A power supply business data monitoring method and system based on a large model

Abstract

The application is suitable for the technical field of power supply service monitoring, and particularly relates to a power supply service data monitoring method and system based on a large model, which comprises the following steps: delimiting a monitoring area of power supply service data, selecting a monitoring subject, determining a distribution route of a distributed optical fiber, connecting one end of the distributed optical fiber to a signal transceiver, collecting sensing data by using a sensing device pre-installed on the monitoring subject, and creating a fluctuation range corresponding to the sensing device by using historical fluctuations of the sensing data; and installing a variable resistor at the sensing device, wherein the distributed optical fiber is bonded with the variable resistor. The application can eliminate false alarms caused by normal production fluctuations by setting a time delay circuit breaker, accurately identify and respond to real abnormalities, thereby greatly improving the stability and reliability of power supply service data monitoring, ensuring the safe and stable operation of power supply equipment, and effectively reducing operation and maintenance costs.

Description

Technical Field

[0001] This invention relates to the field of power supply service monitoring technology, and in particular to a power supply service data monitoring method and system based on a large model. Background Technology

[0002] In the process of monitoring power supply business data, thermal imaging technology or sensors are usually used to locate abnormal equipment. Since the monitoring scope usually involves multiple lines, substations and other key nodes, the coverage area is wide and the operating status of various equipment is complex. Although thermal imaging technology can capture the surface temperature distribution of equipment in real time and identify overheating or abnormal hot spots, the thermal imaging range is limited and cannot cover all equipment and lines. If sensors are used for monitoring, all sensors must be connected to the control system to transmit, process and manage the collected sensor data in a unified manner, which will increase the difficulty of hardware deployment and maintenance costs.

[0003] Therefore, "how to combine distributed optical fibers and sensing devices for comprehensive anomaly monitoring" is the technical problem that this invention aims to solve. Summary of the Invention

[0004] The purpose of this invention is to provide a power supply service data monitoring method and system based on a large model, so as to solve the problem of "how to combine distributed optical fibers and sensing devices to perform blind-spot-free anomaly monitoring" mentioned in the background art.

[0005] To achieve the above objectives, the present invention provides the following technical solution: A method for monitoring power supply service data based on a large model, the method comprising: Define the monitoring area for power supply business data, select the monitoring subject, determine the deployment route of distributed optical fiber, connect one end of the distributed optical fiber to the signal transceiver, use the sensing devices pre-installed on the monitoring subject to collect sensing data, and use the historical fluctuations of the sensing data to create a fluctuation range that corresponds one-to-one with the sensing devices. A variable resistor is installed at the sensing device, wherein the distributed optical fiber is bonded to the variable resistor. When the sensing data exceeds the fluctuation range, the deviation value is recorded, the variable resistor is activated, the resistance value of the variable resistor is collected, and a positive correlation between the deviation value and the resistance value is established. Calculate the distance from each variable resistor to the signal transceiver, start the signal transceiver, inject pulsed light signals into the distributed optical fiber, obtain feedback information, locate the abnormal subject through the distance, generate a monitoring report, and send it to the preset terminal; From the monitoring subject, a disturbance subject is defined, and a bypass channel is set at the variable resistor of the disturbance subject. A time-delay circuit breaker is installed in the bypass channel. An application strategy is generated and written into the time-delay circuit breaker.

[0006] Furthermore, the steps of defining the monitoring area for power supply service data, selecting the monitoring subject, and determining the deployment route of distributed optical fibers include: Draw a diagram of the equipment layout within the monitored area and mark the main monitoring components; Set the risk level for each monitored entity, create a cabling strategy that corresponds one-to-one with the risk level, and adjust the cabling route.

[0007] Furthermore, the step of creating a fluctuation range corresponding one-to-one with the sensing device based on the historical fluctuations of the sensing data includes: Acquire historical values ​​of sensor data and sort them in ascending order to build a queue; Remove outliers from the queue, combine the minimum and maximum values ​​in the queue, and generate a fluctuation range.

[0008] Furthermore, the step of installing a variable resistor at the sensing device includes: The number and type of variable resistors are configured according to the risk level of the monitored entity; When the deviation value is greater than the threshold, the variable resistor is adjusted to the maximum resistance value.

[0009] Furthermore, the steps of calculating the distance from each variable resistor to the signal transceiver, activating the signal transceiver, injecting pulsed optical signals into the distributed optical fiber, and obtaining feedback information include: By integrating all sensor data, defining a standard time, collecting feedback information at the standard time, and obtaining background noise; A noise baseline model is created, and the feedback information is preprocessed.

[0010] Furthermore, the steps of defining a disturbance subject from the monitoring subject, setting a bypass channel at the variable resistor of the disturbance subject, wherein a time-delay circuit breaker is installed in the bypass channel, generating an application strategy, and writing it into the time-delay circuit breaker include: An interrupt mechanism is embedded in the time-delay circuit breaker, which is triggered when the sensor data re-enters the fluctuation range. The start and stop times of the variable resistor and the time-delay circuit breaker are recorded, a monitoring log is generated, and stored in the sensing device.

[0011] Furthermore, the system includes: The delineation module is used to delineate the monitoring area of ​​power supply business data, select the monitoring subject, determine the deployment route of distributed optical fiber, connect one end of the distributed optical fiber to the signal transceiver, use the sensing devices pre-installed on the monitoring subject to collect sensing data, and use the historical fluctuations of the sensing data to create a fluctuation range that corresponds one-to-one with the sensing devices. A module is established to install a variable resistor at the sensing device, wherein the distributed optical fiber is bonded to the variable resistor. When the sensing data exceeds the fluctuation range, the deviation value is recorded, the variable resistor is activated, the resistance value of the variable resistor is collected, and a positive correlation between the deviation value and the resistance value is established. The calculation module is used to calculate the distance from each variable resistor to the signal transceiver, start the signal transceiver, inject pulse light signals into the distributed optical fiber, obtain feedback information, locate the abnormal subject through the distance, generate a monitoring report, and send it to the preset terminal. The writing module is used to define the disturbance subject from the monitoring subject, set a bypass channel at the variable resistor of the disturbance subject, wherein a time delay circuit breaker is installed in the bypass channel, generate an application strategy, and write it into the time delay circuit breaker.

[0012] Furthermore, the delineation module includes: The drawing unit is used to draw the equipment layout diagram within the monitored area and mark the main monitoring objects; The configuration unit is used to set the risk level of each monitored entity, create a wiring strategy that corresponds one-to-one with the risk level, and adjust the wiring route. The sorting unit is used to acquire historical values ​​of sensor data and sort them in ascending order to build a queue; The deletion unit is used to remove outliers from the queue, integrate the minimum and maximum values ​​in the queue, and generate a fluctuation range.

[0013] Furthermore, the establishment module includes: A configuration unit is used to configure the number and type of variable resistors based on the risk level of the monitored entity; An adjustment unit is used to adjust the variable resistor to its maximum resistance value when the deviation value is greater than a threshold value.

[0014] Furthermore, the computing module includes: The unit is used to integrate all sensor data, define a standard time, collect feedback information at the standard time, and obtain background noise. A preprocessing unit is used to create a noise baseline model and preprocess the feedback information.

[0015] Compared with the prior art, the beneficial effects of the present invention are: By deploying distributed optical fibers, comprehensive heat source monitoring of the monitored entity can be achieved, enabling early detection of hidden faults and precise location of anomalies. This significantly improves the monitoring scope and efficiency of power supply business data. Collecting sensor data allows for visualized monitoring of the monitored entity's operational status, providing a data foundation for fault early warning and prediction. Variable resistors can be used to promptly send abnormal signals to preset terminals even when sensors are not connected to the network, simplifying the monitoring architecture, reducing hardware construction and maintenance difficulties, and greatly simplifying data processing. Delayed circuit breakers eliminate false alarms caused by normal production fluctuations, enabling accurate identification and tiered response to genuine anomalies. This significantly improves the stability and reliability of power supply business data monitoring, ensuring the safe and stable operation of power supply equipment and effectively reducing maintenance costs. Attached Figure Description

[0016] Figure 1 A flowchart illustrating the power supply service data monitoring method based on a large model provided in this embodiment of the invention; Figure 2 The first sub-flow flowchart of the power supply service data monitoring method based on a large model provided in the embodiments of the present invention; Figure 3 The second sub-flow flowchart of the power supply service data monitoring method based on a large model provided in the embodiments of the present invention; Figure 4 The third sub-flow flowchart of the power supply service data monitoring method based on a large model provided in the embodiments of the present invention; Figure 5 The fourth sub-process flowchart of the power supply service data monitoring method based on a large model provided in the embodiments of the present invention; Figure 6 A block diagram illustrating the composition of a power supply service data monitoring system based on a large model, as provided in an embodiment of the present invention. Figure 7 A block diagram illustrating the composition of the delineation module in the power supply service data monitoring system based on a large model, as provided in an embodiment of the present invention. Figure 8 A block diagram illustrating the components of a module in a power supply service data monitoring system based on a large model, as provided in an embodiment of the present invention. Figure 9 A block diagram of the computing module in the power supply service data monitoring system based on a large model provided in an embodiment of the present invention; Figure 10 This is a block diagram of the writing module in the power supply business data monitoring system based on a large model provided in an embodiment of the present invention. Detailed Implementation

[0017] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the invention.

[0018] In Example 1, Figure 1 The implementation flow of the power supply service data monitoring method based on a large model provided by an embodiment of the present invention is illustrated below: S100: Define the monitoring area for power supply service data, select the monitoring subject, determine the deployment route of distributed optical fiber, connect one end of the distributed optical fiber to the signal transceiver, use the sensing devices pre-installed on the monitoring subject to collect sensing data, and use the historical fluctuations of the sensing data to create a fluctuation range that corresponds one-to-one with the sensing devices.

[0019] The area requiring power supply data monitoring, i.e., the monitoring area, is determined. This area can be a substation or a concentrated area of ​​power equipment. Based on the power grid structure, equipment distribution, and their respective importance, the monitoring entities are identified, including transformers, circuit breakers, switchgear, capacitor banks, and transmission lines. Considering the site environment, equipment distribution, and safety requirements, distributed optical fibers are deployed within the monitoring area, ideally close to the monitored entities. Signal transceivers are installed in the monitoring area, with one end of the distributed optical fiber connected to each transceiver. The transceiver injects pulsed light signals into the distributed optical fiber, utilizing the scattering characteristics of the light signal to detect real-time temperature changes along the fiber. When an abnormal condition occurs in the monitored entity, causing localized heat accumulation, the temperature of the distributed optical fiber rises, altering the scattering characteristics of the light signal. The transceiver captures these changes and converts them into resolvable temperature or heat distribution data, enabling accurate detection and location of abnormal heat accumulation in the monitored entity. Further, the causes of heat accumulation may include internal insulation aging, poor contact, sudden load changes, short circuits, and harmonic interference.

[0020] In addition to using distributed fiber optic monitoring, sensing devices are installed on the monitoring subject according to monitoring needs to collect sensing data from the monitoring subject. The sensing data includes temperature, current, voltage, and vibration. Based on the historical fluctuations of each sensing data, a fluctuation range is created, which is the allowable range of variation of the sensing data under normal operating conditions. A correspondence between the sensing device and the fluctuation range is established. The fluctuation range is different for different production equipment.

[0021] S200: A variable resistor is installed at the sensing device, wherein the distributed optical fiber is bonded to the variable resistor. When the sensing data exceeds the fluctuation range, the deviation value is recorded, the variable resistor is activated, the resistance value of the variable resistor is collected, and a positive correlation between the deviation value and the resistance value is established.

[0022] A variable resistor is installed at the sensing device. The specific installation location of the variable resistor is not limited, but the sensing device and the variable resistor are electrically connected. This means that when the sensing data fluctuates, the variable resistor can be activated, adjusted, or deactivated. When the sensing data exceeds the corresponding fluctuation range, the difference in data deviating from normal operating conditions is recorded, generating a deviation value. The deviation value is the difference between the real-time value under current operating conditions and the standard value under normal operating conditions. When the sensing data exceeds the fluctuation range, the variable resistor is activated, putting it into working state, and its resistance value is collected. The obtained deviation value is correlated with the corresponding variable resistor resistance value to establish a positive correlation between the two. A positive correlation means that the larger the deviation value, the larger the resistance value of the variable resistor. When the deviation value is 0, that is, when the sensing data falls back into the fluctuation range, the variable resistor is deactivated. Deactivation here means disconnecting the power to the variable resistor.

[0023] In this embodiment, when the resistance of the variable resistor increases, a large amount of heat is generated, causing the pulsed optical signal in the distributed optical fiber bonded to the variable resistor to deviate.

[0024] S300: Calculate the distance from each variable resistor to the signal transceiver, start the signal transceiver, inject pulsed light signals into the distributed optical fiber, obtain feedback information, locate the abnormal subject through the distance, generate a monitoring report, and send it to the preset terminal.

[0025] The distance between each variable resistor and the monitoring subject and the signal transceiver is measured. The signal transceiver is then activated to enter working mode and injects pulsed light signals into the already deployed distributed optical fiber. When the pulsed light signals propagate along the distributed optical fiber, reflection and scattering occur when they reach the heat accumulation point. The signal transceiver receives the feedback information returned along the distributed optical fiber, collects the light intensity, propagation delay, and other characteristic parameters from the feedback information, and analyzes them through a large model to accurately locate the heat accumulation point. The monitoring subject at the corresponding location is defined as an abnormal subject. The attribute data of the abnormal subject is collected and written into a preset template to generate a monitoring report. The monitoring report is then sent to a preset terminal, which is the power supply business management personnel terminal.

[0026] S400: Define the disturbance subject from the monitoring subject, and set a bypass channel at the variable resistor of the disturbance subject, wherein a time-delay circuit breaker is installed in the bypass channel, generate an application strategy, and write it into the time-delay circuit breaker.

[0027] Among the monitored entities, identify the disruptive entities. These disruptive entities refer to those whose sensor data might exceed the fluctuation range due to normal production fluctuations. Set up a bypass channel at the variable resistor corresponding to the disruptive entity. This involves connecting a time-delay circuit breaker in parallel across the variable resistor. The time-delay circuit breaker will automatically close after a set countdown, ensuring a circuit continuity.

[0028] For example, a transformer that experiences short-term current peaks based on load changes might experience current fluctuations exceeding its normal range. This triggers a variable resistor, which gradually generates heat. However, since this phenomenon is due to normal production fluctuations, to prevent interference with normal monitoring, the time-delay circuit breaker is set to 5 minutes. After the 5-minute countdown, the circuit breaker closes. Because the time-delay circuit breaker is connected in parallel with the variable resistor, the current does not pass through the variable resistor, allowing the heat to dissipate and restoring the deviated pulse light signal to normal. The advantage of this method is that it effectively prevents false alarms caused by normal production fluctuations and avoids prolonged alarms at one point affecting normal monitoring of other points.

[0029] In Example 2, Figure 2 The first sub-flowchart of the power supply service data monitoring method based on a large model provided by an embodiment of the present invention is shown. The following details the steps of delineating the monitoring area for power supply service data, selecting the monitoring subject, and determining the deployment route of distributed optical fibers: S101: Draw a diagram of the equipment layout within the monitored area and mark the main monitoring subject.

[0030] Based on the building layout and equipment distribution within the monitored area, draw an equipment layout diagram and mark the location of the main monitoring entity within it.

[0031] S102: Set the risk level for each monitored entity, create a cabling strategy that corresponds one-to-one with the risk level, and adjust the cabling route.

[0032] Based on the importance of the monitored entity within the monitored area, the potential impact of faults, and historical operational data, a corresponding risk level is assigned to each monitored entity. These risk levels are categorized as high, medium, and low. A corresponding cabling strategy is then set for each risk level. For example, for a high-risk level monitored entity, the cabling strategy is to spirally attach distributed optical fibers to the location requiring monitoring. For a medium-risk level, the cabling strategy could be an "S"-shaped routing. The deployment route of the distributed optical fibers is adjusted according to the different risk levels.

[0033] In Example 3, Figure 2The first sub-flowchart of the power supply service data monitoring method based on a large model provided by an embodiment of the present invention is shown. The following details the step of creating a fluctuation range corresponding one-to-one with the sensing devices based on the historical fluctuations of the sensor data: S103: Obtain historical values ​​of sensor data, sort them in ascending order, and build a queue.

[0034] Acquire historical values ​​of sensor data, sort all historical values ​​in ascending order, and generate a queue.

[0035] S104: Delete outliers from the queue, integrate the minimum and maximum values ​​in the queue, and generate a fluctuation range.

[0036] Using the interquartile range algorithm, the interquartile range, upper quartile, and lower quartile of the queue are calculated, and outliers in the queue are removed. After removing outliers, the minimum and maximum values ​​are found in the queue, and the fluctuation range is constructed using the minimum and maximum values ​​as endpoints.

[0037] In Example 4, Figure 3 The second sub-flow diagram of the power supply service data monitoring method based on a large model provided in this embodiment of the invention is shown. The step of installing a variable resistor at the sensing device is described in detail below: S201: Configure the number and type of variable resistors according to the risk level of the monitored entity.

[0038] Different numbers and types of variable resistors can be configured for monitoring entities with different risk levels. For example, for high-risk monitoring entities, a larger number of variable resistors can be configured, or variable resistors with faster response speeds and wider adjustment ranges can be selected.

[0039] S202: When the deviation value is greater than the threshold, the variable resistor is adjusted to the maximum resistance value.

[0040] During the monitoring process, when the deviation value exceeds the threshold, it indicates that the monitoring subject may be malfunctioning. At this time, the variable resistor is directly adjusted to the maximum resistance value so as to generate a large amount of heat in a short period of time, thereby enabling the distributed optical fiber to quickly detect abnormal changes.

[0041] In Example 5, Figure 4 The diagram illustrates the third sub-flow of the power supply service data monitoring method based on a large model provided in this embodiment of the invention. The steps of calculating the distance from each variable resistor to the transceiver, activating the transceiver, injecting pulsed optical signals into the distributed optical fiber, and obtaining feedback information are described in detail below: S301: Integrates all sensor data, defines a standard time, collects feedback information at the standard time, and obtains background noise.

[0042] When all sensor data are within the fluctuation range, the corresponding time is defined as the standard time. The feedback information of the standard time is collected to obtain the background noise. The background noise can reflect the natural fluctuation level of the pulse optical signal in the distributed optical fiber under normal operating conditions and the influence of external interference. The cause of the background noise may be the ambient temperature.

[0043] S302: Create a noise baseline model and preprocess the feedback information.

[0044] A noise baseline model is constructed using deep learning algorithms. By analyzing the signal characteristics of distributed optical fibers under normal operating conditions, reference data representing the normal fluctuation range of all monitored entities is extracted to form a benchmark for anomaly detection. Before processing the feedback information, the noise baseline model is used to remove background noise from the feedback information to eliminate irrelevant fluctuations caused by environmental interference in the data.

[0045] In Example 6, Figure 5 The fourth sub-flow diagram of the power supply service data monitoring method based on a large model provided by an embodiment of the present invention is shown. The following details the steps of defining a disturbance subject from the monitoring subject, setting a bypass channel at the variable resistor of the disturbance subject, wherein a time-delay circuit breaker is installed in the bypass channel, generating an application strategy, and writing it into the time-delay circuit breaker: S401: An interrupt mechanism is embedded in the time-delay circuit breaker, which is triggered when the sensor data re-enters the fluctuation range.

[0046] An interrupt mechanism is embedded in the time-delay circuit breaker. When the sensing data detected by the sensing device falls back to the fluctuation range, the interrupt mechanism is triggered. The interrupt mechanism refers to the specific method of disconnecting the power to the variable resistor, so that the time-delay circuit breaker closes and forms an open circuit.

[0047] S402: Record the start and stop times of the variable resistor and the time-delay circuit breaker, generate a monitoring log, and store it in the sensing device.

[0048] Record the start and stop times of variable resistors and time-delay circuit breakers, integrate them to generate a complete monitoring log, and store the monitoring log in the corresponding sensing device.

[0049] Figure 6 The diagram illustrates the structural block diagram of a power supply service data monitoring system based on a large model provided in an embodiment of the present invention. The power supply service data monitoring system 1 based on the large model includes: The delineation module 11 is used to delineate the monitoring area of ​​power supply business data, select the monitoring subject, determine the deployment route of the distributed optical fiber, connect one end of the distributed optical fiber to the signal transceiver, collect sensor data using the sensing devices pre-installed on the monitoring subject, and create a fluctuation range corresponding to the sensing devices using the historical fluctuations of the sensor data. Module 12 is established to install a variable resistor at the sensing device, wherein the distributed optical fiber is bonded to the variable resistor. When the sensing data exceeds the fluctuation range, the deviation value is recorded, the variable resistor is activated, the resistance value of the variable resistor is collected, and a positive correlation between the deviation value and the resistance value is established. The calculation module 13 is used to calculate the distance from each variable resistor to the signal transceiver, start the signal transceiver, inject pulse light signals into the distributed optical fiber, obtain feedback information, locate the abnormal subject through the distance, generate a monitoring report, and send it to the preset terminal. The writing module 14 is used to define a disturbance subject from the monitoring subject, set a bypass channel at the variable resistor of the disturbance subject, wherein a time delay circuit breaker is installed in the bypass channel, generate an application strategy, and write it into the time delay circuit breaker.

[0050] Figure 7 This diagram illustrates the composition of the delineation module 11 in the power supply service data monitoring system based on a large model provided in an embodiment of the present invention. The delineation module 11 includes: The drawing unit 111 is used to draw the equipment layout diagram within the monitoring area and mark the main monitoring subject; Setting unit 112 is used to set the risk level of each monitoring subject, create a wiring strategy that corresponds one-to-one with the risk level, and adjust the wiring route. The sorting unit 113 is used to acquire historical values ​​of sensor data and sort them in ascending order to build a queue; Deletion unit 114 is used to delete outliers in the queue, integrate the minimum and maximum values ​​in the queue, and generate the fluctuation range.

[0051] Figure 8 This diagram illustrates the structural composition of module 12 in the power supply service data monitoring system based on a large model provided in an embodiment of the present invention. Module 12 includes: Configuration unit 121 is used to configure the number and type of variable resistors based on the risk level of the monitoring subject; The adjustment unit 122 is used to adjust the variable resistor to the maximum resistance value when the deviation value is greater than the threshold value.

[0052] Figure 9This diagram illustrates the structural composition of the computing module 13 in the power supply service data monitoring system based on a large model provided in an embodiment of the present invention. The computing module 13 includes: Unit 131 is used to integrate all sensor data, define a standard time, collect feedback information at the standard time, and obtain background noise. The preprocessing unit 132 is used to create a noise reference model and preprocess the feedback information.

[0053] Figure 10 This diagram illustrates the structural composition of the writing module 14 in the power supply service data monitoring system based on a large model provided in an embodiment of the present invention. The writing module 14 includes: Embedded unit 141 is used to embed an interrupt mechanism into the time-delay circuit breaker, and to trigger the interrupt mechanism when the sensing data re-enters the fluctuation range; Storage unit 142 is used to record the start and stop times of the variable resistor and the time-delay circuit breaker, generate monitoring logs, and store them in the sensing device.

[0054] The delineation module 11 is mainly used to complete step S100, the establishment module 12 is mainly used to complete step S200, the calculation module 13 is mainly used to complete step S300, and the writing module 14 is mainly used to complete step S400. The drawing unit 111 is mainly used to complete step S101, the setting unit 112 is mainly used to complete step S102, the sorting unit 113 is mainly used to complete step S103, and the deletion unit 114 is mainly used to complete step S104. Configuration unit 121 is mainly used to complete step S201, and adjustment unit 122 is mainly used to complete step S202; The receiving unit 131 is mainly used to complete step S301, and the preprocessing unit 132 is mainly used to complete step S302; The embedding unit 141 is mainly used to complete step S401, and the storage unit 142 is mainly used to complete step S402.

[0055] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0056] The embodiments described above are merely illustrative of several implementations of the present invention, and while the descriptions are specific and detailed, they should not be construed as limiting the scope of the present invention. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of the present invention, and these modifications and improvements all fall within the scope of protection of the present invention. Therefore, the scope of protection of this patent should be determined by the appended claims.

[0057] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A power supply service data monitoring method based on a large model, characterized in that, The method includes: Define the monitoring area for power supply business data, select the monitoring subject, determine the deployment route of distributed optical fiber, connect one end of the distributed optical fiber to the signal transceiver, use the sensing devices pre-installed on the monitoring subject to collect sensing data, and use the historical fluctuations of the sensing data to create a fluctuation range that corresponds one-to-one with the sensing devices. A variable resistor is installed at the sensing device, wherein the distributed optical fiber is bonded to the variable resistor. When the sensing data exceeds the fluctuation range, the deviation value is recorded, the variable resistor is activated, the resistance value of the variable resistor is collected, and a positive correlation between the deviation value and the resistance value is established. Calculate the distance from each variable resistor to the signal transceiver, start the signal transceiver, inject pulsed light signals into the distributed optical fiber, obtain feedback information, locate the abnormal subject through the distance, generate a monitoring report, and send it to the preset terminal; From the monitoring subject, a disturbance subject is defined, and a bypass channel is set at the variable resistor of the disturbance subject. A time-delay circuit breaker is installed in the bypass channel. An application strategy is generated and written into the time-delay circuit breaker.

2. The power supply service data monitoring method based on a large model according to claim 1, characterized in that, The steps of defining the monitoring area for power supply service data, selecting the monitoring subject, and determining the deployment route of distributed optical fibers include: Draw a diagram of the equipment layout within the monitored area and mark the main monitoring components; Set the risk level for each monitored entity, create a cabling strategy that corresponds one-to-one with the risk level, and adjust the cabling route.

3. The power supply service data monitoring method based on a large model according to claim 1, characterized in that, The step of creating a fluctuation range corresponding one-to-one with the sensing device based on the historical fluctuations of the sensing data includes: Acquire historical values ​​of sensor data and sort them in ascending order to build a queue; Remove outliers from the queue, combine the minimum and maximum values ​​in the queue, and generate a fluctuation range.

4. The power supply service data monitoring method based on a large model according to claim 2, characterized in that, The step of installing a variable resistor at the sensing device includes: The number and type of variable resistors are configured according to the risk level of the monitored entity; When the deviation value is greater than the threshold, the variable resistor is adjusted to the maximum resistance value.

5. The power supply service data monitoring method based on a large model according to claim 3, characterized in that, The steps of calculating the distance from each variable resistor to the transceiver, activating the transceiver, injecting pulsed optical signals into the distributed optical fiber, and obtaining feedback information include: By integrating all sensor data, defining a standard time, collecting feedback information at the standard time, and obtaining background noise; A noise baseline model is created, and the feedback information is preprocessed.

6. The power supply service data monitoring method based on a large model according to claim 5, characterized in that, The steps of defining the disturbance subject from the monitoring subject, setting a bypass channel at the variable resistor of the disturbance subject, wherein a time-delay circuit breaker is installed in the bypass channel, generating an application strategy, and writing it into the time-delay circuit breaker include: An interrupt mechanism is embedded in the time-delay circuit breaker, which is triggered when the sensor data re-enters the fluctuation range. The start and stop times of the variable resistor and the time-delay circuit breaker are recorded, a monitoring log is generated, and stored in the sensing device.

7. A power supply service data monitoring system based on a large model, characterized in that, The system includes: The delineation module is used to delineate the monitoring area of ​​power supply business data, select the monitoring subject, determine the deployment route of distributed optical fiber, connect one end of the distributed optical fiber to the signal transceiver, use the sensing devices pre-installed on the monitoring subject to collect sensing data, and use the historical fluctuations of the sensing data to create a fluctuation range that corresponds one-to-one with the sensing devices. A module is established to install a variable resistor at the sensing device, wherein the distributed optical fiber is bonded to the variable resistor. When the sensing data exceeds the fluctuation range, the deviation value is recorded, the variable resistor is activated, the resistance value of the variable resistor is collected, and a positive correlation between the deviation value and the resistance value is established. The calculation module is used to calculate the distance from each variable resistor to the signal transceiver, start the signal transceiver, inject pulse light signals into the distributed optical fiber, obtain feedback information, locate the abnormal subject through the distance, generate a monitoring report, and send it to the preset terminal. The writing module is used to define the disturbance subject from the monitoring subject, set a bypass channel at the variable resistor of the disturbance subject, wherein a time delay circuit breaker is installed in the bypass channel, generate an application strategy, and write it into the time delay circuit breaker.

8. The power supply service data monitoring system based on a large model according to claim 7, characterized in that, The delineation module includes: The drawing unit is used to draw the equipment layout diagram within the monitored area and mark the main monitoring objects; The configuration unit is used to set the risk level of each monitored entity, create a wiring strategy that corresponds one-to-one with the risk level, and adjust the wiring route. The sorting unit is used to acquire historical values ​​of sensor data and sort them in ascending order to build a queue; The deletion unit is used to remove outliers from the queue, integrate the minimum and maximum values ​​in the queue, and generate a fluctuation range.

9. The power supply service data monitoring system based on a large model according to claim 8, characterized in that, The establishment module includes: A configuration unit is used to configure the number and type of variable resistors based on the risk level of the monitored entity; An adjustment unit is used to adjust the variable resistor to its maximum resistance value when the deviation value is greater than a threshold value.

10. The power supply service data monitoring system based on a large model according to claim 8, characterized in that, The computing module includes: The unit is used to integrate all sensor data, define a standard time, collect feedback information at the standard time, and obtain background noise. A preprocessing unit is used to create a noise baseline model and preprocess the feedback information.

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