Electric meter box temperature control system based on environmental perception

Abstract

The invention discloses an electric meter box temperature control system based on environmental perception, and relates to the technical field of electric meter box temperature control, and the system comprises a position parameter collection module which is used for obtaining static structural parameter information representing an actual fixed installation scene after an electric meter box is installed, constructing a position parameter set representing the long-term operation environment of the target electric meter box; and the environment response module is used for establishing an environment adaptation model corresponding to the temperature change rule of the electric meter box based on the position parameter set and real-time operation data acquired in a data acquisition stage required for completing initialization of the environment adaptation model. According to the invention, through fusion of position parameter modeling, environmental response analysis, temperature rise trend monitoring, dynamic temperature control strategy setting and resource allocation management, intelligent thermal management of the electric meter box in a complex operation environment is realized.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of electric meter box temperature control, in particular to an electric meter box temperature control system based on environmental perception. BACKGROUND

[0002] With the continuous development of urban power distribution networks, the stability and safety of electric meter boxes, which are important devices for terminal energy metering and control, are increasingly valued. In the long-term operation process, the electric meter box is significantly affected by external environmental conditions (such as temperature, illumination, and wind speed) and its installation structure (such as orientation, ventilation condition, etc.), and the internal electronic components may have performance degradation, error increase, or even failure due to heat accumulation.

[0003] To ensure the temperature stability of the internal components of the electric meter box under different environmental conditions, some existing technical solutions have proposed using fans or thermoelectric cooling elements (TEC) for temperature regulation, and monitoring the internal temperature changes of the box through temperature sensors and driving the corresponding temperature control strategy. This kind of solution has played a positive role in improving the temperature control response ability and prolonging the service life of the device.

[0004] However, the current temperature control system still has optimization space in terms of complex environmental adaptability, sensing data effectiveness, temperature control resource allocation and energy consumption control. Especially in the scenario of coexistence of multi-functional devices, limited power consumption of temperature control components and frequent extreme weather conditions, how to realize more refined perception and control logic has become an important direction to further improve the thermal management efficiency of the electric meter box, therefore the present application proposes an electric meter box temperature control system based on environmental perception. SUMMARY

[0005] The purpose of the present application is to provide an electric meter box temperature control system based on environmental perception to solve the problems mentioned in the background.

[0006] The present application can be implemented by the following technical solution: an electric meter box temperature control system based on environmental perception, comprising a position parameter acquisition module, an environmental response module, a temperature rise monitoring module, a temperature regulation control module and a temperature control distribution module; The position parameter acquisition module is used to obtain the static structural parameter information of the electric meter box in the actual installation scenario, which is used to represent the fixed physical environment it is in. The static structural parameter information includes but is not limited to the orientation angle of the electric meter box, the installation height, the front shielding structure information and the surrounding ventilation condition. The orientation angle of the electric meter box, the installation height, the front shielding structure information and the surrounding ventilation constitute a position parameter set for representing the long-term working environment of the electric meter box.

[0007] The environment response module establishes an environment adaptation model for describing the temperature rise law of the meter box based on the position parameter set provided by the position parameter acquisition module and the real-time operation data (including the temperature in the box, the ambient temperature, the light intensity, and the wind speed) collected in the initial stage of the operation of the meter box.

[0008] The temperature rise monitoring module continuously monitors the temperature change trend of the meter box based on the currently collected external environment information and the established environment adaptation model, and identifies the possible overheating risk.

[0009] The temperature regulation control module is used to dynamically set the working parameters of the temperature control components (such as fans and TEC modules) of the meter box according to the temperature rise trend analysis results provided by the temperature rise monitoring module, complete the formulation and instruction issuance of the temperature control strategy.

[0010] The temperature control distribution module is used to realize the dynamic distribution of limited temperature control resources when there are multiple functional devices in the meter box according to their heat sensitivity levels and temperature control priorities.

[0011] Further technical improvements of the present application are that when the temperature control distribution module dynamically distributes temperature control resources, the target temperature control resources contained in the temperature control control instructions are weighted and distributed based on the heat sensitivity level and temperature control priority indicators of each functional device; when the total amount of temperature control resources is insufficient, the priority indicator values of each functional device are sorted according to the sorting results, and the wind speed adjustment value and the current control value are distributed according to the sorting results, forming a temperature control resource distribution table; including the following steps: A1, setting the temperature control priority of each functional device in the meter box and the heat sensitivity , and obtaining the weighted score value corresponding to each functional device based on and weighted calculation ; A2, the temperature control distribution module determines whether the preset resource constraint condition is met according to the resource demand parameter in the temperature control control instruction generated by the temperature regulation control module at the current time and the current executable capability parameter of the temperature control component; If the preset resource constraint condition cannot be met, it is determined that the current temperature control resource is in a limited state, and the resource dynamic distribution mode is entered; A3, based on the weighted score of each functional device in A1, the weighted proportion is distributed: The total score value } is calculated for all weighted score values = ; For each functional device i, the temperature control resource proportion is calculated as: ; wherein, is the total temperature control resource that can be allocated in a period; If the calculated temperature control resource proportion of a certain functional device is less than the minimum temperature control requirement value of the functional device , the functional device does not directly allocate temperature control resources in the current period, and is registered in the "delayed activation queue"; The temperature control allocation module includes the device in the resource allocation table in the subsequent period according to the queuing order of the functional device in the delayed activation queue and the unused resource balance, and uses the timing activation method for intermittent temperature control.

[0012] Further technical improvements of the application are that when the internal humidity is in the set high humidity state and the current temperature is close to the condensation critical temperature, the temperature adjustment control module limits the upper limit of the cooling rate of the temperature control component, adjusts the wind speed level and the current output value, to avoid the formation of condensation in the interior.

[0013] Further technical improvements of the application are that the temperature adjustment control module is also used for validity judgment on the received external environment temperature, illumination intensity and wind speed information, and when the sensing data is missing or unreadable, a preset temperature control parameter setting process is executed to generate temperature control control instructions or abnormal alarm information for ensuring stable operation of the system.

[0014] Further technical improvements of the application are that the temperature adjustment control module is used for selecting a matching strategy from a preset risk-energy consumption mapping relationship based on the thermal risk level information in the temperature rise trend analysis result and combining the energy consumption cost model of the temperature control component, to control the execution frequency and start mode of the temperature control strategy.

[0015] Further technical improvements of the application are that the temperature adjustment control module identifies the target electric meter box in the cooling lag area during the start-up period of the temperature control component based on the temperature drop rate difference of each area, and when a local air circulation limited area is identified, one or more combinations of the following control responses are executed: adjusting the temperature control air duct order, prolonging the temperature control time length or outputting maintenance prompt information, to improve the local heat accumulation phenomenon and improve the overall air circulation balance.

[0016] Further technical improvements of the application are that the temperature adjustment control module is also used for executing a hierarchical temperature control strategy according to the temperature control priority of each functional device in the electric meter box when the target electric meter box is in an extreme weather state, including: M1, the temperature adjustment control module receives real-time external environment data, and judges whether the current is in an extreme weather state based on a preset judgment rule; M2, the temperature control allocation module is used for retrieving the temperature control priority sorting information of the functional device set in the temperature control allocation module; M3, after judging that the target electric meter box is in an extreme weather state, the temperature regulation control module differentially regulates and controls the temperature control resources according to the temperature control priority order of internal functional devices.

[0017] Compared with the prior art, the present application has the following beneficial effects: The present application realizes intelligent thermal management of the electric meter box under complex operating environment by fusing position parameter modeling, environment response analysis, temperature rise trend monitoring, dynamic temperature control strategy setting and resource allocation management. And through the temperature rise monitoring module, the current temperature slope, temperature rise prediction value and high temperature maintenance time are continuously analyzed to accurately judge whether it is in a temperature rise sensitive state and realize early temperature abnormality warning. On the other hand, under the condition of limited temperature control resources, the present application dynamically allocates wind speed and current control parameters based on the heat sensitivity and priority index of multiple internal functional devices to realize temperature control protection of key components and global energy saving optimization. At the same time, the present system has the ability of extreme climate state recognition and differential control to ensure that in special situations such as high temperature, high humidity and no wind, the temperature control strategy is dynamically switched or non-critical equipment operation is limited to ensure the overall thermal safety of the equipment. BRIEF DESCRIPTION OF DRAWINGS

[0018] In order to facilitate those skilled in the art to understand, the present application will be further described below in conjunction with the drawings.

[0019] Figure 1 The system logic diagram of the present application. DETAILED DESCRIPTION

[0020] In order to further illustrate the technical means and effects adopted by the present application to achieve the predetermined invention purpose, the specific embodiments, structures, features and effects according to the present application are described in detail as follows in conjunction with the drawings and preferred embodiments.

[0021] Example 1 Please refer to Figure 1As shown, the present invention provides a temperature control system for an electric meter box based on environmental perception, including a location parameter acquisition module, an environmental response module, a temperature rise monitoring module, a temperature regulation control module, and a temperature control distribution module; The location parameter acquisition module is used to acquire static structural parameter information of the meter box in the actual installation scenario, which is used to characterize its fixed physical environment. This static structural parameter information includes, but is not limited to, the meter box's orientation angle, installation height, front obstruction structure information, and surrounding ventilation conditions. The orientation angle can be measured by an electronic compass or magnetic sensor. During installation, a one-time sampling is triggered to obtain the azimuth angle (in degrees) of the front surface of the meter box relative to the geographical north direction, and it is stored as an integer angle value. The installation height can be obtained through on-site construction data recording or measurement by a laser ranging module. Specifically, it can be obtained by manually inputting the height of the meter box from the ground (in centimeters) during on-site construction, or by automatically obtaining the installation height through a laser ranging module (vertical direction) under certain conditions, with an accuracy error of no more than ±2cm. The type and location of obstructions can be obtained based on on-site registration or image recognition methods. The ventilation status can be classified according to the installation method of the meter box (such as wall mounting, shaft installation, or independent column). Specifically, by using static images taken during installation, image recognition algorithms (YOLO or edge extraction-based structural recognition methods) are used to identify whether there are physical obstructions (such as walls, columns, steel plates, etc.) within 2 meters in front of the meter box, and the type of obstruction and the duration of obstruction are recorded. Ventilation conditions are configured by the system or set manually, depending on the installation method (wall-mounted, recessed, or column-mounted). The ventilation classification level is preset (e.g., Level A: open on all four sides, Level B: closed at the top but open on the sides, Level C: completely enclosed structure). The above information constitutes a set of location parameters used to characterize the long-term working environment of the meter box; The output of the location parameter acquisition module is a standardized location parameter data structure, which is used by the environmental response module for environmental adaptation modeling. Its technical effect is to enable the subsequent temperature control model to distinguish specific installation environments and avoid the failure of a unified strategy in multiple environments. In this embodiment, the location parameter acquisition module unifies the above four pieces of information into a location parameter vector (θ,h,b,v), which respectively represent the orientation angle θ, height h, obstruction mark b, and ventilation level v.

[0022] The environmental response module establishes an environmental adaptation model to describe the temperature rise pattern of the meter box based on the location parameter set provided by the location parameter acquisition module and the real-time operating data (including box temperature, ambient temperature, light intensity, wind speed, etc.) collected during the initial stage of operation of the meter box. Specifically, the environmental response module first collects real-time environmental information around the meter box using devices such as temperature sensors, light sensors, and wind speed sensors. Simultaneously, it combines this information with attributes such as orientation, obstruction, and ventilation provided by the location parameter acquisition module to construct a temperature response behavior description model that is dependent on the installation environment. The model includes characteristic parameters such as heating delay, maximum heating rate, and heating duration. Furthermore, the output of the environmental response module is an environmental adaptation model, which is continuously corrected during the operating cycle. That is, during the system operation phase, the latest collected data is continuously received, and the model parameters are updated using a sliding time window method (such as the most recent 72 hours) to support the temperature monitoring module in judging the temperature rise trend. Its technical effect is to realize differentiated thermal behavior modeling, so that each meter box has a temperature response model that conforms to its own reality, thereby providing data support for temperature control strategy. In this embodiment, the real-time operating data collected in the initial stage of operation of the corresponding meter box is collected in the following way: During the initial system startup phase (3-5 days before operation), time-series data is synchronously collected using the following sensor modules: External ambient temperature (via temperature and humidity sensor); Internal enclosure temperature (NTC thermistors located in the core area of ​​the meter). Light intensity (via photodiode or digital light sensor); Wind speed (using a miniature impeller anemometer).

[0023] Response feature extraction methods: The system normalizes temperature variation data at different times (such as early morning, noon, and dusk) and calculates the following three core features: 1. Heating start-up delay time The time difference between the start of an increase in external temperature and the increase in internal temperature response; 2. Maximum heating rate In the formula, Indicates the internal temperature of the meter box; It represents the instantaneous rate of temperature change, that is, the slope of temperature change at any given moment; 3. Temperature maintenance time The duration for which the internal temperature remains above the threshold.

[0024] Model construction method: Based on the above characteristics, a temperature response prediction model is constructed using piecewise linear fitting or LSTM short sequence learning models. And continuously update the model parameters with subsequent data.

[0025] Furthermore, to ensure the temperature response model has reliable predictive capabilities throughout the year, the environmental response module introduces a seasonal segmented modeling mechanism and combines it with a long-term data sliding window to achieve dynamic updates across seasons, specifically including the following two levels: 1. Seasonal tag modeling mechanism: In the initial construction phase of the temperature response model, the season of the current time is introduced as an additional input label, and the model is divided into: Spring (March–May), summer (June–August), autumn (September–November), and winter (December–February), or clustered into three categories based on total sunlight and average daily temperature: hot season, transitional season, and cold season; During model training, data from different seasons are used for independent modeling or to switch branch weights within the model, avoiding the problem that a single model cannot cover all features.

[0026] 2. The sliding update window and seasonal integration mechanism: During system operation, the current master model is continuously updated using a sliding time window (such as 72 hours or 168 hours), while retaining historical quarterly models as a reference. When a new season begins: a. If the current model's prediction error continues to exceed the preset error threshold, then switch to loading the model from the same season of the previous year as the initial reference. b. Perform short-term adaptive parameter adjustment based on current real-time data for a smooth transition; c. Model version and parameter update records are stored in the model maintenance library for backtracking and operational judgment.

[0027] The temperature monitoring module continuously monitors the temperature change trend of the meter box based on the currently collected external environmental information and the established environmental adaptation model, and identifies potential overheating risks. Specifically, the temperature rise monitoring module receives the environmental adaptation model output by the environmental response module and obtains parameters such as the current external ambient temperature, light intensity and wind speed from the real-time sensing system. Based on the above inputs, it determines whether it has entered the temperature rise sensitive zone, and calculates indicators such as the current temperature change slope, temperature rise prediction value and maintenance time interval by combining historical temperature rise records. When the temperature rise trend is detected to be approaching the risk boundary, the temperature rise monitoring module will output a temperature risk alarm signal and transmit it to the temperature regulation and control module for strategy adjustment. The technical effect of the temperature rise monitoring module is to identify abnormal temperature change trends in advance, enabling the temperature control system to have real-time response capability and improving the initiative of the meter box thermal management. In this embodiment, the temperature rise monitoring module inputs the following information in real time during operation: 1. Ambient temperature (updated every 5 minutes); 2. Current light intensity; 3. Current wind speed; 4. Temperature response prediction model from the environmental response module ; Furthermore, the judgment logic of the temperature rise monitoring module is as follows: 1. Input the current external environment information as an input variable into the temperature response prediction model. It also outputs a predicted warming trend. ; 2. The current real-time temperature inside the chamber Comparison, if it exists: ; If the internal temperature continues to exceed the set upper temperature limit for 15 minutes, a temperature abnormality alarm will be triggered. Furthermore, in the formula, The value of the heating rate deviation threshold indicates the system's sensitivity to abnormal heating rates. The value is set based on the statistical characteristics of the heating rate prediction error in historical operating data, combined with the sensor sampling accuracy and natural fluctuation amplitude in the actual installation environment.

[0028] Finally, the temperature monitoring module generates a temperature trend analysis result (including temperature change curve, deviation threshold, and expected duration) and sends a control start signal to the temperature regulation and control module.

[0029] The temperature regulation and control module is used to dynamically set the operating parameters of the meter box temperature control components (such as fans, TEC modules, etc.) based on the temperature rise trend analysis results provided by the temperature rise monitoring module, and to complete the formulation of temperature control strategies and the issuance of instructions. Specifically, this temperature regulation and control module combines temperature rise trend data with the performance parameters of the temperature control component to adjust the start-up temperature threshold, running time, adjustment range, and energy-saving mode switching logic in real time. The control commands include parameters such as wind speed level, current adjustment ratio, and execution cycle length, ensuring that the temperature control component controls energy consumption while maintaining cooling effectiveness. Furthermore, the technical effect of this temperature regulation and control module is to achieve adaptive temperature control of the meter box under different environmental conditions, avoid the energy waste or insufficient response caused by traditional fixed strategies, and improve the intelligent operation level of the entire system. In this embodiment, the temperature regulation control module inputs the following information: 1. Alarm signals and prediction timing sent by the temperature rise monitoring module; 2. Status of currently available temperature control components (whether the fan is faulty, and the power status of the TEC component); 3. Temperature control strategy library (preset wind speed, current, and cycle table).

[0030] Furthermore, the strategy adjustment logic of the temperature regulation control module is as follows: 1. If the temperature rise prediction results show that the temperature will exceed the threshold within 10 minutes, then immediately issue an "early cooling" command; 2. The control logic is based on the target temperature. Set the fan speed as the core. : ; TEC component current setting is: ; The rate of increase of the actual current temperature inside the meter box over time; The upper limit of safe current for TEC components; in, and This is a strategy constant that supports parameter tuning and optimization.

[0031] Finally, the temperature regulation control module generates a time-stamped temperature control table (action type, execution time, control quantity) and sends it to the execution controller.

[0032] The temperature control distribution module is used to dynamically allocate limited temperature control resources based on the heat sensitivity level and temperature control priority of multiple functional devices inside the meter box. When the temperature control allocation module dynamically allocates temperature control resources, it performs a weighted allocation of the target temperature control resources contained in the temperature control commands based on the thermal sensitivity level and temperature control priority index of each functional device. When the total amount of temperature control resources is insufficient, it sorts the functional devices according to their priority index values ​​and allocates the fan speed adjustment value and current control value according to the sorting result, forming a temperature control resource allocation table. This includes the following steps: A1. Set the following parameters for each functional device inside the meter box: Temperature control priority The priority level is determined based on the functional level, fault sensitivity, and criticality of the functional components (e.g., the main control board is set to high priority). thermal sensitivity Scoring is based on factors such as the temperature resistance limit of functional components and historical overheat risk scores (e.g., communication modules with low temperature resistance have high thermal sensitivity). Weighted score values ​​for each functional component In the formula, and These are the weighting coefficients for the corresponding terms, which are obtained through experiments or experience; A2. The temperature control allocation module determines whether the resource constraints are met based on the resource requirement parameters in the temperature control command generated by the temperature regulation and control module at the current moment, combined with the current executable capability parameters of the temperature control component. This includes the following two aspects: a1. Wind speed resource assessment: a11: Temperature control commands include target wind speed levels. ; a12: The system obtains the maximum supported wind speed level of the current fan component. ; a13: If satisfied > If so, then wind speed resources are considered limited; a2. Current resource assessment: a21: The temperature control command includes a target current value. ; a22: The system obtains the maximum available current capacity of the current TEC component. ; a23: The total current required by the control strategy (based on the cumulative value after allocation to each functional device). > If so, then the current resource is considered limited; If any of the above resource dimensions cannot meet the requirements of the target control strategy, the current temperature control resources are determined to be in a limited state, and the system enters the dynamic resource allocation mode. A3. Weighted scores based on the functional components in A1 Distribute according to weighted proportions: For all weighted score values ​​{ Calculate the total score = ; For each functional device i, calculate its temperature control resource ratio. for: In the formula, Total temperature control resources available for allocation within the cycle; If the calculated temperature control resource ratio of a certain functional device If the temperature requirement is less than the minimum temperature control requirement of the functional device, the functional device will not be directly allocated temperature control resources in this cycle, but will be registered in the "delayed activation queue". The temperature control allocation module, based on the queuing order of functional devices in the delayed activation queue and the amount of unused resources, includes the device in the resource allocation table in fixed rounds in subsequent cycles, and uses a timed activation method for intermittent temperature control to ensure that all devices are still covered under resource constraints. The final "resource allocation table" includes: functional device identifier, specific values ​​of allocated resources (wind speed level, current output ratio), control mode (continuous control or timed activation) and its corresponding execution time period.

[0033] Specifically, the temperature control distribution module collects temperature data and operating status information of the main electronic components (such as circuit breaker control module, communication module, energy consumption chip, etc.) inside the meter box, and sets the temperature control priority of each functional device according to the historical temperature rise trend and the functional level of the functional device; when the temperature control resources are insufficient, the temperature control distribution module prioritizes the cooling needs of high-risk or high heat-sensitive functional devices, while other functional devices maintain thermal balance through a rotation cooling strategy. The technical effect of this temperature control distribution module is to achieve the orderly allocation of temperature control resources, avoid the risk of thermal runaway of key functional components due to resource dispersion or indiscriminate cooling, and thus ensure the overall safety and stability of the system operation.

[0034] In this embodiment, the solution is as follows: 1. Functional Component Information Acquisition: The temperature control distribution module identifies the core functional components inside the meter box, such as the metering main board, circuit breaker mechanism, communication module, and power supply module. Furthermore, each functional device is equipped with a temperature sensing point (such as an NTC or digital temperature chip), which collects data once every minute; 2. Priority setting basis: The temperature control distribution module performs weighted calculations based on the functional component category, operating temperature tolerance range, and historical error frequency to obtain the score of the corresponding functional component. 3. Allocation control logic: Set a total budget for temperature control resources (such as airflow and current); Resources are allocated proportionally based on priority level. If temperature control resources are insufficient, an interval switching adjustment mechanism is adopted to ensure that priority objects are continuously controlled; 4. Result Output: A "temperature control resource allocation table" is generated once per cycle, which is used by the controller to perform resource adjustments.

[0035] Example 2 Compared to Example 1, when the internal humidity is at a set high humidity level and the current temperature is close to the condensation critical temperature, the temperature regulation control module limits the upper limit of the cooling rate of the temperature control component, adjusts the fan speed level and current output value to avoid internal condensation, including: B1. Obtain humidity status parameters: The humidity sensor unit installed in the meter box collects the current relative humidity data, which is combined with the real-time temperature inside the box obtained by the internal temperature sensor as the basic parameter for condensation risk assessment. B2. The system inputs real-time humidity and temperature data into the preset condensation risk judgment model. This model is based on experimental calibration to form a temperature and humidity critical matching table, which is used to determine "under the current humidity conditions, if the temperature inside the chamber is below how much, there is a risk of condensation". If the current temperature is less than the critical temperature difference (e.g., 2°C) than the set safety threshold, the system determines that the current state is a "high condensation risk state". B3. When the current condition is determined to be "high condensation risk state", the system will limit the temperature control rate in the original temperature regulation strategy, specifically as follows: b31. Limit the maximum wind speed of the fan assembly to prevent strong winds and strong cooling. b32. Limit the upper limit of cooling current of TEC components to reduce heat extraction speed; b33. Dynamically insert a "cooling rate limit parameter" into the temperature control command to set the maximum allowable temperature drop per unit time (e.g., a maximum drop of 0.5°C per minute). B4. When real-time monitoring data shows that the temperature and humidity inside the chamber have returned to a safe range (e.g., the temperature is more than 2°C above the critical value, or the humidity drops below the set threshold), the system will remove the rate limit and restore the original temperature control command execution logic.

[0036] Example 3 Compared to Embodiments 1 and 2, the temperature monitoring module in Embodiment 3 is also used to determine the validity of the received external ambient temperature, light intensity, and wind speed information. When the sensing data is missing or unreadable, it executes a preset temperature control parameter setting process to generate temperature control commands or abnormal alarm information to ensure stable system operation. Specifically, the validity determination of the external ambient temperature, light intensity, and wind speed information includes the following steps: Z1. Data Reading Integrity Verification: In each acquisition cycle, the success rate of reading data from temperature, light, and wind speed sensors is judged. If any data source fails to acquire data or has missing data fields in two consecutive cycles, the sensing data is considered invalid. Z2. Data parsability verification: The received data is parsed numerically. If the data format cannot be parsed (e.g., the value is empty, the encoding is illegal, or the unit conversion is impossible), then the current perceived data is considered unreadable. Z3. Parameter value range verification: Based on the working range of the corresponding sensor, verify whether the collected data falls within its reasonable physical range (such as temperature -40℃~85℃, wind speed 0~30m / s, etc.). If it does not meet the requirements, the current data is considered abnormal. Z4. Abnormal response mechanism trigger: When any sensing data is judged to be faulty or abnormal in the above verification, the temperature monitoring module will execute the preset temperature control parameter setting process, including: enabling the default temperature adjustment strategy parameters (such as fixed start-up temperature threshold and wind speed level), disabling the trend judgment model involved by the fault signal source, and sending a temperature control command marked as "degraded operation" to the temperature adjustment control module. Z5. Alarm Information Output: Simultaneously generate structured alarm information containing abnormal items, abnormal types, affected functional modules, and response strategies, and send it to the maintenance terminal or user interface through the system alarm module.

[0037] Example 4 Compared to Embodiments 1, 2, or 3, the temperature regulation control module in Embodiment 4 is used to select a matching strategy from a preset risk-energy consumption mapping relationship based on the thermal risk level information in the temperature rise trend analysis results and the energy consumption cost model of the temperature control component. This controls the execution frequency and activation mode of the temperature control strategy to optimize energy consumption performance while ensuring cooling response capability. Specifically, it includes the following technical steps: Y1. Calculation of thermal risk level: When outputting the temperature rise monitoring module, the current thermal risk level information is also included. The thermal risk level is calculated based on the following factors: Current temperature change slope; The degree of deviation of the predicted temperature value from the upper limit of the temperature range; The expected duration of the high temperatures and the extent of deviation from historical averages; Based on the above three factors, the risk level value K∈[0,1] is calculated by normalization weighting and is classified into three levels: "low risk", "medium risk" and "high risk". Y2, Energy Consumption Cost Modeling for Temperature Control Behavior: The temperature regulation and control module maintains a set of operating cost tables for temperature control components, which characterize the average unit energy consumption of various temperature control strategies, as shown in this embodiment: Fan running at low speed: 1 unit power consumption; High-speed fan operation: 2 units of power consumption; TEC components operate at low current: 3 units of power consumption; TEC High Efficiency Mode: 5 units of power consumption; When the temperature regulation and control module is working, the above costs are used as cost parameters for the selection of control strategies; Y3. Construct a recommended mapping table between thermal risk levels and temperature control strategies. In this embodiment, it is shown in Table 1 below: Table 1 The temperature regulation and control module selects the minimum cost strategy from the set of allowed strategies as the content of the current control command based on the current thermal risk level. If the previous strategy is the same as the current recommended strategy and the start-stop interval constraint is not exceeded, the running state will be maintained to avoid unnecessary frequent switching. Y4. After completing the matching of thermal risk level and cost, the temperature regulation and control module generates corresponding temperature control instructions based on the capability parameters of the temperature control components, including fields such as start / stop signal, wind speed level, current ratio and execution sequence, and marks the energy-saving level of the current strategy.

[0038] Example 5 Compared to Example 4, the temperature regulation control module in Example 5, during the activation of the temperature control component, identifies areas with lagging cooling within the target meter box based on the differences in temperature drop rates in different areas. Upon identifying areas with restricted local airflow, it executes one or more combinations of the following control responses: adjusting the temperature control duct sequence, extending the temperature control duration, or outputting maintenance prompts, to improve local heat accumulation and enhance overall airflow uniformity. Specifically, these include: H1. Temperature distribution monitoring: During the operation of the temperature control component, the temperature monitoring module obtains the temperature change sequence of each area through temperature sensors deployed near different functional devices in the meter box. H2. Regional Response Analysis: Normalize the temperature changes of each region before and after the temperature control component is activated, calculate the rate of temperature drop per unit time, and mark the region as a "cooling lag zone" if the difference between the rate of temperature drop of a certain region and the rate of temperature drop of other regions is greater than the preset rate threshold. H3. Smoothness judgment: The basis for judging whether there is an area with poor air circulation is: the temperature drop rate in the area is lower than the set proportion (e.g., 50%) of the global average rate, and this continues for multiple sampling cycles. H4. Response measures: If there are areas with the above-mentioned cooling lag, the temperature regulation control module will adjust the control sequence of the temperature control air duct according to the hot spot location, appropriately extend the temperature control duration, and send a regional wind speed enhancement command to the temperature control distribution module. H5. When the same area is identified as a region with lagging cooling multiple times in a row, the system will generate a preliminary judgment result of duct blockage or poor airflow, and output a maintenance prompt signal for reference by the maintenance system or management platform.

[0039] Example 6 Compared to Example 5, the temperature regulation control module in Example 6 is further used to implement a graded temperature control strategy based on the temperature control priority of each functional device inside the meter box when the target meter box is identified as being in extreme weather conditions, thereby improving the system's operational stability in high-risk environments. The specific implementation methods include: M1, Extreme Weather Condition Assessment: The temperature regulation control module receives real-time external environmental data from sensors and determines whether the current weather conditions are extreme based on preset judgment rules. In this embodiment, the real-time external environmental data includes ambient temperature, light intensity, air humidity, and wind speed information. The judgment rules include: m11. The duration for which the ambient temperature continuously exceeds the first high temperature threshold (e.g., 40°C) exceeds the set time window (e.g., 1 hour). m12, Light intensity exceeds the set upper limit threshold (e.g., 80000 lux). m13, relative humidity exceeding 90%, and external wind speed below 1.0 m / s for more than 30 minutes; When multiple of the above indicators are simultaneously under unfavorable conditions, the system identifies it as an extreme weather condition. M2, Priority Acquisition of Functional Devices: The temperature control priority sorting information of the functional components set in the temperature control allocation module is retrieved. Each component is assigned a clear priority label based on its thermal sensitivity, structural location, electrical function importance, and other factors. M3, Differentiated Temperature Control Strategy Implementation: After determining that the target meter box is in extreme weather conditions, the temperature regulation control module performs differentiated regulation of temperature control resources according to the temperature control priority order of internal functional components, specifically including: 1. For functional devices with temperature control priority in the top 25%, the system prioritizes allocating the largest available temperature control resources, including: Set the fan speed to the highest available level currently supported by the fan. The TEC component current is set to the upper limit of its current safe operating range; 2. For functional devices with temperature control priority in the middle range (26%-75%): Temperature control cycle intervals are shortened to 50%-70% of standard execution cycles; The temperature control trigger threshold is lowered (e.g., reduced by 2-3°C compared to normal operating conditions) to enable earlier response; 3. For functional devices whose temperature control priority is in the bottom 25% range: The warm trigger action is delayed by 1-2 standard cycles; The temperature control fan speed is set to the minimum effective level currently allowed by the system; A redundancy mechanism is retained to compensate for the impact once the core components have stabilized.

[0040] The above strategies are recorded in a structured temperature control strategy table during execution, which is then called by the system scheduling module.

[0041] The above formulas are all dimensionless calculations. The formulas are derived from software simulations based on a large amount of collected data to obtain the most recent real-world results. The preset parameters and thresholds in the formulas are set by those skilled in the art according to the actual situation.

[0042] The temperature monitoring module is also used to determine the validity of the received external ambient temperature, light intensity, and wind speed information, and to execute a preset temperature control parameter setting process when the sensing data is missing or unreadable, generating temperature control commands or abnormal alarm information to ensure stable system operation. Specifically, the validity determination of external ambient temperature, light intensity, and wind speed information includes the following steps: Z1. Data Reading Integrity Verification: In each acquisition cycle, the success rate of reading data from temperature, light, and wind speed sensors is judged. If any data source fails to acquire data or has missing data fields in two consecutive cycles, the sensing data is considered invalid. Z2. Data parsability verification: The received data is parsed numerically. If the data format cannot be parsed (e.g., the value is empty, the encoding is illegal, or the unit conversion is impossible), then the current perceived data is considered unreadable. Z3. Parameter value range verification: Based on the working range of the corresponding sensor, verify whether the collected data falls within its reasonable physical range (such as temperature -40℃~85℃, wind speed 0~30 m / s, etc.). If it does not meet the requirements, the current data is considered abnormal. Z4. Abnormal response mechanism trigger: When any sensing data is judged to be invalid or abnormal in the above verification, the temperature monitoring module will execute the preset temperature control parameter setting process, including: enabling the default temperature adjustment strategy parameters (such as fixed start-up temperature threshold and wind speed level), disabling the trend judgment model involved by the failure signal source, and sending a temperature control command marked as "degraded operation" to the temperature adjustment control module. Z5. Alarm Information Output: Simultaneously generate structured alarm information containing abnormal items, abnormal types, affected functional modules, and response strategies, and send it to the maintenance terminal or user interface through the system alarm module.

[0043] The above description is merely a preferred embodiment of the present invention and is not intended to limit the present invention in any way. Although the present invention has been disclosed above with reference to preferred embodiments, it is not intended to limit the present invention. Any person skilled in the art can make some modifications or alterations to the above-disclosed technical content to create equivalent embodiments without departing from the scope of the present invention. Any simple modifications, equivalent changes and alterations made to the above embodiments based on the technical essence of the present invention without departing from the scope of the present invention shall still fall within the scope of the present invention.

Claims

1. A temperature control system for an electric meter box based on environmental perception, characterized in that, include: The location parameter acquisition module is used to acquire static structural parameter information that characterizes the actual fixed installation scenario of the meter box after it is installed, and to construct a location parameter set that characterizes the long-term operating environment of the target meter box. The environmental response module, based on the location parameter set and the real-time operating data collected during the data acquisition phase required to complete the initialization of the environmental adaptation model, establishes an environmental adaptation model corresponding to the temperature change pattern of the meter box. The temperature rise monitoring module receives the environmental adaptation model and, based on the currently collected external ambient temperature, light intensity, and wind speed information, determines whether the target meter box has entered the temperature rise sensitive zone and outputs the temperature rise trend analysis results. The temperature regulation and control module is used to receive the temperature rise trend analysis results, and in combination with the temperature control capability parameters of the preset temperature control components in the meter box, select a temperature control strategy from the preset strategy library and generate a temperature control command. The temperature control allocation module dynamically allocates temperature control resources when they are limited, based on temperature control commands and the temperature control priority and thermal sensitivity of multiple functional devices inside the target meter box.

2. The meter box temperature control system based on environmental perception according to claim 1, characterized in that, The temperature monitoring module determines whether the target meter box has entered the temperature-sensitive zone through the following steps: Collect current ambient temperature, light intensity, and wind speed information, and combine them with the environmental adaptation model to calculate the temperature change slope, predicted temperature rise, and expected high temperature duration of the target meter box under the current environmental conditions. The external ambient temperature, light intensity, and wind speed information are compared with the corresponding preset temperature rise rate deviation threshold, temperature prediction upper limit threshold, and high temperature duration upper limit threshold, respectively. When any indicator exceeds the corresponding threshold, it is determined that the target meter box has entered the temperature rise sensitive zone, and a temperature rise trend analysis result containing the above comparison results is generated.

3. The meter box temperature control system based on environmental perception according to claim 1, characterized in that, When the temperature control allocation module dynamically allocates temperature control resources, it performs weighted allocation of the target temperature control resources contained in the temperature control command based on the thermal sensitivity level and temperature control priority index of each functional device. When the total amount of temperature control resources is insufficient, the components are sorted according to their priority index values, and the fan speed adjustment value and current control value are allocated according to the sorting results to form a temperature control resource allocation table.

4. The meter box temperature control system based on environmental perception according to claim 3, characterized in that, The method for dynamically allocating temperature control resources in the temperature control allocation module includes: A1. Set temperature control priorities for each functional device inside the meter box. and heat sensitivity and based on and Weighted calculations are used to obtain the weighted score values ​​for each functional device. ; A2. The temperature control allocation module determines whether the preset resource constraints are met based on the resource requirement parameters in the temperature control command generated by the temperature regulation and control module at the current moment, combined with the current executable capability parameters of the temperature control component. If the preset resource constraints cannot be met, the current temperature control resources are determined to be in a limited state, and the system enters the dynamic resource allocation mode. A3. Weighted scores based on the functional components in A1 Distribute according to weighted proportions: For all weighted score values ​​{ Calculate the total score = ; For each functional device i, calculate its temperature control resource allocation. for: In the formula, Total temperature control resources available for allocation within the cycle; If the calculated temperature control resource ratio of a certain functional device If the temperature requirement is less than the minimum temperature control requirement of the functional device, then the functional device will not be directly allocated temperature control resources in this cycle and will be registered in the "delayed activation queue". The temperature control allocation module, based on the queuing order of functional devices in the delayed activation queue and the amount of unused resources, includes the device in the resource allocation table in fixed rounds in subsequent cycles, and uses a timed activation method for intermittent temperature control.

5. A temperature control system for an electric meter box based on environmental perception according to claim 2, characterized in that, The temperature monitoring module determines the validity of the received external ambient temperature, light intensity, and wind speed information. When the sensing data is missing or unreadable, it executes a preset temperature control parameter setting process to generate temperature control commands or abnormal alarm information to ensure the stable operation of the system.

6. A temperature control system for an electric meter box based on environmental perception according to claim 1, characterized in that, The temperature regulation and control module is used to select a matching strategy from a preset risk-energy consumption mapping relationship based on the thermal risk level information in the temperature rise trend analysis results and the energy consumption cost model of the temperature control component, and to control the execution frequency and start mode of the temperature control strategy.

7. A temperature control system for an electric meter box based on environmental perception according to claim 1, characterized in that, During the activation of the temperature control component, the temperature regulation control module identifies areas with lagging cooling in the target meter box based on the differences in the rate of temperature decrease in each area. When a local area with restricted air circulation is identified, it executes one or more control response combinations, such as adjusting the temperature control duct sequence, extending the temperature control duration, or outputting maintenance prompt information.

8. A temperature control system for an electric meter box based on environmental perception according to claim 1, characterized in that, The temperature regulation control module is also used to execute a graded temperature control strategy based on the temperature control priority of each functional component inside the meter box when the target meter box is identified as being in extreme weather conditions. This strategy includes: M1, the temperature regulation and control module receives real-time external environmental data and determines whether the current weather conditions are extreme based on preset judgment rules; M2, retrieves the temperature control priority sorting information of the functional devices set in the temperature control allocation module; M3. After determining that the target meter box is in extreme weather conditions, the temperature regulation and control module performs differentiated regulation of temperature control resources according to the temperature control priority order of internal functional components.

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