Intelligent substation process layer network disconnection fault analysis device

Abstract

The application relates to the technical field of network disconnection fault positioning, and discloses an intelligent substation process layer network disconnection fault analysis device which comprises a dynamic monitoring module, a static analysis module and a prewarning display module; the dynamic monitoring module is used for detecting whether the process layer network port running state is abnormal at the device node interface end in real time; the static analysis module is used for receiving information at the receiving end and analyzing the process layer network fault causes and positioning fault point coordinates; and the prewarning display module is used for displaying the fault analysis results, predicting the probability of the next fault occurrence on the basis of the static analysis, and reminding and displaying the coordinate position of the next fault point occurrence. The process layer network interface running state is judged through the monitoring of the device node end, a "point-chain" network distribution graph model is constructed, historical fault data and online real-time data are compared and analyzed, the time for manually checking faults can be effectively shortened, and the fault processing efficiency can be directly and effectively improved.

Description

TECHNICAL FIELD

[0001] The application relates to the technical field of network disconnection fault positioning, and particularly relates to an intelligent substation process layer network disconnection fault analysis device. BACKGROUND

[0002] The intelligent substation is a substation which adopts advanced, reliable, integrated, low-carbon and environment-friendly intelligent devices, and automatically completes basic functions such as information collection, measurement, control, protection, metering and monitoring according to the basic requirements of information digitization, communication platform networking and information sharing standardization, and can support real-time automatic control, intelligent adjustment, online analysis and decision-making, and collaborative interaction of the power grid and other advanced functions. In recent years, great progress has been made in the research and construction of intelligent substations in China. The intelligent substation is an intelligent node of the smart grid and plays a basic role in the research and implementation of the smart grid. Hundreds of intelligent substations have been constructed as pilot projects in various parts of the country. According to the current operation conditions of the intelligent substations that have been put into operation, the faults and problems of the intelligent substations generally occur in the process layer of the intelligent substations. The process layer network is a network connecting the process layer devices and the bay layer devices, and is generally an optical fiber network. The connection of the digital devices of the intelligent substation in the process layer is a digital network information interaction formed by GOOSE and SV networks. Once the GOOSE disconnection or SV disconnection alarm occurs in the intelligent substation, experienced technical personnel can quickly determine the fault point, but ordinary technical personnel have no idea where to start when searching for faults. At present, when the SV or GOOSE link interruption occurs, the process layer messages are directly captured for manual analysis. Since the SV and GOOSE message flow is huge, it is extremely inefficient to rely on manual checking of a large number of messages, and the accuracy cannot be guaranteed. In particular, for some occasional or irregular faults, it is more difficult for human to intercept fault information. Therefore, in order to enable the process layer of the intelligent substation to operate safely and reliably, it is necessary and urgent to analyze the network disconnection fault of the process layer of the substation.

[0003] The prior art mainly analyzes whether the fault and the abnormality exist based on the network message analyzer, but cannot analyze the causes and positions of the fault and the abnormality. It can be seen that the function of the current network message analyzer is limited to alarming the abnormality and the fault in the network, but the troubleshooting and the cause analysis of the final fault are completed by the operation personnel. However, the amount of data displayed by the system is huge and mixed, especially when a device port or link fault occurs to cause information transmission interruption, the large amount of sudden alarm information displayed by the system will make the operation personnel have no idea where to start, so that the fault diagnosis and analysis process excessively depends on the on-site experience of the manufacturer and the operation personnel, which brings great challenges to the safe and reliable operation of the secondary system of the intelligent substation. SUMMARY

[0004] The application aims to provide a smart substation process layer network disconnection fault analysis device, which can effectively filter out effective information of substation network disconnection fault by monitoring equipment node end to judge process layer network interface running state, constructing a "point-chain" network distribution diagram model, comparing and analyzing historical fault data and online real-time data, effectively shortening the time of manual fault troubleshooting, and can effectively improve the efficiency of fault processing by extracting fault node address according to effective coding information and positioning fault points.

[0005] To achieve the above object, the application provides the following technical scheme.

[0006] The application provides a smart substation process layer network disconnection fault analysis device, which comprises a dynamic monitoring module, a static analysis module and a pre-warning display module.

[0007] As a further scheme of the application, the dynamic monitoring module comprises a controller, an optical power meter, a temperature sensor and a voltage sensor.

[0008] As a further scheme of the present application: the static analysis module locates the process layer network fault point based on a "point-chain" hierarchical positioning model, including "point" positioning, "chain" positioning and model analysis; the "point" positioning can filter out abnormal running equipment node numbers based on the node equipment monitoring data of the dynamic monitoring module combined with historical fault occurrence data; firstly, the "point" positioning extracts the optical power value in the controller, and if the detected optical power value is lower than the threshold value, it indicates that there is a fault point in the optical fiber network, and the node equipment numbers are recorded as 1, 2, 3, …, n; based on the equipment node numbers, the node equipment involved in the optical fiber network fault point can be quickly found; then the equipment running temperature and running voltage in the controller are further extracted to screen the node equipment; if the extracted data is too different from the last transmission data and has the same data trend compared with the historical fault data, it indicates that the node equipment is a fault node equipment.

[0009] As a further scheme of the present application: due to the mutual communication between the node equipments, there are multiple optical fiber links in a certain node equipment; on the basis of determining the fault node equipment, the "chain" positioning is used to locate the coordinates of the fault optical fiber link; by receiving the process layer SV and GOOSE data, and screening and analyzing the SV and GOOSE fault messages, abnormal data are extracted for fault optical fiber link positioning, wherein the optical fiber link numbers are recorded as L n1 , L n2 , L n3 , …, L nm , n is the node equipment number; if the link fails, it involves the mutual connection between the sending end and the receiving end, so the correlation analysis is performed on the node equipment involved in the screening and analysis of the SV and GOOSE fault messages; if the two fault node equipments have correlation, it indicates that the fault occurs on the optical fiber of the port of the two node equipments; based on this, the fault optical fiber network chain positioning coordinates can be obtained.

[0010] As a further scheme of the present application: based on the fact that the process layer network of the intelligent substation is in a dynamic running state and each link is in a different load running state, the model analysis is set to construct the process layer optical fiber network chain distribution model; the connection relationship between the nodes is introduced based on the node equipment distribution points; the load margin of the link is determined according to the dynamic change data in the dynamic monitoring module; the network chain running threshold value is set based on the transmission distance between the node equipments; the network chain running margin is determined by comparing the real-time monitoring data with the set threshold value; according to the margin, the network chain can be protected by breaking the circuit in time, and the network chain can be regulated and repaired in time, so as to prevent regional network collapse due to the running failure of a certain link.

[0011] As a further scheme of the present application: the early warning display module is used for displaying the fault positioning result of the static analysis module while predicting the operation fault probability of other links, comprising a display, a probability prediction, and a fault point prediction.

[0012] As a further scheme of the present application: the display is used for visualizing the fault analysis result and the prediction result, and respectively displaying the alarm point and the early warning point, the result visualization has a guiding effect on fault maintenance to some extent, and avoids increasing the maintenance time due to the unfamiliarity of the maintenance personnel with the route, the probability prediction is based on the network chain model in the model analysis to predict the fault probability of the existing network chain, because there is a complex interaction relationship between each network chain, the network chain has an important influence on other links when the network chain fails, the correlation between the fault link and other links is analyzed by using the logical relationship between each network chain, the higher the correlation is, the higher the probability of the link failure is, the probability prediction is divided into different probability levels according to the correlation size, the link with a higher possibility of fault probability has a priority protection level, that is, the link can be preferentially protected and repaired, because the distances of the fiber links are different, the probabilities of the faults occurring on the links are still different, so the fault point prediction is set to predict the fault point occurrence probability of the network chain, mainly by setting a timing device at the interface of the sending end and the receiving end, judging the optical fiber line state change according to the time change of the received data and the link optical power size change fluctuation measured by the optical power meter, and setting a inflection point detection device for the optical fiber line with a transmission inflection point, mainly because the bending of the transmission route can easily affect the transmission signal rate, and can even cause fiber transmission blockage failure.

[0013] As a further scheme of the present application, an intelligent substation process layer network chain breakage fault analysis device comprises the following analysis process:

[0014] Step 1: first, real-time monitoring of process layer network link interface operation data, respectively arranging controllers, optical power meters, temperature sensors, and voltage sensors at each node device, the controller is used for controlling the operation scheduling and data acquisition of other monitoring devices, and numbering the monitoring points of each node device, and transmitting the monitoring point detection data to the static analysis module, the optical power meter is used for monitoring the optical power value of the optical fiber network chain to represent the stability of the communication transmission of the optical fiber network chain, the temperature sensor is used for detecting the equipment operation temperature to prevent the equipment from being damaged due to overload operation caused by high operation temperature, and the voltage sensor is used for real-time monitoring of the node device operation voltage value, and the input / output current stability of the device interface can be judged by measuring the voltage value.

[0015] Step 2: After the monitoring device arrangement in the dynamic monitoring module is completed, the node-network chain layout parameters are integrated to construct the process layer network model. First, the SCD (substation configuration description) file is imported to parse the SV and GOOSE fault messages. Second, the connection relationship between nodes is imported based on the node device distribution points, and the process layer optical fiber network chain distribution model is constructed according to the transmission distance between node devices and the basic parameters of node devices. The location of the network link failure is alarmed.

[0016] The step 2 further includes:

[0017] Step 2-1: Based on the node device monitoring data of the dynamic monitoring module and the historical fault occurrence data, the abnormal operation device node number is screened out to locate the fault occurrence area. First, the optical power value in the controller is extracted. If the detected optical power value is lower than the threshold value, it indicates that there is a fault point in the optical fiber network. The node device numbers are recorded as 1, 2, 3, …, n. Based on the device node number, the node devices involved in the optical fiber network fault point can be quickly found. Then the device operating temperature and operating voltage in the controller are further extracted to screen the node devices. If the extracted data is significantly different from the last transmission data and has the same data trend compared with the historical fault data, it indicates that the node device is a fault node device.

[0018] Step 2-2: Based on the determination of the fault node device, the "chain" positioning of the fault occurrence area is performed. By receiving the process layer SV and GOOSE data, and screening and analyzing the SV and GOOSE fault messages, abnormal data is extracted for fault optical fiber link positioning. The optical fiber link numbers are recorded as L n1 , L n2 , L n3 , …, L nm , n. If the link fails, it involves the mutual connection between the sending end and the receiving end. Therefore, while screening and analyzing the SV and GOOSE fault messages, the related analysis of the node devices involved is performed. If there is a correlation between the two fault node devices, it indicates that the fault occurs on the optical fiber of the port of the two node devices. Based on this, the fault optical fiber network chain positioning coordinates can be obtained.

[0019] Step 3: While performing fault analysis and positioning on the fault occurrence area, the running failure probability of other links is predicted, and based on the analysis of the static analysis module, the probability of the next fault occurrence is predicted, and the coordinate position of the next fault point is warned.

[0020] The step 3 further includes:

[0021] Step 3-1: On the basis of the process layer fiber optic network chain distribution model, the load margin of the link is determined according to the dynamic change data in the dynamic monitoring module, the network chain operation threshold is set based on the transmission distance between node devices, the real-time monitoring data is compared with the set threshold to determine the network chain operation margin, and the network chain can be protected and regulated and repaired in time according to the margin, so as to prevent regional network collapse caused by the operation failure of a link;

[0022] Step 3-2: On the basis of the network chain model, the fault probability of the existing network chain is predicted, because there is a complex interaction relationship between the network chains, so when the network chain fails, it has an important influence on other links, the correlation between the fault link and other links is analyzed by using the logical relationship between the network chains, the higher the correlation, the higher the probability of link failure, the probability prediction is divided into different probability levels according to the correlation size, and the link with higher fault probability has a priority protection level, that is, it can preferentially protect and repair other links without failure;

[0023] Step 3-2: Because the distances of the fiber links are different, the probabilities of failure on the links are also different, so the fault point prediction is set to predict the probability of the fault point of the network chain, mainly by setting a timing device at the interface of the sending end and the receiving end, judging the state change of the optical fiber line according to the time change of the received data and the size change fluctuation of the link optical power measured by the optical power meter, and setting a inflection point detection device for the optical fiber line with a transmission inflection point, mainly because the bending of the transmission route can easily affect the transmission signal rate, and serious can cause optical fiber transmission jam failure.

[0024] Step 4: The display visualizes the fault analysis result and the prediction result, and displays the alarm point and the early warning point respectively, and the result visualization has a guiding effect on fault repair to some extent, avoiding the increase of repair time due to the unfamiliarity of repair personnel with the route.

[0025] Compared with the prior art, the beneficial effects of the present application are:

[0026] By judging the process layer network interface operation state through the monitoring device node end, a "point-chain" network distribution graph model is constructed, effective information of the substation network chain fault can be effectively screened out by comparing and analyzing the historical fault data and the online real-time data, the time for manual fault checking can be effectively shortened, the causes and fault points of the occurred faults are counted and coded, the fault node address is extracted according to the effective coded information, the fault point is located, and the efficiency of fault handling can be directly and effectively improved. BRIEF DESCRIPTION OF DRAWINGS

[0027] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings needed to be used in the embodiments or prior art description will be briefly introduced as follows. Obviously, the drawings in the following description are only some embodiments of the present application, and other drawings can be obtained by those skilled in the art without any creative effort based on these drawings.

[0028] Figure 1 It is a structure schematic view of a kind of intelligent substation process layer network chain break fault analysis device.

[0029] In the figure: 1, dynamic monitoring module;2, static analysis module;3, early warning display module;11, controller;12, optical power meter;13, temperature sensor;14, voltage sensor;21, "point" positioning;22, "chain" positioning;23, model analysis;31, display;32, probability prediction;33, fault point prediction. DETAILED DESCRIPTION

[0030] In order to make the technical problems to be solved by the present application, technical solutions and beneficial effects more clearly, the present application will be further described in detail below in combination with drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and not used to limit the present application.

[0031] Embodiment:

[0032] Please refer to Figure 1The embodiment of the application discloses an intelligent substation process layer network disconnection fault analysis device, which comprises a dynamic monitoring module (1), a static analysis module (2) and a warning display module (3). The dynamic monitoring module (1) is used for detecting whether the running state of a process layer network port is abnormal at a device node interface end in real time, and comprises a controller (11), an optical power meter (12), a temperature sensor (13) and a voltage sensor (14). The controller (11) is used for controlling the running scheduling and data acquisition of other monitoring devices, numbering each node device monitoring point and transmitting the monitoring point detection data to the static analysis module (2). The optical power meter (12) is used for monitoring the optical power value of an optical fiber network chain to represent the stability of communication transmission of the optical fiber network chain. The temperature sensor (13) is used for detecting the device running temperature to prevent the device from being damaged due to overload operation caused by excessively high running temperature. The voltage sensor (14) is used for monitoring the node device running voltage value in real time. The voltage value can be determined to judge the input / output current stability of the device interface. The static analysis module (2) is used for receiving information at a receiving end and analyzing and processing the data information to analyze the process layer network fault reason and locate the fault point coordinates. The process layer network fault point is located based on a "point-chain" hierarchical positioning model, which comprises "point" positioning (21), "chain" positioning (22) and model analysis (23). The "point" positioning (21) can filter out abnormal running device node numbers based on the node device monitoring data of the dynamic monitoring module (1) and historical fault occurrence data. First, the "point" positioning (21) extracts the optical power value in the controller (11). If the detected optical power value is lower than a threshold value, it indicates that there is a fault point in the optical fiber network, and the node device numbers are recorded as 1, 2, 3, …, n. Based on the device node numbers, the node device involved in the optical fiber network fault point can be quickly found. Then, the device running temperature and running voltage in the controller (11) are further extracted to screen the node device. If the extracted data is greatly different from the last transmission data and has the same data trend compared with the historical fault data, it indicates that the node device is a fault node device. Since the node devices are interconnected, there are multiple optical fiber links in a certain node device. Based on the determined fault node device, the "chain" positioning (22) is used for locating the coordinates of the fault optical fiber link. The process layer SV and GOOSE data are received, the SV and GOOSE fault packets are screened and analyzed, the abnormal data are extracted, and the fault optical fiber link is located. The optical fiber link numbers are recorded as L n1 , L n2 , L n3 , …, L nm, n is the node device number, if the link fails, the mutual connection between the sending end and the receiving end is involved, so the correlation analysis is performed on the node devices involved in the filtering and analysis of the SV and GOOSE fault messages, if the two fault node devices have correlation, it indicates that the fault occurs on the optical fiber of the ports of the two node devices, based on this, the fault optical fiber network chain positioning coordinates can be obtained, based on the fact that the process layer network of the smart substation is in a dynamic running state and each link is in a different load running state, a model analysis (23) is provided to construct the process layer optical fiber network chain distribution model, the connection relationship between the nodes is imported based on the node device distribution point, the load margin of the link is determined according to the dynamic change data in the dynamic monitoring module (1), the network chain running threshold is set based on the transmission distance between the node devices, the real-time monitoring data is compared with the set threshold to determine the network chain running margin, according to the margin, the network chain can be protected and controlled and repaired in time, to prevent regional network collapse due to the running failure of a link, the early warning display module (3) is used to display the fault analysis result and predict the probability of the next fault occurrence and remind the coordinate position of the next fault point, including a display (31), a probability prediction (32) and a fault point prediction (33), the display (31) is used to visualize the fault analysis result and the prediction result, and the alarm point and the early warning point are displayed respectively, the result visualization has a guiding effect on fault repair to some extent, which avoids increasing the repair time due to the unfamiliarity of the repair personnel with the route, the probability prediction (32) predicts the fault probability of the existing network chain based on the network chain model in the model analysis (23), because there is a complex interaction relationship between the network chains, so the failure of a network chain has an important influence on other links, the correlation between the fault link and other links is analyzed by using the logical relationship between the network chains, the higher the correlation, the higher the probability of link failure, the probability prediction (32) is divided into different probability levels according to the correlation, the link with a higher probability of fault occurrence has a priority protection level, that is, it can perform priority protection repair on other links that have not failed, because the distances of the optical fiber links are different, the probabilities of failure on the links are still different, so the fault point prediction (33) is provided to predict the probability of the fault point of the network chain, mainly by setting a timing device at the interface of the sending end and the receiving end, judging the state change of the optical fiber line according to the time change of the received data and the size change fluctuation of the link optical power measured by the optical power meter (12), and setting a inflection point detection device for the optical fiber line with a transmission inflection point, mainly because the bending of the transmission route can easily affect the transmission signal rate, and serious can cause optical fiber transmission jam failure

[0033] The application also provides an analysis process of the smart substation process layer network chain fault analysis device, and the specific steps are as follows:

[0034] Step 1: First, real-time monitoring of process layer network link interface operation data, respectively, in each node device controller, optical power meter, temperature sensor, voltage sensor, the controller is used to control the operation schedule and data acquisition of other monitoring devices and number the node device monitoring points, the monitoring point detection data is transmitted to the static analysis module, the optical power meter is used to monitor the optical power value of the optical fiber network chain to characterize the stability of the communication transmission of the optical fiber network chain, the temperature sensor is used to detect the equipment operating temperature, to prevent the equipment from being damaged due to overload operation caused by high operating temperature, the voltage sensor is used to monitor the node device operating voltage value in real time, the input / output current stability of the device interface can be judged by measuring the voltage value.

[0035] Step 2: After the dynamic monitoring module is arranged, the process layer network model is constructed by integrating the node-network chain layout parameters, first, the SCD (substation configuration description) file is imported to parse the SV, GOOSE fault message, and second, the connection relationship between nodes is imported based on the node device distribution point, and the process layer optical fiber network chain distribution model is constructed according to the transmission distance between node devices and the basic parameters of node devices, and the position of network link failure is alarmed.

[0036] The step 2 further comprises:

[0037] Step 2-1: Based on the node device monitoring data of the dynamic monitoring module and the historical fault occurrence data, the abnormal operation device node number is screened out to locate the fault area, first, the "point" positioning will extract the optical power value in the controller, if the detected optical power value is lower than the threshold value, it indicates that there is a fault point in the optical fiber network, the node device number is recorded as 1, 2, 3, …, n, based on the device node number, the node device involved in the optical fiber network fault point can be quickly found, then the device operating temperature and operating voltage in the controller are further extracted to screen the node device, if the extracted data is too different from the last transmission data and there is the same data trend compared with the historical fault data, it indicates that the node device is a fault node device;

[0038] Step 2-2: Based on the determination of the fault node device, the "chain" positioning of the fault area is carried out, by receiving the process layer SV, GOOSE data, and screening and analyzing the SV, GOOSE fault message, the abnormal data is extracted to locate the fault optical fiber link, wherein the optical fiber link number is recorded as L n1 , L n2 , L n3 , …, L nm, n is the node device number, if the link fails, the mutual connection between the sending end and the receiving end is involved, so the correlation analysis is performed on the node devices involved in the filtering and analysis of the SV and GOOSE fault messages, if the two fault node devices have correlation, it indicates that the fault occurs on the optical fiber of the ports of the two node devices, based on this, the fault optical fiber network chain positioning coordinates can be obtained.

[0039] Step 3: While analyzing the fault area for fault analysis and positioning, the running failure probability of other links is predicted, and based on the analysis of the static analysis module, the probability of the next fault occurrence is predicted, and the coordinate position of the next fault point is warned.

[0040] The step 3 further comprises:

[0041] Step 3-1: Based on the process layer optical fiber network chain distribution model, the load margin of the link is determined according to the dynamic change data in the dynamic monitoring module, the network chain running threshold is set based on the transmission distance between the node devices, the real-time monitoring data is compared with the set threshold to determine the network chain running margin, according to the margin, the network chain can be protected and repaired in time, and regional network collapse caused by running failure of a link can be prevented;

[0042] Step 3-2: Based on the network chain model, the fault probability of the existing network chain is predicted, because there are complex interaction relationships between the network chains, when the network chain fails, it has an important influence on other links, the correlation between the fault link and other links is analyzed by using the logical relationship between the network chains, the higher the correlation, the higher the probability of link failure, the probability prediction is divided into different probability levels according to the correlation, the link with higher probability of fault probability has priority protection level, that is, it can give priority to the protection and repair of other links that have not failed;

[0043] Step 3-2: Because the optical fiber link has different transmission distances, the probability of failure on the link is still different, so the fault point prediction is set to predict the probability of fault point occurrence of the network chain, mainly through the interface of the sending end and the receiving end, the time change of the received data and the size change fluctuation of the link optical power measured by the optical power meter are used to judge the state change of the optical fiber line, and the inflection point detection device is set for the optical fiber line with transmission inflection point, mainly the bending of the transmission route can affect the transmission signal rate, and serious can cause optical fiber transmission jam failure.

[0044] Step 4: The display visualizes the fault analysis result and the prediction result, and displays the alarm point and the early warning point respectively, the result visualization has a guiding effect on fault repair to some extent, and avoids increasing the repair time due to the unfamiliarity of the repair personnel with the route.

[0045] The working principle of the present application is: judging the running state of the process layer network interface through the monitoring device node end to build a "point-chain" network distribution model, comparing and analyzing the historical fault data and online real-time data can effectively screen out the effective information of the substation network chain breakage fault, which can effectively shorten the time of manual troubleshooting, and the causes and fault points of the occurred faults are statistically coded, the fault node address is extracted according to the effective coding information to locate the fault point, which can directly and effectively improve the efficiency of fault handling.

[0046] The above is only the preferred specific embodiment of the present application, but the protection scope of the present application is not limited to this, any person skilled in the art can make equivalent replacement or change according to the technical scheme and the inventive concept of the present application within the technical range disclosed by the present application, which should be covered in the protection scope of the present application.

Claims

1. An intelligent substation process level network break fault resolution apparatus, comprising: It comprises a dynamic monitoring module (1), a static analysis module (2) and a pre-warning display module (3), the dynamic monitoring module (1) is used for detecting whether the running state of the process layer network port is abnormal at the device node interface end in real time, the static analysis module (2) is used for receiving information at the receiving end and analyzing and processing data information to analyze the process layer network fault cause and locate the fault point coordinate, and the pre-warning display module (3) is used for displaying the fault analysis result, predicting the probability of the next fault occurrence and reminding the coordinate position of the next fault point occurrence on the basis of the analysis of the static analysis module (2). The dynamic monitoring module (1) comprises a controller (11), an optical power meter (12), a temperature sensor (13) and a voltage sensor (14), the controller (11) is used for controlling the operation scheduling and data acquisition of other monitoring devices, numbering the node device monitoring points and transmitting the monitoring point detection data to the static analysis module (2), the optical power meter (12) is used for monitoring the optical power value of the optical fiber network chain to represent the stability of the communication transmission of the optical fiber network chain, the temperature sensor (13) is used for detecting the device running temperature to prevent the device from being damaged due to overload operation caused by excessively high running temperature, and the voltage sensor (14) is used for monitoring the node device running voltage value in real time to judge the input / output current stability of the device interface by measuring the voltage value; the static analysis module (2) is based on a "point-chain" hierarchical positioning model to locate the process layer network fault point, comprising "point" positioning (21), "chain" positioning (22) and model analysis (23), the "point" positioning (21) screens out abnormal running device node numbers based on the node device monitoring data of the dynamic monitoring module (1) and historical fault occurrence data, first, the "point" positioning (21) extracts the optical power value in the controller (11), if the detected optical power value is lower than the threshold value, it indicates that there is a fault point in the optical fiber network, and the node device numbers are recorded as 1, 2, 3, …, n, based on the device node numbers, the node device involved in the optical fiber network fault point is quickly found out, then the device running temperature and running voltage in the controller (11) are further extracted to screen the node device, if the extracted data is greatly different from the last transmission data and has the same data trend compared with the historical fault data, it indicates that the node device is a fault node device; Since there are multiple fiber links between the node devices due to the interconnection of the node devices, on the basis of determining the faulty node device, the "chain" positioning (22) is used to locate the coordinates of the faulty fiber link, by receiving process layer SV, GOOSE data, and screening and analyzing SV, GOOSE fault messages, extracting abnormal data for fault fiber link positioning, wherein the fiber link number is L n1 , L n2 , L n3 , ……, L nm , n is the node device number, if the link fails, the interconnection between the sending end and the receiving end is involved, so the node devices involved are analyzed for correlation while the SV, GOOSE fault messages are screened and analyzed, if the two faulty node devices have correlation, it indicates that the fault occurs on the fiber of the ports of the two node devices, and the fault fiber network chain positioning coordinates are obtained. 2.The intelligent substation process level network break fault analysis device of claim 1, wherein, The pre-warning display module (3) is used for displaying the fault positioning result of the static analysis module (2) and predicting the running fault probability of other links, comprising a display (31), a probability prediction (32) and a fault point prediction (33). 3.The intelligent substation process level network break fault analysis device of claim 2, wherein, The display (31) is used for visualizing the fault analysis result and the prediction result, and respectively displaying the alarm point and the early warning point. The result visualization has a guiding effect on the fault maintenance to some extent, and avoids increasing the maintenance time due to the unfamiliarity of the maintenance personnel with the route. The probability prediction (32) is used for predicting the fault probability of the existing network chain fault on the basis of the network chain model in the model analysis (23). Since there is a complex interaction relationship between each network chain, the network chain has an important influence on other links when the network chain fails. The logical relationship between each network chain is used to analyze the correlation between the fault link and other links. The higher the correlation is, the higher the probability of the link failure is. The probability prediction (32) is divided into different probability levels according to the correlation size. The link with the higher probability of the fault probability occurrence has a priority protection level, that is, the link can perform the priority protection repair on other links without failure. Since the optical fiber link distances are different, the probabilities of the failure occurring on the links are still different. Therefore, the fault point prediction (33) is arranged to predict the probability of the fault point of the network chain. The timing device is arranged at the interface of the sending end and the receiving end. The optical power meter (12) is used for judging the state change of the optical fiber line according to the time change of the received data and the size change fluctuation of the link optical power measured by the optical power meter (12). The inflection point detection device is arranged on the optical fiber line with the transportation inflection point. The main function of the inflection point detection device is to prevent the bending of the transmission route from affecting the transmission signal rate, and to prevent the optical fiber transmission from being blocked and failing.

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