Line fault early warning method and system based on elbow type head parameter online monitoring analysis

Abstract

The invention discloses a line fault early warning method based on elbow type head parameter online monitoring analysis, and relates to the technical field of electric power grid operation risk monitoring, and the method comprises the steps: determining elbow type head information in each line, and dividing the elbow type head information into at least one group of associated elbow type head groups; on the basis of the actually measured temperature information of the online elbow-shaped head, actually measured temperature information of a missing elbow-shaped head is predicted, and total actually measured temperature information of the associated elbow-shaped head group is obtained; on the basis of the conversion temperature information of the online elbow-shaped head, the conversion temperature information of the missing elbow-shaped head is predicted, and the total conversion temperature information of the associated elbow-shaped head group is obtained; the operation risk of the line is judged according to the on-line temperature information of the at least one associated elbow-shaped head group; according to the early warning method and system, the missing elbow-shaped head is predicted through the online elbow-shaped head, so that the temperature information of the whole associated elbow-shaped head group is obtained to judge the line operation risk, and the problem that the line temperature information at the joint cannot be accurately judged after a certain (multiple) elbow-shaped heads are offline or communication is lost is avoided.

Description

Technical Field

[0001] The present invention relates to the technical field of power grid operation risk monitoring, and in particular to a line fault early warning method and system based on online monitoring and analysis of elbow head parameters. Background Art

[0002] At present, in the power distribution system, equipment such as inflatable cabinets, network ring cabinets, and cable branch boxes are widely used. These devices use elbow heads (elbow cable connectors) when they are led out, and the elbow heads in the power distribution system generally have the characteristics of wide deployment range and multiple points. Affected by the processing technology, construction quality, operating conditions and operating environment, once the elbow head of the high-voltage cable fails, it will cause overheating fires and even explosion accidents, directly threatening the normal operation of the distribution network. Since the elbow head installation has high insulation requirements and no current passes through, if online monitoring is not carried out in time, once a fault occurs, the impact will be great. Therefore, monitoring the real-time temperature of the electrical connection points inside the cable elbow head can effectively avoid the blind spots of line monitoring and improve the reliability and safety of the distribution network lines.

[0003] In the prior art, most of them only monitor the temperature of each elbow head, and indirectly measure the line operating temperature at the elbow head installation location by monitoring the temperature data of the elbow head through a temperature sensor, and then transmit the monitored temperature data to the background server in real time for early warning analysis. Although this method can provide online early warning of the line operating condition at the joint through the operating status of the elbow head, it is impossible to determine the line temperature information at the joint when a certain elbow head is offline or the communication is lost, thereby failing to provide accurate temperature warning for the joint and the directly related lines. In addition, when monitoring and analyzing the operating temperature of the elbow head, only the readings sensed by the sensor are judged, rather than a direct analysis of the actual line temperature, and the factor that the line temperature transmitted to the elbow head will cause changes in accuracy and lead to inaccurate collection results is ignored.

[0004] In view of this, this application is hereby filed. Summary of the invention

[0005] The purpose of the present invention is to provide a line fault early warning method and system based on online monitoring and analysis of elbow head parameters. The early warning method and system predict the missing elbow head through the online elbow head to obtain the temperature information of the entire associated elbow head group to judge the line operation risk, thereby avoiding the inability to accurately judge the line temperature information at the joint due to one (or more) elbow heads being offline or communication being lost; at the same time, the actual elbow head temperature information obtained by combining the sensor reading and the actual heat transfer temperature change is considered during temperature acquisition, further improving the accuracy of the final line temperature information calculation.

[0006] The embodiment of the present invention is achieved as follows: In a first aspect, a line fault warning method based on online monitoring and analysis of elbow head parameters includes the following steps: obtaining line information to be monitored, determining elbow head information in each line, establishing an elbow head distribution network based on the elbow head information, and dividing all elbow heads in the line into at least one group of associated elbow head groups according to the elbow head distribution network, wherein the elbow head information includes the type, quantity and installation position of the elbow heads; in each group of the associated elbow head groups, predicting the measured temperature information of the missing elbow head based on the measured temperature information of the online elbow head, and obtaining the total measured temperature information of the associated elbow head group. ; and based on the conversion temperature information of the online elbow head, the conversion temperature information of the missing elbow head is predicted to obtain the total conversion temperature information of the associated elbow head group; the operation risk of the line is judged by using the online temperature information of at least one group of the associated elbow head groups, wherein the online temperature information includes the total measured temperature information and the total conversion temperature information; wherein, when predicting the conversion temperature information of the missing elbow head based on the conversion temperature information of the online elbow head, the heat flow change of the online elbow head thermal conversion component during the loss period is calculated, and the conversion temperature information of the online elbow head is obtained based on the heat flow change.

[0007] In some optional embodiments, the step of calculating the heat flow change of an online elbow-type head thermal conversion component during a loss period and obtaining the conversion temperature information of the online elbow-type head based on the heat flow change includes the following steps: determining the area where the thermal conversion component performs heat transfer, and obtaining the separate heat flow information of each area of ​​the thermal conversion component during the loss period; combining all the separate heat flow information to obtain the total heat flow; calculating the heat flow change based on the total heat flow, and calculating the temperature change based on the heat flow change; and calculating the conversion temperature information based on the temperature change and the initial temperature of the thermal conversion component at the moment of loss.

[0008] In some optional embodiments, the obtaining of the distributed heat flow information of each area of ​​the heat conversion component during the loss period includes the following steps: determining a basic distributed heat flow and a first changed distributed heat flow of each area of ​​the heat conversion component during the loss period, and calculating the distributed heat flow information based on the basic distributed heat flow and the first changed distributed heat flow, wherein the first changed distributed heat flow is the heat flow increased or decreased due to a change in thermal conductivity caused by a temperature change of the heat conversion component during the loss period.

[0009] In some optional embodiments, the method of obtaining the distributed heat flow information of each area of ​​the heat conversion component during the loss period also includes the following steps: determining the second changed distributed heat flow of each area of ​​the heat conversion component during the loss period, and calculating the distributed heat flow information based on the basic distributed heat flow, the first changed distributed heat flow and the second changed distributed heat flow, wherein the second changed distributed heat flow is the increase or decrease in heat flow caused by the change in thermal contact area due to deformation of the heat conversion component due to temperature change during the loss period.

[0010] In some optional embodiments, after calculating the heat flow change of the online elbow head thermal conversion component during the loss period, the following steps are also included: determining a heat flow influence amount, where the heat flow influence amount refers to the heat change data that increases or decreases due to the influence of a non-thermal conversion component on the thermal conversion component during heat transfer; calculating an actual heat flow change amount based on the heat flow influence amount and the heat flow change amount, and obtaining the conversion temperature information of the online elbow head based on the actual heat flow change amount.

[0011] In some optional implementations, the prediction of the conversion temperature information of the missing elbow head based on the conversion temperature information of the online elbow head includes the following steps: establishing a prediction model, obtaining the model-predicted conversion temperature information and the actually measured conversion temperature information of the online elbow head, optimizing and iterating the prediction model using the difference between the model-predicted conversion temperature information and the actually measured conversion temperature information, and predicting the conversion temperature information of the missing elbow head based on the prediction model after optimization and iteration, wherein the model-predicted conversion temperature information refers to the conversion temperature information of the online elbow head obtained by calculating using the prediction model; the actually measured conversion temperature information refers to the conversion temperature information of the online elbow head obtained by calculating using the heat flow change.

[0012] In some optional embodiments, after predicting the conversion temperature information of the missing elbow head based on the conversion temperature information of the online elbow head, the following steps are also included: obtaining the changed conversion temperature information of the missing elbow head during the loss period, merging the changed conversion temperature information with the predicted conversion temperature information of the missing elbow head to obtain corrected conversion temperature information, and participating in the calculation of the total conversion temperature information of the associated elbow head group based on the corrected conversion temperature information, wherein the changed conversion temperature information refers to the information that the temperature of the missing elbow head changes due to changes in its own thermal conductivity and / or thermal contact causing changes in heat flow, resulting in changes.

[0013] In some optional implementations, the use of online temperature information of at least one group of associated elbow head groups to judge the operating risk of the line includes the following steps: determining the online temperature information of each group of associated elbow head groups, marking the associated elbow head groups whose online temperature information is higher than the warning temperature information as risk-associated elbow head groups, obtaining the difference between the online temperature information and the warning temperature information of each group of risk-associated elbow head groups to obtain multiple sub-difference values, calculating the total difference value based on the sub-difference values, and judging the risk level of the line based on the total difference value.

[0014] In some optional implementations, the number of missing elbow heads in each group of associated elbow head groups is determined, and the associated elbow head groups with the number of missing elbow heads higher than a preset value are also marked as risky associated elbow head groups.

[0015] Secondly, the line fault early warning system based on online monitoring and analysis of elbow head parameters includes: A first acquisition unit, which is used to acquire line information to be monitored, determine elbow head information in each line, establish an elbow head distribution network based on the elbow head information, and divide all elbow heads in the line into at least one group of associated elbow head groups according to the elbow head distribution network, wherein the elbow head information includes the number and installation position of the elbow heads; A first calculation unit is used to predict the measured temperature information of the missing elbow head in each group of the associated elbow head groups based on the measured temperature information of the online elbow head to obtain the total measured temperature information of the associated elbow head group; and predict the conversion temperature information of the missing elbow head based on the conversion temperature information of the online elbow head to obtain the total conversion temperature information of the associated elbow head group; A first judgment unit, which is used to judge the operation risk of the line using online temperature information of at least one group of the associated elbow head groups, wherein the online temperature information includes total measured temperature information and total converted temperature information; The second calculation unit is used to calculate the heat flow change of the online elbow head heat conversion component during the missing period when predicting the conversion temperature information of the missing elbow head based on the conversion temperature information of the online elbow head, and obtain the conversion temperature information of the online elbow head based on the heat flow change.

[0016] The beneficial effects of the embodiments of the present invention are: The line fault warning method and system based on online monitoring and analysis of elbow head parameters provided by the embodiment of the present invention obtains at least one group of associated elbow head groups by associating and dividing all elbow heads in the line. The line attributes of each associated elbow head group are identical, that is, the operating conditions of the elbow heads therein are highly correlated, so that the online elbow heads (in the same associated elbow head group) can be used to predict the operating status of the missing elbow heads, thereby obtaining the total operating temperature information of the entire associated elbow head group, and the temperature information of the line is judged by all the divided associated elbow head groups to achieve the purpose of risk warning, which is no longer limited to the inability to accurately judge the operating risk of the line at the joint because one (or more) elbow heads are offline or the communication is lost; on this basis, when predicting the operating status of the missing elbow head for the online elbow head, the measured temperature information (sensor detection data) and the converted temperature information (heat transfer change data) are simultaneously considered to avoid the situation where the sensor detection reading accuracy is uncontrollable due to the design defects of the elbow head and the detection temperature error is large, thereby further ensuring the accuracy of the final line temperature information calculation.

[0017] In general, the line fault warning method and system based on online monitoring and analysis of elbow head parameters provided in the embodiments of the present invention utilize the method of associated group prediction, while taking into account the difference between the collected data and the actual data and performing a certain filling method to provide the accuracy of overall temperature prediction and calculation. Compared with the traditional method of directly detecting the elbow head temperature only through sensors, it is more reliable and more in line with the actual situation. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings required for use in the embodiments are briefly introduced below. It should be understood that the following drawings only show certain embodiments of the present invention and therefore should not be regarded as limiting the scope. For ordinary technicians in this field, other related drawings can be obtained based on these drawings without creative work.

[0019] Figure 1 A flowchart of the main steps of the early warning method provided by an embodiment of the present invention; Figure 2 for Figure 1 A flow chart of one of the main steps S300 is shown; Figure 3 for Figure 2 The sub-step flow chart of step S300 is shown; Figure 4 for Figure 1 A flow chart of one of the main steps S200 is shown; Figure 5A flowchart of step S300, one of the main steps provided in another embodiment of the present invention; Figure 6 for Figure 1 A flow chart of one of the main steps S400 is shown; Figure 7 A modular schematic diagram of an early warning system provided in an embodiment of the present invention.

[0020] Icons: 500 - early warning system; 510 - first acquisition unit; 520 - first calculation unit; 530 - first judgment unit; 540 - second calculation unit. DETAILED DESCRIPTION

[0021] In order to make the purpose, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Generally, the components of the embodiments of the present invention described and shown in the drawings here can be arranged and designed in various different configurations.

[0022] Therefore, the following detailed description of the embodiments of the present invention provided in the accompanying drawings is not intended to limit the scope of the invention claimed for protection, but merely represents selected embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0023] It should be understood that the "system", "device" and / or "module" used in the present invention is a method for distinguishing different components, elements, parts, portions or assemblies at different levels. However, if other words can achieve the same purpose, the words can be replaced by other expressions.

[0024] As shown in the present invention and claims, unless the context clearly indicates an exception, the words "a", "an", "an" and / or "the" do not refer to the singular, but also include the plural. In general, the terms "include" and "comprise" only indicate the inclusion of the steps and elements that have been clearly identified, and these steps and elements do not constitute an exclusive list, and the method or device may also include other steps or elements.

[0025] Flowcharts are used in the present invention to illustrate the operations performed by the system according to the embodiments of the present application. It should be understood that the preceding or following operations are not necessarily performed accurately in order. On the contrary, the various steps may be processed in reverse order or simultaneously. At the same time, other operations may also be added to these processes, or one or more operations may be removed from these processes. Example

[0026] For power grid line monitoring, especially when the elbow head is abnormal due to elbow head failure or short circuit of the line where the elbow head is located, the temperature information is obtained in real time through the temperature sensor (remote communication) arranged on the elbow head, so as to realize early warning analysis and judgment and control the line operation status. However, in actual operation, this method is limited by two aspects. One of them is that after a certain (multiple) elbow head monitoring point is offline or lost, the data of the point cannot be collected, resulting in missing monitoring. We generally infer the possible situation of the missing monitoring point based on historical data and some related monitoring points. This method can obtain certain reference results, but how to more accurately predict the situation of the missing monitoring point is the key issue; the other is that the elbow head is affected by processing technology, construction quality and other problems. When it is conducting heat transfer, there will be different degrees of transfer loss, which will lead to a gap between the data detected by the sensor and the actual data. This gap may be small in the elbow head with controllable accuracy, but there will be a large gap if the accuracy is not controllable, which affects the accuracy of the final line operation status judgment. In response to the above two problems, we proposed a new monitoring and analysis method, which uses model learning to predict the presence of missing monitoring points. It also takes into account heat transfer losses and the differences between collected data, so as to obtain more realistic data for overall calculation and ensure the accuracy of line operation status judgment.

[0027] Please refer to Figure 1 The present embodiment provides a line fault early warning method based on online monitoring and analysis of elbow head parameters, comprising the following steps: S100: Obtain the line information to be monitored, determine the elbow head information in each line, establish an elbow head distribution network based on the elbow head information, and divide all the elbow heads in the line into at least one group of associated elbow head groups according to the elbow head distribution network, wherein the elbow head information includes the type, quantity and installation position of the elbow head; this step indicates that all the elbow head information in the line to be monitored is confirmed, and it is necessary to confirm the number and installation position of all the elbow heads in the line to be monitored, so as to determine whether the related elbow heads are associated according to the installation position (for example, the elbow heads on the same series line or the same type of elbow heads within a limited distance are used as associated elbow heads), thereby constructing an elbow head distribution network in the entire line to be monitored (each node in the network represents the installation position of the elbow head, and the line between the two elbow heads represents the actual connection relationship), thereby determining at least one group of associated elbow head groups based on the elbow head distribution network, and all the elbow heads in the associated elbow head group have the same operating conditions and attributes, and can have a high degree of state correlation and similarity during operation.

[0028] S200: In each group of the associated elbow head groups, the measured temperature information of the missing elbow head is predicted based on the measured temperature information of the online elbow head to obtain the total measured temperature information of the associated elbow head group; and the conversion temperature information of the missing elbow head is predicted based on the conversion temperature information of the online elbow head to obtain the total conversion temperature information of the associated elbow head group; this step represents the judgment and calculation for the temperature information of each group of associated elbow head groups. Since there may be offline or missing elbow heads, it is impossible to obtain all the monitoring temperature data of all the elbow heads in the associated elbow head group through sensor data. However, the characteristics that all the elbow heads in the associated elbow head group have a high correlation and similarity in operating status can be used to reasonably infer and calculate the temperature data of the offline or missing elbow heads, that is, the online elbow heads are used to predict the temperature data of the missing elbow heads.

[0029] On the basis of the aforementioned use of online elbow heads to predict the temperature data of missing elbow heads, considering that the actual temperature of each elbow head and its connection includes sensor data and temperature change data generated during heat transfer, these two aspects need to be considered when using online elbow heads to predict the temperature data of missing elbow heads. Specifically, it includes predicting the measured temperature information of the missing elbow head based on the measured temperature information of the online elbow head, so that the measured temperature information of the missing elbow head is obtained by predicting the measured temperature information of the online elbow head. This prediction method refers to output calculation by means of a deep learning model or a statistical model, and statistics the measured temperature information of all elbow heads each time, and find the correlation change law of the measured temperature information of all elbow heads, so that when a certain (multiple) elbow heads are missing the temperature data, the correlation change law can be used to predict the missing measured temperature data and fill in the blank data of the missing points of this monitoring. By using the online elbow head to predict the temperature data of the missing elbow head, the measured temperature information of all elbow heads in the latest time (segment) can be obtained, so that the total measured temperature information of the associated elbow head group is calculated based on the measured temperature information of all elbow heads.

[0030] Similarly, on the other hand, it also includes predicting the conversion temperature information of the missing elbow head based on the conversion temperature information of the online elbow head. The conversion temperature information represents the actual temperature change of the thermal sensing contact part of the elbow head during heat transfer. The temperature change is determined by the elbow head processing technology, materials and operating status. It is combined with the data directly detected by the sensor to more accurately obtain the actual temperature information of the connection. That is, on the basis of the above-mentioned calculation of the total measured temperature information of the associated elbow head group, it is also necessary to calculate the total conversion temperature information of the associated elbow head group.

[0031] Specifically, the conversion temperature information of the missing elbow head is predicted based on the conversion temperature information of the online elbow head, and the total conversion temperature information of the associated elbow head group is obtained. As mentioned above, the prediction method here also refers to output calculation through a deep learning model or a statistical model, and the conversion temperature information of all elbow heads is counted each time to find the correlation change law of the conversion temperature information of all elbow heads. When one (or more) elbow heads lack the temperature data, the correlation change law can be used to predict the conversion temperature data of the missing elbow head, fill in the blank data of the missing points of this monitoring, and calculate the total conversion temperature information of the associated elbow head group after obtaining the conversion temperature information of all elbow heads, so as to facilitate the calculation of the real-time temperature of the associated elbow head group.

[0032] Through the above technical solution, the measured temperature information and conversion temperature information of the missing elbow head are obtained by model prediction. The measured temperature information can be directly obtained through sensor data, while the conversion temperature information needs to be obtained through the results of various tests under the original design parameters of the elbow head, so as to calculate the heat transfer loss of the elbow head under the corresponding operating conditions, and then calculate the obtained conversion temperature change. The heat transfer loss of the elbow head under the corresponding operating conditions requires, on the one hand, the various operating condition test results of the original design parameters, and on the other hand, the current heat flow transfer data needs to be detected (such as through thermistor detection), so as to obtain the conversion temperature change information by comparing the corresponding operating condition test results under the heat flow data, that is, to perform step S300.

[0033] S300: When predicting the conversion temperature information of the missing elbow head based on the conversion temperature information of the online elbow head, calculate the heat flow change of the online elbow head thermal conversion component during the loss period, and obtain the conversion temperature information of the online elbow head based on the heat flow change. This step means calculating the temperature change during the loss period by obtaining the heat flow change of the elbow head thermal conversion component, and calculating the conversion temperature information of the online elbow head by combining the temperature change with the initial conversion temperature at the moment of loss. It should be noted that the loss period refers to the time period from the beginning of data loss of the missing elbow head to the recovery of data (temperature detection data and heat flow detection data). The conversion temperature information of the missing elbow head is predicted by the conversion temperature information of the online elbow head obtained during this time period, thereby ensuring the accuracy of the associated prediction results during the loss period (under the premise of data loss).

[0034] In addition, by using the part of the elbow head that transfers heat (i.e., the heat conversion component) to detect heat flow changes, the temperature changes caused by it can be determined by detecting the heat flow. Compared with directly measuring the temperature of the heat conversion component, on the one hand, thermistor detection is easier to install, and on the other hand, heat changes are easier to detect. It does not need to use other temperature sensors to detect heat and then convert it into temperature output, which will cause calculation errors in the conversion process. Instead, this (heat to temperature) conversion error is reduced by comparing with the measurement results of the original design parameter conditions.

[0035] S400: Using the online temperature information of at least one group of the associated elbow head groups to judge the operation risk of the line, wherein the online temperature information includes the total measured temperature information and the total conversion temperature information. This step indicates that through the above steps, the online temperature information of the associated elbow head group is obtained, and the online temperature information is obtained by combining the total measured temperature information and the total conversion temperature information. The online temperature information of all groups in the line is used to calculate the early warning temperature of the line, so as to judge the operation risk.

[0036] Through the above technical scheme, on the one hand, it is considered that even when the communication of the elbow head is offline or lost, risk analysis of the operating line can still be carried out; on the other hand, it is considered that when the sensor acquires data, there is a temperature change caused by actual heat transfer loss and the monitoring data cannot be accurately obtained. Based on the above two considerations, the online temperature information of the associated elbow head group is calculated based on the measured temperature information and the converted temperature information. The calculated result is more accurate and more in line with reality, so that more reliable judgment results can be obtained when judging the line operation risk.

[0037] Considering that the heat flow detection of the heat conversion component is not uniform when the heat is transferred at various locations of the heat conversion component, if point detection is performed, the error will increase. Therefore, in this embodiment, the range heat flow detection of the heat conversion component is performed. For details, please refer to Figure 2 , the step of calculating the heat flow variation of the online elbow head heat conversion component during the loss period, and obtaining the conversion temperature information of the online elbow head based on the heat flow variation comprises the following steps: S310: Determine the area where the heat conversion component performs heat transfer, and obtain the separate heat flow information obtained by each area of ​​the heat conversion component during the loss period; this step means dividing and confirming the part of the heat conversion component that performs heat transfer, obtaining multiple (heat transfer) area parts, arranging heat flow detection points on each area part, obtaining the separate heat flow information obtained by each area part during the loss period, and then performing the subsequent step S320: Merge all the separate heat flow information to obtain the total heat flow; this step means merging and calculating the separate heat flow information to obtain the total heat flow, thereby achieving the purpose of regional range detection and avoiding the problem of increased error due to setting single-point detection.

[0038] S330: Calculate the heat flow variation based on the total heat flow, and calculate the temperature variation based on the heat flow variation; this step indicates that after obtaining the total heat flow, the heat flow variation (the ratio of the total heat flow to the loss period) can be calculated based on the loss period, and after obtaining the heat flow variation, it can be compared with the temperature change result table of the corresponding working conditions under the original design parameters of the elbow head to obtain the temperature variation, and then proceed to the subsequent step S340: Calculate the conversion temperature information based on the temperature variation and the initial temperature of the heat conversion component at the moment of loss; this step indicates calculating the above-mentioned temperature variation and the initial heat conversion component (conversion temperature) at the moment of loss to obtain the conversion temperature information of the heat conversion component (elbow head) at this time. Through the aforementioned technical scheme, the initial test parameter of how much temperature change the elbow head will produce for each heat flow passing through can be used, so that the temperature change produced by the heat flow change in different time periods can be obtained at any time, and then combined with the initial conversion temperature (also calculated by the heat flow change method) to obtain the conversion temperature information at this time. A relatively accurate conversion temperature calculation amount can be obtained at any time in any missing period, thereby further ensuring the accuracy of subsequent prediction of the conversion temperature of the missing elbow head.

[0039] On the basis of the above technical solutions, when testing the heat flow information of each area, due to the different processing technology and materials used in the heat conversion components of the elbow head, its own heat transfer performance will also change after the temperature changes. For example, its thermal conductivity will decrease after the temperature rises, resulting in a decrease in the heat transfer flow per unit time. Considering this part of the change, please refer to Figure 3 The step of obtaining the heat flow information of each area of ​​the heat conversion component during the loss period includes the following steps: S311: Determine the basic partial heat flow and the first variable partial heat flow of each area of ​​the heat conversion component during the loss period, and calculate the partial heat flow information based on the basic partial heat flow and the first variable partial heat flow, wherein the first variable partial heat flow is the heat flow increased or decreased due to the change in thermal conductivity caused by the temperature change of the heat conversion component during the loss period. This step indicates that when determining the heat flow information of each area, it is necessary to determine at least two parts of heat flow, namely, the basic heat flow and the first change heat flow. The basic heat flow refers to the basic heat flow data detected by the heat flow detection point itself, and the first change heat flow is the heat flow increased or decreased by the change in thermal conductivity of the heat conversion component due to temperature change during the loss period, indicating that the thermal conductivity of the heat conversion component (each area) changes due to temperature change (during the loss period). This change needs to be detected by a high-precision thermistor (difficult to be detected by a general sensor element), which is generally obtained through a calibration parameter table. The changed (increased or decreased) heat flow is recorded as the first change heat flow, so that the basic heat flow and the first change heat flow are combined to obtain the heat flow information.

[0040] Based on the above scheme, the heat conversion component will generally be accompanied by thermal expansion and deformation after the temperature changes in addition to the change in thermal conductivity, which will cause the contact area between it and the circuit to change, thus affecting the heat flow per unit time. Therefore, in order to consider the above issues, please refer to Figure 3 In this embodiment, the step of obtaining the heat flow information of each area of ​​the heat conversion component during the loss period further includes the following steps: S312: Determine the second change partial heat flow of each area of ​​the heat conversion component during the loss period, and calculate the partial heat flow information based on the basic partial heat flow, the first change partial heat flow and the second change partial heat flow, wherein the second change partial heat flow is the heat flow caused by the change in thermal contact area caused by the deformation of the heat conversion component due to temperature change during the loss period. This step indicates that when determining the partial heat flow information of each area, it is also necessary to determine the third part of the heat flow, that is, the second change partial heat flow, which is the heat flow caused by the change in thermal contact area caused by the deformation of the heat conversion component due to temperature change during the loss period. It means that due to the change in temperature (during the loss period), the shape of the heat conversion component (especially the area connected to the line) changes, resulting in an increase (decrease) in the area of ​​contact with the line. At this time, under the premise of the same thermal conductivity, the heat transfer flow will also change after the contact area changes. Therefore, this part of the change is recorded as the second change partial heat flow, so that the second change partial heat flow is combined with the basic partial heat flow and the first change partial heat flow to obtain the partial heat flow information.

[0041] It should be noted that the thermal contact area needs to be determined according to the design style of the heat conversion component itself. The part that contacts the circuit may adopt a U-shaped card, for example. In this case, the change in contact area occurs on the inner side surfaces of the two ends of the U-shaped card; in another case, a ring-shaped card may be adopted. In this case, the change in contact area occurs on the inner surface of the ring-shaped card; in another case, a strip card may be adopted. In this case, the change in contact area occurs on the contact side. Regardless of the design style, it is necessary to determine in advance how many contact surfaces are used, the initial contact area, and the area retained to be contacted, so as to judge the change in the thermal contact area. At this time, the increased contact area is combined with the thermal conductivity and the heat transfer time (determined according to the loss period) to calculate the second change heat flow.

[0042] The above technical solution takes into account the situation that the heat transfer rate changes due to the change in thermal conductivity and thermal contact area caused by the temperature change of the heat conversion component itself. On this basis, since the heat conversion component is installed in the elbow head through an internal fixing part (integrated fixing or detachable fixing), the heat transfer temperature change will also cause the heat transfer of these non-heat conversion components (internal fixing parts) to change. In different implementations, for example, the increase in thermal conductivity of the non-heat conversion component or the deformation of the heat conversion component will also cause the heat transfer rate of the heat conversion component (various regions) to change, and this change should also be considered in the heat flow change of the heat conversion component.

[0043] Specifically, after calculating the heat flow change of the online elbow head thermal conversion component during the loss period, the following steps are also included: determining the heat flow influence, which refers to the heat flow change data that is increased or decreased due to the influence of the non-thermal conversion component on the thermal conversion component during heat transfer; this step means that for the non-thermal conversion component, due to temperature changes such as increased thermal conductivity, which leads to the diversion of the heat flow information of the heat conversion component, and deformation that squeezes the heat conversion component and affects the contact area of ​​the heat conversion component, which causes the change of the heat flow information, similar to the above-mentioned heat change data that increases or decreases due to the influence on the thermal conversion component during heat transfer is obtained, which is recorded as the heat flow influence, and then the actual heat flow change is calculated based on the heat flow influence and the heat flow change, and the conversion temperature information of the online elbow head is calculated by the actual heat flow change.

[0044] In this embodiment, as mentioned above, when predicting the conversion temperature information of the missing elbow head based on the conversion temperature information of the online elbow head, a prediction model is used for prediction calculation. The prediction model can perform prediction calculation based on the correlation characteristics of all elbow heads. However, considering that the model can use the historical data trend of a single elbow head for the next prediction calculation in addition to using the correlation characteristics when predicting, it can avoid the problem of insufficient prediction accuracy caused by sudden changes in the predicted elbow head (large changes in the trend between the associated elbow heads), so as to achieve the purpose of continuously improving the prediction accuracy. Please refer to Figure 4 The method of predicting the conversion temperature information of the missing elbow head based on the conversion temperature information of the online elbow head comprises the following steps: S210: Establish a prediction model, obtain the model-predicted conversion temperature information and the actual measured conversion temperature information of the online elbow head; this step means using the established prediction model, which can not only make predictions based on the characteristics of high correlation and similarity between related elbow heads, but also make statistics or learning predictions based on the historical data of a single elbow head, and conduct supervised learning on the predicted conversion temperature data of each elbow head and the conversion temperature information calculated by the above-mentioned heat flow change, and then proceed to the subsequent step S220: optimize and iterate the prediction model by using the difference between the model-predicted conversion temperature information and the actual measured conversion temperature information; this step means optimizing and iterating the prediction model by using the difference between the two (model-predicted conversion temperature information and actual measured conversion temperature information) to improve the prediction accuracy of the model. Among them, the model-predicted conversion temperature information refers to the conversion temperature information of the online elbow head calculated by the prediction model; the actual measured conversion temperature information refers to the conversion temperature information of the online elbow head calculated by the heat flow change.

[0045] S230: Predicting the conversion temperature information of the missing elbow head based on the optimized and iterated prediction model. This step means predicting the conversion temperature information of the missing elbow head based on the continuously iterated prediction model. At this time, the prediction model not only has the ability to use the characteristics of high correlation and similarity between related elbow heads for associated prediction, but also has the characteristic of accurate prediction for the trend of a single elbow head. Taking the above two aspects into consideration, when the associated prediction of the conversion temperature information data of the missing elbow head is made, the prediction of the missing elbow head can be made under the condition that it is limited by the trend of the historical data of the elbow head, thereby avoiding the problem of large prediction accuracy error caused by sudden changes in the predicted missing elbow head.

[0046] Based on the above scheme, since the predicted conversion temperature information of the missing elbow head is obtained, in addition to the above consideration of the heat flow change of the online elbow head, the missing elbow head also has a heat flow change. Therefore, based on the predicted conversion temperature information of the missing elbow head, the problem of conversion temperature change caused by the heat flow change is also considered. Figure 5 , and after predicting the missing elbow head conversion temperature information based on the online elbow head conversion temperature information, the following steps are also included: S350: Obtain the change conversion temperature information of the missing elbow head during the missing period; wherein the change conversion temperature information refers to the information that the missing elbow head changes in temperature due to the change in heat flow caused by the change in its own thermal conductivity and / or thermal contact. This step indicates that the change in heat flow caused by the change in its own thermal conductivity and / or thermal contact of the missing elbow head also needs to be considered. The change in heat flow refers to the calculation method of the change in heat flow of the online elbow head, and the information that the change in temperature caused by the change in heat flow of the missing elbow head is recorded as the change conversion temperature information.

[0047] S360: The change conversion temperature information is combined with the predicted conversion temperature information of the missing elbow head to obtain the corrected conversion temperature information. This step means combining the predicted conversion temperature information of the missing elbow head obtained by the prediction model with the change conversion temperature information obtained in the aforementioned step S340 to obtain the corrected conversion temperature information. Then, the subsequent step S370 is performed: based on the corrected conversion temperature information, the total conversion temperature information of the associated elbow head group is calculated. This step means that the more realistic and practical corrected conversion temperature information is used to calculate the total conversion temperature information, so that the online temperature information of the associated elbow head group obtained in the end is more accurate and reasonable.

[0048] Through the above technical solution, it can ensure that the online temperature information of the associated elbow head group is more reasonable, more comprehensive, more accurate and practical. Therefore, when the online temperature information of the associated elbow head group is involved in the operation risk calculation of the line, a more reliable calculation result can be obtained. For example, the specific risk calculation process adopts the following method, please refer to Figure 6 The method of using the online temperature information of at least one group of the associated elbow head groups to judge the operation risk of the line includes the following steps: S410: Determine the online temperature information of each group of associated elbow-type head groups, and mark the associated elbow-type head groups whose online temperature information is higher than the warning temperature information as risk-associated elbow-type head groups; this step means judging the online temperature information of all groups of associated elbow-type head groups, and marking the associated elbow-type head groups whose online temperature information is higher than the warning temperature information as risk-associated elbow-type head groups. The warning temperature information is the critical risk temperature that can cause high-temperature operation failure in the line to be monitored, and it participates in the judgment and calculation in a predetermined manner (such as industry experience value or historical data learning of the line).

[0049] S420: Obtain the difference between the online temperature information and the warning temperature information of each group of the risk-associated elbow-type head groups, and obtain multiple sub-difference values; this step indicates that it is necessary to further extract the difference of the risk-associated elbow-type head groups whose online temperature information is higher than the warning temperature information, that is, record the higher part as the difference value. It should be noted that if there is only one group of risk-associated elbow-type head groups, there is one difference value, and if there are multiple groups of risk-associated elbow-type head groups, there are multiple difference values. Then proceed to the subsequent step S430: calculate the total difference value based on the sub-difference values, and judge the risk level of the line based on the total difference value. This step indicates that all the sub-difference values ​​are combined to calculate the total difference value. The combined calculation method is, for example, averaging calculation or weighted average calculation, and the total difference value obtained is used to judge the risk level of the line, such as judging according to the risk level comparison table (which can be obtained through artificial stunning settings).

[0050] Through the above technical solution, the risk level of the line can be judged based on the sub-difference values ​​of all risk-associated elbow head groups. On this basis, considering that in addition to the high risk caused by excessively large difference values, if there are too many offline or lost elbow heads in the associated elbow head group, the risk of line operation will also increase (proving that there are other factors that lead to too many lost elbow heads, such as external force damage, too long maintenance cycle, elbow heads being interfered with by communication, etc.), so it is necessary to consider this situation for risk judgment. Specifically, in this embodiment, the number of missing elbow heads in each group of the associated elbow head groups is determined, and the associated elbow head groups with the number of missing elbow heads higher than the preset value are also marked as risk-associated elbow head groups. Through the aforementioned technical solution, in addition to considering the situation of large difference values, another risk situation (too many missing elbow heads) is also considered, thereby improving the comprehensiveness of the operation risk judgment.

[0051] This embodiment also provides a line fault warning system 500 based on online monitoring and analysis of elbow head parameters, see Figure 7The modular schematic diagram of the line fault warning system 500 based on online monitoring and analysis of elbow head parameters is mainly used to divide the functional modules of the line fault warning system 500 based on online monitoring and analysis of elbow head parameters according to the embodiment of the above method. For example, each functional module can be divided, or two or more functions can be integrated into one processing module. The above integrated modules can be implemented in the form of hardware or in the form of software functional modules. It should be noted that the division of modules in the present invention is schematic and is only a logical functional division. There may be other division methods in actual implementation. For example, in the case of dividing each functional module corresponding to each function, Figure 7 What is shown is only a schematic diagram of a system / device, wherein the line fault warning system 500 based on online monitoring and analysis of elbow head parameters may include a first acquisition unit 510, a first calculation unit 520, a first judgment unit 530 and a second calculation unit 540. The functions of each unit module are described below.

[0052] A first acquisition unit 510 is used to acquire line information to be monitored, determine elbow head information in each line, establish an elbow head distribution network based on the elbow head information, and divide all elbow heads in the line into at least one group of associated elbow head groups according to the elbow head distribution network, wherein the elbow head information includes the type, quantity and installation location of the elbow head; The first calculation unit 520 is used to predict the measured temperature information of the missing elbow head in each group of the associated elbow head groups based on the measured temperature information of the online elbow head to obtain the total measured temperature information of the associated elbow head group; and predict the conversion temperature information of the missing elbow head based on the conversion temperature information of the online elbow head to obtain the total conversion temperature information of the associated elbow head group; in an optional embodiment, the first calculation unit 520 is also used to establish a prediction model, obtain the model-predicted conversion temperature information and the actual measured conversion temperature information of the online elbow head, use the difference between the model-predicted conversion temperature information and the actual measured conversion temperature information to optimize and iterate the prediction model, and perform conversion temperature information calculation on the missing elbow head based on the prediction model after optimization and iteration. The model predicts the conversion temperature information, wherein the model predicts the conversion temperature information of the online elbow head obtained by calculating the prediction model; the actually measured conversion temperature information refers to the conversion temperature information of the online elbow head obtained by calculating the heat flow change; and the change conversion temperature information of the missing elbow head during the loss period is obtained, the change conversion temperature information is combined with the predicted conversion temperature information of the missing elbow head to obtain the corrected conversion temperature information, and the total conversion temperature information of the associated elbow head group is calculated based on the corrected conversion temperature information, wherein the change conversion temperature information refers to the information that the temperature of the missing elbow head itself changes due to the change in heat flow caused by the change in its own thermal conductivity and / or thermal contact.

[0053] The first judgment unit 530 is used to judge the operation risk of the line using the online temperature information of at least one group of the associated elbow head groups, wherein the online temperature information includes the total measured temperature information and the total conversion temperature information; in an optional implementation manner, the first judgment unit 530 is also used to determine the online temperature information of each group of the associated elbow head groups, mark the associated elbow head groups whose online temperature information is higher than the warning temperature information as risk-associated elbow head groups, obtain the difference between the online temperature information and the warning temperature information of each group of the risk-associated elbow head groups, obtain multiple sub-difference values, calculate the total difference value based on the sub-difference values, and judge the risk level of the line based on the total difference value.

[0054] The second calculation unit 540 is used to calculate the heat flow change of the online elbow head heat conversion component during the loss period when predicting the conversion temperature information of the missing elbow head based on the conversion temperature information of the online elbow head, and obtain the conversion temperature information of the online elbow head based on the heat flow change. In an optional embodiment, the second calculation unit 540 is also used to determine the area where the heat conversion component performs heat transfer, and obtain the partial heat flow information obtained by each area of ​​the heat conversion component during the loss period; combine all the partial heat flow information to obtain the total heat flow; calculate the heat flow change based on the total heat flow, and calculate the temperature change based on the heat flow change; calculate the conversion temperature information based on the temperature change and the initial temperature of the heat conversion component at the time of loss; and determine the basic partial heat flow and the first change partial heat flow of each area of ​​the heat conversion component during the loss period, based on the The basic partial heat flow and the first change partial heat flow are used to calculate the partial heat flow information, wherein the first change partial heat flow is the heat flow increased or decreased due to the change in thermal conductivity of the heat conversion component caused by temperature change during the loss period; and it is also used to determine the second change partial heat flow of each area of ​​the heat conversion component during the loss period, and the partial heat flow information is calculated based on the basic partial heat flow, the first change partial heat flow and the second change partial heat flow, wherein the second change partial heat flow is the heat flow increased or decreased due to the change in thermal contact area caused by deformation of the heat conversion component due to temperature change during the loss period.

[0055] In the above embodiments, the more specific working process of each functional unit can refer to the corresponding content disclosed in the above embodiments. In addition, each functional unit can be implemented in whole or in part by software, hardware, firmware or any combination thereof. When implemented using software, it can be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on a computer, the process or function described in the embodiment of the present application is generated in whole or in part. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions can be stored in a computer-readable storage medium, or transmitted from one computer-readable storage medium to another computer-readable storage medium. For example, the computer instructions can be transmitted from one website site, computer, server or data center to another website site, computer, server or data center by wired or wireless means. The computer-readable storage medium can be any available medium that a computer can access or a data storage device such as a server or data center that includes one or more available media integrated. The available medium can be a magnetic medium (e.g., a floppy disk, a hard disk, a tape), an optical medium (e.g., a DVD), or a semiconductor medium (e.g., a solid-state hard disk (sol-identified state disk, SSD)), etc.

[0056] The embodiments of the present application are described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0057] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture including an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0058] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process in the computer or other programmable device. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0059] Obviously, those skilled in the art can make various changes and modifications to the embodiments of the present application without departing from the spirit and scope of the present application. Thus, if these modifications and variations of the embodiments of the present application fall within the scope of the claims of the present application and their equivalents, the present application is also intended to include these modifications and variations.

Claims

1. A line fault early warning method based on online monitoring and analysis of elbow head parameters, characterized in that: The steps include: Acquire information of the line to be monitored, determine information of the elbow heads in each line, establish an elbow head distribution network based on the elbow head information, and divide all the elbow heads in the line into at least one group of associated elbow head groups according to the elbow head distribution network, wherein the elbow head information includes the type, quantity and installation position of the elbow heads; In each group of the associated elbow head groups, the measured temperature information of the missing elbow head is predicted based on the measured temperature information of the online elbow head to obtain the total measured temperature information of the associated elbow head group; and the conversion temperature information of the missing elbow head is predicted based on the conversion temperature information of the online elbow head to obtain the total conversion temperature information of the associated elbow head group; Using online temperature information of at least one group of the associated elbow head groups to judge the operation risk of the line, wherein the online temperature information includes total measured temperature information and total converted temperature information; When predicting the conversion temperature information of the missing elbow head based on the conversion temperature information of the online elbow head, the heat flow change of the online elbow head heat conversion component during the missing period is calculated, and the conversion temperature information of the online elbow head is obtained based on the heat flow change.

2. The line fault early warning method based on online monitoring and analysis of elbow head parameters according to claim 1 is characterized in that: The step of calculating the heat flow variation of the online elbow head heat conversion component during the loss period and obtaining the conversion temperature information of the online elbow head based on the heat flow variation comprises the following steps: Determine the area where the heat conversion component performs heat transfer, and obtain the partial heat flow information obtained by each area of ​​the heat conversion component during the loss period; combine all the partial heat flow information to obtain the total heat flow; Calculate the heat flow change based on the total heat flow, and calculate the temperature change according to the heat flow change; The conversion temperature information is calculated based on the temperature change amount and the temperature amount of the heat conversion component at the initial time of loss.

3. The line fault early warning method based on online monitoring and analysis of elbow head parameters according to claim 2 is characterized in that: The step of obtaining the heat flow information of each area of ​​the heat conversion component during the loss period includes the following steps: Determine the basic partial heat flow and the first variable partial heat flow of each area of ​​the heat conversion component during the loss period, and calculate the partial heat flow information based on the basic partial heat flow and the first variable partial heat flow, wherein the first variable partial heat flow is the heat flow increased or decreased due to the change in thermal conductivity caused by the temperature change of the heat conversion component during the loss period.

4. The line fault early warning method based on online monitoring and analysis of elbow head parameters according to claim 3 is characterized in that: The step of obtaining the heat flow information of each area of ​​the heat conversion component during the loss period also includes the following steps: Determine the second changed partial heat flow of each area of ​​the heat conversion component during the loss period, and calculate the partial heat flow information based on the basic partial heat flow, the first changed partial heat flow and the second changed partial heat flow, wherein the second changed partial heat flow is the increase or decrease in heat flow caused by the change in thermal contact area due to deformation of the heat conversion component caused by temperature change during the loss period.

5. The line fault early warning method based on online monitoring and analysis of elbow head parameters according to claim 1 is characterized in that: The step of calculating the change in heat flow of the online elbow-type heat conversion component during the loss period also includes the following steps: Determine a heat flow influence amount, where the heat flow influence amount refers to the heat change data increased or decreased due to the influence of the non-heat conversion component on the heat conversion component during heat transfer; An actual heat flow variation is calculated based on the heat flow influence amount and the heat flow variation amount, and conversion temperature information of the online elbow head is obtained based on the actual heat flow variation amount.

6. The line fault early warning method based on online monitoring and analysis of elbow head parameters according to any one of claims 1 to 5, characterized in that: The method of predicting the conversion temperature information of the missing elbow head based on the conversion temperature information of the online elbow head comprises the following steps: A prediction model is established to obtain the model-predicted conversion temperature information and the actually measured conversion temperature information of the online elbow head, and the difference between the model-predicted conversion temperature information and the actually measured conversion temperature information is used to optimize and iterate the prediction model. Based on the prediction model after optimization and iteration, the conversion temperature information of the missing elbow head is predicted, wherein the model-predicted conversion temperature information refers to the conversion temperature information of the online elbow head obtained by calculating the prediction model; and the actually measured conversion temperature information refers to the conversion temperature information of the online elbow head obtained by calculating the heat flow change.

7. The line fault early warning method based on online monitoring and analysis of elbow head parameters according to claim 6 is characterized in that: The method further includes the following steps after predicting the conversion temperature information of the missing elbow head based on the conversion temperature information of the online elbow head: Obtain the changed conversion temperature information of the missing elbow head during the missing period, merge the changed conversion temperature information with the predicted conversion temperature information of the missing elbow head to obtain corrected conversion temperature information, and participate in the calculation of the total conversion temperature information of the associated elbow head group based on the corrected conversion temperature information, wherein the changed conversion temperature information refers to the information that the temperature of the missing elbow head changes due to changes in its own thermal conductivity and / or thermal contact causing changes in heat flow.

8. The line fault early warning method based on online monitoring and analysis of elbow head parameters according to claim 7 is characterized in that: The method of using the online temperature information of at least one group of the associated elbow head groups to judge the operation risk of the line comprises the following steps: Determine the online temperature information of each group of associated elbow head groups, mark the associated elbow head groups whose online temperature information is higher than the warning temperature information as risk-associated elbow head groups, obtain the difference between the online temperature information and the warning temperature information of each group of risk-associated elbow head groups, obtain multiple sub-difference values, calculate the total difference value based on the sub-difference values, and judge the risk level of the line based on the total difference value.

9. The line fault early warning method based on online monitoring and analysis of elbow head parameters according to claim 8 is characterized in that: Determine the number of missing elbow-type heads in each group of associated elbow-type head groups, and also mark the associated elbow-type head groups with the number of missing elbow-type heads higher than a preset value as risky associated elbow-type head groups.

10. A line fault early warning system based on online monitoring and analysis of elbow head parameters, characterized in that: include: A first acquisition unit, which is used to acquire line information to be monitored, determine elbow head information in each line, establish an elbow head distribution network based on the elbow head information, and divide all elbow heads in the line into at least one group of associated elbow head groups according to the elbow head distribution network, wherein the elbow head information includes the number and installation position of the elbow heads; A first calculation unit is used to predict the measured temperature information of the missing elbow head in each group of the associated elbow head groups based on the measured temperature information of the online elbow head to obtain the total measured temperature information of the associated elbow head group; and predict the conversion temperature information of the missing elbow head based on the conversion temperature information of the online elbow head to obtain the total conversion temperature information of the associated elbow head group; A first judgment unit, which is used to judge the operation risk of the line using online temperature information of at least one group of the associated elbow head groups, wherein the online temperature information includes total measured temperature information and total converted temperature information; The second calculation unit is used to calculate the heat flow change of the online elbow head heat conversion component during the missing period when predicting the conversion temperature information of the missing elbow head based on the conversion temperature information of the online elbow head, and obtain the conversion temperature information of the online elbow head based on the heat flow change.

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