tank internal storage capacity data and the petrochemical equipment tank material strength data to obtain the petrochemical equipment tank storage bearing capacity data;

[0104] Step S145: Construct a space rectangular coordinate system of the petrochemical equipment tank according to the petrochemical equipment tank internal storage capacity data and the petrochemical equipment tank external diameter data to obtain the petrochemical equipment tank space rectangular coordinate system data;

[0105] Step S146: Construct a simulation model of the petrochemical equipment tank according to the petrochemical equipment tank space rectangular coordinate system data and the petrochemical equipment tank storage bearing capacity data to obtain the petrochemical equipment tank simulation model data.

[0106] In the embodiments of the present invention, when performing the material strength detection of the petrochemical equipment tank, material samples of the equipment tank are collected. These samples include the materials of the tank wall, bottom and joints of the equipment tank. Then, using standardized mechanical testing methods, such as tensile tests, compression tests or hardness tests, key performance indicators such as tensile strength, compressive strength, yield strength, hardness, etc. of the samples are tested. Testing equipment uses tools such as universal material testing machines and hardness testers to conduct detailed inspections on samples at different positions. Through tensile tests, the fracture point and ductility of the material can be obtained, hardness tests evaluate the wear resistance of the material surface, and compression tests can evaluate the deformation ability of the material under high pressure. These measured mechanical property parameters will serve as the basic data for subsequent simulation models and bearing capacity analysis. Based on the structural data of the petrochemical equipment tank, a high-precision laser rangefinder is used to measure the external diameter of the petrochemical equipment tank. Multiple positions of the tank body are selected for measurement, including the bottom, top and middle, etc., to ensure the representativeness of the measurement results. The laser rangefinder accurately measures the external diameter by emitting a laser beam and receiving the reflected signal. For equipment tanks with complex shapes, three-dimensional laser scanning technology can be used to obtain point cloud data at different angles for further diameter calculation. The measurement data will be analyzed by data processing software to obtain the accurate value of the external diameter of the petrochemical equipment tank. Based on the structural data of the petrochemical equipment tank, to determine the geometric shape of the equipment tank, three-dimensional laser scanning technology is used to obtain the internal geometric structure of the equipment tank. Then, by combining parameters such as the diameter, length and height of the tank body, the internal storage capacity is calculated through formulas. The specific calculation method is to use the basic volume formula of a cylindrical storage tank: V = πr2h where r is the radius of the tank body and h is the height of the tank body. If the shape of the equipment tank is a complex geometric body, precise calculations need to be carried out through appropriate geometric models. The calculation results will generate the internal volume data of the petrochemical equipment tank. After obtaining the internal storage capacity data and material strength data of the petrochemical equipment tank, mechanical calculation methods are used to evaluate the storage bearing capacity of the petrochemical equipment tank, analyze the strength and pressure resistance performance of the material of the petrochemical equipment tank, and evaluate the pressure that the tank body material can withstand when storing substances. By combining the storage capacity with the strength limit of the tank body material, the bearing capacity of the equipment tank under the maximum storage capacity is calculated. The specific calculation process includes considering factors such as the density of the stored substance, the pressure distribution in the storage tank, and the yield strength of the material. After completing the capacity calculation and external diameter measurement of the petrochemical equipment tank, a spatial rectangular coordinate system of the equipment tank is established. According to the external diameter and storage capacity of the petrochemical equipment tank, by setting the origin position of the tank body (usually taking the bottom or the center position of the tank), the tank body is divided into multiple coordinate segments. Using the Cartesian coordinate system, different parts of the tank body (such as the top, bottom and side) are calibrated in the coordinate system according to their spatial positions. The construction of the rectangular coordinate system needs to ensure the accurate expression of the geometric shape of the tank body and be able to reflect the stress distribution of the equipment tank when storing substances.Based on the spatial rectangular coordinate system and storage capacity data of the petrochemical equipment tank, a simulation model of the petrochemical equipment tank is constructed using finite element analysis software. The geometric model and coordinate system of the petrochemical equipment tank are imported, and the physical properties of each coordinate point are set, including the elastic modulus, yield strength, etc. of the material. Then, based on the storage capacity data, simulation calculations are carried out to simulate the stress, strain, and deformation processes of the petrochemical equipment tank under different loads. Through simulation calculations, the stress distribution, internal pressure distribution, and weak areas that occur in the equipment tank under working conditions can be obtained.

[0107] Preferably, step S2 includes the following steps:

[0108] Step S21: Analyze the deformation trend of the inner wall of the petrochemical equipment tank according to the simulation model data of the petrochemical equipment tank to obtain the deformation trend data of the inner wall of the petrochemical equipment tank;

[0109] Step S22: Detect the damage of the outer wall of the petrochemical equipment tank according to the simulation model data of the petrochemical equipment tank to obtain the damage data of the outer wall of the petrochemical equipment tank;

[0110] Step S23: Calculate the thickness attenuation of the outer wall of the petrochemical equipment tank based on the damage data of the outer wall of the petrochemical equipment tank to obtain the thickness attenuation data of the outer wall of the petrochemical equipment tank;

[0111] Step S24: Conduct abnormal superposition analysis of the petrochemical equipment tank based on the deformation trend data of the inner wall of the petrochemical equipment tank and the thickness attenuation data of the outer wall of the petrochemical equipment tank to obtain the abnormal superposition data of the petrochemical equipment tank.

[0112] As an example of the present invention, refer to Figure 2 As shown, in this example, step S2 includes:

[0113] Step S21: Analyze the deformation trend of the inner wall of the petrochemical equipment tank according to the simulation model data of the petrochemical equipment tank to obtain the deformation trend data of the inner wall of the petrochemical equipment tank;

[0114] In the embodiment of the present invention, according to the simulation model data of the petrochemical equipment tank, the initial geometric shape and its force condition of the inner wall of the equipment tank are obtained. Using the finite element analysis method, the internal pressure, temperature, and external environment changes of the equipment tank under different working conditions are simulated to obtain the force distribution and strain state of the inner wall of the tank. On this basis, the time-stepping method is used to dynamically analyze the deformation of the inner wall, and the deformation trend of the inner wall of the petrochemical equipment tank evolving over time is tracked. By comparing the inner wall stress and strain data at different time points, the deformation trend data of the inner wall is obtained, reflecting the permanent deformation or fatigue failure that occurs in the inner wall of the equipment tank.

[0115] Step S22: Detect the damage of the outer wall of the petrochemical equipment tank according to the simulation model data of the petrochemical equipment tank to obtain the damage data of the outer wall of the petrochemical equipment tank;

[0116] In the embodiment of the present invention, based on the simulation model data of the petrochemical equipment tank, the numerical simulation method is used to detect the damage of the outer wall of the equipment tank. By simulating and analyzing the stress condition of the equipment tank after long-term use, especially the influence of the external environment on the tank body (such as wind pressure, temperature change, etc.) and the internal liquid pressure. Combining with the material characteristics of the petrochemical equipment tank, the simulation model will simulate the damage forms such as cracks, dents, and corrosion on the outer wall due to long-term load-bearing. During the detection process, a multi-level grid division method is adopted to calculate the stress concentration area at each position of the outer wall point by point, and the damage is judged through the area with excessive stress. The detection of the damaged outer wall compares with the historical monitoring data to identify the damage state of the current equipment and generate the damaged outer wall data.

[0117] Step S23: Calculate the thickness attenuation of the outer wall of the petrochemical equipment tank based on the damaged data of the outer wall of the petrochemical equipment tank to obtain the thickness attenuation data of the outer wall of the petrochemical equipment tank;

[0118] In the embodiment of the present invention, based on the damaged data of the outer wall of the petrochemical equipment tank, the calculation of the outer wall thickness attenuation is carried out. According to the damage type and distribution of the outer wall of the equipment tank, the thickness attenuation area is determined. By measuring each point of the outer wall of the equipment tank and combining the actual situation of the damaged area, the corresponding mathematical model (such as a modified linear or nonlinear attenuation formula) is used to calculate the thickness change at different positions of the outer wall. The attenuation calculation formula takes into account the influence of different environmental factors on the outer wall of the equipment tank, such as chemical corrosion, temperature fluctuation, and mechanical wear. By collecting the thickness data of each part of the outer wall of the equipment tank and performing trend analysis on it, the overall outer wall thickness attenuation curve is calculated.

[0119] Step S24: Perform abnormal superposition analysis on the petrochemical equipment tank based on the deformation trend data of the inner wall of the petrochemical equipment tank and the thickness attenuation data of the outer wall of the petrochemical equipment tank to obtain the abnormal superposition data of the petrochemical equipment tank.

[0120] In the embodiment of the present invention, after obtaining the deformation trend data of the inner wall of the petrochemical equipment tank and the thickness attenuation data of the outer wall, the abnormal superposition analysis of the petrochemical equipment tank is carried out. This analysis combines the deformation trend of the inner wall and the thickness attenuation data of the outer wall to evaluate the overall health state of the equipment tank. The specific method is to conduct a time series comparison between the inner wall deformation data and the thickness attenuation data of the outer wall to identify the mutual influence between the two. For example, the deformation of the inner wall will accelerate the damage of the outer wall, or the thickness attenuation of the outer wall will intensify the stress concentration of the inner wall. The superposition analysis uses mathematical modeling methods (such as weighted average, fuzzy comprehensive evaluation, or machine learning algorithms) to comprehensively process these data to identify potential abnormal patterns, and the abnormal superposition data reflects the abnormal degree of the petrochemical equipment tank in the current state.

[0121] Preferably, step S21 includes the following steps:

[0122] Step S211: Simulate the overfilling condition of petroleum based on the petrochemical equipment tank simulation model data to obtain the overfilling data of the petrochemical equipment tank;

[0123] Step S212: Estimate the internal air pressure growth of the petrochemical equipment tank based on the overfilling data of the petrochemical equipment tank to obtain the internal air pressure growth data of the petrochemical equipment tank;

[0124] Step S213: Analyze the stress growth of the inner wall of the petrochemical equipment tank according to the internal air pressure growth data of the petrochemical equipment tank and the overfilling data of the petrochemical equipment tank to obtain the stress growth data of the inner wall of the petrochemical equipment tank;

[0125] Step S214: Analyze the deformation trend of the petrochemical equipment tank based on the stress growth data of the inner wall of the petrochemical equipment tank and the internal air pressure growth data of the petrochemical equipment tank to obtain the deformation trend data of the petrochemical equipment tank.

[0126] In the embodiments of the present invention, by using the petrochemical equipment tank simulation model data, combined with the structure, material, and storage capacity of the petrochemical equipment tank, etc., the storage situation of petroleum in the tank is analyzed through a computer simulation system. The specific operation is to input various design parameters of the petrochemical equipment tank (such as tank capacity, overfill threshold, liquid characteristics, etc.) into the simulation system to generate the dynamic changes during the petroleum filling process, especially the liquid behavior in the case of overfilling of the tank. The simulation model can simulate different degrees of overfilling situations, record information such as the spatial distribution of the overfilled area, the change in liquid height, and the liquid layer in contact with the tank body, and output the petroleum overfill data of the petrochemical equipment tank. By analyzing the petroleum overfill data in the petrochemical equipment tank, the impact on the internal air pressure is calculated. Based on the relationship between liquid density, temperature, and the filling amount and gas compressibility, the change in the internal air pressure of the petrochemical equipment tank is calculated using the fluid dynamics equation. The specific operation includes taking the density, overfill amount, and ambient temperature of the petroleum as inputs, and combining with the interaction model between gas and liquid to generate a prediction of air pressure change in the simulation tool. The air pressure change is affected by the overfill amount of petroleum. The more overfilled, the greater the air pressure. Through the numerical simulation of the air pressure increase, the internal air pressure increase data of the petrochemical equipment tank is obtained. This step combines the internal air pressure increase data of the petrochemical equipment tank and the petroleum overfill data, and uses the finite element analysis (FEA) method to analyze the stress increase of the inner wall of the petrochemical equipment tank. By inputting information such as air pressure increase data, the force exerted by the overfilled liquid on the inner wall of the tank, and the elastic modulus and yield strength of the tank body material, the stress of the inner wall is calculated. The stress analysis mainly considers the pressure change caused by the increase in air pressure on the inner wall of the tank, and further combines the physical properties of the tank body material for simulation. The calculation results of the stress increase can reflect the load-bearing situation and structural safety of the inner wall of the petrochemical equipment tank under different overfilling conditions. This process generates the inner wall stress increase data of the petrochemical equipment tank. Taking the inner wall stress increase data and the air pressure change data as inputs, the deformation behavior of the tank body is simulated and analyzed using the elastic mechanics model. By considering factors such as the geometric shape, material properties, and internal air pressure of the tank body, the deformation trend of the petrochemical equipment tank under different working conditions is simulated. The deformation trend analysis includes the evaluation of phenomena such as longitudinal and transverse deformation, local protrusion and shrinkage of the tank body. Through numerical calculation using finite element software, the deformation trend data of the petrochemical equipment tank is obtained.

[0127] Preferably, step S213 includes the following steps:

[0128] Analyze the pressure state of the inner wall connection points according to the internal air pressure increase data of the petrochemical equipment tank to obtain the pressure state data of the inner wall connection points;

[0129] Detect the local stress concentration of the inner wall connection points for the pressure state data of the inner wall connection points to obtain the local gravitational concentration data of the inner wall connection points;

[0130] Measure the height of the petroleum in the petrochemical equipment tank based on the data of overfilling of petroleum in the tank, and obtain the data of the height of the petroleum in the petrochemical equipment tank;

[0131] Obtain the stored petroleum density data; calculate the bottom liquid pressure of the petrochemical equipment tank according to the data of the height of the petroleum in the petrochemical equipment tank and the stored petroleum density data, and obtain the data of the bottom liquid pressure of the petrochemical equipment tank;

[0132] Based on the data of the bottom liquid pressure of the petrochemical equipment tank and the data of local gravitational concentration at the inner wall connection points, analyze the stress growth of the inner wall of the petrochemical equipment, and obtain the data of the stress growth of the inner wall of the petrochemical equipment.

[0133] In the embodiments of the present invention, according to the internal air pressure growth data of the petrochemical equipment tank, combined with the structural characteristics and materials of the tank body, the pressure state of the inner wall connection points of the petrochemical equipment tank is analyzed. The specific operations include inputting the tank body structure parameters (such as connection point positions, geometric dimensions, etc.) and air pressure data, and using mechanical analysis tools to analyze the pressure of the inner wall connection points. By calculating the stress distribution around the connection points, the pressure levels borne by the connection points under different air pressure conditions are evaluated. The pressure state of the inner wall connection points is usually affected by air pressure, liquid gravity, and the external environment of the tank body. Therefore, by analyzing these parameters, the pressure state data of the inner wall connection points under different working environments can be obtained. Using the pressure state data of the inner wall connection points of the petrochemical equipment tank, local stress concentration detection is performed on the connection points. The specific operation is to calculate the local stress of the inner wall connection points using a stress analysis model (such as the finite element analysis method). By setting the pressure data at the inner wall connection points, combined with the geometric shape, material properties, etc. of the connection points, and applying the stress concentration formula, the stress concentration areas around the connection points are identified. This analysis focuses on whether stress concentration occurs at the connection points under the action of pressure, especially whether there are high-stress areas around the connection points, which may lead to potential rupture risks or structural fatigue problems. The output local gravitational concentration data. This step measures the actual height of the oil in the tank by combining the overfilling data of the petrochemical equipment tank. The operation process includes measuring the height of the liquid in the petrochemical equipment tank in real time or regularly according to the filling amount and distribution characteristics of the oil, through the liquid level gauge on the inner wall of the tank or through ultrasonic ranging equipment. During the measurement process, the overfilling data collected by the sensor is used to confirm the filling position of the oil and determine the position of the liquid level in the tank. Based on this information, the actual height data of the oil can be obtained. The density data of the stored oil is obtained from the operation data of the petrochemical equipment tank. This data usually comes from the actual chemical composition analysis of the oil or is obtained through experimental measurement. In order to accurately reflect the changes of the oil under different environmental conditions, considering that the density of the oil changes with temperature, pressure, and composition, it is necessary to collect the density values under specific conditions. Through the data acquisition system, this data is used for subsequent calculations, including the calculation of the bottom liquid pressure and stress analysis. This step uses the oil height data and the density data of the oil in the petrochemical equipment tank to calculate the pressure of the liquid at the bottom of the tank, and inputs the oil height and density data into the liquid pressure calculation formula. The liquid pressure calculation formula is usually: P = ρ·g·h, where P is the pressure, ρ is the liquid density, g is the acceleration due to gravity, and h is the liquid height. The pressure generated by the bottom liquid is calculated through this formula, and this pressure increases with the increase of the oil height. During this process, the uniformity of the liquid layer and the stability of the density must be considered to ensure the accuracy of the calculation.Obtain the liquid pressure data at the bottom of the petrochemical equipment tank. Combine the liquid pressure data at the bottom of the petrochemical equipment tank and the local gravitational concentration data at the inner wall connection points. Conduct stress growth analysis on the inner wall of the petrochemical equipment through a structural mechanics model. The bottom liquid pressure will be input as a force. Combine the local stress concentration data at the inner wall connection points and use the finite element analysis method to conduct stress growth analysis on the inner wall of the petrochemical equipment tank. This analysis focuses on the inner wall stress changes caused by the increase in liquid pressure and local stress concentration, especially the distribution of high stress areas. Through this process, the stress growth trend data of the inner wall of the petrochemical equipment tank can be obtained.

[0134] Preferably, step S22 includes the following steps:

[0135] Step S221: Obtain the storage environment data of the petrochemical equipment tank; collect the humid environment of the storage environment according to the storage environment data of the petrochemical equipment tank to obtain the humid data of the storage environment of the petrochemical equipment tank;

[0136] Step S222: Calculate the generation probability of corrosion medium for the humid data of the storage environment of the petrochemical equipment tank based on the simulation model data of the petrochemical equipment tank to obtain the generation probability data of the outer wall corrosion medium;

[0137] Step S223: Calculate the pitting probability of the outer wall for the generation probability data of the outer wall corrosion medium to obtain the pitting probability data of the outer wall of the equipment tank;

[0138] Step S234: Estimate the corrosion diffusion based on the pitting probability data of the outer wall of the equipment tank to obtain the corrosion diffusion data of the outer wall of the equipment tank;

[0139] Step S225: Measure the temperature fluctuation of the storage environment of the petrochemical equipment tank to obtain the temperature fluctuation data of the storage environment of the tank;

[0140] Step S226: Calculate the growth trend of the thermal stress of the outer wall of the equipment tank according to the temperature fluctuation data of the storage environment to obtain the growth trend data of the thermal stress of the outer wall of the equipment tank;

[0141] Step S227: Conduct damage detection on the outer wall of the petrochemical equipment tank based on the growth trend data of the thermal stress of the outer wall of the equipment tank and the corrosion diffusion data of the outer wall of the equipment tank to obtain the damage data of the outer wall of the petrochemical equipment tank.

[0142] In the embodiments of the present invention, relevant data of the storage environment of petrochemical equipment tanks are collected in real time by installing environmental monitoring devices (such as temperature and humidity sensors). The specific operation is to set multiple sensors around the petrochemical equipment tanks to regularly or real-time measure environmental parameters such as temperature and humidity. Through the data acquisition system, these data are recorded and the humidity condition of the storage environment is analyzed. Humidity data is a key factor affecting the corrosion of the outer wall of petrochemical equipment tanks. Therefore, the collected humidity data will be used for the subsequent calculation of the generation probability of corrosive media. In addition, the humidity information collected by the sensors needs to be uploaded to the control system through the data transmission module. In this step, according to the humidity data of the storage environment of the petrochemical equipment tanks, the generation probability of corrosive media is calculated through a simulation model. Parameters such as humidity data, environmental temperature, humidity, and the corrosion resistance of the tank body material are input into the simulation model. The simulation model, based on these input data, simulates the probability of the presence of corrosive media exposed on the outer wall of the petrochemical equipment tanks, such as the presence probability of moisture, salts, or chemical gases. The generation of corrosive media is usually related to humidity, temperature, and the concentration of external pollutants. Through model calculation, the generation probability of corrosive media for each outer wall area can be obtained. According to the corrosive media generation probability data obtained in the previous step, the pitting probability of the outer wall is calculated. Pitting is a local phenomenon of metal corrosion, usually occurring in an environment where there are corrosive media and the metal surface is uneven. In this step, according to the generated corrosive media generation probability data, combined with the material characteristics, surface treatment status, and environmental factors of the outer wall of the equipment tank, a pitting model is used for calculation. The pitting probability calculation depends on factors such as humidity, temperature, and medium concentration. By analyzing these factors, the pitting probability data for different areas of the outer wall can be obtained. Based on the outer wall pitting probability data, the prediction of corrosion propagation is carried out. Corrosion propagation refers to the process by which the corrosion process spreads from the initial pitting point to an area. According to the outer wall pitting probability data, combined with the material, thickness, and protection measures of the outer wall of the petrochemical equipment tank, a corrosion propagation model is used for prediction. Specifically, by calculating the diffusion path and speed of the corrosive media on the surface of the outer wall of the equipment tank after pitting occurs, the direction and degree of corrosion propagation are determined. The prediction of corrosion propagation usually takes into account environmental factors (such as humidity and temperature changes), operating conditions, and the physical characteristics of the outer wall of the tank (such as surface roughness, etc.). The obtained corrosion propagation data is used to monitor the temperature fluctuations of the storage environment of the petrochemical equipment tank through devices such as temperature sensors or infrared temperature detectors. The specific operation is to arrange multiple temperature sensors at different positions of the equipment tank to record the temperature changes of the storage environment in real time. The temperature fluctuation data includes parameters such as the fluctuation range and change rate of the environmental temperature at different time periods. Temperature fluctuations have an important impact on the thermal stress changes of the outer wall of petrochemical equipment tanks. Therefore, this process needs to be accurately measured and recorded. The collected temperature fluctuation data will be used as the basic data for calculating the growth trend of thermal stress. According to the temperature fluctuation data of the storage environment, the growth trend of the thermal stress of the outer wall of the equipment tank is calculated.The specific operations include inputting temperature fluctuation data and factors such as the material properties, thickness, and thermal expansion coefficient of the outer wall of the equipment tank into a thermal stress analysis model. Thermal stress is usually caused by temperature gradients resulting from environmental temperature changes. The stress model takes into account the temperature fluctuations on the outer wall of the tank to calculate the growth trend of thermal stress. Through thermal stress calculation, the stress changes borne by the outer wall of the equipment tank under different temperature fluctuations are obtained. Combining the thermal stress growth trend data of the outer wall of the equipment tank and the corrosion diffusion data, damage detection of the outer wall of the petrochemical equipment tank is carried out. Through the thermal stress growth trend data, the influence of stress caused by temperature fluctuations on the outer wall material is analyzed. At the same time, the corrosion diffusion data is used to evaluate the expansion and damage of the corrosion area. Combining these two factors, a mechanical analysis model is used to calculate the degree of damage to the outer wall and predict the types of cracks, spalling, or damage caused by the damage. Through this comprehensive analysis, the damage data of the outer wall of the equipment tank is obtained.

[0143] Preferably, step S24 includes the following steps:

[0144] Step S241: Statistically analyze the deformation positions of the inner wall of the petrochemical equipment tank based on the deformation trend data of the inner wall of the petrochemical equipment tank to obtain the deformation position data of the inner wall of the petrochemical equipment tank;

[0145] Step S242: Detect the defect overlapping areas of the petrochemical equipment tank according to the deformation position data of the inner wall of the petrochemical equipment tank and the thickness attenuation data of the outer wall of the petrochemical equipment tank to obtain the defect overlapping area data of the petrochemical equipment tank;

[0146] Step S243: Calculate the local stress superposition of the defect overlapping areas of the petrochemical equipment tank to obtain the local stress superposition data of the petrochemical equipment tank;

[0147] Step S244: Estimate the rigidity attenuation of the petrochemical equipment tank according to the defect overlapping area data of the petrochemical equipment tank and the local stress superposition data of the petrochemical equipment tank to obtain the rigidity attenuation data of the petrochemical equipment tank;

[0148] Step S245: Conduct an abnormal superposition analysis of the petrochemical equipment tank based on the rigidity attenuation data of the petrochemical equipment tank and the local stress superposition data of the petrochemical equipment tank to obtain the abnormal superposition data of the petrochemical equipment tank.

[0149] In the embodiments of the present invention, deformation trend data of the inner wall of a petrochemical equipment tank is obtained. These data are usually collected regularly by inner wall sensors or monitoring devices (such as strain gauges or laser scanning devices), reflecting the deformation of the inner wall of the equipment tank. Data analysis tools or algorithms are used to statistically analyze the deformation data, and analyze the deformation changes of the inner wall of the petrochemical equipment tank in different regions. By performing position analysis on the deformation trend data, high-risk regions of inner wall deformation are identified, and corresponding deformation position data is generated. This step relies on the inner wall deformation position data and outer wall thickness attenuation data of the petrochemical equipment tank. The inner wall deformation position data provides the deformation degree of each region of the inner wall, while the outer wall thickness attenuation data reflects the damage or corrosion condition of the outer wall. By integrating these two types of data, defect regions where there are overlaps on the inner and outer walls of the equipment tank are detected. The specific operation includes using coordinate matching technology to combine the deformation position data with the thickness attenuation data to determine which regions have an intersection between inner wall deformation and outer wall thickness attenuation. These regions are the defect overlap regions, which are high-risk regions for greater damage to the equipment tank. Based on the defect overlap region data, local stress superposition calculation is performed. The local stress superposition calculation mainly focuses on the stress changes generated by the intersection of inner and outer wall defects within the defect overlap region. A finite element analysis (FEA) model is used to simulate the stress in the defect overlap region, and the inner wall deformation data and outer wall thickness attenuation data are input. During the calculation process, the influence of multiple factors such as external pressure, internal pressure, and temperature fluctuations on the equipment tank needs to be considered. Through stress analysis, local stress superposition data for each overlap region is obtained. Combining the defect overlap region data and the local stress superposition data, an estimation of the rigidity attenuation of the equipment tank is performed. Rigidity attenuation refers to the process in which the overall rigidity of the equipment tank decreases due to defects and stress concentration. The specific operation is to combine the stress superposition data with the mechanical properties of the tank body material (such as Young's modulus, Poisson's ratio, etc.) and perform rigidity analysis using a structural mechanics model. During the simulation, the different parts of the equipment tank are weighted according to the degree of stress superposition, so as to obtain the rigidity attenuation degree of the entire tank body, and the rigidity attenuation data of the petrochemical equipment tank is obtained. Combining the rigidity attenuation data of the petrochemical equipment tank and the local stress superposition data, abnormal superposition analysis is performed. The purpose of the abnormal superposition analysis is to identify whether there are abnormal situations in the equipment tank caused by the combined action of multiple factors (such as inner and outer wall defects, stress concentration, and rigidity attenuation). During the analysis process, through multi-dimensional analysis of the rigidity attenuation data and the local stress superposition data, a comprehensive algorithm (such as weighted average, data fusion, etc.) is used to obtain the comprehensive abnormality degree of the equipment tank in different regions. The abnormal superposition data can reveal the risk of structural damage or functional failure of the petrochemical equipment tank under specific regions and specific conditions.

[0150] Preferably, step S3 includes the following steps:

[0151] Step S31: Analyze the accumulation of material damage to the petrochemical equipment tank based on the abnormal superimposed data of the petrochemical equipment tank to obtain the material damage accumulation data of the petrochemical equipment tank;

[0152] Step S32: Estimate the structural fatigue condition of the petrochemical equipment tank based on the material damage accumulation data of the petrochemical equipment tank to obtain the structural fatigue data of the petrochemical equipment tank;

[0153] Step S33: Conduct an analysis of the attenuation of the structural stability of the equipment tank based on the structural fatigue data of the petrochemical equipment tank and the material damage accumulation data of the petrochemical equipment tank to obtain the structural stability attenuation data of the equipment tank;

[0154] Step S34: Calculate the rupture probability of the petrochemical tank based on the structural fatigue data of the petrochemical equipment tank and the structural stability attenuation data of the equipment tank to obtain the rupture probability data of the petrochemical equipment tank.

[0155] As an example of the present invention, refer to Figure 3 As shown, in this example, step S3 includes:

[0156] Step S31: Analyze the accumulation of material damage to the petrochemical equipment tank based on the abnormal superimposed data of the petrochemical equipment tank to obtain the material damage accumulation data of the petrochemical equipment tank;

[0157] In the embodiment of the present invention, based on the abnormal superimposed data of the petrochemical equipment tank, the high-stress areas and defect overlapping areas on the inner and outer walls of the equipment tank are identified. On this basis, the material damage of the equipment tank is analyzed using the material damage accumulation theory (such as the Miner linear cumulative damage theory). The specific operations include: According to the stress distribution data of the abnormal superimposed area, combined with the mechanical parameters of the equipment tank body material (such as yield strength, fatigue limit, elongation) and the working load data during long-term operation, calculate the damage accumulation degree of each area. By introducing a damage factor, the damage accumulation degree of each area is quantified to obtain the material damage accumulation data of the petrochemical equipment tank. The damage accumulation data reflects the attenuation degree of the material performance of the equipment tank under the influence of high stress and defects.

[0158] Step S32: Estimate the structural fatigue condition of the petrochemical equipment tank based on the material damage accumulation data of the petrochemical equipment tank to obtain the structural fatigue data of the petrochemical equipment tank;

[0159] In the embodiments of the present invention, based on the accumulated data of material damage of the petrochemical equipment tank, the structural fatigue condition is further estimated. The key to fatigue condition estimation lies in determining the fatigue life of the equipment tank under long-term cyclic loads. Based on the material damage data, representative damage areas are selected, and combined with the working environment parameters of the equipment tank (such as pressure fluctuations, temperature cycles, mechanical vibrations, etc.), the fatigue load cycles are statistically analyzed. Secondly, fatigue analysis methods (such as the S-N curve method or the crack propagation method) are used to quantitatively calculate the structural fatigue state of the tank body, and evaluate the fatigue accumulation degree and remaining life of the structure under different working conditions. Through the above analysis, the structural fatigue data of the equipment tank are obtained, including the fatigue damage degree and remaining fatigue life of the equipment tank in each high-risk area.

[0160] Step S33: Based on the structural fatigue data of the petrochemical equipment tank and the accumulated data of material damage of the petrochemical equipment tank, perform an analysis on the attenuation of the structural stability of the equipment tank to obtain the data on the attenuation of the structural stability of the equipment tank;

[0161] In the embodiments of the present invention, by integrating the structural fatigue data and material damage data of the petrochemical equipment tank, an analysis on the attenuation of the equipment structure stability is carried out. The specific operation is as follows: By combining the structural fatigue data and the accumulated damage data, determine the comprehensive influence of fatigue damage and material property attenuation on the stiffness and strength of the tank body structure. Secondly, use the finite element analysis (FEA) method to perform a stability analysis on the overall structure of the equipment tank, and simulate the attenuation trend of stability under different pressure, temperature, and stress conditions. During the analysis process, focus on the structural deformation and the degree of stability attenuation of the key parts of the tank body (such as welding points, connection areas, local stress concentration areas). By quantifying the structural stability attenuation index, the data on the attenuation of the structural stability of the equipment tank are obtained.

[0162] Step S34: Calculate the rupture probability of the petrochemical tank based on the structural fatigue data of the petrochemical equipment tank and the data on the attenuation of the structural stability of the equipment tank to obtain the data on the rupture probability of the petrochemical equipment tank.

[0163] In the embodiments of the present invention, in this step, based on the structural fatigue data and the data on the attenuation of the structural stability of the petrochemical equipment tank, calculate the probability of the equipment tank rupturing. Select the high-risk areas of the equipment tank body, and combine the structural fatigue degree and the data on the attenuation of stability. Use probability risk assessment methods (such as Monte Carlo simulation or reliability analysis methods) to evaluate the rupture probability of the equipment tank under various loads and working conditions. By inputting the fatigue accumulation data, material property attenuation data, and the data on the attenuation of the structural stability, use the rupture failure criterion (such as the Von Mises criterion or the crack propagation criterion) to judge the rupture risk of the tank body structure. Finally, perform a statistical analysis on the rupture probabilities of all risk areas to obtain the overall data on the rupture probability of the petrochemical equipment tank.

[0164] Preferably, step S4 includes the following steps:

[0165] Step S41: Calculate the leakage probability data of the petrochemical equipment tank based on the petrochemical equipment tank rupture probability data and the petrochemical equipment tank structure fatigue data, and obtain the petrochemical equipment tank leakage probability data;

[0166] Step S42: Conduct a safety risk assessment of the petrochemical equipment tank according to the petrochemical equipment tank leakage probability data and the petrochemical equipment tank rupture probability data, and obtain the petrochemical equipment tank safety risk data;

[0167] Step S43: Conduct an abnormal assessment of the health status of the petrochemical equipment tank based on the petrochemical equipment tank safety risk data and the petrochemical equipment tank leakage probability data, and obtain the petrochemical equipment tank health status abnormal data;

[0168] Step S44: Repair the petrochemical equipment tank according to the petrochemical equipment tank health status abnormal data to obtain the petrochemical equipment tank repair data.

[0169] In the embodiments of the present invention, by combining the rupture probability data and structural fatigue data of petrochemical equipment tanks, the leakage probability calculation is carried out for different regions of the equipment tanks. The specific operations include: carefully screening the high fatigue damage regions, local stress concentration regions, and regions with attenuated structural stability to clarify the distribution of potential leakage points. Subsequently, based on the material mechanical property parameters (such as crack growth rate, fracture toughness, etc.) and fatigue cumulative data, a leakage failure probability model (such as the Paris equation based on crack growth rate or leakage failure function) is used to calculate the leakage probability of each high-risk point. By statistically analyzing the probability data of each potential leakage point and using the method of superposing failure probabilities, the leakage probability data of the overall petrochemical equipment tank is obtained. Based on the leakage probability data and rupture probability data, a safety risk assessment of the petrochemical equipment tank is carried out. The specific method includes: inputting the leakage probability and rupture probability data into a risk assessment model, and combining the operating parameters of the equipment tank (such as internal pressure, temperature fluctuation, tank volume) and environmental impact factors (such as corrosion medium concentration, temperature and humidity conditions) to calculate the overall and local safety risk values of the equipment tank. During the risk assessment process, the quantitative risk assessment (QRA) method is adopted. By setting risk level thresholds, the safety risks are classified, and high-risk regions and high-risk operating conditions are identified. Through the above operations, the safety risk data of the petrochemical equipment tank is obtained, including the overall risk level, risk distribution in each region, and the impact degree of potential tank failures, etc. Based on the safety risk data and leakage probability data of the petrochemical equipment tank, an abnormal assessment of the health state of the equipment tank is carried out. For the regions with high leakage probability and high risk levels, combined with historical operating data and real-time monitoring data, the identification of abnormal points in the state of the equipment tank is carried out. Secondly, using a health state assessment algorithm (such as a health assessment method based on threshold determination or a data-driven health scoring method), a quantitative analysis of the health state of each region of the equipment tank is carried out to generate abnormal health state indicators. By calculating the degree of deviation of the health state from the normal threshold, the abnormal regions and severity of the health state of the equipment tank are identified, and the abnormal health state data of the petrochemical equipment tank is obtained, including the distribution of abnormal regions, the values of abnormal indicators, and the impact degree on the operating state of the equipment tank. According to the abnormal health state data of the petrochemical equipment tank, repair operations are carried out for the abnormal regions and states of the equipment tank. The specific implementation process includes: by analyzing the abnormal health state data in detail, locating the high-risk regions and abnormal types (such as crack growth, wall thickness thinning, pitting corrosion damage) of the equipment tank. Subsequently, according to the abnormal type and severity, repair techniques and processes are selected, such as specific repair methods like welding repair, coating reinforcement, local plate replacement, crack reinforcement, etc. For the crack growth region, repair is carried out using welding repair and heat treatment processes; for the corrosion pitting region, corrosion removal and anti-corrosion coating reinforcement are carried out.After the repair operation is completed, repair effect detection is carried out, including ultrasonic non-destructive testing, pressure testing, stress testing, etc., to ensure that the repair quality meets the safety standards, and petrochemical equipment tank repair data is generated. The data content includes the repair area, repair process parameters, repair effect evaluation results, and subsequent status monitoring suggestions, etc.

[0170] The above are only specific embodiments of the present invention, enabling those skilled in the art to understand or implement the present invention. Various modifications to these embodiments will be obvious to those skilled in the art, and the general principles defined herein can be implemented in other embodiments without departing from the spirit or scope of the present invention. Therefore, the present invention will not be limited to these embodiments shown herein, but rather to the broadest scope consistent with the principles and novel features invented herein.

Claims

1. A petrochemical equipment tank health status assessment method based on multidimensional data, characterized in that: The following steps are involved: Step S1: acquiring petrochemical equipment tank data; collecting petrochemical equipment tank structure data according to the petrochemical equipment tank data, thereby obtaining petrochemical equipment tank structure data; constructing a petrochemical equipment tank simulation model based on the petrochemical equipment tank data and the petrochemical equipment tank structure data, thereby obtaining petrochemical equipment tank simulation model data; Step S2: performing deformation trend analysis of the inner wall of the petrochemical equipment tank according to the petrochemical equipment tank simulation model data to obtain deformation trend data of the inner wall of the petrochemical equipment tank; performing damage detection of the outer wall of the petrochemical equipment tank according to the petrochemical equipment tank simulation model data to obtain damage data of the outer wall of the petrochemical equipment tank; performing abnormal superposition analysis of the petrochemical equipment tank based on the deformation trend data of the inner wall of the petrochemical equipment tank and the damage data of the outer wall of the petrochemical equipment tank to obtain abnormal superposition data of the petrochemical equipment tank; Step S3: Performing equipment tank structure stability attenuation analysis based on the abnormal superposition data of the petrochemical equipment tank to obtain equipment tank structure stability attenuation data; performing petrochemical tank rupture probability calculation based on the equipment tank structure stability attenuation data to obtain petrochemical equipment tank rupture probability data; Step S4: Based on the petrochemical equipment tank rupture probability data, perform an abnormal health status assessment of the petrochemical equipment tank to obtain abnormal health status data of the petrochemical equipment tank; perform petrochemical equipment tank repair on the petrochemical equipment tank data according to the abnormal health status data of the petrochemical equipment tank to obtain petrochemical equipment tank repair data.

2. The petrochemical equipment tank health status assessment method based on multidimensional data according to claim 1 is characterized in that: Step S1 includes the following steps: Step S11: Obtain petrochemical equipment tank data; Step S12: collecting the structure of the petrochemical equipment tank according to the petrochemical equipment tank data, thereby obtaining the petrochemical equipment tank structure data; Step S13: acquiring the material of the petrochemical equipment tank according to the petrochemical equipment tank data, thereby obtaining the material data of the petrochemical equipment tank; Step S14: constructing a petrochemical equipment tank simulation model based on the petrochemical equipment tank material data and the petrochemical equipment tank structure data to obtain the petrochemical equipment tank simulation model data.

3. The petrochemical equipment tank health status assessment method based on multidimensional data according to claim 2 is characterized in that: Step S14 includes the following steps: Step S141: Perform material strength test of the petrochemical equipment tank according to the material data of the petrochemical equipment tank to obtain the material strength data of the petrochemical equipment tank; Step S142: measuring the outer diameter of the tank according to the petrochemical equipment tank structure data to obtain the outer diameter data of the petrochemical equipment tank; Step S143: Calculate the internal storage capacity according to the petrochemical equipment tank structure data to obtain the internal storage capacity data of the petrochemical equipment tank; Step S144: Calculate the storage carrying capacity of the petrochemical equipment tank according to the internal storage capacity data of the petrochemical equipment tank and the material strength data of the petrochemical equipment tank to obtain the storage carrying capacity data of the petrochemical equipment tank; Step S145: constructing a rectangular coordinate system of the petrochemical equipment tank space according to the internal storage capacity data of the petrochemical equipment tank and the external diameter data of the petrochemical equipment tank, and obtaining the rectangular coordinate system data of the petrochemical equipment tank space; Step S146: constructing a petrochemical equipment tank simulation model according to the petrochemical equipment tank spatial rectangular coordinate system data and the petrochemical equipment tank storage carrying capacity data to obtain the petrochemical equipment tank simulation model data.

4. The petrochemical equipment tank health status assessment method based on multidimensional data according to claim 1 is characterized in that: Step S2 includes the following steps: Step S21: performing deformation trend analysis of the inner wall of the petrochemical equipment tank according to the petrochemical equipment tank simulation model data to obtain deformation trend data of the inner wall of the petrochemical equipment tank; Step S22: performing damage detection on the outer wall of the petrochemical equipment tank according to the petrochemical equipment tank simulation model data to obtain damage data on the outer wall of the petrochemical equipment tank; Step S23: performing thickness attenuation calculation of the outer wall of the petrochemical equipment tank based on the damage data of the outer wall of the petrochemical equipment tank to obtain thickness attenuation data of the outer wall of the petrochemical equipment tank; Step S24: performing abnormal superposition analysis of the petrochemical equipment tank based on the petrochemical equipment tank inner wall deformation trend data and the petrochemical equipment tank outer wall thickness attenuation data to obtain abnormal superposition data of the petrochemical equipment tank.

5. The petrochemical equipment tank health status assessment method based on multidimensional data according to claim 4 is characterized in that: Step S21 includes the following steps: Step S211: simulating the overfilling condition of petroleum according to the petrochemical equipment tank simulation model data to obtain the overfilling data of petrochemical equipment tank; Step S212: estimating the internal gas pressure growth of the petrochemical equipment tank based on the petroleum overfilling data of the petrochemical equipment tank, and obtaining the internal gas pressure growth data of the petrochemical equipment tank; Step S213: performing stress growth analysis on the inner wall of the petrochemical equipment tank according to the internal air pressure growth data of the petrochemical equipment tank and the petroleum overfilling data of the petrochemical equipment tank, and obtaining stress growth data on the inner wall of the petrochemical equipment tank; Step S214: performing deformation trend analysis of the petrochemical equipment tank based on the stress growth data of the inner wall of the petrochemical equipment tank and the gas pressure growth data inside the petrochemical equipment tank to obtain deformation trend data of the petrochemical equipment tank.

6. The petrochemical equipment tank health status assessment method based on multidimensional data according to claim 4 is characterized in that: Step S213 includes the following steps: According to the internal gas pressure growth data of the petrochemical equipment tank, the pressure state of the inner wall connection point is analyzed to obtain the pressure state data of the inner wall connection point; Performing a local stress concentration test on the inner wall connection point pressure state data to obtain local gravity concentration data on the inner wall connection point; The oil height data of the petrochemical equipment tank is obtained by measuring the oil height data according to the oil overfilling data of the petrochemical equipment tank; Obtaining the stored oil density data; calculating the liquid pressure at the bottom of the petrochemical equipment tank according to the petroleum height data and the stored oil density data of the petrochemical equipment tank, and obtaining the liquid pressure data at the bottom of the petrochemical equipment tank; Based on the liquid pressure data at the bottom of the petrochemical equipment tank and the local gravity concentration data at the inner wall connection point, the stress growth analysis of the inner wall of the petrochemical equipment is carried out to obtain the stress growth data of the inner wall of the petrochemical equipment.

7. The petrochemical equipment tank health status assessment method based on multidimensional data according to claim 4 is characterized in that: Step S22 includes the following steps: Step S221: acquiring storage environment data of petrochemical equipment tanks; collecting storage environment humidity data according to the storage environment data of petrochemical equipment tanks to obtain storage environment humidity data of petrochemical equipment tanks; Step S222: Calculate the probability of corrosive medium generation for the storage environment humidity data of the petrochemical equipment tank according to the petrochemical equipment tank simulation model data to obtain the probability data of corrosive medium generation for the outer wall; Step S223: Calculate the probability of pitting corrosion of the outer wall based on the probability data of the outer wall corrosive medium generation, and obtain the probability data of pitting corrosion of the outer wall of the equipment tank; Step S224: performing corrosion diffusion estimation based on the pitting probability data of the equipment tank outer wall to obtain corrosion diffusion data of the equipment tank outer wall; Step S225: measuring the storage environment temperature fluctuation of the petrochemical equipment tank storage environment data to obtain the tank storage environment temperature fluctuation data; Step S226: Calculate the growth trend of thermal stress on the outer wall of the equipment tank according to the storage environment temperature fluctuation data to obtain the growth trend data of thermal stress on the outer wall of the equipment tank; Step S227: Perform damage detection on the outer wall of the petrochemical equipment tank based on the thermal stress growth trend data of the outer wall of the equipment tank and the corrosion diffusion data of the outer wall of the equipment tank to obtain damage data on the outer wall of the petrochemical equipment tank.

8. The petrochemical equipment tank health status assessment method based on multidimensional data according to claim 4 is characterized in that: Step S24 includes the following steps: Step S241: performing statistics on the inner wall deformation position of the petrochemical equipment tank based on the inner wall deformation trend data of the petrochemical equipment tank to obtain the inner wall deformation position data of the petrochemical equipment tank; Step S242: performing defect overlap area detection on the petrochemical equipment tank according to the inner wall deformation position data of the petrochemical equipment tank and the outer wall thickness attenuation data of the petrochemical equipment tank to obtain defect overlap area data of the petrochemical equipment tank; Step S243: performing local stress superposition calculation on the defect overlap area data of the petrochemical equipment tank to obtain local stress superposition data of the petrochemical equipment tank; Step S244: estimating the rigidity attenuation of the petrochemical equipment tank according to the defect overlap area data of the petrochemical equipment tank and the local stress superposition data of the petrochemical equipment tank, and obtaining the rigidity attenuation data of the petrochemical equipment tank; Step S245: performing abnormal superposition analysis of the petrochemical equipment tank based on the rigid attenuation data of the petrochemical equipment tank and the local stress superposition data of the petrochemical equipment tank to obtain abnormal superposition data of the petrochemical equipment tank.

9. The petrochemical equipment tank health status assessment method based on multidimensional data according to claim 1 is characterized in that: Step S3 includes the following steps: Step S31: performing a petrochemical equipment tank material damage accumulation analysis based on the petrochemical equipment tank abnormal superposition data to obtain petrochemical equipment tank material damage accumulation data; Step S32: Estimating the fatigue status of the petrochemical equipment tank structure according to the accumulated data of damage to the petrochemical equipment tank material, and obtaining the fatigue data of the petrochemical equipment tank structure; Step S33: performing equipment tank structure stability attenuation analysis based on petrochemical equipment tank structure fatigue data and petrochemical equipment tank material damage accumulation data to obtain equipment tank structure stability attenuation data; Step S34: Calculate the petrochemical tank rupture probability based on the petrochemical equipment tank structure fatigue data and the equipment tank structure stability attenuation data to obtain the petrochemical equipment tank rupture probability data.

10. The petrochemical equipment tank health status assessment method based on multidimensional data according to claim 1, characterized in that: Step S4 includes the following steps: Step S41: Calculate the leakage probability of the petrochemical equipment tank based on the petrochemical equipment tank rupture probability data and the petrochemical equipment tank structure fatigue data to obtain the petrochemical equipment tank leakage probability data; Step S42: Performing a safety risk assessment on the petrochemical equipment tank according to the petrochemical equipment tank leakage probability data and the petrochemical equipment tank rupture probability data to obtain the petrochemical equipment tank safety risk data; Step S43: performing abnormal health status assessment of the petrochemical equipment tank based on the petrochemical equipment tank safety risk data and the petrochemical equipment tank leakage probability data to obtain abnormal health status data of the petrochemical equipment tank; Step S44: repairing the petrochemical equipment tank according to the abnormal health status data of the petrochemical equipment tank to obtain petrochemical equipment tank repair data.

Images