Intelligent stress monitoring system, method and device for natural gas hydrate reaction kettle

Abstract

The invention discloses an intelligent stress monitoring system, method and device for a natural gas hydrate reaction kettle, relates to the technical field of natural gas hydrate full-size mining well simulation test systems, and is applied to the natural gas hydrate full-size mining well simulation test systems. In the system, data acquisition modules are arranged in one-to-one correspondence with a plurality of measuring points on a reaction kettle in a natural gas hydrate full-size mining well simulation test system; the data acquisition module acquires a strain signal at a corresponding measuring point; the multiple analog-to-digital conversion modules respectively convert the strain signals at the multiple measuring points into digital strain signals; the remote monitoring platform determines the stress state of each measuring point according to the multiple digital strain signals, early warning control is completed based on the safety threshold value and the multiple stress states, and the safety monitoring precision of the strength of the reaction kettle in the natural gas hydrate full-size mining well simulation test system can be improved.

Description

Technical Field

[0001] The present application relates to the technical field of a full-scale natural gas hydrate production well simulation test system, and in particular to a stress intelligent monitoring system, method and device for a natural gas hydrate reactor. Background Art

[0002] As an important clean energy source, natural gas hydrate has attracted much attention for its mining technology. The full-scale natural gas hydrate mining well simulation test system is mainly used to study the law of mud and sand flowing into the wellbore of the hydrate reservoir under different mining conditions and the sand control effect of different sand control devices. However, there are many technical difficulties in the natural gas hydrate mining process, such as the complex formation temperature and pressure environment and the variable reservoir structure, which brings great challenges to the design and operation of the full-scale natural gas hydrate mining well simulation test system.

[0003] In general, on-site nondestructive testing, ultrasonic thickness measurement, and on-site physical and chemical failure analysis tests can only detect surface defects. However, the cracks in the full-scale natural gas hydrate production well simulation test system all start from the inner wall of the kettle. The monitoring methods of the production well simulation test system in the existing technology are mostly limited to the collection and analysis of local parameters. For the internal high pressure of 30MPa and the surface minimum temperature of -80℃, there is a lack of comprehensive, real-time, and intelligent monitoring methods, which makes it difficult to ensure the structural strength and operation safety of the system, and it is impossible to detect and warn crack defects in time. Summary of the invention

[0004] The purpose of the present application is to provide a natural gas hydrate reactor stress intelligent monitoring system, method and device, which can improve the accuracy of reactor strength safety monitoring in a natural gas hydrate full-scale production well simulation test system.

[0005] To achieve the above objectives, this application provides the following solutions:

[0006] In a first aspect, the present application provides a stress intelligent monitoring system for a natural gas hydrate reactor, wherein the stress intelligent monitoring system for a natural gas hydrate reactor is applied to a natural gas hydrate full-scale production well simulation test system, wherein the data acquisition module is set in one-to-one correspondence with multiple measuring points on the reactor in the natural gas hydrate full-scale production well simulation test system;

[0007] The plurality of data acquisition modules are all connected to the multi-analog-to-digital conversion module; the multi-analog-to-digital conversion module is connected to the remote monitoring platform;

[0008] The data acquisition module is used to obtain the strain signal at the corresponding measuring point;

[0009] The multi-analog-to-digital conversion module is used to convert the strain signals at multiple measuring points into digital strain signals respectively;

[0010] The remote monitoring platform is used to determine the stress state of each measuring point according to the multiple digital strain signals, and complete early warning control based on the safety threshold and the multiple stress states.

[0011] Optionally, the data acquisition modules at any measuring point are arranged in a three-way right-angle strain rosette.

[0012] Optionally, the data acquisition module is a temperature stress integrated low-temperature acquisition sensor.

[0013] Optionally, the multi-analog-to-digital conversion module includes: a plurality of analog-to-digital conversion units;

[0014] The analog-to-digital conversion unit corresponds one-to-one to the data acquisition module;

[0015] The data acquisition modules are connected to the remote monitoring platform and the corresponding data acquisition modules respectively.

[0016] In a second aspect, the present application provides a method for intelligently monitoring stress of a natural gas hydrate reactor, wherein the method for intelligently monitoring stress of a natural gas hydrate reactor is applied to a stress intelligent monitoring system of a natural gas hydrate reactor as described above, and the method for intelligently monitoring stress of a natural gas hydrate reactor comprises:

[0017] Determine any measuring point as the current measuring point, and obtain the strain signal at the current measuring point;

[0018] Convert the strain signal at the current measuring point into a digital signal to obtain a digital strain signal at the current measuring point;

[0019] According to the digital strain signal at the current measuring point, the stress state of the current measuring point is determined using the stress value algorithm model;

[0020] When the stress state of the current measuring point is greater than the safety threshold, a strength warning of the current measuring point is issued.

[0021] Optionally, the stress value algorithm model is:

[0022]

[0023] Among them, δ1 is the maximum principal stress at the measuring point, E is the elastic modulus of the reactor body material, ε0 is the strain test value in the 0° direction of the measuring point, and ε 90 is the 90° strain test value of the measuring point, μ is the Poisson's ratio of the reactor body material, ε 45 is the strain test value of the measuring point in the 45° direction, δ2 is the minimum principal stress of the measuring point, and α is the principal stress direction of the measuring point.

[0024] In a third aspect, the present application provides a stress intelligent monitoring device for a natural gas hydrate reactor, wherein the stress intelligent monitoring device for a natural gas hydrate reactor applies the stress intelligent monitoring method for a natural gas hydrate reactor, and the stress intelligent monitoring device for a natural gas hydrate reactor comprises:

[0025] The current measuring point strain signal acquisition module is used to determine any measuring point as the current measuring point and acquire the strain signal at the current measuring point;

[0026] A digital strain signal conversion module is used to convert the strain signal at the current measuring point into a digital signal to obtain the digital strain signal at the current measuring point;

[0027] A stress state determination module is used to determine the stress state of the current measuring point using a stress value algorithm model according to the digital strain signal at the current measuring point;

[0028] The strength warning module is used to issue a strength warning for the current measuring point when the stress state of the current measuring point is greater than a safety threshold.

[0029] According to the specific embodiments provided in this application, this application discloses the following technical effects:

[0030] The present application provides a system, method and device for intelligent stress monitoring of a natural gas hydrate reactor. The system analyzes and calculates the stress state of the reactor of a full-scale natural gas hydrate production well simulation test system when it is in a working state based on the collected detection signals, sets a safety threshold of the stress value on the reactor surface, and compares the stress value obtained through monitoring and experience accumulation with the safety threshold. If the stress value is greater than the safety threshold, a warning signal is given. Through intelligent monitoring means, real-time monitoring and evaluation of the structural strength and operational safety of the full-scale natural gas hydrate production well simulation test system are achieved, thereby improving the safety and reliability of the test system.

[0031] This application solves the problem that conventional non-destructive testing methods cannot warn in advance that the reactor cracks from the inside out; uses temperature stress integrated low-temperature acquisition sensors for on-site remote monitoring, solves the correlation between the surface temperature and stress gradient of the low-temperature reactor; realizes the intelligent online monitoring and operation and maintenance of the furnace of the full-scale natural gas hydrate mining well simulation test system, which can reduce the cost of manual inspection and other costs by 400,000 to 500,000 yuan per year; real-time online monitoring of the surface temperature and stress state of the reactor operating in a low-temperature and high-pressure state, 7×24 hours of uninterrupted monitoring to know the stress state of the monitored object, once the stress value reaches the set threshold value, the data is pushed to the cloud in time, and the temperature state of the reactor surface is pushed at the same time, the client timely and accurately judges the structural strength safety state, and continuously analyzes the change trend and fatigue state of the monitoring parts stored in the cloud, which plays a role in monitoring and warning for crack defects; realizes comprehensive monitoring of all key parts of the test system to ensure the comprehensiveness and accuracy of the monitoring data. Using cloud computing and big data analysis technology, the real-time evaluation of the system structure strength and operation status is realized, and the timeliness and accuracy of the evaluation are improved. Set the warning threshold, automatically trigger the warning mechanism, and improve the safety and reliability of the system. Through cloud servers, remote data management and analysis can be achieved to improve management efficiency and convenience. BRIEF DESCRIPTION OF THE DRAWINGS

[0032] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0033] Figure 1 A schematic structural diagram of a full-scale natural gas hydrate production well simulation test system provided in one embodiment of the present application.

[0034] Figure 2 A schematic diagram of a temperature-stress integrated sensor provided in one embodiment of the present application.

[0035] Figure 3 This is a schematic diagram of the installation of a temperature-stress integrated sensor provided in one embodiment of the present application.

[0036] Figure 4 This is a schematic diagram of the key position layout of the reactor of the natural gas hydrate full-scale production well simulation test system provided in one embodiment of the present application.

[0037] Figure 5 A diagram of a collector and controller for a reactor cloud data intelligent monitoring system for a natural gas hydrate full-scale production well simulation test system provided in one embodiment of the present application.

[0038] Figure 6 This is a diagram of the software login interface of the reactor cloud data intelligent monitoring system for a natural gas hydrate full-scale production well simulation test system provided in one embodiment of the present application.

[0039] Figure 7 This is the first schematic diagram of the software interface of the reactor cloud data intelligent monitoring system for the natural gas hydrate full-scale production well simulation test system provided in one embodiment of the present application.

[0040] Figure 8 This is a second schematic diagram of the software interface of the reactor cloud data intelligent monitoring system for the natural gas hydrate full-scale production well simulation test system provided in one embodiment of the present application.

[0041] Fig. 9 A schematic diagram of the structure of a full-scale natural gas hydrate production well simulation test system provided in one embodiment of the present application. DETAILED DESCRIPTION

[0042] The following will be combined with the drawings in the embodiments of the present application to clearly and completely describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0043] In order to make the above-mentioned objects, features and advantages of the present application more obvious and easy to understand, the present application is further described in detail below with reference to the accompanying drawings and specific implementation methods.

[0044] The full-scale natural gas hydrate mining well simulation test system consists of a simulated reactor, a full-scale simulated wellbore, a gas injection module, a liquid injection module, a temperature control module, a pressure-stabilizing production module, a gas-liquid-solid three-phase separation and metering module, a data acquisition and processing module, and an auxiliary system. The device is used to study the performance of sand screens under casing completion and open hole completion. It can be set and collect the flow rate of the fluid in real time, the pressure drop of the sand screen and the formation pressure drop, the inlet pressure and outlet pressure of the system in real time. The data obtained can be processed by special software to obtain the performance curve and evaluation results of the sand screen.

[0045] The reactor in the full-scale natural gas hydrate production well simulation test system is a container that bears a pressure of 30MPa or above. It belongs to the category of pressure vessels in the pressure-bearing category of special equipment. Its safety and reliability are particularly important, especially when some pressure vessels have been used for more than 10 years, their technical indicators decline year by year, and there are also changes in the operating environment, large load changes, abnormal loads and other conditions. The combination of these factors often causes fatigue damage to the equipment after a certain number of years of use. Once an accident occurs, the consequences will be catastrophic.

[0046] In an exemplary embodiment, a stress intelligent monitoring system for a natural gas hydrate reactor is provided, which integrates multiple sensors, cloud computing and big data analysis technologies, solves the problem in the prior art that cracks spread from the inner wall to the outer wall and there is no early warning, realizes real-time monitoring and intelligent evaluation of the structural strength and operating status of the test system, and improves the safety and reliability of the system.

[0047] The intelligent stress monitoring system of the natural gas hydrate reactor is applied to a full-scale natural gas hydrate production well simulation test system. Fig. 9 , the full-scale natural gas hydrate mining well simulation test system - simulation reactor, gas injection module, liquid injection module, pressure-stabilized gas production module, temperature control module, data acquisition processing and display module and other auxiliary system modules. The stress intelligent monitoring system of the natural gas hydrate reactor includes: a multi-analog-to-digital conversion module, a remote monitoring platform and multiple data acquisition modules; the data acquisition module is set one-to-one with multiple measuring points on the reactor in the full-scale natural gas hydrate mining well simulation test system; multiple data acquisition modules are connected to the multi-analog-to-digital conversion module; the multi-analog-to-digital conversion module is connected to the remote monitoring platform; the data acquisition module is used to obtain the strain signal at the corresponding measuring point; the multi-analog-to-digital conversion module is used to convert the strain signals at multiple measuring points into digital strain signals respectively; the remote monitoring platform is used to determine the stress state of each measuring point according to multiple digital strain signals, and complete early warning control based on safety thresholds and multiple stress states. The arrangement of the data acquisition module at any measuring point is a three-way right-angle strain rosette. The data acquisition module is an integrated low-temperature acquisition sensor for temperature and stress. The multi-analog-to-digital conversion module includes: multiple analog-to-digital conversion units; the analog-to-digital conversion units correspond to the data acquisition modules one by one; the data acquisition modules are connected to the remote monitoring platform and the corresponding data acquisition modules respectively. The collected temperature and stress alarm values ​​form a temperature stress alarm curve, which is used to characterize the stress alarm values ​​at different temperatures.

[0048] In this embodiment, a temperature-stress integrated sensor is arranged at the part (i.e., the measuring point) that is prone to cracking in the full-scale natural gas hydrate mining well simulation test system, and the stress state of the key parts of the reactor of the simulation test system is monitored online in real time. The temperature and stress state of the monitored object are monitored 24 hours a day, 7 days a week. Once the stress value reaches the set threshold, the data is pushed to the cloud (remote monitoring platform) in time. The client can judge the structural strength state in a timely and accurate manner, and continuously analyze the change trend and fatigue state of the monitoring part stored in the cloud, which plays a role in monitoring and early warning of crack defects. This method is oriented towards process detection and monitoring, and combines the methods and functions of remote intelligent monitoring of cloud data. It applies advanced sensor technology, data acquisition technology, information communication technology, and mathematical model analysis technology to realize intelligent cloud data monitoring of the strength and safety of the simulation test system.

[0049] A temperature stress integrated sensor is set in the full-scale natural gas hydrate mining well simulation test system. The model of the temperature stress integrated sensor is YT-YL-1WD-2022R0009-01. The surface temperature of the reactor in the simulation test system is between 0℃ and -80℃. The sensor is a custom-designed and manufactured low-temperature resistant temperature stress integrated sensor, which is arranged on the surface of the reactor to monitor its temperature changes and stress changes during operation. The temperature stress change signal is collected and transmitted to the cloud after the signal conditioning module or the analog-to-digital conversion module, and stored in the form of cloud data. The cloud data analyzes and calculates the stress state of the reactor shell in the working state according to the collected detection signal. The safety threshold of the stress value of the reactor shell is set, and the stress value obtained by monitoring and experience accumulation is compared with the safety threshold. If it is greater than the safety threshold, an early warning signal is given. The early warning signal is remotely transmitted through the Internet such as 4G / 5G signals, and data is pushed through SMS, email, client and other forms. By installing a temperature stress integrated sensor on the key part of the reactor surface, the real-time collected status data is sent to the cloud, and the cloud data analysis is used to judge its danger level to achieve remote intelligent monitoring.

[0050] The method of using the intelligent stress monitoring system for the natural gas hydrate reactor shown in this embodiment is as follows.

[0051] Step 1: Figure 2 The temperature stress integrated sensor is installed in Figure 1 The surface of the reactor of the full-scale natural gas hydrate mining well simulation test system is shown. After professional design, calculation, testing and calibration, a special -80℃ low-temperature resistant sensor is customized, and the sensor technical parameters are customized according to the requirements of Table 1.

[0052] Table 1 Sensor parameters

[0053]

[0054]

[0055] Step 2: Install and arrange the temperature and stress integrated sensor according to Figure 3 way.

[0056] Step 3: According to Figure 4 The temperature stress integrated sensor is arranged as shown.

[0057] Further, the temperature stress integrated sensor is Figure 4 Connect to a single reactor, or follow Figure 5 Connect multiple welding machines.

[0058] Further work is done on the architecture of the monitoring system.

[0059] Step 4: Collect stress change signals and transmit them to the cloud after passing through the signal conditioning module or analog-to-digital conversion module, and store them in the form of cloud data; the stress strain signal conditioning module first receives the original signals from the stress strain sensor (such as resistance change, voltage change, etc.), and then amplifies these signals through the internal circuit to improve the signal strength and signal-to-noise ratio. Then, according to the needs, the signal is converted, such as converting analog signals into digital signals, or converting voltage signals into current signals. During the conversion process, the module will use isolation technologies such as magnetoelectricity to achieve mutual isolation of input and output signals to eliminate ground loop interference and common mode interference. Finally, the processed signal is output to the control system or data acquisition equipment.

[0060] The main function of the analog-to-digital conversion module is to convert the analog stress and strain signals into digital signals for processing, analysis and storage by computers, microcontrollers or other digital systems. These signals reflect the stress or strain state of the object being measured. The analog-to-digital conversion module receives these analog signals and converts them into digital signals through internal conversion mechanisms (such as successive approximation, integral, parallel comparison, etc.).

[0061] When the fatigue stress amplitude of the reactor structural material Q345 reaches more than 100MPa, it is a stage where fatigue cracks may appear in many places, and once cracks appear, the rate of expansion will be very fast. The first-level warning signal is set at 90MPa and the second-level alarm signal is set at 100MPa.

[0062] Considering that the weld near the reactor is a spherical surface, the stress state of the measuring point is a three-dimensional stress state, and a three-dimensional right-angle strain rosette (3 channels) needs to be arranged at the measuring point; where stress concentration occurs, the stress state of the measuring point is a three-dimensional stress state. In addition to the two principal stress values ​​of the measured point, the principal stress direction is also unknown. 45° three-dimensional right-angle strain rosettes are arranged at these key locations. By installing a temperature stress integrated sensor at the key parts of the reactor surface, the real-time collected status data is sent to the cloud, and the cloud data analysis is used to determine its danger level to achieve remote intelligent monitoring.

[0063] Step 5: Figure 6 , Figure 7 and Figure 8 As shown, the monitoring software system performs real-time remote intelligent monitoring and can give an alarm in time when there are signs of accidents or unexpected events in the structure. Furthermore, the cloud data intelligent monitoring software of the reactor of the natural gas hydrate full-scale mining well simulation test system is based on the B / S architecture, and the database adopts the My SQL data management system, which integrates data acquisition and analysis, graphic display, remote control and data management. The interface is simple and beautiful, easy to operate, and the clamping force monitoring content of the welding machine is fully and intuitively displayed. The early warning signal is remotely transmitted through the Internet such as 4G / 5G signals, and data is pushed through various forms such as SMS, email, and client.

[0064] Step 6: Figure 7 and Figure 8 As shown, in the full-scale natural gas hydrate production well simulation test system, the reactor intelligent monitoring software system can process historical monitoring data (including access, trend analysis and report analysis).

[0065] Access to historical monitoring data: Allow users to query, retrieve and browse historical monitoring data stored in the database. Support filtering and searching by time range and specific conditions (such as location, device ID, parameter type, etc.). Provide data preview, download and export functions to facilitate users to further analyze or share data with other systems. Implementation points: Design efficient data storage solutions, such as using relational databases or NoSQL databases, and choose appropriate storage methods based on data size and query requirements. Implement flexible query interfaces and support SQL queries or custom query languages ​​to cope with complex query requirements. Provide user-friendly interfaces, such as web-based query interfaces or mobile applications, to facilitate users to access data anytime, anywhere.

[0066] Trend analysis: Use visualization tools to display trend changes in monitoring data, such as line charts, bar charts, scatter plots, etc. Support statistical analysis of trends, such as calculating average values, maximum values, minimum values, standard deviations, etc. Provide anomaly detection functions to automatically identify and mark abnormal points or trend changes in data.

[0067] Implementation points: Integrate powerful visualization libraries (such as D3.js, ECharts, Highcharts, etc.) to achieve dynamic visualization of data. Develop data analysis algorithms, such as time series analysis, cluster analysis, etc., to deeply explore the laws and patterns behind the data. Design user-customizable views and panels to allow users to configure and save analysis views according to their needs.

[0068] Report analysis automatically generates and displays reports in various formats, such as PDF, Excel, HTML, etc., to meet the reading needs of different users. Report customization is supported, and users can select data sources, report templates, and display content as needed. Reports can be generated and pushed at a scheduled time, such as notifying users via email or messages.

[0069] Key points: Design a flexible report template system to support user-defined report styles and content. Implement a report generation engine that can automatically generate reports based on templates and data sources. Integrate email services or message push services to implement scheduled report delivery and notification functions. Provide reliable data support for understanding the crack status of the furnace shell and analyzing the crack causes and the resulting structural damage.

[0070] In an exemplary embodiment, a method for intelligently monitoring stress of a natural gas hydrate reactor is provided. The method for intelligently monitoring stress of a natural gas hydrate reactor is applied to an intelligently monitoring stress system of a natural gas hydrate reactor. The method for intelligently monitoring stress of a natural gas hydrate reactor comprises:

[0071] S1: Determine any measuring point as the current measuring point and obtain the strain signal at the current measuring point.

[0072] S2: Convert the strain signal at the current measuring point into a digital signal to obtain a digital strain signal at the current measuring point.

[0073] S3: According to the digital strain signal at the current measuring point, the stress state of the current measuring point is determined using the stress value algorithm model.

[0074] S4: When the stress state of the current measuring point is greater than the safety threshold, a strength warning of the current measuring point is issued.

[0075] The stress value algorithm model is:

[0076]

[0077] Among them, δ1 is the maximum principal stress at the measuring point, E is the elastic modulus of the reactor body material, ε0 is the strain test value in the 0° direction of the measuring point, and ε 90 is the 90° strain test value of the measuring point, μ is the Poisson's ratio of the reactor body material, ε45 is the strain test value of the measuring point in the 45° direction, δ2 is the minimum principal stress of the measuring point, and α is the principal stress direction of the measuring point.

[0078] The stress range of the reactor is calculated by the above formula. In the strength monitoring of the reactor, the formula for the frequency statistics of the stress range is:

[0079]

[0080] Among them, C and K are the S-N curve constants of the main beam structure, r is the series of stress variation in the load spectrum, and f i is the frequency of occurrence of each level of variation, is the number of stress ranges at each level, D is the sum of damage when the structure is destroyed, N is the total number of ranges in the spectrum time t, the spectrum time t refers to the actual number of working cycles (working time) represented by a load spectrum, and n is the number of repetitions of the load spectrum when the structure is destroyed. The analysis selected D = 0.8, C = 1011.714486, K = 3.3, among which the selection of damage and D when the structure is destroyed is different. The selection of this parameter has an important influence on the test conclusion. After field practice, it is believed that the selection of 0.80 is closer to the actual situation and the data is more accurate. Through the above formula, the fatigue strength of the reactor can be calculated through the monitored stress data.

[0081] In an exemplary embodiment, a stress intelligent monitoring device for a natural gas hydrate reactor is provided. The stress intelligent monitoring device for a natural gas hydrate reactor uses a stress intelligent monitoring method for a natural gas hydrate reactor. The stress intelligent monitoring device for a natural gas hydrate reactor includes:

[0082] The current measuring point strain signal acquisition module is used to determine any measuring point as the current measuring point and acquire the strain signal at the current measuring point.

[0083] The digital strain signal conversion module is used to convert the strain signal at the current measuring point into a digital signal to obtain the digital strain signal at the current measuring point.

[0084] The stress state determination module is used to determine the stress state of the current measuring point according to the digital strain signal at the current measuring point using the stress value algorithm model.

[0085] The strength warning module is used to issue a strength warning for the current measuring point when the stress state of the current measuring point is greater than a safety threshold.

[0086] The technical features of the above embodiments may be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0087] This article uses specific examples to illustrate the principles and implementation methods of this application. The description of the above embodiments is only used to help understand the method and core ideas of this application. At the same time, for those skilled in the art, according to the ideas of this application, there will be changes in the specific implementation methods and application scope. In summary, the content of this specification should not be understood as limiting this application.

Claims

1. A stress intelligent monitoring system for a natural gas hydrate reactor, characterized in that: The stress intelligent monitoring system of the natural gas hydrate reactor is applied to a natural gas hydrate full-scale mining well simulation test system. The stress intelligent monitoring system of the natural gas hydrate reactor includes: a multi-analog-to-digital conversion module, a remote monitoring platform and multiple data acquisition modules; The data acquisition module is arranged in one-to-one correspondence with a plurality of measuring points on the reactor in the natural gas hydrate full-scale production well simulation test system; The plurality of data acquisition modules are all connected to the multi-analog-to-digital conversion module; the multi-analog-to-digital conversion module is connected to the remote monitoring platform; The data acquisition module is used to obtain the strain signal at the corresponding measuring point; The multi-analog-to-digital conversion module is used to convert the strain signals at multiple measuring points into digital strain signals respectively; The remote monitoring platform is used to determine the stress state of each measuring point according to the multiple digital strain signals, and complete early warning control based on the safety threshold and the multiple stress states.

2. The intelligent stress monitoring system for a natural gas hydrate reactor according to claim 1, characterized in that: The arrangement of the data acquisition modules at any measuring point is a three-way right-angle strain rosette.

3. The intelligent stress monitoring system for a natural gas hydrate reactor according to claim 1, characterized in that: The data acquisition module is a temperature stress integrated low-temperature acquisition sensor.

4. The intelligent stress monitoring system for a natural gas hydrate reactor according to claim 1, characterized in that: The multi-analog-to-digital conversion module comprises: a plurality of analog-to-digital conversion units; The analog-to-digital conversion unit corresponds one-to-one to the data acquisition module; The data acquisition modules are connected to the remote monitoring platform and the corresponding data acquisition modules respectively.

5. A method for intelligently monitoring stress of a natural gas hydrate reactor, characterized in that: The method for intelligently monitoring stress of a natural gas hydrate reactor is applied to a system for intelligently monitoring stress of a natural gas hydrate reactor as claimed in any one of claims 1 to 4, and the method for intelligently monitoring stress of a natural gas hydrate reactor comprises: Determine any measuring point as the current measuring point, and obtain the strain signal at the current measuring point; Convert the strain signal at the current measuring point into a digital signal to obtain a digital strain signal at the current measuring point; According to the digital strain signal at the current measuring point, the stress state of the current measuring point is determined using the stress value algorithm model; When the stress state of the current measuring point is greater than the safety threshold, a strength warning of the current measuring point is issued.

6. The method for intelligent stress monitoring of a natural gas hydrate reactor according to claim 5, characterized in that: The stress value algorithm model is: Among them, δ1 is the maximum principal stress of the measuring point, E is the elastic modulus of the reactor body material, ε0 is the strain test value in the 0° direction of the measuring point, ε90 is the strain test value in the 90° direction of the measuring point, μ is the Poisson's ratio of the reactor body material, ε 45 is the strain test value of the measuring point in the 45° direction, δ2 is the minimum principal stress of the measuring point, and α is the principal stress direction of the measuring point.

7. A stress intelligent monitoring device for a natural gas hydrate reactor, characterized in that: The intelligent stress monitoring device for a natural gas hydrate reactor uses the intelligent stress monitoring method for a natural gas hydrate reactor as claimed in any one of claims 5 to 6, and the intelligent stress monitoring device for a natural gas hydrate reactor comprises: The current measuring point strain signal acquisition module is used to determine any measuring point as the current measuring point and acquire the strain signal at the current measuring point; A digital strain signal conversion module is used to convert the strain signal at the current measuring point into a digital signal to obtain the digital strain signal at the current measuring point; A stress state determination module is used to determine the stress state of the current measuring point using a stress value algorithm model according to the digital strain signal at the current measuring point; The strength warning module is used to issue a strength warning for the current measuring point when the stress state of the current measuring point is greater than a safety threshold.

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