Data risk evaluation system and method based on visual model

Abstract

The invention discloses a data risk evaluation system and method based on a visual model. The system comprises a numerical value acquisition end analysis module, a numerical value acquisition end transmission module, a cloud platform end numerical value receiving module and a cloud platform end numerical value transmission risk evaluation module. Characteristics of each piece of subclass item information are expressed by means of a numerical value characteristic chart at a numerical value acquisition end, the numerical value characteristic chart cannot be illegally changed in a data sending process, and then the numerical value characteristic chart is compared with received numerical value information at a cloud platform end. Whether each piece of subclass item information is illegally changed in the sending process or not is judged, so that it is ensured that high-efficiency risk evaluation can be conducted when collected data needing to provide input indexes in a thermal power generating unit performance model are transmitted to a cloud platform end; and then the information transmission process is perfected and improved in a deeper level.

Description

Technical Field

[0001] The invention discloses a data risk assessment system and method based on a visualization model, belonging to the field of information security control. Background Art

[0002] Thermal power performance calculation is an effective means to evaluate and analyze boiler performance and thermal economy of thermal power units. The design of the scheme generally follows the standards of GB / T10184-2015 "Power Station Boiler Performance Test Procedure" and DL / T904-2015 "Calculation Method of Technical and Economic Indicators of Thermal Power Plants". At present, thermal power performance calculation often uses time series database to manage calculation indicators, but because the actual thermal power performance calculation based on the visualization model needs to include many types of data and is complex, there is a possibility that the data will be illegally modified during the transmission process, and the data security risk index will increase sharply. If the data error cannot be discovered in time, the wrong data will be calculated. If it is a non-important parameter, the overall result will have little impact, but if it is key data, it will have a great impact on the final result, and then the accuracy of thermal power performance calculation is low, which will also affect the subsequent production and life.

[0003] Therefore, the present invention provides a data risk assessment system and method based on a visualization model. Summary of the invention

[0004] In order to solve the deficiencies in the prior art, the present invention provides a data risk assessment system and method based on a visualization model, which can ensure that the collected data required to provide input indicators in the thermal power unit performance model can be efficiently risk assessed when transmitted to the cloud platform, and then the information transmission process can be improved at a deeper level.

[0005] The present invention adopts the following technical solution.

[0006] On one hand, the present invention provides a data risk assessment system based on a visualization model, comprising: a numerical data collection end analysis module, a numerical data collection end transmission module, a cloud platform end numerical data receiving module, and a cloud platform end numerical data transmission risk assessment module;

[0007] The numerical acquisition end analysis module is used to provide data of input indicators in the thermal power unit performance model, and group the data provided for the input indicators into different categories to obtain a number of information messages, thereby forming a numerical feature chart;

[0008] The transmission module of the numerical value collection end is used to synchronously transmit a plurality of information messages containing embedded class item identifiers and numerical value characteristic charts to the numerical value receiving module of the cloud platform end;

[0009] The cloud platform-side numerical value receiving module is used to synchronously receive a number of information messages and numerical value feature charts containing embedded class item identifiers, then decompress and restore the information messages, and then send the restored numerical value information and numerical value feature charts to the cloud platform-side numerical value transmission risk assessment module;

[0010] The cloud platform-side numerical transmission risk assessment module is used to receive the restored numerical information and numerical characteristic charts, and then assess and inspect the risk of this numerical transmission based on the restored numerical information and numerical characteristic charts, so as to determine whether there is a risk in the transmission of this numerical information, that is, to determine whether all sub-category information has been illegally changed.

[0011] Preferably, the numerical value collection end analysis module includes a numerical value information grouping component, a numerical value quantity collection component, a numerical value information reduction component, and a numerical feature chart forming component;

[0012] The numerical information grouping component is used to divide the data of the input indicators provided to the thermal power unit performance model into three general categories according to the acquisition source of the numerical information, and each general category includes three sub-category information;

[0013] The numerical quantity collection component is used to collect the numerical quantities of all sub-category information that needs to be transmitted, and is abbreviated as T s,t , specifically, s is the total category number to which each sub-category item information belongs, and t is the sub-category item number of each sub-category item information;

[0014] The numerical decrement component performs a decrement operation on all sub-category item information to obtain a number of information messages that need to be transmitted, and adds embedded category item identifiers to the several information messages;

[0015] The numerical feature chart forming component is used to construct a numerical feature chart according to the numerical value of each sub-category item information, which is recorded as JPG.

[0016] Preferably, in the numerical characteristic chart forming component, the workflow is:

[0017] S1-1: Get the numerical value T of each sub-category information based on different collection sources s,t ;

[0018] S1-2: Based on the numerical value T of each sub-category information s,t The byte number in the format chart within the pre-set area size is filled with pixels corresponding to the pre-set color value, and the corresponding pixels are recorded as px values;

[0019] S1-3: After each unit cell is filled with the px value corresponding to the color value, a numerical feature chart JPG is obtained, the attribute of the numerical feature chart is set to be read-only and non-overwriteable, and the numerical feature chart JPG is transmitted to the numerical acquisition end transmission module.

[0020] Preferably, in step S1-2, the filling workflow is:

[0021] S1-2-1: The number of cells in the pre-set area size 3*3 format chart is 9, presented in a chart with three rows and three columns, and the numerical value of each sub-category item information is obtained in order T s,t The number of bytes in is denoted as B ,t ;

[0022] S1-2-2: byte number B 1,1 Add the corresponding px value to the unit cell in row 1 and column 1 of the chart, and replace the byte number B 1,2 Add the corresponding px value to the unit grid in row 1 and column 2 of the chart, and replace the byte number B 1,3 Add the corresponding px value to the unit grid in row 1 and column 3 of the chart; 2,1 Add the corresponding px value to the unit cell in row 2 and column 1 in the chart, and replace the byte number B 2,2 Add the corresponding px value to the unit grid in row 2 and column 2 of the chart, and replace the byte number B 2,3 Add the corresponding px value to the unit grid in row 2 and column 3 of the chart; 3,1 Add the corresponding px value to the unit cell in row 3 and column 1 in the chart, and replace the byte number B 3,2 Add the corresponding px value to the unit grid in row 3, column 2 in the chart, and replace the byte number B 3,3 The corresponding px value is added to the unit cell in row 3 and column 3 of the chart.

[0023] Preferably, in step S1-2-2, the order in which px corresponding to the byte number is added to the unit cells in the format chart within the pre-set area size of 3*3 is from top to bottom row by row, and the unit cells in each row are filled with px values ​​from left to right, and 1 byte corresponds to one px value in the corresponding unit cell.

[0024] Preferably, the numerical value collection end transmission module includes a numerical value receiving component and a numerical value information synchronous transmission component;

[0025] The numerical value receiving component is used to receive a plurality of information messages containing embedded category item identifiers transmitted from the numerical information reduction component and a numerical feature chart constructed by the numerical feature chart forming component according to the numerical value of each subcategory item information;

[0026] The numerical information synchronous transmission component is used to synchronously transmit a number of information messages containing embedded class item identifiers and numerical feature charts to the cloud platform-side numerical receiving module via multiple communication links.

[0027] Preferably, the cloud platform-side numerical value receiving module includes a numerical information synchronous receiving component, a recovery component, and a numerical information transmission component;

[0028] The numerical information synchronous receiving component is used to synchronously receive a plurality of information messages and numerical characteristic charts containing embedded class item identifiers via a plurality of communication links;

[0029] The recovery component is used to decompress and recover a plurality of information messages containing embedded category item identifiers to obtain a plurality of subcategory item information and corresponding embedded category item identifiers;

[0030] The numerical information transmission component is used to send the restored sub-category item information and the corresponding embedded category item identification and numerical feature chart to the cloud platform-side numerical transmission risk assessment module.

[0031] Preferably, the cloud platform-side numerical transmission risk assessment module includes an information receiving component, a numerical quantity extraction component, and a transmission risk assessment component;

[0032] The information receiving component is used to receive the restored information of several sub-category items and the corresponding embedded category item identifiers and numerical feature charts;

[0033] The numerical value extraction component is used to extract the numerical values ​​of the restored sub-category information, and the obtained numerical values ​​are recorded as W s,t Specifically, s is the total category number to which each sub-category information belongs, t is the sub-category number of each sub-category information, and the total category number and sub-category number of the corresponding numerical information are obtained according to the embedded category identifier;

[0034] The transmission risk assessment component is used to compare the extracted and restored numerical values ​​of several sub-category item information with the numerical characteristic chart, so as to determine whether there is a risk in the current numerical transmission, that is, to determine whether all sub-category item information has been illegally changed.

[0035] Preferably, the workflow of the transmission risk assessment component is:

[0036] S2-1: Extract the numerical value W of several restored sub-category information s,t ;

[0037] S2-2: Read the pixels of the numerical feature chart based on the order of the chart rows and columns using the functions and methods provided by the Scipy, PIL, NumPy and Matplotlib data analysis libraries, and extract the pixel points corresponding to the color values ​​pre-filled in each unit cell in the numerical feature chart JPG, that is, the px value, recorded as P s,t , specifically, s and t represent the row and column numbers of the unit grid respectively, that is, s is the total category number to which each sub-category information belongs, and t is the sub-category number of each sub-category information;

[0038] S2-3: The px value of each unit cell is P s,t Sequentially and W s,t In comparison, if the pixel position P s,t and numerical value W s,t When the comparison results are inconsistent, it means that the corresponding sub-category item information has been illegally changed during the transmission process. On the contrary, if the comparison results are consistent, the risk index during the transmission process is low and there is no illegal change.

[0039] The present invention also provides a risk assessment method for a data risk assessment system based on a visualization model, comprising the following steps:

[0040] Step 1: Group the data provided to the input indicator into different categories to obtain several information messages, and add embedded category item identifiers to the several information messages, thereby forming a numerical feature chart;

[0041] Step 2: A number of information messages containing embedded class item identifiers and numerical feature charts are synchronously transmitted to the numerical receiving module on the cloud platform;

[0042] Step 3: Synchronously receive several information messages and numerical feature charts containing embedded class item identifiers, then decompress and restore the information messages, and then send the restored numerical information and numerical feature charts to the numerical transmission risk assessment module on the cloud platform;

[0043] Step 4: Receive the restored numerical information and numerical characteristic chart, and then evaluate and calibrate the risk of this numerical transmission based on the restored numerical information and numerical characteristic chart, so as to determine whether there is a risk in this numerical transmission, that is, to determine whether all sub-category information has been illegally changed.

[0044] The beneficial effect of the present invention lies in that, compared with the prior art, the data risk assessment system based on a visualization model described in the present invention represents the characteristics of each sub-category item information by means of a numerical feature chart at the numerical collection end, and the numerical feature chart cannot be illegally modified in the data sending process. Then, the cloud platform end compares the numerical feature chart with the received numerical information to determine whether each sub-category item information has been illegally modified in the sending process, thereby ensuring that the collected data that needs to provide input indicators in the thermal power unit performance model can be efficiently risk assessed when transmitted to the cloud platform end, and then the information transmission process is improved at a deeper level. At the same time, according to the above-mentioned work flow, risk assessment is also performed on the collected sub-category information, and then based on the risk assessment, it is determined whether the information of each sub-category can be reliably and safely stored on the cloud platform. If there is illegal modification of a sub-category information, it will be determined that there is a risk and security, which will prevent the data from being stored on the cloud platform. Then other methods will be used to retrieve the sub-type information, ensuring that the data providing the input indicators in the thermal power unit performance model are reliable and accurate data information, thereby improving the efficiency of creating a visualization model and reducing the difficulty of establishing a visualization model. BRIEF DESCRIPTION OF THE DRAWINGS

[0045] Figure 1 It is a working schematic diagram of a data risk assessment system and method based on a visualization model in an embodiment of the present invention;

[0046] Figure 2 This is a format chart with an area size of 3*3 used in the embodiment of the present invention. DETAILED DESCRIPTION

[0047] In order to make the purpose, technical scheme and advantages of the present invention clearer, the technical scheme of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. The embodiments described in this application are only part of the embodiments of the present invention, not all of them. Based on the spirit of the present invention, other embodiments obtained by ordinary technicians in this field without creative work are all within the scope of protection of the present invention.

[0048] like Figure 1 to Figure 2 As shown, Embodiment 1 of the present invention discloses a data risk assessment system based on a visualization model, including a numerical value collection end analysis module, a numerical value collection end transmission module, a cloud platform end numerical value receiving module, and a cloud platform end numerical value transmission risk assessment module;

[0049] In an embodiment of the present invention, the numerical acquisition end analysis module is used to provide data of input indicators in the thermal power unit performance model, and group the data provided for the input indicators into different categories to obtain a number of information messages, thereby forming a numerical feature chart.

[0050] Furthermore, the numerical acquisition end analysis module includes a numerical information grouping component, a numerical quantity acquisition component, a numerical information reduction component, and a numerical feature chart forming component; the numerical information grouping component is used to divide the data of the input indicators provided to the thermal power unit performance model into three general categories according to the acquisition source of the numerical information, and each general category includes three sub-category information; the numerical quantity acquisition component is used to collect the numerical quantities of all sub-category information that need to be transmitted, and is abbreviated as T s,t Specifically, s is the total category number to which each sub-category item information belongs, and t is the sub-category item number of each sub-category item information; the numerical decrement component performs a decrement operation on all sub-category item information to obtain a number of information messages that need to be transmitted, and at the same time adds an embedded category item identifier to the several information messages, and then transmits the several information messages containing the embedded category item identifier to the numerical acquisition end transmission module; the numerical feature chart forming component is used to construct a numerical feature chart according to the numerical value of each sub-category item information, recorded as JPG, and then transmits the numerical feature chart to the numerical acquisition end transmission module. At the numerical collection end, the characteristics of each sub-category item information are represented by a numerical feature chart, which cannot be illegally modified during the data transmission process. Then, at the cloud platform end, the numerical feature chart is compared with the received numerical information to determine whether each sub-category item information has been illegally modified during the transmission process. This ensures that the collected data required to provide input indicators in the thermal power unit performance model can be efficiently risk assessed when transmitted to the cloud platform end, and then the information transmission process can be improved at a deeper level.

[0051] To further explain, data collection provides data for input indicators of the model, and data collection has three sources. Data collected in real time by measuring points, such as real-time load, main steam temperature, main steam flow and other measuring points; manually reported data is usually data that cannot be collected by measuring points, and is reported by professionals after testing or meter reading, such as slag combustibles, coal quality coefficient, boiler pressure, auxiliary power consumption (when no collection is done); third-party collected data is provided by a third-party system, and data is obtained through the network interface opened by the other party, which can make up for the defects of manual reporting that requires manual intervention to a certain extent, such as auxiliary power consumption, voltage and current can be obtained from the interface provided by the power collection system.

[0052] Therefore, since the actual thermal power performance calculation based on the visualization model needs to include many and complex data types, only 9 parameters are taken in this implementation, which are divided into three categories according to different data sources. In the implementation of the present invention, in the numerical information grouping component, the input index data in the thermal power unit performance model is divided into three general categories, each general category includes three sub-category information, the first general category includes three sub-category information, specifically including real-time load, main steam temperature, main steam flow, the second general category includes three sub-category information, specifically including slag combustibles, coal quality coefficient, boiler pressure, the third general category includes three sub-category information, specifically including auxiliary power consumption, voltage and current, which is only the embodiment used in the present invention, and can be selected according to actual conditions.

[0053] To further explain, the embedded category item identifier includes the general category item and sub-category item of the corresponding numerical information. For example, if the embedded category item identifier is "22", it means that the numerical information is the second sub-category item information under the second general category item, that is, the coal slag coefficient. Based on this example, the meaning of other embedded category item identifiers can be obtained.

[0054] The present invention further illustrates that in the numerical characteristic chart forming component, the workflow is:

[0055] S1-1: Get the numerical value T of each sub-category information based on different collection sources s,t ;

[0056] S1-2: Based on the numerical value T of each sub-category information s,t The byte number in the format chart within the pre-set area size is filled with pixels corresponding to the pre-set color value, and the corresponding pixels are recorded as px values;

[0057] S1-3: After each unit cell is filled with the px value corresponding to the color value, a numerical feature chart JPG is obtained, and the numerical feature chart JPG is transmitted to the numerical acquisition end transmission module.

[0058] The present invention further illustrates that in step S1-2, the workflow of filling is:

[0059] S1-2-1: The number of cells in the pre-set area format chart is 9, and it is presented in a chart with three rows and three columns. The numerical value of each sub-category item information is obtained in order T s,t The number of bytes in is denoted as B s,t ;

[0060] S1-2-2: byte number B 1,1 Add the corresponding px value to the unit cell in row 1 and column 1 of the chart, and replace the byte number B 1,2 Add the corresponding px value to the unit grid in row 1 and column 2 of the chart, and replace the byte number B1,3 Add the corresponding px value to the unit grid in row 1 and column 3 of the chart; 2,1 Add the corresponding px value to the unit cell in row 2 and column 1 in the chart, and replace the byte number B 2,2 Add the corresponding px value to the unit grid in row 2 and column 2 of the chart, and replace the byte number B 2,3 Add the corresponding px value to the unit grid in row 2 and column 3 of the chart; 3,1 Add the corresponding px value to the unit cell in row 3 and column 1 in the chart, and replace the byte number B 3,2 Add the corresponding px value to the unit grid in row 3, column 2 in the chart, and replace the byte number B 3,3 The corresponding px value is added to the unit cell in row 3 and column 3 of the chart.

[0061] It is further supplemented in the implementation of the present invention that in the step S1-2-2, the order in which the px corresponding to the byte number is added to the unit grid in the format chart within the pre-set area size of 3*3 is from top to bottom row by row, and the unit grid of each row is filled with px values ​​from left to right, and at the same time, 1 byte corresponds to one px value in the corresponding unit grid.

[0062] It is further supplemented in the implementation of the present invention that in the step S1-3, after each unit cell is completely filled, a numerical characteristic chart of a 3*3 area size is formed, and the attribute of the numerical characteristic chart is set to read-only and non-overwritable to ensure that it will not be illegally rewritten during the transmission workflow.

[0063] Further supplement, according to the numerical value T of each sub-category item information s,t The byte number in the format chart within the pre-set area size is filled with pixels corresponding to the pre-set color value. The pre-set color can be selected according to experimental needs and habits. In the implementation of the present invention, non-black blocks such as red, green and blue can be selected.

[0064] It is further supplemented that the format chart within the pre-set area size selects white as the background color, and the table lines that constitute the chart are black.

[0065] In the implementation of the present invention, the transmission module at the value collection end is used to synchronously transmit a number of information messages containing embedded class item identifiers and value feature charts to the value receiving module at the cloud platform end.

[0066] The present invention further illustrates that the transmission module at the numerical acquisition end includes a numerical receiving component and a numerical information synchronous transmission component; the numerical receiving component is used to receive a plurality of information messages containing embedded class item identifiers transmitted from a numerical information reduction component and a numerical feature chart constructed according to the numerical quantity of each sub-class item information from a numerical feature chart forming component; the numerical information synchronous transmission component is used to synchronously transmit a plurality of information messages containing embedded class item identifiers and numerical feature charts to the numerical receiving module at the cloud platform end via multiple communication links.

[0067] In the implementation of the present invention, the cloud platform-side numerical receiving module is used to synchronously receive a number of information messages and numerical feature charts containing embedded class item identifiers, then decompress and restore the information messages, and then send the restored numerical information and numerical feature charts to the cloud platform-side numerical transmission risk assessment module.

[0068] The present invention further illustrates that the cloud platform-side numerical value receiving module includes a numerical information synchronous receiving component, a recovery component, and a numerical information transmission component; the numerical information synchronous receiving component is used to synchronously receive a number of information messages and numerical feature charts containing embedded class item identifiers via multiple communication links; the recovery component is used to decompress and restore the number of information messages containing embedded class item identifiers to obtain a number of sub-class item information and corresponding embedded class item identifiers; the numerical information transmission component is used to send the restored number of sub-class item information and corresponding embedded class item identifiers and numerical feature charts to the cloud platform-side numerical value transmission risk assessment module.

[0069] In the implementation of the present invention, the cloud platform-side numerical transmission risk assessment module is used to receive the restored numerical information and numerical characteristic charts, and then assess and inspect the risk of this numerical transmission based on the restored numerical information and numerical characteristic charts, so as to determine whether there is a risk in the current numerical information transmission, that is, to determine whether all sub-category information has been illegally changed.

[0070] In the implementation of the present invention, it is further supplemented that the cloud platform-side numerical transmission risk assessment module includes an information receiving component, a numerical value extraction component, and a transmission risk assessment component; the information receiving component is used to receive the restored sub-category information and the corresponding embedded category identifier and numerical feature chart; the numerical value extraction component is used to extract the numerical value of the restored sub-category information, and the obtained numerical value is recorded as W s,tSpecifically, s is the total category number to which each sub-category information belongs, t is the sub-category number of each sub-category information, and the total category number and sub-category number of the corresponding numerical information are obtained according to the embedded category identifier; the transmission risk assessment component is used to compare the numerical quantities of several sub-category information after extraction and restoration with the numerical characteristic chart, so as to determine whether there is a risk in this numerical transmission, that is, to determine whether all sub-category information has been illegally changed.

[0071] In the implementation of the present invention, it is further supplemented that the workflow of the transmission risk assessment component is:

[0072] S2-1: Extract the numerical value W of several restored sub-category information s,t ;

[0073] S2-2: Read the pixels of the numerical feature chart based on the order of the chart rows and columns using the functions and methods provided by the Scipy, PIL, NumPy and Matplotlib data analysis libraries, and extract the pixel points corresponding to the color values ​​pre-filled in each unit cell in the numerical feature chart JPG, that is, the px value, recorded as P s,t , specifically, s and t represent the row and column numbers of the unit grid respectively, that is, s is the total category number to which each sub-category information belongs, and t is the sub-category number of each sub-category information;

[0074] S2-3: The px value of each unit cell is P s,t Sequentially and W s,t In comparison, if the pixel position P s,t and numerical value W s,t When the comparison results are inconsistent, it means that the corresponding sub-category item information has been illegally changed during the transmission process. On the contrary, if the comparison results are consistent, the risk index during the transmission process is low and there is no illegal change.

[0075] The present invention further illustrates that no matter what programming language is used, the official programming language will provide a corresponding image reading method, or a third-party image library can be found to read and process the image, such as Scipy and PIL libraries in Python, and the operating system will provide some image processing components, such as GDIPlus, etc. Or use OpenCV, which supports C++ and Python, and also has Java and C# packaging. The functions are the same, that is, after being packaged in different languages, there will be some subtle differences in subtleties such as method parameters, enumeration, etc., but the final idea of ​​image processing is still the same, and the specific language selection can be selected according to the actual situation.

[0076] The present invention further illustrates that the numerical feature chart cannot be illegally modified during the data sending process. Therefore, when the cloud platform receives the numerical feature chart, it can extract safe and reliable numerical characteristics, thereby eliminating the need to extract the numerical value itself in the subsequent transmission risk assessment, greatly reducing irrelevant calculations and improving the overall transmission and assessment efficiency.

[0077] Embodiment 2 of the present invention provides a risk assessment method for a data risk assessment system based on a visualization model as described in Embodiment 1, comprising the following steps:

[0078] Step 1: Group the data provided to the input indicator into different categories to obtain several information messages, and add embedded category item identifiers to the several information messages, thereby forming a numerical feature chart;

[0079] Step 2: A number of information messages containing embedded class item identifiers and numerical feature charts are synchronously transmitted to the numerical receiving module on the cloud platform;

[0080] Step 3: Synchronously receive several information messages and numerical feature charts containing embedded class item identifiers, then decompress and restore the information messages, and then send the restored numerical information and numerical feature charts to the numerical transmission risk assessment module on the cloud platform;

[0081] Step 4: Receive the restored numerical information and numerical characteristic chart, and then evaluate and calibrate the risk of this numerical transmission based on the restored numerical information and numerical characteristic chart, so as to determine whether there is a risk in this numerical transmission, that is, to determine whether all sub-category information has been illegally changed.

[0082] In summary, the data risk assessment system based on a visualization model described in the above embodiment represents the characteristics of each sub-category item information by means of a numerical feature chart at the numerical collection end. The numerical feature chart cannot be illegally modified in the data sending process. Then, the cloud platform end compares the numerical feature chart with the received numerical information to determine whether each sub-category item information has been illegally modified in the sending process, thereby ensuring that the collected data that needs to provide input indicators in the thermal power unit performance model can be efficiently risk assessed when transmitted to the cloud platform end, and then the information transmission process is improved at a deeper level. At the same time, according to the above-mentioned work flow, risk assessment is also performed on the collected sub-category information, and then based on the risk assessment, it is determined whether the information of each sub-category can be reliably and safely stored on the cloud platform. If there is illegal modification of a sub-category information, it will be determined that there is a risk and security, which will prevent the data from being stored on the cloud platform. Then other methods will be used to retrieve the sub-type information, ensuring that the data providing the input indicators in the thermal power unit performance model are reliable and accurate data information, thereby improving the efficiency of creating a visualization model and reducing the difficulty of establishing a visualization model.

[0083] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the above embodiments, ordinary technicians in the relevant field should understand that the specific implementation methods of the present invention can still be changed or replaced by equivalents, and any changes or equivalent replacements that do not depart from the spirit and scope of the present invention should be covered within the scope of protection of the claims of the present invention.

Claims

1. A data risk assessment system based on a visualization model, characterized in that: include: Numerical data collection end analysis module, numerical data collection end transmission module, cloud platform end numerical data receiving module, cloud platform end numerical data transmission risk assessment module; The numerical acquisition end analysis module is used to provide data of input indicators in the thermal power unit performance model, and group the data provided for the input indicators into different categories to obtain a number of information messages, thereby forming a numerical feature chart; The transmission module of the numerical value collection end is used to synchronously transmit a plurality of information messages containing embedded class item identifiers and numerical value characteristic charts to the numerical value receiving module of the cloud platform end; The cloud platform-side numerical value receiving module is used to synchronously receive a number of information messages and numerical value feature charts containing embedded class item identifiers, then decompress and restore the information messages, and then send the restored numerical value information and numerical value feature charts to the cloud platform-side numerical value transmission risk assessment module; The cloud platform-side numerical transmission risk assessment module is used to receive the restored numerical information and numerical characteristic charts, and then assess and inspect the risk of this numerical transmission based on the restored numerical information and numerical characteristic charts, so as to determine whether there is a risk in the transmission of this numerical information, that is, to determine whether all sub-category information has been illegally changed.

2. According to claim 1, a data risk assessment system based on a visualization model is characterized in that: The numerical value collection end analysis module includes a numerical value information grouping component, a numerical value quantity collection component, a numerical value information reduction component, and a numerical feature chart forming component; The numerical information grouping component is used to divide the data of the input indicators provided to the thermal power unit performance model into three general categories according to the acquisition source of the numerical information, and each general category includes three sub-category information; The numerical quantity acquisition component is used to collect the numerical quantities of all sub-category information that needs to be transmitted, and is abbreviated as T s,t , specifically, s is the total category number to which each sub-category item information belongs, and t is the sub-category item number of each sub-category item information; The numerical decrement component performs a decrement operation on all sub-category item information to obtain a number of information messages that need to be transmitted, and adds embedded category item identifiers to the several information messages; The numerical feature chart forming component is used to construct a numerical feature chart according to the numerical value of each sub-category item information, which is recorded as JPG.

3. According to the data risk assessment system based on visualization model in claim 2, it is characterized in that: In the numerical feature chart forming component, the workflow is: S1-1: Get the numerical value T of each sub-category information based on different collection sources s,t ; S1-2: Based on the numerical value T of each sub-category information s,t The byte number in the format chart within the pre-set area size is filled with pixels corresponding to the pre-set color value, and the corresponding pixels are recorded as px values; S1-3: After each unit cell is filled with the px value corresponding to the color value, a numerical feature chart JPG is obtained, the attribute of the numerical feature chart is set to be read-only and non-overwriteable, and the numerical feature chart JPG is transmitted to the numerical acquisition end transmission module.

4. A data risk assessment system based on a visualization model according to claim 3, characterized in that: In step S1-2, the filling workflow is: S1-2-1: The number of cells in the pre-set area format chart is 9, and it is presented in a chart with three rows and three columns. The numerical value of each sub-category item information is obtained in order T s,t The number of bytes in is denoted as B s,t ; S1-2-2: byte number B 1,1 Add the corresponding px value to the unit cell in row 1 and column 1 of the chart, and replace the byte number B 1,2 Add the corresponding px value to the unit grid in row 1 and column 2 of the chart, and replace the byte number B 1,3 Add the corresponding px value to the unit grid in row 1 and column 3 of the chart; 2,1 Add the corresponding px value to the unit cell in row 2 and column 1 in the chart, and replace the byte number B 2,2 Add the corresponding px value to the unit grid in row 2 and column 2 of the chart, and replace the byte number B 2,3 Add the corresponding px value to the unit grid in row 2 and column 3 of the chart; 3,1 Add the corresponding px value to the unit cell in row 3 and column 1 in the chart, and replace the byte number B 3,2 Add the corresponding px value to the unit grid in row 3, column 2 in the chart, and replace the byte number B 3,3 The corresponding px value is added to the unit cell in row 3 and column 3 of the chart.

5. The data risk assessment system based on a visualization model according to claim 4 is characterized in that: In the step S1-2-2, the order in which px corresponding to the byte number is added to the unit grid in the format chart within the pre-set area size of 3*3 is from top to bottom row by row, and the unit grid of each row is filled with px values ​​from left to right, and at the same time, 1 byte corresponds to one px value in the corresponding unit grid.

6. The data risk assessment system based on a visualization model according to claim 1, characterized in that: The numerical value collection end transmission module includes a numerical value receiving component and a numerical value information synchronous transmission component; The numerical value receiving component is used to receive a plurality of information messages containing embedded category item identifiers transmitted from the numerical information reduction component and a numerical feature chart constructed by the numerical feature chart forming component according to the numerical value of each subcategory item information; The numerical information synchronous transmission component is used to synchronously transmit a number of information messages containing embedded class item identifiers and numerical feature charts to the cloud platform-side numerical receiving module via multiple communication links.

7. The data risk assessment system based on a visualization model according to claim 6 is characterized by: The cloud platform-side numerical value receiving module includes a numerical information synchronous receiving component, a recovery component, and a numerical information transmission component; The numerical information synchronous receiving component is used to synchronously receive a plurality of information messages and numerical characteristic charts containing embedded class item identifiers via a plurality of communication links; The recovery component is used to decompress and recover a plurality of information messages containing embedded category item identifiers to obtain a plurality of subcategory item information and corresponding embedded category item identifiers; The numerical information transmission component is used to send the restored sub-category item information and the corresponding embedded category item identification and numerical feature chart to the cloud platform-side numerical transmission risk assessment module.

8. The data risk assessment system based on a visualization model according to claim 4 is characterized by: The cloud platform-side numerical transmission risk assessment module includes an information receiving component, a numerical quantity extraction component, and a transmission risk assessment component; The information receiving component is used to receive the restored sub-category information and the corresponding embedded category identifier and numerical feature chart; The numerical value extraction component is used to extract the numerical values ​​of the restored sub-category information, and the obtained numerical values ​​are recorded as W s,t Specifically, s is the total category number to which each sub-category information belongs, t is the sub-category number of each sub-category information, and the total category number and sub-category number of the corresponding numerical information are obtained according to the embedded category identifier; The transmission risk assessment component is used to compare the extracted and restored numerical values ​​of several sub-category item information with the numerical characteristic chart, so as to determine whether there is a risk in the current numerical transmission, that is, to determine whether all sub-category item information has been illegally changed.

9. The data risk assessment system based on a visualization model according to claim 8, characterized in that: The workflow of the transmission risk assessment component is: S2-1: Extract the numerical value W of several restored sub-category information s,t ; S2-2: Read the pixels of the numerical feature chart based on the order of the chart rows and columns using the functions and methods provided by the Scipy, PIL, NumPy and Matplotlib data analysis libraries, and extract the pixel points corresponding to the color values ​​pre-filled in each unit cell in the numerical feature chart JPG, that is, the px value, recorded as P s,t , specifically, s and t represent the row and column numbers of the unit grid respectively, that is, s is the total category number to which each sub-category information belongs, and t is the sub-category number of each sub-category information; S2-3: The px value of each unit cell is P s,t Sequentially and W s,t In comparison, if the pixel position P s,t and numerical value W s,t When the comparison results are inconsistent, it means that the corresponding sub-category item information has been illegally changed during the transmission process. On the contrary, if the comparison results are consistent, the risk index during the transmission process is low and there is no illegal change.

10. A risk assessment method for a data risk assessment system based on a visualization model as claimed in any one of claims 1 to 9, characterized in that: The following steps are involved: Step 1: Group the data provided to the input indicator into different categories to obtain several information messages, and add embedded category item identifiers to the several information messages, thereby forming a numerical feature chart; Step 2: A number of information messages containing embedded class item identifiers and numerical feature charts are synchronously transmitted to the numerical receiving module on the cloud platform; Step 3: Synchronously receive several information messages and numerical feature charts containing embedded class item identifiers, then decompress and restore the information messages, and then send the restored numerical information and numerical feature charts to the numerical transmission risk assessment module on the cloud platform; Step 4: Receive the restored numerical information and numerical characteristic chart, and then evaluate and calibrate the risk of this numerical transmission based on the restored numerical information and numerical characteristic chart, so as to determine whether there is a risk in this numerical transmission, that is, to determine whether all sub-category information has been illegally changed.

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