Intelligent cloud platform architecture oriented to industrial internet

Abstract

The invention discloses an industrial internet-oriented intelligent cloud platform architecture, and relates to the technical field of industrial chemical intelligent cloud monitoring, and the platform collects equipment state data in real time through a chemical reactor integrated sensor group, transmits the equipment state data to a cloud end through the internet, and carries out the processing on a cloud platform, and obtains an equipment safety data group. Storing the data to a cloud storage system; the cloud platform extracts and filters the equipment security data set, analyzes and calculates a chemical reaction stability index HXF, and carries out primary evaluation on the reaction stability with a preset chemical reaction stability threshold A; and if the stability reaches the standard, triggering a secondary evaluation mechanism, further analyzing a chemical reaction stability index HXF and a wall surface pressure change coefficient Byl, calculating an equipment degradation index LHZ, judging the health condition of the equipment, generating an early warning report when necessary, and transmitting the early warning report to related personnel in real time through the Internet so as to take maintenance or shutdown measures in time.

Description

Technical Field

[0001] The present invention relates to the technical field of industrial chemical intelligent cloud monitoring, and in particular to an intelligent cloud platform architecture for the industrial Internet. Background Art

[0002] In modern industrial production, the Industrial Internet has gradually become a key infrastructure to promote the digitalization and intelligent transformation of the manufacturing industry. As the demand for automation and efficiency in the manufacturing industry continues to increase, more and more companies are beginning to use Industrial Internet technology to remotely monitor equipment, perform predictive maintenance, and perform data analysis to improve production efficiency, reduce maintenance costs, and extend equipment life. Especially in high-risk industries such as chemicals, oil and gas, the stability and safety of equipment are crucial. The Industrial Internet can help companies achieve real-time data collection, cloud analysis, and intelligent decision-making, thereby optimizing equipment performance during chemical reactions and ensuring the safe and stable operation of chemical reactions.

[0003] In the Chinese invention application with application publication number CN117589375A, a chemical safety detection method, system, terminal equipment and storage medium are disclosed. The sensitivity detection is performed on the corresponding gas monitoring points in the target chemical area, and the gas monitoring points are judged whether the detection abnormality occurs according to the corresponding sensitivity detection result. If the sensitivity detection result is normal, it is judged whether the gas monitoring point issues a first-level alarm signal. If it does, the number of the target gas monitoring points is further obtained. If the number is single, the corresponding associated gas monitoring points are obtained, and it is judged whether the associated gas monitoring points output the corresponding second-level alarm signal within the preset time interval. If it does, the number of the target associated gas monitoring points corresponding to the output of the second-level alarm signal is continuously obtained and analyzed. If the number exceeds the preset associated number threshold, it means that a hazardous gas leak has occurred in the current target chemical area. This application scheme can improve the detection effect of chemical safety.

[0004] In combination with the prior art, the above application still has the following deficiencies: In a large chemical plant, dozens of chemical reactors are operating at the same time. In order to ensure production efficiency and equipment safety, it is necessary to monitor the operating status of the reactor in real time and be able to perform preventive maintenance before problems occur. Due to reliance on single-point monitoring data, it is difficult to fully reflect the overall safety status of the chemical area, and there is a lack of dynamic assessment mechanism for equipment degradation. In addition, the sensitivity detection standard is not applicable to all possible gas types and leakage modes, which can easily cause false alarms or missed reports. This not only increases maintenance costs, but may also delay timely response to potential hazards and affect the safety management effect of chemical facilities. Summary of the invention

[0005] In view of the deficiencies in the prior art, the present invention provides an intelligent cloud platform architecture for the Industrial Internet, which solves the problems in the above-mentioned background technology.

[0006] To achieve the above objectives, the present invention is implemented through the following technical solutions: an intelligent cloud platform architecture for industrial Internet, including a data acquisition module, a cloud platform processing module, a cloud platform data extraction module, a cloud platform analysis module, a chemical reaction stability assessment module and an equipment degradation assessment module; The data acquisition module is used to install an integrated sensor group at the monitoring point of the chemical reactor to collect equipment status data in real time, and then upload the equipment status data to the cloud platform via the Internet; The cloud platform processing module is used to receive device status data in real time, perform preprocessing, obtain device safety data groups, and then store the device safety data groups in the cloud storage system; The cloud platform data extraction module is used to access the device safety data group in the cloud data history storage system, filter the device safety data group according to the required conditions, extract the real-time device safety data group and the filtered historical device safety data group, and transmit the extracted device safety data group to the cloud platform analysis module in real time; The cloud platform analysis module is used to perform summary calculations based on the extracted real-time equipment safety data group to obtain the inner cavity gas fluctuation coefficient Nqt, the fluid viscosity variation coefficient Lnd, the heat flow density fluctuation coefficient Rmd and the wall pressure variation coefficient Byl; The chemical reaction stability evaluation module is used to perform summary calculation based on the obtained inner cavity gas fluctuation coefficient Nqt, fluid viscosity variation coefficient Lnd and heat flow density fluctuation coefficient Rmd, obtain the chemical reaction stability index HXF, and perform an initial evaluation with the preset chemical reaction stability threshold A, and trigger a secondary evaluation mechanism based on the evaluation results; The equipment degradation assessment module is used to perform summary calculations based on the chemical reaction stability index HXF and the wall pressure variation coefficient Byl when the initial assessment shows that the equipment is working normally, obtain the equipment degradation index LHZ, perform a secondary assessment with the preset equipment degradation threshold B, and generate early warning information based on the assessment results.

[0007] Preferably, the data acquisition module includes a sensor acquisition unit and an Internet transmission unit; The sensor acquisition unit collects equipment status data in real time by setting monitoring points at different positions of the chemical reactor and installing an integrated sensor group in each monitoring point; The integrated sensor group includes a reaction generated gas concentration sensor, a flow meter, a pressure sensor and a heat flow sensor; The concentration qt of the gas generated by the reaction is directly collected by a gas concentration sensor; The gas flow F is directly collected by a flow meter; The inner cavity volume tj, wall thickness hd and equipment surface area mj are fixed parameters for chemical reactor design; The heat flow rl is directly collected by a heat flow sensor; The wall pressure bm and the external pressure wb are directly collected by pressure sensors; The Internet transmission unit connects the integrated sensor group to the cloud platform for communication via the Internet HTTPS protocol, and transmits the device status data to the cloud platform in real time.

[0008] Preferably, the cloud platform processing module includes a pre-processing unit and a cloud storage unit; The preprocessing unit is used to receive the device status data in real time, and perform data cleaning, denoising, format conversion and normalization processing to obtain a device safety data group; The equipment safety data group includes an inner cavity gas fluctuation factor data group, a wall pressure change data group, a heat flow density data group and a fluid viscosity variation factor data group; The inner cavity gas fluctuation factor data group includes the inner cavity volume tj, the reaction generated gas concentration qt and the gas flow rate F; The fluid viscosity variation factor data group includes fluid viscosity nd, inner cavity temperature wd and inner cavity pressure yl; The heat flux density data set includes equipment surface area mj and heat flux rl; The wall pressure change data group includes the wall pressure bm, the external pressure wb and the wall thickness hd; The cloud storage unit is used to store the device safety data group in real time in the cloud storage system. The cloud storage system includes a cloud data real-time storage system and a cloud data historical storage system. The cloud storage system classifies the device safety data group according to the data type, data source, sensor ID, sensor measurement value and collection timestamp, and stores it in real time in the cloud data real-time storage system, and transfers the previous set of data in the cloud data real-time storage system to the cloud data historical storage system.

[0009] Preferably, the cloud platform data extraction module includes a data access unit and a data extraction unit; The data access unit is used to access the device safety data group in the cloud data history storage system, and filter the data according to the required conditions based on the data type, data source, sensor ID, sensor measurement value and acquisition timestamp, and transmit the filtered data to the data extraction unit through the query interface; The data extraction unit is used to extract in real time the device safety data group in the cloud data real-time storage system and the historical device safety data group filtered by the data access unit, and transmit the extracted device safety data group to the cloud platform analysis module in real time.

[0010] Preferably, the cloud platform analysis module includes an inner cavity gas fluctuation calculation unit, a fluid viscosity variation calculation unit, a heat flow density fluctuation calculation unit and a wall pressure variation calculation unit; The inner cavity gas fluctuation calculation unit is used to perform summary calculation based on the acquired inner cavity gas fluctuation factor data group to obtain the inner cavity gas fluctuation coefficient Nqt; The inner cavity gas fluctuation coefficient Nqt is calculated and obtained by the following formula: ; Where N is the number of sampling times, qt i represents the concentration of the gas generated by the reaction at the i-th sampling, qt, avg It represents the average value of the gas concentration qt generated by N sampling reactions. represents the rate of change of gas flow rate F with time t, represents partial derivative; The fluid viscosity variation calculation unit is used to perform summary calculation based on the acquired fluid viscosity variation factor data group to obtain the fluid viscosity variation coefficient Lnd; The fluid viscosity variation coefficient Lnd is calculated by the following formula: ; Where, nd i represents the fluid viscosity nd of the i-th sampling, nd avg represents the average value of the viscosity nd of all sampled fluids, and N represents the number of sampling times; The heat flux density fluctuation calculation unit is used to perform summary calculation based on the acquired heat flux density data group to obtain the heat flux density fluctuation coefficient Rmd; The heat flux density fluctuation coefficient Rmd is calculated by the following formula: ; In the formula, represents the rate of change of heat flow rl with time t, T grad It represents the temperature gradient, the degree of temperature change per unit distance, and a represents the thermal conductivity.

[0011] Preferably, the wall pressure change calculation unit is used to perform summary calculation based on the acquired wall pressure change data group to obtain the wall pressure change coefficient Byl; The wall pressure variation coefficient Byl is calculated by the following formula: ; In the formula, It represents the rate of change of wall pressure bm with time t.

[0012] Preferably, the chemical reaction stability assessment module includes a chemical reaction stability calculation unit and a chemical reaction stability assessment unit; The chemical reaction stability calculation unit is used to perform summary calculation based on the obtained inner cavity gas fluctuation coefficient Nqt, fluid viscosity variation coefficient Lnd and heat flow density fluctuation coefficient Rmd to obtain a chemical reaction stability index HXF; The chemical reaction stability index HXF is calculated by the following formula: ; Wherein, e represents an exponential function, k1, k2 and k3 represent the weight coefficients of the inner cavity gas fluctuation coefficient Nqt, the fluid viscosity variation coefficient Lnd and the heat flow density fluctuation coefficient Rmd, respectively, and k1+k2+k3=1. The specific values ​​are set by the user according to the actual situation.

[0013] Preferably, the chemical reaction stability evaluation unit is used to access the equipment safety data group in the cloud data history storage system, analyze the historical chemical reaction stability average value through the cloud platform, perform a preset chemical reaction stability threshold A, and perform a preliminary evaluation with the obtained chemical reaction stability index HXF, and trigger a secondary evaluation mechanism based on the evaluation results. The specific evaluation scheme is as follows; When the chemical reaction stability index HXF ≥ the chemical reaction stability threshold A, it means that the equipment is working normally, maintaining normal monitoring, and triggering the secondary evaluation mechanism; When the chemical reaction stability index HXF is less than the chemical reaction stability threshold A, it indicates that the equipment is operating abnormally. At this time, the cloud platform generates a first warning report, transmits the first warning report to the mobile device of relevant personnel through the Internet, and notifies the relevant personnel to adjust the abnormal data.

[0014] Preferably, the equipment degradation assessment module includes an equipment degradation calculation unit and an equipment degradation assessment unit; The equipment degradation calculation unit is used to obtain the equipment degradation index LHZ by summarizing and calculating the chemical reaction stability index HXF and the wall pressure variation coefficient Byl obtained when the equipment is initially evaluated to be working normally; The equipment degradation index LHZ is calculated by the following formula: .

[0015] Preferably, the equipment degradation assessment unit is used to preset the equipment degradation threshold B, perform secondary assessment with the acquired equipment degradation index LHZ, and generate warning information according to the assessment result. The specific secondary assessment scheme is as follows; When the equipment degradation index LHZ ≥ equipment degradation threshold B, it means that the equipment health does not meet the standard. At this time, the cloud platform controls the equipment control system through the Internet to shut down the equipment, and generates a second early warning report on the cloud platform. The second early warning report is transmitted to the mobile device of relevant personnel through the Internet for equipment inspection; When the equipment degradation index LHZ is less than the equipment degradation threshold B, it means that the equipment is healthy and meets the standard. At this time, normal monitoring is maintained.

[0016] The present invention provides an intelligent cloud platform architecture for the industrial Internet, which has the following beneficial effects: (1) The platform's data acquisition module collects equipment status data in real time through a variety of sensors installed in the chemical reactor, and transmits the data to the cloud platform via the Internet. Then, the cloud platform processing module preprocesses, classifies, and stores the collected data to ensure that the equipment safety data can be accessed by subsequent modules at any time. The data extraction module screens and extracts real-time and historical data from the storage system to provide accurate data support for further equipment status analysis.

[0017] (2) The platform can calculate the inner cavity gas fluctuation coefficient Nqt, fluid viscosity variation coefficient Lnd, heat flow density fluctuation coefficient Rmd and wall pressure variation coefficient Byl based on the extracted equipment safety data. These parameters provide the basis for the chemical reaction stability assessment module, thereby calculating the chemical reaction stability index HXF and performing a preliminary assessment. The chemical reaction stability assessment module can not only detect the stability of the chemical reaction, but also trigger a secondary assessment mechanism when an anomaly is detected. If the reaction stability does not meet the standard, the platform will automatically generate an early warning report and notify relevant personnel so that the anomaly can be handled in a timely manner.

[0018] (3) The equipment degradation assessment module of the platform further evaluates the degradation status of the equipment based on the stability results of the chemical reaction. By calculating the equipment degradation index LHZ, the health standard of the equipment can be identified to ensure that the equipment operates in a safe working state. If the equipment degradation index LHZ exceeds the preset equipment degradation threshold B, the cloud platform will shut down the equipment through the control system of the Internet control device and send an early warning report to relevant personnel so that the equipment can be inspected and maintained as soon as possible. Overall, this intelligent cloud platform architecture realizes intelligent monitoring of equipment status, chemical reaction stability detection and equipment degradation assessment, thereby effectively improving the intelligence and safety of equipment management, and providing strong technical support for chemical reaction equipment management in the industrial Internet environment. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] Figure 1 This is a schematic diagram of the architecture flow of an intelligent cloud platform for the Industrial Internet according to the present invention. DETAILED DESCRIPTION

[0020] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0021] Example 1 See also Figure 1 , the present invention provides an intelligent cloud platform architecture for industrial Internet. To achieve the above purpose, the present invention is implemented through the following technical solutions: including a data acquisition module, a cloud platform processing module, a cloud platform data extraction module, a cloud platform analysis module, a chemical reaction stability assessment module and an equipment degradation assessment module; The data acquisition module is used to install an integrated sensor group at the monitoring point of the chemical reactor to collect equipment status data in real time, and then upload the equipment status data to the cloud platform via the Internet; The cloud platform processing module is used to receive device status data in real time, perform preprocessing, obtain device safety data groups, and then store the device safety data groups in the cloud storage system; The cloud platform data extraction module is used to access the device safety data group in the cloud data history storage system, filter the device safety data group according to the required conditions, extract the real-time device safety data group and the filtered historical device safety data group, and transmit the extracted device safety data group to the cloud platform analysis module in real time; The cloud platform analysis module is used to perform summary calculations based on the extracted real-time equipment safety data group to obtain the inner cavity gas fluctuation coefficient Nqt, the fluid viscosity variation coefficient Lnd, the heat flow density fluctuation coefficient Rmd and the wall pressure variation coefficient Byl; The chemical reaction stability evaluation module is used to perform summary calculation based on the obtained inner cavity gas fluctuation coefficient Nqt, fluid viscosity variation coefficient Lnd and heat flow density fluctuation coefficient Rmd, obtain the chemical reaction stability index HXF, and perform an initial evaluation with the preset chemical reaction stability threshold A, and trigger a secondary evaluation mechanism based on the evaluation results; The equipment degradation assessment module is used to perform summary calculations based on the chemical reaction stability index HXF and the wall pressure variation coefficient Byl when the initial assessment shows that the equipment is working normally, obtain the equipment degradation index LHZ, perform a secondary assessment with the preset equipment degradation threshold B, and generate early warning information based on the assessment results.

[0022] In this embodiment, through the data acquisition module, the equipment status data in the chemical reactor can be collected in real time at a high frequency and transmitted to the cloud platform via the Internet. The cloud platform processing module preprocesses and stores these data so that the subsequent modules can retrieve them at any time to ensure the effectiveness and efficient use of the data. This process not only improves the data processing speed, but also provides a solid foundation for cloud analysis. Compared with the traditional manual data collection and storage method, the modular automated data collection significantly improves the real-time and accuracy of data acquisition. After data processing, the cloud platform analysis module generates the inner cavity gas fluctuation coefficient Nqt, the fluid viscosity variation coefficient Lnd, the heat flow density fluctuation coefficient Rmd and the wall pressure variation coefficient Byl by performing in-depth calculations on the extracted data. Based on these parameters, the chemical reaction stability evaluation module calculates the chemical reaction stability index HXF, which can quickly evaluate the stability of the chemical reactor. For the evaluation results, the system also provides a secondary evaluation mechanism to ensure that relevant personnel can obtain early warning information in time under abnormal conditions so that adjustment measures can be taken quickly. Compared with traditional equipment monitoring methods, this cloud platform architecture has greatly improved the accuracy of fault prediction and reduced the possibility of fault omission through refined data analysis, thereby better ensuring the stability of the chemical reaction process. The equipment degradation assessment module calculates the equipment degradation index LHZ based on further analysis of the chemical reaction stability index HXF and the wall pressure variation coefficient Byl, accurately assesses the health status of the equipment, and promptly warns of potential equipment degradation problems. This multi-level evaluation mechanism plays an important role in equipment management and provides a systematic solution for the full life cycle monitoring of equipment. Compared with the single data monitoring method currently on the market, the introduction of this cloud platform has made significant improvements in improving the intelligent level of chemical reactor equipment management, effectively improving the safety of the production process, the accuracy of reaction control, and the operation and maintenance efficiency of equipment, and expanding new space for the application of industrial Internet technology in the chemical industry.

[0023] Example 2 This embodiment is explained in Example 1, please refer to Figure 1 ,Specifically: the data acquisition module includes a sensor acquisition unit and an Internet transmission unit; The sensor acquisition unit collects equipment status data in real time by setting monitoring points at different positions of the chemical reactor and installing an integrated sensor group in each monitoring point; The integrated sensor group includes a reaction generated gas concentration sensor, a flow meter, a pressure sensor and a heat flow sensor; The Internet transmission unit connects the integrated sensor group to the cloud platform for communication via the Internet HTTPS protocol, and transmits the device status data to the cloud platform in real time.

[0024] In this embodiment, through the coordinated operation of the sensor acquisition unit and the Internet transmission unit, real-time monitoring of multi-dimensional state parameters in the chemical reactor is achieved. The sensor acquisition unit installs an integrated sensor group at different positions of the reactor, which can accurately collect key parameters such as the concentration, flow, pressure and heat flow of the reaction generated gas, and provides basic data for comprehensive monitoring of the equipment status. The HTTPS protocol is used to transmit data to the cloud platform securely and efficiently through the Internet transmission unit to ensure the real-time and integrity of the data. This modular design not only improves the accuracy and timeliness of data acquisition, but also provides a stable and reliable original data source for subsequent cloud processing and analysis. Compared with the traditional offline data acquisition method, the application of this module reduces the risk of manual intervention and data delay, significantly improves the level of automated monitoring of chemical reaction equipment, and provides a strong guarantee for the safety and reliability of industrial production processes.

[0025] Example 3 This embodiment is explained in Example 2. Please refer to Figure 1 ,Specifically: the cloud platform processing module includes a pre-processing unit and a cloud storage unit; The preprocessing unit is used to receive the device status data in real time, and perform data cleaning, denoising, format conversion and normalization processing to obtain a device safety data group; The equipment safety data group includes an inner cavity gas fluctuation factor data group, a wall pressure change data group, a heat flow density data group and a fluid viscosity variation factor data group; The inner cavity gas fluctuation factor data group includes the inner cavity volume tj, the reaction generated gas concentration qt and the gas flow rate F; The fluid viscosity variation factor data group includes fluid viscosity nd, inner cavity temperature wd and inner cavity pressure yl; The heat flux density data set includes equipment surface area mj and heat flux rl; The wall pressure change data group includes the wall pressure bm, the external pressure wb and the wall thickness hd; The cloud storage unit is used to store the device safety data group in real time in the cloud storage system. The cloud storage system includes a cloud data real-time storage system and a cloud data historical storage system. The cloud storage system classifies the device safety data group according to the data type, data source, sensor ID, sensor measurement value and collection timestamp, and stores it in real time in the cloud data real-time storage system, and transfers the previous set of data in the cloud data real-time storage system to the cloud data historical storage system.

[0026] In this embodiment, efficient management and processing of chemical reactor equipment status data are achieved through the combination of a preprocessing unit and a cloud storage unit. First, the preprocessing unit cleans, denoises, converts formats and normalizes the data to ensure the accuracy, consistency and standardization of the data, making subsequent analysis more scientific. Furthermore, the system classifies the processed data according to various factors. This detailed classification significantly improves the operability and traceability of the data. In addition, the cloud storage unit combines real-time data storage with historical data storage, and comprehensively manages the equipment status data through multi-dimensional information such as timestamps and sensor IDs. Compared with traditional systems, the integrated processing and storage solution of this module can quickly respond to real-time monitoring needs, while providing efficient data history backtracking capabilities, facilitating subsequent analysis and evaluation, and significantly improving the monitoring accuracy of chemical reaction equipment and the intelligent level of data management.

[0027] Example 4 This embodiment is explained in Example 3, please refer to Figure 1 ,Specifically: the cloud platform data extraction module includes a data access unit and a data extraction unit; The data access unit is used to access the device safety data group in the cloud data history storage system, and filter the data according to the required conditions based on the data type, data source, sensor ID, sensor measurement value and acquisition timestamp, and transmit the filtered data to the data extraction unit through the query interface; The data extraction unit is used to extract in real time the device safety data group in the cloud data real-time storage system and the historical device safety data group filtered by the data access unit, and transmit the extracted device safety data group to the cloud platform analysis module in real time.

[0028] In this embodiment, the cloud platform data extraction module significantly improves the efficiency of obtaining and analyzing equipment safety data through the cooperation of the data access unit and the data extraction unit, demonstrating the advantages of efficient data management. The data access unit can not only flexibly access the equipment safety data in the historical storage system, but also accurately filter the data according to the data type, data source, sensor ID, sensor measurement value and acquisition timestamp, which enables the platform to quickly locate and extract data in a specific context to ensure the relevance and real-time nature of the data. Subsequently, the data extraction unit will instantly transmit the data in the real-time storage system and the filtered historical data group to the cloud platform analysis module. Such a design not only reduces unnecessary data transmission and processing burdens, but also ensures that the analysis module obtains the most relevant and filtered historical data and the latest real-time data, which facilitates dynamic tracking and accurate analysis of the equipment status. Compared with the traditional flat data storage and extraction method, this structured and modular data extraction process has higher flexibility and adaptability in data management, thereby improving the accuracy and response speed of data processing, and helping to more timely and accurately evaluate the status and predict faults of the equipment.

[0029] Example 5 This embodiment is explained in Example 4. Please refer to Figure 1 ,Specifically: the cloud platform analysis module includes an inner cavity gas fluctuation calculation unit, a fluid viscosity variation calculation unit, a heat flow density fluctuation calculation unit and a wall pressure change calculation unit; The inner cavity gas fluctuation calculation unit is used to perform summary calculation based on the acquired inner cavity gas fluctuation factor data group to obtain the inner cavity gas fluctuation coefficient Nqt; The inner cavity gas fluctuation coefficient Nqt is calculated and obtained by the following formula: ; Where N is the number of sampling times, qt i represents the concentration of the gas generated by the reaction at the i-th sampling, qt, avg It represents the average value of the gas concentration qt generated by N sampling reactions. represents the rate of change of gas flow rate F with time t, represents partial derivative; The fluid viscosity variation calculation unit is used to perform summary calculation based on the acquired fluid viscosity variation factor data group to obtain the fluid viscosity variation coefficient Lnd; The fluid viscosity variation coefficient Lnd is calculated by the following formula: ; Where, nd i represents the fluid viscosity nd of the i-th sampling, nd avgrepresents the average value of the viscosity nd of all sampled fluids, and N represents the number of sampling times; The heat flux density fluctuation calculation unit is used to perform summary calculation based on the acquired heat flux density data group to obtain the heat flux density fluctuation coefficient Rmd; The heat flux density fluctuation coefficient Rmd is calculated by the following formula: ; In the formula, represents the rate of change of heat flow rl with time t, T grad It represents the temperature gradient, the degree of temperature change per unit distance, and a represents the thermal conductivity.

[0030] The wall pressure change calculation unit is used to perform summary calculation based on the acquired wall pressure change data group to obtain the wall pressure change coefficient Byl; The wall pressure variation coefficient Byl is calculated by the following formula: ; In the formula, It represents the rate of change of wall pressure bm with time t.

[0031] In this embodiment, through the design and implementation of the cloud platform analysis module, the inner cavity gas fluctuation coefficient Nqt, the fluid viscosity variation coefficient Lnd, the heat flow density fluctuation coefficient Rmd and the wall pressure variation coefficient Byl can be efficiently calculated and monitored. These parameters not only provide accurate data support for the real-time monitoring of the chemical reactor, but also lay a scientific basis for the stable operation of the equipment. Especially in the chemical reaction process, the real-time evaluation of these fluctuation coefficients can quickly identify potential abnormal situations, thereby greatly reducing the risk of equipment failure and downtime, and improving production efficiency. In addition, the automated analysis capability effectively reduces manual intervention, improves the timeliness and accuracy of data processing, provides more reliable decision-making support for equipment maintenance, and ultimately realizes the intelligence and efficiency of equipment management, and promotes the improvement of production safety and economic benefits in the entire industrial Internet environment.

[0032] Example 6 This embodiment is explained in Example 5. Please refer to Figure 1 , specifically: the chemical reaction stability assessment module includes a chemical reaction stability calculation unit and a chemical reaction stability assessment unit; The chemical reaction stability calculation unit is used to perform summary calculation based on the obtained inner cavity gas fluctuation coefficient Nqt, fluid viscosity variation coefficient Lnd and heat flow density fluctuation coefficient Rmd to obtain a chemical reaction stability index HXF; The chemical reaction stability index HXF is calculated by the following formula: ; Wherein, e represents an exponential function, k1, k2 and k3 represent the weight coefficients of the inner cavity gas fluctuation coefficient Nqt, the fluid viscosity variation coefficient Lnd and the heat flow density fluctuation coefficient Rmd, respectively, and k1+k2+k3=1. The specific values ​​are set by the user according to the actual situation.

[0033] The chemical reaction stability evaluation unit is used to access the equipment safety data group in the cloud data history storage system, analyze the historical chemical reaction stability average value through the cloud platform, perform a preset chemical reaction stability threshold A, and perform a preliminary evaluation with the obtained chemical reaction stability index HXF, and trigger a secondary evaluation mechanism based on the evaluation results. The specific evaluation scheme is as follows; When the chemical reaction stability index HXF ≥ the chemical reaction stability threshold A, it means that the equipment is working normally, maintaining normal monitoring, and triggering the secondary evaluation mechanism; When the chemical reaction stability index HXF is less than the chemical reaction stability threshold A, it indicates that the equipment is operating abnormally. At this time, the cloud platform generates a first warning report, transmits the first warning report to the mobile device of relevant personnel through the Internet, and notifies the relevant personnel to adjust the abnormal data.

[0034] In this embodiment, the design and implementation of the chemical reaction stability assessment module greatly improves the operational safety and efficiency of the chemical reactor. By calculating the chemical reaction stability index HXF in real time and performing a preliminary assessment with the preset chemical reaction stability threshold A, the module can quickly identify the working status of the equipment. When the equipment is normal, the monitoring state is maintained and the secondary assessment mechanism is triggered to ensure continuous attention to the stability of the reaction process; when an abnormality occurs, the system will automatically generate an early warning report and transmit it to the mobile devices of relevant personnel in real time, prompting them to take corresponding measures quickly. This mechanism not only shortens the response time and reduces the risk of delays caused by human intervention, but also significantly improves the reliability of the equipment and the stability of the chemical reaction process through data-driven decision support, providing important guarantees for production safety, and ultimately realizing the chemical industry's higher requirements for intelligence, automation and efficiency.

[0035] Example 7 This embodiment is explained in Example 6. Please refer to Figure 1 , specifically: the equipment degradation assessment module includes an equipment degradation calculation unit and an equipment degradation assessment unit; The equipment degradation calculation unit is used to obtain the equipment degradation index LHZ by summarizing and calculating the chemical reaction stability index HXF and the wall pressure variation coefficient Byl obtained when the equipment is initially evaluated to be working normally; The equipment degradation index LHZ is calculated by the following formula: .

[0036] The equipment degradation assessment unit is used to preset the equipment degradation threshold B, perform secondary assessment with the acquired equipment degradation index LHZ, and generate early warning information according to the assessment result. The specific secondary assessment scheme is as follows; When the equipment degradation index LHZ ≥ equipment degradation threshold B, it means that the equipment health does not meet the standard. At this time, the cloud platform controls the equipment control system through the Internet to shut down the equipment, and generates a second early warning report on the cloud platform. The second early warning report is transmitted to the mobile device of relevant personnel through the Internet for equipment inspection; When the equipment degradation index LHZ is less than the equipment degradation threshold B, it means that the equipment is healthy and meets the standard. At this time, normal monitoring is maintained.

[0037] In this embodiment, by introducing the equipment degradation assessment module, the industrial Internet intelligent cloud platform significantly improves the monitoring and maintenance capabilities of the chemical reactor. The equipment degradation calculation unit of this module relies on the chemical reaction stability index HXF and the wall pressure variation coefficient Byl to accurately calculate the equipment degradation index LHZ, thereby realizing a scientific assessment of the health status of the equipment. When the preset equipment degradation threshold B is reached, the system can automatically issue an alarm and quickly control the equipment to shut down, thereby effectively avoiding potential equipment failures and safety hazards, and ensuring the continuity and safety of production. In addition, when the equipment is in normal condition, the system continues to monitor to ensure that the equipment is always in the best working condition. This intelligent monitoring and early warning mechanism not only improves the efficiency of equipment management, but also reduces the need for manual intervention, ultimately achieving the optimization of the production process and the effective allocation of resources, saving costs and reducing downtime for enterprises, and further enhancing the reliability and safety of equipment.

[0038] Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present invention, and that the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. An intelligent cloud platform architecture for the industrial Internet, characterized by: It includes data acquisition module, cloud platform processing module, cloud platform data extraction module, cloud platform analysis module, chemical reaction stability assessment module and equipment degradation assessment module; The data acquisition module is used to install an integrated sensor group at the monitoring point of the chemical reactor to collect equipment status data in real time, and then upload the equipment status data to the cloud platform via the Internet; The cloud platform processing module is used to receive device status data in real time, perform preprocessing, obtain device safety data groups, and then store the device safety data groups in the cloud storage system; The cloud platform data extraction module is used to access the device safety data group in the cloud data history storage system, filter the device safety data group according to the required conditions, extract the real-time device safety data group and the filtered historical device safety data group, and transmit the extracted device safety data group to the cloud platform analysis module in real time; The cloud platform analysis module is used to perform summary calculations based on the extracted real-time equipment safety data group to obtain the inner cavity gas fluctuation coefficient Nqt, the fluid viscosity variation coefficient Lnd, the heat flow density fluctuation coefficient Rmd and the wall pressure variation coefficient Byl; The chemical reaction stability evaluation module is used to perform summary calculation based on the obtained inner cavity gas fluctuation coefficient Nqt, fluid viscosity variation coefficient Lnd and heat flow density fluctuation coefficient Rmd, obtain the chemical reaction stability index HXF, and perform an initial evaluation with the preset chemical reaction stability threshold A, and trigger a secondary evaluation mechanism based on the evaluation results; The equipment degradation assessment module is used to perform summary calculations based on the chemical reaction stability index HXF and the wall pressure variation coefficient Byl when the initial assessment shows that the equipment is working normally, obtain the equipment degradation index LHZ, perform a secondary assessment with the preset equipment degradation threshold B, and generate early warning information based on the assessment results.

2. According to claim 1, the intelligent cloud platform architecture for industrial Internet is characterized by: The data acquisition module includes a sensor acquisition unit and an Internet transmission unit; The sensor acquisition unit collects equipment status data in real time by setting monitoring points at different positions of the chemical reactor and installing an integrated sensor group in each monitoring point; The integrated sensor group includes a reaction generated gas concentration sensor, a flow meter, a pressure sensor and a heat flow sensor; The Internet transmission unit connects the integrated sensor group to the cloud platform for communication via the Internet HTTPS protocol, and transmits the device status data to the cloud platform in real time.

3. According to claim 2, the intelligent cloud platform architecture for industrial Internet is characterized by: The cloud platform processing module includes a pre-processing unit and a cloud storage unit; The preprocessing unit is used to receive the device status data in real time, and perform data cleaning, denoising, format conversion and normalization processing to obtain a device safety data group; The equipment safety data group includes an inner cavity gas fluctuation factor data group, a wall pressure change data group, a heat flow density data group and a fluid viscosity variation factor data group; The inner cavity gas fluctuation factor data group includes the inner cavity volume tj, the reaction generated gas concentration qt and the gas flow rate F; The fluid viscosity variation factor data group includes fluid viscosity nd, inner cavity temperature wd and inner cavity pressure yl; The heat flux density data set includes equipment surface area mj and heat flux rl; The wall pressure change data group includes the wall pressure bm, the external pressure wb and the wall thickness hd; The cloud storage unit is used to store the device safety data group in real time in the cloud storage system. The cloud storage system includes a cloud data real-time storage system and a cloud data historical storage system. The cloud storage system classifies the device safety data group according to the data type, data source, sensor ID, sensor measurement value and collection timestamp, and stores it in real time in the cloud data real-time storage system, and transfers the previous set of data in the cloud data real-time storage system to the cloud data historical storage system.

4. The intelligent cloud platform architecture for industrial Internet according to claim 3 is characterized by: The cloud platform data extraction module includes a data access unit and a data extraction unit; The data access unit is used to access the device safety data group in the cloud data history storage system, and filter the data according to the required conditions based on the data type, data source, sensor ID, sensor measurement value and acquisition timestamp, and transmit the filtered data to the data extraction unit through the query interface; The data extraction unit is used to extract in real time the device safety data group in the cloud data real-time storage system and the historical device safety data group filtered by the data access unit, and transmit the extracted device safety data group to the cloud platform analysis module in real time.

5. The intelligent cloud platform architecture for industrial Internet according to claim 4 is characterized by: The cloud platform analysis module includes an inner cavity gas fluctuation calculation unit, a fluid viscosity variation calculation unit, a heat flow density fluctuation calculation unit and a wall pressure variation calculation unit; The inner cavity gas fluctuation calculation unit is used to perform summary calculation based on the acquired inner cavity gas fluctuation factor data group to obtain the inner cavity gas fluctuation coefficient Nqt; The inner cavity gas fluctuation coefficient Nqt is calculated and obtained by the following formula: ； Where N is the number of sampling times, qt i represents the concentration of the gas generated by the reaction at the i-th sampling, qt, avg It represents the average value of the gas concentration qt generated by N sampling reactions. represents the rate of change of gas flow rate F with time t, represents partial derivative; The fluid viscosity variation calculation unit is used to perform summary calculation based on the acquired fluid viscosity variation factor data group to obtain the fluid viscosity variation coefficient Lnd; The fluid viscosity variation coefficient Lnd is calculated by the following formula: ； Where, nd i represents the fluid viscosity nd of the i-th sampling, nd avg represents the average value of the viscosity nd of all sampled fluids, and N represents the number of sampling times; The heat flux density fluctuation calculation unit is used to perform summary calculation based on the acquired heat flux density data group to obtain the heat flux density fluctuation coefficient Rmd; The heat flux density fluctuation coefficient Rmd is calculated by the following formula: ； In the formula, represents the rate of change of heat flow rl with time t, T grad It represents the temperature gradient, the degree of temperature change per unit distance, and a represents the thermal conductivity.

6. The intelligent cloud platform architecture for industrial Internet according to claim 5 is characterized by: The wall pressure change calculation unit is used to perform summary calculation based on the acquired wall pressure change data group to obtain the wall pressure change coefficient Byl; The wall pressure variation coefficient Byl is calculated by the following formula: ； In the formula, It represents the rate of change of wall pressure bm with time t.

7. The intelligent cloud platform architecture for industrial Internet according to claim 5 is characterized by: The chemical reaction stability assessment module includes a chemical reaction stability calculation unit and a chemical reaction stability assessment unit; The chemical reaction stability calculation unit is used to perform summary calculation based on the obtained inner cavity gas fluctuation coefficient Nqt, fluid viscosity variation coefficient Lnd and heat flow density fluctuation coefficient Rmd to obtain a chemical reaction stability index HXF; The chemical reaction stability index HXF is calculated by the following formula: ； Wherein, e represents an exponential function, k1, k2 and k3 represent the weight coefficients of the inner cavity gas fluctuation coefficient Nqt, the fluid viscosity variation coefficient Lnd and the heat flow density fluctuation coefficient Rmd, respectively, and k1+k2+k3=1. The specific values ​​are set by the user according to the actual situation.

8. The intelligent cloud platform architecture for industrial Internet according to claim 7 is characterized by: The chemical reaction stability evaluation unit is used to access the equipment safety data group in the cloud data history storage system, analyze the historical chemical reaction stability average value through the cloud platform, perform a preset chemical reaction stability threshold A, and perform a preliminary evaluation with the obtained chemical reaction stability index HXF, and trigger a secondary evaluation mechanism based on the evaluation results. The specific evaluation scheme is as follows; When the chemical reaction stability index HXF ≥ the chemical reaction stability threshold A, it means that the equipment is working normally, maintaining normal monitoring, and triggering the secondary evaluation mechanism; When the chemical reaction stability index HXF is less than the chemical reaction stability threshold A, it indicates that the equipment is operating abnormally. At this time, the cloud platform generates a first warning report, transmits the first warning report to the mobile device of relevant personnel through the Internet, and notifies the relevant personnel to adjust the abnormal data.

9. The intelligent cloud platform architecture for industrial Internet according to claim 8 is characterized by: The equipment degradation assessment module includes an equipment degradation calculation unit and an equipment degradation assessment unit; The equipment degradation calculation unit is used to obtain the equipment degradation index LHZ by summarizing and calculating the chemical reaction stability index HXF and the wall pressure variation coefficient Byl obtained when the equipment is initially evaluated to be working normally; The equipment degradation index LHZ is calculated by the following formula: 。 10. The intelligent cloud platform architecture for industrial Internet according to claim 9, characterized in that: The equipment degradation assessment unit is used to preset the equipment degradation threshold B, perform secondary assessment with the acquired equipment degradation index LHZ, and generate early warning information according to the assessment result. The specific secondary assessment scheme is as follows; When the equipment degradation index LHZ ≥ equipment degradation threshold B, it means that the equipment health does not meet the standard. At this time, the cloud platform controls the equipment control system through the Internet to shut down the equipment, and generates a second early warning report on the cloud platform. The second early warning report is transmitted to the mobile device of relevant personnel through the Internet for equipment inspection; When the equipment degradation index LHZ is less than the equipment degradation threshold B, it means that the equipment is healthy and meets the standard. At this time, normal monitoring is maintained.

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