Wire temperature diagnosis method for intelligent signboard and intelligent signboard

Abstract

The invention provides a line temperature diagnosis method for an intelligent signboard and the intelligent signboard, and belongs to the technical field of abnormity diagnosis, and the method specifically comprises the steps: carrying out the temperature measurement of a power transmission line through employing the intelligent signboard, obtaining the temperature measurement data at different moments, and combining the environment temperature data and the transmission power in the adjacent time period of the moments, when it is determined that the temperature abnormal condition of the power transmission line does not meet the requirement, temperature measurement data of the power transmission line in a preset time period is transmitted to a monitoring platform, and when it is determined that the line temperature deviation coefficient of the power transmission line is not abnormal by using other power transmission lines in the monitoring platform and the temperature measurement data of the power transmission line at different moments, the power transmission line is monitored. According to the line temperature deviation coefficient of the power transmission line with different identification times in the monitoring platform, the temperature anomaly diagnosis mode of the power transmission line is determined, and the accuracy of the temperature anomaly diagnosis result of the power transmission line is improved.

Description

Technical Field

[0001] The present invention belongs to the technical field of abnormal diagnosis, and in particular relates to a line temperature diagnosis method for a smart sign and a smart sign. Background Art

[0002] Transmission lines will inevitably generate heat during operation. Monitoring the line temperature of transmission lines can not only detect abnormal conditions of transmission lines, but also detect line losses of transmission lines in real time. This makes how to detect and process line temperature a technical problem that needs to be solved urgently.

[0003] In order to detect and process the line temperature of the power transmission line, the invention patent application CN201410595301.3 "Online detection system and method for conductor temperature of power transmission line" connects the second wireless communication module with the temperature monitoring terminal, thereby solving the power supply problem of long-term operation in the field and realizing unmanned remote measurement of conductor temperature. However, there are the following technical problems: When performing line temperature diagnosis, the line temperature of the transmission line will be affected by many factors such as the load of the transmission line and the ambient temperature. Therefore, if a fixed line temperature threshold is used, it will be impossible to accurately evaluate the actual operating status of the transmission line.

[0004] In view of the above technical problems, the present application specifically provides a line temperature diagnosis method for a smart sign and a smart sign. Summary of the invention

[0005] To achieve the purpose of the present invention, the present invention adopts the following technical solutions: According to one aspect of the present invention, a line temperature diagnosis method for a smart sign is provided.

[0006] A line temperature diagnosis method for a smart sign, specifically comprising: S1 determines the change of the transmission power of the transmission line based on the analysis result of the temperature measurement data of the smart sign, and proceeds to the next step when it is determined that the power change of the transmission line meets the requirements based on the change of the transmission power of the transmission line; S2 uses the smart sign to measure the temperature of the transmission line to obtain temperature measurement data at different times, and combines the ambient temperature data and the transmission power in the time period near the time to determine that the temperature abnormality of the transmission line does not meet the requirements, and then proceeds to the next step; S3 transmits the temperature measurement data of the transmission line within a preset time period to the monitoring platform, and uses other transmission lines in the monitoring platform and the temperature measurement data of the transmission line at different times to determine that there is no abnormality in the line temperature deviation coefficient of the transmission line, and determines the temperature abnormality diagnosis method of the transmission line according to the line temperature deviation coefficient of the transmission line with different identification times in the monitoring platform.

[0007] The beneficial effects of the present invention are: By utilizing other transmission lines in the monitoring platform and the temperature measurement data of the transmission lines at different times, it is determined whether there is any abnormality in the line temperature deviation coefficient of the transmission line, thereby realizing the evaluation of the abnormality of the transmission line from the deviation between the temperature measurement data of other transmission lines and the temperature measurement data of the transmission line, avoiding the technical problem that the accuracy of judging the temperature abnormality does not meet the requirements due to the single consideration of the temperature measurement data of the transmission line, and ensuring the accuracy of the evaluation and screening of the transmission lines with abnormal line temperatures.

[0008] According to the line temperature deviation coefficient of the transmission line with different identification times in the monitoring platform, the temperature anomaly diagnosis method of the transmission line is determined, thereby avoiding the technical problem of inaccurate diagnosis results of the line temperature anomaly of the transmission line using smart signs. By combining the identification times, the error diagnosis times of the transmission line using smart signs are determined, thereby improving the accuracy of the diagnosis results of the line temperature anomaly.

[0009] A further technical solution is that the variation of the transmission power of the transmission line includes the power variation time of the transmission line in different time periods and the power variation amount at the power variation time.

[0010] A further technical solution is that the power change moment is a moment when the power deviation from the adjacent moment is not within a preset interval.

[0011] A further technical solution is that the power variation is a power deviation between the power variation moment and an adjacent moment.

[0012] A further technical solution is to determine whether the power variation of the transmission line meets the requirements, specifically including: Determining the power change moments of the transmission line in different time periods based on the change of the transmission power of the transmission line; Determining a power variation period in the period by using the number of the power variation moments; Determine whether the power variation of the transmission line meets the requirement according to the number of the power variation time periods.

[0013] A further technical solution is that the power change period is a period in which the number of power change moments is greater than the number of preset moments.

[0014] A further technical solution is that, when the number of the power change time periods is not within a preset time period number range, it is determined that the power change of the transmission line does not meet the requirements.

[0015] A further technical solution is to use a monitoring platform to perform temperature anomaly diagnosis and processing when the power variation of the transmission line does not meet the requirements.

[0016] A further technical solution is that the method for determining the abnormal temperature diagnosis mode of the transmission line is: Determine the number of times the transmission line is identified within a preset time period based on the number of times the transmission line is identified on the monitoring platform; The line temperature deviation coefficients of different identification times are normalized to obtain the identification error weight coefficients of different identification times; The sum of the identification error weight coefficients of the number of identifications of the transmission line within a preset time period is used to determine the sum of the error coefficients, and the temperature anomaly diagnosis method of the transmission line is determined using the sum of the error coefficients.

[0017] A further technical solution is to utilize the deviation coefficient and determine the abnormal temperature diagnosis method of the transmission line, specifically including: Based on the error coefficient and , a preset diagnostic method corresponding to the error coefficient and is determined, and the temperature anomaly diagnostic method of the power transmission line is determined using the preset diagnostic method.

[0018] A further technical solution is that the abnormality diagnosis method is to use the monitoring platform to perform temperature abnormality diagnosis and processing and to use a smart sign to perform temperature abnormality diagnosis and processing.

[0019] In a second aspect, the present invention provides a smart sign, which is applied to the above-mentioned line temperature diagnosis method for the smart sign, specifically comprising: Temperature measurement module, line temperature diagnosis module, data transmission module; The temperature measurement module is responsible for performing temperature measurement processing on the transmission line to obtain temperature measurement data at different times; The line temperature diagnosis module is responsible for determining whether there is an abnormality in the line temperature deviation coefficient of the transmission line by using other transmission lines in the monitoring platform and the temperature measurement data of the transmission line at different times; The data transmission module is responsible for data transmission processing with the monitoring platform.

[0020] Other features and advantages will be described in the following description, and partly become apparent from the description, or understood by practicing the invention. The purpose and other advantages of the invention are realized and obtained by the structures particularly pointed out in the description and the drawings.

[0021] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, preferred embodiments are given below and described in detail with reference to the accompanying drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] The above and other features and advantages of the present invention will become more apparent by describing in detail exemplary embodiments thereof with reference to the attached drawings.

[0023] Figure 1 It is a flow chart of a line temperature diagnosis method for a smart sign; Figure 2 It is a flow chart for determining whether the power variation of the transmission line meets the requirements; Figure 3 It is a flow chart to determine that the temperature anomaly of the transmission line does not meet the requirements; Figure 4 The present invention is a flowchart of a method for determining a temperature anomaly diagnosis method for a power transmission line. DETAILED DESCRIPTION

[0024] In order to enable those skilled in the art to better understand the technical solutions in this specification, the technical solutions in the embodiments of this specification will be clearly and completely described below in conjunction with the drawings in the embodiments of this specification. Obviously, the described embodiments are only part of the embodiments of this specification, not all of the embodiments. Based on the embodiments of this specification, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of this specification.

[0025] For ease of understanding, the scheme will be described below through Example 1 and Example 2. Example

[0026] To solve the above problems, according to one aspect of the present invention, Figure 1 According to one aspect of the present invention, a line temperature diagnosis method for a smart sign is provided, which specifically includes: S1 determines the change of the transmission power of the transmission line based on the analysis result of the temperature measurement data of the smart sign, and proceeds to the next step when it is determined that the power change of the transmission line meets the requirements based on the change of the transmission power of the transmission line; Furthermore, the variation of the transmission power of the transmission line includes the power variation time of the transmission line in different time periods and the power variation amount at the power variation time.

[0027] Specifically, the power change moment is a moment when the power deviation from the adjacent moment is not within a preset interval.

[0028] It can be understood that the power variation is the power deviation between the power variation moment and the adjacent moment.

[0029] It should be noted that if Figure 2 As shown, determining whether the power variation of the transmission line meets the requirements specifically includes: Determining the power change moments of the transmission line in different time periods based on the change of the transmission power of the transmission line; Determining a power variation period in the period by using the number of the power variation moments; Determine whether the power variation of the transmission line meets the requirement according to the number of the power variation time periods.

[0030] Furthermore, the power change period is a period in which the number of power change moments is greater than the number of preset moments.

[0031] It can be understood that when the number of the power change time periods is not within the preset time period number range, it is determined that the power change of the transmission line does not meet the requirements.

[0032] Specifically, when the power variation of the transmission line does not meet the requirements, the monitoring platform is used to perform temperature anomaly diagnosis and processing.

[0033] In another embodiment, determining whether the power variation of the transmission line meets the requirement specifically includes: Based on the variation of the transmission power of the transmission line, determining the power variation moments of the transmission line in different time periods, and when the number of the power variation moments does not meet the requirement, determining that the power variation of the transmission line does not meet the requirement; When the number of power change moments is not within the preset change moment number range: When it is determined based on the number of power change moments in different time periods that there is no power change period in the time period, it is determined that the power change condition of the transmission line meets the requirements; When the number of power change moments is within a preset change moment number interval or there is a power change period: Acquire the number of power change time periods, and when the number of the power change time periods is not within a preset time period number interval, determine that the power change of the transmission line does not meet the requirements; When the number of power change periods is within the preset period number range: The number of power change periods on different dates is determined based on the distribution data of the power change periods. When there is a date where the number of power change periods is greater than a preset period number threshold: The date when the number of power change periods is greater than the preset period number threshold is used as the power change date, and when the number of the power change dates does not meet the requirement, it is determined that the power change of the transmission line does not meet the requirement; When the number of power change dates meets the requirement: Determine the date variation coefficients of different power variation dates according to the proportion of the number of power variation moments in different power variation dates, and when the sum of the date variation coefficients of different power variation dates does not meet the requirements, determine that the power variation of the transmission line does not meet the requirements; When there is no date with a number of power change periods greater than the preset period number threshold or the sum of the date change coefficients of different power change dates meets the requirement: The date variation coefficients of different dates are determined by the proportion of the number of power variation moments on different dates, and whether the power variation of the transmission line meets the requirements is determined according to the average value of the date variation coefficients of different dates.

[0034] S2 uses the smart sign to measure the temperature of the transmission line to obtain temperature measurement data at different times, and combines the ambient temperature data and the transmission power in the time period near the time to determine that the temperature abnormality of the transmission line does not meet the requirements, and then proceeds to the next step; Specifically, Figure 3 As shown, determining that the temperature abnormality of the transmission line does not meet the requirements specifically includes: Based on the ambient temperature data and the transmission power at different times in the adjacent time period, the temperature thresholds at the different times are determined by using a preset mapping function; Determine the line temperature at different times according to the temperature measurement data at different times, and determine the temperature abnormality moment in the said time in combination with the temperature threshold value corresponding to the different times; Whether the temperature anomaly of the power transmission line meets the requirement is determined by the number of temperature anomaly moments within a preset time period.

[0035] It should be noted that the value range of the adjacent time period is between 30 minutes and 1 hour.

[0036] Furthermore, the temperature abnormality moment is the moment when the line temperature is greater than a temperature threshold.

[0037] Specifically, when the number of temperature abnormal moments within a preset time period is greater than the preset number of abnormal moments, it is determined that the temperature abnormality of the transmission line does not meet the requirement.

[0038] It is understandable that when the temperature anomaly of the power transmission line meets the requirements, the intelligent signboard is used to perform temperature anomaly diagnosis and processing.

[0039] In another embodiment, determining that the abnormal temperature of the transmission line does not meet the requirement specifically includes: S21 determines the temperature thresholds at different times based on the ambient temperature data and the transmission power at different times in the adjacent time period and using a preset mapping function; S22 determines the line temperature at different times according to the temperature measurement data at different times, and determines the temperature abnormality moment in the moments according to the temperature thresholds corresponding to the different times; Optionally, the above step S22 includes the following contents: S221 determines the line temperature at different times according to the temperature measurement data at different times, and determines that there is no abnormal temperature moment in the said time in combination with the temperature threshold corresponding to the different times, then determines that the abnormal temperature of the transmission line meets the requirements, and when there is an abnormal temperature moment in the said time, enters step S222; S222: obtaining the number of abnormal temperature moments; when the number of abnormal temperature moments is greater than a preset abnormal number threshold, determining that the abnormal temperature of the transmission line does not meet the requirements; when the number of abnormal temperature moments is not greater than the preset abnormal number threshold, proceeding to step S223; S223 determines the interval data between different temperature abnormal moments based on the distribution data of different temperature abnormal moments, and uses the interval data to determine the aggregated abnormal moments among the temperature abnormal moments. When the number of the aggregated abnormal moments does not meet the requirement, it is determined that the temperature abnormality of the transmission line does not meet the requirement. When the number of the aggregated abnormal moments meets the requirement, the process proceeds to step S224. S224 obtains the number ratio of the temperature abnormal moments. When the number ratio of the temperature abnormal moments is within the preset ratio range, the process goes to step S23. When the number ratio of the temperature abnormal moments is not within the preset ratio range, it is determined that the temperature abnormality of the transmission line meets the requirements.

[0040] S23 determines the abnormal weight coefficients at different moments of temperature abnormality based on the deviations between the line temperature at different moments of temperature abnormality and the temperature threshold using a preset mapping function, determines the sum of the weight coefficients by summing up the abnormal weight coefficients at different moments of temperature abnormality within a preset time period, and determines whether the temperature abnormality of the transmission line meets the requirements based on the sum of the weight coefficients.

[0041] Optionally, the above step S23 includes the following contents: S231 determines the abnormal weight coefficients of different temperature abnormal moments based on the deviations between the line temperature and the temperature threshold at different temperature abnormal moments by using a preset mapping function. When there is a temperature abnormal moment with an abnormal weight coefficient greater than the preset weight coefficient threshold, the process proceeds to step S232. When there is no temperature abnormal moment with an abnormal weight coefficient greater than the preset weight coefficient threshold, the process proceeds to step S233. S232: The temperature abnormality moment when the abnormality weight coefficient is greater than the preset weight coefficient threshold is regarded as the serious abnormality moment. When the number of the serious abnormality moments does not meet the requirement, it is determined that the temperature abnormality of the transmission line does not meet the requirement. When the number of the serious abnormality moments meets the requirement, the process proceeds to step S233. S233 determines the sum of weight coefficients by summing the abnormal weight coefficients at different temperature abnormal moments within a preset time period, and determines whether the temperature abnormality of the transmission line meets the requirements based on the sum of weight coefficients.

[0042] S3 transmits the temperature measurement data of the transmission line within a preset time period to the monitoring platform, and uses other transmission lines in the monitoring platform and the temperature measurement data of the transmission line at different times to determine that there is no abnormality in the line temperature deviation coefficient of the transmission line, and determines the temperature abnormality diagnosis method of the transmission line according to the line temperature deviation coefficient of the transmission line with different identification times in the monitoring platform.

[0043] Further, determining that there is no abnormality in the line temperature deviation coefficient of the transmission line specifically includes: Determining similar transmission lines of the other transmission lines based on the transmission power and ambient temperature data of the other transmission lines at different times; Determine the deviation at different times according to the temperature measurement data of the similar transmission line and the transmission line at different times, and use the deviation to determine the deviation time of different similar transmission lines; The deviation coefficients of different similar transmission lines are determined by the proportion of the number of deviation moments of different similar transmission lines, the line temperature deviation coefficient of the transmission line is determined by the average value of the deviation coefficients of different similar transmission lines, and whether there is an abnormality in combination with a preset temperature deviation coefficient threshold.

[0044] It can be understood that the similar transmission lines are other transmission lines whose transmission power and ambient temperature data at different times are within 5%.

[0045] Furthermore, the deviation moment is the moment when the deviation amount does not meet the requirement.

[0046] Specifically, when the line temperature deviation coefficients of different similar power transmission lines are greater than a preset temperature deviation coefficient threshold, it is determined that there is an abnormality in the line temperature of the power transmission line.

[0047] It is understandable that when the line temperature of the transmission line is abnormal, a temperature abnormality signal is directly issued, and the monitoring platform is used to perform temperature abnormality diagnosis and processing.

[0048] Specifically, Figure 4 As shown, the method for determining the abnormal temperature diagnosis mode of the transmission line is: Determine the number of times the transmission line is identified within a preset time period based on the number of times the transmission line is identified on the monitoring platform; The line temperature deviation coefficients of different identification times are normalized to obtain the identification error weight coefficients of different identification times; The sum of the identification error weight coefficients of the number of identifications of the transmission line within a preset time period is used to determine the sum of the error coefficients, and the temperature anomaly diagnosis method of the transmission line is determined using the sum of the error coefficients.

[0049] Furthermore, the method of diagnosing abnormal temperature of the power transmission line by using the deviation coefficient specifically includes: Based on the error coefficient and , a preset diagnostic method corresponding to the error coefficient and is determined, and the temperature anomaly diagnostic method of the power transmission line is determined using the preset diagnostic method.

[0050] It should also be noted that the abnormality diagnosis method is to use the monitoring platform to perform temperature abnormality diagnosis and processing and to use a smart sign to perform temperature abnormality diagnosis and processing.

[0051] In another embodiment, the method for determining the abnormal temperature diagnosis mode of the power transmission line is: S41 determines the number of identifications of the transmission line within a preset time period based on the number of identifications of the transmission line on the monitoring platform; Optionally, the above step S41 includes the following contents: S411 determines the number of identifications of the transmission line within a preset time period based on the number of identifications of the transmission line on the monitoring platform. When the number of identifications within the preset time period is greater than a preset identification number threshold, it is determined to use the monitoring platform to perform temperature anomaly diagnosis processing. When the number of identifications within the preset time period is not greater than the preset identification number threshold, the process proceeds to step S412. S412: if it is determined according to the interval between the identification times within the preset time length that there is no identification times with an interval length less than the preset interval length, the process proceeds to step S42; if there is an identification times with an interval length less than the preset interval length, the process proceeds to step S413; S413 takes the number of identification times with an interval duration less than the preset interval duration as the number of cluster identification times. When the number of cluster identification times is greater than the preset cluster number threshold, it is determined to use the monitoring platform to perform temperature anomaly diagnosis processing. When the number of cluster identification times is not greater than the preset cluster number threshold, it proceeds to step S42.

[0052] S42 uses the line temperature deviation coefficients of different recognition times to obtain recognition error weight coefficients of different recognition times after normalization processing, and performs recognition deviation times of the smart sign in the recognition times according to the recognition error weight coefficient; Optionally, the above step S42 includes the following contents: S421 uses the line temperature deviation coefficients of different identification times to perform normalization processing to obtain identification error weight coefficients of different identification times. When the average value of the identification error weight coefficients of different identification times meets the requirements, the process proceeds to step S422. When the average value of the identification error weight coefficients of different identification times does not meet the requirements, it is determined to use the monitoring platform to perform temperature anomaly diagnosis processing; S422: when there is no identification number with a recognition error weight coefficient greater than the preset error coefficient threshold, it is determined to use the intelligent sign to perform temperature abnormality diagnosis processing; when there is an identification number with a recognition error weight coefficient greater than the preset error coefficient threshold, it proceeds to step S423; S423 determines the number of identification deviations of the smart sign in the identification times according to the identification error weight coefficient. When the number of identification deviations does not meet the requirement, it is determined to use the monitoring platform to perform temperature anomaly diagnosis processing. When the number of identification deviations meets the requirement, it proceeds to step S43.

[0053] S43 determines the recognition error coefficient of the smart sign according to the recognition error weight coefficients of different recognition deviation times, and determines the temperature anomaly diagnosis method of the power transmission line using the recognition error coefficient.

[0054] Furthermore, the number of recognition deviations of the smart sign in the number of recognitions is the number of recognitions in which the recognition error weight coefficient is greater than a preset coefficient threshold.

[0055] Specifically, the recognition error coefficient is determined according to the sum of recognition error weight coefficients of different recognition deviation times. Example

[0056] In a second aspect, the present invention provides a smart sign, which is applied to the above-mentioned line temperature diagnosis method for the smart sign, specifically comprising: Temperature measurement module, line temperature diagnosis module, data transmission module; The temperature measurement module is responsible for performing temperature measurement processing on the transmission line to obtain temperature measurement data at different times; The line temperature diagnosis module is responsible for determining whether there is an abnormality in the line temperature deviation coefficient of the transmission line by using other transmission lines in the monitoring platform and the temperature measurement data of the transmission line at different times; The data transmission module is responsible for data transmission processing with the monitoring platform.

[0057] Each embodiment in this specification is described in a progressive manner, and the same or similar parts between the embodiments can be referred to each other, and each embodiment focuses on the differences from other embodiments. In particular, for the device, equipment, and non-volatile computer storage medium embodiments, since they are basically similar to the method embodiments, the description is relatively simple, and the relevant parts can be referred to the partial description of the method embodiment.

[0058] The above is a description of a specific embodiment of the specification. Other embodiments are within the scope of the appended claims. In some cases, the actions or steps recorded in the claims can be performed in an order different from that in the embodiments and still achieve the desired results. In addition, the processes depicted in the drawings do not necessarily require the specific order or continuous order shown to achieve the desired results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0059] The above description is only one or more embodiments of this specification and is not intended to limit this specification. For those skilled in the art, one or more embodiments of this specification may have various changes and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of one or more embodiments of this specification shall be included in the scope of the claims of this specification.

Claims

1. A line temperature diagnosis method for a smart sign, characterized in that: Specifically include: Determine the change of the transmission power of the transmission line based on the analysis result of the temperature measurement data of the smart sign, and proceed to the next step when it is determined that the power change of the transmission line meets the requirements based on the change of the transmission power of the transmission line; The intelligent sign is used to measure the temperature of the transmission line to obtain temperature measurement data at different times, and when it is determined that the temperature abnormality of the transmission line does not meet the requirements in combination with the ambient temperature data and the transmission power in the period near the time, the next step is entered; The temperature measurement data of the transmission line within a preset time period is transmitted to a monitoring platform, and the temperature measurement data of other transmission lines in the monitoring platform and the transmission line at different times are used to determine that there is no abnormality in the line temperature deviation coefficient of the transmission line, and according to the line temperature deviation coefficient of different identification times of the transmission line in the monitoring platform, a temperature abnormality diagnosis method of the transmission line is determined.

2. A photovoltaic power control method for a transformer as claimed in claim 1, characterized in that: The variation of the transmission power of the transmission line includes the power variation time of the transmission line in different time periods and the power variation amount at the power variation time.

3. A photovoltaic power control method for a transformer as claimed in claim 2, characterized in that: The power change moment is a moment at which the power deviation from the adjacent moment is not within a preset interval.

4. A photovoltaic power control method for a transformer as claimed in claim 2, characterized in that: The power variation is a power deviation between the power variation time and an adjacent time.

5. A photovoltaic power control method for a transformer as claimed in claim 1, characterized in that: Determining whether the power variation of the transmission line meets the requirements, specifically including: Based on the variation of the transmission power of the transmission line, determining the power variation time of the transmission line in different time periods; Determining a power variation period in the period by using the number of the power variation moments; Determine whether the power variation of the transmission line meets the requirement according to the number of the power variation time periods.

6. A photovoltaic power control method for a transformer as claimed in claim 5, characterized in that: The power change period is a period in which the number of power change moments is greater than the number of preset moments.

7. A photovoltaic power control method for a transformer as claimed in claim 1, characterized in that: When the power variation of the transmission line does not meet the requirements, the monitoring platform is used to perform temperature anomaly diagnosis and processing.

8. A photovoltaic power control method for a transformer as claimed in claim 1, characterized in that: The method for determining the abnormal temperature diagnosis mode of the transmission line is: Determine the number of times the transmission line is identified within a preset time period based on the number of times the transmission line is identified on the monitoring platform; The line temperature deviation coefficients of different identification times are normalized to obtain the identification error weight coefficients of different identification times; The sum of the identification error weight coefficients of the number of identifications of the transmission line within a preset time period is used to determine the sum of the error coefficients, and the temperature anomaly diagnosis method of the transmission line is determined using the sum of the error coefficients.

9. A photovoltaic power control method for a transformer as claimed in claim 8, characterized in that: The method of diagnosing abnormal temperature of the power transmission line by using the deviation coefficient specifically includes: Based on the error coefficient and , a preset diagnostic method corresponding to the error coefficient and is determined, and the temperature anomaly diagnostic method of the power transmission line is determined using the preset diagnostic method.

10. A smart sign, applied to the line temperature diagnosis method for a smart sign as claimed in any one of claims 1 to 9, characterized in that: Specifically include: Temperature measurement module, line temperature diagnosis module, data transmission module; The temperature measurement module is responsible for performing temperature measurement processing on the transmission line to obtain temperature measurement data at different times; The line temperature diagnosis module is responsible for determining whether there is an abnormality in the line temperature deviation coefficient of the transmission line by using other transmission lines in the monitoring platform and the temperature measurement data of the transmission line at different times; The data transmission module is responsible for data transmission processing with the monitoring platform.

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