Temperature control method, system and equipment of electric energy metering box and medium

Abstract

The invention provides a temperature control method, system and device for an electric energy metering box and a medium, and the method comprises the steps: calculating a heat dissipation capability index representing an external heat dissipation condition and a load change index representing a heating trend of an element through obtaining element-level, region-level and environment-level temperature data of a box body; when the load change exceeds a trend threshold value and the heat dissipation capability is lower than an exchange threshold value, it is judged that a heat accumulation early warning state is entered; when the element temperature does not reach the alarm value, an active heat dissipation strategy is started in advance, and the heat dissipation assembly is controlled to enter a first preset operation state; during the execution period, continuously monitoring the index change, and adjusting the operation parameters until the load index is lower than a recovery threshold value; in addition, the operation data containing the early warning state and the metering data are stored in an associated mode and uploaded to a remote platform. By implementing the technical scheme provided by the invention, the problem that passive heat dissipation cannot deal with dynamic thermal load can be effectively solved, element performance degradation and metering precision drift are prevented, the service life of equipment is prolonged, and the intelligent operation and maintenance efficiency is improved.

Description

Technical Field

[0001] This invention relates to the field of industrial internet technology, and in particular to a temperature control method, system, device and medium for an electricity metering box. Background Technology

[0002] With the comprehensive advancement of smart grid construction and the rapid development of the power Internet of Things, electricity metering boxes, as key sensing units at the end of the power grid, are playing an increasingly important role in electricity metering, distribution protection, and data acquisition. How to achieve precise monitoring and intelligent management of the real-time temperature, operating conditions, and power quality of electrical components such as metering chips and circuit breakers within the box has become a core requirement for ensuring the safe operation of the power grid and improving metering accuracy.

[0003] In existing technologies, electricity metering boxes generally employ natural ventilation or fixed passive heat dissipation structures, lacking active thermal management mechanisms. During actual operation, core components such as metering chips and circuit breakers within the box continuously generate Joule heat. Because the heat dissipation flux of passive heat dissipation structures is fixed, they cannot dynamically adjust in response to fluctuations in internal heat load or changes in external ambient temperature. Especially under extreme conditions of combined high-temperature and high-load operation, heat accumulates within the box and is difficult to dissipate, easily causing the operating temperature of core components to exceed their tolerance limits. This heat accumulation not only causes irreversible degradation of component physical performance and a sharp increase in failure rate, but also directly leads to drift in electricity metering accuracy, posing a risk of equipment performance degradation or malfunction. Summary of the Invention

[0004] In view of this, this application provides a temperature control method, system, device and medium for an electricity metering box to solve the above problems.

[0005] Firstly, a method for temperature control of an electricity metering box is provided, the method comprising:

[0006] Acquire component-level temperature data, area-level temperature data, and environmental-level temperature data from the power metering box;

[0007] Based on component-level temperature data, region-level temperature data, and environmental-level temperature data, heat dissipation capacity indicators characterizing the external heat dissipation conditions of the enclosure and load change indicators characterizing the heat generation trend of components are calculated.

[0008] When the load change index is greater than the preset trend threshold and the heat dissipation capacity index is less than the preset exchange threshold, the power metering box is determined to be in a heat accumulation warning state.

[0009] Based on the heat accumulation warning status, the active heat dissipation strategy is activated, and when the component-level temperature data is less than the preset alarm threshold, the first adjustment command is issued to the intelligent temperature control unit in the power metering box according to the active heat dissipation strategy.

[0010] According to the first adjustment command, the active heat dissipation component in the intelligent temperature control unit is adjusted to operate to the first preset operating state;

[0011] During the implementation of the active cooling strategy, the changes in heat dissipation capacity indicators and load change indicators are continuously monitored until the load change indicators are less than the preset recovery threshold, and the operating parameters of the active cooling components are adjusted.

[0012] Operational data, including those showing early warnings of heat accumulation, are linked and stored with electricity metering data, and then uploaded to a remote management platform.

[0013] The above technical solution, through joint acquisition and analysis of component-level, area-level, and environmental-level temperature data of the power metering box, can simultaneously reflect the internal heating status of the box and the external heat dissipation conditions. The calculated heat dissipation capacity index and load change index can be used to accurately determine whether there is a risk of heat accumulation in the box. Thus, when a heat accumulation trend occurs, active heat dissipation control is automatically triggered to adjust the temperature in advance, preventing the internal temperature of the box from rising continuously. This avoids the reduction in measurement accuracy, shortened lifespan, or safety hazards caused by overheating of components. Furthermore, remote monitoring and maintenance can be achieved through the uploading of operational data.

[0014] Optionally, based on component-level temperature data, region-level temperature data, and environmental-level temperature data, heat dissipation capacity indicators characterizing the external heat dissipation conditions of the enclosure and load change indicators characterizing the component heating trend are calculated, specifically including:

[0015] Construct a sliding sampling window of a preset length, acquire multiple regional sampling values ​​of regional temperature data within the sliding sampling window, and acquire multiple environmental sampling values ​​of environmental temperature data within the sliding sampling window;

[0016] Calculate the arithmetic mean of the sampled values ​​for each region to obtain the regional moving average.

[0017] Calculate the arithmetic mean of each environmental sample value to obtain the environmental moving average;

[0018] Calculate the average temperature difference between the regional sliding average and the environmental sliding average, and use the average temperature difference as an indicator of heat dissipation capacity;

[0019] Obtain the current component temperature value at the current sampling time from the component-level temperature data, and extract the historical component temperature value at the previous sampling time from the component-level temperature data, wherein the previous sampling time and the current sampling time are separated by a preset sampling time step;

[0020] Calculate the instantaneous temperature difference between the current component temperature value and the historical component temperature value, and divide the instantaneous temperature difference value by the sampling time step to obtain the original rate of change;

[0021] The original rate of change is processed by a first-order low-pass filtering algorithm to obtain the filtered rate of change value, which is then used as an indicator of load change.

[0022] The above technical solution, by setting a sliding sampling window and calculating the sliding average of the regional and ambient temperatures respectively, and then determining the heat dissipation capacity index based on the average temperature difference between the two, can dynamically reflect the changes in external heat dissipation efficiency over different time periods. At the same time, by performing low-pass filtering on the component temperature change rate, instantaneous noise interference in temperature sampling can be eliminated, thereby obtaining a more stable and accurate result for judging the load change trend, providing a highly reliable quantitative basis for subsequent heat accumulation early warning and proactive heat dissipation decision-making.

[0023] Optionally, based on the heat accumulation warning status, an active heat dissipation strategy is activated, and when the component-level temperature data is lower than a preset alarm threshold, a first adjustment command is issued to the intelligent temperature control unit in the power metering box according to the active heat dissipation strategy, specifically including:

[0024] Calculate the excess difference between the load change index and the trend threshold, and construct a thermal imbalance calculation model based on the excess difference and the heat dissipation capacity index;

[0025] The thermal imbalance coefficient is calculated using a thermal imbalance degree calculation model to quantify the current thermal accumulation risk level. The thermal imbalance coefficient is positively correlated with the excess difference and negatively correlated with the heat dissipation capacity index.

[0026] Call the fan speed control mapping table preset in the intelligent temperature control unit, and find the target pulse duty cycle that matches the thermal imbalance coefficient in the fan speed control mapping table;

[0027] A pulse width modulation signal containing the target pulse duty cycle is generated, and the pulse width modulation signal is sent to the intelligent temperature control unit as the first adjustment command.

[0028] The above technical solution constructs a thermal imbalance model by calculating the excess difference between the load change index and the trend threshold and combining it with the heat dissipation capacity index. This model can quantitatively represent the current thermal risk level of the enclosure. Based on this thermal imbalance coefficient, the corresponding pulse duty cycle is matched in the fan speed control mapping table to achieve adaptive adjustment of the fan speed. This makes the heat dissipation response proportional to the degree of thermal risk, avoiding energy waste or insufficient heat dissipation caused by fixed-rate control, and improving the accuracy and energy efficiency of temperature control.

[0029] Optionally, according to the first adjustment command, the active heat dissipation component in the intelligent temperature control unit is adjusted to operate to a first preset operating state, specifically including:

[0030] According to the preset component start-up sequence, a maximum stroke drive signal is sent to the electric adjustable louver to drive the blades of the electric adjustable louver to rotate to the position of maximum ventilation section.

[0031] The position feedback signal of the electrically adjustable louver is monitored. When the position feedback signal indicates that the louver has reached the position of the maximum ventilation section, a soft start ramp signal is generated based on the target pulse duty cycle. The variable frequency cooling fan is controlled to increase its speed according to the soft start ramp signal until it reaches the steady-state speed corresponding to the target pulse duty cycle.

[0032] The system collects real-time speed signals from the variable frequency cooling fan. When the deviation between the real-time speed signal and the steady-state speed is within a preset error range, it confirms that the active cooling component has been running in the first preset operating state.

[0033] The above technical solution controls the coordinated action of the electric adjustable louvers and variable frequency cooling fan through a preset start sequence. The soft start process of opening the maximum ventilation section first and then starting the fan can avoid airflow blockage and instantaneous current surge, ensuring smooth airflow for heat dissipation. Based on position feedback and closed-loop monitoring of fan speed, the operating status is confirmed, which can ensure that the active heat dissipation components operate safely and stably to the target working condition, improving the reliability and response stability of the system's heat dissipation performance.

[0034] Optionally, during the execution of the active cooling strategy, the changes in heat dissipation capacity indicators and load change indicators are continuously monitored until the load change indicators are less than a preset recovery threshold. The operating parameters of the active cooling components are then adjusted, specifically including:

[0035] Calculate the values ​​of load change indicators in real time and start the preset stability timer;

[0036] When the load change index value remains below the preset recovery threshold and the stability timer duration reaches the preset stability period, the current heat dissipation capacity index is obtained.

[0037] Compare the current heat dissipation capacity index with the preset thermal balance benchmark value;

[0038] If the heat dissipation capacity index is greater than the thermal balance reference value, a second adjustment command is generated, and the variable frequency cooling fan is controlled to switch from the first preset operating state to the second preset operating state based on the second adjustment command. The second preset operating state is used to maintain low-power active heat dissipation.

[0039] If the current heat dissipation capacity index is less than or equal to the thermal balance reference value, a shutdown command is generated to control the variable frequency cooling fan to stop running and to control the electric adjustable louvers to reset to the closed state.

[0040] The above technical solution achieves dynamic judgment of the thermal recovery process of the enclosure by continuously monitoring load change indicators and combining them with a stability timer. When the thermal state is stable, it can intelligently distinguish whether to enter the low power maintenance mode or completely shut down based on the comparison results of heat dissipation capacity indicators and thermal balance benchmark values. This ensures that excessive heat dissipation is avoided after the temperature returns to normal, and maintains necessary ventilation when the heat dissipation environment is insufficient, thus taking into account both temperature safety and energy consumption optimization.

[0041] Optionally, during the execution of the active cooling strategy, the changes in heat dissipation capacity indicators and load change indicators are continuously monitored until the load change indicators are less than a preset recovery threshold, and the operating parameters of the active cooling components are adjusted accordingly. This also includes:

[0042] Repeat the following adjustment steps until the load change index is less than the preset recovery threshold or the target pulse duty cycle reaches the preset ratio:

[0043] Within the current monitoring period, obtain the sampled values ​​of the load change index at multiple consecutive sampling times, and construct the current state vector by arranging the sampled values ​​in chronological order.

[0044] Based on the current state vector, calculate the descent slope of the load change index, and compare the descent slope with the preset minimum effective suppression slope to determine the heat dissipation gain requirement.

[0045] Based on the heat dissipation gain requirements, the target pulse duty cycle currently being executed by the variable frequency cooling fan is superimposed and calculated using a preset step amplitude to obtain the updated target pulse duty cycle.

[0046] The updated target pulse duty cycle is sent as a new control parameter to the intelligent temperature control unit for execution, and the variable frequency cooling fan is driven to perform cooling actions according to the updated target pulse duty cycle.

[0047] The above technical solutions, by performing state vector analysis on load change indicators at multiple consecutive sampling times and calculating the descent slope, can evaluate the dynamic trend of heat dissipation effect in real time; by performing step-by-step superposition adjustment of fan duty cycle based on heat dissipation gain requirements, a progressive heat dissipation enhancement process can be achieved on demand, avoiding frequent start-stop or over-adjustment of the temperature control system, improving the smoothness and accuracy of heat dissipation control, and enabling the system to maintain an effective temperature drop rate before the heat is fully released.

[0048] Optionally, operational data including heat accumulation warning status can be linked and stored with electricity metering data, and then uploaded to a remote management platform, specifically including:

[0049] Extract the electricity metering data during the period of heat accumulation warning and parse out the real-time load current value;

[0050] The real-time load current value is squared to obtain the calculation result to quantify the Joule heating effect. Based on the calculation result, a preset load temperature rise characteristic table is queried to obtain the theoretical temperature rise rate corresponding to the current load.

[0051] Calculate the absolute value of the difference between the current load change index and the theoretical temperature rise rate, and use the absolute value of the difference as the thermoelectric coupling deviation.

[0052] The thermoelectric coupling deviation is compared with the preset contact fault judgment threshold to generate a heat source attribute label. The heat source attribute label is used to characterize whether the current temperature rise is driven by normal load current or abnormal contact resistance.

[0053] Heat source attribute tags are used as metadata, bound and encapsulated with operation data and electricity metering data to generate structured logs, which are then uploaded to the remote management platform.

[0054] The above technical solution, by extracting power metering data during the heat accumulation warning period and correlating it with temperature characteristics, calculates the theoretical temperature rise rate corresponding to the load current and compares it with the actual temperature rise trend, can identify abnormal heating phenomena caused by abnormal contact resistance; the generated heat source attribute tags and operation logs are uploaded to the remote management platform, which can realize the tracing of the heating type of the power metering box and fault location, and improve the operation and maintenance department's early warning capability for potential contact faults and the efficiency of remote diagnosis.

[0055] Secondly, a temperature control system for an energy metering box is provided, the system comprising:

[0056] The data acquisition module is configured to acquire component-level temperature data, area-level temperature data, and environmental-level temperature data from the power metering box.

[0057] The index calculation module is configured to calculate, based on the component-level temperature data, region-level temperature data, and environmental-level temperature data, a heat dissipation capacity index characterizing the external heat dissipation conditions of the enclosure and a load change index characterizing the heating trend of the components.

[0058] The status determination module is configured to determine that the power metering box is in a heat accumulation warning state when the load change index is greater than a preset trend threshold and the heat dissipation capacity index is less than a preset exchange threshold.

[0059] The instruction issuing module is configured to activate an active heat dissipation strategy based on the heat accumulation warning state, and issue a first adjustment instruction to the intelligent temperature control unit in the power metering box according to the active heat dissipation strategy when the component-level temperature data is less than a preset alarm threshold.

[0060] The operation control module is configured to control the active heat dissipation component in the intelligent temperature control unit to operate to a first preset operating state according to the first adjustment command;

[0061] The dynamic adjustment module is configured to continuously monitor the changes in the heat dissipation capacity index and the load change index during the execution of the active heat dissipation strategy, until the load change index is less than a preset recovery threshold, and then adjust the operating parameters of the active heat dissipation component.

[0062] The data exchange module is configured to associate and store the operating data containing the heat accumulation early warning status with the power metering data, and upload it to the remote management platform.

[0063] Thirdly, an electronic device is provided, including a processor, a memory, a user interface, and a network interface, wherein the memory is used to store instructions, the user interface and the network interface are both used to communicate with other devices, and the processor is used to execute the instructions stored in the memory to cause the electronic device to perform the method as described in any of the above.

[0064] Fourthly, a computer-readable storage medium is provided, the computer-readable storage medium storing instructions that, when executed, perform the method as described in any of the preceding claims.

[0065] In summary, implementing one or more technical solutions provided in this application has at least the following technical effects or advantages:

[0066] By constructing a multi-layered temperature monitoring system covering component, regional, and environmental levels, and combining dynamic index calculation with proactive heat dissipation strategies, the system achieves full-cycle perception and adaptive control of the internal thermal state of the power metering box. The system can proactively intervene before heat accumulates significantly, avoiding delayed high-temperature responses, and automatically match the optimal heat dissipation mode based on environmental changes and load fluctuations, achieving a dynamic balance between heat dissipation capacity and energy consumption.

[0067] Furthermore, by coupling the analysis of temperature characteristics and electricity metering data, the system can further identify abnormal heat sources and generate heat source attribute tags, providing data-driven fault location and health assessment basis for the remote platform. This enables intelligent thermal management and remote operation and maintenance closed loop of the metering box, significantly improving the safety, stability and maintainability of equipment operation. Attached Figure Description

[0068] Figure 1 This is an exemplary system architecture diagram of a temperature control method or a temperature control system for an energy metering box according to the present application.

[0069] Figure 2This is a flowchart illustrating a temperature control method for an electricity metering box disclosed in this application.

[0070] Figure 3 This is a schematic diagram of a temperature control system for an energy metering box disclosed in this application;

[0071] Figure 4 This is a schematic diagram of the structure of an electronic device disclosed in this application.

[0072] Explanation of reference numerals in the attached diagram: 100, System architecture; 101, First terminal device; 102, Second terminal device; 103, Third terminal device; 104, Network; 105, Server; 301, Data acquisition module; 302, Indicator calculation module; 303, Status determination module; 304, Command issuance module; 305, Operation control module; 306, Dynamic adjustment module; 307, Data exchange module; 401, Processor; 402, Communication bus; 403, User interface; 404, Network interface; 405, Memory. Detailed Implementation

[0073] To enable those skilled in the art to better understand the technical solutions in this specification, the technical solutions in the embodiments of this specification will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments.

[0074] In the description of the embodiments of this application, the words "for example" or "for instance" are used to indicate examples, illustrations, or explanations. Any embodiment or design that is described as "for example" or "for instance" in the embodiments of this application should not be construed as being more preferred or advantageous than other embodiments or design options. Rather, the use of the words "for example" or "for instance" is intended to present the relevant concepts in a specific manner.

[0075] In the description of the embodiments of this application, the term "multiple" means two or more. For example, multiple systems means two or more systems, and multiple screen terminals means two or more screen terminals. Furthermore, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the indicated technical features. Thus, a feature defined with "first" or "second" may explicitly or implicitly include one or more of that feature. The terms "comprising," "including," "having," and variations thereof all mean "including but not limited to," unless otherwise specifically emphasized.

[0076] Figure 1An exemplary system architecture diagram is shown, illustrating an embodiment of a temperature control method or a temperature control system for an energy metering box that can be applied according to this application.

[0077] like Figure 1 As shown, the system architecture 100 may include a first terminal device 101, a second terminal device 102, a third terminal device 103, a network 104, and a server 105. The network 104 is used as a medium to provide communication links between the terminal devices 101, 102, 103, and the server 105. The network 104 may include various connection types, such as wired or wireless communication links or fiber optic cables, etc.

[0078] Users can use terminal devices 101, 102, and 103 to interact with server 105 via network 104 to receive or send messages, etc. Various communication client applications can be installed on terminal devices 101, 102, and 103, such as model training applications, video recognition applications, web browser applications, social platform software, etc.

[0079] Terminal devices 101, 102, and 103 can be either hardware or software. When terminal devices 101, 102, and 103 are hardware, they can be various electronic devices with displays, including but not limited to smartphones, tablets, e-book readers, MP3 (Moving Picture Experts Group Audio Layer III) players, MP4 (Moving Picture Experts Group Audio Layer IV) players, laptops, and desktop computers, etc. When terminal devices 101, 102, and 103 are software, they can be installed in the aforementioned electronic devices. They can be implemented as multiple software programs or software modules (e.g., multiple software programs or software modules used to provide distributed services) or as a single software program or software module. No specific limitations are imposed here.

[0080] When terminals 101, 102, and 103 are hardware devices, video capture devices can also be installed on them. These video capture devices can be various devices capable of capturing video, such as cameras, sensors, etc. Users can use the video capture devices on terminals 101, 102, and 103 to capture video.

[0081] Server 105 can be a server that provides various services, such as a backend server for processing data displayed on terminal devices 101, 102, and 103. The backend server can analyze and process the received data and can feed back the processing results (such as recognition results) to the terminal devices.

[0082] It should be noted that a server can be either hardware or software. When the server is hardware, it can be implemented as a distributed server cluster consisting of multiple servers, or as a single server. When the server is software, it can be implemented as multiple software programs or software modules (e.g., multiple software programs or software modules used to provide distributed services), or as a single software program or software module. No specific limitations are made here.

[0083] It should be understood that Figure 1 The number of terminal devices, networks, and servers shown is merely illustrative. Depending on implementation needs, any number of terminal devices, networks, and servers can be included. In particular, if the target data does not need to be obtained remotely, the above system architecture may exclude the network and include only terminal devices or servers.

[0084] Figure 2 This is a flowchart illustrating a temperature control method for an energy metering box according to an embodiment of this application. This method can be implemented using a computer program, a microcontroller, or run on a temperature control system for the energy metering box. The computer program can be integrated into an application or run as a standalone utility application. The specific steps of the temperature control method for an energy metering box are described in detail below.

[0085] S201: Acquire component-level temperature data, area-level temperature data, and environmental-level temperature data from the power metering box.

[0086] In this embodiment, component-level temperature data is used to represent the real-time thermal information of the surface of key heat-generating electronic components in the power metering box. It is an accurate value collected by a miniature temperature sensor that is directly attached or in close contact with the surface of the heat source, and can most directly reflect the operating thermal load status of the core component. For example, the data may specifically include the packaging temperature of the metering chip surface, the contact temperature of the moving and stationary contacts of the circuit breaker, and the temperature rise value at the wiring terminal, etc.

[0087] Specifically, a communication connection is established with a three-dimensional temperature monitoring network deployed inside and outside the electricity metering box to periodically read analog or digital signals uploaded by various sensors. Feedback signals from temperature sensors distributed at different spatial locations inside the box are analyzed to obtain regional temperature data. This data reflects the average air temperature at different height levels or functional zones within the box, used to assess the diffusion and convection distribution of heat inside the box. Data from sensors installed in shaded areas or vents outside the box are collected to obtain environmental temperature data. This data serves as a physical benchmark for heat exchange, characterizing the natural cooling potential provided by the current external atmospheric environment. The synchronously collected temperature values ​​from these three multi-dimensional sources are then time-aligned, converted from analog to digital, and formatted to complete the real-time acquisition of the electricity metering box's overall thermodynamic fundamental data.

[0088] Furthermore, when constructing a three-dimensional temperature monitoring network, component-level sensors preferably employ NTC thermistors or infrared non-contact probes with high insulation performance. These are tightly bonded to high-impedance risk points such as the electricity meter terminal blocks, circuit breaker moving and stationary contacts, and cable joints using thermally conductive silicone grease. The sensor leads must use twisted-pair shielded cables to resist interference from the power frequency electromagnetic field within the enclosure. Area-level sensors should be deployed in convection dead zones inside the enclosure (such as the top corners) and directly above the main heat source to capture the worst-case scenario of hot air accumulation and avoid data distortion caused by installation in areas directly exposed to fan airflow. Environmental-level sensors are installed on the shaded side of the enclosure's outer wall or inside the air inlet louvers, and equipped with physical sunshades to prevent artificially inflated ambient temperature readings caused by solar radiation heat. In addition, before analog-to-digital conversion, an RC low-pass filter circuit is connected in series in the hardware circuit to filter out spike pulse interference coupled to the sensor link from power grid fluctuations.

[0089] S202: Based on component-level temperature data, region-level temperature data, and environmental-level temperature data, calculate the heat dissipation capacity index characterizing the external heat dissipation conditions of the enclosure and the load change index characterizing the heat generation trend of the components.

[0090] For example, the system performs feature decoupling and deep computation on real-time acquired multi-source heterogeneous temperature data. On one hand, by comparing the gradient difference between the temperature inside the enclosure and the external environment, the driving potential energy for natural heat exchange in the enclosure under the current physical environment is evaluated, thereby quantifying the heat dissipation capacity index reflecting objective heat dissipation conditions. On the other hand, by performing longitudinal time-domain trend analysis on component-level temperature data, the transient temperature rise rate of core components due to current load fluctuations is captured, thereby extracting the load change index reflecting the intensity of internal heat source impact. Through the above calculation process, the original discrete temperature values ​​are transformed into feature parameters that can characterize the system's external heat dissipation potential and internal heating trend, providing a decoupled logical basis for subsequent determination of heat accumulation state.

[0091] In one possible implementation, based on component-level temperature data, region-level temperature data, and environmental-level temperature data, a heat dissipation capacity index characterizing the external heat dissipation conditions of the enclosure and a load change index characterizing the component's heating trend are calculated. Specifically, this includes: constructing a sliding sampling window of a preset length; acquiring multiple region-level temperature data sampling values ​​within the sliding sampling window; acquiring multiple environmental-level temperature data sampling values ​​within the sliding sampling window; calculating the arithmetic mean of each region's sampling values ​​to obtain the region sliding average; calculating the arithmetic mean of each environmental sampling value to obtain the environmental sliding average; and calculating the region sliding average versus the environmental sliding average. The average temperature difference between the moving averages is used as an indicator of heat dissipation capacity. The current component temperature value at the current sampling time is obtained, and the historical component temperature value at the previous sampling time is extracted, where a preset sampling time step separates the previous and current sampling times. The instantaneous temperature difference between the current and historical component temperatures is calculated, and the instantaneous temperature difference is divided by the sampling time step to obtain the original rate of change. The original rate of change is processed using a first-order low-pass filtering algorithm to obtain the filtered rate of change value, which is then used as an indicator of load change.

[0092] In this embodiment, the sampling time step (Δt) refers to the minimum time interval for the control system to acquire discretized data, which is a key parameter determining the system's sensitivity to thermal shock response. The selection of this parameter follows the Shannon sampling theorem and the principle of thermal inertia matching; it must be small enough to capture transient temperature rises caused by short circuits or overloads (typically in the millisecond to second range), and large enough to avoid excessive amplification of quantization noise by differential operations. The filter smoothing factor (α) is a dimensionless coefficient used in the low-pass filter to adjust the weight between signal following and noise suppression; its physical meaning lies in defining the system's rate of forgetting historical data.

[0093] Specifically, the system first allocates two circular buffers of length N in memory, following a first-in, first-out (FIFO) principle. At any time k, the regional temperature sequence T within the buffers is read. zone =[T z (k), T z (k-1),...,T z [(k-N+1)] and environmental temperature sequence T env =[T e (k), T e (k-1),...,T e [(k-N+1)], where T z (ki) represents the regional temperature sample value at time ki, T e(ki) represents the ambient temperature sample value at time ki. The first step is to use a moving average model to filter out Gaussian white noise caused by uneven spatial convection. The calculation formula is as follows: The heat dissipation capacity index H obtained here idx (k) In a physical sense, it characterizes the temperature difference-driven term ΔT in Newton's law of cooling, Q = h·A·ΔT. This index directly reflects the physical limit of the enclosure's ability to dissipate internal heat to the outside world solely through natural heat exchange at the current moment. In this thermodynamic model, Q represents the heat exchange rate (i.e., the amount of heat dissipated per unit time), h represents the convective heat transfer coefficient (which depends on the enclosure's natural ventilation structure and surface material), and A represents the effective surface area for heat exchange between the enclosure and the external environment. Since the structural parameters h and A are relatively fixed constants for a given power metering box, the heat dissipation capacity index H... idx The magnitude of (k) directly determines the strength of the driving potential energy for the enclosure to dissipate internal heat to the external environment solely through natural convection and heat conduction mechanisms at the current moment. The second step is to... (The sentence is incomplete and requires more context to translate accurately.) comp To extract the trend features characterizing load mutations, first perform discrete differentiation to calculate the original rate of change R. raw (k): R raw (k) = (T) comp (k)-T comp (k-1) / Δt. Since the sampling signal of temperature sensors (such as NTC thermistors or thermocouples) is usually superimposed with high-frequency electromagnetic interference, directly using R... raw This leads to amplification of derivative noise (noise power spectral density increases with the square of the frequency). Therefore, a first-order recursive low-pass filter (IIR filter) is introduced into the system to calculate the final load variation index L. idx (k), the iterative formula is as follows: L idx (k) = α·R raw (k) + (1-α)·L idx (k-1). Where α is the preset filtering smoothing factor (0 < α < 1). If α is small (e.g., 0.1), the system behaves as a large-inertia element, effectively filtering out spike noise and suitable for high electromagnetic interference environments; if α is large (e.g., 0.8), the system behaves as a fast-response element, quickly capturing thermal shocks caused by load current surges. During system initialization or the first calculation cycle, L is set... idx The initial value of (k-1) is 0 or equal to the current original rate of change R. raw (k). Through this algorithm, the system outputs L. idx (k) It retains the true temperature rise trend while shielding false noise interference, providing a high signal-to-noise ratio decision basis for subsequent heat accumulation early warning.

[0094] S203: When the load change index is greater than the preset trend threshold and the heat dissipation capacity index is less than the preset exchange threshold, the power metering box is determined to be in a heat accumulation warning state.

[0095] In this embodiment of the application, the heat accumulation warning state refers to a specific operating condition mark determined based on the coupling of multi-dimensional thermodynamic features. It is used to indicate that the heat load growth rate inside the power metering box has exceeded the balance point of the passive heat dissipation capacity that the current external environment can provide. It indicates that if no active intervention is taken, the temperature inside the box will irreversibly evolve towards the over-temperature boundary. For example, in the control logic, this state is specifically manifested as a specific bit of the internal status register of the MCU (Microcontroller Unit) being set to a logic high level (1), or a predefined fault code 0xA5A5 being written to the holding register address 40001 of the Modbus communication protocol.

[0096] Specifically, the system calls the decision benchmark parameters preset in non-volatile memory to read the trend threshold and exchange threshold, respectively. The trend threshold defines the upper limit of the allowable normal rate of temperature rise of a component per unit time, used to distinguish between normal load fluctuations and load surges with thermal shock risk. The exchange threshold defines the lower limit of the minimum internal and external temperature difference required to maintain effective natural convection heat dissipation, used to define the critical point at which passive heat dissipation mechanisms fail. Subsequently, a dual logical comparison operation is performed: on the one hand, it determines whether the real-time calculated load change index numerically exceeds the trend threshold to confirm whether there is a rapid heat generation behavior from the internal heat source; on the other hand, it determines whether the current heat dissipation capacity index numerically falls below the exchange threshold to confirm whether the external environment has sufficient thermal potential energy to absorb the increased heat. Only when both conditions are simultaneously met—that is, when the system detects a contradictory pair of characteristics—namely, an excessively rapid internal heat generation rate and insufficient external heat dissipation potential—is it confirmed that the system has entered a dangerous operating condition of heat intake and output imbalance, thus determining that the power metering box is in a heat accumulation warning state.

[0097] S204: Based on the heat accumulation warning status, activate the active heat dissipation strategy, and when the component-level temperature data is less than the preset alarm threshold, issue the first adjustment command to the intelligent temperature control unit in the power metering box according to the active heat dissipation strategy.

[0098] For example, in response to a heat accumulation warning, the system executes a feedforward control logic based on multidimensional thermodynamic characteristics within a safe window period before the core components reach the overheating alarm threshold. Specifically, the system first quantitatively assesses the degree of contradiction between the current excessive heat generation rate and the insufficient environmental heat dissipation potential, generating a dimensionless floating-point number between 0 and 1. Based on a preset nonlinear speed regulation strategy, the risk level is directly mapped to specific hardware drive parameters. These parameters are then sent to the actuators via the underlying communication bus, driving components such as cooling fans to intervene and operate in accordance with the intensity of the current thermal risk. This forces an increase in the convective heat transfer coefficient of the enclosure to the outside, establishing a heat dissipation flux capable of offsetting the internal heat generation rate before the temperature rises further due to the thermal inertia of the components.

[0099] In one possible implementation, based on the heat accumulation warning state, an active heat dissipation strategy is activated. When the component-level temperature data is less than a preset alarm threshold, a first adjustment command is issued to the intelligent temperature control unit in the power metering box according to the active heat dissipation strategy. Specifically, this includes: calculating the excess difference between the load change index and the trend threshold; constructing a thermal imbalance calculation model based on the excess difference and the heat dissipation capacity index; calculating the thermal imbalance coefficient of the current heat accumulation risk level using the thermal imbalance calculation model, wherein the thermal imbalance coefficient is positively correlated with the excess difference and negatively correlated with the heat dissipation capacity index; calling the fan speed control mapping table preset in the intelligent temperature control unit and finding the target pulse duty cycle that matches the thermal imbalance coefficient in the fan speed control mapping table; generating a pulse width modulation signal containing the target pulse duty cycle and sending the pulse width modulation signal as the first adjustment command to the intelligent temperature control unit.

[0100] In this embodiment, the thermal imbalance coefficient (η) is a dimensionless control parameter used to quantify the current thermal risk level faced by the system. Essentially, it is a dynamic gain factor used to map multi-dimensional thermodynamic contradictions (such as rapid heat generation and slow heat dissipation) to a one-dimensional actuator drive intensity. Its value directly determines the intervention depth of the active cooling system. For example, this coefficient can be designed as a floating-point number between 0.0 and 1.0, where 0.0 represents no intervention and 1.0 represents full-load operation. The first adjustment command refers to a digital control message containing specific hardware drive parameters (such as duty cycle value and frequency setting). It is the communication carrier connecting the upper-layer algorithm logic and the lower-layer hardware execution mechanism.

[0101] Specifically, after confirming that the warning logic has been triggered, the processor first performs a difference operation to calculate the current load change index L. curr Compared with the preset trend threshold L th The difference between them yields the excess difference ΔL=L. curr -L thThis value physically represents the amount of overheating that has overflowed. Subsequently, a thermal imbalance calculation model based on weighted summation or nonlinear product is constructed. To reflect the aforementioned positive and negative correlation, this model can be solved using the following normalized formula: η = w1·(ΔL / L) max )+w2·(1-(H curr / H ref In this formula, L max and H ref Having with ΔL and H curr For the same physical units, the weighting coefficients w1 and w2 are not fixed; the system supports an adaptive weight drift strategy based on the seasonal dimension. During high-temperature periods in summer (when ambient temperature data is consistently above 35°C), the system automatically increases the environmental weight w2 (e.g., adjusting it to 0.6) to improve sensitivity to deteriorating external heat dissipation. Conversely, during low-temperature periods in winter, the system automatically increases the load weight w1 to primarily prevent localized overheating of components caused by heavy heating loads. max H is the normalization factor for the maximum allowable rate of load change of the system; curr This represents the currently measured heat dissipation capacity; H ref This is a reference heat dissipation capacity value under standard conditions. Using this formula, as ΔL increases (heat generation increases), the first term (ΔL / L)... max An increase in H leads to an increase in η; when H curr When the temperature decreases (the environment is hotter / the temperature difference is smaller), the second term (1-(H)) curr / H ref An increase in η also leads to an increase in η.

[0102] Furthermore, the calculated η value is used as an index key to look up the fan speed in the fan speed mapping table. This mapping table is not a simple linear relationship, but a nonlinear curve (e.g., an S-curve) pre-fitted based on fluid dynamics characteristics to ensure that the fan speed increases gradually in the low-risk zone (quiet and energy-saving), while the speed increases sharply in the high-risk zone (η>0.8) (to implement high-intensity heat dissipation). Based on the percentage value obtained from the table, the timer's toggle threshold is configured to generate a pulse width modulation (PWM) signal with the corresponding duty cycle. When generating the PWM signal, the system dynamically selects the carrier frequency. In the low duty cycle (low speed) range, an ultrasonic frequency band (e.g., above 20kHz) is used to eliminate audible electromagnetic noise, suitable for sensitive scenarios involving nighttime disturbances; in the high duty cycle (high speed) range, it automatically switches to a low frequency band (e.g., 100Hz~2kHz) to reduce the switching losses of the power switching transistors and prevent the drive circuit from overheating, thus achieving a balance between quiet performance and drive efficiency.

[0103] Furthermore, to achieve physical control, the main control CPU encapsulates the parameters of the PWM signal (such as the duty cycle register value Dreg) into a standard industrial communication protocol frame (such as Modbus RTU or a custom CAN frame). This data frame is defined as the first adjustment command. This first adjustment command is sent to the intelligent temperature control unit at the execution layer (specifically, the motor drive controller integrated within the enclosure) via the onboard communication bus. After receiving and parsing the command, the intelligent temperature control unit directly modulates the conduction time of the power switch transistor, driving the active cooling component to operate at a speed precisely matching the calculated result, thereby completing the control closed loop from data model calculation to physical cooling execution.

[0104] S205: According to the first adjustment command, regulate the active heat dissipation component in the intelligent temperature control unit to operate to the first preset operating state.

[0105] For example, in response to the received adjustment command, the intelligent temperature control unit executes a combined control process that includes hardware timing interlocking and closed-loop feedback verification. This process first drives the ventilation adjustment mechanism to the fully open state to establish a low-impedance airflow channel, then controls the forced convection mechanism to smoothly load to the target load according to a preset flexible acceleration curve, and finally confirms, based on sensor feedback data, that the actual physical speed of the active heat dissipation component has converged to the theoretical speed error band corresponding to the target duty cycle, and that the ventilation actuator is at the position of maximum flow cross section.

[0106] In one possible implementation, according to the first adjustment command, the active heat dissipation component in the intelligent temperature control unit is regulated to operate to a first preset operating state. Specifically, this includes: sending a maximum stroke drive signal to the electrically adjustable louver according to a preset component start-up sequence, driving the blades of the electrically adjustable louver to rotate to the position of maximum ventilation cross section; monitoring the position feedback signal of the electrically adjustable louver, and when the position feedback signal indicates that the blades have reached the position of maximum ventilation cross section, generating a soft-start ramp signal based on the target pulse duty cycle, controlling the variable frequency cooling fan to increase its speed according to the soft-start ramp signal until a steady-state speed corresponding to the target pulse duty cycle is reached; collecting the real-time speed signal fed back by the variable frequency cooling fan, and confirming that the active heat dissipation component has operated to the first preset operating state when the deviation between the real-time speed signal and the steady-state speed is within a preset error range.

[0107] In this embodiment, the soft-start ramp signal refers to a voltage control sequence or digital drive instruction set that increases linearly or quasi-linearly with time, used to control the motor speed to smoothly transition from zero to the target value within a preset buffer time, rather than a step-like sudden change. It is used to represent a smooth starting trajectory that can suppress the large current impact and mechanical bearing stress at the moment of motor start-up. For example, the signal can specifically be represented as a PWM pulse sequence that increases the duty cycle by 2% every 50 milliseconds within 2 seconds until it reaches the target value of 60%.

[0108] Specifically, after parsing the received adjustment command, the control is executed strictly following the hardware protection logic of "open before moving". A full-stroke drive level is sent to the stepper motor or servo mechanism connected to the electric adjustment louvers, driving the deflector blades to rotate and open against static friction until they reach the maximum ventilation cross-section position allowed by the mechanical structure, thus pre-establishing a low-resistance heat dissipation channel. During this process, the level status of the limit switch or angle sensor at the louver linkage, i.e., the position feedback signal, is continuously polled or read via interrupt. Only when this signal clearly indicates that the blades have physically reached their position is the start-up lockout of the fan motor released. Using the target pulse duty cycle in the command as the endpoint, combined with the preset start-up duration, the duty cycle increment per unit time is calculated, generating a continuous soft-start ramp signal and outputting it to the fan drive circuit. This controls the fan speed to smoothly climb along the ramp curve, avoiding transient drops in power bus interference within the energy metering box. Once the fan speed stabilizes, the real-time speed is calculated by reading the pulse frequency fed back by the Hall sensor inside the motor. This real-time speed is then compared with the theoretical speed corresponding to the target duty cycle. If the absolute value of the difference between the two converges within the preset error allowable range (e.g., ±50 RPM), it is logically determined that the active cooling component has successfully entered and stably maintained the first preset operating state.

[0109] Furthermore, the system also possesses a fault-tolerant and degraded operation mechanism for hardware failures. When monitoring the position feedback signal of the electrically adjustable louvers, if the louvers are not detected to have reached the maximum ventilation section position within a preset timeout period (e.g., 5 seconds) (indicating mechanical jamming of the louvers or motor failure), the system will no longer execute the interlocking logic of "open first, then move," but will immediately trigger the forced convection emergency mode: forcibly starting the cooling fan to its maximum speed, using high air pressure to attempt to forcibly push open the louvers or dissipate heat through the gaps, and simultaneously uploading an alarm code for "louver failure." Simultaneously, when acquiring the real-time fan speed signal, if the PWM duty cycle is detected to be greater than 0 but the feedback speed is 0 (indicating fan stall), the system will immediately cut off the fan power and initiate intermittent retry logic (e.g., attempting to restart once every 30 seconds, for a total of 3 attempts) to prevent fire caused by coil burnout due to prolonged motor stall.

[0110] S206: During the execution of the active cooling strategy, continuously monitor the changes in heat dissipation capacity indicators and load change indicators until the load change indicators are less than the preset recovery threshold, and adjust the operating parameters of the active cooling components.

[0111] For example, the system executes bidirectional closed-loop regulation logic during the active heat dissipation maintenance phase. On the one hand, by tracking the decay trajectory of load indicators in real time, dynamic gain compensation is performed for operating conditions with lagging heat dissipation effect, forcibly increasing heat dissipation flux to ensure temperature rise suppression effect; on the other hand, after the load returns to the safe range, a graded exit mechanism based on thermal balance criteria is introduced, which intelligently decides whether to switch to low power maintenance mode or perform a complete shutdown and reset based on the residual heat dissipation of the enclosure, thereby ensuring thorough heat dissipation while taking into account system energy efficiency.

[0112] In one possible implementation, during the execution of the active cooling strategy, the changes in the heat dissipation capacity index and the load change index are continuously monitored until the load change index is less than a preset recovery threshold. The operating parameters of the active cooling component are then adjusted. Specifically, this includes: calculating the value of the load change index in real time and starting a preset stability timer; when the load change index value remains below the preset recovery threshold and the stability timer duration reaches a preset stabilization period, the current heat dissipation capacity index is obtained; the current heat dissipation capacity index is compared with a preset thermal balance reference value; if the heat dissipation capacity index is greater than the thermal balance reference value, a second adjustment command is generated, and based on the second adjustment command, the variable frequency cooling fan is controlled to switch from a first preset operating state to a second preset operating state, wherein the second preset operating state is used to maintain low-power active cooling; if the current heat dissipation capacity index is less than or equal to the thermal balance reference value, a shutdown command is generated, controlling the variable frequency cooling fan to stop operating and controlling the electric adjustment louvers to reset to the closed state.

[0113] In this embodiment of the application, the thermal balance reference value is used to represent the physical critical threshold for judging whether the residual heat inside the power metering box has been effectively discharged and whether the temperature difference between the inside and outside has returned to a natural equilibrium state. The thermal balance reference value is the temperature difference value calculated based on the heat capacity characteristics of the box material itself and the natural passive heat dissipation efficiency. When the real-time monitored heat dissipation capacity index is lower than this value, it physically means that the box no longer accumulates excess heat due to thermal inertia. For example, the reference value can be specifically set as a temperature difference between the inside and outside of the box that is less than 3 degrees Celsius or 5 degrees Celsius.

[0114] Specifically, after entering the active heat dissipation maintenance phase, the load change index reflecting the state of the heat source is continuously polled at high frequency. Once the index value is found to have fallen back to the safe range, i.e., below the preset recovery threshold, a software-defined stability timer is immediately triggered to start counting. During the timing process, if the load index rebounds above the threshold even once, the timer is immediately reset to zero; only when the index remains at a low level throughout the entire preset stabilization period (e.g., 60 seconds) is it confirmed that the actual heat load has been relieved, thus effectively filtering out transient jitter in the sensor signal. The system does not shut down directly, but further retrieves the current heat dissipation capacity index and compares it with the preset thermal balance benchmark value. If the comparison result shows that the heat dissipation capacity index is still greater than the benchmark value, it indicates that although the internal heat source is no longer in a high-heat state, the heat accumulated inside the cabinet has not been dissipated (there is thermal inertia). At this time, a second adjustment command containing frequency reduction parameters is generated to control the variable frequency cooling fan to smoothly switch from high speed to low speed operation in the second preset operating state, using low-power airflow to continuously remove residual heat. Conversely, if the heat dissipation capacity index is less than or equal to the benchmark value, it indicates that the inside and outside of the cabinet have reached thermal equilibrium, and no further active intervention is needed. At this time, a shutdown command is generated to cut off the fan power and drive the electric adjustment louvers to rotate in the opposite direction and reset to the closed state, so as to restore the physical protection performance of the cabinet.

[0115] In one possible implementation, during the execution of the active cooling strategy, the changes in the heat dissipation capacity index and the load change index are continuously monitored until the load change index is less than a preset recovery threshold. The operating parameters of the active cooling component are then adjusted. The process further includes: cyclically executing the following adjustment steps until the load change index is less than the preset recovery threshold or the target pulse duty cycle reaches a preset ratio: within the current monitoring cycle, acquiring the sampled values ​​of the load change index at multiple consecutive sampling moments, and constructing a current state vector from each sampled value in chronological order; based on the current state vector, calculating the descent slope of the load change index, and comparing the descent slope with a preset minimum effective suppression slope to determine the heat dissipation gain requirement; based on the heat dissipation gain requirement, superimposing the target pulse duty cycle currently being executed by the variable frequency cooling fan using a preset step size to obtain an updated target pulse duty cycle; and sending the updated target pulse duty cycle as a new control parameter to the intelligent temperature control unit for execution, and driving the variable frequency cooling fan to perform heat dissipation actions according to the updated target pulse duty cycle.

[0116] In this embodiment, the current state vector refers to an ordered data set arranged in a strict time series, used to represent the dynamic evolution trajectory of the load change index over time within an independent monitoring time window. It is the data basis for the system to perform trend fitting and slope calculation. For example, the vector can be specifically constructed as a one-dimensional array V=[L(t-9), L(t-8), ..., L(t)] containing the load change index values ​​collected once per second in the past 10 seconds.

[0117] Specifically, after entering the closed-loop maintenance phase of active cooling, the system initiates an iterative loop logic with adaptive adjustment capabilities. Within each preset monitoring cycle, it first extracts load change index samples from the memory buffer pool in batches from the most recent sampling times and reassembles them into a current state vector in chronological order. Using the least squares method or difference algorithm, it performs linear fitting on the data points in this vector to calculate the tangent slope of the data curve, i.e., the descent slope. This slope physically characterizes the effectiveness of suppressing the component temperature rise trend under the current cooling intensity. The real-time calculated descent slope is compared with a preset minimum effective suppression slope. If the real-time slope is less than the baseline slope (i.e., the curve is too flat, and the cooling effect is not as expected), it is determined that the system has a cooling gain requirement. In response to this requirement, it reads the target pulse duty cycle currently being executed by the fan and adds a preset step size (e.g., an increase of 5%) to calculate a higher updated target pulse duty cycle. The updated parameters are sent through the communication interface to force the variable frequency cooling fan to speed up, thereby increasing the heat dissipation. The process is then repeated in the next monitoring cycle until the load index drops back to the safe level or the fan speed reaches the physical limit.

[0118] S207: Link and store the operating data, which includes the heat accumulation warning status, with the electricity metering data, and upload it to the remote management platform.

[0119] For example, after locking in the heat accumulation warning period, the system performs deep fusion and causal analysis of cross-domain data. Specifically, the system aligns and verifies the temperature rise behavior in the thermodynamic dimension with the load characteristics in the electrical dimension to automatically identify the physical causes of abnormal temperature rise (such as normal load effects or abnormal contact impedance). The system structurally encapsulates the attribute tags containing diagnostic conclusions with the original monitoring data to construct a complete evidence chain with fault tracing capabilities. This chain is then pushed to the cloud via an IoT channel, enabling the remote management platform to distinguish, without manual on-site investigation, whether the current temperature rise is a normal physical phenomenon caused by grid load fluctuations or an electrical fault caused by poor equipment contact.

[0120] In one possible implementation, operational data including the heat accumulation warning status is associated and stored with electricity metering data, and then uploaded to a remote management platform. Specifically, this includes: extracting electricity metering data during the duration of the heat accumulation warning status and parsing the real-time load current value; squaring the real-time load current value to quantify the Joule heating effect; querying a preset load temperature rise characteristic table based on the calculation result to obtain the theoretical temperature rise rate corresponding to the current load; calculating the absolute value of the difference between the current load change index and the theoretical temperature rise rate, and using this absolute value as the thermoelectric coupling deviation; comparing the thermoelectric coupling deviation with a preset contact fault judgment threshold to generate a heat source attribute tag, which characterizes whether the current temperature rise is driven by normal load current or by abnormal contact resistance; and binding and encapsulating the heat source attribute tag as metadata with the operational data and electricity metering data to generate a structured log, which is then uploaded to the remote management platform.

[0121] In the embodiments of this application, the thermoelectric coupling deviation is used to represent the degree of deviation between the actual monitored temperature rise trend and the theoretical expected temperature rise calculated based on physical laws. It is a diagnostic index constructed based on the principle of current heating effect, which aims to reveal whether the physical driving mechanism behind the current heating phenomenon conforms to the normal Joule law model. For example, the deviation can be specifically expressed as an absolute temperature difference value (such as 5.2℃) or a normalized deviation percentage.

[0122] Specifically, when the system enters or is in a heat accumulation warning state, the system locks the duration of this state within a specified time window, retrieves all electrical energy metering data for that period from the historical database of the electrical energy metering module, and parses out the high-precision real-time load current value. Based on Joule's law in physics, the current value is squared to obtain an intermediate variable characterizing the intensity of the current's thermal effect. This result is then used as an index to perform a matching query in a pre-set load-temperature rise characteristic table. This characteristic table is constructed based on enclosure thermal simulation or laboratory calibration data, recording the theoretically expected temperature rise rate under different current intensities, thus obtaining the corresponding theoretical temperature rise rate. The system calls the load change index (i.e., the actual temperature rise rate) calculated in real-time in the previous steps, calculates the absolute value of the difference between it and the theoretical temperature rise rate, and defines this value as the thermoelectric coupling deviation. When calculating the thermoelectric coupling deviation, considering the thermal inertia hysteresis effect of heat conduction in physical entities (i.e., after a sudden change in current, the temperature needs a certain period of time to show a change), the system introduces a time-sliding compensation mechanism when querying the load temperature rise characteristic table. Specifically, instead of comparing the current load change index with the theoretical temperature rise of the current, the system compares the current load change index with the theoretical temperature rise calculated from historical current data shifted forward by a preset lag time (e.g., 30 seconds). This preset lag time is a thermal response time constant pre-calibrated based on the specific heat capacity and mass of the busbar material in the power metering box. This phase compensation in time eliminates spurious deviations caused by thermal inertia, significantly improving the accuracy of identifying minor contact resistance faults. The deviation is then compared numerically with a preset contact fault judgment threshold: if the deviation exceeds the threshold, it means the temperature rise is far beyond what the current load can explain, indicating an abnormality caused by excessive contact resistance (e.g., loose terminals); otherwise, it is determined to be driven by normal load. Based on this judgment result, a heat source attribute label with clear semantics is generated (e.g., normal overload or abnormal loose connection). This tag is used as metadata and is time-series aligned and bound to the original operational data and power metering data to construct a structured log containing fault causal logic. This log is then uploaded to the remote management platform via the communication module, providing maintenance personnel with accurate fault diagnosis basis.

[0123] Figure 3 This is a schematic diagram of a temperature control system for an energy metering box according to an embodiment of this application. This system can be implemented through software, hardware, or a combination of both, forming all or part of the overall system. For example... Figure 3 As shown, the system includes:

[0124] The data acquisition module 301 is configured to acquire component-level temperature data, area-level temperature data, and environmental-level temperature data of the power metering box.

[0125] The index calculation module 302 is configured to calculate, based on the component-level temperature data, region-level temperature data, and environmental-level temperature data, a heat dissipation capacity index characterizing the external heat dissipation conditions of the enclosure and a load change index characterizing the heating trend of the components.

[0126] The status determination module 303 is configured to determine that the power metering box is in a heat accumulation warning state when the load change index is greater than a preset trend threshold and the heat dissipation capacity index is less than a preset exchange threshold.

[0127] The instruction issuing module 304 is configured to activate an active heat dissipation strategy based on the heat accumulation warning state, and issue a first adjustment instruction to the intelligent temperature control unit in the power metering box according to the active heat dissipation strategy when the component-level temperature data is less than a preset alarm threshold.

[0128] The operation control module 305 is configured to control the active heat dissipation component in the intelligent temperature control unit to operate to a first preset operating state according to the first adjustment command;

[0129] The dynamic adjustment module 306 is configured to continuously monitor the changes in the heat dissipation capacity index and the load change index during the execution of the active heat dissipation strategy, until the load change index is less than a preset recovery threshold, and adjust the operating parameters of the active heat dissipation component.

[0130] The data exchange module 307 is configured to associate and store the operating data containing the heat accumulation early warning status with the power metering data, and upload it to the remote management platform.

[0131] Based on the above embodiments, as an optional embodiment, the index calculation module 302 is specifically used for: constructing a sliding sampling window of a preset length, acquiring multiple regional sampling values ​​of regional temperature data within the sliding sampling window, and acquiring multiple environmental sampling values ​​of environmental temperature data within the sliding sampling window; calculating the arithmetic mean of each regional sampling value to obtain the regional sliding average; calculating the arithmetic mean of each environmental sampling value to obtain the environmental sliding average; calculating the average temperature difference between the regional sliding average and the environmental sliding average, and using the average temperature difference as a heat dissipation capacity index; acquiring the current component temperature value of the component-level temperature data at the current sampling time, and extracting the historical component temperature value of the component-level temperature data at the previous sampling time, wherein the previous sampling time and the current sampling time are separated by a preset sampling time step; calculating the instantaneous temperature difference between the current component temperature value and the historical component temperature value, and dividing the instantaneous temperature difference by the sampling time step to obtain the original rate of change; processing the original rate of change through a first-order low-pass filtering algorithm to obtain the filtered rate of change value, and using the filtered rate of change value as a load change index.

[0132] Based on the above embodiments, as an optional embodiment, the instruction issuing module 304 is specifically used for: calculating the excess difference between the load change index and the trend threshold; constructing a thermal imbalance calculation model based on the excess difference and the heat dissipation capacity index; calculating the thermal imbalance coefficient of the current heat accumulation risk level using the thermal imbalance calculation model, wherein the thermal imbalance coefficient is positively correlated with the excess difference and negatively correlated with the heat dissipation capacity index; calling the fan speed control mapping table preset in the intelligent temperature control unit, searching for the target pulse duty cycle that matches the thermal imbalance coefficient in the fan speed control mapping table; generating a pulse width modulation signal containing the target pulse duty cycle, and sending the pulse width modulation signal as the first adjustment instruction to the intelligent temperature control unit.

[0133] Based on the above embodiments, as an optional embodiment, the operation control module 305 is specifically used to: send a maximum stroke drive signal to the electric adjustable louver according to a preset component start-up sequence, driving the blades of the electric adjustable louver to rotate to the maximum ventilation section position; monitor the position feedback signal of the electric adjustable louver, and when the position feedback signal indicates that the blades have reached the maximum ventilation section position, generate a soft-start ramp signal based on the target pulse duty cycle, and control the variable frequency cooling fan to increase its speed according to the soft-start ramp signal until it reaches the steady-state speed corresponding to the target pulse duty cycle; collect the real-time speed signal fed back by the variable frequency cooling fan, and when the deviation between the real-time speed signal and the steady-state speed is within a preset error range, confirm that the active cooling component has run to the first preset operating state.

[0134] Based on the above embodiments, as an optional embodiment, the dynamic adjustment module 306 is specifically used for: calculating the value of the load change index in real time and starting a preset stability timer; when it is detected that the value of the load change index remains below a preset recovery threshold and the duration of the stability timer reaches a preset stabilization period, obtaining the current heat dissipation capacity index; comparing the current heat dissipation capacity index with a preset thermal balance reference value; if the heat dissipation capacity index is greater than the thermal balance reference value, generating a second adjustment command, and controlling the variable frequency cooling fan to switch from a first preset operating state to a second preset operating state based on the second adjustment command, wherein the second preset operating state is used to maintain low-power active heat dissipation; if the current heat dissipation capacity index is less than or equal to the thermal balance reference value, generating a stop command, controlling the variable frequency cooling fan to stop operating and controlling the electric adjustment louvers to reset to the closed state.

[0135] Based on the above embodiments, as an optional embodiment, the dynamic adjustment module 306 is specifically used to: cyclically execute the following adjustment steps until the load change index is less than the preset recovery threshold or the target pulse duty cycle reaches the preset ratio: within the current monitoring cycle, obtain the sampled values ​​of the load change index at multiple consecutive sampling moments, and construct the current state vector according to the time sequence of each sampled value; based on the current state vector, calculate the descent slope of the load change index, and compare the descent slope with the preset minimum effective suppression slope to determine the heat dissipation gain requirement; based on the heat dissipation gain requirement, use the preset step amplitude to superimpose the target pulse duty cycle currently being executed by the variable frequency cooling fan to obtain the updated target pulse duty cycle; send the updated target pulse duty cycle as a new control parameter to the intelligent temperature control unit for execution, and drive the variable frequency cooling fan to perform heat dissipation actions according to the updated target pulse duty cycle.

[0136] Based on the above embodiments, as an optional embodiment, the data exchange module 307 is specifically used for: extracting the power metering data during the continuous period of the heat accumulation warning state and parsing out the real-time load current value; performing a square operation on the real-time load current value to obtain the calculation result to quantify the Joule heating effect; querying a preset load temperature rise characteristic table based on the calculation result to obtain the theoretical temperature rise rate corresponding to the current load; calculating the absolute value of the difference between the current load change index and the theoretical temperature rise rate, and using the absolute value of the difference as the thermoelectric coupling deviation; comparing the thermoelectric coupling deviation with a preset contact fault judgment threshold to generate a heat source attribute tag, which is used to characterize whether the current temperature rise is driven by normal load current or by abnormal contact resistance; binding and encapsulating the heat source attribute tag as metadata with the operation data and power metering data to generate a structured log and uploading it to the remote management platform.

[0137] It should be noted that the system provided in the above embodiments is only illustrated by the division of the above functional modules. In actual applications, the above functions can be assigned to different functional modules as needed, that is, the internal structure of the device can be divided into different functional modules to complete all or part of the functions described above. In addition, the system and method embodiments provided in the above embodiments belong to the same concept, and the specific implementation process can be found in the method embodiments, which will not be repeated here.

[0138] This embodiment also discloses an electronic device, referring to... Figure 4 The electronic device may include: at least one processor 401, at least one communication bus 402, user interface 403, network interface 404, and at least one memory 405.

[0139] The communication bus 402 is used to enable communication between these components.

[0140] The user interface 403 may include a display screen and a camera. Optionally, the user interface 403 may also include a standard wired interface and a wireless interface.

[0141] The network interface 404 may optionally include a standard wired interface or a wireless interface (such as a Wi-Fi interface).

[0142] The processor 401 may include one or more processing cores. The processor 401 connects to various parts of the server using various interfaces and lines, and performs various server functions and processes data by running or executing instructions, programs, code sets, or instruction sets stored in memory 405, and by calling data stored in memory 405. Optionally, the processor 401 may be implemented using at least one hardware form of Digital Signal Processing (DSP), Field-Programmable Gate Array (FPGA), or Programmable Logic Array (PLA). The processor 401 may integrate one or a combination of several of the following: Central Processing Unit (CPU), Graphics Processing Unit (GPU), and modem. The CPU primarily handles the operating system, user interface, and applications; the GPU is responsible for rendering and drawing the content required for display; and the modem handles wireless communication. It is understood that the modem may also be implemented as a separate chip without being integrated into the processor 401.

[0143] The memory 405 may include random access memory (RAM) or read-only memory. Optionally, the memory 405 may include a non-transitory computer-readable storage medium. The memory 405 may be used to store instructions, programs, code, code sets, or instruction sets. The memory 405 may include a program storage area and a data storage area, wherein the program storage area may store instructions for implementing an operating system, instructions for at least one function (such as touch function, sound playback function, image playback function, etc.), instructions for implementing the above-described method embodiments, etc.; the data storage area may store data involved in the above-described method embodiments, etc. Optionally, the memory 405 may also be at least one storage device located remotely from the aforementioned processor 401. Figure 4 As shown, the memory 405, which serves as a computer storage medium, may include an operating system, a network communication module, a user interface module, and an application program for a temperature control method for an energy metering box.

[0144] exist Figure 4 In the electronic device shown, the user interface 403 is mainly used to provide an input interface for the user and to obtain the user input data; while the processor 401 can be used to call the application program stored in the memory 405 for a temperature control method of an energy metering box. When executed by one or more processors 401, the electronic device executes one or more methods as described in the above embodiments.

[0145] It should be noted that, for the sake of simplicity, the foregoing method embodiments are all described as a series of actions. However, those skilled in the art should understand that this application is not limited to the described order of actions, as some steps may be performed in other orders or simultaneously according to this application. Furthermore, those skilled in the art should also understand that the embodiments described in the specification are preferred embodiments, and the actions and modules involved are not necessarily essential to this application.

[0146] In the above embodiments, the descriptions of each embodiment have different focuses. For parts not described in detail in a certain embodiment, please refer to the relevant descriptions in other embodiments.

[0147] In the several embodiments provided in this application, it should be understood that the disclosed apparatus can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the shown or discussed mutual couplings or direct couplings or communication connections may be through some service interfaces; indirect couplings or communication connections between apparatuses or units may be electrical or other forms.

[0148] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0149] Furthermore, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0150] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage device (CMD). Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a memory 405 and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods of the various embodiments of this application. The aforementioned memory 405 includes various media capable of storing program code, such as a USB flash drive, external hard drive, magnetic disk, or optical disk.

[0151] The foregoing description is merely an exemplary embodiment of this disclosure and should not be construed as limiting the scope of this disclosure. Any equivalent changes and modifications made in accordance with the teachings of this disclosure shall still fall within the scope of this disclosure. Those skilled in the art will readily conceive of other embodiments of this disclosure upon considering the disclosure in this specification. This application is intended to cover any variations, uses, or adaptations of this disclosure that follow the general principles of this disclosure and include common knowledge or customary techniques in the art not described in this disclosure. The specification and embodiments are considered exemplary only, and the scope of this application is defined by the claims.

Claims

1. A temperature control method of an electric energy metering box, characterized by, The method comprises: obtaining element-level temperature data, region-level temperature data and environment-level temperature data of an electric energy metering box; based on the element-level temperature data, region-level temperature data and environment-level temperature data, calculating a heat dissipation capability index representing the heat dissipation condition outside the box and a load change index representing the heating trend of the element; when the load change index is greater than a preset trend threshold and the heat dissipation capability index is less than a preset exchange threshold, determining that the electric energy metering box is in a heat accumulation warning state; based on the heat accumulation warning state, starting an active heat dissipation strategy, and when the element-level temperature data is less than a preset warning threshold, issuing a first adjustment instruction to the intelligent temperature control unit in the electric energy metering box according to the active heat dissipation strategy; according to the first adjustment instruction, regulating the active heat dissipation component in the intelligent temperature control unit to operate to a first preset operating state; during the execution of the active heat dissipation strategy, continuously monitoring the changes of the heat dissipation capability index and the load change index until the load change index is less than a preset recovery threshold, and adjusting the operating parameters of the active heat dissipation component; storing the operating data containing the heat accumulation warning state and the electric energy metering data in association, and uploading to a remote management platform.

2. The method of claim 1, wherein, The calculation of the heat dissipation capability index representing the heat dissipation condition outside the box and the load change index representing the heating trend of the element based on the element-level temperature data, region-level temperature data and environment-level temperature data comprises: constructing a preset length of a sliding sampling window, obtaining a plurality of region sampling values of the region-level temperature data within the sliding sampling window, and obtaining a plurality of environment sampling values of the environment-level temperature data within the sliding sampling window; calculating the arithmetic mean of each region sampling value to obtain a region sliding average value; calculating the arithmetic mean of each environment sampling value to obtain an environment sliding average value; calculating the average temperature difference value between the region sliding average value and the environment sliding average value, and taking the average temperature difference value as the heat dissipation capability index; obtaining a current element temperature value of the element-level temperature data at a current sampling time, and extracting a historical element temperature value of the element-level temperature data at a previous sampling time, wherein the previous sampling time and the current sampling time are separated by a preset sampling time step; calculating the instantaneous temperature difference value between the current element temperature value and the historical element temperature value, and dividing the instantaneous temperature difference value by the sampling time step to obtain an original change rate; processing the original change rate through a first-order low-pass filter algorithm to obtain a filtered change rate value, and taking the filtered change rate value as the load change index.

3. The method of claim 2, wherein, The starting of the active heat dissipation strategy based on the heat accumulation warning state, and the issuance of the first adjustment instruction to the intelligent temperature control unit in the electric energy metering box according to the active heat dissipation strategy when the element-level temperature data is less than a preset warning threshold, comprises: calculating the excess difference value between the load change index and the trend threshold, and constructing a heat imbalance degree calculation model based on the excess difference value and the heat dissipation capability index; calculating a heat imbalance coefficient quantifying a current heat accumulation risk level by using the heat imbalance degree calculation model, wherein the heat imbalance coefficient is positively correlated with the excessive difference and negatively correlated with the heat dissipation capability indicator; calling a fan speed mapping table pre-stored in the intelligent temperature control unit, and searching for a target pulse duty cycle matching the heat imbalance coefficient in the fan speed mapping table; generating a pulse width modulation signal containing the target pulse duty cycle, and sending the pulse width modulation signal as the first adjustment instruction to the intelligent temperature control unit.

4. The method of claim 3, wherein, The first adjustment instruction is used to control the active heat dissipation component in the intelligent temperature control unit to operate in a first preset operating state, and specifically includes: sending a maximum stroke driving signal to the electrically-controlled adjustment louver according to a preset component starting sequence, so as to drive the blades of the electrically-controlled adjustment louver to rotate to a maximum ventilation cross-section position; monitoring a position feedback signal of the electrically-controlled adjustment louver, and when it is detected that the position feedback signal indicates that the blades have reached the maximum ventilation cross-section position, generating a soft start ramp signal based on the target pulse duty cycle, and controlling the variable-frequency heat dissipation fan to increase the rotating speed according to the soft start ramp signal until a steady-state rotating speed corresponding to the target pulse duty cycle is reached; acquiring a real-time rotating speed signal fed back by the variable-frequency heat dissipation fan, and when a deviation between the real-time rotating speed signal and the steady-state rotating speed is within a preset error range, confirming that the active heat dissipation component has operated in the first preset operating state.

5. The method of claim 4, wherein, During the execution of the active heat dissipation strategy, the changes of the heat dissipation capability indicator and the load change indicator are continuously monitored until the load change indicator is less than a preset recovery threshold, and the operating parameters of the active heat dissipation component are adjusted, specifically including: calculating the value of the load change indicator in real time, and starting a preset stability timer; when it is detected that the value of the load change indicator remains less than the preset recovery threshold, and the timing length of the stability timer reaches a preset stability period, acquiring the current heat dissipation capability indicator; comparing the current heat dissipation capability indicator with a preset heat balance reference value in terms of value; if the heat dissipation capability indicator is greater than the heat balance reference value, a second adjustment instruction is generated, and the variable-frequency heat dissipation fan is controlled to switch from the first preset operating state to a second preset operating state based on the second adjustment instruction, wherein the second preset operating state is used to maintain low-power active heat dissipation; if the current heat dissipation capability indicator is less than or equal to the heat balance reference value, a shutdown instruction is generated, and the variable-frequency heat dissipation fan is controlled to stop operating and the electrically-controlled adjustment louver is controlled to reset to a closed state.

6. The method of claim 5, wherein, During the execution of the active heat dissipation strategy, the changes of the heat dissipation capability indicator and the load change indicator are continuously monitored until the load change indicator is less than a preset recovery threshold, and the operating parameters of the active heat dissipation component are adjusted, and further including: recursively executing the following adjustment steps until the load change indicator is less than the preset recovery threshold or the target pulse duty cycle reaches a preset proportion value: In the current monitoring cycle, sampling values of the load change indicator at multiple continuous sampling moments are obtained, and each sampling value is constructed into a current state vector in time sequence; Based on the current state vector, a descending slope of the load change indicator is calculated, and the descending slope is compared with a preset minimum effective suppression slope to determine a heat dissipation gain requirement; Based on the heat dissipation gain requirement, a preset step size is used to perform superposition calculation on the target pulse duty cycle currently executed by the variable-frequency heat dissipation fan, to obtain an updated target pulse duty cycle; The updated target pulse duty cycle is issued as a new control parameter to the intelligent temperature control unit for execution, and the variable-frequency heat dissipation fan is driven to perform heat dissipation actions according to the updated target pulse duty cycle.

7. The method of claim 1, wherein, The operation data containing the heat accumulation warning state and the electric energy metering data are associated and stored, and uploaded to a remote management platform, specifically including: Extracting electric energy metering data during the duration of the heat accumulation warning state, and parsing real-time load current values; Performing square operation on the real-time load current values to obtain an operation result to quantify the Joule heat effect, querying a preset load temperature rise characteristic table based on the operation result to obtain a theoretical temperature rise rate corresponding to the current current load; Calculating the absolute value of the difference between the current load change indicator and the theoretical temperature rise rate, and taking the absolute value of the difference as a thermoelectric coupling deviation; Comparing the thermoelectric coupling deviation with a preset contact fault determination threshold to generate a heat source attribute label, the heat source attribute label being used to represent whether the current temperature rise is driven by normal load current or abnormal contact resistance; The heat source attribute label is used as metadata, and is bound and packaged with the operation data and the electric energy metering data to generate a structured log, and is uploaded to the remote management platform.

8. A temperature control system for an electricity metering box, characterized by The system comprises: A data acquisition module configured to acquire element-level temperature data, regional-level temperature data and environmental-level temperature data of an electric energy metering box; An indicator calculation module configured to calculate a heat dissipation capacity indicator representing external heat dissipation conditions of the box and a load change indicator representing a heating trend of the element based on the element-level temperature data, the regional-level temperature data and the environmental-level temperature data; A state determination module configured to determine that the electric energy metering box is in a heat accumulation warning state when the load change indicator is greater than a preset trend threshold and the heat dissipation capacity indicator is less than a preset exchange threshold; An instruction issuing module configured to start an active heat dissipation strategy based on the heat accumulation warning state, and issue a first adjustment instruction to an intelligent temperature control unit in the electric energy metering box according to the active heat dissipation strategy when the element-level temperature data is less than a preset alarm threshold; An operation regulation module configured to regulate the active heat dissipation component in the intelligent temperature control unit to a first preset operation state according to the first adjustment instruction; a dynamic adjustment module, configured to monitor the changes of the heat dissipation capability indicator and the load change indicator during the execution of the active heat dissipation strategy, until the load change indicator is less than a preset recovery threshold, and adjust the operation parameter of the active heat dissipation component; a data exchange module, configured to store the operation data containing the heat accumulation warning state and the electric energy metering data in association, and upload to a remote management platform.

9. An electronic device, comprising: An electronic device includes a processor, a memory, a user interface, and a network interface. The memory is configured to store instructions. The user interface and the network interface are configured to communicate with other devices. The processor is configured to execute the instructions stored in the memory to cause the electronic device to perform the method of any one of claims 1-7.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores instructions that, when executed, perform the method of any one of claims 1-7.

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