Dynamic entropy-based intelligent level evaluation system and method for measurement and control equipment

Abstract

The invention relates to the technical field of measurement and control equipment evaluation, in particular to an intelligent level evaluation system and method for measurement and control equipment based on dynamic entropy, which can introduce an entropy theory in intelligent evaluation of the measurement and control equipment and more comprehensively evaluate the intelligent level of the measurement and control equipment by combining the dynamic change process of the measurement and control equipment. The method can be effectively applied to intelligent evaluation of industrial measurement and control equipment, can know the development work of a related evaluation system platform, and has very good application prospect and value in the technical field of measurement and control equipment; the system covers all levels from the hardware infrastructure to the user interaction interface, and ensures the integrity of the evaluation process. The multi-level design can effectively support evaluation of different types of measurement and control equipment.

Description

Technical Field

[0001] The present invention relates to the technical field of measurement and control equipment evaluation, and in particular to a system and method for evaluating the intelligent level of measurement and control equipment based on dynamic entropy. Background Art

[0002] With the rapid development of science and technology, industrial measurement and control equipment is gradually moving towards the era of intelligence. In this transformation process, intelligent measurement and control equipment has greatly promoted production efficiency with its significant characteristics of high efficiency, accuracy and real-time. However, how to scientifically and systematically evaluate the intelligence level of measurement and control equipment has become an urgent problem to be solved. For industrial measurement and control equipment such as CNC machine tools, robots, valve positioners, transmitters, frequency converters and PLCs, their evaluation in the past mainly relied on scale measurement and manual evaluation, which had problems such as strong subjectivity, long time consumption and high cost, and it was difficult to fully and accurately reflect the actual level of measurement and control equipment. Summary of the invention

[0003] In view of this, the present invention provides a system and method for evaluating the intelligent level of measurement and control equipment based on dynamic entropy, which can introduce entropy theory into the intelligent evaluation of measurement and control equipment, and more comprehensively evaluate its intelligent level by combining the dynamic change process of the measurement and control equipment.

[0004] To achieve the above purpose, the technical solution of the present invention is as follows:

[0005] A measurement and control equipment intelligence level evaluation system based on dynamic entropy includes a support layer, a resource layer, a core layer, an application layer and a user layer, wherein the support layer provides hardware support, network infrastructure, an operation evaluation system and a database; the resource layer is used to integrate data resources of various measurement and control equipment, including key parameter data, historical data and configuration information collected in real time; the core layer is used for the core processing unit of the evaluation system, which is responsible for building a dynamic equivalent model and a three-dimensional model of the measurement and control equipment, executing a simulation test process, and processing and analyzing simulation data; the application layer is used to provide specific business functions and services, including intelligence level evaluation, report generation and optimization suggestions; the user layer is used for the interface for direct interaction between the evaluation system and the user, including a PC terminal and a mobile terminal.

[0006] Among them, the support layer determines the data format, development language, test interface, and computing resources; by standardizing the data format, selecting the development language and framework, clearly defining the test interface, and configuring computing resources and security measures, it provides support for the functional implementation of the subsequent resource layer, core layer, application layer, and user layer.

[0007] Among them, the role of the resource layer is to provide data resources for the entire system, which is used to design databases, indicator system libraries, indicator calculation model libraries, evaluation model libraries, test case libraries, and data processing and analysis toolkits; the implementation process of the resource layer in the intelligent evaluation system of measurement and control equipment involves the construction and integration of a series of key resource libraries, including a database for storing evaluation data, an indicator system library for defining evaluation standards, an indicator calculation model library and an evaluation model library for providing calculation and evaluation algorithms, a test case library for collecting and managing test cases, and a data processing and analysis toolkit for supporting data preprocessing and analysis.

[0008] Among them, the role of the core layer is to provide the evaluation system with a core model for measurement and control equipment evaluation, which is used to model the dynamic model of the measurement and control equipment. It is divided into three modules, including a measurement and control equipment key parameter acquisition module, a measurement and control equipment equivalent model construction module, and a test execution module; by constructing a measurement and control equipment key parameter acquisition module, the system collects key data of equipment operation in real time or offline; a mathematical and physical model is established based on the acquired parameters to simulate the behavioral characteristics of the equipment in the actual working environment; the test execution module is responsible for calling the data and models provided by the resource layer according to the preset test plan to perform simulation tests and experimental verifications.

[0009] Among them, the application layer includes indicator calculation module, comprehensive evaluation module and system management module; the implementation process of the application layer in the intelligent evaluation system of measurement and control equipment is based on the dynamic model constructed by the core layer and the resource data provided by the resource layer. The indicator calculation module processes and analyzes the collected data to calculate specific performance indicators; the comprehensive evaluation module uses the algorithm in the evaluation model library to comprehensively evaluate the calculation results and obtain an overall performance evaluation report of the measurement and control equipment; the system management module is responsible for monitoring the operating status of the entire application layer to ensure the coordination between modules and smooth data flow.

[0010] Among them, the user layer builds an instantiated indicator construction module, allowing users to customize or adjust evaluation indicators according to specific needs; through the test process visualization module, the complex evaluation process is displayed in a graphical interface; the interactive log query feedback module provides real-time operation records and problem feedback; the evaluation configuration module allows users to customize evaluation parameters and conditions; the typical verification visualization display module displays the evaluation results in the form of charts or animations; the autonomous operation and maintenance module gives users certain system maintenance permissions.

[0011] The present invention also provides a method for evaluating the intelligent level of measurement and control equipment based on dynamic entropy, which is implemented by the system of the present invention and includes the following steps:

[0012] Step 1: Building the intelligent level evaluation system of measurement and control equipment based on dynamic entropy according to the present invention;

[0013] Step 2: Analyze various measurement and control equipment to extract key parameters that affect the level of intelligence;

[0014] Step 3: Based on the extracted key parameters and using the dynamics principle of the evaluation system, a dynamic equivalent model of the measurement and control equipment is constructed;

[0015] Step 4: Construct a 3D model based on the actual structure and size of the measurement and control equipment;

[0016] Step 5: In the simulation evaluation system, set the simulation parameters according to the actual working conditions of the measurement and control equipment and execute the simulation test process;

[0017] Step 6: Preprocess the data collected during the simulation process; use the information entropy theory to calculate the information correlation between the parameters and perform data analysis;

[0018] Step 7: Set multi-dimensional and diversified evaluation indicators according to the characteristics and actual needs of the measurement and control equipment;

[0019] Step 8: Use information entropy theory to assign values ​​to evaluation indicators; assign weights based on the importance of each indicator in the intelligence level and the information correlation between them, and calculate the comprehensive intelligence level;

[0020] Step 9: Display the evaluation results to users.

[0021] Beneficial effects:

[0022] 1. The system of the present invention can be effectively applied to the intelligent evaluation of industrial measurement and control equipment, and can be used to develop related evaluation system platforms. It has very good application prospects and value in the field of measurement and control equipment technology; the system covers all levels from hardware infrastructure to user interaction interface, ensuring the integrity of the evaluation process. This multi-level design can effectively support the evaluation of different types of measurement and control equipment.

[0023] 2. The system of the present invention can more accurately reflect the performance of the measurement and control equipment in the actual working environment by constructing a dynamic equivalent model and a three-dimensional model of the measurement and control equipment, and combining the information entropy theory for data analysis, thereby improving the reliability of the evaluation results. Users can customize or adjust the evaluation indicators and customize the evaluation parameters and conditions according to their own needs, which greatly enhances the adaptability and flexibility of the system.

[0024] 3. The system of the present invention reduces the need for manual intervention and improves work efficiency by automating the data collection, processing and analysis process. At the same time, the complex evaluation process and results are displayed through a graphical interface, making it easier for users to understand and operate.

[0025] 4. The system support layer of the present invention has clear security measures configured to ensure the security of data transmission and storage, and protect the privacy and data security of users. The system design has good scalability and can easily add new functions and services as technology develops and user needs change. The design of the user layer fully considers the user experience, and enables users to complete the evaluation tasks conveniently and quickly by providing an intuitive interface and rich interactive functions. BRIEF DESCRIPTION OF THE DRAWINGS

[0026] Figure 1 It is a schematic diagram of the intelligent level evaluation system of measurement and control equipment based on dynamic entropy of the present invention.

[0027] Figure 2 The figure is a flow chart of the method for evaluating the intelligent level of measurement and control equipment based on dynamic entropy of the present invention. DETAILED DESCRIPTION

[0028] The present invention is described in detail below with reference to the accompanying drawings and embodiments.

[0029] In the study of dynamical systems, entropy, as an important measure of system complexity, is widely used in the classification and performance evaluation of dynamical systems. The concept of entropy was originally proposed by physicist Clausius to express the second law of thermodynamics. With the deepening of research, the concept of entropy has been gradually extended to dynamical systems, and a variety of entropy theories have been formed, such as topological entropy and information entropy. These entropy theories provide strong support for evaluating the complexity and performance of systems.

[0030] Introducing entropy theory in the intelligent evaluation of measurement and control equipment, the intelligent level of measurement and control equipment can be more comprehensively evaluated by combining the dynamic change process of measurement and control equipment. The present invention proposes a measurement and control equipment intelligent level evaluation system based on dynamic entropy, which realizes scientific and efficient evaluation of the intelligent level of measurement and control equipment. Figure 1 shown.

[0031] The system of the present invention includes a support layer, a resource layer, a core layer, an application layer and a user layer, wherein the support layer provides key components such as hardware support, network infrastructure, operation evaluation system and database; the resource layer is used to integrate data resources of various measurement and control equipment, including key parameter data, historical data, configuration information, etc. collected in real time; the core layer is used as the core processing unit of the evaluation system, which is responsible for building a dynamic equivalent model and a three-dimensional model of the measurement and control equipment, executing a simulation test process, and processing and analyzing simulation data; the application layer is used to provide specific business functions and services, including intelligent level evaluation, report generation and optimization suggestions, etc.; the user layer is used for the interface for direct interaction between the evaluation system and the user, including multiple access methods such as PC and mobile terminals.

[0032] Furthermore, the specific contents of the support layer, resource layer, core layer, application layer and user layer are as follows.

[0033] The support layer needs to determine the data format, development language, test interface, computing resources, etc. As the cornerstone of the intelligent evaluation system of measurement and control equipment, the support layer provides a technical foundation for the system by standardizing data formats, selecting appropriate development languages ​​and frameworks, clearly defining test interfaces, and reasonably configuring computing resources and security measures, ensuring the stability, security, scalability and efficient development of the system, and providing strong support for the subsequent resource layer, core layer, application layer and user layer function realization.

[0034] The role of the resource layer is to provide rich data resources for the entire system, and it is necessary to design resource libraries such as databases, indicator system libraries, indicator calculation model libraries, evaluation model libraries, test case libraries, and data processing and analysis toolkits. The implementation process of the resource layer in the intelligent evaluation system of measurement and control equipment involves the construction and integration of a series of key resource libraries, including databases for storing evaluation data, indicator system libraries for defining evaluation standards, indicator calculation model libraries and evaluation model libraries for providing calculation and evaluation algorithms, test case libraries for collecting and managing test cases, and data processing and analysis toolkits for supporting data preprocessing and analysis.

[0035] The role of the core layer is to provide the evaluation system with a core model for the measurement and control equipment evaluation. It is necessary to model the dynamic model of the measurement and control equipment, which is divided into three modules, including the key parameter acquisition module of the measurement and control equipment, the equivalent model construction module of the measurement and control equipment, and the test execution module. As the core of the intelligent evaluation system for measurement and control equipment, the core layer focuses on the in-depth modeling and simulation of the dynamic model of the measurement and control equipment. By constructing the key parameter acquisition module of the measurement and control equipment, the system can collect key data of the equipment operation in real time or offline; then, a mathematical and physical model is established based on the acquired parameters to simulate the behavioral characteristics of the equipment in the actual working environment; finally, the test execution module is responsible for calling the data and models provided by the resource layer according to the preset test plan to perform simulation tests and experimental verification.

[0036] The role of the application layer is to automate and intelligentize the complex evaluation process. The application layer includes indicator calculation module, comprehensive evaluation module, system management module, etc. The implementation process of the application layer in the intelligent evaluation system of measurement and control equipment is based on the dynamic model constructed by the core layer and the resource data provided by the resource layer. The indicator calculation module processes and analyzes the collected data to calculate specific performance indicators; then, the comprehensive evaluation module uses the algorithm in the evaluation model library to comprehensively evaluate the calculation results and obtain an overall performance evaluation report of the measurement and control equipment; at the same time, the system management module is responsible for monitoring the operating status of the entire application layer to ensure the coordination between modules and the smooth flow of data.

[0037] The role of the user layer is to simplify complex technical operations and provide intuitive and easy-to-use evaluation tools and result displays, including instantiated indicator construction, test process visualization, interactive log query feedback, evaluation configuration, typical verification visualization display, autonomous operation and maintenance and other modules. As the interactive interface between the intelligent evaluation system of measurement and control equipment and users, the user layer focuses on improving user experience and operational convenience in its implementation process. In the implementation process, the instantiated indicator construction module will be built first, allowing users to customize or adjust the evaluation indicators according to specific needs; then, through the test process visualization module, the complex evaluation process will be displayed in a graphical interface, so that users can intuitively understand and operate; at the same time, the interactive log query feedback module provides real-time operation records and problem feedback to help users quickly locate and solve problems; the evaluation configuration module allows users to customize evaluation parameters and conditions to meet the evaluation needs in different scenarios; the typical verification visualization display module displays the evaluation results in the form of intuitive charts or animations to enhance users' understanding of equipment performance; finally, the autonomous operation and maintenance module grants users certain system maintenance permissions, such as data backup, recovery and basic configuration adjustment, to improve the availability and flexibility of the system.

[0038] The present invention also provides a method for evaluating the intelligent level of measurement and control equipment based on dynamic entropy. The evaluation method process is as follows: Figure 2 As shown, the following steps are included:

[0039] Step 1: Building the intelligent level evaluation system of measurement and control equipment based on dynamic entropy according to the present invention;

[0040] Step 2: Conduct a detailed analysis of various measurement and control equipment to extract key parameters that affect the level of intelligence, such as response time, positioning accuracy, control stability, etc.

[0041] Step 3: Based on the extracted key parameters and using the dynamics principles of the evaluation system, construct a dynamic equivalent model of the measurement and control equipment.

[0042] Step 4: Use CAD and CAE software to build a three-dimensional model based on the actual structure and size of the measurement and control equipment.

[0043] Step 5: In the simulation evaluation system, set the simulation parameters according to the actual working conditions of the measurement and control equipment and execute the simulation test process.

[0044] Step 6: Preprocess the data collected during the simulation, including data cleaning, denoising, etc. Then, use the information entropy theory to calculate the information correlation between the parameters, perform data analysis, and provide a quantitative basis for intelligent level evaluation.

[0045] Step 7: According to the characteristics and actual needs of the measurement and control equipment, set multi-dimensional and diversified evaluation indicators, such as response speed, positioning accuracy, stability and adaptability.

[0046] Step 8: Use information entropy theory to assign values ​​to evaluation indicators. According to the importance of each indicator in the intelligence level and the information correlation between them, reasonably assign weights and calculate the comprehensive intelligence level.

[0047] Step 9: Display the evaluation results to users in the form of charts, reports, etc. At the same time, based on the evaluation results, put forward targeted optimization suggestions to help users improve the intelligence level of measurement and control equipment.

[0048] Furthermore, the evaluation system can be deployed in the actual environment for debugging and optimization to ensure the stability and reliability of the evaluation system. Based on user feedback and actual needs, the evaluation system can be continuously optimized and upgraded to continuously improve the intelligence level of the evaluation system and user experience.

[0049] In order to verify the method of the present invention, a set of intelligent level evaluation processes based on dynamic entropy theory are designed for industrial measurement and control equipment such as CNC machine tools, robots, valve positioners, transmitters, frequency converters and PLCs, aiming to comprehensively consider the intelligent characteristics of measurement and control equipment in different application scenarios and the complex association of evaluation elements, avoiding the isolated evaluation of a single indicator and the overlap of multiple indicators. First, the system dynamics method is used to deeply analyze the dynamic structure and interaction relationship between the internal variables of the measurement and control equipment, and a dynamic model reflecting the overall behavior of its motion system is constructed. The model captures and records the change data of key parameters by simulating the evolution of the internal structure and system state of the equipment over time. Then, based on the data output by the above model, a series of evaluation indicators that can quantify the intelligent level of measurement and control equipment are extracted and calculated. These indicators need to fully cover multiple dimensions such as intelligent perception, decision-making, execution and self-optimization of the equipment. And the information entropy theory is introduced for weight allocation, and the importance of each indicator in the comprehensive evaluation system is scientifically evaluated according to the amount of information provided by each indicator. Finally, combined with the quantitative value and weight of each indicator, the intelligent level score of the measurement and control equipment is obtained through comprehensive calculation, realizing a comprehensive and detailed evaluation of the intelligent capability of the equipment.

[0050] An evaluation process is designed for the intelligent level evaluation of measurement and control equipment. The process includes inputting test tasks, analyzing test requirements, describing the object to be tested, selecting evaluation indicators, building a dynamic model of measurement and control equipment, building test cases to execute tests, calculating evaluation indicators, and using information entropy to perform comprehensive evaluation on indicator weights. The specific contents are as follows.

[0051] Step 1: First, you need to enter the test task. During this process, you need to analyze the test requirements and clarify the test object.

[0052] Step 2: Analyze the content and test objects according to the test requirements and select the corresponding evaluation indicators.

[0053] Step 3: Build a dynamic model for the test object. During this process, it is necessary to obtain key equipment parameters, build an equivalent model, and perform simulation tests.

[0054] ① Obtain key parameters of measurement and control equipment

[0055] The types of parameters that need to be obtained include the geometric parameters of the measurement and control equipment, the dynamic performance parameters of the measurement and control equipment, and other parameters. Taking CNC machine tools as an example, the geometric parameters include machine tool structure parameters, moving parts parameters, tool and fixture parameters, as follows:

[0056] (1) Machine tool structural parameters: including the size, shape and position relationship of the machine tool bed, columns, beams, worktable and other components;

[0057] (2) Parameters of moving parts: stroke, speed, acceleration, accuracy, etc. of the spindle and feed axis (X, Y, Z axis, etc.);

[0058] (3) Tool and fixture parameters: tool geometry (such as rake angle, back angle, cutting edge inclination angle, etc.), tool material, fixture clamping method and accuracy, etc.

[0059] Dynamic performance parameters include stiffness parameters, damping characteristics, mass properties, etc., as follows:

[0060] (1) Stiffness parameters: static and dynamic stiffness of each machine tool component, including spindle stiffness, feed system stiffness, etc.;

[0061] (2) Damping characteristics: damping ratio and damping coefficient of each moving part;

[0062] (3) Mass attributes: mass, center of mass position and moment of inertia of each component.

[0063] Other parameters such as cutting parameters include cutting speed, cutting depth, cutting amount, etc., as follows:

[0064] (1) Cutting speed: spindle speed and tool feed speed;

[0065] (2) Cutting depth: the amount of cutting depth per cut;

[0066] (3) Cutting parameters: Cutting parameters determined according to the processing material, tool type and processing quality requirements.

[0067] ② Dynamic model of measurement and control equipment

[0068] (1) Selection of generalized coordinate system

[0069] When constructing a dynamic model of measurement and control equipment, the variables that describe the instantaneous position of each component of the system, namely generalized coordinates, must be selected first. Based on the assumption that the object is regarded as a point mass or a rigid body, the variables can be rectangular coordinates, curvilinear coordinates, or relative angles. The choice of generalized coordinates determines the accuracy of the model's description of the system's dynamic characteristics, which serves as the basis for the subsequent construction of dynamic equations.

[0070] (2) Structural division of measurement and control equipment

[0071] According to the structural characteristics of the equipment, the overall structure of the measurement and control equipment is divided into several sub-structures. The boundary surface after division is the interface of the sub-structure. The division of the structure should retain the original combination of the measurement and control equipment to the greatest extent. For example, the sub-structure of a CNC machine tool includes but is not limited to the bed, workbench, column, tool magazine, tool magazine connecting plate, beam, pallet, ram, spindle, etc.

[0072] (3) Establishment of kinetic model

[0073] The Lagrange equation is one of the important equations in analytical dynamics. First, it is a universal equation of dynamics expressed in a generalized coordinate system, which can be used to solve the dynamic problems of a particle system with ideal complete constraints, and the number of equations is equal to the number of degrees of freedom of the system; second, it is not a vector dynamics equation; finally, there is no unknown constraint reaction force in the equation, and the more constraints the system has, the more prominent this advantage is. The present invention uses the Lagrange equation to establish the equation of the motion system of the measurement and control equipment. The general form of the Lagrange equation is as follows:

[0074]

[0075] Where T is the total kinetic energy of the motion system of the measurement and control equipment, x j is the generalized coordinates of the motion system of the measurement and control equipment, Q j is the generalized force of the measurement and control equipment motion system. For the measurement and control equipment motion system under study, Q j By broad forces Generalized Linear Damping Force and the generalized exciting force Q j ', that is

[0076]

[0077] The kinetic model is as follows:

[0078]

[0079] In the formula, T is the total kinetic energy of the measurement and control equipment motion system, V is the total potential energy of the measurement and control equipment motion system, and D is the Rayleigh energy dissipation function of the measurement and control equipment motion system. The total kinetic energy and total potential energy of the measurement and control equipment are obtained by the sum of the kinetic energy and potential energy of each substructure. Thus, the construction of the dynamic model of the measurement and control equipment is completed.

[0080] Step 4: Build test cases, configure test resources, and execute tests based on test tasks, test requirements, and evaluation indicators.

[0081] Step 5: Collect the process data and result data of the simulation test and calculate the evaluation index value.

[0082] Step 6, comprehensive evaluation of index weighting based on information entropy: Entropy is a thermodynamic physical concept used to indicate the uniformity of energy distribution in space. In system theory, the larger the entropy, the more chaotic the system is and the less information it carries; the smaller the entropy, the more orderly the system is and the more information it carries. The information entropy defined by Shannon is a concept independent of thermodynamic entropy, but has the basic properties of thermodynamic entropy and has a broader and more universal meaning, so it can be called generalized entropy. The present invention determines the weight of each index based on the influence of the relative change degree of the index on the overall motion system of the measurement and control equipment by calculating the information entropy of the index. If the information entropy of a certain index is smaller, it indicates that the variation degree of the index value is greater, the amount of information provided is more, the role it can play in the comprehensive evaluation is also greater, and its weight is also greater. On the contrary, the larger the information entropy of a certain index, the smaller the variation degree of the index value is, the less information provided is, the smaller the role it plays in the comprehensive evaluation is, and the smaller its weight is. Index weighting based on information entropy quantifies and synthesizes multiple intelligent evaluation indicators of measurement and control equipment to complete the decision. The specific method is as follows:

[0083] ①Construct a decision evaluation matrix

[0084] Assume there are n indicator categories, each category has k evaluation indicators, x ij is the jth indicator value of the i-th indicator category, then construct the evaluation matrix A:

[0085]

[0086] ② Standardization

[0087] Use the deviation standardization method to normalize each indicator x in the decision evaluation matrix ij After standardization, the standardized value is expressed as:

[0088]

[0089] In the formula, y ij is the index value after standardization, min(X i ) is the minimum indicator value in the i-th indicator category, max(X i ) is the maximum indicator value in the i-th indicator category.

[0090] ③Calculate prior probability

[0091] Calculate the proportion of the index value of the i-th project under the j-th index:

[0092]

[0093] In the formula, n is the index item, p ij Prior probability of the indicator.

[0094] ④ Calculate the entropy value and coefficient of variation of the indicator

[0095]

[0096] In the formula, e j is the entropy value; and the difference coefficient of the jth indicator is calculated as:

[0097] g j =1-e j

[0098] In the formula, g j is the coefficient of variation.

[0099] ⑤Calculate the weight coefficient of each indicator

[0100] The calculation formula is:

[0101]

[0102] In the formula, ω j is the weight coefficient.

[0103] ⑥ Comprehensive evaluation

[0104] In the process of intelligent evaluation of measurement and control equipment, the weight of indicators is determined in combination with other artificial requirements, and the artificial weight is a j j = 1, 2, ..., n, then the comprehensive weight is obtained by combining the entropy weight of the indicator:

[0105]

[0106] In the formula, β j is the comprehensive weight. Further, the weighted sum of each indicator is performed to obtain the final score:

[0107]

[0108] Where H is the comprehensive score of the measurement and control equipment.

[0109] Thus, a comprehensive evaluation of the intelligence level of measurement and control equipment based on information entropy was completed.

[0110] In summary, the method of the present invention is aimed at industrial measurement and control equipment such as CNC machine tools, robots, valve positioners, transmitters, frequency converters and PLCs, constructs an intelligent level evaluation process based on the dynamic model and information entropy of measurement and control equipment, extracts key parameters of measurement and control equipment, establishes a dynamic equivalent model and a three-dimensional model of measurement and control equipment, constructs a measurement and control equipment simulation system, and executes the test process through simulation to obtain the process data and result data required for the calculation of the intelligent evaluation index of the measurement and control equipment. According to the system dynamics entropy theory, as the running time of the system increases, the degree of chaos of the system also increases. The intelligent level of the measurement and control equipment is comprehensively reflected by multi-dimensional and diversified evaluation indicators. At the same time, the information entropy between the parameters and indicators of the measurement and control equipment reflects the degree of information correlation between them. Therefore, the intelligent evaluation index of the measurement and control equipment is assigned by information entropy to calculate the comprehensive intelligent level. On the basis of the evaluation process, a system framework for intelligent evaluation of measurement and control equipment is further designed, and the evaluation process is hierarchical and modularized to form an evaluation system framework that can be used for reference development. The content of the present invention has very important application prospects and practical significance for promoting the intelligent level evaluation of measurement and control equipment and equipment optimization and upgrading.

[0111] In summary, the above are only preferred embodiments of the present invention and are not intended to limit the protection scope of the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the protection scope of the present invention.

Claims

1. A measurement and control equipment intelligence level evaluation system based on dynamic entropy, characterized in that: It includes support layer, resource layer, core layer, application layer and user layer. The support layer provides hardware support, network infrastructure, operation evaluation system and database; the resource layer is used to integrate data resources of various measurement and control equipment, including key parameter data, historical data and configuration information collected in real time; the core layer is used as the core processing unit of the evaluation system, responsible for building the dynamic equivalent model and three-dimensional model of the measurement and control equipment, executing the simulation test process, and processing and analyzing the simulation data; the application layer is used to provide specific business functions and services, including intelligent level evaluation, report generation and optimization suggestions; The user layer is used for the interface where the evaluation system interacts directly with users, including PC and mobile terminals.

2. The system according to claim 1, characterized in that The support layer determines the data format, development language, test interface, and computing resources; by standardizing data formats, selecting development languages ​​and frameworks, clearly defining test interfaces, and configuring computing resources and security measures, it provides support for the functional implementation of subsequent resource layers, core layers, application layers, and user layers.

3. The system according to claim 1 or 2, characterized in that ,The role of the resource layer is to provide data resources for the ,entire system, ,which is used to design database, indicator system library, indicator ,calculation model library, evaluation model library, test case library, and data ,processing and analysis tool kit; ,The implementation process of the resource layer in the intelligent ,evaluation system of measurement and control equipment involves building and ,integrating a series of key resource libraries, including a database for storing evaluation data, the indicator ,system library defines evaluation standards, the indicator calculation model library and ,evaluation model library provide calculation and evaluation algorithms, the test case library collects and ,manages test cases, and the data processing and ,analysis tool kit supports data preprocessing and analysis.

4. The system according to claim 1 or 2, characterized in that ,The role of the core layer is to provide the evaluation system with ,the core model of measurement and control equipment evaluation for ,the evaluation system, which is used to model the dynamic model of the ,measurement and control equipment. It is divided into three modules, including the ,key parameter acquisition module of measurement and control equipment, the ,equivalent model building module of measurement and control equipment, and the ,test execution module; By building a module for acquiring key parameters of measurement and control equipment, the system collects key data of equipment operation in real time or offline; a mathematical and physical model is established based on the acquired parameters to simulate the behavioral characteristics of the equipment in the actual working environment; The test execution module is responsible for calling the data and models provided by the resource layer according to the preset test plan, and performing simulation tests and experimental verification.

5. The system according to claim 4, characterized in that ,The application layer includes the index calculation module, the ,comprehensive evaluation module and the system management module; ,The implementation process of the application layer in the ,intelligent evaluation system of the measurement and control equipment is based on the ,dynamic model constructed by the core layer and the resource data provided by the ,resource layer, and the collected data is processed and analyzed through the ,index calculation module to calculate specific performance indicators; the comprehensive evaluation module uses the ,algorithm in the evaluation model library to comprehensively evaluate the ,calculate the overall performance evaluation report of the measurement and ,control equipment; the system management module is responsible for monitoring the ,operation status of the entire application layer to ensure the ,coordination work among the modules and the smooth ,data flow.

6. The system according to claim 1 or 2, characterized in that ,The user layer builds an instantiated indicator construction module, ,allowing users to customize or adjust the evaluation indicators according to ,specific needs; through the test process visualization module, the complex ,evaluation process is displayed in a graphical interface; the interactive log query ,feedback module provides real-time operation records and problem feedback; The evaluation configuration module allows users to customize evaluation parameters and conditions; The typical verification visualization display module displays the evaluation results in the form of charts or animations; the autonomous operation and maintenance module grants users certain system maintenance permissions.

7. A method for evaluating the intelligent level of measurement and control equipment based on dynamic entropy, characterized in that: The method is implemented by a system as claimed in any one of claims 1 to 6, comprising the following steps: Step 1: Building the intelligent level evaluation system of measurement and control equipment based on dynamic entropy according to the present invention; Step 2: Analyze various measurement and control equipment to extract key parameters that affect the level of intelligence; Step 3: Based on the extracted key parameters and using the dynamics principle of the evaluation system, a dynamic equivalent model of the measurement and control equipment is constructed; Step 4: Construct a 3D model based on the actual structure and size of the measurement and control equipment; Step 5: In the simulation evaluation system, set the simulation parameters according to the actual working conditions of the measurement and control equipment and execute the simulation test process; Step 6: Preprocess the data collected during the simulation process; use the information entropy theory to calculate the information correlation between the parameters and perform data analysis; Step 7: Set multi-dimensional and diversified evaluation indicators according to the characteristics and actual needs of the measurement and control equipment; Step 8: Use information entropy theory to assign values ​​to evaluation indicators; assign weights based on the importance of each indicator in the intelligence level and the information correlation between them, and calculate the comprehensive intelligence level; Step 9: Display the evaluation results to users.

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