Electrical equipment virtual debugging system and method for determining data exchange priority therein

Abstract

The present application relates to a virtual debugging system for electrical equipment and a method for determining data exchange priority therein, and relates to the field of electrical engineering technology; the method comprises: obtaining multiple target physical field data in the virtual debugging system for electrical equipment, and extracting characteristic information of each target physical field data; the characteristic information comprises at least one characteristic type of the real-time nature, priority, importance, and parameter value of the data; based on the characteristic information and at least one of the real-time data requirements of the virtual debugging system for electrical equipment, determining the color identification of each target physical field data; the color identification comprises at least one of a color type and a color gradient; determining the data exchange priority of each target physical field data based on the color identification; and realizing classification of data-related exchange priorities for cross-module interaction based on the color identification, thereby facilitating the system to reduce unnecessary cross-module data exchange during multi-physical field coupling simulation and optimize computing resources and data transmission efficiency.

Description

Technical Field

[0001] The present application relates to the field of electrical engineering technology, and in particular to a virtual debugging system for electrical equipment and a method for determining data exchange priority therein. Background Art

[0002] The operation of electrical equipment involves more than just electrical characteristics; it also includes the coupled influences of multiple physical fields, such as temperature, mechanical vibration, and airflow. Virtual commissioning systems and digital twin technologies in related technologies primarily focus on electrical simulation and lack comprehensive integration of multiple physical fields. This results in virtual commissioning systems in related technologies being unable to intuitively identify and distinguish the priority, real-time nature, and importance of different data types. For example, real-time electrical fault alarm data and temperature data should be processed differently, but if this distinction is not clearly established, critical data may be delayed.

[0003] Therefore, it is urgent to provide a method that can identify and distinguish the data exchange priorities of multiple data in the virtual debugging system of electrical equipment. Summary of the Invention

[0004] Based on this, it is necessary to provide an electrical equipment virtual debugging system that can identify and distinguish the data exchange priorities of multiple data, as well as a method, device, computer equipment, computer-readable storage medium and computer product for determining the data exchange priority, in order to address the above technical problems.

[0005] In a first aspect, the present application provides a method for determining data exchange priority in a virtual debugging system for electrical equipment, comprising:

[0006] Acquire multiple target physical field data in the electrical equipment virtual debugging system, and extract characteristic information of each target physical field data; the characteristic information includes at least one characteristic type of the data's real-time performance, priority, importance, and parameter value;

[0007] Determining a color identification of each target physical field data based on at least one of the characteristic information and the real-time data requirement of the electrical equipment virtual debugging system; wherein the color identification includes at least one of a color type and a color gradient;

[0008] The data exchange priority of each target physical field data is determined based on the color identification.

[0009] In one embodiment, determining the color identification of each target physical field data based on the characteristic information includes:

[0010] Comparing the characteristic value of the characteristic information of each target physical field data with a preset characteristic threshold; wherein the preset characteristic threshold includes at least one sub-characteristic threshold;

[0011] When the characteristic value of the target physical field data is greater than or equal to a first sub-characteristic threshold, determining that the color identification of the target physical field data is a first color type;

[0012] When the characteristic value of the target physical field data is greater than or equal to the second sub-feature threshold and less than the first sub-feature threshold, determining that the color identification of the target physical field data is a second color type;

[0013] When the characteristic value of the target physical field data is greater than or equal to a third sub-feature threshold and less than the second sub-feature threshold, determining that the color identification of the target physical field data is a third color type;

[0014] When the characteristic value of the target physical field data is less than the third sub-characteristic threshold, determining that the color identification of the target physical field data is a fourth color type;

[0015] The first color type, the second color type, the third color type, and the fourth color type are arranged clockwise in the hue wheel, or the first color type, the second color type, the third color type, and the fourth color type are arranged counterclockwise in the hue wheel.

[0016] In one embodiment, determining the color identification of each target physical field data based on the characteristic information includes:

[0017] Obtaining a normalized value within a preset range corresponding to each feature type of each feature information, and a weight corresponding to each feature type;

[0018] Determining a comprehensive weight of each of the feature information based on the standardized value and the weight of each of the feature types;

[0019] The color type of the corresponding target physical field data is determined based on the size of each comprehensive weight; wherein, as the comprehensive weight increases successively, the color type is arranged clockwise or counterclockwise in the hue wheel.

[0020] In one embodiment, determining the color identification of each target physical field data based on the characteristic information includes:

[0021] Obtaining a normalized value within a preset range corresponding to each feature type of each feature information, and a weight corresponding to each feature type;

[0022] Determining a comprehensive weight of each of the feature information based on the standardized value and the weight of each of the feature types;

[0023] Determine the color value corresponding to each of the comprehensive weights based on a preset color mapping function, and convert the color value into an RGB value;

[0024] The color type of the corresponding target physical field data is determined based on each of the RGB values.

[0025] In one embodiment, determining the color identification of each target physical field data based on the real-time data requirements of the electrical equipment virtual commissioning system includes:

[0026] In a case where the target physical field data belongs to the data required by the real-time data, determining that the color identification of the target physical field data is a first color type;

[0027] In a case where the target physical field data does not belong to the data required by the real-time data, the color identification of the target physical field data is determined to be a second color type.

[0028] In one embodiment, it further includes:

[0029] In the target physical field data belonging to the same color type, obtaining the parameter value of the target physical field data having the same data type; the data type includes electrical parameters, temperature data, vibration data and airflow data;

[0030] The color gradient of the corresponding target physical field data is determined based on the size of the parameter value; wherein, as the size of the parameter value increases successively, the color gradient increases or decreases successively.

[0031] In one embodiment, determining the color identification of each target physical field data based on the characteristic information includes:

[0032] Acquiring the parameter values ​​of the target physical field data having the same data type; the data type includes electrical parameters, temperature data, vibration data, and airflow data;

[0033] For the target physical field data of the same data type, the color gradient of the corresponding target physical field data is determined based on the size of the parameter value; wherein, as the size of the parameter value increases successively, the color gradient increases or decreases successively.

[0034] In one embodiment, it further includes:

[0035] The color type of the target physical field data is determined based on the data type of the target physical field data.

[0036] In one embodiment, determining the data exchange priority of each target physical field data based on the color identification includes:

[0037] As the color types of the target physical field data correspond to the clockwise arrangement in the hue circle, the data exchange priority of the target physical field data increases or decreases in sequence;

[0038] As the color gradient of the target physical field data increases sequentially, the data exchange priority of the target physical field data increases or decreases sequentially.

[0039] In a second aspect, the present application further provides an electrical equipment virtual debugging system, comprising a physical field model module and a data management and exchange layer; the physical field model in the physical field model module comprises an electromagnetic field model, a thermal field model, a mechanical field model, and a fluid field model;

[0040] The data management and exchange layer is used to realize the transmission of each target physical field data between multiple physical field models based on the data exchange priority of each target physical field data in the physical field model module;

[0041] The data exchange priority of the target physical field data is determined by the method for determining the data exchange priority in the electrical equipment virtual debugging system in the first aspect.

[0042] In a third aspect, the present application further provides a device for determining data exchange priority in a virtual debugging system for electrical equipment, comprising:

[0043] A data acquisition module is used to acquire multiple target physical field data in the electrical equipment virtual debugging system and extract characteristic information of each target physical field data; the characteristic information includes at least one characteristic type of the data such as real-time performance, priority, importance, and parameter value;

[0044] a color identification determination module, configured to determine a color identification of each target physical field data based on at least one of the characteristic information and a real-time data requirement of the electrical equipment virtual commissioning system; the color identification including at least one of a color type and a color gradient;

[0045] A priority determination module is used to determine the data exchange priority of each target physical field data based on the color identification.

[0046] In a fourth aspect, the present application further provides a computer device comprising a memory and a processor, wherein the memory stores a computer program, and the processor implements any step in the first aspect when executing the computer program.

[0047] In a fifth aspect, the present application further provides a computer-readable storage medium having a computer program stored thereon, which implements any step in the first aspect when executed by a processor.

[0048] In a sixth aspect, the present application further provides a computer program product, comprising a computer program, which implements any step in the first aspect when executed by a processor.

[0049] In the electrical equipment virtual debugging system provided by the present application, and the method, device, computer equipment, computer-readable storage medium and computer product for determining the data exchange priority therein, the method for determining the data exchange priority in the electrical equipment virtual debugging system obtains multiple target physical field data in the electrical equipment virtual debugging system and extracts characteristic information of each target physical field data; the characteristic information includes at least one characteristic type of the real-time nature, priority, importance, and parameter value of the data; based on the characteristic information and at least one of the real-time data requirements of the electrical equipment virtual debugging system, the color identification of each target physical field data is determined; the color identification includes at least one of the color type and the color gradient; the data exchange priority of each target physical field data is determined based on the color identification; so as to realize the classification of data interacting across modules based on the color identification, so as to dynamically adjust the data exchange priority according to the characteristics such as the real-time nature, priority and importance of the data, which is beneficial to help the system reduce unnecessary cross-module data exchange during the multi-physical field coupling simulation process and optimize computing resources and data transmission efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0050] In order to more clearly illustrate the technical solutions in the embodiments of the present application or related technologies, the following briefly introduces the drawings required for use in the embodiments of the present application or related technical descriptions. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other related drawings can be obtained based on these drawings without paying any creative work.

[0051] Figure 1 Schematic diagram of the architecture of a digital twin-based electrical equipment virtual commissioning system in one embodiment;

[0052] Figure 2 FIG. 1 is an application environment diagram of a method for determining data exchange priority in an electrical equipment virtual debugging system according to an embodiment;

[0053] Figure 3 1 is a flow chart of a method for determining data exchange priority in a virtual debugging system for electrical equipment according to an embodiment;

[0054] Figure 4 A schematic diagram of physical field coupling and data synchronization in one embodiment;

[0055] Figure 5 is a schematic diagram of a data management and exchange layer in one embodiment;

[0056] Figure 6 A schematic diagram of assigning colors to electrical data in one embodiment;

[0057] Figure 7 A schematic diagram of assigning colors to temperature data in one embodiment;

[0058] Figure 8 A schematic diagram of assigning colors to vibration data in one embodiment;

[0059] Figure 9 A schematic diagram of data transmission and synchronization in one embodiment;

[0060] Figure 10 A structural block diagram of a device for determining data exchange priority in a virtual debugging system for electrical equipment according to an embodiment;

[0061] Figure 11 FIG. 1 is a diagram showing the internal structure of a computer device in one embodiment. DETAILED DESCRIPTION

[0062] In order to make the purpose, technical solutions and advantages of this application more clear, the following further describes this application in detail with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain this application and are not intended to limit this application.

[0063] In related technologies, the electrical equipment virtual debugging system is a tool based on computer simulation technology, which is used to debug and verify the design and control of the electrical system in a virtual environment before the actual equipment is put into operation.

[0064] Digital Twin Technology (DTT) enables real-time connection and interaction between virtual models and physical entities. It collects data from physical devices or systems through sensors and Internet of Things (IoT) devices and transmits this data to a virtual model, creating a digital replica of the physical object (the "digital twin"). This virtual model not only reflects the state, performance, and behavior of the physical entity but also simulates its response under different conditions, enabling prediction, analysis, and optimization.

[0065] Because the operation of electrical equipment involves more than just electrical characteristics, it also includes the coupled influences of multiple physical fields, such as temperature, mechanical vibration, and airflow. Virtual commissioning systems and digital twin technologies in related technologies mostly focus on electrical simulation and lack comprehensive integration of multiple physical fields. Consequently, these systems cannot intuitively identify and distinguish the priority, real-time nature, and importance of different data types. For example, real-time electrical fault alarm data and temperature data should be processed differently, but if this distinction is not clearly established, critical data may be delayed.

[0066] Please refer to Figure 1 , shows a schematic diagram of the architecture of a virtual debugging system for electrical equipment based on digital twins, including a simulation core module, a physical field model module, a data management and exchange layer, a user interface, and a calculation and execution module; wherein the physical field model module can specifically include, for example, an electromagnetic field model, a thermal field model, a mechanical field model, and a fluid field model. In order to solve the problem of multi-physical field coupling in electrical equipment, the virtual debugging system for electrical equipment based on digital twins needs to integrate the development and integration of a multi-physical field coupling simulation platform, real-time data acquisition and analysis, intelligent optimization algorithms, and efficient computing technologies. Through these methods, the performance of the virtual debugging system and digital twin technology can be comprehensively improved, so that the equipment can accurately reflect the interaction between multiple physical fields during the design, debugging, monitoring, and optimization process. The development and integration of the multi-physical field coupling simulation platform is used to create a flexible, scalable, and modular platform to achieve the ability to simultaneously simulate the coupling effects of different physical fields such as electromagnetic, thermal, mechanical, and fluid.

[0067] In order to identify and distinguish the data exchange priority of physical field data that needs to be interacted across modules in the electrical equipment virtual debugging system, the embodiment of the present application provides a method for determining the data exchange priority in the electrical equipment virtual debugging system, which can be applied to Figure 2 In the application environment shown, Figure 1 The electrical equipment virtual commissioning system based on digital twin can be Figure 2 The terminal 102 and / or server 104 shown in FIG. Terminal 102 communicates with server 104 via a network. A data storage system can store data that server 104 needs to process. The data storage system can be integrated with server 104 or located in the cloud or on other network servers. Terminal 102 can be, but is not limited to, various personal computers, laptops, smartphones, tablets, etc. Server 104 can be a standalone physical server, a server cluster or distributed system consisting of multiple physical servers, or a cloud server providing cloud computing services.

[0068] In an exemplary embodiment, Figure 3As shown, a method for determining data exchange priority in a virtual debugging system of electrical equipment is provided, and the method is applied to Figure 1 The terminal in FIG is taken as an example to illustrate the method, including the following steps 201 to 203. Among them:

[0069] Step 201 : Acquire multiple target physical field data in the electrical equipment virtual debugging system and extract characteristic information of each target physical field data; the characteristic information includes at least one characteristic type of the data's real-time performance, priority, importance, and parameter value.

[0070] Among them, the electrical equipment virtual debugging system can be an electrical equipment virtual debugging system based on digital twins, which is used to debug and verify the design and control of electrical systems related to electrical equipment through a virtual environment before the actual electrical equipment is put into operation.

[0071] Physical field data includes data related only to its own physical field, which is not transmitted to other physical fields, and also includes data that is transmitted to other physical fields. The target physical field data here refers to the physical field data that needs to be transmitted or exchanged between at least two physical fields. Physical field data refers to parameters of different physical fields, such as electric field strength in electromagnetic fields, temperature in thermal fields, and stress in mechanical fields.

[0072] The characteristic information of the target physical field data may be characteristic information set in advance by management personnel based on needs; the characteristic information may include, for example, the real-time nature, priority, importance, parameter values, etc. The characteristic information of a target physical field data may include only one characteristic type or two or more characteristic types, and this application does not impose specific limitations on this.

[0073] For example, from all physical field data in the digital twin-based electrical equipment virtual commissioning system, target physical field data that interacts with other physical fields is screened out. Feature information of each target physical field data is then extracted to determine the specific feature types included in the feature information of each target physical field data. For example, the feature information of some target physical field data may only involve one of real-time performance, priority, importance, and parameter value, while the feature information of some target physical field data may involve two or more of these characteristics simultaneously.

[0074] Step 202 : determining a color identification of each target physical field data based on at least one of the characteristic information and the real-time data requirement of the electrical equipment virtual debugging system; the color identification includes at least one of a color type and a color gradient.

[0075] Among them, color identification is used to represent the data exchange priority of each target physical field data when it is transmitted in the digital twin-based electrical equipment virtual debugging system. For example, different data exchange priorities can be represented by different color identifications. For example, different data exchange priorities can be represented by the depth and brightness of the same color.

[0076] The present application provides an optional implementation scheme in which the color identification may include at least one of a color type and a color gradient, wherein the color type may include, for example, red, yellow, green, blue and other color types, and the color gradient may include, for example, different shades or brightness of red, different shades or brightness of blue, etc.

[0077] The real-time data requirements of the electrical equipment virtual commissioning system refer to the transmission requirements for at least some target physical field data during the current operating period of the electrical equipment virtual commissioning system. Given the large amount of target physical field data, the electrical equipment virtual commissioning system does not require the interactive transmission of all target physical field data during the same operating period.

[0078] For example, after obtaining the characteristic information of each target physical field data based on executing step 201, the color identification of each target physical field data can be determined based on at least one of the characteristic information and the real-time data requirements of the electrical equipment virtual debugging system based on the current working status of the electrical equipment virtual debugging system.

[0079] Then, step 203 may be executed to determine the data exchange priority corresponding to each target physical data in the current working time period based on the color identification.

[0080] For example, the data exchange priority of the target physical data identified by the red type is higher than the data exchange priority of the target physical data identified by the green type; for example, the data exchange priority of the target physical data identified by the dark red type is higher than the data exchange priority of the target physical data identified by the light pink type.

[0081] In the method for determining the data exchange priority in the electrical equipment virtual debugging system provided by the above-mentioned application, multiple target physical field data in the electrical equipment virtual debugging system are obtained, and characteristic information of each target physical field data is extracted; the characteristic information includes at least one characteristic type of the real-time nature, priority, importance, and parameter value of the data; based on the characteristic information and at least one of the real-time data requirements of the electrical equipment virtual debugging system, the color identification of each target physical field data is determined; the color identification includes at least one of the color type and the color gradient; the data exchange priority of each target physical field data is determined based on the color identification; so as to realize the classification of data interacting across modules based on the color identification, so as to dynamically adjust the data exchange priority according to the characteristics such as the real-time nature, priority and importance of the data, which is conducive to helping the system reduce unnecessary cross-module data exchange during the multi-physical field coupling simulation process and optimize computing resources and data transmission efficiency.

[0082] In an exemplary embodiment, the step 202 of determining the color identification of each target physical field data based on the characteristic information may be implemented by executing steps 221 to 225, wherein:

[0083] Step 221, comparing the characteristic value of the characteristic information of each target physical field data with a preset characteristic threshold; wherein the preset characteristic threshold includes at least one sub-characteristic threshold;

[0084] Step 222: When the characteristic value of the target physical field data is greater than or equal to the first sub-characteristic threshold, determine that the color identification of the target physical field data is a first color type;

[0085] Step 223: When the characteristic value of the target physical field data is greater than or equal to the second sub-characteristic threshold and less than the first sub-characteristic threshold, determine that the color identifier of the target physical field data is a second color type;

[0086] Step 224: if the characteristic value of the target physical field data is greater than or equal to the third sub-characteristic threshold and less than the second sub-characteristic threshold, determine that the color identifier of the target physical field data is a third color type;

[0087] Step 225: When the characteristic value of the target physical field data is less than the third sub-characteristic threshold, determine that the color identifier of the target physical field data is a fourth color type;

[0088] The first color type, the second color type, the third color type and the fourth color type are arranged clockwise in the hue circle, or the first color type, the second color type, the third color type and the fourth color type are arranged counterclockwise in the hue circle.

[0089] Exemplarily, an implementation method for determining the corresponding color identification based on the characteristic information of the target physical field data is provided, which is to calculate the characteristic value corresponding to the characteristic type included in the characteristic information of each target physical field data, and compare the characteristic value of each target physical field data with a preset preset characteristic threshold to assign different color identifications to the target physical field data with different comparison results.

[0090] It should be noted that the present application does not specifically limit the number of sub-feature thresholds included in the pre-set preset feature threshold; for example, only one sub-feature threshold may be included. In this case, the comparison results of the characteristic value of the target physical field data and the preset feature threshold may include two types, one is that the characteristic value is greater than or equal to the preset feature threshold, and the other is that the characteristic value is less than the preset feature threshold. In this case, the target physical field data can be divided into two cases for color identification, for example, one type of target physical field data is color-identified in red, and the other type of target physical field data is color-identified in blue. For example, it is also possible to select the pre-set preset feature threshold to include two or more sub-feature thresholds.

[0091] An optional embodiment is provided in which the pre-set preset feature threshold includes three sub-feature thresholds, namely a first sub-feature threshold, a second sub-feature threshold and a third sub-feature threshold, wherein the first sub-feature threshold is greater than the second sub-feature threshold, and the second sub-feature threshold is greater than the third sub-feature threshold. Based on this, the characteristic value of the characteristic information of each target physical field data is compared with the first sub-feature threshold, the second sub-feature threshold, and the third sub-feature threshold to obtain the comparison result of each target physical field data compared with the preset sub-feature thresholds; specifically, when the comparison result represents the characteristic value of the target physical field data, which is greater than or equal to the first sub-feature threshold, the color identification of the relevant target physical field data can be selected as the first color type; when the comparison result represents the characteristic value of the target physical field data, which is greater than or equal to the second sub-feature threshold and less than the first sub-feature threshold, the color identification of the relevant target physical field data can be selected as the second color type; when the comparison result represents the characteristic value of the target physical field data, which is greater than or equal to the third sub-feature threshold and less than the second sub-feature threshold, the color identification of the relevant target physical field data can be selected as the third color type; when the comparison result represents the characteristic value of the target physical field data, which is less than the third sub-feature threshold, the color identification of the relevant target physical field data can be selected as the fourth color type.

[0092] That is, based on the characteristic value of each target physical field data compared to the size of each sub-feature threshold, different color identifiers are assigned to the corresponding target physical field data in different size intervals. Among them, the above-mentioned first color type can be, for example, a red type, the second color type can be, for example, an orange type, the third color type can be, for example, a yellow type, and the fourth color type can be, for example, a green type. In this embodiment, the first color type, the second color type, the third color type, and the fourth color type are arranged counterclockwise in the hue circle. However, this is only an optional implementation method provided by the present application. The first color type, the second color type, the third color type, and the fourth color type can also be selected, specifically presented as being arranged clockwise in the hue circle. Among them, two adjacent color types can be adjacent to each other in the twelve-color hue circle, or they can be spaced apart in the twelve-color hue circle. This application does not make specific restrictions on this. For example, in the twelve-color hue circle, the five colors of red, orange, yellow, green, and blue are arranged counterclockwise in sequence. The above-mentioned first color type, second color type, third color type, and fourth color type can be the four colors of red, orange, yellow, and green, respectively, or the four colors of red, orange, green, and blue, etc.

[0093] It should be noted that, for a target physical field data, the characteristic value of its corresponding characteristic information is obtained by summing up the characteristic types of the target physical field data; this application does not make any specific restrictions on the specific calculation method of the characteristic value of the target physical field data, and the method for calculating the characteristic value of the target physical field data can be set based on demand.

[0094] Regarding the calculation method of the characteristic value of the characteristic information corresponding to the target physical field data, an optional implementation method is provided, in which each characteristic type can include three situations, such as high, medium, and low. The high characteristic type can be assigned a first score, the medium characteristic type a second score, and the low characteristic type a third score. The characteristic value of the characteristic information corresponding to a target physical field data can be the average of the scores corresponding to each characteristic type included. In the case where each characteristic type includes different classification levels, the scores corresponding to each classification level of each characteristic type can be set separately based on needs.

[0095] An optional implementation method is provided, where for two target physical field data, for example, the feature information corresponding to the first target physical field data and the second target physical field data respectively includes the feature type of priority, and does not include other feature types, wherein the priority corresponding to the first target physical field data is high, and the priority corresponding to the second target physical field data is medium. At this time, the characteristic value corresponding to the first target physical field data is higher than the characteristic value corresponding to the second target physical field data.

[0096] An optional implementation method is provided, for two target physical field data, for example, the feature information of the first target physical field data includes a feature type with high priority and a feature type with medium importance, and the feature information of the second target physical field data includes a feature type with high priority and a feature type with low real-time performance. In this case, the characteristic value corresponding to the first target physical field data can be set to be higher than the characteristic value corresponding to the second target physical field data.

[0097] In an exemplary embodiment, the step 202 of determining the color identification of each target physical field data based on the characteristic information may be implemented by executing steps 311 to 313, wherein:

[0098] Step 311: Obtain a normalized value within a preset range corresponding to each feature type of each feature information, and a weight corresponding to each feature type;

[0099] Step 312: determining a comprehensive weight of each feature information based on the standardized value and weight of each feature type;

[0100] Step 313, determining the color type of the corresponding target physical field data based on the size of each comprehensive weight; wherein, as the comprehensive weight increases successively, the color type is arranged clockwise or counterclockwise in the hue wheel.

[0101] For example, a method for determining the corresponding color identifier based on the feature information of target physical field data is provided by first normalizing each feature type in the feature information corresponding to each target physical field data so that they can be converted to a unified scale. In other words, the normalization process is intended to ensure that different characteristics (feature types) can be fairly compared when assigning colors. For example, each feature type can be normalized to a range of [0, 1]. Specifically, the relevant normalized value can be obtained by using the preset maximum and minimum values ​​corresponding to each feature type, as well as the value of the feature type itself.

[0102] For example, assuming that the value of real-time itself is T, the value of priority itself is P, the value of importance itself is I, and the value of parameter size itself is S; then based on the preset maximum value T corresponding to real-time max , minimum value T min and the real-time value T, calculate the normalized value T' corresponding to the real-time; and, based on the preset maximum value P corresponding to the priority max , minimum value P min and priority value P, calculate the normalized value P' corresponding to the priority; and, based on the preset maximum value I corresponding to the importance max , minimum value Imin and importance value I, calculate the normalized value I' corresponding to the importance; and the preset maximum value S corresponding to the parameter value can be calculated based on the value of the parameter. max , minimum value S min The parameter value is taken as S, and the standardized value S' corresponding to the parameter value is calculated.

[0103] After obtaining the standardized value corresponding to each feature type in the feature information corresponding to each target physical field data, the weight value of the feature information corresponding to each target physical field data is further obtained; specifically, the comprehensive weight of the feature information corresponding to each target physical field data can be calculated through the weight corresponding to each feature type and the calculated standardized value.

[0104] For example, suppose the weight of real-time itself is W T The weight of the priority itself is W P The weight of the importance itself is W I The weight of the parameter value itself is W S , then the comprehensive weight of the characteristic information corresponding to a target physical field data can be calculated based on W T , T', W P , P', W I 、I'、W S , S'. The value range of the comprehensive weight can also be in the range of [0, 1].

[0105] The color type of each target physical field data item can then be determined based on the size of the comprehensive weight corresponding to the characteristic information of each target physical field data item. For example, the color type can be arranged clockwise on the hue circle as the comprehensive weight increases, or counterclockwise on the hue circle as the comprehensive weight increases. Furthermore, the color gradient can be increased as the comprehensive weight increases, or decreased as the comprehensive weight increases.

[0106] In an exemplary embodiment, the above step 202 of determining the color identification of each target physical field data based on the characteristic information can be implemented by executing steps 321 to 324, wherein:

[0107] Step 321: Obtain the normalized value within a preset range corresponding to each feature type of each feature information, and the weight corresponding to each feature type;

[0108] Step 322: Determine the comprehensive weight of each feature information based on the standardized value and weight of each feature type;

[0109] Step 323: determining the color value corresponding to each comprehensive weight based on a preset color mapping function, and converting the color value into an RGB value;

[0110] Step 324 : determining the color type of the corresponding target physical field data based on each RGB value.

[0111] Exemplarily, an implementation method for determining the corresponding color identification based on the characteristic information of the target physical field data is provided as follows:

[0112] For example, a method for determining the corresponding color identifier based on the feature information of target physical field data is provided by first normalizing each feature type in the feature information corresponding to each target physical field data so that they can be converted to a unified scale. In other words, the normalization process is intended to ensure that different characteristics (feature types) can be fairly compared when assigning colors. For example, each feature type can be normalized to a range of [0, 1]. Specifically, the relevant normalized value can be obtained by using the preset maximum and minimum values ​​corresponding to each feature type, as well as the value of the feature type itself.

[0113] For example, assuming that the value of real-time itself is T, the value of priority itself is P, the value of importance itself is I, and the value of parameter size itself is S; then based on the preset maximum value T corresponding to real-time max , minimum value T min and the real-time value T, calculate the normalized value T' corresponding to the real-time; and, based on the preset maximum value P corresponding to the priority max , minimum value P min and priority value P, calculate the normalized value P' corresponding to the priority; and, based on the preset maximum value I corresponding to the importance max , minimum value I min and importance value I, calculate the normalized value I' corresponding to the importance; and the preset maximum value S corresponding to the parameter value can be calculated based on the value of the parameter. max , minimum value S min The parameter value is taken as S, and the standardized value S' corresponding to the parameter value is calculated.

[0114] After obtaining the standardized value corresponding to each feature type in the feature information corresponding to each target physical field data, the weight value of the feature information corresponding to each target physical field data is further obtained; specifically, the comprehensive weight of the feature information corresponding to each target physical field data can be calculated through the weight corresponding to each feature type and the calculated standardized value.

[0115] For example, suppose the weight of real-time itself is WT The weight of the priority itself is W P The weight of the importance itself is W I The weight of the parameter value itself is W S , then the comprehensive weight of the characteristic information corresponding to a target physical field data can be calculated based on W T , T', W P , P', W I 、I'、W S , S'. The value range of the comprehensive weight can also be in the range of [0, 1].

[0116] Furthermore, based on the obtained comprehensive weights corresponding to the characteristic information of each target physical field data, correspondingly adapted color values ​​are obtained. For example, a preset color mapping function can be used to calculate the color values ​​corresponding to each comprehensive weight. The color values ​​can be within the range of [0, 1]. Then, based on a preset conversion function between color values ​​and RGB values, the associated RGB values ​​are determined based on the color values ​​corresponding to the characteristic information of each target physical field data. RGB values ​​specifically include R (Red), G (Green), and B (Blue).

[0117] Then, the RGB value calculated based on each target physical field data can be used as the color type of the target physical field data.

[0118] In an exemplary embodiment, the above step 202, based on the real-time data requirements of the electrical equipment virtual commissioning system, determines the color identification of each target physical field data, which can be achieved by executing steps 331 and 332, wherein:

[0119] Step 331 , when the target physical field data is data that meets real-time data requirements, determining that the color identifier of the target physical field data is a first color type;

[0120] Step 332 : When the target physical field data does not meet the real-time data requirement, determine that the color identification of the target physical field data is a second color type.

[0121] For example, during the current working time period of the electrical equipment virtual debugging system, if a real-time data requirement is set, the data included in the real-time data requirement can be identified to determine which of the multiple target physical field data are included in the real-time data requirement. The target physical field data included in the real-time data requirement is the data with a higher priority during the current working time period, while the target physical field data not included in the real-time data requirement is the data with a lower priority during the current working time period. For example, for the target physical field data included in the real-time data requirement, its corresponding color identification is determined to be a first color type, and for the target physical field data not included in the real-time data requirement, its corresponding color identification is determined to be a second color type.

[0122] Furthermore, after color identification of each target physical field data to determine whether it meets the real-time data requirement, further steps that may be performed include step 333 and step 334, wherein:

[0123] Step 333: Obtain parameter values ​​of target physical field data of the same data type from target physical field data of the same color type; the data types include electrical parameters, temperature data, vibration data, and airflow data;

[0124] Step 334 , determining the color gradient of the corresponding target physical field data based on the parameter value; wherein, as the parameter value increases, the color gradient increases or decreases.

[0125] For example, when determining whether each target physical field data among multiple target physical field data belongs to the real-time data requirement within the current working time period based on color type, the corresponding priorities of multiple target physical field data belonging to the same color type can be further classified; that is, the priorities of multiple target physical field data related to the first color type are further classified, and the priorities of multiple target physical field data related to the second color type are further classified.

[0126] Specifically, it is possible to select the parameter value size of the target physical field data with the same data type in the target physical field data belonging to the same color type, and then sort the priority of the relevant target physical field data based on the parameter value size; for example, as the parameter value size increases successively, the color gradient increases successively; or, as the parameter value size increases successively, the color gradient decreases successively.

[0127] In an exemplary embodiment, the step 202 of determining the color identification of each target physical field data based on the characteristic information may be implemented by executing steps 341 and 342, wherein:

[0128] Step 341, obtaining parameter values ​​of target physical field data of the same data type; the data types include electrical parameters, temperature data, vibration data, and airflow data;

[0129] Step 342, for target physical field data of the same data type, determine the color gradient of the corresponding target physical field data based on the parameter value; wherein, as the parameter value increases, the color gradient increases or decreases.

[0130] Exemplarily, in the case where the characteristic information of most target physical field data includes the characteristic type of parameter value size, an optional implementation method is provided for determining the color identification of each target physical field data based on the characteristic information, which is to obtain the parameter value size of each target physical field data with the same data type, and then determine the color gradient of each target physical field data of the same data type based on the parameter value size of each target physical field data; for example, for each target physical field data of the same data type, as the parameter value size increases successively, the color gradient increases successively; or as the parameter value size increases successively, the color gradient decreases successively.

[0131] That is, the data exchange priority of each target physical field data of the same data type can be identified by different color gradients.

[0132] In an exemplary embodiment, the method further includes: determining a color type of the target physical field data based on a data type of the target physical field data.

[0133] Exemplarily, in order to distinguish target physical field data of different data types, after determining the color gradient corresponding to each target physical field data, the color type corresponding to the target physical field data of each data type can be further determined; for example, the color type of each target physical field data belonging to electrical parameters is red, and each target physical field data belonging to electrical parameters has a red type color gradient, that is, different target physical field data belonging to electrical parameters can be identified by using gradient red of different saturations; the color type of each target physical field data belonging to airflow data is blue, and each target physical field data belonging to airflow data has a blue type color gradient, that is, different target physical field data belonging to electrical parameters can be identified by using gradient blue of different saturations.

[0134] In an exemplary embodiment, the determination of the data exchange priority of each target physical field data based on the color identification performed in the above step 203 can be achieved by executing steps 231 and 232, wherein:

[0135] Step 231 , as the color types of the target physical field data correspond to the clockwise arrangement in the hue circle, the data exchange priority of the target physical field data increases or decreases in sequence;

[0136] Step 232 , as the color gradient of the target physical field data increases sequentially, the data exchange priority of the target physical field data increases or decreases sequentially.

[0137] For example, the data exchange priority of each target physical field data can be determined based on the color type of each target physical field data and the arrangement order in the twelve-color hue wheel; or, the data exchange priority of each target physical field data can be determined based on the color gradient of each target physical field data, that is, the color brightness or saturation (depth). In addition, as mentioned above, for multiple target physical field data whose priorities are determined based on color type, if there are several target physical field data with the same priority level, for example, all of them are in the second level, then the multiple target physical field data in the second level can be further prioritized based on the color gradient of the second-level target physical field data.

[0138] For the electrical equipment virtual debugging system provided in this application, and the method for determining the data exchange priority therein, an optional implementation method is also provided, which can be referred to Figure 1 , the architecture diagram of the electrical equipment virtual commissioning system shown, wherein:

[0139] The simulation core module is responsible for executing the calculation and coupling of each physical field, performing the core calculation of the coupling of multiple physical fields through the coupling algorithm engine, and performing coupling simulation through numerical methods (such as finite element method, finite volume method, etc.); the coupling algorithm engine supports data exchange and feedback between different physical fields; in the embodiment provided in this application, a dedicated solver is provided for each physical field, and different physical fields (electromagnetic field, thermal field, mechanical field, fluid field) use different mathematical models and solution methods according to their characteristics.

[0140] For example, the electromagnetic field uses an electromagnetic field solver (such as Maxwell's equations and Poynting's theorem); the thermal field uses a thermodynamic solver based on heat conduction, convection, and radiation; the mechanical field uses a solver based on elasticity and nonlinear mechanics; the fluid field uses a fluid dynamics solver and uses a coordination algorithm to deal with the coupling problems of different physical fields.

[0141] Physical field model module, the simulation of each physical field is managed through a dedicated module. At the same time, each module has independent input and output interfaces to exchange data with other modules to ensure simulation accuracy and efficiency. The physical field model module includes electromagnetic field module, thermal field module, mechanical field module, and fluid module.

[0142] Data management and exchange layer, such as Figure 4 As shown, it is responsible for transmitting information between different physical field models to ensure data synchronization and consistency. The parameters of different physical fields (such as electric field intensity in electromagnetic fields, temperature in thermal fields, and stress in mechanics) may have different units and representations, so standardized data formats and unified interfaces are required; the data exchange mechanism supports cross-module data exchange and adopts an efficient data transmission mechanism. In the process of multi-physical field coupling simulation, the timing and feedback mechanism of the calculation process of each physical field are precisely controlled to maintain the synchronization of the calculation steps of each physical field.

[0143] Traditional data transmission mechanisms include memory sharing, message queues, and databases. When multiple modules share memory, synchronization issues may occur, especially when multiple processes or threads access the same memory at the same time, which may lead to data consistency and conflict issues. Message queue transmission has a certain delay, especially in high concurrency situations. The message delivery efficiency will decrease, affecting the real-time performance of the system. The read and write speed of the database is slower than that of memory sharing, especially in simulation environments that require frequent exchange of large amounts of data, which poses a performance bottleneck.

[0144] This application can use spatial gradient color identification to "spatially" classify cross-module data according to different characteristics; each type of data can be given a unique color gradient, and the color gradient can be used to represent the different characteristics of the data (such as timeliness, importance, priority, etc.), and the data can be efficiently managed and exchanged based on factors such as the real-time nature of the data, data volume, and module requirements.

[0145] Spatial gradient colors can help clearly distinguish different types of data. For example, real-time data can be marked in red (high priority), while historical data can be marked in blue (low priority). Through color gradients, the priority of data exchange can be dynamically adjusted according to the data requirements of different modules, and resource allocation can be optimized. By spatially classifying data, unnecessary cross-module data exchange can be effectively reduced. For example, if a module only needs to interact with specific types of data, color can be used to distinguish and exchange only specific categories of data, avoiding the exchange of full data and improving efficiency.

[0146] For example Figure 5 As shown, electromagnetic field data, fluid field data, thermal field data, and mechanical field data can each be color-coded (color-coded). For example, electromagnetic field data can be color-coded red, fluid field data can be color-coded blue, thermal field data can be color-coded green, and mechanical field data can be color-coded yellow. You can choose to color-code only real-time data that requires cross-module interaction.

[0147] Furthermore, specific steps for data classification by spatial gradient color are provided as follows, which may include, for example, the embodiments shown in the following steps S1 to S6.

[0148] S1, data analysis and definition of classification rules, including:

[0149] Data identification: Identify all possible cross-module data types in the system, including multi-physics field data such as electrical parameters, temperature, vibration, and airflow;

[0150] Data feature definition: Define some features for each type of data, including:

[0151] Real-time: For example, electrical parameters may require real-time updates, while temperature data can have a longer update interval;

[0152] Priority: Some data (such as electrical fault alarms) may be more important than other data (such as ambient temperature);

[0153] Importance: For example, electromagnetic field data is crucial for real-time control systems, while fluid flow rate data may only be part of an optimization process;

[0154] Data size: The amount of data to be transferred (e.g. large or small data).

[0155] S2, assign color ranges, specifically including color identification design. According to the different characteristics of the data, different color types or color gradients are assigned to each data type. For example:

[0156] Red: for real-time, high-priority, or extremely important data;

[0157] Orange: for slightly less urgent or important data;

[0158] Yellow: used for data that is updated less frequently or does not directly affect control decisions;

[0159] Green: used for non-critical data, which is updated less frequently and does not affect the overall operation of the system;

[0160] Gradient colors: For a specific range of data, you can use gradient colors. For example, the data gradually changes color from the lowest value to the maximum value to help distinguish the size or range of the data.

[0161] S3, data identification and classification, including dynamic identification, assigning color identification to data in different modules. Data is colored when transmitted to indicate its priority, real-time nature, importance, etc.

[0162] For example:

[0163] Real-time data: can be red or dark red, ensuring the highest priority and real-time processing by the system;

[0164] Historical data: Use milder tones, such as green or blue, to indicate that its transmission can be processed later.

[0165] Multi-dimensional classification: In addition to color, data can be identified by other dimensions, such as the data source module, data type, and the physical fields involved, to achieve flexible management in complex systems.

[0166] Provides a way to achieve a unified scale for various types of data, including:

[0167] First, the features of various types of data need to be standardized so that they are on a unified scale. Standardization is to ensure that different characteristics (such as real-time, priority, etc.) can be fairly compared when assigning colors.

[0168] Assume the following data characteristics: real-time (T), priority (P), importance (I), parameter value size or data size (S);

[0169] Normalize each feature so that it is in the range of [0, 1]. The relevant calculation method can be: 、 、 、 Among them, T min 、T max etc. are the minimum and maximum values ​​of the corresponding features.

[0170] In order to assign a color range to the data, we further calculate a comprehensive "weight" value, taking each feature into consideration. Assume that the weight of each feature is: W T 、W P 、W I 、W S ; then the comprehensive weight W total The calculation method can be: Among them, W T 、W P 、W I 、W S It is the weight of each feature, which determines the influence of each feature on the final result; the comprehensive weight W total The values ​​of will be in the range [0, 1], and the data will be mapped to a range of colors according to this weight, for example:

[0171] Red: corresponds to the highest comprehensive weight (i.e. close to 1), indicating extremely high priority and importance;

[0172] Orange: corresponds to a medium comprehensive weight (e.g. 0.6-0.8), indicating important but less urgent data;

[0173] Yellow: corresponds to a lower comprehensive weight (e.g., 0.3-0.6), indicating data with low update frequency or that does not directly affect decision-making;

[0174] Green: corresponds to the lowest comprehensive weight (close to 0), indicating non-critical data with low priority.

[0175] Furthermore, a color mapping function C(W total ), W total The values ​​are mapped to color values, assuming that the color values ​​are in the range [0, 1], where 0 represents green and 1 represents red; for example .

[0176] Specifically, the RGB model can be used, mapped as: green (0, 255, 0), yellow (255, 255, 0), orange (255, 165, 0), red (255, 0, 0).

[0177] For data in a specific range (such as temperature, current, etc.), if you want to use gradient colors to represent the size or range of the data, perform color gradient calculations through the following steps. Assuming that we have data ranging from X min to X max , for each data point X i , use the following formula to calculate its corresponding gradient color: . Use the above formula to change the value from the lowest value X min To the highest value X max Mapped to a gradient from green to red.

[0178] A further specific embodiment is provided:

[0179] Assume the following features and weights: real-time T = 0.9 (near real-time data), priority P = 0.8 (high priority), importance I = 0.7 (medium importance), data size S = 0.5 (small data volume); and assume that the weight of each feature is: W T =0.4, W P =0.3, W I =0.2, W S = 0.1; further normalize the data: 、 、 、 ; Further calculate the comprehensive weight:

[0180] W total =0.4*0.9+0.3*0.8+0.2*0.7+0.1*0.5=0.36+0.24+0.14+0.05=0.79

[0181] Mapping the comprehensive weight to the color range, since W total =0.79, and it is mapped to between red and green, and the resulting color is a color value close to orange or red. Through the above formula, the comprehensive weight is calculated based on the different characteristics of the data (such as real-time, priority, importance, data size, etc.), and the data is mapped to different color ranges. The gradient color is mapped according to the specific value of the data, which is suitable for situations where changes in data size need to be reflected.

[0182] S4, develop a data transmission strategy, including:

[0183] Color-based transmission priority: Different transmission strategies are developed based on the color of the data. For example, real-time data (such as red) is quickly transmitted using a shared memory channel, while less urgent historical data (such as green) is transmitted using a message queue or database.

[0184] Dynamic adjustment: The transmission method of different types of data is adjusted according to the system load and real-time status. For example, when the system load is too high, the processing of low-priority data (such as yellow and green) is delayed to ensure that high-priority data (such as red and orange) is not affected.

[0185] S5, data transmission and synchronization, including:

[0186] Memory sharing and color identification synchronization: For data with high real-time requirements (such as red), memory sharing or direct mapping is used to ensure fast data synchronization between modules;

[0187] Message queue and color identification synchronization: For data with lower real-time requirements (such as yellow and green), asynchronous transmission is carried out through the message queue. Each message in the message queue can be prioritized according to the color identification of the data, ensuring that high-priority data is processed first;

[0188] Synchronization of database processing and color identification: For historical data or large amounts of data, they can be stored in the database, and color identification can help decide when to extract and process these data from the database.

[0189] S6, Data Exchange and Processing, including:

[0190] Data exchange: Color-coded data is exchanged between modules within the system through appropriate channels. For example, red-labeled data can be prioritized for transmission to the control module for real-time processing, while green-labeled data can be retrieved and processed later.

[0191] Data processing and feedback: After data passes through each module, the system provides feedback based on the data's color. Color changes (such as from red to green) can also be used to indicate the status or completion of data processing. For example, when high-priority data is processed, color feedback can be used to inform other modules.

[0192] The process of data classification through spatial gradient colors can effectively improve the efficiency, clarity, and real-time performance of data exchange. The main steps include defining data characteristics and classification rules, assigning colors, managing data transmission based on priority and real-time performance, dynamically adjusting transmission strategies, and using color identification for feedback and optimization. This method can help the system better process and exchange data in complex multi-physics field coupling simulations, improving the system's response speed and overall performance.

[0193] Please refer to Figure 6-Figure 8 For example, when the characteristic types of electrical parameters specifically include high real-time performance, high priority, high importance, and medium data size, the assignable color is red; when the characteristic types of temperature data specifically include low real-time performance, medium priority, medium importance, and low data size, the assignable color is green; when the characteristic types of vibration data specifically include medium real-time performance, medium priority, low importance, and high data size, the assignable color is orange.

[0194] Please refer to Figure 9 , providing a selectable data transmission and synchronization view. For real-time data, historical data, and non-critical data, real-time data is colored red, historical data is colored green, and non-critical data is colored yellow. When real-time data, historical data, and non-critical data are exchanged in the electrical equipment virtual commissioning system, a fast transmission control strategy can be used for real-time data, a delayed transmission control strategy can be used for historical data, and an asynchronous transmission control strategy can be used for non-critical data.

[0195] Among them, real-time data adopts fast transmission, specifically involving: memory sharing, fast synchronization, real-time control processing and real-time decision-making; historical data adopts delayed transmission, specifically involving: database, database extraction, delayed processing, and optimized processing; non-critical data adopts asynchronous transmission, specifically involving: message queue, asynchronous processing, low-priority processing, and system monitoring.

[0196] Data flow and workflow: users select models of different physical fields, set initial conditions (such as current, temperature, pressure, etc.), and set boundary conditions (such as temperature boundary, electromagnetic boundary, fluid boundary, etc.). The simulation core module starts each physical field solver for calculation based on the data and conditions entered by the user, and couples the feedback results of each physical field.

[0197] Result analysis and optimization: The simulation results will be analyzed and optimized by the optimization module. Users can further adjust the design parameters based on the analysis results. Spatial gradient colors can be used to associate data classifications. This is done by analyzing and classifying data features, combined with an effective data exchange mechanism, to form a closed-loop collaborative workflow in various aspects such as data transmission, processing, and visualization. Spatial gradient colors are not only a visualization tool for data classification, but also an important way to optimize data flow, improve system efficiency, and enhance user interaction experience.

[0198] Simulation feedback and iteration, based on the optimization results, the simulation platform can provide feedback on the optimized design through a visual interface, and users can choose to further adjust the model or parameters and perform iterative simulation.

[0199] In summary, the electrical equipment virtual debugging system provided by this application, and the method for determining the data exchange priority therein, can improve the performance of the electrical equipment virtual debugging system based on digital twins and solve the problem of multi-physics field coupling in electrical equipment. Specifically, by integrating a multi-physics field coupling simulation platform, real-time data acquisition and analysis, intelligent optimization algorithms and efficient computing technology, a flexible and scalable system architecture is provided to ensure that the interaction between multiple physical fields can be accurately reflected during the design, debugging, monitoring and optimization of the equipment. In addition, this application classifies cross-module data through spatial gradient color identification, so as to dynamically adjust the priority of data exchange according to the real-time nature, priority and importance of the data. For example, real-time data is represented by red and historical data is represented by blue, which helps the system reduce unnecessary cross-module data exchange during the multi-physics field coupling simulation process and optimize computing resources and data transmission efficiency.

[0200] Furthermore, the electrical equipment virtual debugging system provided by this application, and the method for determining data exchange priority therein, have the following four beneficial effects:

[0201] First, by employing dedicated physics models and solvers, each physical field (electromagnetic, thermal, mechanical, fluid, etc.) can be accurately simulated based on its specific characteristics. The electromagnetic field uses Maxwell's equations and Poynting's theorem, the thermal field uses the heat conduction and convection equations, the mechanical field uses an elasticity solver, and the fluid field relies on a fluid dynamics model. The application of these targeted solvers improves the coupling accuracy between the various physical fields, ensuring that the interactions between multiple physical fields during the simulation process are accurately reflected. The coordination algorithm effectively handles the coupling between the various physical fields and ensures that the simulation steps of each module are synchronized. By optimizing the calculation steps for different physical fields, time lags or inconsistencies in the calculations of each physical field are avoided, improving simulation efficiency and accuracy.

[0202] Secondly, traditional data exchange mechanisms (such as shared memory, message queues, and databases) often face synchronization issues, latency problems, and performance bottlenecks, especially in high-concurrency environments. Shared memory can lead to access conflicts between multiple processes or threads, message queues suffer from reduced efficiency at high concurrency, and database read and write speeds are slow. In this technical solution, cross-module data is dynamically categorized based on timeliness, priority, and module requirements through spatially gradient color identification, reducing unnecessary data exchange and significantly improving data transmission efficiency.

[0203] Third, color gradients can be used to indicate the different priorities and importance of data. For example, real-time data might be marked in red, indicating high-priority information for transmission; while historical data might be marked in blue, indicating a lower priority and reducing its consumption of system resources. This approach allows for efficient allocation of computing resources and network bandwidth, avoiding wasted time and computing power on unnecessary data exchange.

[0204] Fourth, during multi-physics simulations, the calculation results of each physical field affect the states of other physical fields. Therefore, the data exchange layer is responsible for ensuring the synchronization and consistency of parameters (such as electric field intensity, temperature, and stress) between different physical fields. Through a unified data format and standardized interfaces, calculation errors and deviations in simulation results caused by inconsistent data can be avoided.

[0205] It should be understood that, although the various steps in the flowcharts involved in the various embodiments described above are displayed in sequence according to the instructions of the arrows, these steps are not necessarily executed in sequence in the order indicated by the arrows. Unless otherwise specified herein, there is no strict order restriction on the execution of these steps, and these steps can be executed in other orders. Moreover, at least a portion of the steps in the flowcharts involved in the various embodiments described above can include multiple steps or multiple stages, and these steps or stages are not necessarily executed and completed at the same time, but can be executed at different times, and the execution order of these steps or stages is not necessarily to be carried out in sequence, but can be executed in turn or alternately with other steps or at least a portion of steps or stages in other steps.

[0206] Based on the same inventive concept, embodiments of the present application also provide a device for determining data exchange priority in an electrical equipment virtual debugging system, which is used to implement the aforementioned method for determining data exchange priority in the electrical equipment virtual debugging system. The solution provided by this device is similar to the solution described in the aforementioned method. Therefore, the specific limitations of one or more embodiments of the device for determining data exchange priority in an electrical equipment virtual debugging system provided below can be found in the aforementioned limitations of the method for determining data exchange priority in the electrical equipment virtual debugging system, and will not be repeated here.

[0207] In an exemplary embodiment, Figure 10 As shown, a device 80 for determining data exchange priority in an electrical equipment virtual debugging system is provided, comprising: a data acquisition module 81, a color identification determination module 82, and a priority determination module 83, wherein:

[0208] The data acquisition module 81 is used to acquire multiple target physical field data in the electrical equipment virtual debugging system and extract characteristic information of each target physical field data; the characteristic information includes at least one characteristic type of the data such as real-time performance, priority, importance, and parameter value;

[0209] A color identification determination module 82 is configured to determine a color identification of each target physical field data based on at least one of the feature information and the real-time data requirements of the electrical equipment virtual commissioning system; the color identification includes at least one of a color type and a color gradient;

[0210] The priority determination module 83 is used to determine the data exchange priority of each target physical field data based on the color identification.

[0211] In an exemplary embodiment, the color identification determination module 82 is used to determine the color identification of each target physical field data based on the feature information, specifically for: comparing the characteristic value of the feature information of each target physical field data with the size of a preset feature threshold; wherein the preset feature threshold includes at least one sub-feature threshold; when the characteristic value of the target physical field data is greater than or equal to the first sub-feature threshold, the color identification of the target physical field data is determined to be a first color type; when the characteristic value of the target physical field data is greater than or equal to the second sub-feature threshold and less than the first sub-feature threshold, the color identification of the target physical field data is determined to be a second color type; when the characteristic value of the target physical field data is greater than or equal to the third sub-feature threshold and less than the second sub-feature threshold, the color identification of the target physical field data is determined to be a third color type; when the characteristic value of the target physical field data is less than the third sub-feature threshold, the color identification of the target physical field data is determined to be a fourth color type; wherein the first color type, the second color type, the third color type and the fourth color type are arranged clockwise in the hue wheel, or the first color type, the second color type, the third color type and the fourth color type are arranged counterclockwise in the hue wheel.

[0212] In an exemplary embodiment, the color identification determination module 82 is used to determine the color identification of each target physical field data based on the feature information, specifically for: obtaining the standardized value within a preset range corresponding to each feature type of each feature information, and the weight corresponding to each feature type; determining the comprehensive weight of each feature information based on the standardized value and weight of each feature type; determining the color type of the corresponding target physical field data based on the size of each comprehensive weight; wherein, as the comprehensive weight increases successively, the color type is arranged clockwise or counterclockwise in the hue wheel.

[0213] In an exemplary embodiment, the color identification determination module 82 is used to determine the color identification of each target physical field data based on the feature information, specifically for: obtaining the standardized value within a preset range corresponding to each feature type of each feature information, and the weight corresponding to each feature type; determining the comprehensive weight of each feature information based on the standardized value and weight of each feature type; determining the color value corresponding to each comprehensive weight based on a preset color mapping function, and converting the color value into an RGB value; determining the color type of the corresponding target physical field data based on each RGB value.

[0214] In an exemplary embodiment, the color identification determination module 82 is used to determine the color identification of each target physical field data based on the real-time data requirements of the electrical equipment virtual debugging system, specifically: when the target physical field data belongs to the data required by real-time data, determine the color identification of the target physical field data as the first color type; when the target physical field data does not belong to the data required by real-time data, determine the color identification of the target physical field data as the second color type.

[0215] In an exemplary embodiment, the color identification determination module 82 is also used to obtain the parameter value size of the target physical field data having the same data type in the target physical field data belonging to the same color type; the data type includes electrical parameters, temperature data, vibration data and airflow data; the color gradient of the corresponding target physical field data is determined based on the parameter value size; wherein, as the parameter value size increases successively, the color gradient increases or decreases successively.

[0216] In an exemplary embodiment, the color identification determination module 82 is used to determine the color identification of each target physical field data based on characteristic information, specifically for: obtaining the parameter value size of the target physical field data with the same data type; the data type includes electrical parameters, temperature data, vibration data and airflow data; for the target physical field data of the same data type, determining the color gradient of the corresponding target physical field data based on the parameter value size; wherein, as the parameter value size increases successively, the color gradient increases or decreases successively.

[0217] In an exemplary embodiment, the color identification determination module 82 is further configured to determine the color type of the target physical field data based on the data type of the target physical field data.

[0218] In an exemplary embodiment, the priority determination module 83 is used to determine the data exchange priority of each target physical field data based on color identification, specifically: as the color type of the target physical field data corresponds to the clockwise arrangement in the hue wheel, the data exchange priority of the target physical field data increases or decreases successively; as the color gradient of the target physical field data increases successively, the data exchange priority of the target physical field data increases or decreases successively.

[0219] Each module in the apparatus for determining data exchange priority in the aforementioned electrical equipment virtual commissioning system may be implemented in whole or in part via software, hardware, or a combination thereof. Each module may be embedded in or independent of a processor in a computer device in the form of hardware, or may be stored in a computer device memory in the form of software, so that the processor can call and execute the corresponding operations of each module.

[0220] In an exemplary embodiment, a computer device is provided. The computer device may be a terminal, and its internal structure diagram may be as shown in FIG. Figure 11 As shown. The computer device includes a processor, memory, an input / output interface, a communication interface, a display unit, and an input device. The processor, memory, and input / output interface are connected via a system bus, and the communication interface, display unit, and input device are connected to the system bus via the input / output interface. The processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and internal memory. The non-volatile storage medium stores an operating system and computer programs. The internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage medium. The input / output interface of the computer device is used to exchange information between the processor and external devices. The communication interface of the computer device is used to communicate with external terminals via wired or wireless communication, and the wireless communication can be achieved via Wi-Fi, a mobile cellular network, near-field communication (NFC), or other technologies. When executed by the processor, the computer program implements a method for determining data exchange priority in a virtual debugging system for electrical equipment. The display unit of the computer device is used to produce a visually visible image and can be a display screen, a projection device, or a virtual reality imaging device. The display screen can be a liquid crystal display screen or an electronic ink display screen, and the input device of the computer device can be a touch layer covering the display screen, or a button, trackball or touchpad set on the computer device casing, or an external keyboard, touchpad or mouse.

[0221] Those skilled in the art will understand that Figure 11 The structure shown in the figure is only a block diagram of a part of the structure related to the solution of the present application, and does not constitute a limitation on the computer device to which the solution of the present application is applied. The specific computer device may include more or fewer components than shown in the figure, or combine certain components, or have a different component arrangement.

[0222] In an exemplary embodiment, a computer device is provided, including a memory and a processor. The memory stores a computer program, and when the processor executes the computer program, it implements the steps of the method for determining data exchange priority in the electrical equipment virtual debugging system provided in the present application.

[0223] In an exemplary embodiment, a computer-readable storage medium is provided, on which a computer program is stored. When the computer program is executed by a processor, the steps of the method for determining data exchange priority in the electrical equipment virtual debugging system provided in the present application are implemented.

[0224] In an exemplary embodiment, a computer program product is provided, including a computer program. When the computer program is executed by a processor, the computer program implements the steps of the method for determining data exchange priority in the electrical equipment virtual debugging system provided in the present application.

[0225] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, stored data, displayed data, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties, and the collection, use and processing of relevant data must comply with relevant regulations.

[0226] Those skilled in the art will understand that all or part of the processes in the above-mentioned embodiments can be implemented by instructing the relevant hardware through a computer program. The computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. In particular, any reference to memory, database, or other media used in the embodiments provided in this application can include at least one of non-volatile memory and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM can take various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM). The databases involved in the various embodiments provided herein may include at least one of a relational database and a non-relational database. Non-relational databases may include, but are not limited to, blockchain-based distributed databases. The processors involved in the various embodiments provided herein may be, but are not limited to, general-purpose processors, central processing units (CPUs), graphics processing units (GPUs), digital signal processors (DSPs), programmable logic devices (PLDs), quantum computing-based data processing logic devices, artificial intelligence (AI) processors, and the like.

[0227] The technical features of the above embodiments can be combined arbitrarily. In order to make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this application.

[0228] The above-described embodiments merely represent several implementation methods of the present application. While the descriptions are relatively specific and detailed, they should not be construed as limiting the scope of the present application. It should be noted that a person of ordinary skill in the art may make various modifications and improvements without departing from the spirit of the present application, and these modifications and improvements fall within the scope of protection of the present application. Therefore, the scope of protection of the present application shall be determined by the appended claims.

Claims

1. A method for determining data exchange priority in an electrical equipment virtual debugging system, characterized in that: The method comprises: Acquire multiple target physical field data in the electrical equipment virtual debugging system, and extract characteristic information of each target physical field data; the characteristic information includes at least one characteristic type of the data's real-time performance, priority, importance, and parameter value; Determining a color identification of each target physical field data based on at least one of the characteristic information and the real-time data requirement of the electrical equipment virtual debugging system; wherein the color identification includes at least one of a color type and a color gradient; Determining the data exchange priority of each target physical field data based on the color identifier includes: as the color type of the target physical field data corresponds to the clockwise arrangement in the hue wheel, the data exchange priority of the target physical field data increases or decreases in sequence; and / or as the color gradient of the target physical field data increases in sequence, the data exchange priority of the target physical field data increases or decreases in sequence; The method for determining the color identification of each target physical field data based on the characteristic information includes: Obtaining a normalized value within a preset range corresponding to each feature type of each feature information, and a weight corresponding to each feature type; and determining a comprehensive weight of each feature information based on the normalized value and the weight of each feature type; Determining the color type of the corresponding target physical field data based on the size of each comprehensive weight; wherein, as the comprehensive weight increases successively, the color types are arranged clockwise or counterclockwise in the hue circle; or, The color value corresponding to each of the comprehensive weights is determined based on a preset color mapping function, and the color value is converted into an RGB value; and the color type of the corresponding target physical field data is determined based on each of the RGB values.

2. The method according to claim 1, characterized in that The determining the color identification of each target physical field data based on the characteristic information includes: Comparing the characteristic value of the characteristic information of each target physical field data with a preset characteristic threshold; wherein the preset characteristic threshold includes at least one sub-characteristic threshold; When the characteristic value of the target physical field data is greater than or equal to a first sub-characteristic threshold, determining that the color identification of the target physical field data is a first color type; When the characteristic value of the target physical field data is greater than or equal to the second sub-feature threshold and less than the first sub-feature threshold, determining that the color identification of the target physical field data is a second color type; When the characteristic value of the target physical field data is greater than or equal to the third sub-feature threshold and less than the second sub-feature threshold, determining that the color identification of the target physical field data is a third color type; When the characteristic value of the target physical field data is less than the third sub-characteristic threshold, determining that the color identification of the target physical field data is a fourth color type; The first color type, the second color type, the third color type, and the fourth color type are arranged clockwise in the hue wheel, or the first color type, the second color type, the third color type, and the fourth color type are arranged counterclockwise in the hue wheel.

3. The method according to claim 1, characterized in that Determining the color identification of each target physical field data based on the real-time data requirements of the electrical equipment virtual debugging system includes: In a case where the target physical field data belongs to the data required by the real-time data, determining that the color identification of the target physical field data is a first color type; In a case where the target physical field data does not belong to the data required by the real-time data, the color identification of the target physical field data is determined to be a second color type.

4. The method according to any one of claims 1 to 3, characterized in that Also includes: In the target physical field data belonging to the same color type, obtaining the parameter value of the target physical field data having the same data type; the data type includes electrical parameters, temperature data, vibration data and airflow data; The color gradient of the corresponding target physical field data is determined based on the size of the parameter value; wherein, as the size of the parameter value increases successively, the color gradient increases or decreases successively.

5. The method according to claim 1, characterized in that The determining the color identification of each target physical field data based on the characteristic information includes: Acquiring the parameter values ​​of the target physical field data having the same data type; the data type includes electrical parameters, temperature data, vibration data, and airflow data; For the target physical field data of the same data type, the color gradient of the corresponding target physical field data is determined based on the size of the parameter value; wherein, as the size of the parameter value increases successively, the color gradient increases or decreases successively.

6. The method according to claim 5, characterized in that Also includes: The color type of the target physical field data is determined based on the data type of the target physical field data.

7. A virtual debugging system for electrical equipment, characterized in that: It includes a physical field model module and a data management and exchange layer; the physical field models in the physical field model module include electromagnetic field model, thermal field model, mechanical field model and fluid field model; The data management and exchange layer is used to realize the transmission of each target physical field data between multiple physical field models based on the data exchange priority of each target physical field data in the physical field model module; The data exchange priority of the target physical field data is determined by the method for determining the data exchange priority in the electrical equipment virtual debugging system according to any one of claims 1 to 6.

8. A device for determining data exchange priority in a virtual debugging system for electrical equipment, characterized in that: include: A data acquisition module is used to acquire multiple target physical field data in the electrical equipment virtual debugging system and extract feature information of each target physical field data; The characteristic information includes at least one characteristic type of the data, such as real-time performance, priority, importance, and parameter value; a color identification determination module, configured to determine a color identification of each target physical field data based on at least one of the characteristic information and a real-time data requirement of the electrical equipment virtual commissioning system; the color identification including at least one of a color type and a color gradient; a priority determination module, configured to determine the data exchange priority of each target physical field data based on the color identifier, including: as the color type of the target physical field data corresponds to the clockwise arrangement in the hue wheel, the data exchange priority of the target physical field data increases or decreases in sequence; and / or as the color gradient of the target physical field data increases in sequence, the data exchange priority of the target physical field data increases or decreases in sequence; The method in which the color identification determination module is used to determine the color identification of each target physical field data based on the characteristic information includes: Obtaining a normalized value within a preset range corresponding to each feature type of each feature information, and a weight corresponding to each feature type; and determining a comprehensive weight of each feature information based on the normalized value and the weight of each feature type; Determining the color type of the corresponding target physical field data based on the size of each comprehensive weight; wherein, as the comprehensive weight increases successively, the color types are arranged clockwise or counterclockwise in the hue circle; or, The color value corresponding to each of the comprehensive weights is determined based on a preset color mapping function, and the color value is converted into an RGB value; and the color type of the corresponding target physical field data is determined based on each of the RGB values.

9. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 6 are implemented.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 6 are implemented.

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