Operation and maintenance method, system and equipment of high-pressure chemical conveying equipment and medium

Abstract

The invention relates to the technical field of operation and maintenance of industrial equipment, and provides an operation and maintenance method, system and equipment of high-pressure chemical conveying equipment and a medium. Based on the first fluid state information corresponding to each first node, updating the flow state of the fluid twin body in the twin body of the equipment; sending second twinborn fluid state information acquired by each second virtual node on the equipment twinborn body to a corresponding second node; and receiving a material microscopic damage quantitative analysis result sent by each second node, and generating a target operation and maintenance scheme based on each material microscopic damage quantitative analysis result. The method solves the problem that in the prior art, a prospective operation and maintenance decision cannot be provided due to lack of early fault recognition capability.

Description

Technical Field

[0001] This invention relates to the field of industrial equipment operation and maintenance technology, and in particular to a method, system, equipment and medium for the operation and maintenance of high-pressure chemical conveying equipment. Background Technology

[0002] High-pressure chemical conveying equipment serves as the core artery of process industries such as petrochemicals and coal chemicals. It operates for extended periods in harsh environments with high temperatures, high pressures, and corrosive media, demanding stringent safety and reliability. Current maintenance methods for high-pressure chemical conveying equipment primarily rely on periodic shutdowns for inspection and online monitoring based on fixed thresholds. Both methods lack the ability to identify early-stage faults and cannot provide proactive maintenance decisions. Summary of the Invention

[0003] The main objective of this invention is to provide a method, system, equipment, and medium for the operation and maintenance of high-pressure chemical conveying equipment, aiming to solve the problem that existing operation and maintenance methods lack the ability to identify early faults and cannot provide forward-looking operation and maintenance decisions.

[0004] In a first aspect, embodiments of the present invention provide a method for the operation and maintenance of high-pressure chemical conveying equipment, including: The flow state of the fluid twin within the device twin is updated based on the first fluid state information collected by multiple first nodes in real time. The second twin fluid state information collected by each second virtual node on the device twin is sent to its corresponding second node, so that each second node determines whether to trigger material micro-damage quantification analysis based on the second fluid state information it collected and the second twin fluid state information it received, and performs material micro-damage quantification analysis on its corresponding device component when it determines that material micro-damage quantification analysis has been triggered. Receive the material micro-damage quantification analysis results sent by each second node, and generate the target operation and maintenance plan based on the material micro-damage quantification analysis results.

[0005] Secondly, embodiments of the present invention provide an operation and maintenance system for high-pressure chemical conveying equipment, comprising: The update module is used to acquire first fluid state information collected by multiple first nodes in real time, and update the flow state of the fluid twin in the device twin based on the first fluid state information corresponding to each first node. The sending module is used to send the second twin fluid state information collected by each second virtual node on the device twin to its corresponding second node, so that each second node can determine whether to trigger material micro-damage quantification analysis based on the second fluid state information it collected and the second twin fluid state information it received, and when it is determined that material micro-damage quantification analysis is triggered, it performs material micro-damage quantification analysis on its corresponding device component. The generation module is used to receive the material micro-damage quantification analysis results sent by each second node, and generate the target operation and maintenance plan based on the material micro-damage quantification analysis results.

[0006] Thirdly, embodiments of the present invention also provide a terminal device, the terminal device including a processor, a memory, a computer program stored in the memory and executable by the processor, and a data bus for realizing communication between the processor and the memory, wherein when the computer program is executed by the processor, it implements the steps of any of the operation and maintenance methods for high-pressure chemical conveying equipment provided in this specification.

[0007] Fourthly, embodiments of the present invention also provide a storage medium for computer-readable storage, characterized in that the storage medium stores one or more programs, which can be executed by one or more processors to implement the operation and maintenance method steps of any of the high-pressure chemical conveying equipment provided in this specification.

[0008] This invention provides an operation and maintenance method, system, equipment, and medium for high-pressure chemical conveying equipment. The method first acquires first fluid state information collected by multiple first nodes in real time, and updates the flow state of a fluid twin within the equipment twin based on the first fluid state information corresponding to each first node. This constructs a fluid twin synchronized with the fluid in the high-pressure chemical conveying equipment, generating a mirror image reflecting the macroscopic operating conditions of the equipment in digital space, providing an effective physical benchmark for local state analysis. Then, by sending the second twin fluid state information collected by each second virtual node on the equipment twin to its corresponding second node, each second node can compare its collected second fluid state information with the received second twin fluid state information. The system determines whether a material micro-damage quantification analysis has been triggered. When such analysis is triggered, it performs a quantification analysis on the corresponding equipment component. This helps identify subtle, systematic deviations that characterize early material damage and triggers in-depth damage quantification analysis, enabling the prediction of early-stage faults that are difficult to detect using traditional threshold monitoring methods. Finally, by receiving the material micro-damage quantification analysis results from each second node and generating target maintenance plans based on these results, the system automatically generates forward-looking maintenance plans that balance safety and economy. This transforms early warnings into specific, actionable maintenance plans, solving the problem that existing technologies lack early fault identification capabilities and therefore cannot provide forward-looking maintenance decisions. Attached Figure Description

[0009] To more clearly illustrate the technical solutions of the embodiments of this application, the drawings used in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0010] Figure 1 A flowchart illustrating an operation and maintenance method for high-pressure chemical conveying equipment provided in an embodiment of the present invention; Figure 2 This is a schematic diagram of the modular structure of an operation and maintenance system for high-pressure chemical conveying equipment provided in an embodiment of the present invention; Figure 3 This is a schematic block diagram of the structure of a terminal device provided in an embodiment of the present invention. Detailed Implementation

[0011] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0012] The flowchart shown in the attached diagram is for illustrative purposes only and does not necessarily include all content and operations / steps, nor does it necessarily have to be performed in the order described. For example, some operations / steps can be broken down, combined, or partially merged, so the actual execution order may change depending on the actual situation.

[0013] It should be understood that the terminology used in this specification is for the purpose of describing particular embodiments only and is not intended to limit the invention. As used in this specification and the appended claims, the singular forms “a,” “an,” and “the” are intended to include the plural forms unless the context clearly indicates otherwise.

[0014] This invention provides a method, system, equipment, and medium for the operation and maintenance of high-pressure chemical conveying equipment. The operation and maintenance method for this high-pressure chemical conveying equipment can be applied to terminal devices, which can be electronic devices such as tablets, laptops, desktop computers, personal digital assistants, and wearable devices. The terminal device can be a server or a server cluster.

[0015] The following detailed description of some embodiments of the present invention is provided in conjunction with the accompanying drawings. Unless otherwise specified, the following embodiments and features can be combined with each other.

[0016] Please refer to Figure 1 , Figure 1 This is a flowchart illustrating a method for the operation and maintenance of high-pressure chemical conveying equipment, provided as an embodiment of the present invention.

[0017] like Figure 1 As shown, the operation and maintenance method of the high-pressure chemical conveying equipment includes steps S100 to S300.

[0018] Step S100: Real-time acquisition of first fluid state information collected by multiple first nodes, and update the flow state of the fluid twin in the device twin based on the first fluid state information corresponding to each first node.

[0019] The first node is a sensing node deployed at key sections of the main trunk line of the high-pressure chemical conveying equipment. Specific locations include the inlet and outlet of the main pump, the start and end points of the main pipeline, the inlet and outlet of the heat exchanger group for both hot and cold media, and the equipment's main return point. The first node is equipped with a pressure sensor for measuring pressure, a temperature sensor for measuring temperature, a flow velocity sensor for measuring flow rate, and a flow sensor for measuring volumetric flow rate.

[0020] The equipment twin refers to a virtual device constructed in digital space based on the three-dimensional geometric model of the high-pressure chemical conveying equipment, the topological connections of its components, and the physical characteristics of its components, capable of simulating the overall behavior of the high-pressure chemical conveying equipment. The fluid twin refers to the virtual fluid within the equipment twin used to simulate the internal flow state of the medium within the high-pressure chemical conveying equipment.

[0021] Specifically, for each of the first nodes, each sensor set at the first node collects the first fluid state information in real time. The edge processor at the first node sends the first fluid state information and the spatial coordinates corresponding to the first node to the central processor. The central processor updates the flow state of the fluid twin in the device twin based on the first fluid state information corresponding to each of the first nodes.

[0022] In some embodiments, updating the flow state of the fluid twin within the device twin based on the first fluid state information corresponding to each first node includes: Step S121: Assign the first fluid state information corresponding to each first node to its corresponding position in the fluid twin.

[0023] Specifically, for each of the first nodes, after receiving the first fluid state information sent by the edge processor of the first node, the central processing unit finds the position point corresponding to the first node in the fluid twin according to the spatial coordinates of the first node, and assigns the parameter values ​​in the first fluid state information corresponding to the first node, such as pressure value, temperature value and flow rate value, to the parameter variables in the fluid twin corresponding to the position of the first node.

[0024] Step S122: Based on the fluid dynamics conservation equations built into the fluid twin, solve the global flow state of the fluid twin after the assignment to update the flow state of the fluid twin.

[0025] The fluid dynamics conservation equations are a set of governing equations describing the conservation of mass, momentum, and energy. in, For fluid density, For time, For fluid velocity vector, For gradient operators, For hydrostatic pressure, For fluid viscous stress tensor, Force per unit mass of fluid For tensor product, The total energy per unit mass of fluid. The fluid thermodynamic temperature, is the thermal conductivity of the fluid.

[0026] Specifically, after the assignment in step S121 is completed, the central processing unit drives the solver of the fluid twin to start working. The solver uses the assigned boundary conditions and the current state field inside the fluid twin as initial conditions, and uses the finite volume method to numerically solve the built-in fluid dynamics conservation equations. Specifically, the entire computational domain of the fluid twin is divided into a large number of non-overlapping grid cells. Each equation in the governing equations is integrated on each grid cell. The volume integral is transformed into an area integral over the grid cells using the Gaussian divergence theorem, resulting in a set of equations that can solve for the state of the twin fluid (pressure, velocity, temperature) at the central node of each grid cell. After solving the equations, the flow state parameters at the central node of each grid cell inside the fluid twin, including pressure, velocity, temperature, and wall shear stress calculated from the velocity field, are updated.

[0027] Understandably, in steps S121 to S122, firstly, by assigning the first fluid state information of the first node to the corresponding position of the fluid twin, the boundary conditions of the fluid twin are made consistent with the real-time operating state of the fluid within the high-pressure chemical conveying equipment, laying a data foundation for constructing an accurate digital mirror. Then, by globally solving the built-in fluid dynamics conservation equations, the flow state of all regions of the fluid twin is calculated, helping to obtain a complete virtual fluid dynamics state field that reflects the macroscopic operating conditions of the high-pressure chemical conveying equipment.

[0028] Step S200: Send the second twin fluid state information collected by each second virtual node on the device twin to its corresponding second node, so that each second node determines whether to trigger material micro-damage quantification analysis based on the second fluid state information it collected and the second twin fluid state information it received, and performs material micro-damage quantification analysis on its corresponding device component when it determines that material micro-damage quantification analysis has been triggered.

[0029] The first node and the second node are nodes located at different positions on the high-pressure chemical conveying equipment. The second node is a sensing node deployed locally or near equipment components prone to fatigue, corrosion, or erosion. Specific locations include the root of flange connection bolts, near the valve seat sealing surface, the heat-affected zone of pipe welds, and cavitation-prone areas on the inner wall of pump casings. The sensors installed at the second node include a high-frequency pressure sensor for capturing high-frequency dynamic pressure pulsations, an infrared thermometer or distributed optical fiber for monitoring micro-area temperature gradients, a strain gauge for measuring micro-strain on structural surfaces, and an acoustic emission sensor for detecting acoustic emission signals generated by cavitation or micro-leakage.

[0030] The second virtual node refers to a virtual measuring point established on the device twin based on the actual spatial location of the second node, used to collect the state information of the fluid twin at that location. It should be noted that the "second" in "second virtual node" is a naming convention used to correspond with the "second" in "second node" to facilitate readers' understanding of the correspondence between "second node" and "second virtual node," and is not related to the order of the two.

[0031] Specifically, for each of the second virtual nodes, the central processing unit sends the second twin fluid state information collected by each virtual sensor set at the second virtual node to the edge processor of the second node corresponding to the second virtual node, so that the edge processor of the second node determines whether to trigger material micro-damage quantification analysis based on the second fluid state information collected by each sensor set at the second node and the received second twin fluid state information, and performs material micro-damage quantification analysis on the equipment component corresponding to the second node when it is determined that material micro-damage quantification analysis is triggered.

[0032] In some embodiments, the second node determines whether to trigger quantitative analysis of material micro-damage based on the second fluid state information it has collected and the second twin fluid state information it has received, including: Step A: Calculate the state difference information between the second fluid state information and the second twin fluid state information.

[0033] Specifically, for each sensor of the second node, the parameter difference corresponding to the sensor in the second fluid state information is obtained by subtracting the virtual parameter value corresponding to the sensor in the second twin fluid state information from the parameter value corresponding to the sensor in the second fluid state information. The parameter differences corresponding to each sensor constitute the state difference information. After obtaining the state difference information, the state difference information is marked with a timestamp corresponding to the current time. The timestamp is accurate to the millisecond level. For example, the timestamp is 2025-12-02 15:36:45.123, where 2025-12-02 represents the current date (year-month-day) and 15:36:45.123 represents the current time (hour:minute:second.millisecond). The state difference information marked with the timestamp is stored in the edge database corresponding to the second node.

[0034] Step B: Perform statistical analysis on the state difference information within the preset historical time period to determine whether the state difference information has a trend of changing from random fluctuations to systematic deviations; wherein, the end time of the preset historical time period is the current time.

[0035] The current state difference information is the state difference information calculated in step A, and the preset historical time period is at least one month.

[0036] Specifically, the second node extracts all state difference information within the preset historical time period from its corresponding edge database, and performs statistical analysis on each extracted state difference information to determine whether the state difference information has a trend of changing from random fluctuations to systematic deviations.

[0037] In some embodiments, the step of statistically analyzing the state difference information within a preset historical time period to determine whether the state difference information shows a trend of transformation from random fluctuations to systematic deviations includes: Step B1: For each sensor of the second node, arrange the parameter differences corresponding to the state difference information of the sensor in the preset historical time period in a time sequence to obtain the parameter difference sequence corresponding to the sensor, and determine whether the parameter difference sequence has a monotonic trend.

[0038] The monotonic trend is either monotonically increasing or monotonically decreasing.

[0039] Specifically, for each sensor in the second node, when the last preset number of parameter differences in the parameter difference sequence corresponding to the sensor monotonically increase or monotonically decrease, it is determined that the parameter difference sequence corresponding to the sensor has a monotonic trend. For example, if the parameter difference sequence includes 100,000 parameter differences, and the parameter difference sequence starts to monotonically increase or monotonically decrease from the 99,910th parameter difference, then it is determined that the parameter difference sequence has a monotonic trend.

[0040] Step B2: If the parameter difference sequence corresponding to any of the sensors has a monotonic trend, it is determined that the state difference information has a trend of changing from random fluctuation to systematic deviation; if the parameter difference sequence corresponding to each of the sensors does not have a monotonic trend, it is determined that the state difference information does not have a trend of changing from random fluctuation to systematic deviation.

[0041] Understandably, steps B1 to B2 first involve performing time-series analysis on the parameter differences of each sensor within the preset historical time period. This provides effective data for distinguishing between random noise characterizing normal equipment fluctuations and systematic change patterns that may indicate early damage. Then, by determining whether the parameter difference sequence corresponding to any sensor exhibits a monotonic trend, it helps to capture early signals indicating that the local state is beginning to deviate continuously from theoretical expectations, and promptly triggers more in-depth analysis.

[0042] Step C: If it exists, determine whether to trigger the material micro-damage quantitative analysis; if it does not exist, determine whether to not trigger the material micro-damage quantitative analysis.

[0043] Understandably, steps A through C first involve calculating the state difference information between physical measurements and twin theoretical values, transforming macroscopic, mixed signals into differential quantities that can be directly used for anomaly detection, providing basic data for trend analysis. Then, by performing long-term trend statistical analysis on these differential quantities, random interference can be filtered out, weak, persistent system deviations can be identified, and intelligent early warning of potential problems can be achieved. Finally, based on the existence of system deviation trends, an automatic judgment is made to determine whether in-depth microscopic damage quantification analysis of the component is needed without human intervention.

[0044] In some embodiments, the second node performs a quantitative analysis of the material micro-damage of its corresponding equipment component, including: Step D: Call the material damage evolution model corresponding to the equipment component.

[0045] Specifically, for each of the aforementioned equipment components, the corresponding material damage evolution model refers to a mathematical and physical model established based on the material used in the component, its failure mechanism, and specific service environment. This model quantitatively describes the changes in its microscopic damage (such as fatigue crack propagation, corrosion rate, and wear) with time and load. Specific types may include the Paris crack propagation model based on fracture mechanics, the corrosion rate model based on electrochemical kinetics, and the wear model based on the Arcard formula. The material damage evolution models corresponding to different equipment components are not consistent because the selection of the model and parameter calibration depend on the specific material of the component, its heat treatment process, geometric structural characteristics, and the local load and chemical environment in which it is located.

[0046] Step E: Calculate the material damage evolution model based on the second fluid state information sequence corresponding to the second node within a preset historical time period to obtain the material micro-damage quantitative analysis results.

[0047] The preset historical time period has been described in step B and will not be repeated here. The second fluid state information collected by each sensor of the second node is timestamped and stored in the edge database corresponding to the second node. The second fluid state information collected by each sensor of the second node within the preset historical time period is then arranged chronologically to obtain a sequence of second fluid state information within the preset historical time period.

[0048] The results of the material micro-damage quantitative analysis include: equipment component identifier, micro-damage type, current severity quantitative indicators (such as equivalent crack length and corrosion depth), evolution rate prediction (such as crack propagation rate), and remaining life estimated based on the current state and damage rate.

[0049] Specifically, the calculation process in step E is executed by the edge processor of the second node. The edge processor inputs the extracted second fluid state information sequence into the material damage evolution model. The processing logic inside the model converts the second fluid state information (such as local pressure, temperature, and shear stress) at each time step into microscopic driving forces acting on the material (such as local stress amplitude and corrosion current density). The model starts with the initial state of the material at the beginning of the sequence and integrates step by step according to the time step to simulate the accumulation and evolution process of internal damage of the material under the action of historical load sequences. When the integration progresses to the end of the sequence (i.e., the current time), the state variable output by the model is the current quantitative index of the material microscopic damage (such as the current crack length). At the same time, the model calculates the current damage evolution rate based on the current state and the material constitutive relationship, and predicts the remaining lifetime based on the damage evolution rate and the failure threshold. These calculation results are integrated to generate the material microscopic damage quantitative analysis results.

[0050] Understandably, steps D through E first involve calling a material damage evolution model that matches the characteristics of the component, providing a mathematical tool that conforms to physical laws for the quantitative analysis of damage, ensuring the scientific validity and accuracy of the analysis results. Then, the sequence of second fluid state information actually experienced by the component is input into the model for calculation, reproducing the evolution process of material damage in digital space, which can quantify the current state, development speed and remaining life of the damage, providing a direct quantitative basis for operation and maintenance decisions.

[0051] Step S300: Receive the material micro-damage quantification analysis results sent by each second node, and generate the target operation and maintenance plan based on the material micro-damage quantification analysis results.

[0052] Specifically, for each of the second nodes, if the edge processor of the second node performs a quantitative analysis of material micro-damage on the device component corresponding to the second node, the edge processor marks the material micro-damage quantitative analysis result with the device component identifier of the device component corresponding to the second node, and sends the material micro-damage quantitative analysis result marked with the device component identifier to the central processor. The central processor generates a target operation and maintenance plan based on the received material micro-damage quantitative analysis results.

[0053] In some embodiments, generating the target operation and maintenance plan based on the quantitative analysis results of microscopic damage of each material includes: Step S321: Based on the preset operation and maintenance decision knowledge base, perform comprehensive risk assessment processing on the quantitative analysis results of microscopic damage of each material to obtain the component risk assessment list corresponding to the quantitative analysis results of microscopic damage of each material.

[0054] The operation and maintenance decision knowledge base refers to a structured rules database that stores equipment component classification systems, severity assessment rules for various types of damage, component criticality weights, failure consequence level coefficients, and risk assessment calculation formulas.

[0055] Specifically, for each of the material micro-damage quantitative analysis results, based on the equipment component identifier recorded in the material micro-damage quantitative analysis results, the corresponding risk assessment logic is matched in the operation and maintenance decision knowledge base for the material micro-damage quantitative analysis results, and the risk assessment logic is executed based on the material micro-damage quantitative analysis results to generate a component risk assessment list corresponding to the material micro-damage quantitative analysis results.

[0056] The risk assessment logic refers to a set of calculation rules customized for specific types of components and damage modes, used to calculate their comprehensive risk score and risk level. It encapsulates normalization methods, score mapping relationships, weighting coefficients, and synthesis formulas.

[0057] Specifically, the risk assessment logic executes as follows: The risk assessment logic reads the current severity quantification index from the material micro-damage quantification analysis results and normalizes it to a current state index (such as relative crack propagation) using a predefined physical failure threshold for the component in the knowledge base. Simultaneously, it extracts the evolution rate prediction and remaining lifetime, and queries the built-in severity level table based on the current state index to obtain a basic severity score. Based on the evolution rate prediction, it queries the urgency coefficient table to obtain a risk adjustment factor. It reads the component criticality weight and the consequence severity coefficient of this type of damage mode from the knowledge base. Substituting the above four items (basic severity score, risk adjustment factor, component criticality weight, and consequence severity coefficient) into the embedded weighted calculation formula (e.g., a multiplicative model), it calculates the comprehensive risk score and determines the risk level based on the score range. Simultaneously, it generates a decision response timeframe based on the remaining lifetime. Finally, it outputs a component risk assessment list containing items such as the equipment component identifier, risk level, comprehensive risk score, and decision response timeframe.

[0058] Step S322: Obtain dynamic management data from the enterprise management system, and execute a preset multi-objective constraint optimization algorithm based on the risk assessment list of each component and the dynamic management data to generate an initial operation and maintenance plan.

[0059] The dynamic management data refers to variable data related to operation and maintenance decisions that are acquired in real time from the enterprise asset management system, production execution system, and human resources system. This data mainly includes spare parts inventory quantity and procurement cycle, future production plans and equipment downtime windows, and the skills and scheduling status of available maintenance teams. The multi-objective constrained optimization algorithm refers to a mathematical programming algorithm that aims to minimize the total expected operation and maintenance cost while simultaneously satisfying constraints such as safety, resource availability, and production feasibility; for example, a mixed-integer linear programming algorithm.

[0060] Specifically, the central processing unit's decision engine first synchronizes the latest dynamic management data. Then, it constructs an optimization model by combining all entries from the component risk assessment list with the dynamic management data. The model's decision variable is the start intervention time allocated to each component to be intervened with. The objective function is to minimize the sum of planned maintenance costs, unplanned downtime risk costs, and additional resource scheduling costs. Constraints include: the start time of each task must be earlier than its "decision response time limit" (safety constraint); at any given time, the total demand for various maintenance resources (manpower, spare parts, tools) must not exceed its availability (resource constraint); maintenance tasks must be scheduled within the equipment's downtime planning window (production constraint). The decision engine calls the solver to solve this model. Upon successful solution, it outputs an initial operation and maintenance plan, which clarifies the suggested maintenance time, required resource list, and preliminary global execution order for each component to be intervened with.

[0061] Step S323: Perform feasibility verification and conflict resolution on the initial operation and maintenance plan to generate the target operation and maintenance plan.

[0062] Specifically, the decision engine performs a detailed simulation of the initial maintenance plan. First, based on the maintenance task knowledge base, it verifies whether the specific spare parts, specialized tools, and skilled work teams required for each task are indeed available within the suggested time window, and whether environmental conditions (such as whether process isolation is required) are met. Simultaneously, it checks whether different tasks have conflicts over the same scarce resource (such as a single large crane) at the micro-timescale. When feasibility issues or resource conflicts are detected, the engine handles them according to preset resolution rules. These rules follow the principles of "priority first" and "minimum disturbance," prioritizing the plans of high-risk or high-urgency tasks and attempting to eliminate conflicts by fine-tuning the start times of other tasks and exploring resource alternatives (such as work teams with equivalent qualifications), while minimizing the overall cost increase of the plan. This process iterates until all conflicts are resolved and the plan is fully executable. The final target maintenance plan is a detailed action plan that includes precise time scheduling, complete resource allocation, no conflicts, and specific operational requirements.

[0063] Understandably, steps S321 to S323 involve: first, standardizing the risk assessment of micro-damage results using an operation and maintenance decision knowledge base, transforming physical damage data into a unified, horizontally comparable risk metric, providing a basis for prioritization in global decision-making; then, executing a multi-objective constraint optimization algorithm by combining real-time dynamic management data, calculating the theoretically lowest-cost collaborative maintenance plan for all high-risk components under complex real-world business constraints, achieving optimal matching of resources and needs in time and space; and finally, ensuring the executability of the theoretical solution in the physical world by performing engineering feasibility verification and conflict resolution on the optimized initial solution.

[0064] The method provided in this embodiment firstly acquires first fluid state information collected by multiple first nodes in real time, and updates the flow state of the fluid twin within the equipment twin based on the first fluid state information corresponding to each first node, thus constructing a fluid twin synchronized with the fluid in the high-pressure chemical conveying equipment. This generates a mirror image reflecting the macroscopic operating conditions of the equipment in digital space, providing an effective physical benchmark for local state analysis. Then, by sending the second twin fluid state information collected by each second virtual node on the equipment twin to its corresponding second node, each second node determines whether to trigger microscopic material damage based on its collected second fluid state information and the received second twin fluid state information. The system performs material micro-damage quantification analysis, and when it determines that a material micro-damage quantification analysis is triggered, it performs material micro-damage quantification analysis on the corresponding equipment components. This helps to identify weak systematic deviations that characterize early material damage and triggers in-depth damage quantification analysis, enabling the prediction of early fault hazards that are difficult to detect using traditional threshold monitoring methods. Finally, by receiving the material micro-damage quantification analysis results sent by each second node and generating target operation and maintenance plans based on these results, the system automatically generates forward-looking operation and maintenance plans that balance safety and economy. This transforms early warnings into specific and executable maintenance action plans, solving the problem that existing technologies cannot provide forward-looking operation and maintenance decisions due to a lack of early fault identification capabilities.

[0065] Please see Figure 2 , Figure 2 This application provides an operation and maintenance system 100 for high-pressure chemical conveying equipment. The system includes an update module 110, a sending module 120, and a generation module 130. The update module 110 is used to acquire first fluid state information collected by multiple first nodes in real time, and update the flow state of the fluid twin within the equipment twin based on the first fluid state information corresponding to each first node. The sending module 120 is used to send second twin fluid state information collected by each second virtual node on the equipment twin to its corresponding second node, so that each second node determines whether to trigger material micro-damage quantification analysis based on its collected second fluid state information and the received second twin fluid state information, and performs material micro-damage quantification analysis on its corresponding equipment component when the trigger is determined. The generation module 130 is used to receive the material micro-damage quantification analysis results sent by each second node, and generate a target operation and maintenance plan based on the material micro-damage quantification analysis results.

[0066] In some implementations, the operation and maintenance system 100 for high-pressure chemical conveying equipment can be applied to terminal equipment.

[0067] It should be noted that those skilled in the art will understand that, for the sake of convenience and brevity, the specific working process of the operation and maintenance system 100 for the high-pressure chemical conveying equipment described above can be referred to the corresponding process in the aforementioned embodiment of the operation and maintenance method for high-pressure chemical conveying equipment, and will not be repeated here.

[0068] Please see Figure 3 , Figure 3 This is a schematic block diagram of the structure of a terminal device 200 provided in an embodiment of the present invention.

[0069] like Figure 3 As shown, the terminal device 200 includes a processor 201 and a memory 202, which are connected via a bus 203, such as an I2C (Inter-integrated Circuit) bus.

[0070] Specifically, processor 201 provides computing and control capabilities to support the operation of the entire terminal device. Processor 201 can be a Central Processing Unit (CPU), but it can also be other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. Among these, the general-purpose processor can be a microprocessor or any conventional processor.

[0071] Specifically, the memory 202 can be a Flash chip, a read-only memory (ROM) disk, an optical disk, a USB flash drive, or a portable hard drive, etc.

[0072] Those skilled in the art will understand that Figure 3 The structure shown is merely a block diagram of a portion of the structure related to the embodiments of the present invention, and does not constitute a limitation on the terminal device to which the embodiments of the present invention are applied. A specific server may include more or fewer components than those shown in the figure, or combine certain components, or have different component arrangements.

[0073] The processor is used to run a computer program stored in a memory, and when executing the computer program, implements any of the operation and maintenance methods for high-pressure chemical conveying equipment provided in the embodiments of the present invention.

[0074] In one embodiment, the processor is configured to run a computer program stored in memory, and when executing the computer program, perform the following steps: The flow state of the fluid twin within the device twin is updated based on the first fluid state information collected by multiple first nodes in real time. The second twin fluid state information collected by each second virtual node on the device twin is sent to its corresponding second node, so that each second node determines whether to trigger material micro-damage quantification analysis based on the second fluid state information it collected and the second twin fluid state information it received, and performs material micro-damage quantification analysis on its corresponding device component when it determines that material micro-damage quantification analysis has been triggered. Receive the material micro-damage quantification analysis results sent by each second node, and generate the target operation and maintenance plan based on the material micro-damage quantification analysis results.

[0075] It should be noted that those skilled in the art will understand that, for the sake of convenience and brevity, the specific working process of the terminal device 200 described above can be referred to the corresponding process in the aforementioned embodiment of the operation and maintenance method for high-pressure chemical conveying equipment, and will not be repeated here.

[0076] This invention also provides a storage medium for computer-readable storage, wherein the storage medium stores one or more programs that can be executed by one or more processors to implement the steps of any of the operation and maintenance methods for high-pressure chemical conveying equipment provided in the specification of this invention.

[0077] The storage medium can be an internal storage unit of the terminal device described in the foregoing embodiments, such as the hard drive or memory of the terminal device. Alternatively, the storage medium can be an external storage device of the terminal device, such as a plug-in hard drive, Smart Media Card (SMC), Secure Digital (SD) card, or Flash Card equipped on the terminal device.

[0078] Those skilled in the art will understand that all or some of the steps, systems, or apparatuses disclosed above, and their functional modules / units, can be implemented as software, firmware, hardware, or suitable combinations thereof. In hardware embodiments, the division between functional modules / units mentioned in the above description does not necessarily correspond to the division of physical components; for example, a physical component may have multiple functions, or a function or step may be performed collaboratively by several physical components. Some or all physical components may be implemented as software executed by a processor, such as a central processing unit, digital signal processor, or microprocessor, or as hardware, or as an integrated circuit, such as an application-specific integrated circuit. Such software may be distributed on a computer-readable medium, which may include computer storage media (or non-transitory media) and communication media (or transient media). As is known to those skilled in the art, the term computer storage media includes volatile and non-volatile, removable and non-removable media implemented in any method or technology for storing information (such as computer-readable instructions, data structures, program modules, or other data). Computer storage media include, but are not limited to, RAM, ROM, EEPROM, flash memory or other memory technologies, CD-ROM, digital versatile disc (DVD) or other optical disc storage, magnetic cartridges, magnetic tape, disk storage or other magnetic storage devices, or any other medium that can be used to store desired information and can be accessed by a computer. Furthermore, it is well known to those skilled in the art that communication media typically contain computer-readable instructions, data structures, program modules, or other data in modulated data signals such as carrier waves or other transmission mechanisms, and may include any information delivery medium.

[0079] It should be understood that the term "and / or" as used in this specification and the appended claims refers to any combination and all possible combinations of one or more of the associated listed items, and includes such combinations. It should be noted that, herein, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or system that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or system. Without further limitation, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or system that includes that element.

[0080] The sequence numbers of the above embodiments of the present invention are merely for descriptive purposes and do not represent the superiority or inferiority of the embodiments. The above descriptions are only specific embodiments of the present invention, but the scope of protection of the present invention is not limited thereto. Any person skilled in the art can easily conceive of various equivalent modifications or substitutions within the technical scope disclosed in the present invention, and these modifications or substitutions should all be covered within the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be determined by the scope of the claims.

Claims

1. A method for the operation and maintenance of high-pressure chemical conveying equipment, characterized in that, include: The flow state of the fluid twin within the device twin is updated based on the first fluid state information collected by multiple first nodes in real time. The second twin fluid state information collected by each second virtual node on the device twin is sent to its corresponding second node, so that each second node determines whether to trigger material micro-damage quantification analysis based on the second fluid state information it collected and the second twin fluid state information it received, and performs material micro-damage quantification analysis on its corresponding device component when it determines that material micro-damage quantification analysis has been triggered. Receive the material micro-damage quantification analysis results sent by each second node, and generate the target operation and maintenance plan based on the material micro-damage quantification analysis results.

2. The operation and maintenance method for high-pressure chemical conveying equipment according to claim 1, characterized in that, The step of updating the flow state of the fluid twin within the device twin based on the first fluid state information corresponding to each first node includes: The first fluid state information corresponding to each of the first nodes is assigned to its corresponding position in the fluid twin; The global flow state of the fluid twin is solved based on the fluid dynamics conservation equations built into the fluid twin, thereby updating the flow state of the fluid twin.

3. The operation and maintenance method for high-pressure chemical conveying equipment according to claim 1, characterized in that, The second node determines whether to trigger quantitative analysis of material micro-damage based on the second fluid state information it collects and the second twin fluid state information it receives, including: Calculate the state difference information between the second fluid state information and the second twin fluid state information; Statistical analysis is performed on the state difference information within a preset historical time period to determine whether the state difference information shows a trend of transformation from random fluctuations to systematic deviations; wherein, the end time of the preset historical time period is the current time. If present, determine the trigger for quantitative analysis of microscopic damage to the material. If it does not exist, it is determined that the material micro-damage quantitative analysis will not be triggered.

4. The operation and maintenance method for high-pressure chemical conveying equipment according to claim 3, characterized in that, The step of statistically analyzing the state difference information within a preset historical time period to determine whether the state difference information shows a trend of transformation from random fluctuations to systematic deviations includes: For each sensor in the second node, the parameter differences corresponding to the state difference information of the sensor in the preset historical time period are arranged in time sequence to obtain the parameter difference sequence corresponding to the sensor, and it is determined whether the parameter difference sequence has a monotonic trend. If the parameter difference sequence corresponding to any of the sensors has a monotonic trend, it is determined that the state difference information has a trend of changing from random fluctuations to systematic deviations; If the parameter difference sequence corresponding to each of the sensors does not have a monotonic trend, it is determined that the state difference information does not have a trend of changing from random fluctuations to systematic deviations.

5. The operation and maintenance method for high-pressure chemical conveying equipment according to claim 1, characterized in that, The second node performs quantitative analysis of the material micro-damage of its corresponding equipment components, including: Call the material damage evolution model corresponding to the equipment component; The material damage evolution model is calculated based on the second fluid state information sequence corresponding to the second node within a preset historical time period to obtain the quantitative analysis results of material micro-damage.

6. The operation and maintenance method for high-pressure chemical conveying equipment according to claim 1, characterized in that, The generation of the target operation and maintenance plan based on the quantitative analysis results of microscopic damage of each material includes: Based on the preset operation and maintenance decision knowledge base, the results of the quantitative analysis of microscopic damage of each material are subjected to comprehensive risk assessment, and a risk assessment list of components corresponding to the quantitative analysis results of microscopic damage of each material is obtained. The system acquires dynamic management data from the enterprise management system and executes a preset multi-objective constraint optimization algorithm based on the risk assessment list of each component and the dynamic management data to generate an initial operation and maintenance plan. The initial operation and maintenance plan is subjected to feasibility verification and conflict resolution to generate the target operation and maintenance plan.

7. The operation and maintenance method for high-pressure chemical conveying equipment according to claim 6, characterized in that, The pre-set operation and maintenance decision knowledge base performs comprehensive risk assessment processing on the quantitative analysis results of microscopic damage of each material, resulting in a component risk assessment list corresponding to the quantitative analysis results of microscopic damage of each material, including: For each of the material micro-damage quantitative analysis results, based on the equipment component identifier recorded in the material micro-damage quantitative analysis results, the corresponding risk assessment logic is matched in the operation and maintenance decision knowledge base for the material micro-damage quantitative analysis results, and the risk assessment logic is executed based on the material micro-damage quantitative analysis results to generate a component risk assessment list corresponding to the material micro-damage quantitative analysis results.

8. A maintenance system for high-pressure chemical conveying equipment, characterized in that, include: The update module is used to acquire first fluid state information collected by multiple first nodes in real time, and update the flow state of the fluid twin in the device twin based on the first fluid state information corresponding to each first node. The sending module is used to send the second twin fluid state information collected by each second virtual node on the device twin to its corresponding second node, so that each second node can determine whether to trigger material micro-damage quantification analysis based on the second fluid state information it collected and the second twin fluid state information it received, and when it is determined that material micro-damage quantification analysis is triggered, it performs material micro-damage quantification analysis on its corresponding device component. The generation module is used to receive the material micro-damage quantification analysis results sent by each second node, and generate the target operation and maintenance plan based on the material micro-damage quantification analysis results.

9. A terminal device, characterized in that, The terminal device includes a processor and a memory; The memory is used to store computer programs; The processor is used to execute the computer program and, in executing the computer program, implement the operation and maintenance method for the high-pressure chemical conveying equipment as described in any one of claims 1 to 7.

10. A computer storage medium for computer storage, characterized in that, The computer storage medium stores one or more programs, which can be executed by one or more processors to implement the operation and maintenance method of the high-pressure chemical conveying equipment as described in any one of claims 1 to 7.

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