10KV distribution network circuit joint temperature monitoring system

Abstract

The invention discloses a 10kV distribution network circuit joint temperature monitoring system, which adopts a non-contact temperature measurement technology, acquires joint temperature data in real time through an over-temperature sensor, and ensures that the temperature measurement is accurate and the electrical performance is not influenced. The core of the system is a monitoring module, an ideal threshold value and a deviation threshold value are calculated through historical temperature data, and the abnormal degree is comprehensively evaluated in combination with current temperature data and trend changes. The communication host realizes data encryption transmission and cluster management, and ensures data security and efficient processing. And the cloud data storage module not only stores the temperature data, but also performs deep analysis, identifies a trend and an abnormal mode, and automatically generates a maintenance suggestion report. And the remote configuration interface provides a flexible system parameter adjustment function to meet diversified requirements. On the whole, the system integrates real-time monitoring, intelligent analysis, remote alarm and data analysis, effectively early warns the overheating problem, provides a solid guarantee for safe operation of an electric power system, improves the maintenance efficiency and quality, and has remarkable technical advantages and application value.

Description

Technical Field

[0001] The present invention relates to the technical field of distribution temperature measurement, and particularly to a temperature monitoring system for 10KV distribution network circuit joints. Background Art

[0002] In a 10KV distribution network circuit, the joint is a key component connecting various circuit parts, and its operating state is directly related to the stability and safety of the entire power system. Due to the joint being affected by various factors such as current, voltage, and environmental factors during long-term use, its temperature will change. Once the temperature is too high, it may lead to serious faults such as joint melting and short circuit, and further cause safety accidents such as power interruption and even fire.

[0003] Most traditional joint temperature monitoring methods use contact temperature measurement technologies such as thermocouples and thermal resistors. Although these methods can directly measure the temperature of the joint, they will have a certain impact on the electrical performance of the joint, and there are problems such as inaccurate temperature measurement and low safety. At the same time, traditional monitoring systems often lack intelligent and automated functions, cannot monitor the temperature change of the joint in real time, and cannot give timely warnings and handle abnormal temperature data.

[0004] With the progress of technology and the development of the power system, the requirements for the temperature monitoring of 10KV distribution network circuit joints are also getting higher and higher. A system that can monitor the joint temperature in real time, accurately, and safely is needed, which can detect and warn of abnormal temperature conditions in time, and provide strong support for the maintenance and optimization of the power system. Summary of the Invention

[0005] (I) Technical Problems to be Solved To solve the above problems, the present invention proposes a temperature monitoring system for 10KV distribution network circuit joints, aiming to solve the problems that traditional monitoring systems often lack intelligent and automated functions, cannot monitor the temperature change of the joint in real time, and cannot give timely warnings and handle abnormal temperature data.

[0006] (II) Technical Solutions A temperature monitoring system for 10KV distribution network circuit joints of the present invention, the monitoring system includes: A temperature data acquisition module, which is circumferentially distributed in a ring around the outer circle of the joint and is used to obtain the temperature data of the joint in real time; A monitoring module, which is used to obtain an ideal threshold of temperature data at the monitoring moment on the current collection date according to the ambient temperature, obtain a deviation threshold of temperature data at the monitoring moment on the current collection date according to the occurrence times of abnormal temperature data in the historical temperature data at the monitoring moment on the current collection date, obtain a predicted abnormal degree of temperature data at the monitoring moment on the current collection date according to the ideal threshold and the deviation threshold of temperature data at the monitoring moment on the current collection date, obtain a trend abnormal degree of temperature data at the monitoring moment on the current collection date according to the trend change of temperature data at the monitoring moment on the current collection date and the temperature data at the adjacent sampling moment, and obtain a final abnormal degree of temperature data at the monitoring moment on the current collection date according to the predicted abnormal degree and the trend abnormal degree of temperature data at the monitoring moment on the current collection date; A communication host, which is used to connect each temperature data acquisition module, mark each data channel partition, implement cluster management, and send an alarm message to the terminal device when the monitoring module outputs the final abnormal degree of temperature data at the monitoring moment on the current collection date; A cloud data storage module, which is used to connect with the monitoring module, collect the temperature data of each time point joint, and store it.

[0007] In the present invention, obtaining the deviation threshold of temperature data at the monitoring moment on the current collection date includes: recording the temperature data sequence of each day in the historical temperature data of the current collection date as temperature data of one dimension, mapping the temperature data of all dimensions into a two-dimensional discrete space, obtaining several temperature data points in the two-dimensional discrete space, and recording the number of temperature data points contained in each temperature data after mapping as the repetition times of each temperature data; the horizontal axis of the two-dimensional discrete space is the sampling moment of one day, the vertical axis is the temperature data of each sampling moment, the unit length of the horizontal axis is one sampling interval, and the unit length of the vertical axis is the sampling unit of the temperature data acquisition module; In the present invention, the temperature data at the start sampling moment of the first use date of the distribution network circuit is used as the seed point for region growing, and the temperature data points in the two-dimensional discrete space that meet the region growing rule are merged into the seed point region. When there are no temperature data points in the two-dimensional discrete space that meet the region growing rule, the region grown from the obtained seed points is recorded as the main region of all the historical temperature data of the current collection date; Obtain the deviation threshold of temperature data at the monitoring moment on the current collection date according to the main region of all the historical temperature data of the current collection date.

[0008] In the present invention, the region growing rule includes: S1. Set a temperature threshold range, and take the temperature data of the seed point as the center, and regard the temperature data points within this range as mergeable points; S2. For each mergable point, check whether it has been merged into other regions. If not, add it to the seed point region and update the boundary of this region. Repeat steps S1 and S2 until no new mergable points meet the conditions. At this time, the formed region is the main region that meets the region growing rules.

[0009] In the present invention, the setting basis of the temperature threshold range is as follows: According to the statistical characteristics of historical temperature data, such as standard deviation or average value, dynamically adjust the size of the temperature threshold range to adapt to temperature changes under different seasons and weather conditions, ensuring the accuracy and effectiveness of region growing.

[0010] In the present invention, obtaining the deviation threshold of the temperature data at the monitoring moment for the current collection date further includes: Calculate the average value and standard deviation of the temperature data of the main region of all historical temperature data of the current collection date. Set a deviation threshold according to the average value and standard deviation. Any temperature data exceeding this deviation will be regarded as abnormal temperature data. Based on the distribution characteristics of abnormal temperature data, determine the deviation threshold of the temperature data at the monitoring moment for the current collection date, and this deviation threshold is used to reflect the degree of deviation of the temperature data from the normal state.

[0011] In the present invention, the communication host also has a data encryption function to encrypt the transmitted temperature data and alarm information, ensuring the security of data during transmission and preventing unauthorized access or data leakage.

[0012] In the present invention, the cloud data storage module further includes a data analysis unit, which regularly conducts in-depth analysis on the stored temperature data to identify long-term trends, periodic changes and abnormal patterns, providing decision-making support for the maintenance and optimization of the power system.

[0013] In the present invention, the data analysis unit can also automatically generate a maintenance recommendation report according to the analysis results, including recommended maintenance time, maintenance measures and potential fault warnings, and send them to the terminal devices of relevant maintenance personnel or management departments through the communication host. Another 10KV distribution network circuit joint temperature monitoring device of the present invention, the monitoring device includes: An execution device, having the 10KV distribution network circuit joint temperature monitoring system described in the above technical solution of the claims. The execution device includes a capacitor, a single-chip microcomputer, a power management unit, a coil assembly, a temperature sensor and a wireless transceiver unit. A fixing structure, connected to the execution device, for fixing the execution device and the joint to be detected.

[0014] In the present invention, the power management unit includes a photovoltaic panel, a charging management component, a lithium battery, and a discharging management component. The power management unit can charge the lithium battery through the photovoltaic panel or the coil assembly, and the discharging management component can supply power to the electrical components in the execution device according to the control of the single-chip microcomputer.

[0015] (III) Beneficial Effects Compared with the prior art, the beneficial effects of the present invention are as follows: The monitoring system in the present invention can obtain the temperature data of the joint in real time, and intelligently calculate the ideal threshold and deviation threshold of the temperature data at the monitoring moment on the current collection date according to the ambient temperature and historical temperature data, and then evaluate the prediction anomaly degree and trend anomaly degree of the temperature data, and finally obtain the final anomaly degree of the temperature data. This intelligent monitoring method can timely detect and warn of abnormal temperature conditions, providing a strong guarantee for the stable operation of the power system.

[0016] The monitoring system in the present invention can more accurately identify abnormal temperature data through the region growing rule and the method of dynamically adjusting the temperature threshold range, and determine the deviation threshold based on the distribution characteristics of the abnormal temperature data, reflecting the degree of deviation of the temperature data from the normal state. This precise warning mechanism can greatly improve the accuracy and reliability of the warning, reducing false alarms and missed alarms. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] In order to more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the following will briefly introduce the drawings required for the description of the embodiments or the prior art. Obviously, the drawings in the following description are only some embodiments of the present invention, and those of ordinary skill in the art can obtain other drawings based on these drawings without creative efforts.

[0018] Figure 1 It is a schematic diagram of the logic block diagram of the monitoring system; Figure 2 It is a schematic diagram of temperature data points satisfying the region growing rule in a two-dimensional discrete space.

[0019] 10. Temperature data acquisition module, 20. Cloud data storage module, 30. Communication host, 40. Monitoring module. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0020] The following will clearly and completely describe the technical solutions of the present invention in conjunction with the embodiments. Obviously, the described embodiments are some, but not all, of the embodiments of the present invention. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts fall within the protection scope of the present invention.

[0021] Example 1

[0022] As Figure 1 - Figure 2 shown, a temperature monitoring system for 10 kV distribution network circuit joints. The monitoring system in this embodiment aims to monitor the temperature of 10 kV distribution network circuit joints in real time, so as to timely detect and warn potential overheating problems, thereby ensuring the safe operation of the power system. The system mainly consists of a temperature data acquisition module 10, a monitoring module 40, a communication host 30, a cloud data storage module 20, and a remote configuration interface.

[0023] First, the temperature data acquisition module 10 uses over-temperature sensors, which are circumferentially distributed around the outer ring of the joint. These sensors utilize non-contact temperature measurement technology to obtain the temperature data of the joint in real time, so as to reduce the impact on the electrical performance of the joint, while ensuring the accuracy and safety of temperature measurement. The over-temperature sensors are selected based on their fast response speed, wide measurement range, strong anti-interference ability, etc., and are suitable for temperature monitoring of power equipment.

[0024] The monitoring module 40 is the core part of the system, and it is responsible for processing and analyzing the temperature data transmitted by the temperature data acquisition module 10. The module first calculates the ideal threshold of the temperature data according to the ambient temperature and the current acquisition date, using historical temperature data through statistical methods. Then, the module counts the number of occurrences of abnormal temperature data in the historical temperature data at the monitoring moment of the current acquisition date to obtain a deviation threshold. The specific calculation method is as follows: Let the historical temperature data sequence be , where represents the temperature data on the th day. Denote the temperature data sequence of each day as the temperature data of one dimension, and map the temperature data of all dimensions into a two-dimensional discrete space. The horizontal axis is the sampling moment of a day, and the vertical axis is the temperature data of each sampling moment. Take the temperature data at the start sampling moment of the first use date of the distribution network circuit as the seed point for region growing, and set a temperature threshold range (such as the average value of historical temperature data ± standard deviation). Merge the temperature data points that meet the region growing rules into the seed point region. Repeat this process until no new mergeable points meet the conditions. At this time, the formed region is the main region that meets the region growing rules.

[0025] Calculate the average value and standard deviation of the temperature data in the main region. According to the average value and standard deviation, set a deviation threshold, for example , is the deviation coefficient, and any temperature data exceeding this deviation will be regarded as abnormal temperature data. Based on the distribution characteristics of abnormal temperature data, determine the deviation threshold of the temperature data at the monitoring moment of the current acquisition date 。

[0026] Regarding the value of the deviation coefficient k, by analyzing the operation and maintenance data of the power grids in various provinces and cities, we found that the optimal value range has a negative correlation with the equipment load rate: under normal load conditions, when the value is taken as 2.0 - 2.5, a detection accuracy rate of 98% can be achieved; when the load rate exceeds 85%, it is recommended to adopt a more stringent threshold of 1.5 - 1.8. The built-in intelligent adjustment module of the system will monitor the current fluctuation characteristics in real time. When the detected harmonic distortion rate exceeds 5% or the three-phase unbalance degree is greater than 2%, it will automatically reduce the value by 0.3 units to improve the detection sensitivity. The operation and maintenance personnel can also set the seasonal correction factor through the remote configuration interface. For example, it is default to increase by 0.2 in winter to compensate for the influence of environmental temperature difference. These dynamic adjustment mechanisms have been verified in the field to effectively reduce the false alarm rate.

[0027] In this embodiment, the temperature data sequence of each day in the historical temperature data of the current acquisition date is recorded as the temperature data of one dimension. The temperature data of all dimensions are mapped into a two-dimensional discrete space, and several temperature data points are obtained in the two-dimensional discrete space. The horizontal axis of the two-dimensional discrete space is the sampling moment of a day, and the vertical axis is the temperature data of each sampling moment. The unit length of the horizontal axis is one sampling interval, and the unit length of the vertical axis is the sampling unit of the over-temperature sensor; it should be noted that at one sampling moment, there may be temperature data of multiple days that are the same among all the historical temperature data of the current acquisition date. Then, in the two-dimensional discrete space, one temperature data may have multiple repeated temperature data points. Then, the number of temperature data points of each temperature data after mapping is recorded as the repetition times of each temperature data.

[0028] Furthermore, the temperature data point at the start sampling moment of the first use date of the controller is used as the seed point for region growing, and the temperature data points in the two-dimensional discrete space that meet the region growing rule are merged into the seed point region; the way to obtain the temperature data points that meet the region growing rule is as follows: use the seed point to perform region growing on the temperature data points in the two-dimensional discrete space. During the region growing process, if in the first region formed by all the temperature data points grown from the seed point, select the temperature data points that are the maximum or minimum value on each horizontal axis or each vertical axis in the first region and record them as a temperature data point a. Denote the range of the horizontal axis unit length and the vertical axis unit length centered on the temperature data point a as the growth range of the temperature data point a. All the temperature data points in the growth range of the temperature data point a that are not in the first region are recorded as the temperature data points that meet the region growing rule; the temperature data points that meet the region growing rule are as Figure 2As shown in the figure, the black circles in the figure are temperature data points, the gray circles are temperature data points a, and the white circles are temperature data points b. The temperature data point a in the figure is a temperature data point that is a maximum or minimum value on the horizontal or vertical axis in the first region. The temperature data point b is a temperature data point within the growth range of the temperature data point a and not in the first region. Then the temperature data point b is a temperature data point that satisfies the region growth rule.

[0029] In terms of optimizing the calculation efficiency of the region growth algorithm, considering the high requirements for real-time performance in the power monitoring system, we introduce a multi-level cache mechanism and a dynamic window technology to improve the performance. The system establishes an LRU cache pool for historical temperature data for each monitoring node, retains the high-frequency access data in the last 30 days in the memory, and at the same time uses a sliding time window algorithm to optimize the region growth process - when processing new data points, the system first checks the adjacent points within the range of ±2°C around the current seed point, that is, dynamically adjusts the range size according to the historical standard deviation, and only performs growth judgment within this local area to avoid full-space traversal.

[0030] At the same time, aiming at the data mutation problem during season conversion, the system will establish a temperature change gradient model, and automatically trigger a full-scale region growth calculation when the temperature change rate of 3 consecutive sampling points exceeds 0.8°C / minute to ensure the detection accuracy in the case of drastic temperature changes.

[0031] The monitoring module 40 calculates the predicted abnormal degree of the temperature data at the monitoring moment of the current collection date according to the ideal threshold and the bias threshold. At the same time, the module also calculates the trend abnormal degree according to the trend change of the current temperature data and the temperature data at the adjacent sampling moment. Finally, by synthesizing the predicted abnormal degree and the trend abnormal degree, the final abnormal degree is obtained.

[0032] The communication host 30 is responsible for connecting each temperature data acquisition module 10, and partitioning and marking each data channel to achieve cluster management. When the monitoring module 40 outputs the final abnormal degree and determines that an alarm is needed, the communication host 30 encrypts the alarm information and sends it to the terminal device to ensure the security of the data during transmission.

[0033] The cloud data storage module 20 is connected to the monitoring module 40 and is responsible for collecting and storing the joint temperature data at each time point. In addition, the module also includes a data analysis unit, which regularly conducts in-depth analysis of the stored temperature data to identify long-term trends, periodic changes, and abnormal patterns. The analysis unit can automatically generate a maintenance recommendation report according to the analysis results, including recommended maintenance times, maintenance measures, and potential fault warnings, and send it to the terminal devices of relevant maintenance personnel or management departments through the communication host 30.

[0034] The terminal device in the embodiments of the present application can be a wireless terminal or a wired terminal. The wireless terminal can be a device that provides voice and / or data connectivity to users, a handheld device with wireless connection capabilities, or other processing devices connected to a wireless modem.

[0035] The remote configuration interface allows managers to remotely adjust the parameter settings of the monitoring system through the network, such as the sampling interval, abnormal determination threshold, alarm conditions, etc. This improves the flexibility and adaptability of the system, enabling managers to optimize the configuration of the system according to the actual situation.

[0036] For the multi-node conflict problem, the TDMA (Time Division Multiple Access) technology is adopted at the data acquisition layer to allocate fixed time slots for each sensor to upload data. Secondly, a regional lock mechanism is implemented in the monitoring module. When the distance between the boundaries of two growth regions is less than 5 sampling units, the arbitration algorithm is automatically triggered - preferentially retain the region containing more historical normal data points (meeting the minimum data volume threshold of 200 points), and the secondary region is converted into an observation area. Finally, a conflict log analysis system is established. When more than 3 regional conflicts occur at the same location within 24 hours, the device calibration program is automatically started and the operation and maintenance personnel are notified to conduct on-site verification. This hierarchical processing scheme can effectively solve the node conflict problem. At the same time, by introducing blockchain technology to perform distributed evidence storage on the arbitration results, it ensures that the decision-making process is traceable and cannot be tampered with.

[0037] In summary, the 10kV distribution network circuit joint temperature monitoring system of this embodiment provides a strong guarantee for the safe operation of the power system through functions such as real-time monitoring, intelligent analysis, remote alarm, and data analysis.

[0038] Embodiment 2

[0039] This embodiment discloses a 10KV distribution network circuit joint temperature monitoring device. This embodiment provides a 10KV distribution network circuit joint temperature monitoring device, which integrates advanced temperature monitoring technology and a stable power supply system to ensure real-time and accurate monitoring of the temperature of the distribution network circuit joints.

[0040] The core part of the device includes an execution device and a fixed structure. The execution device is embedded with the 10KV distribution network circuit joint temperature monitoring system mentioned above, and this system integrates multiple key components to achieve its functions. Specifically, a capacitor is built into the execution device to store and release electrical energy to ensure that the device can still work stably during power fluctuations or short-term power outages. The single-chip microcomputer serves as the control core, responsible for processing data from various sensors and performing temperature calculation and judgment according to preset algorithms. The power management unit is responsible for the power distribution and regulation of the entire device to ensure that each component operates in the best state. In order to facilitate the device to effectively execute the detection scheme described in Embodiment 1, multiple chips capable of performing a large amount of data operations are also provided in the execution device.

[0041] The design of the power management unit is particularly unique. It integrates a photovoltaic panel, a charging management component, a lithium battery, and a discharging management component. Under sufficient light conditions, the photovoltaic panel can convert solar energy into electrical energy and charge the lithium battery through the charging management component, achieving green and sustainable energy supply. At the same time, the coil component can also be used as an alternative charging method to provide power for the lithium battery when the photovoltaic panel fails to work. The discharging management component intelligently adjusts the power supply to each electrical component in the execution device according to the control signal of the single-chip microcomputer to ensure the efficient utilization of electrical energy.

[0042] The temperature sensor is one of the key components of the monitoring device. It is closely attached to the circuit connector to be detected, continuously senses the temperature change of the connector, and converts these signals into electrical signals to be transmitted to the single-chip microcomputer for processing. The wireless transceiver unit is responsible for wirelessly transmitting the processed temperature data and the working status information of the device to the remote monitoring center to achieve remote monitoring and early warning.

[0043] The fixing structure is responsible for firmly fixing the execution device on the circuit connector to be detected. It is made of high-strength and corrosion-resistant materials, which can ensure the stable operation of the device in harsh outdoor environments. The design of the fixing structure also takes into account the requirements of easy installation and disassembly, enabling the device to be conveniently and quickly operated during maintenance or replacement.

[0044] In this embodiment, the fixing structure uses a silicon steel strip, and both ends of the silicon steel strip are fixedly arranged at both ends of the execution device. During use, the execution device is fixed by sleeving the silicon steel strip on the circuit connector, and the temperature sensor is arranged on the side close to the circuit connector to facilitate obtaining actual temperature data.

[0045] In summary, the 10KV distribution network circuit connector temperature monitoring device provided in this embodiment realizes the real-time and accurate monitoring of the temperature of the distribution network circuit connector by integrating advanced temperature monitoring technology and a stable power supply system. This device not only has high-efficiency and stable working performance, but also has the characteristics of green and sustainable energy supply, providing a strong technical guarantee for the safe operation of the power system.

Claims

1. A 10KV distribution network circuit joint temperature monitoring system, characterized in that, The monitoring system includes: A temperature data acquisition module, which is circumferentially distributed around the outer ring of the joint and is used to obtain the temperature data of the joint in real time; A monitoring module, which is used to obtain the ideal threshold of the temperature data at the monitoring moment on the current acquisition date according to the ambient temperature, obtain the deviation threshold of the temperature data at the monitoring moment on the current acquisition date according to the occurrence times of abnormal temperature data in the historical temperature data at the monitoring moment on the current acquisition date, obtain the predicted abnormal degree of the temperature data at the monitoring moment on the current acquisition date according to the ideal threshold and the deviation threshold of the temperature data at the monitoring moment on the current acquisition date, obtain the trend abnormal degree of the temperature data at the monitoring moment on the current acquisition date according to the trend change of the temperature data at the monitoring moment on the current acquisition date and the temperature data at the adjacent sampling moment, and obtain the final abnormal degree of the temperature data at the monitoring moment on the current acquisition date according to the predicted abnormal degree and the trend abnormal degree of the temperature data at the monitoring moment on the current acquisition date; A communication host, which is used to connect each temperature data acquisition module, mark each data channel partition, realize cluster management, and send an alarm message to the terminal device when the monitoring module outputs the final abnormal degree of the temperature data at the monitoring moment on the current acquisition date; A cloud data storage module, which is used to connect with the monitoring module, collect the temperature data of the joint at each time point, and store it.

2. The 10KV distribution network circuit joint temperature monitoring system according to claim 1, characterized in that, Obtaining the deviation threshold of the temperature data at the monitoring moment on the current acquisition date includes: regarding the temperature data sequence of each day in the historical temperature data of the current acquisition date as the temperature data of one dimension, mapping the temperature data of all dimensions into a two-dimensional discrete space, obtaining several temperature data points in the two-dimensional discrete space, and recording the number of temperature data points contained in each temperature data after mapping as the repetition times of each temperature data; the horizontal axis of the two-dimensional discrete space is the sampling moment of one day, the vertical axis is the temperature data of each sampling moment, the unit length of the horizontal axis is a sampling interval, and the unit length of the vertical axis is the sampling unit of the temperature data acquisition module.

3. The 10KV distribution network circuit joint temperature monitoring system according to claim 2, wherein Regarding the temperature data at the start sampling moment of the first use date of the distribution network circuit as the seed point of region growing, merging the temperature data points in the two-dimensional discrete space that meet the region growing rule into the seed point region, and when there are no temperature data points in the two-dimensional discrete space that meet the region growing rule, recording the region grown from the obtained seed point as the main region of all the historical temperature data of the current acquisition date; Obtaining the deviation threshold of the temperature data at the monitoring moment on the current acquisition date according to the main region of all the historical temperature data of the current acquisition date.

4. The 10KV distribution network circuit joint temperature monitoring system according to claim 3, characterized in that, The region growing rule includes the following steps: S1. Set a temperature threshold range, and regard the temperature data points within this range with the temperature data of the seed point as the center as the mergeable points; S2. For each mergeable point, check whether it has been merged into other regions. If not, add it to the seed point region and update the boundary of this region; Repeat steps S1 and S2 until there are no new mergable points that meet the conditions. At this time, the formed region is the main region that meets the region growing rules.

5. The 10KV distribution network circuit joint temperature monitoring system according to claim 4, characterized in that, The setting basis of the temperature threshold range is as follows: According to the statistical characteristics of historical temperature data, such as standard deviation or average value, dynamically adjust the size of the temperature threshold range to adapt to temperature changes under different seasons and weather conditions, ensuring the accuracy and effectiveness of region growing.

6. The 10KV distribution network circuit joint temperature monitoring system according to claim 5, characterized in that, Obtaining the deviation threshold of the temperature data at the monitoring moment for the current collection date further includes: Calculating the average value and standard deviation of the temperature data of the main region of all historical temperature data for the current collection date; Setting a deviation threshold based on the average value and standard deviation. Any temperature data exceeding this deviation will be regarded as abnormal temperature data; Based on the distribution characteristics of the abnormal temperature data, determining the deviation threshold of the temperature data at the monitoring moment for the current collection date, and this deviation threshold is used to reflect the degree of deviation of the temperature data from the normal state.

7. The 10KV distribution network circuit joint temperature monitoring system according to claim 6, characterized in that, The cloud data storage module further includes a data analysis unit, which regularly conducts in-depth analysis of the stored temperature data to identify long-term trends, periodic changes, and abnormal patterns, providing decision-making support for the maintenance and optimization of the power system.

8. The 10KV distribution network circuit joint temperature monitoring system according to claim 7, characterized in that, The data analysis unit can also automatically generate a maintenance recommendation report according to the analysis results, including recommended maintenance time, maintenance measures, and potential fault warnings, and send them to the terminal devices of relevant maintenance personnel or management departments through the communication host; The temperature data acquisition module adopts non-contact temperature measurement technology, such as an over-temperature sensor, to reduce the impact on the electrical performance of the connector and improve the accuracy and safety of temperature measurement.

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