Thermal physical property and stability comprehensive measuring device and method suitable for molten salt containing impurities

Abstract

The application discloses a comprehensive measuring device and method for thermophysical properties and stability of molten salt containing impurities, and relates to the technical field of molten salt detection. The measuring device comprises a high-temperature sealed reaction cavity, an integrated multi-parameter sensing and measuring module, a dynamic thermal cycle driving module, an impurity self-adaptive processing module, a data processing module and an industrial computer main control unit. The measuring method is to simulate actual engineering conditions by the dynamic thermal cycle driving module, and to perform dynamic thermal cycle on the molten salt containing impurities. In the dynamic thermal cycle process, the multi-parameter sensing and measuring module is used to measure the thermophysical properties of the molten salt containing impurities. After the dynamic thermal cycle, the data processing module is used to process the thermophysical properties, and the industrial computer main control unit is used to calculate the comprehensive stability. When the engineering network is good or the local measurement result is suspicious, the data is uploaded to the cloud, and the CNN neural network model pre-trained in the cloud is used for verification and calibration. The application takes into account the mechanism and data, and provides a selection basis for engineering application of the molten salt containing impurities.

Description

Technical Field

[0001] This invention relates to the field of molten salt detection technology, specifically to a comprehensive measurement device and method for the thermophysical properties and stability of molten salt containing impurities. Background Technology

[0002] Molten salt, as a core material in high-temperature energy storage, nuclear reactor cooling, and chemical media, directly determines the safety and reliability of engineering applications through its thermal properties (density, viscosity, thermal conductivity, specific heat, primary crystallization temperature, electrical conductivity, etc.) and thermal stability (property drift and compositional evolution during thermal cycling, etc.). In practical engineering scenarios, molten salt inevitably contains impurities such as metal ions, oxides, and carbides (typically ranging from 0.1% to 5 wt%). These impurities significantly affect the thermal properties of molten salt, accelerate its compositional deterioration, and consequently lead to safety hazards such as equipment corrosion and reduced system efficiency. Therefore, achieving accurate and simultaneous measurement of the thermal properties and stability of impurity-containing molten salts is of great significance for optimizing molten salt formulations and adapting them to engineering applications. Currently, existing molten salt measurement technologies have formed a certain research foundation.

[0003] Chinese patent (publication number CN114674870B) discloses a high-temperature liquid molten salt thermophysical property parameter measuring device and parameter inversion method. This method achieves multi-parameter thermophysical property measurement through single-cavity integration, attempting to solve the problem of cumbersome traditional single-parameter measuring equipment. However, this method does not consider the interference of large impurities in molten salt on the measurement. Its measurement object is only suitable for high-purity molten salt and cannot be adapted to the measurement scenario of molten salt containing impurities. Moreover, its sensor does not adopt a structural design that resists impurity adhesion and polarization. During the measurement process, the measurement accuracy is easily reduced due to impurity adhesion and polarization. In addition, this method cannot simulate the alternating hot and cold cycle under actual engineering conditions. It can only realize the thermophysical property measurement under static conditions and cannot simultaneously acquire the property drift data during the thermal cycle process, thus failing to complete the stability assessment.

[0004] Chinese patent (publication number CN117030586B) discloses a device for testing the corrosion and thermal stability of molten salt flow, the core of which is to monitor the corrosion and thermal stability of molten salt in flow state; however, this method does not integrate any thermophysical parameter measurement module, and can only realize partial monitoring related to corrosion and stability, and cannot simultaneously measure thermophysical parameters such as density, viscosity, and thermal conductivity, resulting in the separation of thermophysical and stability data, and the inability to establish the correlation between the two; in addition, the device does not provide a quantitative stability assessment algorithm, and cannot calculate the comprehensive stability index through thermophysical drift rate and impurity concentration change rate, and can only make qualitative judgments, and cannot provide accurate data support for engineering applications.

[0005] Chinese patent (publication number CN120594617A) discloses a highly adaptable in-situ monitoring method for molten salt thermal storage systems, the core of which lies in the electrochemical monitoring of impurity ions in molten salt. However, this patent only focuses on the single monitoring of impurity ions, without involving the measurement of any thermophysical parameters or integrating a thermal cycle drive module, and thus cannot achieve comprehensive measurement of thermophysical properties and stability. In addition, the impurity monitoring in this patent only adopts an electrochemical method, without setting up an impurity adaptive treatment structure such as physical filtration, vacuum degassing, and inert gas protection, which cannot maintain the stability of the composition during the molten salt measurement process, and cannot intercept the interference of large particulate impurities on the measurement.

[0006] To address the shortcomings of the existing technologies, there is an urgent need to develop a comprehensive measurement device and method that can adapt to molten salt measurement scenarios containing impurities, achieve simultaneous measurement of thermal properties and stability, possess impurity adaptive processing capabilities, and enable stability assessment through quantification algorithms. This would solve the technical challenges of existing technologies failing to meet practical engineering needs. Summary of the Invention

[0007] Based on the above-mentioned technical problems, this application discloses a comprehensive measurement device for the thermal properties and stability of molten salt containing impurities, specifically including: a high-temperature sealed reaction chamber, an integrated multi-parameter sensing and measurement module, a dynamic thermal cycle driving module, an impurity adaptive processing module, a data processing module, and an industrial control computer main control unit; The high-temperature sealed reaction chamber is the core carrier. Its internal cavities are respectively sealed and connected to the input end of the integrated multi-parameter sensing and measurement module, sealed and connected to the liquid inlet and outlet ends of the dynamic thermal cycle drive module, and sealed and connected to the output end of the impurity adaptive processing module. The integrated multi-parameter sensing and measurement module collects thermophysical parameters, including density, viscosity, thermal conductivity, DSC specific heat temperature and electrical conductivity. All signal output terminals are electrically connected to the signal input terminals of the data processing module, including a density measurement unit, a viscosity measurement unit, a laser flash thermal conductivity measurement unit, a DSC specific heat temperature measurement unit and a four-electrode electrical conductivity measurement unit. The dynamic thermal cycle drive module simulates actual engineering conditions to realize dynamic hot and cold alternation cycle of molten salt containing impurities. Its input end is electrically connected to the control output end of the data processing module, and includes an electromagnetic pump, a heat tracing pipeline, a heat exchanger and a flow regulating valve. The impurity adaptive processing module provides a pure and stable molten salt environment for thermophysical property and stability measurements, including a multi-stage microporous ceramic filter, a vacuum filtration pump, an online spectral monitoring probe, and an inert gas source; The data processing module is electrically connected to the high-temperature sealed reaction chamber, the integrated multi-parameter sensing and measurement module, and the dynamic thermal cycle drive module, respectively, and converts the collected analog signals into digital signals and transmits them to the industrial computer main control unit. It includes a signal isolation amplifier, an A / D converter, and a multi-channel data acquisition card. The industrial control computer main control unit is bidirectionally electrically connected to the data processing module, receives digital signals transmitted by the data processing module, and outputs preset control logic instructions, impurity correction algorithm instructions, and comprehensive stability evaluation instructions.

[0008] Preferably, the integrated multi-parameter sensing and measurement module specifically comprises: The density measurement unit includes a platinum sinker suspended in the internal cavity and a high-precision electronic balance. The platinum sinker, as the input end of the unit, extends below the molten salt surface and its surface is sputtered with a Ta-Ir anti-adhesion coating. The high-precision electronic balance outputs a buoyancy signal. The input end of the viscosity measurement unit is a coaxial cylindrical rotor that extends into the molten salt. It is connected to the drive mechanism using a magnetic fluid sealing structure to prevent high-temperature molten salt and impurities from contaminating the drive components and outputs a torque signal. The laser flash thermal conductivity measurement unit includes a CVD diamond optical window, a laser emitter, and a temperature response detector installed on the side wall of the furnace. The emitting end of the laser emitter and the detection end of the temperature response detector serve as the input ends of the unit. They are connected to the internal cavity through the CVD diamond optical window and output a temperature response curve signal. The input terminals of the DSC specific heat temperature measurement unit are the DSC crucible and the heat flow sensor. The DSC crucible is placed in the molten salt inside the high-temperature resistant crucible, and the heat flow sensor is attached to the outer wall of the DSC crucible, outputting heat flow and temperature curve signals. The input of the four-electrode conductivity measurement unit consists of four platinum-iridium alloy electrodes that extend into the molten salt. It employs an anti-impurity polarization design and outputs an AC impedance signal. The input terminals of each unit are physically isolated.

[0009] Preferably, the impurity adaptive processing module specifically comprises: The multi-stage microporous ceramic filter is installed in series on the feed pipe of the internal cavity. Its input end is connected to the molten salt feed device, and its output end is sealed and connected to the feed port of the internal cavity to intercept large particle impurities. The control input terminal of the vacuum filtration pump is electrically connected to the control output terminal of the data processing module, and its output terminal is sealed and connected to the internal cavity to perform vacuum degassing treatment on the internal cavity. The input end of the online spectral monitoring probe extends into the molten salt inside the internal cavity through a high-temperature resistant optical fiber, and its signal output end is electrically connected to the signal input end of the data processing module. It collects the characteristic spectral absorption intensity of impurity ions in the molten salt in real time and outputs the impurity concentration signal. The output end of the inert gas source is sealed and connected to the inert atmosphere interface of the internal cavity, and its control input end is electrically connected to the control output end of the data processing module to control the inert gas flow rate and pressure.

[0010] Preferably, the data processing module specifically comprises: The input of the signal isolation amplifier is connected to the signal output of each unit of the integrated multi-parameter sensing and measurement module, the light intensity signal of the online spectral monitoring probe, and the operating status signal of the electromagnetic pump, respectively, to isolate and amplify various signals and avoid signal interference. The input terminal of the A / D converter is electrically connected to the output terminal of the signal isolation amplifier, and the output terminal is electrically connected to the multi-channel data acquisition card to convert analog signals into digital signals. The multi-channel data acquisition card is bidirectionally electrically connected to the main control unit of the industrial control computer, transmitting all acquired digital signals to the main control unit of the industrial control computer, and receiving control commands output by the main control unit of the industrial control computer and forwarding them to the control input terminals of each module.

[0011] The method for comprehensively measuring the thermophysical properties and stability of molten salts containing impurities, as described above, is as follows: The molten salt sample containing impurities is fed into the internal cavity of the high-temperature sealed reaction chamber through the feed pipeline; After the sample passes through the multi-stage microporous ceramic filter of the impurity adaptive processing module to filter out large interfering impurities, the high-pressure sealing flange is closed, and the internal cavity is degassed by a vacuum pump. Inert gas is introduced to a slightly positive pressure to obtain a stable molten salt containing impurities. The initial impurity concentration is collected by an online spectral monitoring probe. Based on stable molten salt containing impurities, the industrial computer main control unit outputs temperature setting instructions to the data processing module, and the dynamic thermal cycle drive module controls the heating. After the molten salt is heated to the set test temperature, the industrial computer main control unit outputs cycle control instructions to the dynamic thermal cycle drive module to simulate the actual engineering conditions and perform dynamic hot and cold alternation cycle of the molten salt containing impurities. The integrated multi-parameter sensing and measurement module is activated to simultaneously collect the thermophysical parameters of the molten salt containing impurities, including density, viscosity, thermal conductivity, DSC specific heat temperature, electrical conductivity and impurity concentration. After the dynamic thermal cycle ends, the main control unit of the industrial computer calls the preset comprehensive stability evaluation algorithm to calculate the comprehensive stability index; Based on the comprehensive stability index, the impurity-containing molten salt was determined to have engineering application stability, and a thermal property and stability assessment report was generated.

[0012] Preferably, the synchronous acquisition of thermophysical parameters of the impurity-containing molten salt specifically involves: during the dynamic alternating hot and cold cycle of the impurity-containing molten salt, the multi-parameter sensing and measurement module synchronously acquires density, viscosity, thermal conductivity, DSC specific heat temperature, electrical conductivity, and impurity concentration in separate units. After the thermal property acquisition is completed, the various raw data are isolated and amplified by the signal isolation amplifier of the data processing module, and then the analog signal is converted into a digital signal by the A / D converter and transmitted to the main control unit of the industrial computer for data storage.

[0013] Preferably, the synchronous acquisition of the sub-units specifically includes: The density measurement unit is immersed in a platinum sinker below the surface of a molten salt solution containing impurities. A high-precision electronic balance collects the buoyancy-related signals of the sinker and converts them into raw density data. The viscosity measurement unit's coaxial cylindrical rotor rotates inside a molten salt containing impurities, collecting rotor torque signals and converting them into raw viscosity data. The laser flash thermal conductivity measurement unit emits a laser to the impurity-containing molten salt through a CVD diamond optical window, and the temperature response detector collects the thermal diffusion signal and converts it into raw thermal conductivity data. The DSC specific heat temperature measurement unit is placed inside the DSC crucible containing impurities in the high-temperature resistant crucible. It synchronously senses the temperature change of the molten salt. The heat flow sensor is attached to the outer wall of the DSC crucible to collect the heat flow and temperature curve signals. The specific heat and corresponding temperature data of the impurities in the molten salt are extracted through curve analysis. The four-electrode conductivity measurement unit extends four platinum-iridium alloy electrodes into the molten salt containing impurities, collects the AC impedance signal between the electrodes, and converts the AC impedance signal into raw conductivity data of the molten salt containing impurities.

[0014] Impurity concentration is collected by using an online spectral monitoring probe to collect the characteristic spectral absorption intensity of target impurity ions in molten salt containing impurities through a high-temperature resistant optical fiber, and then converting it into real-time raw data of impurity concentration.

[0015] Preferably, the comprehensive stability evaluation algorithm specifically involves: after the dynamic thermal cycle ends, calculating the thermal property parameter drift rate during the dynamic thermal cycle based on the collected, processed, and stored thermal property parameters, using the following formula:

[0016] in, For the first The drift rate of each thermophysical property parameter (i=1 corresponds to density, i=2 corresponds to viscosity, i=3 corresponds to thermal conductivity, i=4 corresponds to DSC specific heat temperature, i=5 corresponds to electrical conductivity). This represents the total number of samplings during the dynamic thermal cycling process. To preset the total number of dynamic thermal cycles, For the first During the second sampling Real-time acquired values ​​of the thermophysical parameters, For the first The initial collected values ​​of the thermal property parameters, For the first The average drift rate of all sampling points for a given thermophysical property parameter; The formula for calculating the rate of change in impurity concentration is:

[0017] in, This represents the overall rate of change of impurity concentration throughout the entire dynamic thermal cycle. For the first Real-time impurity concentration at the time of the next sampling The initial impurity concentration, This represents the impurity concentration at the end of the dynamic thermal cycle. The weight of the rate of change in impurity concentration at the end of the cycle; The comprehensive stability index is calculated based on the drift rate of thermophysical parameters and the change rate of impurity concentration.

[0018] Preferably, the calculation of the comprehensive stability index specifically involves: Calculate the combined average drift rate of all thermophysical parameters throughout the entire dynamic thermal cycle. The formula is:

[0019] in, For the first The weights of the thermophysical parameters can be adjusted according to engineering requirements; The weighting coefficients for the stability of preset thermophysical parameters and impurity concentration are used to calculate the comprehensive stability index, using the following formula:

[0020] in, It is the overall stability index of molten salt containing impurities. , These are the weighting coefficients for the stability of thermophysical parameters and the stability of impurity concentration, respectively.

[0021] Preferably, the determination that the impurity-containing molten salt possesses engineering application stability is specifically based on: a comprehensive stability index. and the preset safety and stability threshold for molten salt engineering applications To determine the stability level, when The impurity-containing molten salt was determined to possess excellent stability for engineering applications, making it suitable for high-end precision engineering scenarios; when The impurity-containing molten salt was determined to possess adequate stability for engineering applications and be suitable for conventional engineering scenarios; when The impurity-containing molten salt was determined to have the stability required for optimized engineering applications. Process adjustments were necessary, and optimization suggestions and key parameters exceeding limits were recorded simultaneously. The molten salt containing impurities was determined to lack stability for engineering applications and was prohibited from being used directly in engineering projects. The reasons for the non-compliance were recorded in detail. After receiving the report generation instruction, the industrial computer main control unit automatically integrates all relevant data and completes the data classification and organization according to the preset report template; When the reliability of the network status monitoring results is questionable, the data is uploaded to the cloud for verification and calibration using a pre-trained CNN neural network.

[0022] Compared with the prior art, the technical solution of this application has the following technical effects: This invention integrates six modules, including a high-temperature sealed reaction chamber and an integrated multi-parameter sensing and measurement module, to achieve simultaneous and comprehensive measurement of thermal properties such as density, viscosity, thermal conductivity, DSC specific heat temperature, and electrical conductivity, as well as thermal stability, thereby significantly improving measurement efficiency and data correlation. This invention effectively suppresses the interference of impurities on the measurement process by using a multi-stage filtration, vacuum degassing, online spectral monitoring and inert gas protection design of an impurity adaptive processing module, combined with the sensor's anti-impurity adhesion and anti-polarization structure optimization. This enables accurate measurement of molten salt containing impurities (0.1–5 wt%), breaking through the limitation of existing technologies that are only applicable to high-purity molten salts. This invention simulates actual engineering conditions through a dynamic thermal cycle drive module and, combined with a quantitative comprehensive stability evaluation algorithm, can accurately calculate the drift rate of thermophysical parameters, the change rate of impurity concentration, and the comprehensive stability index. It also enables multi-level engineering application stability determination, providing scientific and accurate data support for molten salt formulation optimization and engineering application adaptation. This invention, through the collaborative design of the data processing module and the industrial control computer main control unit, realizes automated control of the measurement process, synchronous data acquisition and processing, and automatic generation of evaluation reports, further improving the convenience and reliability of measurement and fully meeting the measurement needs of actual engineering scenarios.

[0023] The above description is only an overview of the technical solution of this application. In order to better understand the technical means of this application and implement it in accordance with the contents of the specification, and to make the above and other objects, features and advantages of this application more easily understood, the preferred embodiments of this application are described in detail below with reference to the accompanying drawings.

[0024] The above and other objects, advantages and features of this application will become more apparent to those skilled in the art from the following detailed description of specific embodiments in conjunction with the accompanying drawings. Attached Figure Description

[0025] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort. In all drawings, similar elements or parts are generally identified by similar reference numerals. In the drawings, the elements or parts are not necessarily drawn to scale.

[0026] Based on the description of the figures and their corresponding technical content in the document, the titles of the figures are as follows: Figure 1 This is a structural diagram of a device suitable for comprehensively measuring the thermal properties and stability of molten salt containing impurities. Figure 2 This is a general flowchart for a comprehensive measurement method of the thermophysical properties and stability of molten salts containing impurities; Figure 3 This is a general architecture diagram for a comprehensive measurement method of the thermophysical properties and stability of molten salts containing impurities; Figure 4 This is a structural diagram of the cloud-based CNN neural network model in this application; Figure 5 This is a graph showing the thermophysical property data of a conventional sample at different temperatures in the embodiments of this application; Figure 6 This is a graph showing the stability data of conventional samples at different temperatures in the embodiments of this application; Figure 7 This is a graph showing the thermal properties of abnormal samples at different temperatures in the embodiments of this application; Figure 8 This is a graph showing the stability data of abnormal samples at different temperatures in the embodiments of this application.

[0027] Figure Descriptions: 1. High-temperature sealed reaction chamber; 2. Integrated multi-parameter sensing and measurement module; 3. Dynamic thermal cycle drive module; 4. Impurity adaptive processing module; 5. Data processing module; 6. Industrial control computer main control unit; 7. Density measurement unit; 8. Viscosity measurement unit; 9. Laser flash thermal conductivity measurement unit; 10. DSC specific heat temperature measurement unit; 11. Four-electrode conductivity measurement unit; 12. Electromagnetic pump; 13. Heat tracing pipeline; 14. Heat exchanger; 15. Flow regulating valve; 16. Multi-stage microporous ceramic filter; 17. Vacuum filtration pump; 18. Online spectral monitoring probe; 19. Inert gas source; 20. Signal isolation amplifier; 21. A / D converter; 22. Multi-channel data acquisition card. Detailed Implementation

[0028] To make the objectives, technical solutions, and advantages of the embodiments of this application clearer, the technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, not all embodiments. In the following description, specific details such as specific configurations and modules are provided only to help fully understand the embodiments of this application. Therefore, those skilled in the art should understand that various changes and modifications can be made to the embodiments described herein without departing from the scope and spirit of this application. In addition, for clarity and brevity, descriptions of known functions and structures are omitted in the embodiments.

[0029] It should be understood that the phrase "an embodiment" or "this embodiment" throughout the specification means that a specific feature, structure, or characteristic related to the embodiment is included in at least one embodiment of this application. Therefore, "an embodiment" or "this embodiment" appearing throughout the specification does not necessarily refer to the same embodiment. Furthermore, these specific features, structures, or characteristics can be combined in any suitable manner in one or more embodiments.

[0030] Furthermore, reference numerals and / or letters may be repeated in different examples within this application. Such repetition is for the purpose of simplification and clarity and does not in itself indicate a relationship between the various embodiments and / or settings discussed.

[0031] In this article, the term "and / or" is merely a description of the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can mean: A exists alone, B exists alone, and A and B exist simultaneously. The term " / and" in this article describes another type of relationship between related objects, indicating that two relationships can exist. For example, A / and B can mean: A exists alone, and A and B exist alone. In addition, the character " / " in this article generally indicates that the related objects before and after it are in an "or" relationship.

[0032] In this article, the term "at least one" is merely a description of the relationship between related objects, indicating that there can be three relationships. For example, "at least one of A and B" can mean: A exists alone, A and B exist simultaneously, or B exists alone.

[0033] It should also be noted that, in this document, relational terms such as "first" and "second" are used only to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion.

[0034] Example 1 mainly describes a comprehensive measurement device for the thermophysical properties and stability of molten salt containing impurities, such as... Figure 1 As shown, it specifically includes: 1. High-temperature sealed reaction chamber; 2. Integrated multi-parameter sensing and measurement module; 3. Dynamic thermal cycle drive module; 4. Impurity adaptive processing module; 5. Data processing module; and 6. Industrial control computer main control unit. The high-temperature sealed reaction chamber 1 is the core carrier. Its internal chambers are respectively sealed and connected to the input end of the integrated multi-parameter sensing and measurement module 2, sealed and connected to the liquid inlet and outlet ends of the dynamic thermal cycle drive module 3, and sealed and connected to the output end of the impurity adaptive processing module 4. The integrated multi-parameter sensing and measurement module 2 collects thermal property parameters, including density, viscosity, thermal conductivity, DSC specific heat temperature and electrical conductivity. All signal output terminals are electrically connected to the signal input terminals of the data processing module 5, including density measurement unit 7, viscosity measurement unit 8, laser flash thermal conductivity measurement unit 9, DSC specific heat temperature measurement unit 10 and four-electrode electrical conductivity measurement unit 11. The dynamic thermal cycle drive module 3 simulates actual engineering conditions to realize dynamic hot and cold alternation cycle of molten salt containing impurities. Its input end is electrically connected to the control output end of the data processing module 5, including electromagnetic pump 12, heat tracing pipeline 13, heat exchanger 14 and flow regulating valve 15. The impurity adaptive processing module 4 provides a pure and stable molten salt environment for the measurement of thermophysical properties and stability, including a multi-stage microporous ceramic filter 16, a vacuum filtration pump 17, an online spectral monitoring probe 18, and an inert gas source 19; The data processing module 5 is electrically connected to the high-temperature sealed reaction chamber 1, the integrated multi-parameter sensing and measurement module 2, and the dynamic thermal cycle drive module 3, respectively, and converts the collected analog signals into digital signals and transmits them to the industrial computer main control unit 6, including a signal isolation amplifier 20, an A / D converter 21, and a multi-channel data acquisition card 22; The main control unit 6 of the industrial control computer is bidirectionally electrically connected to the data processing module 5, receives digital signals transmitted by the data processing module 5, and outputs preset control logic instructions, impurity correction algorithm instructions and comprehensive stability evaluation instructions.

[0035] Furthermore, the high-temperature sealed reaction chamber 1 specifically comprises a high-temperature resistant crucible, a furnace body insulation layer, a high-pressure sealing flange, an inert atmosphere interface, and a temperature detection probe; The high-temperature resistant crucible is the core structure of the internal cavity. Its inner wall is made of graphite / boron nitride composite ceramic material, and its outer wall is attached to the furnace body insulation layer. The working temperature range is 300~1200℃. It is resistant to corrosion from fluorine, chloride salts, metal oxides and carbide impurities and is used to contain molten salt samples containing impurities. The high-pressure sealing flange is sealed to the open end of the high-temperature crucible, and multiple sealing interfaces are provided through it, which are respectively used for the input end of the integrated multi-parameter sensing and measurement module 2, the inlet and outlet liquid pipelines of the dynamic thermal cycle drive module 3, the output pipeline of the impurity adaptive treatment module 4, and the inert atmosphere interface. The inert atmosphere interface is connected to the inert gas source 19 in the impurity adaptive treatment module 4 via a pipeline, and is used to fill the internal cavity with Ar or N2 to isolate oxidation and maintain the stability of the molten salt composition. The temperature detection probe extends into the interior of the high-temperature resistant crucible, and its signal output terminal is electrically connected to the signal input terminal of the data processing module 5. It is used to collect the temperature signal of the molten salt inside the cavity in real time and feed it back to the temperature control system.

[0036] Furthermore, the integrated multi-parameter sensing and measurement module 2 specifically includes: the density measurement unit 7, which includes a platinum sinker suspended in the internal cavity and a high-precision electronic balance. The platinum sinker serves as the input end of the unit and extends below the molten salt surface. Its surface is sputtered with a Ta-Ir anti-adhesion coating to reduce the adhesion of impurities on the sinker surface and reduce measurement errors. The signal output end of the high-precision electronic balance feeds back buoyancy-related signals. The input end of the viscosity measurement unit 8 is a coaxial cylindrical rotor that extends into the molten salt. It is connected to the drive mechanism using a magnetic fluid sealing structure to prevent high-temperature molten salt and impurities from contaminating the drive components. Its signal output end feeds back the torque signal. The laser flash thermal conductivity measurement unit 9 includes a CVD diamond optical window, a laser emitter, and a temperature response detector installed on the side wall of the furnace. The emitting end of the laser emitter and the detection end of the temperature response detector serve as the input end of the unit. They are connected to the internal cavity through the CVD diamond optical window to achieve non-contact acquisition of molten salt thermal diffusion signals. The signal output end feeds back the temperature response curve signal. The input terminals of the DSC specific heat temperature measurement unit 10 are the DSC crucible and the heat flow sensor. The DSC crucible is placed in the molten salt inside the high-temperature resistant crucible, and the heat flow sensor is attached to the outer wall of the DSC crucible. The signal output terminal feeds back the heat flow and temperature curve signal. The input of the four-electrode conductivity measurement unit 11 consists of four platinum-iridium alloy electrodes that extend into the molten salt. It adopts an anti-impurity polarization design and the signal output provides feedback of AC impedance signal. The input terminals of each unit are physically isolated to prevent spatial interference, thus avoiding mutual interference between measurement signals and ensuring measurement accuracy.

[0037] Furthermore, the dynamic thermal cycle drive module 3 is specifically configured such that: the control output terminal of the dynamic thermal cycle drive module 3 is electrically connected to the heating wire surrounding the high-temperature resistant crucible, and its signal input terminal is electrically connected to the temperature detection probe of the high-temperature sealed reaction chamber 1. It adopts a PID+fuzzy control algorithm to achieve a temperature control accuracy of ±0.5℃, and is also electrically connected to the data processing module 5 to receive temperature setting commands. The electromagnetic pump 12 serves as a drive unit, with its control input terminal electrically connected to the control output terminal of the data processing module 5 to receive drive control commands; its inlet serves as the input terminal of the module, and is sealed and connected to the outlet at the bottom of the internal cavity through the heat tracing pipeline 13; its outlet serves as the output terminal of the module, and is connected to the input terminal of the heat exchanger 14 through the heat tracing pipeline 13. The control input terminal of the heat exchanger 14 is electrically connected to the control output terminal of the data processing module 5 to receive heating / cooling control commands and adjust the molten salt temperature; its output terminal flows back to the liquid inlet at the top of the internal cavity through the heat tracing pipeline 13, forming a closed loop to realize the forced circulation of molten salt. A flow regulating valve 15 is installed in series on the heat tracing and conveying pipeline 13. Its control input terminal is electrically connected to the control output terminal of the data processing module 5, and is used to regulate the molten salt circulation flow rate. The standard metal corrosion test piece can be detachably installed in the circulation loop downstream of the heat exchanger 14, and is completely immersed in the circulating molten salt. It is used to synchronously acquire dynamic corrosion data of the molten salt containing impurities, and its status can be monitored through the observation window reserved in the loop.

[0038] Furthermore, the impurity adaptive processing module 4 specifically consists of a multi-stage microporous ceramic filter 16 installed in series on the feed pipe of the internal cavity. Its input end is connected to the molten salt feed device, and its output end is sealed to the feed port of the internal cavity. It is used to intercept solid impurities with a particle size greater than 1μm and prevent large particles of impurities from entering the cavity and interfering with the measurement. The control input terminal of the vacuum filtration pump 17 is electrically connected to the control output terminal of the data processing module 5, and its output terminal is sealed and connected to the internal cavity for vacuum degassing treatment of the internal cavity. The input end of the online spectral monitoring probe 18 extends into the molten salt inside the internal cavity through a high-temperature resistant optical fiber. Its signal output end is electrically connected to the signal input end of the data processing module 5, which is used to collect the characteristic spectral absorption intensity of impurity ions in the molten salt in real time and to feed back the impurity concentration signal. The output end of the inert gas source 19 is sealed and connected to the inert atmosphere interface of the internal cavity, and its control input end is electrically connected to the control output end of the data processing module 5 to control the inert gas flow rate and pressure.

[0039] Furthermore, data processing module 5 specifically comprises: The input terminals of the signal isolation amplifier 20 are respectively connected to the signal output terminals of each unit of the integrated multi-parameter sensing and measurement module 2, the light intensity signal of the online spectral monitoring probe 18, and the operating status signal of the electromagnetic pump 12, in order to isolate and amplify various signals and avoid signal interference. The input terminal of the A / D converter 21 is electrically connected to the output terminal of the signal isolation amplifier 20, and the output terminal is electrically connected to the multi-channel data acquisition card 22, which is used to convert analog signals into digital signals; The multi-channel data acquisition card 22 is bidirectionally electrically connected to the main control unit 6 of the industrial computer. On the one hand, it transmits all the acquired digital signals to the main control unit 6 of the industrial computer, and on the other hand, it receives the control commands output by the main control unit 6 of the industrial computer and forwards them to the control input terminals of each module.

[0040] Example 2, based on Example 1, describes in detail a comprehensive measurement method for the thermophysical properties and stability of molten salts containing impurities, such as... Figure 2 , Figure 3 As shown, specifically: The molten salt sample containing impurities is fed into the internal cavity of the high-temperature sealed reaction chamber 1 through the feed pipeline; After the sample passes through the multi-stage microporous ceramic filter 16 of the impurity adaptive processing module 4 to filter out large interfering impurities, the high-pressure sealing flange is closed, and the internal cavity is degassed by the vacuum pump 17. Inert gas is introduced to a slightly positive pressure to obtain a stable molten salt containing impurities, and its initial impurity concentration is collected by the online spectral monitoring probe 18. Based on a stable molten salt containing impurities, the main control unit 6 of the industrial computer outputs a temperature setting command to the data processing module 5, and the dynamic thermal cycle drive module 3 controls the heating. After the molten salt is heated to the set test temperature, the main control unit 6 of the industrial computer outputs a cycle control command to the dynamic thermal cycle drive module 3 to simulate the actual engineering working conditions and perform dynamic hot and cold alternation cycle of the molten salt containing impurities. Start the integrated multi-parameter sensing and measurement module 2 to simultaneously collect the thermophysical parameters of the molten salt containing impurities, including density, viscosity, thermal conductivity, DSC specific heat temperature, electrical conductivity and impurity concentration; After the dynamic thermal cycle ends, the main control unit 6 of the industrial computer calls the preset comprehensive stability evaluation algorithm to calculate the comprehensive stability index; Based on the comprehensive stability index, the impurity-containing molten salt was determined to have engineering application stability, and a thermal property and stability assessment report was generated.

[0041] Furthermore, the vacuum degassing process requires the vacuum level inside the internal cavity to reach 10. -3 Below Pa, the inert gas is Ar or After the gas is introduced, a slight positive pressure is maintained in the cavity to isolate it from air oxidation and ensure the stability of the molten salt containing impurities.

[0042] Furthermore, the circulation parameters of the dynamic thermal cycle drive module 3 can be preset by the main control unit 6 of the industrial computer, including a temperature circulation range of 400~800℃, a number of cycles of 100~500 times, and a circulation flow rate of molten salt containing impurities of 0.01~0.5m / s, which accurately simulates the molten salt operation state under actual engineering conditions.

[0043] Furthermore, the thermophysical parameters of the impurity-containing molten salt are collected simultaneously. Specifically, during the dynamic alternating hot and cold cycle of the impurity-containing molten salt, the multi-parameter sensing and measurement module collects density, viscosity, thermal conductivity, DSC specific heat temperature, electrical conductivity, and impurity concentration in separate units. After the thermal property acquisition is completed, the signal isolation amplifier 20 of the data processing module 5 isolates and amplifies various signals, and then the analog signals are converted into digital signals by the A / D converter 21 and transmitted to the main control unit 6 of the industrial control computer for data storage.

[0044] Furthermore, data is collected synchronously in separate units, specifically as follows: Density measurement unit 7 is immersed below the surface of molten salt containing impurities using a platinum sinker. A high-precision electronic balance collects the sinker's buoyancy-related signals and converts them into raw density data. Viscosity measurement unit 8 uses a coaxial cylindrical rotor to rotate inside molten salt containing impurities, collects rotor torque signals, and converts them into raw viscosity data. The laser flash thermal conductivity measurement unit 9 emits a laser to the impurity-containing molten salt through the CVD diamond optical window, and the temperature response detector collects the thermal diffusion signal and converts it into raw thermal conductivity data. The DSC specific heat temperature measurement unit 10 is placed inside the DSC crucible containing impurity molten salt in a high-temperature resistant crucible. It synchronously senses the temperature change of the molten salt. The heat flow sensor is attached to the outer wall of the DSC crucible to collect the heat flow and temperature curve signals. The specific heat and corresponding temperature data of the impurity molten salt are extracted through curve analysis. The four-electrode conductivity measurement unit 11 extends into the molten salt containing impurities through four platinum-iridium alloy electrodes, collects the AC impedance signal between the electrodes, and converts the AC impedance signal into the raw conductivity data of the molten salt containing impurities.

[0045] Impurity concentration is collected by the online spectral monitoring probe 18 through a high-temperature resistant optical fiber, which collects the characteristic spectral absorption intensity of the target impurity ions in the impurity-containing molten salt and converts it into real-time raw impurity concentration data.

[0046] Furthermore, the viscosity measurement employs a power-law model to fit the apparent viscosity of the impurity-containing molten salt, which is used to correct the original viscosity data. The correction formula is as follows:

[0047] in, Shear rate, As a liquidity behavior index, The shear rate of the impurity molten salt; the main control unit 6 of the industrial computer calculates the impurity concentration based on the synchronously collected data. Automatic adjustment It compensates for measurement errors caused by the shear thinning or thickening effect of molten salt containing impurities, ensuring that the viscosity measurement accuracy is ≤3%.

[0048] Furthermore, the specific heat and corresponding temperature of the molten salt containing impurities are extracted from the heat flow and temperature curve signals acquired by the DSC specific heat and temperature measurement unit 10. The calculation formula is as follows:

[0049] in, For specific heat, The heat corresponding to the heat flow signal. The mass of the molten salt sample in the DSC crucible. This represents the temperature change, and the corresponding temperature is the DSC specific heat temperature.

[0050] Furthermore, the conductivity calculation converts the AC impedance signal acquired by the four-electrode conductivity measurement unit 11 into conductivity data. The calculation formula is as follows:

[0051] in, The conductivity of the molten salt containing impurities. The distance between the two measuring electrodes. For the collected AC impedance, This represents the effective conductive area of ​​the electrode.

[0052] Furthermore, after the dynamic thermal cycle drive module 3 completes the preset number of cycles (100~500 times), it automatically stops running and sends a cycle termination signal to the main control unit 6 of the industrial computer. After receiving the signal, the main control unit 6 of the industrial computer synchronously controls the integrated multi-parameter sensing and measurement module 2 and the online spectral monitoring probe 18 to stop data acquisition and complete the storage and processing of all data.

[0053] Furthermore, the comprehensive stability assessment algorithm is as follows: After the dynamic thermal cycle ends, based on the collected, processed, and stored thermal property parameters, the drift rate of the thermal property parameters during the dynamic thermal cycle is calculated, using the following formula:

[0054] in, For the first The drift rate of each thermophysical property parameter (i=1 corresponds to density, i=2 corresponds to viscosity, i=3 corresponds to thermal conductivity, i=4 corresponds to DSC specific heat temperature, i=5 corresponds to electrical conductivity). This represents the total number of samplings during the dynamic thermal cycling process. To preset the total number of dynamic thermal cycles, For the first During the second sampling Real-time acquired values ​​of the thermophysical parameters, For the first The initial collected values ​​of the thermal property parameters, For the first The average drift rate of all sampling points for a given thermophysical property parameter; The formula for calculating the rate of change in impurity concentration is:

[0055] in, This represents the overall rate of change of impurity concentration throughout the entire dynamic thermal cycle. For the first Real-time impurity concentration at the time of the next sampling The initial impurity concentration, This represents the impurity concentration at the end of the dynamic thermal cycle. The weight of the rate of change in impurity concentration at the end of the cycle; The comprehensive stability index is calculated based on the drift rate of thermophysical parameters and the change rate of impurity concentration.

[0056] Furthermore, the comprehensive stability index is calculated as follows: Calculate the combined average drift rate of all thermophysical parameters throughout the entire dynamic thermal cycle. The formula is:

[0057] in, For the first The drift rate of the thermal property parameter, For the first The weights of the thermophysical parameters can be adjusted according to engineering requirements; The weighting coefficients for the stability of preset thermophysical parameters and impurity concentration are used to calculate the comprehensive stability index, using the following formula:

[0058] in, It is the overall stability index of molten salt containing impurities. This represents the overall rate of change of impurity concentration throughout the entire dynamic thermal cycle. These are the weighting coefficients for the stability of thermophysical parameters and the stability of impurity concentration, respectively.

[0059] Furthermore, the impurity-containing molten salt was determined to possess stability for engineering applications, specifically based on the comprehensive stability index. and the preset safety and stability threshold for molten salt engineering applications To determine the stability level, when The impurity-containing molten salt was determined to possess excellent stability for engineering applications, making it suitable for high-end precision engineering scenarios; when The impurity-containing molten salt was determined to possess adequate stability for engineering applications and be suitable for conventional engineering scenarios; when The impurity-containing molten salt was determined to have the stability required for optimized engineering applications. Process adjustments were necessary, and optimization suggestions and key parameters exceeding limits were recorded simultaneously. The molten salt containing impurities was determined to lack stability for engineering applications and was prohibited from being used directly in engineering projects. The reasons for the non-compliance were recorded in detail. After receiving the report generation instruction, the main control unit 6 of the industrial computer automatically integrates all relevant data and completes the data classification and organization according to the preset report template; When the reliability of the network status monitoring results is questionable, the data is uploaded to the cloud for verification and calibration using a pre-trained CNN neural network.

[0060] Furthermore, the main control unit 6 of the industrial control computer integrates the following content: basic measurement information (molten salt sample number, measurement date, set test temperature, dynamic thermal cycling parameters, etc.), thermophysical parameter data (initial value, real-time sampled value, cumulative drift rate, comprehensive average drift rate), impurity concentration data (initial value, real-time sampled value, comprehensive change rate), comprehensive stability index calculation process and results, multi-level stability judgment results, judgment basis and corresponding level adaptation scenarios (or optimization suggestions).

[0061] Furthermore, the data uploaded to the cloud includes basic data for the entire dynamic thermal cycle (initial / real-time thermophysical parameters, initial / real-time impurity concentration, number of cycles, sampling frequency, operating parameters) and local calculation results; the industrial control computer main control unit 6 uploads the encrypted complete data to the cloud server via industrial Ethernet (or 5G private network); the cloud server receives the data through a preset receiving interface, completes data decryption and verification, and after confirming that the data is complete and unaltered, triggers the cloud CNN inference process.

[0062] Furthermore, the cloud-based CNN neural network inference specifically involves: standardizing and preprocessing the uploaded multi-dimensional basic data, constructing an input feature vector adapted to the CNN model, inputting a CNN model with a structure of 3 convolutional layers, 2 fully connected layers, and 1 output layer, performing forward propagation inference, and outputting the cloud-based CNN inference stability index; When the credibility of local verification is questionable, verification is performed based on the cloud-based CNN inference stability index, and the weights of the local calculation formula are adjusted and recalculated.

[0063] like Figure 4The diagram shows the structure of a cloud-based CNN neural network model. Its input layer has no activation function, and the input feature vector has a dimension of 1×16. Its function is to receive preprocessed input features and provide a basis for subsequent feature extraction. Convolutional layer 1 (Conv1) uses 32 1×3 kernels with a stride of 1, Same padding, ReLU activation function, and 1×16 output dimension. It is used to initially extract shallow features from the input features (such as the trend of changes in basic parameters). Pooling layer 1 (MaxPool1) has no activation function, uses a 1×2 pooling kernel with a stride of 2, uses Valid padding, and has an output dimension of 1×8. It is used to reduce feature dimensions, retain key shallow features, and reduce computational consumption. Convolutional layer 2 (Conv2) uses 64 1×3 kernels with a stride of 1, Same padding, ReLU activation function, and 1×8 output dimension to extract mid-level features (such as parameter coupling change features and operating condition fluctuation features). Pooling layer 2 (MaxPool2) has no activation function, uses a 1×2 pooling kernel with a stride of 2, padding mode of Valid, and an output dimension of 1×4. It is used to further reduce dimensionality, strengthen key mid-layer features, and improve the model's generalization ability. Convolutional layer 3 (Conv3) uses 128 1×3 kernels with a stride of 1, Same padding, ReLU activation function, and 1×4 output dimension to extract deep features (such as parameter correlation features and stability correlation features under abnormal conditions). Pooling layer 3 (MaxPool3) has no activation function, uses a 1×2 pooling kernel with a stride of 2, padding mode of Valid, and an output dimension of 1×2. It is used to compress deep features, retain core feature information, and provide input for the fully connected layer. Fully connected layer 1 (FC1) contains 64 neurons, with a dropout probability of 0.3, an activation function of ReLU, and an output dimension of 1×64. It is used to fuse and map the features extracted by the convolutional layer and transform them into a high-dimensional feature vector. Fully connected layer 2 (FC2) contains 32 neurons, with a dropout probability of 0.3, an activation function of ReLU, and an output dimension of 1×32. It is used to further optimize feature mapping and improve the correlation between features and stability index. The output layer contains one neuron (corresponding to the overall stability level), uses the Softmax activation function, and performs output normalization, with an output dimension of 1.

[0064] Furthermore, the training parameters for the cloud-based CNN neural network are as follows: the optimizer is the Adam optimizer, the initial learning rate is 0.001, and the decay coefficient is 0.99; the loss function is the mean squared error loss function (MSE), the number of training iterations is 500, and the batch size is 32.

[0065] This embodiment describes in detail a comprehensive measurement method for the thermal properties and stability of molten salt containing impurities. A dynamic thermal cycling drive module 3 simulates actual engineering conditions by subjecting the molten salt containing impurities to dynamic thermal cycling. During the dynamic thermal cycling process, a multi-parameter sensing module measures the thermal properties of the molten salt containing impurities. After the dynamic thermal cycling, the thermal property parameters are processed by a data processing module 5, and the comprehensive stability is calculated by an industrial control computer main control unit 6. When the engineering network is good or the local measurement results are questionable, the data is uploaded to the cloud for verification and calibration using a pre-trained CNN neural network model in the cloud.

[0066] Example 3, based on Example 1 or 2, describes in detail the measurement of thermophysical properties and stability assessment of industrial molten salt containing impurities under switching between normal and abnormal operating conditions using this method, as follows: Industrial ternary mixed molten salt NaNO2-KNO3-NaNO was selected as the test sample. Two types of samples were set up. The impurity component under normal operating conditions was a single chloride ion impurity with an initial impurity mass fraction of 0.5 wt% (within the normal industrial allowable range). The impurity under abnormal operating conditions was a complex impurity of chloride ions, metal oxides, and sulfates with an initial impurity mass fraction of 3.8 wt% (far exceeding the normal range, with a significant difference between samples). The normal thermal cycling temperature range was set at 280℃~520℃, and the abnormal operating temperature range was 280℃~600℃. A temperature abrupt change (±40℃) occurred once every 5 cycles.

[0067] The stability grading rules are as follows: Level 1 (highly stable) 0.9~1.0, Level 2 (stable and usable) 0.8~0.9, Level 3 (basically stable) 0.7~0.8, and Level 4 (unstable) <0.7.

[0068] Based on the NIST-Molten-Salts-Database (SRD27) dataset released by the National Institute of Standards and Technology (NIST), and combined with a local database, a feature set of sodium nitrate-potassium nitrate binary mixed molten salt was constructed after data processing and annotation. Based on this feature set, a cloud-based CNN neural network model was pre-trained.

[0069] Two sets of experiments were set up. The first set was based on samples under normal operating conditions, and 80 thermal cycles were performed, with the first 50 cycles under normal operating conditions and the last 30 cycles switching to abnormal operating conditions. 12 sets of data were collected per cycle, and a total of 960 sets of valid data were collected in a single experiment. The thermophysical property data of the normal sample were obtained through a multi-parameter sensing module, as shown in Table 1 below: Table 1. Thermal property data of standard samples

[0070] According to Table 1 and Figure 5 The thermophysical property data of the conventional samples shown at different temperatures demonstrate that the multi-parameter sensing and measurement module of this device is highly sensitive to the thermophysical property measurement of the conventional samples in both normal and abnormal temperature ranges.

[0071] Based on thermophysical parameters, the stability index was calculated locally under the first 50 normal operating conditions with an average value of 0.89 and a fluctuation range of 0.87 to 0.91. The local reliability was determined to be no anomaly, and the cloud CNN inference was not triggered. The stability level was level 2 (stable and available). The average stability index for the last 30 abnormal operating conditions was 0.82, with a fluctuation range of 0.75 to 0.88. Combined with stability data analyzed by professionals, the following results were obtained: Figure 6 The figure shows the stability data of conventional samples at different temperatures. As can be seen from the figure, the stability measured by this method maintains a high degree of fit in all temperature ranges, which verifies the accuracy of this method for conventional samples.

[0072] The second group of samples, based on abnormal operating conditions, underwent 80 thermal cycles, with the first 50 cycles under normal operating conditions and the last 30 cycles under abnormal operating conditions. Measurements were performed using a multi-parameter sensing module, and the resulting thermophysical property data for the abnormal samples are shown in Table 2 below. Table 2. Thermal property data of abnormal samples

[0073] According to Table 2 and Figure 7 The thermophysical property data of the normal samples shown at different temperatures demonstrate that the multi-parameter sensing and measurement module of this device is highly sensitive to the thermophysical property measurement of abnormal samples in both normal and abnormal temperature ranges.

[0074] Based on thermophysical parameters and through local mechanism calculations, the average stability index of the first 50 normal operating conditions was 0.81, with a fluctuation range of 0.78 to 0.84, and the stability level was Level 2 (stable and usable). Under the last 30 abnormal operating conditions, the average stability index was 0.75, with a fluctuation range of 0.64 to 0.86 (fluctuation value 0.22 > threshold 0.15). The local reliability was questionable, triggering cloud-based CNN inference. The average stability index of the cloud-based CNN inference was 0.71, with a fluctuation range of 0.65 to 0.76. Based on this range, the local parameters were adjusted and recalculated, resulting in a corrected average stability index of 0.73, with a fluctuation range of 0.65 to 0.78. The stability level was determined to be Level 3 (basically stable).

[0075] Combining stability data analyzed by professionals, the following results were obtained: Figure 8 The figure shows the thermophysical property data of the abnormal samples at different temperatures. As can be seen from the figure, the method maintains a high degree of fit for abnormal samples under normal conditions, but the error increases under abnormal conditions, thus triggering cloud CNN inference. The cloud CNN inference still maintains a high degree of fit, and the local calculation results adjusted accordingly have a high degree of fit, which verifies the accuracy of the cloud CNN inference and the effectiveness of the adjustment.

[0076] This embodiment details the measurement and stability assessment of the thermophysical properties of industrial molten salt containing impurities under switching between normal and abnormal operating conditions using the proposed method. By comparing the data from local raw calculations, cloud-based CNN inference, local corrected calculations, and professional manual analysis, the stability and fitting degree of each method under different operating conditions are verified. It is demonstrated that the local mechanism calculation method is stable and reliable under normal operating conditions without triggering cloud inference, and under abnormal operating conditions, parameters can be corrected through cloud-based CNN inference to obtain results that highly match professional manual analysis. The method is accurate and effective, with reasonable judgment logic, and can achieve hierarchical stable identification and parameter self-correction.

[0077] The above are merely preferred embodiments of the present invention and are not intended to limit the scope of protection of the present invention. For those skilled in the art, the present invention can have various modifications and variations. Any changes, modifications, substitutions, integrations, and parameter changes made to these embodiments within the spirit and principles of the present invention, without departing from the principles and spirit of the present invention, through conventional substitutions or to achieve the same function, fall within the scope of protection of the present invention.

Claims

1. A comprehensive measuring device for the thermophysical properties and stability of molten salt containing impurities, characterized in that: It includes a high-temperature sealed reaction chamber (1), an integrated multi-parameter sensing and measurement module (2), a dynamic thermal cycle drive module (3), an impurity adaptive processing module (4), a data processing module (5), and an industrial computer main control unit (6). The high-temperature sealed reaction chamber (1) is the core carrier. Its internal chambers are respectively sealed and connected to the input end of the integrated multi-parameter sensing and measurement module (2), sealed and connected to the liquid inlet and outlet ends of the dynamic thermal cycle drive module (3), and sealed and connected to the output end of the impurity adaptive processing module (4). The integrated multi-parameter sensing and measurement module (2) collects thermal property parameters, including density, viscosity, thermal conductivity, DSC specific heat temperature and electrical conductivity. All signal output terminals are electrically connected to the signal input terminals of the data processing module (5), including a density measurement unit (7), a viscosity measurement unit (8), a laser flash thermal conductivity measurement unit (9), a DSC specific heat temperature measurement unit (10) and a four-electrode electrical conductivity measurement unit (11). The dynamic thermal cycle drive module (3) simulates actual engineering conditions to realize dynamic hot and cold alternation cycle of molten salt containing impurities. Its input end is electrically connected to the control output end of the data processing module (5), including electromagnetic pump (12), heat tracing pipeline (13), heat exchanger (14) and flow regulating valve (15). The impurity adaptive processing module (4) provides a pure and stable molten salt environment for thermophysical property and stability measurement, including a multi-stage microporous ceramic filter (16), a vacuum filtration pump (17), an online spectral monitoring probe (18), and an inert gas source (19). The data processing module (5) is electrically connected to the high-temperature sealed reaction chamber (1), the integrated multi-parameter sensing and measurement module (2) and the dynamic thermal cycle drive module (3) respectively, and converts the collected analog signals into digital signals and transmits them to the industrial computer main control unit (6), including a signal isolation amplifier (20), an A / D converter (21) and a multi-channel data acquisition card (22). The industrial control computer main control unit (6) is bidirectionally electrically connected to the data processing module (5), receives digital signals transmitted by the data processing module (5), and outputs preset control logic instructions, impurity correction algorithm instructions and comprehensive stability evaluation instructions.

2. The comprehensive measurement device for the thermophysical properties and stability of molten salt containing impurities according to claim 1, characterized in that: The integrated multi-parameter sensing and measurement module (2) is specifically as follows: The density measurement unit (7) includes a platinum sinker suspended in the internal cavity and a high-precision electronic balance. The platinum sinker serves as the input end of the unit and extends below the molten salt surface. Its surface is sputtered with a Ta-Ir anti-adhesion coating, and the high-precision electronic balance outputs a buoyancy signal. The input end of the viscosity measurement unit (8) is a coaxial cylindrical rotor that extends into the molten salt. It is connected to the drive mechanism using a magnetic fluid sealing structure to prevent high-temperature molten salt and impurities from contaminating the drive components and outputs a torque signal. The laser flash thermal conductivity measurement unit (9) includes a CVD diamond optical window, a laser emitter, and a temperature response detector set on the side wall of the furnace body. The emitting end of the laser emitter and the detection end of the temperature response detector serve as the input end of the unit. They are connected to the internal cavity through the CVD diamond optical window and output a temperature response curve signal. The input of the DSC specific heat temperature measurement unit (10) is the DSC crucible and the heat flow sensor. The DSC crucible is placed in the molten salt inside the high temperature resistant crucible, and the heat flow sensor is attached to the outer wall of the DSC crucible, outputting the heat flow and temperature curve signal. The input of the four-electrode conductivity measurement unit (11) consists of four platinum-iridium alloy electrodes that extend into the molten salt. It adopts an anti-impurity polarization design and outputs an AC impedance signal. The input terminals of each unit are physically isolated.

3. The comprehensive measurement device for the thermophysical properties and stability of molten salt containing impurities according to claim 1, characterized in that: The impurity adaptive processing module (4) is specifically as follows: The multi-stage microporous ceramic filter (16) is installed in series on the feed pipe of the internal cavity. Its input end is connected to the molten salt feed device, and its output end is sealed and connected to the feed port of the internal cavity to intercept large particle impurities. The control input terminal of the vacuum filtration pump (17) is electrically connected to the control output terminal of the data processing module (5), and its output terminal is sealed and connected to the internal cavity to perform vacuum degassing treatment on the internal cavity. The input end of the online spectral monitoring probe (18) extends into the molten salt inside the internal cavity through a high-temperature resistant optical fiber. Its signal output end is electrically connected to the signal input end of the data processing module (5) to collect the characteristic spectral absorption intensity of impurity ions in the molten salt in real time and output the impurity concentration signal. The output end of the inert gas source (19) is sealed and connected to the inert atmosphere interface of the internal cavity, and its control input end is electrically connected to the control output end of the data processing module (5) to control the inert gas flow rate and pressure.

4. The comprehensive measurement device for the thermophysical properties and stability of molten salt containing impurities according to claim 1, characterized in that: The data processing module (5) is specifically: The input terminal of the signal isolation amplifier (20) is connected to the signal output terminal of each unit of the integrated multi-parameter sensing and measurement module (2), the light intensity signal of the online spectral monitoring probe (18), and the operating status signal of the electromagnetic pump (12) respectively, to isolate and amplify various signals and avoid signal interference; The input terminal of the A / D converter (21) is electrically connected to the output terminal of the signal isolation amplifier (20), and the output terminal is electrically connected to the multi-channel data acquisition card (22) to convert the analog signal into a digital signal. The multi-channel data acquisition card (22) is bidirectionally electrically connected to the main control unit (6) of the industrial computer, transmits all acquired digital signals to the main control unit (6), and receives control commands output by the main control unit (6) of the industrial computer and forwards them to the control input terminals of each module.

5. A method for comprehensively measuring the thermal properties and stability of molten salt containing impurities, used for comprehensively measuring thermal properties and stability based on the apparatus described in claims 1-4, characterized in that: Specifically: The molten salt sample containing impurities is fed into the internal cavity of the high-temperature sealed reaction chamber (1) through the feed pipeline; After the sample passes through the multi-stage microporous ceramic filter (16) of the impurity adaptive processing module (4) to filter out large interfering impurities, the high-pressure sealing flange is closed, and the internal cavity is degassed by vacuum pump (17). Inert gas is introduced to a slightly positive pressure to obtain a stable molten salt containing impurities, and its initial impurity concentration is collected by the online spectral monitoring probe (18). Based on stable impurity-containing molten salt, the industrial computer main control unit (6) outputs temperature setting instructions to the data processing module (5), and the dynamic thermal cycle drive module (3) controls the heating. After the molten salt is heated to the set test temperature, the industrial computer main control unit (6) outputs cycle control instructions to the dynamic thermal cycle drive module (3) to simulate the actual engineering working conditions and carry out dynamic hot and cold alternation cycle of impurity-containing molten salt. Start the integrated multi-parameter sensing and measurement module (2) to simultaneously collect the thermal properties of the molten salt containing impurities, including density, viscosity, thermal conductivity, DSC specific heat temperature, electrical conductivity and impurity concentration; After the dynamic thermal cycle ends, the main control unit (6) of the industrial computer calls the preset comprehensive stability evaluation algorithm to calculate the comprehensive stability index; Based on the comprehensive stability index, the impurity-containing molten salt was determined to have engineering application stability, and a thermal property and stability assessment report was generated.

6. The method for comprehensively measuring the thermophysical properties and stability of molten salts containing impurities according to claim 5, characterized in that: The synchronous acquisition of thermophysical parameters of the impurity-containing molten salt specifically involves the following: during the dynamic alternating hot and cold cycle of the impurity-containing molten salt, the multi-parameter sensing and measurement module synchronously acquires density, viscosity, thermal conductivity, DSC specific heat temperature, electrical conductivity, and impurity concentration in separate units. After the thermal property acquisition is completed, the various raw data are isolated and amplified by the signal isolation amplifier (20) of the data processing module (5), and then the analog signal is converted into a digital signal by the A / D converter (21) and transmitted to the main control unit (6) of the industrial computer for data storage.

7. The method for comprehensively measuring the thermophysical properties and stability of molten salts containing impurities according to claim 6, characterized in that: The unit-level synchronous data acquisition specifically includes: The density measurement unit (7) is immersed below the surface of the molten salt containing impurities by a platinum sinker. A high-precision electronic balance collects the sinker buoyancy-related signals and converts them into raw density data. The viscosity measurement unit (8) has a coaxial cylindrical rotor that rotates inside the molten salt containing impurities, collects the rotor torque signal, and converts it into raw viscosity data; The laser flash thermal conductivity measurement unit (9) emits a laser to the impurity-containing molten salt through the CVD diamond optical window, and the temperature response detector collects the thermal diffusion signal and converts it into raw thermal conductivity data. The DSC specific heat temperature measurement unit (10) is placed inside the DSC crucible containing impurities in the high-temperature crucible. It synchronously senses the temperature change of the molten salt. The heat flow sensor is attached to the outer wall of the DSC crucible to collect the heat flow and temperature curve signals. The specific heat and corresponding temperature data of the impurities in the molten salt are extracted through curve analysis. The four-electrode conductivity measurement unit (11) extends into the interior of the impurity-containing molten salt through four platinum-iridium alloy electrodes, collects the AC impedance signal between the electrodes, and converts the AC impedance signal into the raw conductivity data of the impurity-containing molten salt. Impurity concentration is collected by using an online spectral monitoring probe (18) to collect the characteristic spectral absorption intensity of target impurity ions in molten salt containing impurities through a high-temperature resistant optical fiber, and then converts it into real-time raw data of impurity concentration.

8. The method for comprehensively measuring the thermophysical properties and stability of molten salts containing impurities according to claim 5, characterized in that: The comprehensive stability assessment algorithm specifically involves: after the dynamic thermal cycle ends, calculating the thermal property parameter drift rate during the dynamic thermal cycle based on the collected, processed, and stored thermal property parameters, using the following formula: ； in, For the first The drift rate of each thermophysical property parameter (i=1 corresponds to density, i=2 corresponds to viscosity, i=3 corresponds to thermal conductivity, i=4 corresponds to DSC specific heat temperature, i=5 corresponds to electrical conductivity). This represents the total number of samplings during the dynamic thermal cycling process. To preset the total number of dynamic thermal cycles, For the first During the second sampling Real-time acquired values ​​of the thermophysical parameters, For the first The initial collected values ​​of the thermal property parameters, For the first The average drift rate of all sampling points for a given thermophysical property parameter; The formula for calculating the rate of change in impurity concentration is: ； in, This represents the overall rate of change of impurity concentration throughout the entire dynamic thermal cycle. For the first Real-time impurity concentration at the time of the next sampling The initial impurity concentration, This represents the impurity concentration at the end of the dynamic thermal cycle. The weight of the rate of change in impurity concentration at the end of the cycle; The comprehensive stability index is calculated based on the drift rate of thermophysical parameters and the change rate of impurity concentration.

9. The method for comprehensively measuring the thermophysical properties and stability of molten salts containing impurities according to claim 8, characterized in that: The calculation of the comprehensive stability index is specifically as follows: Calculate the combined average drift rate of all thermophysical parameters throughout the entire dynamic thermal cycle. The formula is: ； in, For the first The weights of the thermophysical parameters can be adjusted according to engineering requirements; The weighting coefficients for the stability of preset thermophysical parameters and impurity concentration are used to calculate the comprehensive stability index, using the following formula: ； in, It is the overall stability index of molten salt containing impurities. These are the weighting coefficients for the stability of thermophysical parameters and the stability of impurity concentration, respectively.

10. The method for comprehensively measuring the thermophysical properties and stability of molten salts containing impurities according to claim 5, characterized in that: The determination that the impurity-containing molten salt possesses stability for engineering applications is specifically based on: a comprehensive stability index. and the preset safety and stability threshold for molten salt engineering applications , , To determine the stability level, when The impurity-containing molten salt was determined to possess excellent stability for engineering applications, making it suitable for high-end precision engineering scenarios; when The impurity-containing molten salt was determined to possess adequate stability for engineering applications and be suitable for conventional engineering scenarios; when The impurity-containing molten salt was determined to have the stability required for optimized engineering applications. Process adjustments were necessary, and optimization suggestions and key parameters exceeding limits were recorded simultaneously. The molten salt containing impurities was determined to lack stability for engineering applications and was prohibited from being used directly in engineering projects. The reasons for the non-compliance were recorded in detail. After receiving the report generation instruction, the main control unit (6) of the industrial computer automatically integrates all relevant data and completes the data classification and organization according to the preset report template; When the reliability of the network status monitoring results is questionable, the data is uploaded to the cloud for verification and calibration using a pre-trained CNN neural network.

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