An intelligent cloud platform architecture for industrial Internet

Abstract

The present invention discloses an intelligent cloud platform architecture for industrial Internet, which relates to the technical field of intelligent cloud monitoring of industrial chemistry. The platform collects device status data in real time through an integrated sensor group of a chemical reactor, transmits it to the cloud via the Internet, processes it on the cloud platform to obtain a device safety data group, and stores it in a cloud storage system; the cloud platform extracts and filters the device safety data group, analyzes and calculates a chemical reaction stability index HXF, and conducts a primary evaluation of reaction stability with a preset chemical reaction stability threshold A; if the stability meets the standard, a secondary evaluation mechanism is triggered, and by further analyzing the chemical reaction stability index HXF and the wall pressure change coefficient Byl, the device deterioration index LHZ is calculated to judge the device health status, and a warning report is generated when necessary and transmitted to relevant personnel in real time via the Internet for timely maintenance or shutdown measures.

Description

Technical Field

[0001] The present invention relates to the technical field of industrial chemical intelligent cloud monitoring, and specifically provides 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 for promoting the digital and intelligent transformation of the manufacturing industry. With the increasing demand for automation and high efficiency in the manufacturing industry, more and more enterprises have started to use industrial Internet technology for remote monitoring, predictive maintenance, and data analysis of equipment to improve production efficiency, reduce maintenance costs, and extend the service life of equipment. Especially in high-risk industries such as chemical, petroleum, and natural gas, the stability and safety of equipment are crucial. The industrial Internet can help enterprises achieve real-time data collection, cloud analysis, and intelligent decision-making, thereby optimizing the performance of equipment in the chemical reaction process and ensuring the safe and stable operation of chemical reactions.

[0003] In the Chinese invention application with the application publication number CN117589375A, a chemical safety detection method, system, terminal device, and storage medium are disclosed. The sensitivity of the corresponding gas monitoring points in the target chemical area is detected, and it is determined whether there is an abnormal detection at the gas monitoring points according to the corresponding sensitivity detection results. If the sensitivity detection result is normal, it is determined whether the gas monitoring point issues a first-level alarm signal. If so, the number of the target gas monitoring points is further determined. If the number is single, the corresponding associated gas monitoring point is obtained, and it is determined whether the associated gas monitoring point outputs a corresponding second-level alarm signal within a preset time interval. If so, the number of the target associated gas monitoring points corresponding to the second-level alarm signal is continuously obtained and analyzed. If the number exceeds the preset associated quantity threshold, it indicates that there is a hazardous gas leakage situation in the current target chemical area. The solution of this application can improve the detection effect of chemical safety.

[0004] Combined with the existing technology, the above application still has the following deficiencies:

[0005] In a large chemical plant, dozens of chemical reactors are running simultaneously. To ensure production efficiency and equipment safety, it is necessary to monitor the operating status of the reactors in real time and be able to perform preventive maintenance before problems occur. Due to relying on single-point monitoring data, it is difficult to comprehensively reflect the overall safety status in the chemical area and lacks a dynamic evaluation mechanism for equipment degradation. In addition, the sensitivity detection standard is not applicable to all possible gas types and leakage modes, which is prone to false alarms or missed alarms. This not only increases the maintenance cost but also may delay the timely response to potential hazards and affect the safety management effect of chemical facilities. Summary of the Invention

[0006] In view of the deficiencies of 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.

[0007] To achieve the above objectives, the present invention is realized through the following technical solutions: An intelligent cloud platform architecture for the industrial Internet includes a data acquisition module, a cloud platform processing module, a cloud platform data extraction module, a cloud platform analysis module, a chemical reaction stability evaluation module, and an equipment deterioration evaluation module;

[0008] The data acquisition module is used to install an integrated sensor group at the monitoring point positions in the chemical reactor to collect equipment status data in real time, and then upload the equipment status data to the cloud platform through the Internet;

[0009] The cloud platform processing module is used to receive the equipment status data in real time, perform preprocessing, obtain the equipment safety data group, and then store the equipment safety data group in the cloud storage system;

[0010] The cloud platform data extraction module is used to access the equipment safety data group in the cloud data historical storage system, filter the equipment safety data group according to the required conditions, extract the real-time equipment safety data group and the filtered historical equipment safety data group, and transmit the extracted equipment safety data group to the cloud platform analysis module in real time;

[0011] The cloud platform analysis module is used to perform summary calculations based on the extracted real-time equipment safety data group to obtain the internal cavity gas fluctuation coefficient Nqt, the fluid viscosity variation coefficient Lnd, the heat flux density fluctuation coefficient Rmd, and the wall pressure change coefficient Byl;

[0012] The chemical reaction stability evaluation module is used to perform summary calculations based on the obtained internal cavity gas fluctuation coefficient Nqt, fluid viscosity variation coefficient Lnd, and heat flux density fluctuation coefficient Rmd to obtain the chemical reaction stability index HXF, and conduct a primary evaluation with a preset chemical reaction stability threshold A, and trigger a secondary evaluation mechanism based on the evaluation results;

[0013] When the equipment deterioration evaluation module initially evaluates that the equipment is working normally, it performs summary calculations based on the obtained chemical reaction stability index HXF and wall pressure change coefficient Byl to obtain the equipment deterioration index LHZ, conducts a secondary evaluation with a preset equipment deterioration threshold B, and generates a warning message based on the evaluation results.

[0014] Preferably, the data acquisition module includes a sensor acquisition unit and an Internet transmission unit;

[0015] The sensor acquisition unit sets monitoring points at different positions in the chemical reactor and installs an integrated sensor group in each monitoring point to collect equipment status data in real time;

[0016] The integrated sensor group includes a reaction-generated gas concentration sensor, a flow meter, a pressure sensor, and a heat flux sensor;

[0017] The reaction-generated gas concentration qt is directly collected by the gas concentration sensor;

[0018] The gas flow rate F is directly collected by the flow meter;

[0019] The internal cavity volume tj, the wall thickness hd, and the device surface area mj are fixed parameters for the chemical reactor design;

[0020] The heat flux rl is directly collected by the heat flux sensor;

[0021] The wall pressure bm and the external pressure wb are directly collected by the pressure sensor;

[0022] The Internet transmission unit communicates and connects the integrated sensor group with the cloud platform through the Internet HTTPS protocol, and transmits the device status data to the cloud platform in real time.

[0023] Preferably, the cloud platform processing module includes a preprocessing unit and a cloud storage unit;

[0024] 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 the device safety data group;

[0025] The device safety data group includes an internal cavity gas fluctuation factor data group, a wall pressure change data group, a heat flux density data group, and a fluid viscosity variation factor data group;

[0026] The internal cavity gas fluctuation factor data group includes the internal cavity volume tj, the reaction-generated gas concentration qt, and the gas flow rate F;

[0027] The fluid viscosity variation factor data group includes the fluid viscosity nd, the internal cavity temperature wd, and the internal cavity pressure yl;

[0028] The heat flux density data group includes the device surface area mj and the heat flux rl;

[0029] The wall pressure change data group includes the wall pressure bm, the external pressure wb, and the wall thickness hd;

[0030] The cloud storage unit is used to store the device security data group in real time into the cloud storage system. The cloud storage system includes a cloud data real-time storage system and a cloud data historical storage system. After classifying the device security data group according to data type, data source, sensor ID, sensor measurement value, and acquisition timestamp, the cloud storage system stores it in real time into the cloud data real-time storage system, and transfers the previous group of data in the cloud data real-time storage system to the cloud data historical storage system.

[0031] Preferably, the cloud platform data extraction module includes a data access unit and a data extraction unit;

[0032] The data access unit is used to access the device security data group in the cloud data historical storage system, filter the data according to the required conditions based on 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;

[0033] The data extraction unit is used to extract the device security data group in the cloud data real-time storage system and the historical device security data group filtered by the data access unit in real time, and transmit the extracted device security data group to the cloud platform analysis module in real time.

[0034] Preferably, the cloud platform analysis module includes an internal cavity gas fluctuation calculation unit, a fluid viscosity variation calculation unit, a heat flux density fluctuation calculation unit, and a wall pressure change calculation unit;

[0035] The internal cavity gas fluctuation calculation unit is used to perform a summary calculation based on the obtained internal cavity gas fluctuation factor data group to obtain the internal cavity gas fluctuation coefficient Nqt;

[0036] The internal cavity gas fluctuation coefficient Nqt is obtained through the following formula;

[0037] ;

[0038] In the formula, N represents the number of sampling times, qt i represents the reaction-generated gas concentration qt at the i-th sampling, qt avg represents the average value of the reaction-generated gas concentration qt for N samplings, represents the change rate of the gas flow F with respect to time t, represents the partial derivative;

[0039] The fluid viscosity variation calculation unit is used to perform a summary calculation based on the obtained fluid viscosity variation factor data group to obtain the fluid viscosity variation coefficient Lnd;

[0040] The fluid viscosity variation coefficient Lnd is obtained through the following formula;

[0041] ;

[0042] In the formula, ηd i represents the fluid viscosity ηd at the i-th sampling, and ηd avg represents the average value of all sampled fluid viscosities ηd, and N represents the number of samplings;

[0043] The heat flux density fluctuation calculation unit is used to perform a summary calculation based on the obtained heat flux density data set to obtain a heat flux density fluctuation coefficient Rmd;

[0044] The heat flux density fluctuation coefficient Rmd is obtained through the following formula;

[0045] ;

[0046] In the formula, represents the change rate of the heat flux rl with respect to time t, and T grad represents the temperature gradient, which is the degree of temperature change per unit distance, and a represents the thermal conductivity.

[0047] Preferably, the wall pressure change calculation unit is used to perform a summary calculation based on the obtained wall pressure change data set to obtain a wall pressure change coefficient Byl;

[0048] The wall pressure change coefficient Byl is obtained through the following formula;

[0049] ;

[0050] In the formula, represents the change rate of the wall pressure bm with respect to time t.

[0051] Preferably, the chemical reaction stability evaluation module includes a chemical reaction stability calculation unit and a chemical reaction stability evaluation unit;

[0052] The chemical reaction stability calculation unit is used to perform a summary calculation based on the obtained internal cavity gas fluctuation coefficient Nqt, fluid viscosity variation coefficient Lnd, and heat flux density fluctuation coefficient Rmd to obtain a chemical reaction stability index HXF;

[0053] The chemical reaction stability index HXF is obtained through the following formula;

[0054] ;

[0055] In the formula, e represents the exponential function, and k1, k2, and k3 respectively represent the weight coefficients of the internal cavity gas fluctuation coefficient Nqt, fluid viscosity variation coefficient Lnd, and heat flux density fluctuation coefficient Rmd, and k1 + k2 + k3 = 1, and their specific values are set by the user according to the actual situation.

[0056] Preferably, the chemical reaction stability evaluation unit is used to access the device safety data group in the cloud data historical storage system, analyze the average value of the historical chemical reaction stability through the cloud platform, set a preset chemical reaction stability threshold A, and conduct a preliminary evaluation with the obtained chemical reaction stability index HXF, and trigger a secondary evaluation mechanism according to the evaluation result. The specific evaluation scheme is as follows;

[0057] When the chemical reaction stability index HXF ≥ the chemical reaction stability threshold A, it indicates that the device is working normally, maintains normal monitoring, and triggers a secondary evaluation mechanism;

[0058] When the chemical reaction stability index HXF < the chemical reaction stability threshold A, it indicates that the device is working abnormally. At this time, the cloud platform generates a first warning report and transmits the first warning report to the mobile device of relevant personnel through the Internet to notify relevant personnel to adjust the abnormal data.

[0059] Preferably, the device deterioration evaluation module includes a device deterioration calculation unit and a device deterioration evaluation unit;

[0060] The device deterioration calculation unit is used to summarize and calculate according to the obtained chemical reaction stability index HXF and the wall pressure change coefficient Byl when the device is initially evaluated to be working normally, and obtain the device deterioration index LHZ;

[0061] The device deterioration index LHZ is obtained through the following formula;

[0062] 。

[0063] Preferably, the device deterioration evaluation unit is used to set a preset device deterioration threshold B, conduct a secondary evaluation with the obtained device deterioration index LHZ, and generate a warning message according to the evaluation result. The specific secondary evaluation scheme is as follows;

[0064] When the device deterioration index LHZ ≥ the device deterioration threshold B, it indicates that the device health is not up to standard. At this time, the cloud platform controls the control system of the device to shut down the device through the Internet, and generates a second warning report on the cloud platform and transmits the second warning report to the mobile device of relevant personnel through the Internet for device inspection;

[0065] When the device deterioration index LHZ < the device deterioration threshold B, it indicates that the device health meets the standard, and normal monitoring is maintained at this time.

[0066] The present invention provides an intelligent cloud platform architecture for industrial Internet. It has the following beneficial effects:

[0067] (1) The data acquisition module of this platform collects the device status data in real time through various sensors installed in the chemical reactor, and transmits this data to the cloud platform via the Internet. Then, the cloud platform processing module preprocesses, classifies, and stores the collected data, ensuring that the device security data can be accessed by subsequent modules at any time. The data extraction module filters and extracts real-time data and historical data from the storage system, providing accurate data support for further device status analysis.

[0068] (2) This platform can calculate the internal cavity gas fluctuation coefficient Nqt, fluid viscosity variation coefficient Lnd, heat flux density fluctuation coefficient Rmd, and wall pressure change coefficient Byl based on the extracted device security data. These parameters provide the basis for the chemical reaction stability evaluation module to calculate the chemical reaction stability index HXF and conduct a preliminary evaluation. The work of the chemical reaction stability evaluation module can not only detect the stability of the chemical reaction but also trigger a secondary evaluation mechanism when an anomaly is detected. If the reaction stability does not meet the standard, the platform will automatically generate a warning report and notify the relevant personnel for timely anomaly handling.

[0069] (3) The device deterioration evaluation module of this platform further evaluates the deterioration state of the device based on the chemical reaction stability results. By calculating the device deterioration index LHZ, the health standard of the device can be identified to ensure that the device operates in a safe working state. If the device deterioration index LHZ exceeds the preset device deterioration threshold B, the cloud platform controls the control system of the device to shut down the device via the Internet and sends a warning report to the relevant personnel for inspection and maintenance of the device as soon as possible. Overall, this intelligent cloud platform architecture realizes the intelligent monitoring of device status, chemical reaction stability detection, and device deterioration evaluation, effectively improving the intelligence and security of device management and providing strong technical support for the management of chemical reaction devices in the industrial Internet environment. Description of the Drawings

[0070] Figure 1 It is a schematic flow diagram of an intelligent cloud platform architecture for an industrial Internet-oriented invention of the present invention. Detailed Embodiments

[0071] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

[0072] Embodiment 1

[0073] Please refer to Figure 1, the present invention provides an intelligent cloud platform architecture for industrial Internet. To achieve the above object, the present invention is realized 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 evaluation module, and a device deterioration evaluation module;

[0074] The data acquisition module is used to install an integrated sensor group at the monitoring point position of the chemical reactor to collect device status data in real time, and then upload the device status data to the cloud platform through the Internet;

[0075] The cloud platform processing module is used to receive the device status data in real time, perform preprocessing to obtain a device safety data group, and then store the device safety data group in the cloud storage system;

[0076] The cloud platform data extraction module is used to access the device safety data group in the cloud data historical 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;

[0077] The cloud platform analysis module is used to perform summary calculations based on the extracted real-time device safety data group to obtain the inner cavity gas fluctuation coefficient Nqt, the fluid viscosity variation coefficient Lnd, the heat flux density fluctuation coefficient Rmd, and the wall pressure change coefficient Byl;

[0078] The chemical reaction stability evaluation module is used to perform summary calculations based on the obtained inner cavity gas fluctuation coefficient Nqt, the fluid viscosity variation coefficient Lnd, and the heat flux density fluctuation coefficient Rmd to obtain the chemical reaction stability index HXF, and conduct a primary evaluation with a preset chemical reaction stability threshold A, and trigger a secondary evaluation mechanism based on the evaluation result;

[0079] When the device deterioration evaluation module evaluates that the device is working normally initially, it performs summary calculations based on the obtained chemical reaction stability index HXF and the wall pressure change coefficient Byl to obtain the device deterioration index LHZ, and conducts a secondary evaluation with a preset device deterioration threshold B, and generates a warning message based on the evaluation result.

[0080] 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 through the Internet. The cloud platform processing module then preprocesses and stores and classifies these data for subsequent modules to retrieve at any time, ensuring the effectiveness and efficient utilization 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 acquisition and storage methods, this modular automated data acquisition 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 flux density fluctuation coefficient Rmd, and the wall pressure change coefficient Byl by performing in-depth calculations on the extracted data. Based on these parameters, the chemical reaction stability evaluation module calculates and obtains 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 receive early warning information in case of abnormal conditions so that adjustment measures can be taken promptly. Compared with the traditional equipment monitoring methods, this cloud platform architecture significantly improves the accuracy of fault prediction through refined data analysis, reduces the possibility of missed fault reports, and thus better guarantees the stability of the chemical reaction process. The equipment deterioration evaluation module further analyzes based on the chemical reaction stability index HXF and the wall pressure change coefficient Byl, calculates and obtains the equipment deterioration index LHZ, accurately evaluates the health status of the equipment, and promptly warns of potential equipment deterioration 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 methods on the current market, the introduction of this cloud platform has made remarkable improvements in enhancing the intelligent level of the equipment management of the chemical reactor, effectively improving the safety of the production process, the accuracy of reaction control, and the operation and maintenance efficiency of the equipment, and expanding new space for the application of industrial Internet technology in the chemical industry field.

[0081] Embodiment 2

[0082] This embodiment is an explanatory description based on Embodiment 1. Please refer to Figure 1 , specifically: The data acquisition module includes a sensor acquisition unit and an Internet transmission unit;

[0083] The sensor acquisition unit sets monitoring points at different positions in the chemical reactor and installs an integrated sensor group in each monitoring point to collect equipment status data in real time;

[0084] The integrated sensor group includes a reaction-generated gas concentration sensor, a flowmeter, a pressure sensor, and a heat flux sensor;

[0085] The Internet transmission unit communicates and connects the integrated sensor group with the cloud platform through the Internet HTTPS protocol, and transmits the device status data to the cloud platform in real time.

[0086] In this embodiment, through the coordinated operation of the sensor acquisition unit and the Internet transmission unit, the real-time monitoring of multi-dimensional state parameters in the chemical reactor is realized. The sensor acquisition unit installs an integrated sensor group at different positions of the reactor, and can accurately collect key parameters such as the concentration, flow rate, pressure and heat flow rate of the reaction-generated gas, providing basic data for the comprehensive monitoring of the device status. The Internet transmission unit uses the HTTPS protocol to transmit data to the cloud platform safely and efficiently, ensuring 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 risks of manual intervention and data delay, significantly improves the automation monitoring level of chemical reaction equipment, and provides a strong guarantee for the safety and reliability in the industrial production process.

[0087] Embodiment 3

[0088] This embodiment is an explanatory description based on Embodiment 2. Please refer to Figure 1 , specifically: The cloud platform processing module includes a preprocessing unit and a cloud storage unit;

[0089] 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 the device safety data group;

[0090] The device safety data group includes an internal cavity gas fluctuation factor data group, a wall pressure change data group, a heat flux density data group and a fluid viscosity variation factor data group;

[0091] The internal cavity gas fluctuation factor data group includes the internal cavity volume tj, the reaction-generated gas concentration qt and the gas flow rate F;

[0092] The fluid viscosity variation factor data group includes the fluid viscosity nd, the internal cavity temperature wd and the internal cavity pressure yl;

[0093] The heat flux density data group includes the device surface area mj and the heat flux rl;

[0094] The wall pressure change data group includes the wall pressure bm, the external pressure wb and the wall thickness hd;

[0095] The cloud storage unit is used to store the device security data group in the cloud storage system in real time. The cloud storage system includes a cloud data real-time storage system and a cloud data historical storage system. After classifying the device security data group according to data type, data source, sensor ID, sensor measurement value, and acquisition timestamp, the cloud storage system stores it in the cloud data real-time storage system in real time, and transfers the previous group of data in the cloud data real-time storage system to the cloud data historical storage system.

[0096] In this embodiment, through the combination of the preprocessing unit and the cloud storage unit, the efficient management and processing of the device status data of the chemical reactor are realized. First, the preprocessing unit performs data cleaning, denoising, format conversion, and normalization processing on the data, ensuring the accuracy, consistency, and standardization of the data, making subsequent analysis more scientific. Further, the system classifies the processed data according to various factors, and this detailed classification significantly improves the data operability and traceability. In addition, the cloud storage unit combines real-time data storage and historical data storage, and comprehensively manages the device 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 requirements, and at the same time provide efficient data historical backtracking capabilities, facilitating subsequent analysis and evaluation, and significantly improving the monitoring accuracy of chemical reaction equipment and the intelligent level of data management.

[0097] Embodiment 4

[0098] This embodiment is an explanatory description based on Embodiment 3. Please refer to Figure 1 , specifically: The cloud platform data extraction module includes a data access unit and a data extraction unit;

[0099] The data access unit is used to access the device security data group in the cloud data historical storage system, filter the data according to the required conditions based on 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;

[0100] The data extraction unit is used to extract the device security data group in the cloud data real-time storage system and the historical device security data group filtered by the data access unit in real time, and transmit the extracted device security data group to the cloud platform analysis module in real time.

[0101] In this embodiment, the cloud platform data extraction module significantly improves the efficiency of obtaining and analyzing device security 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 device security data in the historical storage system, but also accurately filter the data according to data type, data source, sensor ID, sensor measurement value, and acquisition timestamp, enabling the platform to quickly locate and extract data in specific scenarios and ensuring the relevance and timeliness of the data. Subsequently, the data extraction unit will immediately 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 the unnecessary data transmission and processing burden, but also ensures that the analysis module obtains the most relevant and screened historical data and the latest real-time data, facilitating the dynamic tracking and accurate analysis of the device 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 contributing to more timely and accurate device status evaluation and fault prediction.

[0102] Embodiment 5

[0103] This embodiment is an explanatory description based on Embodiment 4. Please refer to Figure 1 , specifically: The cloud platform analysis module includes an internal cavity gas fluctuation calculation unit, a fluid viscosity variation calculation unit, a heat flux density fluctuation calculation unit, and a wall pressure change calculation unit;

[0104] The internal cavity gas fluctuation calculation unit is used to perform a summary calculation based on the obtained internal cavity gas fluctuation factor data group to obtain the internal cavity gas fluctuation coefficient Nqt;

[0105] The internal cavity gas fluctuation coefficient Nqt is calculated and obtained through the following formula;

[0106] ;

[0107] In the formula, N represents the number of samplings, qt i represents the reaction-generated gas concentration qt of the i-th sampling, qt avg represents the average value of the reaction-generated gas concentration qt of N samplings, represents the change rate of the gas flow F with respect to time t, represents the partial derivative;

[0108] The fluid viscosity variation calculation unit is used to perform a summary calculation based on the obtained fluid viscosity variation factor data group to obtain the fluid viscosity variation coefficient Lnd;

[0109] The fluid viscosity variation coefficient Lnd is calculated and obtained through the following formula;

[0110] ;

[0111] In the formula, ηd i represents the fluid viscosity ηd at the i-th sampling, and ηd avg represents the average value of all sampled fluid viscosities ηd, and N represents the number of samplings;

[0112] The heat flux density fluctuation calculation unit is used to perform summary calculations based on the obtained heat flux density data set to obtain the heat flux density fluctuation coefficient Rmd;

[0113] The heat flux density fluctuation coefficient Rmd is obtained by calculation through the following formula;

[0114] ;

[0115] In the formula, represents the change rate of the heat flux rl with respect to time t, and T grad represents the temperature gradient, the degree of temperature change within a unit distance, and a represents the thermal conductivity.

[0116] The wall pressure change calculation unit is used to perform summary calculations based on the obtained wall pressure change data set to obtain the wall pressure change coefficient Byl;

[0117] The wall pressure change coefficient Byl is obtained by calculation through the following formula;

[0118] ;

[0119] In the formula, represents the change rate of the wall pressure bm with respect to time t.

[0120] In this embodiment, through the design and implementation of the cloud platform analysis module, the internal cavity gas fluctuation coefficient Nqt, the fluid viscosity variation coefficient Lnd, the heat flux density fluctuation coefficient Rmd, and the wall pressure change coefficient Byl can be calculated and monitored efficiently. 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 during the chemical reaction process, the real-time evaluation of these fluctuation coefficients can quickly identify potential abnormal situations, thereby greatly reducing the equipment failure risk and downtime, and improving production efficiency. In addition, the automated analysis ability 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 intelligentization and high efficiency of equipment management, promoting the improvement of production safety and economic benefits in the entire industrial Internet environment.

[0121] Embodiment 6

[0122] This embodiment is explained in Embodiment 5. Please refer to Figure 1 , specifically: The chemical reaction stability evaluation module includes a chemical reaction stability calculation unit and a chemical reaction stability evaluation unit;

[0123] The chemical reaction stability calculation unit is used to perform a summary calculation based on the obtained inner cavity gas fluctuation coefficient Nqt, fluid viscosity variation coefficient Lnd, and heat flux density fluctuation coefficient Rmd to obtain the chemical reaction stability index HXF;

[0124] The chemical reaction stability index HXF is obtained through the following formula;

[0125] ;

[0126] In the formula, e represents the exponential function, k1, k2, and k3 respectively represent the weight coefficients of the inner cavity gas fluctuation coefficient Nqt, fluid viscosity variation coefficient Lnd, and heat flux density fluctuation coefficient Rmd, and k1 + k2 + k3 = 1. Their specific values are set by the user according to the actual situation.

[0127] The chemical reaction stability evaluation unit is used to access the device safety data group in the cloud data historical storage system, analyze the historical chemical reaction stability average value through the cloud platform, set 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 according to the evaluation result. The specific evaluation scheme is as follows;

[0128] When the chemical reaction stability index HXF ≥ the chemical reaction stability threshold A, it indicates that the device is working normally, maintains normal monitoring, and triggers a secondary evaluation mechanism;

[0129] When the chemical reaction stability index HXF < the chemical reaction stability threshold A, it indicates that the device is working abnormally. At this time, the cloud platform generates a first warning report and transmits the first warning report to the relevant personnel's mobile device through the Internet to notify the relevant personnel to adjust the abnormal data.

[0130] In this embodiment, the design and implementation of the chemical reaction stability evaluation module have greatly improved the operating safety and efficiency of the chemical reactor. By calculating the chemical reaction stability index HXF in real time and conducting a preliminary evaluation with the preset chemical reaction stability threshold A, this module can quickly identify the working state of the equipment. When the equipment is normal, it maintains the monitoring state and triggers a secondary evaluation mechanism to continuously monitor the stability of the reaction process. When an abnormality occurs, the system automatically generates a warning report and immediately transmits it to the mobile devices of relevant personnel, prompting them to take corresponding measures quickly. This mechanism not only shortens the response time and reduces the delay risk 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 an important guarantee for production safety and ultimately meeting the higher requirements of the chemical industry for intelligence, automation, and high efficiency.

[0131] Example 7

[0132] This embodiment is an explanatory description based on Example 6. Please refer to Figure 1 , specifically: The equipment deterioration evaluation module includes an equipment deterioration calculation unit and an equipment deterioration evaluation unit;

[0133] The equipment deterioration calculation unit is used to summarize and calculate based on the obtained chemical reaction stability index HXF and the wall pressure change coefficient Byl when initially evaluating that the equipment is working normally, and obtain the equipment deterioration index LHZ;

[0134] The equipment deterioration index LHZ is obtained through the following formula;

[0135] .

[0136] The equipment deterioration evaluation unit is used to preset the equipment deterioration threshold B, conduct a secondary evaluation with the obtained equipment deterioration index LHZ, and generate a warning message based on the evaluation result. The specific secondary evaluation scheme is as follows;

[0137] When the equipment deterioration index LHZ ≥ the equipment deterioration threshold B, it indicates that the equipment health is not up to standard. At this time, the cloud platform controls the control system of the equipment to shut down the equipment through the Internet, generates a second warning report on the cloud platform, and transmits the second warning report to the mobile device end of relevant personnel through the Internet for equipment inspection;

[0138] When the equipment deterioration index LHZ < the equipment deterioration threshold B, it indicates that the equipment health meets the standard. At this time, normal monitoring is maintained.

[0139] In this embodiment, by introducing the equipment deterioration evaluation module, the industrial Internet intelligent cloud platform has significantly improved the monitoring and maintenance capabilities of the chemical reactor. The equipment deterioration calculation unit of this module relies on the chemical reaction stability index HXF and the wall pressure change coefficient Byl to accurately calculate the equipment deterioration index LHZ, achieving a scientific evaluation of the equipment health status. When the preset equipment deterioration threshold B is reached, the system can automatically issue an alarm and quickly control the equipment to stop, thus 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 continuously monitors it to ensure that the equipment is always in the best working state. This intelligent monitoring and early warning mechanism not only improves the efficiency of equipment management, but also reduces the need for manual intervention, ultimately realizing the optimization of the production process and the effective allocation of resources, saving costs and reducing downtime for the enterprise, and further enhancing the reliability and safety of the equipment.

[0140] Although the embodiments of the present invention have been shown and described, those of ordinary skill in the art can understand that various changes, modifications, substitutions, and variations can be made to these embodiments without departing from the principles and spirit of the present invention. 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, and perform data cleaning, denoising, format conversion and normalization processing to obtain a device safety data group, and then store the device safety data group in a cloud storage system; 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 fluid viscosity variation factor data group includes the inner cavity temperature wd and the inner cavity pressure yl; The heat flux density data set includes equipment surface area mj; 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; ； ； ； 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. and They represent the rate of change of gas flow F and heat flow rl with time t, represents the partial derivative, 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, T grad It represents the temperature gradient, the degree of temperature change per unit distance, and a represents the thermal conductivity; 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; 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 obtained when the equipment is initially assessed to be working normally, obtain the equipment degradation index LHZ, and perform a secondary assessment with the preset equipment degradation threshold B.

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 the intelligent cloud platform architecture for industrial Internet according to claim 1, it 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 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 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 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.

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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