A smart monitoring and control system for cable branch boxes

Abstract

This invention relates to the field of intelligent monitoring and control technology for power distribution equipment, specifically an intelligent monitoring and adjustment system for cable branch boxes. The system includes: a data acquisition module for acquiring real-time current, high-frequency partial discharge pulse data, multi-point temperature of the joint surface, humidity inside the box, and predicted load data of the power distribution network; an internal status observation module for retrieving the actual highest internal temperature of the joint; a lifespan consumption calculation module for calculating the real-time insulation lifespan consumption rate by combining temperature cycles, humidity, and partial discharge data; a health status assessment module for generating predicted remaining service life, a health index, and early warning information; and a feedforward collaborative adjustment module for outputting local microclimate adjustment commands and global power grid dispatch commands. This invention elevates the monitoring object to the lifespan risk under the combined effects of internal hotspots, insulation aging, and load impacts, enabling early identification and proactive adjustment of hidden joint degradation.

Description

Technical Field

[0001] This invention relates to the field of intelligent monitoring and control technology for power distribution equipment, specifically to an intelligent monitoring and adjustment system for cable branch boxes. Background Technology

[0002] With the continuous changes in the load structure of urban power distribution networks, the application scale of cable branch boxes in commercial complexes, underground spaces, and centralized access scenarios for new energy vehicles continues to expand. During long-term operation, these devices are easily affected by factors such as load fluctuations, high humidity environment inside the box, and limited heat dissipation conditions of joints, which can lead to problems such as joint temperature rise, insulation aging, and partial discharge. How to more accurately monitor the operating status of cable branch boxes and make timely adjustments has become an important issue in the condition-based operation and maintenance of power distribution equipment. Traditional cable distribution box operation monitoring currently relies mainly on the following methods: collecting joint surface temperature, monitoring humidity inside the box, and issuing alarms when parameters exceed limits; However, surface temperature monitoring, humidity monitoring, and over-limit alarms all have certain drawbacks. For example, surface temperature monitoring is difficult to reflect the actual hot spots inside the joint, and it is easy to encounter the problem that internal heating has intensified while the external temperature measurement has not yet reached the preset abnormal alarm threshold. Humidity monitoring can usually only reflect the environmental conditions and is difficult to combine with load changes and insulation degradation for comprehensive judgment. Over-limit alarms are mainly triggered by a single threshold and cannot reflect the life consumption process under the combined effects of temperature cycling, partial discharge, and high humidity environment. They are also difficult to adjust the local environment in advance or coordinate the load distribution on the grid side before the peak load arrives. Summary of the Invention

[0003] To solve the above-mentioned technical problems, the present invention provides an intelligent monitoring and adjustment system for cable branch boxes. Specifically, the technical solution of the present invention includes: The data acquisition module is used to acquire real-time electrical status data and environmental microclimate data of the joints inside the cable branch box through local sensors installed in the cable branch box, and to acquire power distribution network load forecast data from the upper-level dispatching system through a communication interface; wherein, the real-time electrical status data includes real-time current and high-frequency partial discharge pulse data, the high-frequency partial discharge pulse data includes discharge amplitude and discharge frequency, and the environmental microclimate data includes multi-point temperature of the joint surface and humidity inside the cable branch box; An internal state observation module is used to calculate the true highest internal temperature of the joint based on the multi-point temperature on the joint surface and the real-time current. The lifespan consumption calculation module is used to extract temperature cycle characteristics based on the actual highest temperature inside the joint, and combine the actual highest temperature inside the joint, the humidity inside the box, and the high-frequency partial discharge pulse data to calculate the real-time insulation lifespan consumption rate. The health status assessment module is used to calculate the predicted value of the remaining service life based on the real-time insulation life consumption rate, and generate the cable branch box health index and the early warning information of the remaining service life. The feedforward coordinated regulation module is used to generate and output local microclimate regulation commands and global power grid dispatch commands for controlling the dehumidification equipment and cooling fans installed in the cable branch box, based on the health index of the cable branch box, the remaining service life warning information, and the power distribution network load forecast data.

[0004] Optionally, the internal state observation module is specifically used for: The multi-point temperature of the joint surface and the real-time current are input into a preset thermal resistance and thermal capacity network model. The Joule heat generation rate is calculated by multiplying the square of the real-time current by the preset initial value of the contact resistance obtained from the factory parameters or acceptance test records. By combining the Joule heat generation rate and the multi-point temperature on the joint surface, the true maximum temperature inside the joint can be deduced.

[0005] Optionally, the lifespan calculation module is further configured to calculate cumulative mechanical stress damage to generate a predicted contact resistance value, specifically including: The amplitude and frequency of temperature cycles are extracted from the actual highest temperature inside the joint using the rainflow counting method, and used as the temperature cycle characteristics. Using the linear cumulative damage rule, the cumulative damage value of the micro-mechanical stress on the internal contact surface of the joint is calculated based on the amplitude and the frequency. The cumulative damage value is multiplied by a preset resistance ratio coefficient to obtain the contact resistance increment, and the preset initial contact resistance value is added to the contact resistance increment to generate the predicted contact resistance value.

[0006] Optionally, when calculating the real-time insulation lifetime consumption rate, the lifetime consumption calculation module is specifically used for: The temperature-activated aging term is calculated based on the Arrhenius equation and the actual highest temperature inside the joint. The humidity correction term is determined based on the humidity inside the chamber. The temperature-activated aging term and the humidity correction term are combined to form the base aging rate. Using the inverse power law relationship, the discharge amplitude and discharge frequency in the high-frequency partial discharge pulse data are converted into an electrical stress acceleration factor; Multiply the base aging rate by the electrical stress acceleration factor to output the real-time insulation life consumption rate.

[0007] Optionally, the health status assessment module is specifically used for: The cumulative lifetime loss value is obtained by integrating the real-time insulation lifetime consumption rate over time. The remaining service life is predicted by subtracting the cumulative service life loss value from the preset initial design service life of the cable branch box. The ratio of the predicted remaining service life to the initial design life of the cable branch box is used as the health index of the cable branch box. The configuration is as follows: if the predicted remaining service life is lower than the preset service life threshold, then generate the remaining service life warning information; otherwise, generate the normal operation status data tag.

[0008] Optionally, the process by which the feedforward collaborative regulation module generates local microclimate regulation instructions includes: The configuration is as follows: if the real-time consumption rate of the insulation life is greater than the preset aging critical threshold, then the local microclimate adjustment command is generated based on the humidity inside the box to trigger the dehumidification device and the cooling fan; otherwise, the command to maintain the current operating state is generated.

[0009] Optionally, the process by which the feedforward coordinated adjustment module generates global power grid dispatch instructions includes: The configuration is as follows: if the real-time insulation life consumption rate after the execution of the local microclimate adjustment command continues to be greater than the aging critical threshold within a preset time window, then the dynamic capacity expansion limit value is calculated based on the distribution network load forecast data, and the global power grid dispatch command containing a local load transfer request is output to the upper-level dispatch system; otherwise, normal state confirmation information that does not require load transfer is generated.

[0010] Optionally, the system further includes an adaptive correction module for: The data acquisition module acquires updated environmental microclimate data after executing the local microclimate adjustment command and the global power grid dispatch command. The updated environmental microclimate data is fed back to the lifetime consumption calculation module to recalculate the real-time insulation lifetime consumption rate, forming a dynamic closed-loop control.

[0011] Compared with the prior art, the present invention has the following beneficial effects: 1. To address the problem in the background technology that surface temperature monitoring is difficult to reflect the true hot spots inside the joint and is prone to lag, this system acquires the temperature and real-time current at multiple points on the joint surface through a data acquisition module. The internal state observation module inputs the above data into a preset thermal resistance and thermal capacity network model, and calculates the Joule heat generation rate using the square of the real-time current and the preset initial value of the contact resistance to deduce the true maximum temperature inside the joint. This mechanism effectively compensates for the physical defects of external temperature measurement and heat transfer lag, enabling the system to identify hidden internal heat sources in advance before the external temperature reaches the preset over-limit threshold, thus improving the early warning capability for joint temperature rise under high load conditions.

[0012] 2. To address the issue that over-limit alarms in the background technology cannot reflect the lifespan consumption process under the combined effects of temperature cycling, high-frequency partial discharge, and high humidity, the lifespan consumption calculation module of this system uses the rainflow counting method to extract the cyclic characteristics of the actual highest internal temperature, and uses the linear cumulative damage law to calculate mechanical stress damage to generate dynamic contact resistance prediction values. Simultaneously, the Arrhenius equation is used to convert the highest internal temperature and humidity inside the chamber into a basic aging rate, and the inverse power law is used to convert the amplitude and frequency of partial discharge into an electrical stress acceleration factor. Multiplying these two factors yields the real-time insulation lifespan consumption rate, which is then integrated by the health status assessment module to obtain the remaining service life prediction value and health index. This mechanism transforms the traditional single-point passive alarm into a real-time quantification of the degradation caused by the coupling of multiple physical fields (heat, humidity, and electricity), providing accurate data support for preventative equipment maintenance. Attached Figure Description

[0013] The present invention will be further explained below with reference to the accompanying drawings and embodiments: Figure 1 This is a structural diagram of the system of the present invention. Detailed Implementation

[0014] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to specific embodiments.

[0015] Example 1: Please see Figure 1 A smart monitoring and control system for cable branch boxes, comprising: The data acquisition module is used to acquire real-time electrical status data and environmental microclimate data of the joints inside the cable branch box through local sensors installed in the cable branch box, and to acquire power distribution network load forecast data from the upper-level dispatching system through the communication interface. The real-time electrical status data includes real-time current and high-frequency partial discharge pulse data. The high-frequency partial discharge pulse data includes discharge amplitude and discharge frequency. The environmental microclimate data includes multi-point temperature of the joint surface and humidity inside the cable branch box. The internal state observation module is used to calculate the true maximum temperature inside the joint based on the multi-point temperature and real-time current on the joint surface. The life consumption calculation module is used to extract temperature cycle characteristics based on the actual highest temperature inside the joint, and combine the actual highest temperature inside the joint, humidity inside the box and high-frequency partial discharge pulse data to calculate the real-time insulation life consumption rate. The health status assessment module is used to calculate the predicted value of the remaining service life based on the real-time insulation life consumption rate, and generate the cable branch box health index and the early warning information of the remaining service life. The feedforward coordinated regulation module is used to generate and output local microclimate regulation commands and global power grid dispatch commands for controlling the dehumidification equipment and cooling fans installed in the cable branch box, based on the cable branch box health index, remaining service life early warning information and power distribution network load forecast data.

[0016] This embodiment provides an overall operating mechanism for an intelligent monitoring and regulation system for cable branch boxes. Specifically, this embodiment uses a 10kV cable branch box in a core urban business district as an example scenario. This cable branch box is located near the entrance and exit of an underground parking garage and undertakes the branch power supply tasks for office buildings, commercial complexes, and centralized new energy vehicle charging piles. During weekday evening peak hours, the load in this area will increase beyond the preset change rate threshold. During the rainy season or after heavy rain, a microclimate environment with high humidity, condensation, and poor heat dissipation is easily formed inside the box. The system no longer uses the surface temperature of the joint as the sole criterion for judgment, but instead focuses on the coupling relationship between hot spots inside the cable joint, aging of insulation materials, partial discharge, and changes in grid load to form an integrated link for monitoring, evaluation, and regulation. The details are as follows: The data acquisition module is installed in the cable branch box or in the control unit near it. It obtains the real-time current of the branch circuit through a current transformer or electronic current sensor, and obtains the discharge pulse signal near the joint through a high-frequency partial discharge sensor. It extracts the discharge amplitude and discharge frequency from the discharge pulse signal. The discharge amplitude reflects the energy level of a single discharge activity at the insulation defect, and the discharge frequency reflects the degree of activity of the local defect being repeatedly excited under the current electric field, humidity and pollution conditions. For environmental microclimate data, the data acquisition module obtains the temperature of multiple points on the surface of the cable joint through temperature sensors attached to different circumferential and axial positions, and obtains the humidity inside the box through humidity sensors. Since the temperature of the outer surface of the joint is not the same as the true highest temperature of the internal conductor, contact or crimp interface, the internal state observation module further combines the physical fact of the heat source generated by the real-time current and the heat dissipation boundary reflected by the multi-point surface temperature to estimate the true temperature of the location where the highest temperature is concentrated inside the joint. After obtaining the actual maximum internal temperature, the lifespan calculation module extracts temperature cycle characteristics. These temperature cycle characteristics are not simply recording the maximum temperature, but rather focusing on the micro-movements of the metal contact surface, relaxation of the crimp interface, and thermal fatigue of the insulation material caused by repeated temperature rises and falls. For cable joints, being in a state of repeated thermal expansion and contraction without exceeding the temperature for a long time will also gradually increase the contact resistance and make it easier for local hot spots to form. The lifespan calculation module also incorporates the humidity inside the enclosure and high-frequency partial discharge pulse data into the same calculation process. High humidity reduces the creepage margin of insulation surfaces and promotes water treeing. Partial discharge indicates that there is electric field concentration or micro-gaps inside or at the interface of the insulation. When both occur simultaneously with high temperature, insulation aging is significantly accelerated. The system outputs the real-time insulation life consumption rate based on this, so that maintenance personnel can see not only whether the current temperature is safe, but also the intensity of the current operating state's consumption of the remaining insulation life. The health status assessment module generates a predicted value of remaining service life, a health index of the cable branch box, and a warning information on remaining service life based on the real-time insulation life consumption rate. The health index can be set to close to 1 to indicate that the equipment meets the preset normal operation indicators, and close to 0 to indicate that the equipment has insufficient life reserve. The feedforward coordinated adjustment module further receives the health index, the warning information on remaining service life, and the distribution network load forecast data issued by the upper-level dispatch system to determine whether it is necessary to start local microclimate adjustment in advance before the arrival of the load peak, or to issue global grid dispatch instructions related to load transfer, load limiting, or dynamic capacity expansion boundaries to the distribution automation master station when the physical adjustment in the box is insufficient to suppress the accelerated life consumption. To facilitate understanding of the data flow, a simplified process can be described as follows: Within a sampling period, the data acquisition module generates a set of status records, which include fields representing current status, connector surface temperature status, internal humidity status, discharge status, and future load trends. The internal status observation module converts these status records into internal hotspot status. The lifespan consumption calculation module then converts the internal hotspot status, humidity status, and discharge status into lifespan consumption status. The health status assessment module summarizes the lifespan consumption status from multiple consecutive periods into a health status. The feedforward coordinated adjustment module outputs internal adjustment actions or grid dispatch requests based on the health status and future load trends. This process reflects the step-by-step transformation of data from measurable quantities to actual equipment failure risk quantities, rather than simply issuing temperature over-limit alarms. Furthermore, to maintain consistency in terminology throughout the text, the aforementioned in-box adjustment action corresponds to the local microclimate adjustment command in the embodiment, the power grid dispatch request corresponds to the global power grid dispatch command, the internal hotspot status corresponds to the actual highest temperature inside the joint and its location characterization result, and the life consumption status corresponds to the real-time insulation life consumption rate and its associated risk level. Therefore, in the subsequent description of this embodiment, if simplified expressions such as adjustment action, dispatch request, and hotspot status appear, they are all procedural descriptions of the terminology in the aforementioned embodiment and do not indicate the addition of different modules or different technical objects. In case of anomalies or data loss, if a surface temperature sensor at a connector temporarily loses connection, the system can verify its effectiveness by using the trends of other measuring points at the same connector and adjacent sampling periods, and mark the measuring point as requiring maintenance. If a high-frequency partial discharge sensor experiences isolated spikes due to interference from external switch operations, the system can filter these spikes by checking the continuity of discharge frequency and the repetition of multiple periods to avoid misjudging occasional electromagnetic disturbances as persistent insulation defects. If the communication interface is temporarily unable to obtain load forecast data from the upper-level dispatching system, the system can temporarily degrade to a conservative control mode based on local real-time current trends and historical load curves of similar days, and prohibit the output of mandatory load transfer commands that require grid-side cooperation to avoid miscontrol due to incomplete dispatching information. In the aforementioned business district example scenario, on a weekday afternoon, the system detected that the current in a certain branch circuit was increasing with the increase in the number of charging piles put into operation. The temperature of multiple measuring points on the connector surface had not yet exceeded the traditional alarm temperature, but the humidity inside the box remained at a high level, and the high-frequency partial discharge signal began to show repetitive pulses. The internal status observation module determined that the hot spot inside the connector was higher than the visible temperature on the outer surface, and the life consumption calculation module recognized that this state would significantly accelerate the consumption of insulation life. Based on this, the health status assessment module reduced the health index, and when the upper-level scheduling system predicted that there would still be a peak charging load at night, the feedforward collaborative adjustment module output dehumidification, ventilation, and load collaborative adjustment related instructions in advance. The purpose of this mechanism is to upgrade the monitoring objects of cable branch boxes from visible temperature, humidity and current values ​​to the life risks under the combined effects of internal hot spots, insulation aging and load impact, so as to achieve early identification and proactive adjustment of hidden joint deterioration and reduce the delayed handling caused by relying solely on over-limit alarms. The internal state observation module is specifically used for: Input the multi-point temperature and real-time current of the joint surface into the preset thermal resistance and thermal capacity network model; The Joule heat generation rate is calculated by multiplying the square of the real-time current by the preset initial value of the contact resistance obtained from the factory parameters or acceptance test records. By combining the Joule heat generation rate and the temperature at multiple points on the joint surface, the true maximum temperature inside the joint can be deduced.

[0017] This embodiment provides a mechanism for internal state observation. Specifically, during the continuous operation of the aforementioned cable branch box in the business district, relying solely on the temperature of the patch on the outer surface of the connector has technical limitations: the outer surface temperature is affected by the airflow inside the box, the sensor mounting position, the thickness of the connector insulation layer, and the heat conduction path of the metal shielding layer, and may lag behind the actual temperature rise of the internal conductor and the crimping interface; when the charging pile load rises rapidly, the Joule heat inside the connector first accumulates in the conductor and contact interface, while the outer surface temperature needs to be conducted through the insulation layer and sheath before gradually increasing. Therefore, it is necessary to introduce internal state observation based on the thermal resistance and thermal capacity network model. The following is a detailed description: The internal state observation module inputs the multi-point temperature and real-time current of the connector surface into a preset thermal resistance and thermal capacity network model. This thermal resistance and thermal capacity network model can treat the cable connector as a heat transfer network composed of an internal conductor, contact interface, insulation layer, sheath layer, and air boundary inside the box. Thermal resistance is used to characterize the ease of heat transfer between different material layers, and thermal capacity is used to characterize the hysteresis characteristics of temperature change after each material layer absorbs heat. When the real-time current flows through the connector contact resistance, Joule heating is generated, which is one of the main heat sources for the formation of internal hot spots. The initial value of the contact resistance can be obtained from factory parameters, acceptance test records, calibration data of connectors of the same model, or benchmark test data after installation. The system determines the current heat source intensity through the real-time current and the initial state of the contact resistance, and then, combined with the external heat dissipation boundary reflected by the multi-point temperature of the connector surface, it infers the true maximum temperature inside the connector. The pre-defined thermal resistance and thermal capacity network model specifically constructs a multi-dimensional thermal node network that characterizes the internal conductor, contact interface, insulation layer, sheath layer, and air boundary inside the box. It uses the thermal conductivity and specific heat capacity of each physical layer material to set the equivalent thermal resistance and thermal capacity between nodes. Based on the law of conservation of energy, it establishes a set of thermal balance differential equations for each node. Combining the Joule heat generated by real-time current and the multi-point temperature boundary conditions on the joint surface, iteratively solves the temperature distribution of each internal node and extracts the true highest temperature inside the joint. For ease of understanding, a simplified data flow example can be used: the surface measuring points can be simplified to three locations, representing the temperature status of the left, middle, and right sides of the connector, respectively; when all three measuring points are in a state where the temperature is rising and the temperature change rate of the middle measuring point is greater than that of the other measuring points, the thermal resistance and thermal capacity network model will determine that the internal heat source is closer to the middle contact interface; when the real-time current increases synchronously, the model will attribute the temperature rise more to the Joule heat generated by the load current, rather than simply the ambient temperature rise; therefore, the output of the internal state observation module is not a direct reading of a certain measuring point, but the location of the highest temperature most likely to occur inside the connector and its thermal state; Under the fault tolerance mechanism, if the temperature difference between multiple points on the surface is abnormal, such as a certain measuring point suddenly being lower than the ambient temperature inside the box or having a completely opposite trend to that of adjacent measuring points, the system can determine that the measuring point has detachment, poor contact, or acquisition failure, and reduce the weight of the measuring point in the thermal resistance and thermal capacitance network model or temporarily remove the measuring point; if the real-time current sensor shows short-term distortion, the system can use the current balance relationship of adjacent loops, the measurement value on the switch cabinet side, or the current state of the previous stable cycle for reliability verification; if the initial value of the contact resistance is missing, the system can use conservative initial parameters of the same type and specification connector, and include the branch box in the list of equipment that needs to be verified on-site; In the main scenario of the business district, before the start of the evening rush hour, the surface temperature of the connector was still within an acceptable range. However, the system found that the temperature rise rate of the middle measuring point was faster than that of the two measuring points at both ends. At the same time, the real-time current had increased with the commissioning of the charging pile. Based on the thermal resistance and thermal capacity network model, the internal state observation module determined that a hot spot with a temperature higher than the surface reading may have formed inside the connector crimping interface, and provided the actual highest internal temperature to the subsequent lifespan consumption calculation process. The purpose of this step is to compensate for the lag in the response of surface temperature measurement to internal hot spots, so that subsequent aging assessments are based on the thermal state closer to the failure source, thereby improving the ability to identify contact interface heating and insulation thermal damage in advance. The lifespan calculation module is also used to calculate cumulative mechanical stress damage to generate predicted contact resistance values, specifically including: The amplitude and frequency of temperature cycles were extracted from the actual highest temperature inside the joint using the rainflow counting method, and used as temperature cycle characteristics. Using the linear cumulative damage rule, the cumulative damage value of the micro-mechanical stress on the internal contact surface of the joint is calculated based on the amplitude and frequency. The cumulative damage value is multiplied by a preset resistance ratio coefficient to obtain the contact resistance increment, and the preset initial contact resistance value is added to the contact resistance increment to generate the predicted contact resistance value.

[0018] This embodiment provides a mechanism for predicting contact resistance. Specifically, based on the aforementioned internal hotspot observation, if contact resistance is considered as a fixed parameter, there will be technical limitations in long-term operation scenarios: cable joints repeatedly expand and contract under the influence of daily load peak and valley changes, intermittent start and stop of charging piles, and ambient temperature fluctuations, resulting in slight displacement of the metal contact surface, attenuation of clamping force, and disturbance of oxide film; even if the temperature does not exceed the alarm threshold at any time, repeated temperature cycles will gradually accumulate mechanical stress damage and cause the contact resistance to rise; therefore, this embodiment introduces temperature cycle characteristics and mechanical stress accumulation damage into the life consumption calculation module. The following is a detailed description: The lifespan calculation module uses the rainflow counting method to extract the amplitude and frequency of temperature cycles from the time series of the actual highest temperature inside the joint. The rainflow counting method is suitable for describing the cyclic process of repeated loading and unloading in material fatigue. Mapped to the cable joint scenario, the temperature rise corresponds to the thermal expansion of the metal and insulation structure, and the temperature drop corresponds to the thermal contraction. The larger the cycle amplitude and the higher the frequency, the more obvious the fretting fatigue of the contact surface. The module uses the linear cumulative damage law to accumulate the microscopic mechanical damage caused by different temperature cycles. This cumulative damage does not indicate that the joint has failed immediately, but rather indicates the degree of deterioration of the crimping interface relative to the initial fastening state. The system then correlates the cumulative damage with a preset resistance ratio coefficient to obtain the contact resistance increment, which together with the initial contact resistance forms the predicted contact resistance value. The preset resistance ratio coefficient is an empirical constant. Its specific value is obtained in advance by performing thermal cycling fatigue calibration tests on cable joints of the same type and specification, fitting the positive proportional relationship between the cumulative damage value of micro-mechanical stress and the measured change in contact resistance. It is used to characterize the increase in contact interface resistance corresponding to a unit of mechanical damage. Furthermore, to ensure consistency between this embodiment and the aforementioned internal state observation process, the predicted contact resistance value, once generated, can be used as the contact resistance update parameter in the thermal resistance-capacity network model for subsequent sampling cycles. In this embodiment, the preset initial contact resistance value used to calculate the Joule heat generation rate corresponds to a baseline parameter at the initial stage of system commissioning, after maintenance and reset, or before an effective cumulative damage record has been formed. During continuous operation, the internal state observation module can manage the versions of this baseline parameter and the predicted contact resistance value generated in this embodiment without changing the meaning of the embodiment's description: the initial contact resistance value is used for the first calculation or after maintenance and reset, while the latest predicted contact resistance value is preferentially used as the equivalent contact resistance for subsequent rolling calculations. Thus, the Joule heat generation rate, the actual maximum internal temperature, temperature cycle damage, and the new predicted contact resistance form a cycle-by-cycle iterative relationship, avoiding the ambiguity caused by treating the contact resistance as a static constant in the previous text and then treating it as a dynamic quantity in the later text. To facilitate understanding, a simplified explanation can be provided: Within a certain period, the sequence of highest internal temperatures can be identified into two categories: small-amplitude cycles and large-amplitude cycles. Small-amplitude cycles represent the switching between light and medium loads during normal operation, while large-amplitude cycles represent the rapid thermal shock caused by the concentrated commissioning of charging piles or a sudden increase in commercial air conditioning load. The system no longer treats each sampling point as an independent risk feature, but instead extracts the above-mentioned rise and fall process as a cyclic event. The single mechanical stress damage value of a small-amplitude cycle is less than or equal to a set threshold, but the frequency of occurrence is greater than a frequency threshold; the frequency of occurrence of a large-amplitude cycle is less than or equal to a frequency threshold, but the single mechanical stress damage value is greater than a set threshold. After accumulation, the predicted contact resistance value will gradually increase from the initial installation state with long-term thermal cycling, thus reflecting the amplification effect of joint aging on subsequent heat generation. Furthermore, in the first operating phase, the system uses the initial contact resistance value to estimate Joule heat. After several temperature cycles are identified and accumulated, the system obtains a contact resistance prediction value higher than the initial value. When entering the next operating phase, the internal state observation module uses the updated equivalent contact resistance to re-estimate Joule heat and internal hot spots, so that the subsequent lifetime consumption calculation can reflect the evolution link of increased contact resistance and, in turn, increased temperature. In cases of anomalies or missing data, if there are sampling gaps in the temperature sequence, the module can first determine whether the gap duration is shorter than the preset interpolation time. Short gaps can be smoothly filled according to the preceding and following trends, while long gaps are not included in the fatigue cycle count and an uncertainty metric is added to the health assessment. If a temperature mutation is detected that is inconsistent with changes in current and environment, the system can regard it as a candidate event for sensor anomalies to avoid including fault readings in mechanical fatigue damage. If a cable joint has just been repaired or re-crimped, the system can reset or correct the initial state of the contact resistance based on maintenance confirmation information to prevent old damage records from continuing to affect the assessment of new joints. In this reset scenario, subsequent internal state observations will also resume using the new initial value of the contact resistance as the benchmark for heat source estimation. In the business district example scenario, the load fluctuation of the cable branch box was within the preset allowable range. In the evening, due to the successive connection of charging piles, multiple temperature rise and fall cycles occurred. Although the highest temperature on the joint surface did not reach the traditional alarm point, the hot spot temperature curve output by the internal status observation module showed frequent rise and fall processes. The life consumption calculation module sorted these rise and fall processes into temperature cycle events and updated the contact resistance prediction value accordingly, indicating that the joint may generate more heat under the same load in the future. The purpose of this mechanism is to incorporate hidden damage caused by repeated thermal cycling without exceeding the temperature into the system evaluation, so that the contact resistance is no longer regarded as a static constant, thereby revealing the long-term evolution process of electrothermal amplification caused by mechanical loosening of cable joints. The lifetime consumption calculation module is specifically used for calculating the real-time insulation lifetime consumption rate when: Based on the Arrhenius equation, the temperature-activated aging term is calculated based on the actual highest temperature inside the joint, and the humidity correction term is determined based on the humidity inside the chamber. The temperature-activated aging term and the humidity correction term are combined to convert into the base aging rate. Using the inverse power law relationship, the discharge amplitude and discharge frequency in high-frequency partial discharge pulse data are converted into electrical stress acceleration factors; Multiply the base aging rate by the electrical stress acceleration factor to output the real-time insulation life consumption rate.

[0019] This embodiment provides a mechanism for calculating the real-time insulation life consumption rate. Specifically, after estimating the evolution of internal hot spots and contact resistance, if equipment health is still evaluated solely based on temperature, the combined accelerating effects of high humidity microclimate and partial discharge on insulation materials will be ignored. In cable branch boxes, the molecular chain movement of insulation materials intensifies at high temperatures, accelerating chemical aging. In high humidity environments, conductive channels or water trees are more likely to form on insulation surfaces and at internal defects. Under repeated partial discharge, micro-gaps, interface defects, and contamination traces are continuously eroded. Therefore, this embodiment incorporates thermal aging, humidity effects, and electrical stress into the life consumption calculation. The following is a detailed description: The lifespan consumption calculation module, based on the thermal activation aging law expressed by the Arrhenius equation, converts the actual maximum temperature inside the joint and the humidity inside the box into a basic aging rate; the basic aging rate here is used to describe the chemical aging intensity of the insulating material under the current hot and humid environment and without significant partial discharge conditions; the higher the temperature, the more active the internal chemical reaction and oxidation process of the material; the higher the humidity, the more obvious the impact of interface polarization, condensation and moisture migration on the insulation strength; The module uses the inverse power law to convert the discharge amplitude and frequency in high-frequency partial discharge pulse data into an electrical stress acceleration factor. When the discharge amplitude is greater than a preset amplitude threshold, it indicates that the electrical stress impact of a single discharge on the local insulation is greater than the benchmark value. When the discharge frequency is greater than a preset frequency threshold, it indicates that the defect is subjected to repeated electric field action within a preset time period, and the insulation erosion accumulation rate increases. The module combines the basic aging rate with the electrical stress acceleration factor to output the real-time insulation life consumption rate. To avoid mechanically interpreting humidity as part of the Arrhenius temperature term itself, in engineering implementation, the basic aging rate can be broken down into two steps: temperature-activated aging term and humidity correction term. First, the thermal aging strength of the insulation material at the current temperature is determined based on the actual highest temperature inside the joint, and then the thermal aging strength is corrected based on the humidity range inside the box. For example, when the humidity inside the chamber is in the dry or normal range, the humidity correction term is close to the baseline state; when the humidity inside the chamber is close to the condensation risk zone or the long-term high humidity zone, the humidity correction term is increased, so that the basic aging rate reflects the risk of moisture migration, decreased surface creepage margin and water treeing. After this treatment, the Arrhenius equation is still used to express the dominant role of temperature on the chemical aging reaction rate, while the humidity inside the chamber is used as an environmental acceleration correction factor in the same basic aging rate. The two together form the thermal and humid basic aging result, avoiding the confusion of different physical mechanisms into a single temperature formula. In specific engineering implementation, the activation energy constant and pre-exponential factor of the insulation material contained in the above Arrhenius equation and temperature-activated aging term are all pre-determined and solidified in the system through laboratory accelerated thermal aging tests on the corresponding grade of insulation material in the cable branch box, so as to ensure the physical accuracy of the basic aging rate calculation. For ease of understanding, a simplified state transition example can be used: The system divides the thermal and humidity state into three levels: the first warning interval, the second warning interval, and the third warning interval, and the discharge state into three levels: no obvious repetitive discharge, slight repetitive discharge, and active repetitive discharge. When the thermal and humidity state is high and the discharge state is slight repetitive discharge, the lifespan depletion state is determined to be at the level requiring attention. When the thermal and humidity state enters the severe level and is accompanied by active repetitive discharge, the lifespan depletion state enters the level requiring active intervention. This state transition reflects the physical degradation trend of the insulating material under multiple stresses of heat, humidity, and electricity, rather than simply reacting to a single sensor reading exceeding the limit. Under the fault-tolerant mechanism, if short-duration dense pulses appear in the partial discharge pulse data at the moment of switching operation, the system can identify them by combining the switching status record and waveform duration, and distinguish between transient operation and continuous partial discharge; if the humidity sensor detects near saturation but the temperature measuring point does not show a risk of condensation, the system can cross-verify the humidity inside the chamber with the chamber wall temperature or the ambient temperature to prevent misjudgment caused by contamination of a single humidity probe; if the partial discharge sensor is under maintenance or offline, the module can only output a basic aging assessment based on the thermal and humid environment, while setting the electrical stress acceleration factor to a conservative state or marking it as pending confirmation, to avoid giving overly accurate life conclusions when key data is missing; In the main scenario of the business district, the humidity in the underground space increases after the rainstorm, and the humidity in the cable branch box remains high for a long time. After the charging load increases in the evening, the internal hot spot temperature rises accordingly, and the high-frequency partial discharge sensor captures repetitive pulses. The life consumption calculation module identifies the thermal and humidity conditions as the basic aging enhancement state and identifies the repetitive discharge pulses as the electrical stress acceleration factor, and finally outputs a high real-time insulation life consumption rate. The purpose of this mechanism is to avoid simplifying insulation life assessment to a single temperature judgment, thereby achieving real-time quantification of high temperature, high humidity and partial discharge coupling degradation, and providing a unified risk scale for subsequent health assessment and active adjustment; The health status assessment module is specifically used for: The cumulative lifetime loss value is obtained by integrating the real-time insulation lifetime consumption rate over time. The remaining service life is predicted by subtracting the cumulative service life loss value from the preset initial design life of the cable branch box. The ratio of the predicted remaining service life to the initial design life of the cable branch box is used as the health index of the cable branch box. The configuration is as follows: if the predicted remaining service life is lower than the preset service life threshold, then generate a warning message for the remaining service life; otherwise, generate a normal operating status data label.

[0020] This embodiment provides a mechanism for health status assessment. Specifically, after the real-time insulation life consumption rate has been established, if the system only displays the aging intensity at a certain moment, it still cannot meet the needs of asset management and maintenance decision-making. The failure of cable branch boxes is usually not caused by a single high temperature or a single discharge, but is gradually accumulated under the combined action of long-term thermal, damp and electrical stress. Therefore, this embodiment transforms real-time risks into equipment health status that can be used for operation and maintenance planning by using cumulative life loss, predicted remaining service life, and health index. The details are as follows: The health status assessment module accumulates the real-time insulation life consumption rate over time to obtain the cumulative life loss value; this accumulation process can be understood as continuously recording the aging history data experienced by the equipment at different operating stages: under low load, low humidity, and no obvious discharge, the real-time insulation life consumption rate is lower than the standard benchmark value; under high load, high humidity, and active partial discharge, the real-time insulation life consumption rate is higher than the standard benchmark value. The module uses the preset initial design life of the cable branch box to subtract the cumulative life loss value to obtain the remaining service life prediction value; the initial design life can be determined based on the equipment manufacturer's data, insulation material grade, installation specifications and operation and maintenance unit's asset ledger; the health index is obtained from the relative relationship between the remaining service life prediction value and the initial design life, and is used to map branch boxes with different installation times and different specifications to a unified health evaluation scale. In terms of specific measurement methods, the real-time insulation life consumption rate can be configured as the equivalent life consumed per unit time, or as a life consumption multiple relative to rated operating conditions. When it is configured as the equivalent life consumed per unit time, the health status assessment module directly accumulates the cumulative life loss value according to the sampling period. When it is configured as a life consumption multiple, the health status assessment module first multiplies the multiple by the corresponding sampling period duration to convert it into equivalent life consumption time, and then accumulates it. Therefore, the cumulative life loss value is kept in the same or convertible time dimension as the initial design life of the cable branch box, avoiding the situation where the dimensionless risk score is directly deducted from the design life; if a certain hour is operated under the benchmark aging conditions, then that hour can be recorded as an equivalent life loss of about one hour; if the consumption rate is significantly increased under the superposition of high temperature, high humidity and repeated discharge conditions, then the same one hour can be recorded as an equivalent life loss of more than one hour. To facilitate understanding, a simplified scenario can be used: The system divides a day into several operating segments. The first segment represents a low-load, dry state at night; the second segment represents a high-load, humid state during the evening peak; and the third segment represents a recovery state after the load has decreased. The cumulative lifespan loss increment in the first segment is lower than the set average, while the cumulative lifespan loss increment in the second segment is higher than the set average. The contribution of the third segment is determined based on humidity and whether the discharge has recovered. The health status assessment module does not treat the second segment as an isolated single alarm event, but rather incorporates it into the long-term cumulative lifespan data model to obtain the predicted remaining lifespan and health index. Under the fault tolerance mechanism, if the cumulative lifespan loss value cannot be fully obtained due to missing historical data, the system can establish an initial estimate from the equipment commissioning date, inspection records, historical alarm records, and operating data of the same model of equipment in the same area, and gradually correct it in subsequent operation; if the predicted remaining lifespan value is close to the preset lifespan threshold but the data confidence level is low, the system can generate a warning level that needs to be reviewed, instead of directly giving a shutdown recommendation; if the predicted remaining lifespan value is not lower than the threshold, the system generates a normal operating status data label, while retaining the lifespan consumption trend record for comparison in subsequent high-load seasons; In the main scenario of the business district, the cable branch box has been in operation for many years. After a period of continuous monitoring, the system found that the life consumption rate fluctuated less than the set threshold on ordinary working days. However, during the nights after heavy rain and the peak charging load, the real-time insulation life consumption rate increased significantly. The health status assessment module included these high consumption periods in the cumulative life loss value and found that the predicted value of the remaining service life was close to the maintenance threshold set by the operation and maintenance unit. Therefore, it generated the remaining service life warning information and reduced the health index at the same time. The purpose of this mechanism is to transform instantaneous monitoring results into long-term life management indicators, thereby supporting equipment maintenance prioritization, load operation strategy adjustment, and asset status assessment, and avoiding passive handling based solely on a single temperature alarm. The process by which the feedforward collaborative regulation module generates local microclimate regulation instructions includes: The configuration is as follows: if the real-time insulation life consumption rate is greater than the preset aging critical threshold, then a local microclimate adjustment command is generated to trigger the dehumidification equipment and cooling fan based on the humidity inside the box; otherwise, a command is generated to maintain the current operating state.

[0021] This embodiment provides a mechanism for local microclimate regulation. Specifically, if the system only generates an early warning without changing the environment inside the box after the health status can be assessed, it is still considered passive monitoring. In underground spaces, coastal cities, or rainy season scenarios, high humidity and hot spot temperature rise often coexist in cable branch boxes. Simply starting the fan after the temperature exceeds the limit is insufficient to meet the timeliness requirements for suppressing accelerated insulation aging. Therefore, this embodiment introduces local microclimate regulation based on the real-time insulation life consumption rate in the feedforward collaborative regulation module. The following is a detailed description: The feedforward collaborative adjustment module compares the real-time insulation life consumption rate with the preset aging critical threshold. This aging critical threshold can be set by the operation and maintenance unit based on the insulation material grade, equipment importance, regional power supply reliability requirements, and historical fault experience. It is used to identify the state where continuing to maintain the current environment will significantly accelerate the life consumption. When the real-time insulation life consumption rate is greater than the aging critical threshold, the module no longer only judges whether the temperature exceeds the limit, but also generates a local microclimate adjustment command in combination with the humidity inside the box. If the humidity inside the chamber exceeds the preset humidity threshold, the dehumidification equipment will be triggered first to reduce the risk of condensation, moisture migration and surface creepage; if the internal hot spot temperature exceeds the preset temperature threshold or the heat dissipation is insufficient, the cooling fan will be triggered to promote airflow inside the chamber and reduce heat accumulation near the joints; if the real-time insulation life consumption rate does not exceed the aging critical threshold, the system will generate instructions to maintain the current operating state to avoid frequent start-stop of the equipment, which would increase energy consumption and wear of the actuators. For ease of understanding, a simplified control state example can be used: when the lifespan consumption state is normal, the actuator remains in standby mode; when the lifespan consumption state is high and the humidity is high, the dehumidifier operates first; when the lifespan consumption state is high and the temperature rise is significant, the cooling fan operates first; when the lifespan consumption state is high and both humidity and temperature rise are unfavorable, the dehumidifier and the cooling fan operate in coordination. The core of this control logic lies in adjusting according to the causes of insulation aging, rather than mechanically separating temperature and humidity into two unrelated control loops. Under the fault-tolerant mechanism, if the dehumidification equipment is in a fault or maintenance state, the system can generate dehumidification failure feedback, increase the operating priority of the cooling fan, and send on-site handling prompts to the operation and maintenance platform; if the humidity inside the chamber may further increase due to the entry of external humid air after the cooling fan starts running, the system can limit the continuous operation time of the fan or adopt an intermittent ventilation and dehumidification linkage strategy; if the real-time insulation life consumption rate does not exceed the threshold but the humidity inside the chamber is close to the condensation risk zone, the system can start low-intensity preventive dehumidification without triggering the complete high-risk adjustment process; if the sensor data is not reliable enough, the system can adopt a conservative maintenance strategy and require manual verification to avoid accidental activation of the actuator; In the main scenario of the business district, the humidity inside the box increases after a rainstorm, and the charging load increases in the evening, causing the internal hot spot temperature to rise. The system determines that the real-time insulation life consumption rate exceeds the critical aging threshold, and humidity is one of the main adverse factors. Therefore, the feedforward collaborative adjustment module outputs a local microclimate adjustment command to start the dehumidification equipment and link the cooling fan to improve the humid and hot environment inside the box before the load peak arrives. If the weather clears up the next day, the humidity inside the box decreases, and the load is stable, the system generates a command to maintain the current operating state to avoid unnecessary equipment start-ups and shutdowns. The purpose of this mechanism is to actively disrupt the high-temperature and high-humidity coupling environment before the accelerated aging of insulation occurs, thereby reducing the triggering conditions for partial discharge and chemical aging of materials, and realizing the transformation from passive alarm to active environmental regulation. The process by which the feedforward coordinated regulation module generates global power grid dispatch instructions includes: The configuration is as follows: if the real-time insulation life consumption rate after the execution of the local microclimate adjustment command continues to be greater than the aging critical threshold within the preset time window, then the dynamic capacity expansion limit value is calculated based on the distribution network load forecast data, and a global power grid dispatch command containing a local load transfer request is output to the upper-level dispatch system; otherwise, normal state confirmation information that does not require load transfer is generated.

[0022] This embodiment provides a mechanism for global power grid dispatch coordination. Specifically, even after local microclimate regulation can be activated, there may still be technical limitations: when the cable branch box is under continuous high load power supply, or when the joint itself has reached the deterioration state of the preset aging assessment threshold, dehumidification and heat dissipation can only improve the external environment and cannot reduce the Joule heat generated by the current; if the branch box continues to be subjected to a load exceeding the rated capacity limit, even if the fan and dehumidification equipment are already running, the real-time insulation life consumption rate may still remain high; therefore, this embodiment introduces grid-side load coordination when local regulation is insufficient. The details are as follows: After the local microclimate adjustment command is executed, the feedforward collaborative adjustment module continues to monitor whether the real-time insulation life consumption rate is continuously greater than the aging critical threshold within the preset time window; the preset time window is used to eliminate short-term disturbances, such as when the air flow is not yet stable when the fan is first started, or the short-term increase caused by instantaneous load fluctuations; only when the high consumption state continues to exist within this window, the system determines that the risk cannot be fully suppressed by the box adjustment alone. At this point, the module calculates the dynamic capacity expansion limit value based on the distribution network load forecast data. The dynamic capacity expansion limit value can be understood as the load boundary that the branch box can still safely bear under the combined constraints of the current internal hotspots, the microclimate inside the box, the health index, and the future load trend. If the predicted load will exceed this boundary, the system outputs a global power grid dispatching instruction to the external distribution automation master station. This instruction includes a local load transfer request, so that some loads can be borne by adjacent feeders, backup ring network paths, or adjustable load resources. To make the relationship between the dynamic capacity expansion limit calculation process and the distribution network load forecast data clearer, in the specific implementation, the feedforward coordinated adjustment module does not only give a fixed limit based on the future load curve itself, but also uses the distribution network load forecast data as the future current sequence to be tested, and combines the currently observed real-time insulation life consumption rate, the humidity change trend inside the box after local adjustment, and the health index to perform boundary search. Specifically, the system can first obtain the expected current levels for several future periods from the predicted load curve, and then perform trial calculations according to candidate load levels from low to high: for each candidate load level, the system estimates its corresponding internal heating trend and life consumption trend; if the candidate level will not cause the real-time insulation life consumption rate to continuously exceed the aging critical threshold during the predicted period, it is considered an acceptable load level; if continuing to increase the candidate level will cause the life consumption rate to continuously exceed the aging critical threshold again, then the previous acceptable load level is used as the dynamic capacity expansion limit value; in this way, the dynamic capacity expansion limit value reflects both the feedforward constraint of load prediction on future current and the limitation of local equipment health status on load capacity; For ease of understanding, a simplified example of scheduling status can be used: After local adjustment is executed, the system generates two results: mitigated and unmitigated. If the lifetime consumption status decreases from an abnormally high value to an acceptable range, a normal status confirmation message indicating no load transfer is required is output. If the lifetime consumption status remains high and load forecasting shows continued charging demand in the evening, the system generates a scheduling request that includes suggestions to reduce the load of this branch box, transfer some charging piles or commercial air conditioning loads, etc. This request does not directly replace the master station's scheduling decision, but rather transforms the underlying equipment lifetime risk into a constraint that the power grid can recognize. Under the fault-tolerant mechanism, if the distribution network load forecast data is missing or delayed, the system will not output a precise dynamic capacity expansion limit value, but will instead send a local risk status and conservative load reduction suggestion to the master station. If the master station reports that the current grid topology does not meet the conditions for load transfer, the system can maintain local microclimate adjustment and raise the warning level, prompting maintenance personnel to conduct on-site inspections or arrange temporary load limits. If the real-time insulation life consumption rate shows a downward trend within the preset time window but is still slightly higher than the threshold, the system can extend the observation window and maintain local adjustment to avoid frequent requests for grid-side switching due to short-term boundary states. If the consumption rate recovers to an acceptable range after local adjustment, the system generates normal state confirmation information that no load transfer is required and records the effect of this adjustment for subsequent strategy optimization. In the main scenario of the business district, dehumidification equipment and cooling fans have been running in advance, but the concentrated charging load continues to rise at night. The system found that the real-time insulation life consumption rate failed to fall within the continuous observation window. Data from the distribution network load forecast showed that the charging demand would remain high in the next few hours. Based on this, the feedforward coordinated adjustment module generated information related to the dynamic capacity expansion limit value and output a global grid dispatching instruction containing a local load transfer request to the distribution automation master station, suggesting that some transferable loads be transferred to adjacent power supply paths or that peak shaving be performed on the adjustable charging load. The purpose of this mechanism is to transfer the equipment life risk of the cable branch box to the distribution network operation control layer when the microclimate regulation inside the box reaches the capacity boundary. In this way, the intensity of the joint heat source is reduced by changing the power flow distribution, thereby achieving the coordination of local equipment protection and global power supply dispatch. Example 2: The system also includes an adaptive correction module, used for: The updated environmental microclimate data after executing local microclimate regulation commands and global power grid dispatch commands is obtained through the data acquisition module. The updated environmental microclimate data is fed back to the life consumption calculation module to recalculate the real-time insulation life consumption rate, forming a dynamic closed-loop control.

[0023] This embodiment provides a mechanism for adaptive correction and dynamic closed-loop control. Specifically, after the aforementioned local adjustment and global scheduling commands are executed, if there is a lack of feedback on the adjustment results, it is difficult to accurately assess the improvement effect of the control commands on the microclimate inside the box and the insulation life consumption status. Different cable branch boxes have different installation locations, sealing levels, ventilation paths, joint aging levels, and surrounding heat source conditions, so the same dehumidification or heat dissipation commands may produce different effects. Therefore, this embodiment sets up an adaptive correction module to feed back the adjusted environmental microclimate changes to the life consumption calculation process, forming a continuously correcting closed loop. The details are as follows: After the local microclimate adjustment command is executed, the adaptive correction module obtains the updated multi-point temperature of the connector surface, humidity inside the box, and necessary real-time current and partial discharge data through the data acquisition module; if the global power grid dispatch command is adopted by the master station and causes load transfer, the module can also confirm whether the load-side adjustment has actually occurred through real-time current changes. The adaptive correction module feeds back the updated environmental microclimate data to the lifetime consumption calculation module to recalculate the real-time insulation lifetime consumption rate. If the recalculation result shows that the lifetime consumption has decreased to an acceptable range, the system maintains the current control state and records that the adjustment is effective. If the recalculation result is still too high, the system can continue to maintain or upgrade the adjustment action and classify the abnormal reasons as such as humidity not decreasing, insufficient heat dissipation, load not decreasing, or partial discharge still active. Furthermore, in order to keep the closed-loop logic consistent with the data link in the embodiment, the updated environmental microclimate data in this embodiment still uses the multi-point temperature of the joint surface and the humidity inside the box as the main feedback quantities; wherein, after the multi-point temperature of the joint surface is fed back, the internal state observation module first re-inverts to obtain the new true maximum temperature inside the joint, and then the life consumption calculation module re-calculates the real-time insulation life consumption rate in combination with the humidity inside the box. In this embodiment, real-time current and partial discharge data serve as synchronous reference values ​​to verify whether the adjustment is actually effective and to support recalculation. They do not change the core link of the updated environmental microclimate data being fed back to form dynamic closed-loop control. In other words, the main feedback path of the closed loop is configured as follows: the adjusted surface temperature and humidity inside the chamber are input into the internal state observation module to generate the true maximum temperature inside the connector, which is then input into the lifespan consumption calculation module. Real-time current and partial discharge data continue to be input in parallel by the data acquisition module along the original path to ensure that the timing of the data used for recalculation is consistent with the on-site operating status. For ease of understanding, a simplified closed-loop process can be adopted: The system first outputs a local action of dehumidification and ventilation, and collects feedback data such as changes in humidity, surface temperature, and discharge frequency; if the humidity decreases, the temperature drops, and the discharge frequency decreases, the system marks the action as valid; if the humidity decreases but the temperature does not drop, it indicates that the main limitation may come from the load heat source or an increase in contact resistance; if the temperature drops but the discharge is still active, it indicates that the insulation defect may be quite obvious, and a higher level of geometric consistency anomaly or insulation damage inspection prompt needs to be generated; this closed-loop process enables the system to correct subsequent control strategies based on the actual response on site. In case of anomalies or missing data, if the actuator feedback shows that it has started but the environmental data has not changed significantly, the system can determine that the dehumidification equipment is draining abnormally, the fan duct is blocked, the enclosure is not properly sealed, or the sensor is malfunctioning, and send an equipment-side maintenance prompt to the operation and maintenance platform. If the real-time current does not decrease after the global scheduling command is issued, the system can identify that the master station has not executed the command, the topology does not have the conditions for power transfer, or the load-side response is insufficient, and continue to maintain local regulation and high-risk warnings. If the updated environmental microclimate data shows short-term reverse fluctuations, such as the fan starting causing a momentary disturbance in the humidity inside the enclosure, the system can set a stable observation period and then recalculate to avoid misjudging transient disturbances as regulation failures. If multiple closed-loop adjustments still cannot reduce the real-time insulation life consumption rate, the system can output on-site power outage maintenance or infrared retesting suggestions. In the business district example scenario, the system has activated the dehumidification equipment and cooling fan, and sent a partial load transfer request to the main station. The data acquisition module detects a decrease in humidity inside the box, a drop in surface temperature of some joints, and a decrease in the real-time current of the branch after the main station adopts the load transfer. The adaptive correction module feeds back these updated data to the lifetime consumption calculation module, and obtains a lower real-time insulation lifetime consumption rate again. The system then records this adjustment as a valid closed-loop event. If humidity decreases on another night but the partial discharge frequency does not decrease, the system further indicates that the joint may have an irreversible insulation defect, and on-site diagnosis needs to be arranged. The purpose of this mechanism is to enable the monitoring and control system to perform post-execution verification and continuous correction, thereby preventing control commands from remaining at the open-loop level and enabling cable distribution boxes in different installation environments to form a more stable dynamic closed-loop control based on their own responses.

[0024] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit it. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention.

Claims

1. An intelligent monitoring and control system for cable branch boxes, characterized in that, include: The data acquisition module is used to acquire real-time electrical status data and environmental microclimate data of the joints inside the cable branch box through local sensors installed in the cable branch box, and to acquire power distribution network load forecast data from the upper-level dispatching system through a communication interface; wherein, the real-time electrical status data includes real-time current and high-frequency partial discharge pulse data, the high-frequency partial discharge pulse data includes discharge amplitude and discharge frequency, and the environmental microclimate data includes multi-point temperature of the joint surface and humidity inside the cable branch box; An internal state observation module is used to calculate the true highest internal temperature of the joint based on the multi-point temperature on the joint surface and the real-time current. The lifespan consumption calculation module is used to extract temperature cycle characteristics based on the actual highest temperature inside the joint, and combine the actual highest temperature inside the joint, the humidity inside the box, and the high-frequency partial discharge pulse data to calculate the real-time insulation lifespan consumption rate. The health status assessment module is used to calculate the predicted value of the remaining service life based on the real-time insulation life consumption rate, and generate the cable branch box health index and the early warning information of the remaining service life. The feedforward coordinated adjustment module is used to generate and output local microclimate adjustment commands and global power grid dispatch commands for controlling the dehumidification equipment and cooling fans installed in the cable branch box, based on the health index of the cable branch box, the remaining service life warning information and the power distribution network load forecast data. The lifetime consumption calculation module is specifically used for calculating the real-time insulation lifetime consumption rate when: The temperature-activated aging term is calculated based on the Arrhenius equation and the actual highest temperature inside the joint. The humidity correction term is determined based on the humidity inside the chamber. The temperature-activated aging term and the humidity correction term are combined to form the base aging rate. Using the inverse power law relationship, the discharge amplitude and discharge frequency in the high-frequency partial discharge pulse data are converted into an electrical stress acceleration factor; Multiply the basic aging rate by the electrical stress acceleration factor to output the real-time insulation life consumption rate; The process by which the feedforward collaborative regulation module generates local microclimate regulation instructions includes: The configuration is as follows: if the real-time consumption rate of the insulation life is greater than the preset aging critical threshold, then the local microclimate adjustment command is generated based on the humidity inside the box to trigger the dehumidification device and the cooling fan; otherwise, the command to maintain the current operating state is generated. The process by which the feedforward coordinated regulation module generates global power grid dispatch instructions includes: The configuration is as follows: if the real-time insulation life consumption rate after the execution of the local microclimate adjustment command continues to be greater than the aging critical threshold within a preset time window, then the dynamic capacity expansion limit value is calculated based on the distribution network load forecast data, and the global power grid dispatch command containing a local load transfer request is output to the upper-level dispatch system; otherwise, normal state confirmation information that does not require load transfer is generated.

2. The intelligent monitoring and adjustment system for cable branch boxes according to claim 1, characterized in that, The internal state observation module is specifically used for: The multi-point temperature of the joint surface and the real-time current are input into a preset thermal resistance and thermal capacity network model. The Joule heat generation rate is calculated by multiplying the square of the real-time current by the preset initial value of the contact resistance obtained from the factory parameters or acceptance test records. By combining the Joule heat generation rate and the multi-point temperature on the joint surface, the true maximum temperature inside the joint can be deduced.

3. The intelligent monitoring and adjustment system for cable branch boxes according to claim 1, characterized in that, The lifespan depletion calculation module is also used to calculate the cumulative mechanical stress damage to generate a predicted contact resistance value, specifically including: The amplitude and frequency of temperature cycles are extracted from the actual highest temperature inside the joint using the rainflow counting method, and used as the temperature cycle characteristics. Using the linear cumulative damage rule, the cumulative damage value of the micro-mechanical stress on the internal contact surface of the joint is calculated based on the amplitude and the frequency. The cumulative damage value is multiplied by a preset resistance ratio coefficient to obtain the contact resistance increment, and the preset initial contact resistance value is added to the contact resistance increment to generate the predicted contact resistance value.

4. The intelligent monitoring and adjustment system for cable branch boxes according to claim 1, characterized in that, The health status assessment module is specifically used for: The cumulative lifetime loss value is obtained by integrating the real-time insulation lifetime consumption rate over time. The remaining service life is predicted by subtracting the cumulative service life loss value from the preset initial design service life of the cable branch box. The ratio of the predicted remaining service life to the initial design life of the cable branch box is used as the health index of the cable branch box. The configuration is as follows: if the predicted remaining service life is lower than the preset service life threshold, then generate the remaining service life warning information; otherwise, generate the normal operation status data tag.

5. The intelligent monitoring and adjustment system for cable branch boxes according to claim 1, characterized in that, The system also includes an adaptive correction module for: The data acquisition module acquires updated environmental microclimate data after executing the local microclimate adjustment command and the global power grid dispatch command. The updated environmental microclimate data is fed back to the lifetime consumption calculation module to recalculate the real-time insulation lifetime consumption rate, forming a dynamic closed-loop control.

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