Cable branch box heat dissipation control method and system based on multi-source data

Abstract

The application provides a cable branch box heat dissipation control method and system based on multi-source data, belonging to the technical field of control, comprising: obtaining internal temperature data and load current data of a cable branch box; based on the internal temperature data and the load current data, determining a first time when the internal temperature data rises from below a preset temperature threshold to above the preset temperature threshold, and a second time when the load current data rises from below a preset current threshold to above the preset current threshold; determining the time length from the second time to the first time as a temperature rise response delay value; based on the temperature rise response delay value, determining the start-up advance time length of the heat dissipation equipment. This method can realize precise feedforward control matched with the thermal characteristics of the branch box without relying on a complex thermal model, effectively suppresses the temperature peak value, and avoids energy waste caused by premature start-up.

Description

Technical Field

[0001] This application relates to the field of control technology, and in particular to a heat dissipation control method and system for cable branch boxes based on multi-source data. Background Technology

[0002] As a crucial connection and distribution node in power distribution networks, cable distribution boxes experience significant temperature rises due to resistive losses in components such as cable joints and busbars when load current flows through them. To prevent excessive temperature from causing insulation aging or even failure, forced cooling devices are typically required.

[0003] Existing heat dissipation control methods mostly employ start-stop logic based on temperature thresholds or simple timing control. However, cable distribution boxes inherently possess significant thermal inertia, meaning there is a non-negligible lag time between an increase in load current and a corresponding rise in internal temperature. If the heat dissipation equipment is only activated when the detected temperature exceeds a limit, the actual internal temperature often exceeds the safe range due to the thermal delay, making it difficult to effectively suppress the temperature rise peak. Conversely, if a fixed lead time is used to activate the heat dissipation, the varying thermal inertia under different operating conditions can easily lead to problems such as premature activation (wasting energy) or delayed activation (insufficient protection). Summary of the Invention

[0004] This application provides a method and system for heat dissipation control of cable branch boxes based on multi-source data to improve the above-mentioned problems.

[0005] To achieve the above objectives, this application adopts the following technical solution: In a first aspect, this application proposes a heat dissipation control method for cable branch boxes based on multi-source data, applied to a heat dissipation control system for cable branch boxes based on multi-source data. The system includes a control terminal and heat dissipation equipment. The method is executed by the control terminal and includes: acquiring internal temperature data and load current data of the cable branch box; determining, based on the internal temperature data and load current data, a first moment when the internal temperature data rises from below a preset temperature threshold to above a preset temperature threshold, and a second moment when the load current data rises from below a preset current threshold to above a preset current threshold; determining the duration from the second moment to the first moment as a temperature rise response delay value; and determining the start-up advance time of the heat dissipation equipment based on the temperature rise response delay value.

[0006] Therefore, by monitoring the internal temperature and load current in real time, capturing the moment when they cross corresponding preset thresholds, and using the time difference to directly obtain the temperature rise response delay value characterizing the system's thermal inertia, the startup advance time of the heat dissipation equipment can be adaptively determined. Compared with traditional fixed threshold or timing control, this method does not require the pre-establishment of a complex thermal model, enabling the heat dissipation equipment to precisely intervene before the temperature rises significantly, effectively suppressing the temperature rise peak, while avoiding energy waste caused by premature startup. It achieves precise feedforward control that matches the actual thermal response characteristics of the branch box, significantly improving the timeliness and energy efficiency of heat dissipation.

[0007] In conjunction with the first aspect, the method may optionally further include: acquiring ambient temperature data and solar radiation intensity data on the surface of the cable branch box; determining the ambient heat effect value based on the ambient temperature data and solar radiation intensity data on the box surface; and determining the output power level of the heat dissipation equipment based on the ambient heat effect value.

[0008] Therefore, by incorporating two types of external environmental data—ambient temperature and solar radiation intensity—the thermal effects of the external environment on the branch box can be comprehensively quantified, and the output power level of the heat dissipation equipment can be adjusted accordingly. This allows heat dissipation control to not only rely on the internal state but also dynamically adapt to changes in external weather conditions: actively increasing heat dissipation power to prevent overheating in high-temperature, high-sunlight environments, and automatically reducing power to reduce energy consumption in milder environments. Through the coordinated optimization of startup timing and output power, a comprehensive technical effect that ensures both equipment safety and significant energy savings is achieved.

[0009] In conjunction with the first aspect, optionally, the start-up advance time of the heat dissipation equipment is determined based on the temperature rise response delay value, including: obtaining the temperature rise response delay value corresponding to multiple load current rise events in the cable branch box during historical operation, and the occurrence time of each load current rise event; arranging the temperature rise response delay values ​​in chronological order based on each occurrence time to obtain a record of delay value changes; determining drift segments where multiple consecutive temperature rise response delay values ​​continuously increase or decrease based on the record of temperature rise response delay value changes; obtaining the amount of delay value change per unit time within the drift segment, and determining the amount of delay value change as the drift rate; determining a trend compensation amount based on the drift rate and the time interval between the current time and the end time of the drift segment; and superimposing the temperature rise response delay value and the trend compensation amount to obtain the expected temperature rise response delay value, which is used as the start-up advance time.

[0010] Therefore, by analyzing historical delay value changes, drift segments where the delay value continuously increases or decreases can be automatically identified. Based on the drift rate and current time, trend extrapolation compensation is performed to obtain the expected temperature rise response delay value. This method allows the advance start-up time to dynamically follow the slow evolution of the equipment's thermal characteristics, such as response lag caused by gradually increasing contact resistance or aging insulation materials. This avoids the problem of gradual mismatch in traditional fixed-parameter control over long-term operation, thus significantly improving the long-term adaptability and operational reliability of heat dissipation control.

[0011] In conjunction with the first aspect, optionally, determining the startup advance time of the heat dissipation device based on the temperature rise response delay value further includes: identifying the fluctuation pattern of the delay value that recurs within the same month in the delay value change record, and recording the fluctuation offset corresponding to different time points in the fluctuation pattern; querying the fluctuation offset corresponding to the current time point in the fluctuation pattern based on the occurrence time of the current event; and superimposing the temperature rise response delay value with the trend compensation amount to obtain the expected temperature rise response delay value, which is used as the startup advance time, including: superimposing the temperature rise response delay value, the fluctuation offset, and the trend compensation amount to obtain the expected temperature rise response delay value, which is used as the startup advance time.

[0012] Therefore, based on trend compensation, the seasonal fluctuation patterns of recurring delay values ​​within the same month are further extracted and utilized, and the corresponding fluctuation offsets are superimposed. By simultaneously compensating for long-term drift trends and repeatable seasonal cycle effects, the final expected temperature rise response delay value can more comprehensively filter out interference caused by environmental and load periodic changes, enabling the early start-up timing of heat dissipation equipment to maintain high accuracy throughout the year, achieving more stable and efficient adaptive heat dissipation control.

[0013] In conjunction with the first aspect, optionally, before obtaining the temperature rise response delay value corresponding to multiple load current rise events in the cable branch box during historical operation, the method further includes: obtaining load current data of the cable branch box during historical operation; based on the load current data, determining load current rise events where the current surge exceeds a preset mutation threshold, and marking them as impulsive load events; marking load current rise events not marked as impulsive load events as continuous load events; obtaining the temperature rise response delay value corresponding to multiple load current rise events in the cable branch box during historical operation includes: obtaining the temperature rise response delay value corresponding to the load current rise event marked as a continuous load event.

[0014] Therefore, by setting a sudden change threshold, load current rise events can be categorized into impulsive load events and sustained load events, and only the temperature rise response delay value corresponding to sustained load events can be used for subsequent analysis. This data preprocessing strategy effectively eliminates abnormal and unrepresentative data caused by short-term impulsive loads such as motor startup, making the learning samples more realistically reflect the basic thermal inertia characteristics of the branch box under sustained heat load. This not only improves the data quality for subsequent drift analysis and mapping modeling but also makes the early start-up time determined based on this data more representative and robust.

[0015] In conjunction with the first aspect, optionally, the system also includes an ambient temperature sensor installed on the cable branch box. Based on ambient temperature data and solar radiation intensity data on the box surface, the system determines the ambient thermal effect value, including: acquiring a solar radiation exposure coefficient based on the ambient temperature sensor, wherein the solar radiation exposure coefficient characterizes the measured temperature rise of the ambient temperature sensor under unit solar radiation intensity; determining the additional temperature rise of the sensor caused by solar radiation based on solar radiation intensity data and solar radiation exposure coefficient, as a temperature measurement deviation value; correcting the ambient temperature data based on the temperature measurement deviation value to obtain corrected ambient temperature data; converting the corrected ambient temperature data into a first thermal effect component based on a pre-stored first correspondence between ambient temperature and thermal effect; converting the current solar radiation intensity data into a second thermal effect component based on a pre-stored second correspondence between solar radiation intensity and thermal effect; and using the sum of the first and second thermal effect components as the ambient thermal effect value.

[0016] Therefore, by correcting the sensor's additional temperature rise caused by sunlight using a pre-calibrated solar exposure coefficient, radiation errors are eliminated, resulting in a more accurate air temperature. Simultaneously, the corrected ambient temperature and solar intensity are converted into first and second thermal effect components, respectively, and then summed to obtain the ambient thermal effect value. This processing method accurately quantifies air convection and solar radiation as independent heat sources, avoiding false information introduced by radiation heating of the sensor itself. This significantly improves the accuracy of external heat load assessment, making the decision on heat dissipation output power level more scientific and reliable, and effectively avoiding overcooling or insufficient heat dissipation caused by distorted environmental parameter measurements.

[0017] In conjunction with the first aspect, optionally, acquiring the internal temperature data of the cable branch box includes: acquiring temperature data collected by two or more temperature sensors installed inside the cable branch box, wherein the two or more temperature sensors are installed in different locations; after determining the output power level of the heat dissipation device based on the ambient thermal effect value, the following steps are taken: based on the temperature data collected by the two or more temperature sensors, determining the maximum temperature difference inside the cable branch box; based on the preset correspondence between the maximum temperature difference and the power adjustment coefficient, determining the power adjustment coefficient corresponding to the maximum temperature difference; based on the power adjustment coefficient, correcting the output power level, and controlling the heat dissipation device to operate at the corrected output power level.

[0018] Therefore, by deploying multiple internal temperature sensors and acquiring their maximum temperature difference values, the output power level is corrected based on the correlation between the maximum temperature difference and the power adjustment coefficient. This method fully considers the uneven temperature distribution inside the branch box. When obvious local hot spots appear, heat dissipation is automatically enhanced to quickly eliminate the risk of overheating, while the power is appropriately reduced when the internal temperature is relatively uniform to avoid overall overcooling. This refined power adjustment based on internal temperature difference feedback significantly reduces ineffective heat dissipation energy consumption while ensuring the safety of critical hot spots, achieving differentiated thermal management that balances safety and energy saving.

[0019] In conjunction with the first aspect, optionally, the start-up advance time of the heat dissipation equipment is determined based on the temperature rise response delay value, including: acquiring the temperature rise response delay values ​​corresponding to multiple load current rise events in the cable branch box during historical operation, and the load current change rate corresponding to each event; determining the mapping relationship between the change rate and the delay value based on the load current change rate corresponding to each event and the temperature rise response delay value; determining the current load current change rate based on the currently acquired load current data; determining the temperature rise response delay value corresponding to the current load current change rate based on the mapping relationship, as the dynamic response delay value; and using the dynamic response delay value as the start-up advance time of the heat dissipation equipment.

[0020] Therefore, by establishing a mapping relationship between the load current change rate and the temperature rise response delay value using historical data, and quickly matching the corresponding dynamic response delay value based on the current load current change rate during real-time operation, this method allows the start-up advance time to be dynamically adjusted according to the current rise rate of each load event. This provides the most suitable advance amount for both rapid loading and slow rise scenarios. Compared to using a fixed delay value, this approach more accurately adapts to the actual thermal response characteristics under different transient loads, further improving the timeliness and accuracy of heat dissipation intervention, and is particularly suitable for applications with frequent load fluctuations or significant differences in impact characteristics.

[0021] Secondly, this application proposes a heat dissipation control system for cable branch boxes based on multi-source data, comprising: The acquisition module is used to acquire internal temperature data and load current data of the cable branch box; The first determining module is used to determine, based on internal temperature data and load current data, the first moment when the internal temperature data rises from below a preset temperature threshold to above a preset temperature threshold, and the second moment when the load current data rises from below a preset current threshold to above a preset current threshold. The second determining module is used to determine the duration from the second moment to the first moment as the temperature rise response delay value; The third determination module is used to determine the start-up advance time of the heat dissipation device based on the temperature rise response delay value.

[0022] A third aspect of the present invention provides a processing apparatus, the processing apparatus comprising: At least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor to enable the at least one processor to perform the method proposed in the first aspect of the present invention.

[0023] A fourth aspect of the present invention provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the method as described in the first aspect of the present invention. Attached Figure Description

[0024] Figure 1 This is a flowchart illustrating a heat dissipation control method for a cable branch box based on multi-source data, as proposed in an embodiment of this application.

[0025] Figure 2 This is a schematic diagram of a heat dissipation control system for a cable branch box based on multi-source data, as proposed in an embodiment of this application.

[0026] Figure 3 This is a schematic diagram of the structure of a processing device proposed in an embodiment of this application. Detailed Implementation

[0027] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0028] This application proposes a multi-source data-based heat dissipation control system for cable branch boxes, including a control terminal, heat dissipation equipment, an internal temperature sensor group, a load current sensor, an ambient temperature sensor, and a solar radiation intensity sensor. The internal temperature sensor group can be, for example, a thermocouple, a PT100 platinum resistance thermometer, or a semiconductor digital temperature sensor; the load current sensor can be an open-loop or closed-loop Hall effect sensor or a Rogowski coil current transformer; the solar radiation intensity sensor can be a silicon photovoltaic solar meter or a total radiation meter; the ambient temperature sensor is preferably a precision platinum resistance thermometer with a radiation shield. The internal temperature sensor group includes at least two temperature probes installed at different locations within the branch box, such as at cable joints, above the main busbar, and in the middle of the box. The load current sensor is located on the main incoming or outgoing circuit. The ambient temperature sensor is generally installed on the outside of the box, and the solar radiation intensity sensor is installed on or near the top of the box. The control terminal is connected to all sensors and heat dissipation equipment via signal lines or wirelessly to achieve data acquisition and equipment control.

[0029] The control terminal is an industrial microprocessor or programmable controller, whose internal memory contains the program for implementing the method of this invention, as well as preset parameters such as temperature and current thresholds and corresponding relationship tables. The heat dissipation device can be a variable frequency fan or an air conditioner, etc., whose start / stop and power can be adjusted by the control terminal.

[0030] Figure 1 This application presents a method for heat dissipation control of cable branch boxes based on multi-source data, executed by a control terminal, and specifically includes the following steps: S101: Obtain internal temperature data and load current data of the cable branch box.

[0031] Understandably, the control terminal communicates with temperature sensors located inside the cable branch box and current sensors installed on the main circuit to collect internal temperature and load current signals in real time. Internal temperature data typically refers to the representative temperature of key heat-generating components within the branch box or the air inside the box, while load current data reflects the real-time electrical load transmitted by the branch box. The data acquisition process can be performed at a fixed sampling period, and after signal conditioning and analog-to-digital conversion, it becomes a numerical sequence that the control terminal can process. For example, the fixed sampling period can be set differently depending on the data type; for instance, temperature data could be collected every 5 seconds, and current data every 1 second, to balance data accuracy and processor load.

[0032] S102: Based on internal temperature data and load current data, determine the first moment when the internal temperature data rises from below the preset temperature threshold to above the preset temperature threshold, and the second moment when the load current data rises from below the preset current threshold to above the preset current threshold.

[0033] Specifically, the real-time temperature values ​​are compared with preset temperature thresholds, such as the equipment safety limit of 70°C, and the current values ​​are compared with preset current thresholds, such as 60% of the rated current representing a significant increase in load. When the temperature sequence changes from below the threshold to above or equal to the threshold, the control terminal records the moment of this crossing event, called the first moment, which is the starting point when the temperature begins to enter the range requiring heat dissipation intervention.

[0034] Similarly, when the current sequence changes from below its critical value to above or equal to the critical value, the moment when this crossing event occurs is recorded and called the second moment. These two moments can be determined through sampling point comparison and threshold cross-detection algorithms. For example, when a sampling moment value is greater than or equal to the threshold while the previous sampling moment value is less than the threshold, it is determined that a crossing has occurred at that moment. Alternatively, to avoid false triggering caused by signal noise, the temperature or current data can be filtered by moving average before threshold comparison, or a hysteresis band can be set, meaning the crossing threshold must be maintained for more than a certain number of sampling periods before the event is confirmed.

[0035] It is understandable that the increase in load current is the fundamental reason for the rise in internal temperature. However, due to the thermal inertia of the branch box itself, the temperature rise will lag behind the change in current. Therefore, the second moment is usually earlier than the first moment, and a time difference is formed between the two.

[0036] S103: The duration from the second moment to the first moment is determined as the temperature rise response delay value.

[0037] Understandably, after obtaining the first and second moments corresponding to the same load temperature rise process, the control terminal calculates the time interval between these two moments, i.e., the duration obtained by subtracting the second moment from the first moment. This duration is the temperature rise response delay value, which quantitatively reflects the thermal lag time exhibited by the system from the point where the load current begins to increase significantly until the internal temperature of the branch box reaches the required heat dissipation control level. The magnitude of the delay value is mainly determined by factors such as the thermal capacity of cables and accessories, the box structure, and heat dissipation conditions. To further improve robustness, the temperature rise response delay value can also be taken as the average or median of the delays of several recent similar events to eliminate the influence of a single random disturbance.

[0038] S104: Determine the start-up advance time of the heat dissipation device based on the temperature rise response delay value.

[0039] Understandably, since the system only requires forced cooling from the heat dissipation equipment when the temperature truly approaches or exceeds the critical value, to avoid temperature overshoot due to thermal delay, the heat dissipation equipment should not be activated only when the temperature exceeds the limit, but rather should be activated in advance. Therefore, the control terminal can set the start-up advance time equal to the temperature rise response delay value, or perform a simple conversion based on the delay value. For example, the start-up advance time can be calculated by multiplying the delay value by a preset safety factor, such as 1.1, to accommodate possible fluctuations in operating conditions.

[0040] During real-time operation, when the control terminal detects an upward trend in the load current and anticipates exceeding the preset current threshold, it activates the cooling equipment ahead of schedule based on the pre-set start-up time. For example, if the temperature rise response delay is 5 minutes, the cooling equipment start-up command is issued approximately 5 minutes before the actual current exceeds the limit, ensuring that cooling intervenes precisely when the temperature is about to rise significantly, thereby effectively suppressing the temperature rise peak and achieving precise feedforward control that matches the system's thermal inertia.

[0041] For example, as one implementation, step S104 may include the following steps: S1041a: Obtain the temperature rise response delay value corresponding to multiple load current rise events in the cable branch box during historical operation, as well as the occurrence time of each load current rise event.

[0042] Specifically, the control terminal retrieves relevant records of load current rise events that have occurred multiple times from the historical operation data storage area.

[0043] Each load current rise event refers to an event for which the corresponding temperature rise response delay value has been detected and calculated according to the aforementioned S102 and S103 methods. For each such event, the control terminal records not only its temperature rise response delay value but also the time of occurrence of the event. These data constitute a set of time series samples used to analyze the trend of the delay value evolving with operating time.

[0044] Optionally, the following steps may be included prior to this: S202: Obtain the load current data of the cable branch box during historical operation.

[0045] Specifically, the control terminal retrieves load current timing data recorded by the cable branch box during its past operation from its own long-term operating database or a dedicated waveform recording storage unit. This data is typically collected and stored by current sensors at uniform sampling intervals, fully covering the detailed waveforms of multiple load change processes. By reading historical current data, the control terminal can retrospectively analyze the specific characteristics of each load rise event, rather than just the event summaries pre-calculated by steps such as S101 and S103.

[0046] S203: Based on load current data, identify load current rise events where the current surge exceeds a preset threshold and mark them as impact load events.

[0047] Specifically, for each process where the current rises significantly from a lower level, the control terminal extracts the current surge increment, i.e., the jump amplitude of the current from the initial value to the peak value during that rise event. Simultaneously, the system presets a sudden change threshold, such as 30% of the rated current, as the limit for the step change, to distinguish the severity of the current change. This sudden change threshold can be dynamically adjusted according to the load type of the branch box. If historical records show primarily impact loads, the threshold can be appropriately increased, or a joint criterion of surge increment and duration can be introduced to more accurately distinguish the load nature.

[0048] If the sudden increase in current during a load current surge exceeds the preset threshold, it indicates that the load connection exhibits rapid and significant current surge characteristics, similar to a direct motor start-up or transformer inrush current, representing a sudden surge of high power. The control terminal classifies such events as impact load events and marks them accordingly. These events are characterized by an extremely rapid current surge, but often have a short duration or do not fully correspond to a stable heat accumulation process.

[0049] S204: Mark load current rise events that were not marked as impulsive load events as continuous load events.

[0050] After identifying and labeling impulsive load events, other load current rise events remaining in the historical load current data—that is, events where the current surge does not exceed the preset threshold and the rise is relatively gradual or the step amplitude is limited—are uniformly labeled as continuous load events by the control terminal. These events typically reflect a normal gradual increase in load or the stable commissioning of high-power electrical equipment. Their thermal effects have a clearer and more stable causal relationship with the temperature rise process of the branch box, making them suitable as samples for learning thermal inertia characteristics.

[0051] S205: Obtain the temperature rise response delay value corresponding to the load current rise event marked as a continuous load event.

[0052] From the previously stored event records, only entries marked as continuous load events are selected, and their corresponding temperature rise response delay values ​​are extracted. Events marked as impulsive loads, even if they have corresponding delay values, are excluded and not included in subsequent historical data analysis. The set of temperature rise response delay values ​​obtained through this step has less interference and more accurately reflects the basic thermal response hysteresis characteristics of the cable branch box under continuous heat load.

[0053] S1042a: Based on each occurrence time, arrange the temperature rise response delay values ​​in chronological order to obtain a record of delay value changes.

[0054] The control terminal sorts the corresponding temperature rise response delay values ​​according to the occurrence time of each event, forming a sequence of delay value changes over time, i.e., a delay value change record. For example, this record could be a series of data points arranged in ascending order of timestamps: (t1, D1), (t2, D2), ..., (tn, Dn), where t is the event occurrence time and D is the temperature rise response delay value. This temporal arrangement allows for observation of whether the delay value gradually increases, gradually decreases, or remains stable. To improve the representativeness of the record, outlier removal can be performed on the original delay values; that is, removing those exceeding three standard deviations before arranging.

[0055] S1043a: Based on the record of temperature rise response delay value changes, determine the drift segment where multiple consecutive temperature rise response delay values ​​continuously increase or decrease.

[0056] Understandably, a drift segment must meet two conditions: first, the segment must contain multiple consecutive delay values; second, these delay values ​​must exhibit a continuous, roughly unidirectional change, meaning that each subsequent value is either significantly greater than or significantly less than the previous value.

[0057] The control terminal can determine whether a continuous subsequence meets the drift characteristics through methods such as sliding windows and monotonicity tests, and mark it as a drift segment. This drift segment represents a directional, non-random evolution of the branch box's thermal response characteristics during the operation period of that segment, such as changes in thermal inertia caused by gradually increasing contact resistance or insulation aging. Specifically, the length of the sliding window can be set to, for example, 10 events, and the monotonicity test allows for occasional small reverse fluctuations; as long as the statistical significance of the overall trend meets the preset confidence level, the drift segment can be confirmed.

[0058] S1044a: Obtain the change in delay value per unit time within the drift segment and determine the change in delay value as the drift rate. Alternatively, weighted linear regression can be used, assigning greater weight to more recent data points to obtain a rate value that better reflects the recent drift trend.

[0059] Within the identified drift range, the control terminal calculates the magnitude of the change in delay value per unit time; this magnitude is the drift rate. Specifically, this can be calculated by dividing the total change in delay value from the first to the last value within the range by the time span of the range, or by performing a linear fit on the data points within the range and taking the slope of the fitted line as the drift rate. Its physical meaning is: how much the system's temperature rise response delay value increases or decreases on average per unit time within the drift range. This rate quantifies the speed of characteristic drift.

[0060] S1045a: Determine the trend compensation amount based on the drift rate and the time interval between the current time and the end time of the drift segment.

[0061] The control terminal determines the time interval between the current time point and the end time point of the most recent drift segment, that is, how long has passed since the end of the drift segment. Then, it multiplies this time interval by the previously calculated drift rate to obtain the trend compensation amount.

[0062] Understandably, if the drift segment is characterized by a continuously increasing delay value, the trend compensation is positive; if it's characterized by a continuously decreasing delay value, the compensation is negative. Assuming the device's delay characteristics continue to evolve at this drift rate, the amount of change in delay value since the end of the drift segment is the compensation. This extrapolation ensures that the delay value used at this moment can compensate for the accumulated drift effect during this period.

[0063] S1046a: The temperature rise response delay value is superimposed with the trend compensation amount to obtain the expected temperature rise response delay value, which is used as the start-up advance time.

[0064] Understandably, when the trend compensation is positive, the expected delay value increases accordingly, indicating a positive drift in the system's thermal hysteresis characteristics, meaning the temperature response becomes slower; conversely, when the trend compensation is negative, the expected delay value decreases, indicating a faster thermal response. The sum of these values ​​is called the expected temperature rise response delay value, which combines the current measured delay level with the change in delay value over a period derived from the historical drift rate. The control terminal directly uses this expected value as the start-up advance time of the heat dissipation equipment, allowing the timing of the early start-up to adaptively adjust according to the long-term drift of the equipment's thermal characteristics.

[0065] S1047a: Determine the fluctuation pattern of the delay value that recurs within the same month in the delay value change record, and record the fluctuation offset of the corresponding time point in the fluctuation pattern.

[0066] The control terminal performs periodic analysis on the records of delay value changes, looking for regular fluctuations that repeat across years and appear monthly; these regular fluctuations are called fluctuation patterns. For example, fluctuation patterns can be extracted by calculating the arithmetic mean of historical delay values ​​for each month, or by using seasonal decomposition algorithms, such as STL decomposition, to separate trends from seasonal fluctuations.

[0067] Understandably, due to the fact that external climatic conditions, such as high temperatures in summer and low temperatures in winter, tend to repeat themselves similarly every year, the thermal response delay value of cable branch boxes often shows an overall trend of being higher or lower in the same or similar months, thus forming an approximately periodic fluctuation on an annual scale. The control terminal abstracts this stable and repeating delay value fluctuation feature within the same month to obtain the fluctuation pattern.

[0068] Subsequently, within this fluctuation pattern, for different calendar dates, the deviation of that date from the annual average lag value or a certain benchmark value is recorded; this deviation is the fluctuation offset for that date. For example, if, within a certain annual cycle, the lag value in July is generally higher than the annual average by a certain percentage or absolute amount, then this excess is recorded as the fluctuation offset for the corresponding July. These offsets constitute a reference table that can be consulted.

[0069] S1048a: Based on the occurrence time of the current event, query the fluctuation offset corresponding to the current time point in the fluctuation mode.

[0070] When a new load current rise event occurs in real time and it is necessary to determine the advance start-up time of the heat dissipation equipment, the control terminal obtains the occurrence time of the current event, and then queries the fluctuation mode and offset table in a time-matching manner to find the fluctuation offset corresponding to the current time point.

[0071] For example, if the current event occurs in July of a certain year, the fluctuation offset value representing July is found from the fluctuation pattern record. This offset represents the degree to which the temperature rise response delay value tends to deviate from the normal baseline due to repeatable periodic external environmental factors during the current seasonal period.

[0072] S1049a: The temperature rise response delay value, fluctuation offset, and trend compensation are superimposed to obtain the expected temperature rise response delay value, which is used as the start-up advance time.

[0073] The control terminal superimposes the following three quantities: first, the temperature rise response delay value obtained from the most recent actual measurement, which represents the current basic thermal response characteristics; second, the fluctuation offset corresponding to the current time point, which represents the correction caused by seasonal periodic effects; and third, the determined trend compensation amount, which represents the correction of long-term characteristic drift.

[0074] Understandably, the sum of these three factors yields the final expected temperature rise response delay value. This value integrates real-time observation, long-term evolution trend, and seasonal periodic effects, providing a more comprehensive reflection of the actual temperature rise response lag level of the branch box at the current moment. The control terminal uses this summed result as the start-up advance time of the heat dissipation equipment. This ensures that even under complex conditions of periodic changes in the external environment and slow changes in the equipment's own characteristics, the heat dissipation equipment can still be put into operation at the most appropriate time, achieving precise and reliable heat dissipation feedforward control.

[0075] In some other embodiments, step S104 may also include the following steps: S1041b: Obtain the temperature rise response delay value corresponding to multiple load current rise events in the cable branch box during historical operation, as well as the load current change rate corresponding to each event.

[0076] The control terminal retrieves multiple identified load current rise events from historical operation records. For each event, it not only extracts the temperature rise response delay value but also further traces back the original current time-series data at the time of the event to calculate the load current change rate corresponding to that event. This change rate typically refers to how quickly the current amplitude changes over time as the load current begins to rise significantly from near a preset current threshold until it crosses the threshold; it can be taken as the average slope or maximum slope within that range. Therefore, each set of data contains a delay value and a rate value, forming a historical sample set. Alternatively, the average rate of change within a fixed time window before and after the current crosses the threshold can be chosen as the rate to standardize the calculation.

[0077] S1042b: Determine the mapping relationship between the rate of change of load current and the temperature rise response delay value corresponding to each event.

[0078] Specifically, historical data is used to establish a mapping relationship between the rate of change of load current and the temperature rise response delay. This mapping relationship can be achieved in various ways, such as using the least squares method to perform polynomial fitting to obtain a functional equation, or dividing the data into rate intervals and calculating the average delay value within each interval to form a lookup table rule. For example, a first-order linear regression model or a power-law function can be used for fitting, or a nonlinear mapping model can be constructed using decision trees or K-nearest neighbors algorithms in machine learning. The essence of the mapping relationship is to learn the differences in the thermal inertia performance of the branch box under different load ramp-up rates.

[0079] S1043b: Determine the current load current change rate based on the currently acquired load current data.

[0080] During real-time operation, the control terminal continuously monitors load current data. When an upward trend in current is detected, such as an increase in current values ​​at several consecutive sampling points, or when the current value approaches a preset current threshold, the control terminal uses the same method as defined in the historical event section to instantly calculate the current load current change rate. This requires the control terminal to perform online slope calculation on the current sequence, for example, taking the average current difference within the most recent time window as the current change rate to characterize the speed at which the current load increases.

[0081] S1044b: Based on the mapping relationship, determine the temperature rise response delay value corresponding to the current load current change rate, and use it as the dynamic response delay value.

[0082] Using the current rate of change as input, and substituting it into the mapping relationship, the corresponding temperature rise response delay value is obtained through table lookup, interpolation, or function calculation, and is specifically referred to as the dynamic response delay value. This dynamic delay value reflects the branch box temperature rise response lag time predicted based on historical experience under the current load change rate. Unlike directly using the most recent measured delay value, this method adapts to the transient characteristics of each load event, providing greater precision.

[0083] S1045b: Uses the dynamic response delay value as the startup advance time of the heat dissipation device.

[0084] Specifically, the control terminal directly determines the dynamic response delay value as the start-up advance time for the heat dissipation equipment. When the system determines that the heat dissipation equipment needs to be started earlier, for example, when it detects that the current is about to exceed a critical value or that preventative cooling is required, it issues a start-up command in advance according to this time. In this way, the start-up advance takes into account both the inherent thermal inertia of the equipment and is dynamically adjusted according to the real-time load change rate, so that the timing of heat dissipation intervention matches the nature of the strong thermal shock of power generation, further improving control accuracy and energy efficiency.

[0085] S105: Obtain ambient temperature data and solar radiation intensity data on the surface of the cable branch box.

[0086] Specifically, by communicating with ambient temperature sensors located outside the cable distribution box, such as temperature probes installed in shaded areas on the outside of the box or in nearby weather screens, ambient temperature data reflecting the micro-environmental temperature of the distribution box is obtained. Simultaneously, by communicating with solar radiation intensity sensors installed on the surface or top of the distribution box, such as total radiation meters or silicon photovoltaic solar meters, the actual solar radiation illuminance data received by the surface of the cable distribution box, i.e., solar radiation intensity data, is obtained. Both types of data are periodically sampled and sent to the control terminal, collectively describing the external thermal environment conditions acting on the distribution box.

[0087] S106: Determine the environmental thermal effect value based on ambient temperature data and solar radiation intensity data on the surface of the enclosure.

[0088] Using the acquired ambient temperature and solar radiation intensity data, a quantitative index is generated through a built-in preset algorithm or corresponding relationship to comprehensively characterize the strength of the heating effect of the external environment on the interior of the branch box. This index is the ambient thermal effect value.

[0089] Understandably, the higher the ambient temperature, the stronger the convective heat transfer from the air into the enclosure; the greater the solar radiation intensity, the more radiant heat is absorbed by the enclosure surface, and consequently, the greater the heat conducted into the interior. Therefore, the environmental heat load value can be designed as a function of these two parameters, such that this value increases accordingly when the ambient temperature rises or the solar radiation intensifies. In practical implementation, this correspondence can be stored in the control terminal in the form of formulas, tables, or polynomials. For example, in a simple case, the temperature and solar radiation values ​​can be normalized and then weighted to obtain the heat load value, so as to uniformly measure the magnitude of the environmental heat load.

[0090] For example, step S106 may include the following steps: S1061: Obtain the solar exposure coefficient based on the ambient temperature sensor, where the solar exposure coefficient characterizes the measured temperature rise of the ambient temperature sensor under unit solar radiation intensity.

[0091] The solar exposure coefficient of the ambient temperature sensor installed in the cable branch box is obtained by pre-calibration or by reading factory parameters.

[0092] Understandably, although ambient temperature sensors are generally installed on the outside of a housing or even equipped with radiation shields, they are still subject to heating from direct or diffuse solar radiation during actual use, causing the measured temperature to be higher than the actual air temperature. The solar exposure coefficient k quantifies the sensitivity to this radiative heating effect; that is, when the solar radiation intensity is 1 unit (e.g., 1 W / m²), the additional temperature rise caused by the sensor absorbing radiation. This coefficient can be measured under controlled experimental conditions or derived by comparing field data with a reference real temperature and regressing the result, storing it as an inherent characteristic of the sensor in the parameter area of ​​the control terminal. Alternatively, the solar exposure coefficient can be adaptively updated by establishing a dynamic response model of the sensor to radiation and using Kalman filtering to estimate the coefficient online using multiple sets of data over a period of time.

[0093] S1062: Based on solar radiation intensity data and solar radiation exposure coefficient, determine the additional temperature rise of the sensor caused by solar radiation as the temperature measurement deviation value.

[0094] During real-time operation, the control terminal acquires the current solar radiation intensity data E (unit: W / m²), multiplies it by the known solar radiation exposure coefficient k, and calculates the additional temperature rise caused by solar radiation irradiating the ambient temperature sensor: ΔT = k × E. This ΔT is the temperature measurement deviation value, reflecting the extent to which the ambient temperature sensor deviates from the actual ambient temperature under radiation conditions. This deviation is entirely attributed to solar radiation, without considering other secondary factors. When the sensor is placed in a location heavily affected by wind, a wind speed factor can be introduced to correct the solar exposure coefficient, i.e., using the form k' = k / (1 + b·v), where v is the wind speed and b is the wind speed correction coefficient.

[0095] S1063: Correct the ambient temperature data based on the temperature measurement deviation value to obtain the corrected ambient temperature data.

[0096] The control terminal will collect the raw ambient temperature measurement values ​​in real time. Subtracting the temperature measurement deviation value ΔT yields the corrected ambient temperature data. This correction eliminates the spurious temperature rise caused by solar radiation on the sensor readings, making the obtained data closer to the actual air temperature around the branch box. The corrected ambient temperature is used for subsequent thermal effect assessment, improving the accuracy of external heat load calculations.

[0097] S1064: Based on the pre-stored first correspondence between ambient temperature and thermal effect, convert the corrected ambient temperature data into a first thermal effect component.

[0098] Specifically, the control terminal's memory pre-stores a first correspondence, which defines the contribution of external air temperature to the internal thermal environment of the branch box under different real ambient temperatures. This contribution can be expressed as a lookup table, a piecewise linear function, or a polynomial curve. For example, this relationship can be set such that for every 10°C increase in air temperature, the contribution to internal thermal effects increases by a certain percentage.

[0099] Specific example: The first correspondence can be stored in the form of... = ( - The linear formula for ), where This is an empirical coefficient. This is a reference temperature.

[0100] Alternatively, a discrete table with a step size of 5℃ can be used, such as 20℃→0.2, 25℃→0.35, 30℃→0.5, etc. The control terminal substitutes the corrected ambient temperature value into this first correspondence and outputs a value, called the first thermal component. This component represents the equivalent influence of convective heat transfer, dominated by external air temperature, on the internal temperature rise of the branch box.

[0101] S1065: Based on the pre-stored second correspondence between solar radiation intensity and thermal effect, convert the solar radiation intensity data at the current moment into a second thermal effect component.

[0102] Similarly, the control terminal also pre-stores a second correspondence describing the contribution of direct solar radiation intensity alone to the thermal environment inside the branch box.

[0103] This relationship is established based on factors such as the radiation absorption characteristics of the enclosure surface and the heat conduction of the enclosure walls, and can also be in the form of a table or a function. For example, the second correspondence can be expressed as follows: = E, where The coefficient of radiation and heat conversion of the enclosure is related to the absorptivity of the surface coating, wall thickness, and thermal conductivity; or a more precise coefficient can be used. = E / (1+Rt), where The effective heat-receiving area of ​​the enclosure. This represents the thermal resistance of the enclosure wall. The control terminal substitutes the currently measured solar radiation intensity value into this second correspondence to obtain the second thermal component. This component quantifies the equivalent heat load intensity exerted on the interior by solar radiation through absorption and conduction within the enclosure. It's important to note that the solar radiation intensity data used here represents the radiation value acting on the enclosure, not the same intensity value used for sensor bias correction; however, its physical meaning has shifted from causing sensor errors to heating the enclosure.

[0104] S1066: The sum of the first thermal effect component and the second thermal effect component is taken as the environmental thermal effect value.

[0105] The first thermal component of the control terminal With the second thermal component By simply adding them together, we get the final environmental heat effect value P= + This addition is based on the assumption of linear independent superposition of heat loads, meaning that the effects of air convection heat transfer and radiation heat transfer on the internal temperature can be considered and summed independently. When it is necessary to consider the interaction between the two, an interaction term coefficient can be added after the summation, for example, P= + +β· · , where β is the interaction factor, obtained by fitting experimental data.

[0106] Understandably, the obtained environmental thermal effect value comprehensively reflects the total load of the external thermal environment; the larger the value, the more severe the environment, and the stronger the heat dissipation intervention required. Through the above correction and component decomposition, the calculation of the environmental thermal effect value avoids sensor radiation errors and improves the reliability of thermal management decisions.

[0107] S107: Determine the output power rating of the heat dissipation equipment based on the ambient thermal effect value.

[0108] After obtaining the ambient thermal effect value, the control terminal determines the output power level that the cooling device should operate at based on a preset mapping relationship between this value and the output power level. The mapping relationship can be a stepped grading table, for example, dividing the thermal effect value into several intervals, each interval corresponding to a fixed fan speed level or cooling power percentage; or it can be a continuous function curve, such as output power being directly proportional to the thermal effect value or piecewise linear. For example, if the cooling device is a variable frequency fan, the output power level can be refined to 0-10 levels, with the power level increasing by one level for every 0.1 increase in the ambient thermal effect value. If it is an air conditioner, it can be set to a linear relationship between the compressor's cooling capacity and the thermal effect value. A higher ambient thermal effect value means a more severe external heat load, requiring a higher output power level to provide stronger cooling capacity; conversely, when the environment is mild, a lower power level is selected to reduce the operating energy consumption of the cooling device while ensuring it does not overheat. Finally, the control terminal generates control commands according to the determined level, driving the cooling device to operate at the corresponding power.

[0109] Alternatively, as one implementation method, in order to avoid energy waste caused by excessive cooling, the internal temperature data of the cable branch box can be determined by temperature data collected by two or more temperature sensors located at different positions inside the cable branch box.

[0110] S108: Determine the maximum temperature difference inside the cable branch box based on temperature data collected from two or more temperature sensors.

[0111] Specifically, these sensors may be installed in typical locations such as near cable joints, above busbars, and in the middle of the enclosure to acquire temperature data representing local thermal conditions. The control terminal identifies the highest and lowest temperature measurements from all currently collected values ​​and calculates the difference between them; this difference is the maximum internal temperature difference. This indicator directly reflects the degree of non-uniformity of the temperature field inside the branch box. When the highest temperature measurement is large, it indicates the presence of significant local hot spots or insufficient air mixing, meaning that overall heat dissipation alone may not be sufficient to effectively protect these hot spots. Alternatively, the standard deviation of all measured temperatures can be calculated as a measure of non-uniformity, or the difference between the highest and average temperatures can be directly taken.

[0112] S109: Based on the preset correspondence between the maximum temperature difference and the power adjustment coefficient, determine the power adjustment coefficient corresponding to the maximum temperature difference.

[0113] Specifically, the control terminal's memory can pre-store a table or function relating the maximum temperature difference to the power adjustment coefficient. This relationship is pre-calibrated through thermal simulation or field testing. Specifically, the larger the maximum temperature difference, the larger the adjustment coefficient should be applied to enhance heat dissipation, strengthen air turbulence and heat exchange within the chamber, thereby accelerating hotspot cooling; conversely, when the temperature difference is small, no additional power enhancement is needed, and the coefficient can be maintained at approximately 1 or slightly higher. As an example, this relationship can be set in segments: When ≤5℃, the coefficient α = 1.0; when 5 < When ≤10℃, α=1.1; when 10< At ≤15℃, α=1.2; When the temperature is greater than 15℃, α = 1.3. The control terminal inputs the highest temperature measurement value into this correspondence, and calculates the corresponding power adjustment coefficient α by querying or interpolation. This coefficient is, for example, 1.0, 1.1, 1.2, etc., which means that the output power needs to be increased by 0%, 10%, or 20% on the original basis.

[0114] S110: Based on the power regulation coefficient, correct the output power level and control the heat dissipation equipment to operate according to the corrected output power level.

[0115] Using the baseline output power level determined in step S107 based on the ambient thermal effect as a reference value, and employing the power adjustment coefficient α, the corrected output power level is calculated through a preset correction operation. Then, the control terminal generates the final control command to drive the cooling device to operate according to the corresponding speed setting, voltage, or power setpoint. The correction operation can employ multiplication or directly determine the final level using a lookup table based on the nonlinear characteristics of the power level. Through this internal temperature difference correction, the cooling control not only copes with the overall ambient heat load but also effectively alleviates local overheating, ensuring the safety of critical hotspots while avoiding energy waste caused by overall overcooling.

[0116] Based on the same inventive concept, this application also proposes a heat dissipation control system for cable branch boxes based on multi-source data, comprising: The acquisition module is used to acquire internal temperature data and load current data of the cable branch box; The first determining module is used to determine, based on internal temperature data and load current data, the first moment when the internal temperature data rises from below a preset temperature threshold to above a preset temperature threshold, and the second moment when the load current data rises from below a preset current threshold to above a preset current threshold. The second determining module is used to determine the duration from the second moment to the first moment as the temperature rise response delay value; The third determination module is used to determine the start-up advance time of the heat dissipation device based on the temperature rise response delay value.

[0117] Based on the same inventive concept, embodiments of this application also propose a processing apparatus, which includes: At least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor, the instructions being executed by the at least one processor to enable the at least one processor to perform the cable branch box heat dissipation control method based on multi-source data according to the embodiments of this application.

[0118] In addition, to achieve the above objectives, embodiments of this application also propose a computer-readable storage medium storing a computer program, which, when executed by a processor, implements the cable branch box heat dissipation control method based on multi-source data of the embodiments of this application.

[0119] The following is combined with Figure 3 A detailed description of each component of the processing equipment 300 is provided below: The processor 301 is the control center of the processing device 300. It can be a single processor or a collective term for multiple processing elements. For example, the processor 301 can be one or more central processing units (CPUs), application-specific integrated circuits (ASICs), or one or more integrated circuits configured to implement embodiments of the present invention, such as one or more digital signal processors (DSPs), or one or more field-programmable gate arrays (FPGAs).

[0120] Alternatively, the processor 301 can perform various functions of the processing device 300 by running or executing software programs stored in the memory 302 and by calling data stored in the memory 302.

[0121] In a specific implementation, as one example, processor 301 may include one or more CPUs, for example... Figure 3 CPU0 and CPU1 are shown in the diagram.

[0122] In a specific implementation, as one embodiment, the processing device 300 may also include multiple processors. Each of these processors may be a single-core processor (single-CPU) or a multi-core processor (multi-CPU). Here, a processor may refer to one or more devices, circuits, and / or processing cores used for processing data (e.g., computer program instructions).

[0123] The memory 302 is used to store the software program that executes the solution of the present invention, and the processor 301 controls the execution. The specific implementation method can be referred to the above method embodiment, and will not be repeated here.

[0124] Optionally, the memory 302 may be a read-only memory (ROM) or other type of static storage device capable of storing static information and instructions, random access memory (RAM) or other type of dynamic storage device capable of storing information and instructions, or electrically erasable programmable read-only memory (EEPROM), compact disc read-only memory (CD-ROM) or other optical disc storage, optical disc storage (including compressed optical discs, laser discs, optical discs, digital universal optical discs, Blu-ray discs, etc.), magnetic disk storage media or other magnetic storage devices, or any other medium capable of carrying or storing desired program code in the form of instructions or data structures and accessible by a computer, but not limited thereto. The memory 302 may be integrated with the processor 301 or exist independently, and may be connected via the interface circuit of the processing device 300. Figure 3 (Not shown in the image) is coupled to processor 301, and this embodiment of the invention does not specifically limit this.

[0125] Transceiver 303 is used for communication with other processing devices. For example, if processing device 300 is a terminal, transceiver 303 can be used to communicate with a network device or with another terminal device. As another example, if processing device 300 is a network device, transceiver 303 can be used to communicate with a terminal or with another network device.

[0126] Alternatively, transceiver 303 may include a receiver and a transmitter. Figure 3 (Not shown separately). The receiver is used to implement the receiving function, and the transmitter is used to implement the transmitting function.

[0127] Optionally, the transceiver 303 can be integrated with the processor 301, or it can exist independently and be connected via the interface circuit of the processing device 300. Figure 3(Not shown in the image) is coupled to processor 301, and this embodiment of the invention does not specifically limit this.

[0128] Understandable Figure 3 The structure of the processing device 300 shown does not constitute a limitation on the processing device. The actual processing device may include more or fewer components than shown, or combine certain components, or have different component arrangements.

[0129] Furthermore, the technical effects of the processing device 300 can be referred to the technical effects of the methods in the above-described method embodiments, and will not be repeated here.

[0130] It should be understood that the processor in the embodiments of the present invention can be a central processing unit (CPU), or it can be other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor can be a microprocessor or any conventional processor.

[0131] It should also be understood that the memory in the embodiments of the present invention can be volatile memory or non-volatile memory, or may include both volatile and non-volatile memory. The non-volatile memory can be read-only memory (ROM), programmable read-only memory (PROM), erasable programmable read-only memory (EPROM), electrically erasable programmable read-only memory (EEPROM), or flash memory. The volatile memory can be random access memory (RAM), which is used as an external cache. By way of example, but not limitation, many forms of random access memory (RAM) are available, such as static random access memory (SRAM), dynamic random access memory (DRAM), synchronous dynamic random access memory (SDRAM), double data rate synchronous dynamic random access memory (DDRSDRAM), enhanced synchronous dynamic random access memory (ESDRAM), synchronous linked dynamic random access memory (SLDRAM), and direct rambus RAM (DRRAM). The above embodiments can be implemented, in whole or in part, by software, hardware (such as circuitry), firmware, or any other combination thereof. When implemented in software, the above embodiments can be implemented, in whole or in part, as a computer program product. A computer program product includes one or more computer instructions or computer programs. When the computer instructions or computer programs are loaded or executed on a computer, all or part of the flow or function according to embodiments of the present invention is produced. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. Computer instructions can be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another. For example, computer instructions can be transmitted from one website, computer, server, or data center to another via wired (e.g., infrared, wireless, microwave, etc.) means. A computer-readable storage medium can be any available medium that a computer can access, or a data storage device such as a server or data center that includes one or more sets of available media. Available media can be magnetic media (e.g., floppy disks, hard disks, magnetic tapes), optical media (e.g., DVDs), or semiconductor media. Semiconductor media can be solid-state drives (SSDs).

[0132] It should be understood that the term "and / or" in this article is merely a description of the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A existing alone, A and B existing simultaneously, or B existing alone. A and B can be singular or plural. Additionally, the character " / " in this article generally indicates an "or" relationship between the preceding and following related objects, but it can also represent an "and / or" relationship. Please refer to the context for a more accurate understanding.

[0133] In this invention, "at least one" refers to one or more items, and "more than one" refers to two or more items. "At least one of the following" or similar expressions refer to any combination of these items, including any combination of a single item or a plurality of items. For example, at least one of a, b, or c can represent: a, b, c, ab, ac, bc, or abc, where a, b, and c can be single or multiple. It should be understood that in various embodiments of this invention, the sequence number of the above processes does not imply the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of this invention.

[0134] Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementations should not be considered beyond the scope of this invention.

Claims

1. A heat dissipation control method for cable branch boxes based on multi-source data, characterized in that, A heat dissipation control system for a cable branch box based on multi-source data is provided. The system includes a control terminal and heat dissipation equipment. The method is executed by the control terminal and includes: Acquire internal temperature data and load current data of the cable branch box; Based on the internal temperature data and the load current data, a first moment is determined when the internal temperature data rises from below a preset temperature threshold to above the preset temperature threshold, and a second moment is determined when the load current data rises from below a preset current threshold to above the preset current threshold. The duration from the second moment to the first moment is determined as the temperature rise response delay value; Based on the temperature rise response delay value, the start-up advance time of the heat dissipation device is determined.

2. The heat dissipation control method for a cable branch box based on multi-source data according to claim 1, characterized in that, The method further includes: Acquire ambient temperature data and solar radiation intensity data on the surface of the cable branch box; Based on the ambient temperature data and the solar radiation intensity data on the surface of the enclosure, the ambient thermal effect value is determined; Based on the environmental thermal effect value, the output power level of the heat dissipation device is determined.

3. The heat dissipation control method for a cable branch box based on multi-source data according to claim 2, characterized in that, Based on the temperature rise response delay value, the start-up advance time of the heat dissipation device is determined, including: Obtain the temperature rise response delay value corresponding to multiple load current rise events in the cable branch box during historical operation, as well as the occurrence time of each load current rise event; Based on each occurrence time, the temperature rise response delay values ​​are arranged in chronological order to obtain a record of delay value changes; Based on the temperature rise response delay value change record, determine a series of drift segments in which the temperature rise response delay value continuously increases or continuously decreases; Obtain the change in delay value per unit time within the drift segment, and determine the change in delay value as the drift rate; The trend compensation amount is determined based on the drift rate and the time interval between the current time and the end time of the drift segment; The temperature rise response delay value is superimposed with the trend compensation amount to obtain the expected temperature rise response delay value, which is used as the start-up advance time.

4. The heat dissipation control method for a cable branch box based on multi-source data according to claim 3, characterized in that, Determining the start-up advance time of the heat dissipation device based on the temperature rise response delay value also includes: Identify the fluctuation pattern of the delay value that recurs within the same month in the delay value change record, and record the fluctuation offset of the fluctuation pattern at different time points. Based on the occurrence time of the current event, query the fluctuation offset corresponding to the current time point in the fluctuation mode; The expected temperature rise response delay value is obtained by superimposing the temperature rise response delay value with the trend compensation amount, and is used as the start-up advance time, including: The expected temperature rise response delay value is obtained by superimposing the temperature rise response delay value, the fluctuation offset, and the trend compensation amount, and is used as the start-up advance time.

5. The heat dissipation control method for a cable branch box based on multi-source data according to claim 3, characterized in that, Before obtaining the temperature rise response delay value corresponding to multiple load current rise events in the cable branch box during historical operation, the method further includes: Obtain the load current data of the cable branch box during the historical operation; Based on the load current data, identify load current rise events where the current surge exceeds a preset sudden change threshold, and mark them as impulsive load events. The load current rise event that is not marked as the impulsive load event is marked as a continuous load event; The step of obtaining the temperature rise response delay value corresponding to multiple load current rise events in the cable branch box during historical operation includes: Obtain the temperature rise response delay value corresponding to the load current rise event marked as the continuous load event.

6. The heat dissipation control method for a cable branch box based on multi-source data according to claim 2, characterized in that, The system also includes an ambient temperature sensor installed on the cable branch box, which determines the ambient heat effect value based on the ambient temperature data and the solar radiation intensity data on the box surface, including: The solar exposure coefficient is obtained based on the ambient temperature sensor, wherein the solar exposure coefficient characterizes the measured temperature rise of the ambient temperature sensor under unit solar radiation intensity; Based on the solar radiation intensity data and the solar radiation exposure coefficient, the additional temperature rise of the sensor caused by solar radiation is determined as the temperature measurement deviation value; The ambient temperature data is corrected based on the temperature measurement deviation value to obtain the corrected ambient temperature data. Based on the pre-stored first correspondence between ambient temperature and thermal effect, the corrected ambient temperature data is converted into a first thermal effect component; Based on the pre-stored second correspondence between solar radiation intensity and thermal effect, the solar radiation intensity data at the current moment is converted into a second thermal effect component; The sum of the first thermal effect component and the second thermal effect component is taken as the environmental thermal effect value.

7. The heat dissipation control method for a cable branch box based on multi-source data according to claim 2, characterized in that, The acquisition of the internal temperature data of the cable branch box includes: Acquire temperature data collected by two or more temperature sensors located inside the cable branch box, wherein the two or more temperature sensors are located at different positions; After determining the output power level of the heat dissipation device based on the ambient thermal effect value, the process includes: Based on temperature data collected by two or more of the aforementioned temperature sensors, the maximum temperature difference inside the cable branch box is determined. Based on the preset correspondence between the maximum temperature difference and the power adjustment coefficient, the power adjustment coefficient corresponding to the maximum temperature difference is determined; Based on the power adjustment coefficient, the output power level is corrected, and the heat dissipation device is controlled to operate at the corrected output power level.

8. The heat dissipation control method for a cable branch box based on multi-source data according to claim 1, characterized in that, Based on the temperature rise response delay value, the start-up advance time of the heat dissipation device is determined, including: Obtain the temperature rise response delay value corresponding to multiple load current rise events in the cable branch box during historical operation, as well as the load current change rate corresponding to each event; Based on the load current change rate corresponding to each event and the temperature rise response delay value, determine the mapping relationship between the change rate and the delay value; Based on the currently acquired load current data, determine the current load current change rate; Based on the mapping relationship, the temperature rise response delay value corresponding to the current load current change rate is determined as the dynamic response delay value; The dynamic response delay value is used as the startup advance time of the heat dissipation device.

9. A heat dissipation control system for cable branch boxes based on multi-source data, characterized in that, include: The acquisition module is used to acquire the internal temperature data and load current data of the cable branch box; The first determining module is used to determine, based on the internal temperature data and the load current data, a first moment when the internal temperature data rises from below a preset temperature threshold to above the preset temperature threshold, and a second moment when the load current data rises from below a preset current threshold to above the preset current threshold. The second determining module is used to determine the duration from the second time point to the first time point as the temperature rise response delay value; The third determining module is used to determine the start-up advance time of the heat dissipation device based on the temperature rise response delay value.

10. A processing apparatus, characterized in that, The processing equipment includes: At least one processor; And, a memory communicatively connected to at least one of the processors; The memory stores instructions that can be executed by at least one of the processors, which are executed by at least one of the processors to enable the at least one processor to perform a cable branch box heat dissipation control method based on multi-source data as described in any one of claims 1-8.

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