A comprehensive protection method and device for transformer oil gas detection equipment

Abstract

The application discloses a comprehensive protection method and device for a transformer oil gas detection device, and relates to the field of device protection. In the method, the refrigeration or heating power of a thermoelectric refrigerator is adjusted according to a first humidity value and a first temperature value of a preset target position to obtain first operation data, and the voltage and current parameters of an electro-osmosis unit are adjusted to obtain a second voltage value and a second current value; target operation data, a target voltage value and a target current value are obtained according to a second humidity value and a second temperature value of a current environment, and an adjustment direction and an adjustment range are determined according to a temperature difference value and a humidity difference value; and final operation data, a final voltage value and a final current value are determined according to the adjustment direction and the adjustment range. The technical scheme provided in the application achieves the effects of improving the device protection performance, optimizing the operation efficiency and prolonging the service life.

Description

Technical Field

[0001] This application relates to the technical field of equipment protection, specifically to a comprehensive protection method and device for a gas detection device in transformer oil. Background Technology

[0002] With the increasing complexity of power systems and the growing demand for high reliability, higher requirements are being placed on the performance of gas detection equipment in transformer oil. To ensure the stable operation of these devices in various environments and to prevent measurement errors or equipment damage caused by environmental factors, comprehensive protection technologies are particularly important.

[0003] Currently, common methods for protecting transformer oil gas detection equipment include using temperature and humidity sensors to monitor the environmental conditions around the equipment and adjusting the temperature through simple heating or cooling devices. However, these methods mostly rely on single physical isolation or simple temperature control, lacking comprehensive consideration of multiple environmental factors (such as humidity and temperature), and thus cannot achieve accurate and effective protection.

[0004] Therefore, there is an urgent need for a comprehensive protection method that can adapt to different environmental conditions in a full and dynamic manner to ensure that the gas detection equipment in transformer oil is always in the best working condition. Summary of the Invention

[0005] This application provides a comprehensive protection method and device for a gas detection device in transformer oil, which achieves effective protection of the device by collecting key data and combining real-time adjustment and long-term optimization strategies.

[0006] The first aspect of this application provides a comprehensive protection method for a gas detection device in transformer oil, applied to a protection platform, the method comprising: The system collects the first humidity and first temperature values ​​at the preset target location of the gas detection device in transformer oil, as well as the first voltage and first current values ​​of the electroosmosis unit, and also collects the second humidity and second temperature values ​​of the current environment. Based on the first humidity value and the first temperature value, the cooling or heating power of the thermoelectric cooler is adjusted firstly using a PID control algorithm to obtain the first operating data of the thermoelectric cooler. Based on the first humidity value, the first temperature value, and the first operating data, the voltage and current parameters of the electroosmosis unit are adjusted secondly to obtain the second voltage value and the second current value. The second humidity value and the second temperature value are input into a preset model to obtain target operating data, target voltage value and target current value. The first difference between the first humidity value and the second humidity value and the second difference between the first temperature value and the second temperature value are calculated. The adjustment direction and adjustment range are determined based on the first difference and the second difference. The second operating data is determined based on the target operating data, the first operating data, the adjustment direction, and the adjustment range. The third voltage value and the third current value are determined based on the target voltage value, the target current value, the second voltage value, the second current value, the adjustment direction, and the adjustment range. The thermoelectric cooler is adjusted according to the second operating data, and the electroosmosis unit is adjusted according to the third voltage value and the third current value.

[0007] Optionally, the step of adjusting the cooling or heating power of the thermoelectric cooler using a PID control algorithm based on the first humidity value and the first temperature value to obtain the first operating data of the thermoelectric cooler includes: Calculate the minimum temperature deviation between the first temperature value and the preset target temperature range, and calculate the required cooling or heating power based on the minimum temperature deviation using a PID control algorithm; The direction and magnitude of the current in the thermoelectric cooler are adjusted according to the cooling or heating power to adjust the first temperature value to the target temperature range; Record the first operating data of the thermoelectric cooler during the first adjustment process. The first operating data includes the actual cooling or heating power of the thermoelectric cooler, the direction and magnitude of the current, and the trend of the first temperature value.

[0008] Optionally, the step of making a second adjustment to the voltage and current parameters of the electroosmosis unit based on the first humidity value, the first temperature value, and the first operating data to obtain a second voltage value and a second current value includes: The minimum humidity deviation between the first humidity value and the preset target humidity range is calculated. Based on the minimum temperature deviation, the minimum humidity deviation, and the first operating data, the voltage and current parameters of the electroosmosis unit are calculated by the simulation module to obtain the second voltage value and the second current value, so that the operating efficiency of the electroosmosis unit is greater than or equal to the first threshold and the first humidity value is adjusted to the preset target humidity range.

[0009] Optionally, the step of inputting the second humidity value and the second temperature value into a preset model to obtain the target operating data, target voltage value, and target current value includes: The preset model is obtained by training historical data using machine learning algorithms to establish a mapping relationship between environmental parameters and equipment operating parameters; The second humidity value and the second temperature value are input into the preset model to obtain the optimal operating parameters of the thermoelectric cooler and the electroosmosis unit under the current environment. The optimal operating parameters include target operating data, target voltage value and target current value. The target operating data includes the target cooling or heating power of the thermoelectric cooler. The target voltage value and target current value are parameters for the electroosmosis unit to achieve optimal operating efficiency under the current environmental conditions.

[0010] Optionally, determining the adjustment direction and adjustment range based on the first difference and the second difference includes: Determine whether the first difference and / or the second difference is greater than the second threshold; When the first difference and / or the second difference is greater than the second threshold, the adjustment direction is determined to be to increase the weight of the first operating data, the second voltage value and the second current value, and to decrease the weight of the target operating data, the target voltage value and the target current value; When both the first difference and the second difference are less than or equal to the second threshold, the adjustment direction is determined to be to increase the weight of the target operating data, the target voltage value, and the target current value, and to decrease the weight of the first operating data, the second voltage value, and the second current value. The adjustment range of the weight is determined based on the third difference between the maximum value of the first difference and the second difference and the second threshold.

[0011] Optionally, determining the adjustment range of the weight based on the third difference between the maximum value of the first difference and the second difference and the second threshold includes: The product of the third difference and the preset adjustment range coefficient is calculated as the first adjustment range. The second adjustment range is determined according to the current environment. The first adjustment range and the second adjustment range are added together to obtain the adjustment range.

[0012] Optionally, determining the second operating data based on the target operating data, the first operating data, the adjustment direction, and the adjustment range includes: The first weight of the first running data and the second weight of the target running data are determined based on the adjustment direction and the adjustment magnitude. Calculate the first product of the first running data and the first weight, and calculate the second product of the target running data and the second weight. Calculate the sum of the first product and the second product to determine the second running data.

[0013] A second aspect of this application provides a comprehensive protection system for a gas detection device in transformer oil, comprising a data acquisition module, an adjustment module, a calculation module, and an execution module, wherein: The acquisition module is configured to acquire the first humidity value and the first temperature value at the preset target location of the gas detection device in transformer oil, as well as the first voltage value and the first current value of the electroosmosis unit, and to acquire the second humidity value and the second temperature value of the current environment. The adjustment module is configured to perform a first adjustment on the cooling or heating power of the thermoelectric cooler based on the first humidity value and the first temperature value using a PID control algorithm to obtain the first operating data of the thermoelectric cooler, and to perform a second adjustment on the voltage and current parameters of the electroosmosis unit based on the first humidity value, the first temperature value, and the first operating data to obtain a second voltage value and a second current value. The calculation module is configured to input the second humidity value and the second temperature value into a preset model to obtain target operating data, target voltage value and target current value, calculate the first difference between the first humidity value and the second humidity value, and the second difference between the first temperature value and the second temperature value, and determine the adjustment direction and adjustment range based on the first difference and the second difference; The execution module is configured to determine second operating data based on the target operating data, the first operating data, the adjustment direction, and the adjustment range; determine a third voltage value and a third current value based on the target voltage value, the target current value, the second voltage value, the second current value, the adjustment direction, and the adjustment range; adjust the thermoelectric cooler according to the second operating data; and adjust the electroosmosis unit according to the third voltage value and the third current value.

[0014] A third aspect of this application provides an electronic device 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 foregoing.

[0015] A fourth aspect of this application provides a computer-readable storage medium storing instructions that, when executed, perform the method described in any of the preceding descriptions.

[0016] In summary, one or more technical solutions provided in the embodiments of this application have at least the following technical effects or advantages: 1. By collecting humidity and temperature data from both the internal and external environments of the equipment, and combining this with the voltage and current parameters of the electroosmosis unit, the system can monitor changes in the equipment's operating environment in real time. Utilizing PID control algorithms and preset models, the system can quickly respond to environmental changes, ensuring stable operation of the equipment under various environmental conditions (such as high humidity and temperature fluctuations). 2. By combining immediate adjustments (first and second adjustments) and long-term optimization (obtaining target operating data through a preset model), the system can dynamically balance the immediate needs of the equipment with long-term performance optimization. By calculating the difference between humidity and temperature (first and second differences) and determining the adjustment direction and magnitude based on these differences, the system can flexibly adjust the weights to ensure that immediate needs are met first when the environment changes drastically, while returning to the long-term optimization goal when the environment is relatively stable. 3. By dynamically adjusting the operating parameters of the thermoelectric cooler and the electroosmosis unit, energy consumption can be optimized while ensuring the protective effect of the equipment. For example, when the ambient humidity and temperature change little, the system can reduce the cooling / heating power and the voltage / current of the electroosmosis unit to reduce energy consumption. The preset model is based on historical data and machine learning algorithms and can predict the optimal operating parameters of the equipment under different environmental conditions, further improving the operating efficiency of the system. 4. By precisely controlling the internal temperature and humidity environment of the equipment, more stable conditions can be provided for gas detection in transformer oil, thereby improving detection accuracy and data reliability. For example, in a high humidity environment, by adjusting the parameters of the electroosmosis unit in real time, it is possible to effectively prevent moisture from entering the equipment and avoid detection errors caused by environmental factors. 5. By effectively protecting the equipment from environmental factors such as humidity, temperature fluctuations, and salt spray, the service life of gas detection equipment in transformer oil can be significantly extended. For example, in coastal areas, equipment often faces the dual challenges of high humidity and salt spray corrosion; this method can reduce environmental damage to the equipment through immediate adjustments and long-term optimization. Attached Figure Description

[0017] Figure 1 This is a flowchart illustrating the comprehensive protection method for the gas detection equipment in transformer oil disclosed in the embodiments of this application; Figure 2 This is a schematic diagram of the integrated protection system of the transformer oil gas detection equipment disclosed in the embodiments of this application; Figure 3 This is a schematic diagram of the structure of an electronic device disclosed in an embodiment of this application.

[0018] Explanation of reference numerals in the attached figures: 201, acquisition module; 202, adjustment module; 203, calculation module; 204, execution module; 301, processor; 302, communication bus; 303, user interface; 304, network interface; 305, memory. Detailed Implementation

[0019] 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.

[0020] 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.

[0021] 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.

[0022] This embodiment discloses a comprehensive protection method for a gas detection device in transformer oil, applied to a protection platform. Figure 1 This is a flowchart illustrating the comprehensive protection method for the gas detection equipment in transformer oil disclosed in the embodiments of this application, as shown below. Figure 1 As shown, the method includes the following steps: S101. Collect the first humidity value and the first temperature value of the preset target location of the gas detection device in transformer oil, as well as the first voltage value and the first current value of the electroosmosis unit, and collect the second humidity value and the second temperature value of the current environment. S102. Based on the first humidity value and the first temperature value, the cooling or heating power of the thermoelectric cooler is adjusted firstly using a PID control algorithm to obtain the first operating data of the thermoelectric cooler. Based on the first humidity value, the first temperature value, and the first operating data, the voltage and current parameters of the electroosmosis unit are adjusted secondly to obtain the second voltage value and the second current value. S103. Input the second humidity value and the second temperature value into the preset model to obtain the target operating data, target voltage value and target current value, calculate the first difference between the first humidity value and the second humidity value, and the second difference between the first temperature value and the second temperature value, and determine the adjustment direction and adjustment range based on the first difference and the second difference; S104. Determine second operating data based on the target operating data, the first operating data, the adjustment direction, and the adjustment range; determine third voltage and third current values ​​based on the target voltage value, the target current value, the second voltage value, the second current value, the adjustment direction, and the adjustment range; adjust the thermoelectric cooler according to the second operating data; and adjust the electroosmosis unit according to the third voltage and third current values.

[0023] The system collects the first humidity and first temperature values ​​at a preset target location from a gas detection device in transformer oil, as well as the first voltage and first current values ​​from the electroosmosis unit. The preset target location can be multiple different locations of the detection device, and the first humidity and temperature values ​​can be the average of these locations. Simultaneously, it collects the second humidity and second temperature values ​​of the current environment. This data is used for subsequent real-time adjustments and long-term optimization. Based on the collected first humidity and first temperature values, a PID control algorithm is used to calculate the required cooling or heating power. The PID algorithm adjusts the control quantity through a linear combination of proportional (P), integral (I), and derivative (D) components. Based on the calculation results, the current direction and magnitude of the thermoelectric cooler are adjusted to bring the first temperature value within the preset target temperature range. The operating data of the thermoelectric cooler during the adjustment process is recorded, including the actual cooling or heating power, current direction and magnitude, and the trend of the first temperature value. Combining the first humidity, first temperature, and the first operating data of the thermoelectric cooler, the simulation module calculates the second voltage and second current values ​​of the electroosmosis unit. Adjust the voltage and current parameters of the electroosmosis unit to ensure its operating efficiency is greater than or equal to a first threshold, and adjust the first humidity value to within a preset target humidity range. Input the second humidity value and the second temperature value into a preset model, which is built based on historical data and machine learning algorithms and can predict the optimal operating parameters of the thermoelectric cooler and the electroosmosis unit under current environmental conditions. The optimal operating parameters include target operating data (target cooling or heating power of the thermoelectric cooler), target voltage value, and target current value. Calculate the first difference between the first humidity value and the second humidity value, and the second difference between the first temperature value and the second temperature value. Determine the adjustment direction and adjustment magnitude based on the magnitude of the first and second differences. When the first or second difference is greater than the preset second threshold, the adjustment direction tends to increase the weight of the first operating data, the second voltage value, and the second current value; when both the first and second differences are less than or equal to the second threshold, the adjustment direction tends to increase the weight of the target operating data, the target voltage value, and the target current value. The adjustment magnitude is dynamically determined based on the third difference between the maximum value of the first and second differences and the second threshold. The adjustment range is directly proportional to the third difference, and the proportionality coefficient can be dynamically adjusted based on the equipment's historical operating data and environmental change trends. The second operating data of the thermoelectric cooler is determined based on the target operating data, the first operating data, the adjustment direction, and the adjustment range. The third voltage and third current values ​​of the electroosmosis unit are determined based on the target voltage value, the target current value, the second voltage value, the second current value, the adjustment direction, and the adjustment range. The cooling or heating power of the thermoelectric cooler is adjusted according to the second operating data. The voltage and current parameters of the electroosmosis unit are adjusted according to the third voltage and third current values.

[0024] By combining real-time adjustments with long-term optimization, the equipment can maintain stable operation under various environmental conditions, effectively coping with complex environments such as high humidity and temperature fluctuations. The system can dynamically adjust weights and operating parameters according to environmental changes, balancing immediate needs with long-term optimization goals. Optimizing the operating parameters of the thermoelectric cooler and electroosmosis unit reduces energy consumption and improves equipment operating efficiency. Precise control of the internal temperature and humidity environment provides stable conditions for gas detection, improving detection accuracy. Combined with a cloud computing platform and remote monitoring capabilities, the system monitors equipment status in real time, providing timely warnings and notifying maintenance personnel. Effective protection reduces environmental damage to the equipment, extending its service life.

[0025] Optionally, the step of adjusting the cooling or heating power of the thermoelectric cooler using a PID control algorithm based on the first humidity value and the first temperature value to obtain the first operating data of the thermoelectric cooler includes: Calculate the minimum temperature deviation between the first temperature value and the preset target temperature range, and calculate the required cooling or heating power based on the minimum temperature deviation using a PID control algorithm; The direction and magnitude of the current in the thermoelectric cooler are adjusted according to the cooling or heating power to adjust the first temperature value to the target temperature range; Record the first operating data of the thermoelectric cooler during the first adjustment process. The first operating data includes the actual cooling or heating power of the thermoelectric cooler, the direction and magnitude of the current, and the trend of the first temperature value.

[0026] Calculate the minimum temperature deviation (ΔT) between the first temperature value and the preset target temperature range. The target temperature range is usually a set interval, such as [20℃, 21℃]. The minimum temperature deviation (ΔT) measures the difference between the current temperature and the target temperature and is the basic input of the PID control algorithm. For example, if the current temperature is 19℃, then the minimum temperature deviation is 20-19=1. The PID control algorithm is a closed-loop control algorithm that adjusts the control quantity through a linear combination of proportional (P), integral (I), and derivative (D) components. Based on the control quantity calculated by the PID algorithm, adjust the direction and magnitude of the current in the thermoelectric cooler. When the target temperature is higher than the current temperature, increase the heating power; when the target temperature is lower than the current temperature, increase the cooling power. By adjusting the current direction and magnitude, precise control of the cooling or heating power of the thermoelectric cooler is achieved. During the adjustment process, record the actual cooling or heating power of the thermoelectric cooler, the direction and magnitude of the current, and the trend of the first temperature value. These data are used for subsequent analysis and optimization to ensure the long-term stable operation of the system.

[0027] Through PID control algorithms, thermoelectric coolers can quickly respond to temperature changes and precisely regulate the internal temperature of the equipment to the target temperature range. For example, in transformer oil gas detection equipment, precise temperature control can reduce the impact of ambient temperature fluctuations on detection accuracy. The PID algorithm can dynamically adjust the control input based on real-time errors, adapting to different environmental conditions and equipment operating states. For instance, in high-humidity environments, the internal temperature of the equipment may fluctuate due to humidity changes; the PID control algorithm can adjust the power of the thermoelectric cooler in a timely manner to ensure temperature stability. By optimizing PID parameters, thermoelectric coolers can reduce unnecessary energy consumption while maintaining temperature control accuracy. For example, when the ambient temperature is close to the target temperature, the PID algorithm can reduce cooling or heating power, lowering energy consumption. Precise temperature control reduces stress and aging caused by temperature changes inside the equipment, extending its service life. For example, in transformer oil gas detection equipment, a stable temperature environment can reduce the drift of detection elements, improving detection accuracy and reliability.

[0028] Optionally, the step of making a second adjustment to the voltage and current parameters of the electroosmosis unit based on the first humidity value, the first temperature value, and the first operating data to obtain a second voltage value and a second current value includes: The minimum humidity deviation between the first humidity value and the preset target humidity range is calculated. Based on the minimum temperature deviation, the minimum humidity deviation, and the first operating data, the voltage and current parameters of the electroosmosis unit are calculated by the simulation module to obtain the second voltage value and the second current value, so that the operating efficiency of the electroosmosis unit is greater than or equal to the first threshold and the first humidity value is adjusted to the preset target humidity range.

[0029] Calculate the minimum humidity deviation between the first humidity value and the preset target humidity range. The target humidity range is usually a set interval, such as 40%-60%. The minimum humidity deviation (ΔH) measures the difference between the current humidity and the target humidity and is the basis for subsequent adjustments. For example, if the current humidity is 50%, the minimum humidity deviation is 0; if the current humidity is 70%, the minimum humidity deviation is 70-60=10. Based on the calculated minimum humidity deviation (ΔH), the minimum temperature deviation (ΔT) between the first temperature value and the target temperature range, as well as the first operating data of the thermoelectric cooler (such as actual cooling or heating power, current direction and magnitude, etc.), are used as input parameters for adjusting the electroosmotic unit. A simulation module (such as MATLAB Simulink) is used to calculate the voltage and current parameters of the electroosmotic unit. The simulation module, based on the physical model and control algorithm of the electroosmotic unit, and combined with the current humidity deviation, temperature deviation, and the operating state of the thermoelectric cooler, calculates a second voltage value and a second current value that ensure the operating efficiency of the electroosmotic unit is greater than or equal to the first threshold. For example, a PID control algorithm can be used to dynamically adjust the voltage and current of the electroosmotic unit. The PID algorithm adjusts the control quantity through a linear combination of proportional (P), integral (I), and derivative (D) components, ensuring the operating efficiency and humidity control effect of the electroosmosis unit. The adjusted second voltage and second current values ​​not only ensure that the operating efficiency of the electroosmosis unit is greater than or equal to the first threshold, but also adjust the first humidity value to within the preset target humidity range. This adjustment method effectively responds to changes in ambient humidity, ensuring the stability of the internal humidity of the equipment, thereby improving the accuracy and reliability of gas detection in transformer oil.

[0030] By combining humidity deviation, temperature deviation, and operating data from the thermoelectric cooler, the voltage and current of the electroosmosis unit are dynamically adjusted, precisely controlling the internal humidity within the target range. This ensures the electroosmosis unit's operating efficiency is greater than or equal to a first threshold, reducing unnecessary energy consumption and improving the overall system efficiency. A stable humidity environment reduces detection errors caused by humidity changes, improving the accuracy and reliability of gas detection in transformer oil. Utilizing a simulation module and PID control algorithm, the system can intelligently adjust based on real-time data, adapting to different environmental conditions.

[0031] Optionally, the step of inputting the second humidity value and the second temperature value into a preset model to obtain the target operating data, target voltage value, and target current value includes: The preset model is obtained by training historical data using machine learning algorithms to establish a mapping relationship between environmental parameters and equipment operating parameters; The second humidity value and the second temperature value are input into the preset model to obtain the optimal operating parameters of the thermoelectric cooler and the electroosmosis unit under the current environment. The optimal operating parameters include target operating data, target voltage value and target current value. The target operating data includes the target cooling or heating power of the thermoelectric cooler. The target voltage value and target current value are parameters for the electroosmosis unit to achieve optimal operating efficiency under the current environmental conditions.

[0032] Operating data of the gas detection equipment in transformer oil under different environmental conditions are collected, including humidity, temperature, cooling / heating power of the thermoelectric cooler, and voltage and current of the electroosmosis unit. This historical data is preprocessed, including data cleaning, normalization, and feature extraction, to ensure data quality and consistency. Pre-defined machine learning algorithms (such as support vector machines, neural networks, and decision trees) are selected to train the historical data. The training objective is to establish a mapping relationship between environmental parameters (humidity and temperature) and equipment operating parameters (cooling / heating power, voltage, and current). Model parameters are optimized using methods such as cross-validation to ensure the model's accuracy and generalization ability. The trained model is validated using a validation set to evaluate its performance. Based on the validation results, the model is optimized by adjusting its structure or parameters to improve prediction accuracy. The final pre-defined model can predict the optimal operating parameters of the equipment based on the input environmental parameters (humidity and temperature). The current second humidity and second temperature values ​​are input into the pre-defined model. These input data reflect the current environmental conditions of the equipment. Based on the input second humidity and second temperature values, the pre-defined model predicts the optimal operating parameters of the thermoelectric cooler and electroosmosis unit under the current environment. Optimal operating parameters include target operating data, target voltage value, and target current value. Target operating data: The target cooling or heating power of the thermoelectric cooler. Target voltage value: The voltage value at which the electroosmotic unit achieves optimal operating efficiency under current environmental conditions. Target current value: The current value at which the electroosmotic unit achieves optimal operating efficiency under current environmental conditions. The target operating data, target voltage value, and target current value output by the preset model provide a reference for subsequent equipment adjustments. These parameters are the result of optimization based on historical data and machine learning algorithms, ensuring that the equipment operates at optimal efficiency under current conditions.

[0033] By training historical data using machine learning algorithms, a pre-defined model can accurately predict the optimal operating parameters of equipment based on current environmental conditions. This data-driven prediction method can adapt to different environmental changes, improving the system's adaptability and flexibility. The target operating parameters output by the pre-defined model ensure that the thermoelectric cooler and electroosmosis unit operate at optimal efficiency under current conditions. By optimizing operating parameters, unnecessary energy consumption is reduced, improving the overall operating efficiency of the system. Accurate operating parameter prediction can reduce the operational risks of equipment in complex environments and extend its service life. For example, in environments with high humidity or large temperature fluctuations, the pre-defined model can adjust operating parameters in a timely manner to ensure stable operation of the equipment. The pre-defined model, combined with real-time environmental data, provides data support for intelligent control of the equipment. The system can dynamically adjust operating parameters based on the prediction results of the pre-defined model, achieving intelligent management.

[0034] Optionally, determining the adjustment direction and adjustment range based on the first difference and the second difference includes: Determine whether the first difference and / or the second difference is greater than the second threshold; When the first difference and / or the second difference is greater than the second threshold, the adjustment direction is determined to be to increase the weight of the first operating data, the second voltage value and the second current value, and to decrease the weight of the target operating data, the target voltage value and the target current value; When both the first difference and the second difference are less than or equal to the second threshold, the adjustment direction is determined to be to increase the weight of the target operating data, the target voltage value, and the target current value, and to decrease the weight of the first operating data, the second voltage value, and the second current value. The adjustment range of the weight is determined based on the third difference between the maximum value of the first difference and the second difference and the second threshold.

[0035] Calculate the first difference (ΔH) between the first humidity value and the second humidity value. Calculate the second difference (ΔT) between the first temperature value and the second temperature value. Set a second threshold (Δthreshold) to determine the severity of environmental changes. Determine whether the first difference (ΔH) and / or the second difference (ΔT) are greater than the second threshold (Δthreshold). When the first difference (ΔH) and / or the second difference (ΔT) are greater than the second threshold, it indicates a severe environmental change, requiring priority for immediate adjustments. This involves increasing the weight of the first operating data (immediate operating data of the thermoelectric cooler), the second voltage value, and the second current value (immediate operating parameters of the electroosmotic unit), while decreasing the weight of the target operating data, the target voltage value, and the target current value (long-term optimization parameters based on a preset model). When both the first difference (ΔH) and the second difference (ΔT) are less than or equal to the second threshold, it indicates a stable environmental change, allowing for greater consideration of long-term optimization goals. Increase the weight of the target operating data, the target voltage value, and the target current value, while decreasing the weight of the first operating data, the second voltage value, and the second current value. Choose the maximum value (Δmax) from the first difference (ΔH) and the second difference (ΔT). Calculate the third difference (Δdiff) between the maximum value (Δmax) and the second threshold (Δthreshold): Δdiff = Δmax − Δthreshold.

[0036] By analyzing the relationship between the difference and the threshold, the system can flexibly adjust weights to prioritize responses to drastic environmental changes, ensuring immediate and stable equipment operation. When environmental changes are stable, the system can focus more on long-term optimization goals, improving overall operational efficiency. The adjustment range (A) is dynamically determined based on the third difference (Δdiff), ensuring the system can flexibly adjust weights under different environmental conditions, demonstrating strong adaptability. Through dynamic weight adjustment, the system can find a balance between immediate needs and long-term optimization, reducing unnecessary energy consumption and improving operational efficiency. Precise weight adjustment reduces the operational risks of equipment in complex environments, extends equipment lifespan, and improves detection accuracy and reliability.

[0037] Optionally, determining the adjustment range of the weight based on the third difference between the maximum value of the first difference and the second difference and the second threshold includes: The product of the third difference and the preset adjustment range coefficient is calculated as the first adjustment range. The second adjustment range is determined according to the current environment. The first adjustment range and the second adjustment range are added together to obtain the adjustment range.

[0038] The adjustment magnitude (A) is dynamically determined based on the third difference (Δdiff), and is usually proportional to Δdiff: A = kΔdiff. Here, k is a proportionality coefficient used to adjust the sensitivity of weight changes. The weights of each parameter are dynamically adjusted according to the adjustment direction and magnitude (A): for parameters requiring increased weight, the weight is increased by A; for parameters requiring decreased weight, the weight is decreased by A. The second adjustment magnitude is dynamically determined based on current environmental conditions. It considers the specific characteristics of the current environment, such as seasonal variations in temperature and humidity or long-term operating trends of the equipment. The second adjustment magnitude can be a fixed value or a dynamically calculated value. For example, if the current ambient humidity is high, the second adjustment magnitude can be appropriately increased to enhance the system's responsiveness. First humidity value (H1) = 60%, second humidity value (H2) = 70%, first difference (ΔH) = 10%. First temperature value (T1) = 22℃, second temperature value (T2) = 25℃, second difference (ΔT) = 3℃. The preset second threshold (Δthreshold) = 5. Calculate the maximum difference (Δmax): Δmax = max(10, 3) = 10. Calculate the third difference (Δdiff): Δdiff = 10 − 5 = 5. Calculate the first adjustment magnitude (A1): Assume the adjustment magnitude coefficient (k) = 0.1. A1 = 0.1 * 5% = 0.5. Determine the second adjustment magnitude (A2): Assuming the current ambient humidity is high, the second adjustment magnitude (A2) = 0.3. Calculate the final adjustment magnitude (A): A = A1 + A2 = 0.5 + 0.3 = 0.8. Through the above steps, the final adjustment magnitude (A) is 0.8. The system will dynamically adjust the weights based on this adjustment magnitude to ensure the equipment operates at optimal efficiency under the current environmental conditions.

[0039] By dynamically calculating the adjustment range, the system can flexibly adjust weights according to the severity of environmental changes. When environmental changes are drastic, the adjustment range increases, allowing the system to respond quickly; when environmental changes are stable, the adjustment range decreases, allowing the system to smoothly transition to the long-term optimization goal. The first adjustment range is calculated based on the third difference, ensuring that the system's response to environmental changes has a clear quantitative basis. The preset adjustment range coefficient can be optimized based on the equipment's historical operating data and environmental change trends, further improving system stability. The second adjustment range is dynamically determined based on current environmental conditions, enabling the system to fine-tune for specific environments (such as high humidity or temperature differences), enhancing the equipment's adaptability to complex environments. By accurately calculating the adjustment range, the system can find a balance between immediate needs and long-term optimization, reducing unnecessary energy consumption and improving operating efficiency. For example, when environmental changes are minor, the system can reduce the weight of immediate adjustments and rely more on long-term optimization parameters, thereby reducing energy consumption. Precise weight adjustments reduce the operational risks of equipment in complex environments, slow down the aging of equipment caused by environmental changes, and extend the equipment's service life. A stable operating environment and flexible adjustment strategies can reduce detection errors caused by environmental changes, improving the accuracy and reliability of gas detection in transformer oil.

[0040] Optionally, determining the second operating data based on the target operating data, the first operating data, the adjustment direction, and the adjustment range includes: The first weight of the first running data and the second weight of the target running data are determined based on the adjustment direction and the adjustment magnitude. Calculate the first product of the first running data and the first weight, and calculate the second product of the target running data and the second weight. Calculate the sum of the first product and the second product to determine the second running data.

[0041] Based on the adjustment direction, the weights of the first running data (real-time running data) and the target running data (long-term optimization data) are determined. If the adjustment direction is to increase the weight of the first running data (e.g., drastic environmental changes), then the first weight (W1) is set to be larger, and the second weight (W2) to be smaller. If the adjustment direction is to increase the weight of the target running data (e.g., stable environmental changes), then the second weight (W2) is set to be larger, and the first weight (W1) to be smaller. The adjustment magnitude is dynamically determined based on the third difference, reflecting the degree of drastic environmental changes. The larger the adjustment magnitude, the more significant the change in weight. For example, if the environmental changes drastically, an increase in the adjustment magnitude will significantly increase the weight of the real-time running data. The first product (P1) is the product of the first running data (R1) and the first weight (W1): P1 = R1 × W1. This product reflects the contribution of the real-time running data under the current adjustment direction. The second product (P2) is the product of the target running data (R_target) and the second weight (W2): P2 = Rtarget × W2. This product reflects the contribution of the long-term optimization data under the current adjustment direction. The second operating data (R2) is the sum of the first product (P1) and the second product (P2): R2 = P1 + P2. This sum combines the contributions of real-time operating data and long-term optimization data, and is dynamically adjusted according to current environmental conditions. The second operating data (R2) is used to adjust the cooling or heating power of the thermoelectric cooler to ensure that the internal temperature of the equipment is maintained within the preset target temperature range.

[0042] By dynamically adjusting weights, the system prioritizes immediate needs during periods of drastic environmental change and reverts to long-term optimization goals when environmental changes are stable, achieving a balance between the two. The system dynamically adjusts weights and operating parameters based on the severity of environmental changes, enabling rapid adaptation to different operating conditions and improving equipment adaptability and stability. Through precise calculation of weights and operating data, the system optimizes energy consumption and improves operating efficiency while ensuring stable equipment operation. Precise adjustment of operating parameters reduces operational risks in complex environments, extends equipment lifespan, and improves detection accuracy and reliability. The system can dynamically adjust operating parameters based on real-time data and predictions from preset models, achieving intelligent management.

[0043] This embodiment also discloses a comprehensive protection system for a gas detection device in transformer oil. Figure 2 This is a schematic diagram of the integrated protection system of the transformer oil gas detection equipment disclosed in the embodiments of this application, as shown below. Figure 2 As shown, the system includes a data acquisition module 201, an adjustment module 202, a calculation module 203, and an execution module 204, wherein: The acquisition module 201 is configured to acquire the first humidity value and the first temperature value of the preset target location of the gas detection device in transformer oil, as well as the first voltage value and the first current value of the electroosmosis unit, and to acquire the second humidity value and the second temperature value of the current environment. The adjustment module 202 is configured to perform a first adjustment on the cooling or heating power of the thermoelectric cooler based on the first humidity value and the first temperature value using a PID control algorithm to obtain the first operating data of the thermoelectric cooler, and to perform a second adjustment on the voltage and current parameters of the electroosmosis unit based on the first humidity value, the first temperature value and the first operating data to obtain a second voltage value and a second current value. The calculation module 203 is configured to input the second humidity value and the second temperature value into a preset model to obtain target operating data, target voltage value and target current value, calculate the first difference between the first humidity value and the second humidity value and the second difference between the first temperature value and the second temperature value, and determine the adjustment direction and adjustment range based on the first difference and the second difference. The execution module 204 is configured to determine second operating data based on the target operating data, the first operating data, the adjustment direction, and the adjustment range; determine a third voltage value and a third current value based on the target voltage value, the target current value, the second voltage value, the second current value, the adjustment direction, and the adjustment range; adjust the thermoelectric cooler according to the second operating data; and adjust the electroosmosis unit according to the third voltage value and the third current value.

[0044] Optionally, the adjustment module 202 is configured to: Calculate the minimum temperature deviation between the first temperature value and the preset target temperature range, and calculate the required cooling or heating power based on the minimum temperature deviation using a PID control algorithm; The direction and magnitude of the current in the thermoelectric cooler are adjusted according to the cooling or heating power to adjust the first temperature value to the target temperature range; Record the first operating data of the thermoelectric cooler during the first adjustment process. The first operating data includes the actual cooling or heating power of the thermoelectric cooler, the direction and magnitude of the current, and the trend of the first temperature value.

[0045] Optionally, the adjustment module 202 is configured to: The minimum humidity deviation between the first humidity value and the preset target humidity range is calculated. Based on the minimum temperature deviation, the minimum humidity deviation, and the first operating data, the voltage and current parameters of the electroosmosis unit are calculated by the simulation module to obtain the second voltage value and the second current value, so that the operating efficiency of the electroosmosis unit is greater than or equal to the first threshold and the first humidity value is adjusted to the preset target humidity range.

[0046] Optionally, the computing module 203 is configured to: The preset model is obtained by training historical data using machine learning algorithms to establish a mapping relationship between environmental parameters and equipment operating parameters; The second humidity value and the second temperature value are input into the preset model to obtain the optimal operating parameters of the thermoelectric cooler and the electroosmosis unit under the current environment. The optimal operating parameters include target operating data, target voltage value and target current value. The target operating data includes the target cooling or heating power of the thermoelectric cooler. The target voltage value and target current value are parameters for the electroosmosis unit to achieve optimal operating efficiency under the current environmental conditions.

[0047] Optionally, the computing module 203 is configured to: Determine whether the first difference and / or the second difference is greater than the second threshold; When the first difference and / or the second difference is greater than the second threshold, the adjustment direction is determined to be to increase the weight of the first operating data, the second voltage value and the second current value, and to decrease the weight of the target operating data, the target voltage value and the target current value; When both the first difference and the second difference are less than or equal to the second threshold, the adjustment direction is determined to be to increase the weight of the target operating data, the target voltage value, and the target current value, and to decrease the weight of the first operating data, the second voltage value, and the second current value. The adjustment range of the weight is determined based on the third difference between the maximum value of the first difference and the second difference and the second threshold.

[0048] Optionally, the computing module 203 is configured to: The product of the third difference and the preset adjustment range coefficient is calculated as the first adjustment range. The second adjustment range is determined according to the current environment. The first adjustment range and the second adjustment range are added together to obtain the adjustment range.

[0049] Optionally, the execution module 204 is configured to: The first weight of the first running data and the second weight of the target running data are determined based on the adjustment direction and the adjustment magnitude. Calculate the first product of the first running data and the first weight, and calculate the second product of the target running data and the second weight. Calculate the sum of the first product and the second product to determine the second running data.

[0050] It should be noted that the above embodiments of the apparatus are only illustrated by the division of the above functional modules. In practical 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 apparatus 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.

[0051] This embodiment also discloses an electronic device, as shown in the reference. Figure 3 The electronic device may include: at least one processor 301, at least one communication bus 302, user interface 303, network interface 304, and at least one memory 305.

[0052] The communication bus 302 is used to enable communication between these components.

[0053] The user interface 303 may include a display screen and a camera. Optionally, the user interface 303 may also include a standard wired interface and a wireless interface.

[0054] The network interface 304 may optionally include a standard wired interface or a wireless interface (such as a Wi-Fi interface).

[0055] The processor 301 may include one or more processing cores. The processor 301 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 305, and by calling data stored in memory 305. Optionally, the processor 301 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 301 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 not be integrated into the processor 301 and may be implemented as a separate chip.

[0056] The memory 305 may include random access memory (RAM) or read-only memory. Optionally, the memory 305 may include a non-transitory computer-readable storage medium. The memory 305 can be used to store instructions, programs, code, code sets, or instruction sets. The memory 305 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 305 may also be at least one storage device located remotely from the aforementioned processor 301. Figure 3 As shown, the memory 305, 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 comprehensive protection method for gas detection equipment in transformer oil.

[0057] exist Figure 3In the electronic device shown, the user interface 303 is mainly used to provide an input interface for the user and to obtain the user input data; while the processor 301 can be used to call the application program stored in the memory 305 for the comprehensive protection method of the gas detection device in transformer oil. When executed by one or more processors 301, the electronic device performs one or more methods as described in the above embodiments.

[0058] 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.

[0059] 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.

[0060] 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.

[0061] 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.

[0062] 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.

[0063] 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 305 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 305 includes various media capable of storing program code, such as a USB flash drive, external hard drive, magnetic disk, or optical disk.

[0064] 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. Other embodiments of this disclosure will be readily apparent to those skilled in the art upon consideration of 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 to be considered exemplary only, and the scope and spirit of this disclosure are defined by the claims.

Claims

1. A comprehensive protection method for a gas detection device in transformer oil, characterized in that, Applied to a protection platform, the method includes: The system collects the first humidity and first temperature values ​​at the preset target location of the gas detection device in transformer oil, as well as the first voltage and first current values ​​of the electroosmosis unit, and also collects the second humidity and second temperature values ​​of the current environment. Based on the first humidity value and the first temperature value, the cooling or heating power of the thermoelectric cooler is adjusted firstly using a PID control algorithm to obtain the first operating data of the thermoelectric cooler. Based on the first humidity value, the first temperature value, and the first operating data, the voltage and current parameters of the electroosmosis unit are adjusted secondly to obtain the second voltage value and the second current value. The second humidity value and the second temperature value are input into a preset model to obtain target operating data, target voltage value and target current value. The first difference between the first humidity value and the second humidity value and the second difference between the first temperature value and the second temperature value are calculated. The adjustment direction and adjustment range are determined based on the first difference and the second difference. Based on the target operating data, the first operating data, the adjustment direction, and the adjustment range, second operating data is determined. Third voltage and third current values ​​are determined based on the target voltage value, the target current value, the second voltage value, the second current value, the adjustment direction, and the adjustment range. The thermoelectric cooler is adjusted according to the second operating data, and the electroosmosis unit is adjusted according to the third voltage and third current values. The step of adjusting the cooling or heating power of the thermoelectric cooler using a PID control algorithm based on the first humidity value and the first temperature value to obtain the first operating data of the thermoelectric cooler includes: Calculate the minimum temperature deviation between the first temperature value and the preset target temperature range, and calculate the required cooling or heating power based on the minimum temperature deviation using a PID control algorithm; The direction and magnitude of the current in the thermoelectric cooler are adjusted according to the cooling or heating power to adjust the first temperature value to the target temperature range; Record the first operating data of the thermoelectric cooler during the first adjustment process. The first operating data includes the actual cooling or heating power of the thermoelectric cooler, the direction and magnitude of the current, and the trend of the first temperature value. The step of adjusting the voltage and current parameters of the electroosmosis unit based on the first humidity value, the first temperature value, and the first operating data to obtain a second voltage value and a second current value includes: The minimum humidity deviation between the first humidity value and the preset target humidity range is calculated. Based on the minimum temperature deviation, the minimum humidity deviation, and the first operating data, the voltage and current parameters of the electroosmosis unit are calculated using a simulation module to obtain a second voltage value and a second current value, so that the operating efficiency of the electroosmosis unit is greater than or equal to a first threshold and the first humidity value is adjusted to the preset target humidity range. The step of determining the adjustment direction and adjustment range based on the first difference and the second difference includes: Determine whether the first difference and / or the second difference is greater than the second threshold; When the first difference and / or the second difference is greater than the second threshold, the adjustment direction is determined to be to increase the weight of the first operating data, the second voltage value and the second current value, and to decrease the weight of the target operating data, the target voltage value and the target current value; When both the first difference and the second difference are less than or equal to the second threshold, the adjustment direction is determined to be to increase the weight of the target operating data, the target voltage value, and the target current value, and to decrease the weight of the first operating data, the second voltage value, and the second current value. The adjustment range of the weight is determined based on the third difference between the maximum value of the first difference and the second difference and the second threshold.

2. The comprehensive protection method for the gas detection equipment in transformer oil according to claim 1, characterized in that, The step of inputting the second humidity value and the second temperature value into a preset model to obtain the target operating data, target voltage value, and target current value includes: The preset model is obtained by training historical data using machine learning algorithms to establish a mapping relationship between environmental parameters and equipment operating parameters; The second humidity value and the second temperature value are input into the preset model to obtain the optimal operating parameters of the thermoelectric cooler and the electroosmosis unit under the current environment. The optimal operating parameters include target operating data, target voltage value and target current value. The target operating data includes the target cooling or heating power of the thermoelectric cooler. The target voltage value and target current value are parameters for the electroosmosis unit to achieve optimal operating efficiency under the current environmental conditions.

3. The comprehensive protection method for the gas detection equipment in transformer oil according to claim 1, characterized in that, The step of determining the adjustment range of the weight based on the third difference between the maximum value of the first difference and the second difference and the second threshold includes: The product of the third difference and the preset adjustment range coefficient is calculated as the first adjustment range. The second adjustment range is determined according to the current environment. The first adjustment range and the second adjustment range are added together to obtain the adjustment range.

4. The comprehensive protection method for the gas detection equipment in transformer oil according to claim 1, characterized in that, The step of determining the second operating data based on the target operating data, the first operating data, the adjustment direction, and the adjustment magnitude includes: The first weight of the first running data and the second weight of the target running data are determined based on the adjustment direction and the adjustment magnitude. Calculate the first product of the first running data and the first weight, and calculate the second product of the target running data and the second weight. Calculate the sum of the first product and the second product to determine the second running data.

5. A comprehensive protection system for a gas detection device in transformer oil, characterized in that, It includes a data acquisition module, an adjustment module, a calculation module, and an execution module, and performs the method described in any one of claims 1-4, wherein: The acquisition module is configured to acquire the first humidity value and the first temperature value at the preset target location of the gas detection device in transformer oil, as well as the first voltage value and the first current value of the electroosmosis unit, and to acquire the second humidity value and the second temperature value of the current environment. The adjustment module is configured to perform a first adjustment on the cooling or heating power of the thermoelectric cooler based on the first humidity value and the first temperature value using a PID control algorithm to obtain the first operating data of the thermoelectric cooler, and to perform a second adjustment on the voltage and current parameters of the electroosmosis unit based on the first humidity value, the first temperature value, and the first operating data to obtain a second voltage value and a second current value. The calculation module is configured to input the second humidity value and the second temperature value into a preset model to obtain target operating data, target voltage value and target current value, calculate the first difference between the first humidity value and the second humidity value, and the second difference between the first temperature value and the second temperature value, and determine the adjustment direction and adjustment range based on the first difference and the second difference; The execution module is configured to determine second operating data based on the target operating data, the first operating data, the adjustment direction, and the adjustment range; determine a third voltage value and a third current value based on the target voltage value, the target current value, the second voltage value, the second current value, the adjustment direction, and the adjustment range; adjust the thermoelectric cooler according to the second operating data; and adjust the electroosmosis unit according to the third voltage value and the third current value.

6. An electronic device, characterized in that, The device includes a processor, a memory, a user interface, and a network interface. The memory is used to store instructions. Both the user interface and the network interface are used to communicate with other devices. 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 one of claims 1-4.

7. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores instructions that, when executed, perform the method as described in any one of claims 1-4.

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