A power distribution cabinet safety monitoring system based on remote monitoring

Abstract

The application discloses a power distribution cabinet safety monitoring system based on remote monitoring, and relates to the technical field of power distribution cabinet monitoring.The system comprises a data acquisition module, a safety range acquisition module, an abnormal data transmission number generation module, a verification module and a data recovery module. Original abnormal data is hidden in a transmission number through a gradient value through a unique symbol assignment and encryption algorithm. By comparing data symbol groups, whether the data is tampered with during transmission can be effectively verified, the integrity and reliability of the data are ensured, malicious tampering and interception are prevented, the safety of data transmission is ensured, and misjudgment and security risks caused by data errors are avoided. The data that passes the verification is recovered, the data is ensured not to be tampered with during transmission, and the safety and reliability of the data are ensured. Even if the data is tampered with during transmission, the verification module will prevent the tampered data from entering the recovery module, and misjudgment and security risks caused by data errors are avoided.

Description

TECHNICAL FIELD

[0001] The application belongs to the technical field of power distribution cabinet monitoring, and particularly relates to a power distribution cabinet safety monitoring system based on remote monitoring. BACKGROUND

[0002] The power distribution cabinet is a key equipment in the power system, which undertakes the tasks of power distribution, control, protection and monitoring. The stability and safety of the power distribution cabinet are directly related to the safety of the entire power grid and the normal power use of users. The traditional safety management of the power distribution cabinet is based on a remote monitoring system of sensors. These systems usually set a fixed alarm threshold for each monitoring index (such as temperature, voltage and current);

[0003] However, when transmitting abnormal data, this method usually uses plaintext or simple encoding transmission, and the data is easy to be intercepted, tampered with or maliciously interfered with in the transmission process. Since the safety of data transmission is crucial in the safety monitoring process of the power distribution cabinet, unsafe transmission methods will bring great hidden dangers to the stable operation of the power grid. Therefore, the application provides a power distribution cabinet safety monitoring system based on remote monitoring. SUMMARY

[0004] The application aims to provide a power distribution cabinet safety monitoring system based on remote monitoring, which solves the technical problem that when transmitting abnormal data in the safety monitoring process of the power distribution cabinet, plaintext or simple encoding transmission is usually used, and the data is easy to be intercepted, tampered with or maliciously interfered with in the transmission process.

[0005] A power distribution cabinet safety monitoring system based on remote monitoring comprises:

[0006] A data acquisition module collects and records the historical data of various types of data (such as temperature, voltage and current) of the power distribution cabinet.

[0007] A safety range acquisition module obtains the safety range corresponding to each type of data according to the historical data of each type of data of the power distribution cabinet within a preset time t, t takes the value of 1, 2,..., a, and a represents the total number of days of the preset time t, i.e. a = 60.

[0008] An abnormal data transmission number generation module represents different types of data by different type symbols (◇, ○ and □), obtains the real-time values of various types of data of the power distribution cabinet in real time, compares and analyzes the real-time values of various types of data of the power distribution cabinet with the safety range corresponding to each type of data, determines the abnormal power distribution cabinet, compares and analyzes the real-time values of various types of data of the abnormal power distribution cabinet with the lower limit and upper limit of the safety range of each type of data, obtains the gradient value corresponding to each type of data, obtains the symbol value corresponding to each of the three different type symbols according to the assignment rule between different type symbols (◇, ○ and □), and generates the abnormal data transmission number corresponding to the abnormal power distribution cabinet.

[0009] The verification module obtains the data symbol group when receiving the abnormal data transmission number of the abnormal power distribution cabinet, and compares it with the verification symbol group, and passes the verification if they are consistent, and at the same time, the abnormal data transmission number is input to the data recovery module, otherwise, no processing is performed;

[0010] The data recovery module combines the symbol values corresponding to different types of symbols with the numerical conversion rule to recover and obtain the gradient values corresponding to each type of data.

[0011] As a further scheme of the application, the specific way to obtain the safety range corresponding to each type of data is:

[0012] The daily calculation data corresponding to each type of data in a preset time t is marked as Akt, the mean value Apk corresponding to each type of data is obtained according to the daily calculation data Akt corresponding to each type of data in a preset time t, the standard deviation σk corresponding to each type of data is calculated according to the daily calculation data Akt corresponding to each type of data in a preset time t, then the difference between the mean value Apk and the standard deviation σk corresponding to each type of data is taken as the lower limit value Apk-σk of the safety range of the type data, and the sum of the mean value Apk and the standard deviation σk corresponding to each type of data is taken as the upper limit value Apk+σk of the safety range of the type data, thereby obtaining the safety range Qk[Apk-σk, Apk+σk] corresponding to each type of data, wherein k represents different types of data in the multi-source data, k takes values of 1, 2 and 3, k=1: temperature data; k=2: voltage data; k=3: current data.

[0013] As a further scheme of the application, the specific way to determine the abnormal power distribution cabinet is:

[0014] The real-time values of each type of data of the power distribution cabinet are marked as Dk, the real-time values Dk of each type of data of the power distribution cabinet are compared with the safety range corresponding to each type of data, and the abnormal type data is determined, when there is abnormal type data, it is determined that the power distribution cabinet is an abnormal power distribution cabinet, otherwise, no processing is performed.

[0015] As a further scheme of the application, the specific way to determine the abnormal type data is:

[0016] The real-time values of each type of data are compared with the safety range corresponding to each type of data, the data type whose real-time value is not within the corresponding safety range is marked as abnormal type data, otherwise, no processing is performed.

[0017] As a further scheme of the application, the specific way to obtain the gradient value corresponding to each type of data is:

[0018] When the power distribution cabinet is determined as an abnormal power distribution cabinet, the real-time value corresponding to the abnormal class data is obtained, and when the real-time value corresponding to the abnormal class data is less than the lower limit value of the corresponding type safety range, the absolute value of the difference between the real-time value and the lower limit value is marked as D - As the gradient value of the corresponding type, when the real-time value corresponding to the abnormal class data is greater than the upper limit value of the corresponding type safety range, the absolute value of the difference between the real-time value and the upper limit value is marked as D + As the gradient value of the corresponding type, for non-abnormal class data, 0 is taken as the gradient value R1, R2 and R3 of the corresponding type, and the gradient value corresponding to each type of data is combined with the type symbol of the corresponding data type by " ".

[0019] As a further scheme of the present application: the specific way of representing different class data by different type symbols is:

[0020] The temperature class data is represented by the type symbol, the voltage class data is represented by the type symbol, and the current class data is represented by the type symbol.

[0021] As a further scheme of the present application: the specific way of obtaining the symbol values corresponding to the three different type symbols in combination with the assignment rules between the different type symbols is:

[0022] The assignment rules are:, and, it can be known that is greater than, is greater than, the value of is the smallest, is greater than by 3, is greater than by 2, then is greater than by 5, then is equal to, that is,, and the value of is 5, the value of is 10, and the value of is 8; then the symbol values E1, E2 and E3 corresponding to the three different type symbols, and are 8, 10 and 5 respectively.

[0023] As a further scheme of the present application: the specific way of generating the abnormal data transmission number corresponding to the abnormal power distribution cabinet is:

[0024] , as the abnormal data transmission number of the abnormal power distribution cabinet, is transmitted.

[0025] As a further scheme of the present application: the specific way of comparing the data symbol group with the verification symbol group is:

[0026] When the abnormal data transmission number of the abnormal power distribution cabinet is tampered with and intercepted during transmission, the type symbol is changed to , and the data symbol group is When the abnormal data transmission number of the abnormal power distribution cabinet is not tampered with and intercepted in the transmission process, the data symbol group is, the data symbol group is consistent with the verification symbol group, the verification is passed, and the abnormal data transmission number is transmitted to the data recovery module, otherwise, no processing is performed.

[0027] As a further scheme of the application: the specific way of recovering and obtaining the gradient values corresponding to each type of data is:

[0028] According to the numerical conversion rule: (◇〞U1-E1 / ○〞U2-E2 / □〞U3-E3)=(◇〞R1 / ○〞R2 / □〞R3), the gradient values R1, R2 and R3 corresponding to each type of data are obtained, and the gradient values corresponding to each type of data are recovered and obtained.

[0029] Compared with the prior art, the application has the following beneficial effects:

[0030] (1) In the application, the gradient value is subjected to encryption operation with the preset symbol assignment value, and the original abnormal data is effectively hidden, so that even if the data packet is intercepted in transmission, the attacker cannot directly interpret its real meaning, and the transmission security of the key infrastructure monitoring data is greatly enhanced;

[0031] (2) In the application, the original abnormal data is hidden in the transmission number through the unique symbol assignment value and encryption algorithm, so that even if the data is intercepted, the attacker cannot easily crack its real meaning, which greatly improves the key power data transmission security;

[0032] (3) In the application, by comparing the data symbol group, it can be verified whether the data is tampered with in the transmission process, to ensure the integrity and reliability of the data, prevent malicious tampering and interception, ensure the security of data transmission, and avoid misjudgment and security risks caused by data errors;

[0033] (4) In the application, only the data that passes the verification is recovered, to ensure that the data is not tampered with in the transmission process, and to ensure the security and reliability of the data, even if the data is tampered with in the transmission process, the verification module will prevent the tampered data from entering the recovery module, thereby avoiding the influence of the error data on the subsequent analysis and processing, and through the symbol assignment rule and the gradient value recovery, the original state of the data can be accurately restored without transmitting the original numerical value, only the gradient number is used to recover the data, the bandwidth utilization and transmission security are improved, the integrity and usability of the data are ensured, the stability and robustness of the entire monitoring system are improved, and the recovered data can accurately reflect the actual operation state of the power distribution cabinet, providing accurate data support for subsequent analysis and processing, which helps to timely discover and handle potential security risks. BRIEF DESCRIPTION OF DRAWINGS

[0034] Figure 1 The system framework structure of the application is shown in the figure.

[0035] Figure 2 The framework structure of the verification module of the application is shown in the figure. DETAILED DESCRIPTION

[0036] The technical solutions of the application will be described clearly and completely in connection with the embodiments. Obviously, the described embodiments are only a part of the embodiments of the application, but not all the embodiments. Based on the embodiments in the application, all the other embodiments obtained by those skilled in the art without creative work are within the protection scope of the application.

[0037] Embodiment one: please refer to Figure 1 The application provides a power distribution cabinet safety monitoring system based on remote monitoring, comprising:

[0038] The data acquisition module collects and records the multi-modal historical data of the power distribution cabinet, and the multi-modal data refers to temperature, voltage and current data.

[0039] The safety range acquisition module obtains the safety range corresponding to each type of data of the power grid intelligent terminal according to the multi-modal historical data of the power distribution cabinet within the preset time t, in a specific manner as follows:

[0040] The preset time t is a historical time length of 60 days from the current time, and the data of the day is not included, that is, the preset time t is equal to 60 days.

[0041] The average value of each type of data of the power distribution cabinet corresponding to each day within the preset time t is obtained as the daily calculation data corresponding to each type of data on the day, and the safety range corresponding to each type of data of the power grid intelligent terminal is calculated according to the daily calculation data corresponding to each day of each type of data within the preset time t, in a specific calculation and analysis manner as follows:

[0042] Each type of data corresponding to each day within the preset time t is marked as Akt, where k refers to different types of data in the multi-source data, and also serves as the category number corresponding to each type of data, t refers to different days, k takes the values of 1, 2 and 3, k=1: temperature data; k=2: voltage data; k=3: current data, A1t represents the temperature daily calculation data of the tth day, A2t represents the voltage daily calculation data of the tth day, and A3t represents the current daily calculation data of the tth day, where t takes the values of 1, 2, …, a, and a refers to the total number of days of the preset time t, that is, a=60.

[0043] According to the daily calculation data Akt corresponding to each type of data in each day within the preset time length t, the mean value Apk corresponding to each type of data is obtained, and the safety range Qk corresponding to each type of data of the power grid intelligent terminal is calculated according to the daily calculation data Akt and the mean value Apk corresponding to each type of data in each day within the preset time length T. The specific calculation method is:

[0044] Firstly, through the formula: According to the daily calculation data Akt corresponding to each type of data in each day within the preset time length t, the standard deviation σk corresponding to each type of data is calculated, then the difference between the mean value Apk and the standard deviation σk corresponding to each type of data is taken as the lower limit value Apk-σk of the type data safety range, and the sum of the mean value Apk and the standard deviation σk corresponding to each type of data is taken as the upper limit value Apk+σk of the type data safety range, and then the safety range Qk [Apk-σk, Apk+σk] corresponding to each type of data is obtained;

[0045] The mean value and the standard deviation of the historical data are calculated to dynamically define the safety range, which can be adjusted adaptively with the changes of seasons, environment and load. This greatly reduces the false alarm and missed alarm caused by environmental changes, and significantly improves the accuracy and intelligence level of monitoring.

[0046] The abnormal data transmission number generation module represents different types of data in multi-source data through different symbols, and obtains the real-time values of each type of data of the power distribution cabinet in real time. The real-time values of each type of data of the power distribution cabinet are compared and analyzed with the safety range corresponding to each type of data to determine the abnormal power distribution cabinet. According to the comparison and analysis of the real-time values of each type of data of the abnormal power distribution cabinet and the lower limit value and the upper limit value of the safety range of each type of data, the abnormal data transmission number corresponding to the abnormal power distribution cabinet is generated. The specific method is:

[0047] The temperature, voltage and current data in multi-source data are represented by three different type symbols, i.e. the type symbol is used to represent the temperature data, the type symbol is used to represent the voltage data, and the type symbol is used to represent the current data.

[0048] The specific method for comparing and analyzing the real-time values of each type of data of the power distribution cabinet with the safety range corresponding to each type of data to determine the abnormal power distribution cabinet is:

[0049] The real-time values of each type of data of the power distribution cabinet are marked as Dk, and the real-time values Dk of each type of data of the power distribution cabinet are compared with the safety range Qk [Apk-sigma k, Apk+sigma k] corresponding to each type of data. When at least one type of real-time value is not within the safety range of the corresponding type of data, that is, there is an abnormal type of data, it is determined that the power distribution cabinet is an abnormal power distribution cabinet, otherwise no action is taken, that is, when the real-time values of each type of data of the power distribution cabinet are within the safety range Qk of the corresponding type, no action is taken.

[0050] The real-time values Dk of each type of data are compared with the safety range Qk corresponding to each type of data, and the type of data whose real-time value Dk is not within the corresponding safety range Qk is marked as an abnormal type of data.

[0051] When the power distribution cabinet is determined to be an abnormal power distribution cabinet, the real-time value corresponding to the abnormal type of data of the power distribution cabinet is obtained, and it is compared with the lower limit value and the upper limit value of the safety range of the corresponding type. When the real-time value corresponding to the abnormal type of data is less than the lower limit value of the safety range of the corresponding type, the absolute value of the difference between the real-time value and the lower limit value is marked as D - as the gradient value of the corresponding type, and it is combined with the type symbol of the corresponding type of data through " ", and when the real-time value corresponding to the abnormal type of data is greater than the upper limit value of the safety range of the corresponding type, the absolute value of the difference between the real-time value and the upper limit value is marked as D + as the gradient value of the corresponding type, and it is combined with the type symbol of the corresponding type of data through " ", and for non-abnormal type of data, 0 is taken as the gradient value of the corresponding type;

[0052] The symbols of each type of data of the abnormal power distribution cabinet and the gradient values of each type of data are represented in the form of R1 / ○〞R2 / □〞R3, R1, R2 and R3 respectively represent the gradient values corresponding to each type of data;

[0053] By performing encryption operation on the gradient value and the preset symbol assignment, the original abnormal data is effectively hidden, even if the data packet is intercepted during transmission, the attacker cannot directly interpret its true meaning. At the same time, through the verification of the specific symbol by the verification module, it can effectively identify whether the data is tampered during transmission, greatly enhancing the transmission security of the key infrastructure monitoring data.

[0054] Wherein the three different types of symbols corresponding to temperature, voltage and current are respectively, and the three different types of symbols satisfy the assignment rules: ○+◇=18, ◇+□=13 and ○+◇+□=23, then the symbol assignments E1, E2 and E3 corresponding to the three different types of symbols can be obtained;

[0055] Transmit ◇「R1+E1 / ○」R2+E2 / □」R3+E3 as the abnormal data transmission number ◇「U1 / ○」U2 / □」U3 of the abnormal power distribution cabinet;

[0056] By employing unique symbol assignment and encryption algorithms, the original abnormal data is hidden in the transmission number through gradient values. Even if the data is intercepted, attackers cannot easily decipher its true meaning, which greatly improves the data transmission security of critical power facilities.

[0057] Example 2: As an example 2 of the present invention, please refer to... Figure 2 In specific implementation, compared with Embodiment 1, the only difference between the technical solution of this embodiment and Embodiment 1 is that this embodiment also includes a verification module and a data recovery module;

[0058] The verification module, upon receiving an abnormal data transmission number (◇"U1 / ○"U2 / □"U3) from an abnormal power distribution cabinet, extracts the type symbols for each data type to obtain a data symbol group. This group is then compared with the verification symbol group (◇○□). If they match, the verification passes; otherwise, no processing is performed. If the abnormal data transmission number from the abnormal power distribution cabinet is tampered with or intercepted during transmission, the type symbol (□) is changed to... The data symbol group is ◇○ When the abnormal data transmission number of the abnormal power distribution cabinet is not tampered with or intercepted during transmission, the data symbol group is ◇○□;

[0059] When the verification is successful, the abnormal data transmission number ◇「U1 / ○「U2 / □「U3 will be transmitted to the data recovery module;

[0060] Verify the received abnormal data transmission number. Extract the data symbol group and compare it with the verification symbol group ◇○□. If the data has been tampered with during transmission, the symbol □ will change to... The data symbol group changes to ◇○ After successful verification, the data is transmitted to the data recovery module. By comparing the data symbol groups, it is possible to effectively verify whether the data has been tampered with during transmission, ensuring the integrity and reliability of the data, preventing malicious tampering and interception, ensuring the security of data transmission, and avoiding misjudgments and security risks caused by data errors.

[0061] The data recovery module obtains the symbol values E1, E2 and E3 corresponding to the three different types of symbols according to the three different types of symbols, the satisfied assignment rules (i.e., 18, 13 and 23), and obtains the gradient values R1, R2 and R3 corresponding to the various types of data according to the numerical conversion rule: (◇〞U1-E1 / ○〞U2-E2 / □〞U3-E3)=(◇〞R1 / ○〞R2 / □〞R3), and recovers and obtains the gradient values corresponding to the various types of data.

[0062] The specific way of obtaining the symbol values E1, E2 and E3 corresponding to the three different types of symbols is as follows:

[0063] According to 18, 13 and 23, it can be known that is greater than, is greater than, the value of is the smallest, and is 3 greater than, is 2 greater than, so is 5 greater than, and 23 is equal to 5+3+5=23, that is, 3+8=23, and 3=15, so the value of is 5, and the value of is 10 and is 8.

[0064] The symbol values E1, E2 and E3 corresponding to the three different types of symbols, and are 8, 10 and 5, respectively.

[0065] According to (◇〞U1-E1 / ○〞U2-E2 / □〞U3-E3)=(◇〞R1 / ○〞R2 / □〞R3), the gradient values R1, R2 and R3 corresponding to the various types of data are obtained.

[0066] Only the data that passes the verification is recovered, ensuring that the data is not tampered with during transmission, and ensuring the security and reliability of the data. Even if the data is tampered with during transmission, the verification module will prevent the tampered data from entering the recovery module, thereby avoiding the influence of incorrect data on subsequent analysis and processing. The data that passes the verification is recovered through the symbol value assignment rule and the gradient value recovery, which can accurately restore the original state of the data, ensure the integrity and availability of the data, and improve the stability and robustness of the entire monitoring system. Even in a complex network environment, the recovered data can accurately reflect the actual operating state of the power distribution cabinet, providing accurate data support for subsequent analysis and processing, and helping to discover and handle potential safety hazards in a timely manner.

[0067] ​​Firstly, by learning the historical operation data of the power distribution cabinet in the past period of time, the mean and standard deviation in statistics are used to dynamically calculate a "floating" safety range for temperature, voltage, current and other indicators. Subsequently, the system monitors the current data in real time. Once it is found that the data deviates from the dynamic safety range, it will be immediately determined as an anomaly. Then, the system calculates the "distance" (i.e. gradient value) of the data point from the safety boundary, and encodes and encrypts the gradient value with a specific symbol representing the data type and its encrypted numerical value to generate a unique "abnormal data transmission number". This number is securely sent to the monitoring center, and then decrypted by the data recovery module to accurately restore the abnormal degree of each indicator, providing decision support for operation and maintenance personnel. This avoids tampering with the data of the power distribution cabinet in abnormal conditions during transmission, enhances the transmission security of abnormal data of the power distribution cabinet in abnormal conditions, and further improves the data transmission security of the power distribution cabinet safety monitoring.

[0068] Embodiment three: As an embodiment of the present application, in the specific implementation, compared with embodiment one and embodiment two, the technical solution of the present embodiment is to combine the schemes of embodiment one and embodiment two.

[0069] The above formulas are dimensionless numerical calculations. The formula is obtained by collecting a large amount of data to simulate the most recent real situation. The preset parameters and threshold values in the formula are set by a person skilled in the art according to the actual situation.

[0070] The above is only a specific embodiment of the present application, but the protection scope of the present application is not limited thereto. Any person skilled in the art can easily think of changes or replacements within the technical scope disclosed in the present application, which should be covered within the protection scope of the present application. Therefore, the protection scope of the present application should be subject to the protection scope of the claims.

Claims

1. A power distribution cabinet safety monitoring system based on remote monitoring, characterized in that, include: The data acquisition module collects and records historical data on various parameters of the distribution cabinet, including temperature, voltage, and current. The safety range acquisition module obtains the safety range corresponding to each type of data based on the historical data of various data of the power distribution cabinet within a preset time period t. The value of t is 1, 2, ..., a, where a represents the total number of days in the preset time period t, i.e., a=60. The abnormal data transmission number generation module represents different types of data using different type symbols ◇, ○, and □. It acquires real-time values ​​of various data types in the distribution cabinet, compares and analyzes these real-time values ​​with the corresponding safety ranges to determine abnormal distribution cabinets, compares and analyzes these real-time values ​​with the lower and upper limits of the safety ranges for each type of data to obtain the gradient values ​​for each type of data, and combines the assignment rules between the different type symbols ◇, ○, and □ to obtain the symbol assignments for the three different type symbols, generating the abnormal data transmission number corresponding to the abnormal distribution cabinet. When the verification module receives the abnormal data transmission number from the abnormal power distribution cabinet, it obtains the data symbol group and compares it with the verification symbol group ◇○□. If they match, the verification is passed, and the abnormal data transmission number is sent to the data recovery module. Otherwise, no processing is performed. The data recovery module combines the symbol assignments corresponding to different types of symbols with numerical conversion rules to recover and obtain the gradient values ​​corresponding to each type of data.

2. The power distribution cabinet safety monitoring system based on remote monitoring according to claim 1, characterized in that, The specific methods for obtaining the security range corresponding to each type of data are as follows: The daily calculated data for each type of data within a preset time period t is labeled Akt. The mean Apk of each type of data is obtained based on the daily calculated data Akt within the preset time period t. The standard deviation σk of each type of data is calculated based on the daily calculated data Akt within the preset time period t. The difference between the mean Apk and the standard deviation σk is used as the lower limit Apk-σk of the data class's safety range. The sum of the mean Apk and the standard deviation σk is used as the upper limit Apk+σk of the data class's safety range. Therefore, the safety range Qk[Apk-σk, Apk+σk] for each type of data is obtained, where k represents different types of data in the multi-source data, and k takes values ​​of 1, 2, and 3: k=1: temperature data; k=2: voltage data; k=3: current data.

3. The power distribution cabinet safety monitoring system based on remote monitoring according to claim 2, characterized in that, The specific method for determining abnormal power distribution cabinets is as follows: The real-time values ​​of various data in the power distribution cabinet are marked as Dk. The real-time values ​​Dk of various data in the power distribution cabinet are compared with the corresponding safety ranges of each data. Abnormal data is judged. If abnormal data exists, the power distribution cabinet is judged as abnormal; otherwise, no action is taken.

4. A power distribution cabinet safety monitoring system based on remote monitoring according to claim 3, characterized in that, The specific method for determining abnormal data is as follows: The real-time values ​​of various data types are compared with their respective safety ranges. Data types whose real-time values ​​are outside the corresponding safety ranges are marked as abnormal data; otherwise, no action is taken.

5. A power distribution cabinet safety monitoring system based on remote monitoring according to claim 4, characterized in that, The specific methods for obtaining the gradient values ​​corresponding to each type of data are as follows: When a power distribution cabinet is identified as an abnormal power distribution cabinet, the real-time value corresponding to the abnormal data is obtained. If the real-time value corresponding to the abnormal data is less than the lower limit of the corresponding type of safety range, the absolute value of the difference between the real-time value and the lower limit is marked as D. - As the gradient value for the corresponding type, when the real-time value corresponding to the anomaly data exceeds the upper limit of the corresponding type's safety range, the absolute value of the difference between the real-time value and the upper limit value is marked as D. + As the gradient values ​​for the corresponding types, 0 is used as the gradient values ​​R1, R2 and R3 for non-anomaly data. At the same time, the gradient values ​​corresponding to each type of data are combined with the type symbols of the corresponding data types using "".

6. The power distribution cabinet safety monitoring system based on remote monitoring according to claim 1, characterized in that, The specific way to represent different types of data using different type symbols ◇, ○, and □ is as follows: Temperature data is represented by the type symbol ◇, voltage data by the type symbol ○, and current data by the type symbol □.

7. A power distribution cabinet safety monitoring system based on remote monitoring according to claim 5, characterized in that, The specific method for obtaining the symbol assignments corresponding to the three different types of symbols, ◇, ○, and □, by combining the assignment rules between them, is as follows: The assignment rules are as follows: ○+◇=18, ◇+□=13 and ○+◇+□=23. We know that ○ is greater than ◇, ◇ is greater than □, and □ has the smallest value. ◇ is 3 greater than □, and ○ is 2 greater than ◇, so ○ is 5 greater than □. Therefore, ○+◇+□=23 is equal to □+5+□+3+□=23, which gives 3□+8=23. Calculating 3□=15, we get □ is assigned the value of 5, ○ is assigned the value of 10, and ◇ is assigned the value of 8. Thus, the symbol assignments E1, E2, and E3 for the three different types of symbols ◇, ○, and □ are 8, 10, and 5 respectively.

8. A power distribution cabinet safety monitoring system based on remote monitoring according to claim 7, characterized in that, The specific method for generating the abnormal data transmission number corresponding to the abnormal power distribution cabinet is as follows: Transmit ◇」R1+E1 / ○」R2+E2 / □」R3+E3 as the abnormal data transmission number ◇」U1 / ○」U2 / □」U3 of the abnormal power distribution cabinet.

9. A power distribution cabinet safety monitoring system based on remote monitoring according to claim 8, characterized in that, The specific method for comparing the data symbol group with the verification symbol group ◇○□ is as follows: When the abnormal data transmission number of the abnormal power distribution cabinet is tampered with or intercepted during transmission, the type symbol □ changes to The data symbol group is ◇○ When the abnormal data transmission number of the abnormal power distribution cabinet is not tampered with or intercepted during transmission, the data symbol group is ◇○□. If the data symbol group is consistent with the verification symbol group, the verification is passed, and the abnormal data transmission number is sent to the data recovery module. Otherwise, no processing is performed.

10. A power distribution cabinet safety monitoring system based on remote monitoring according to claim 9, characterized in that, The specific methods for recovering and obtaining the gradient values ​​corresponding to each type of data are as follows: According to the numerical transformation rule: (◇"U1-E1 / ○"U2-E2 / □"U3-E3)=(◇"R1 / ○"R2 / □"R3), the gradient values ​​R1, R2 and R3 corresponding to each type of data are obtained, and the gradient values ​​corresponding to each type of data are recovered.

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