Temperature and humidity control method and system for test box and medium

Abstract

The invention relates to the technical field of temperature and humidity control, in particular to a temperature and humidity control method and system for a test box and a medium. The method comprises the following steps: arranging a plurality of tangential air inlets which are circumferentially distributed at the top of a test box, and forming a spiral flow field from top to bottom in the box body by adjusting the air speed and direction of each air inlet; arranging a plurality of measuring points along the airflow path of the spiral flow field, wherein each measuring point measures the wind speed, temperature and humidity of the current position; correcting the temperature and humidity readings according to the measured wind speed to obtain corrected temperature and humidity data; weighting the corrected temperature and humidity data according to the volume weight of the test box, and calculating to obtain the overall temperature and humidity state of the box body; the humidity difference between the air inlet and the air outlet is measured and the moisture change condition in the box body is calculated by combining the wind speed. The temperature and humidity of the test box are accurately and intelligently controlled through a spiral flow field and a dual inspection mechanism comprising a dominant mode and a distribution state.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of temperature and humidity control, and particularly relates to a temperature and humidity control method and system for a test chamber and a medium. BACKGROUND

[0002] A test chamber is a complete set of equipment that can reproduce and maintain extreme or complex environmental conditions for a long time in a closed space through controllable means such as refrigeration, heating, humidification, dehumidification, illumination, low pressure or vibration, so as to verify the reliability, durability and safety of various products. The traditional temperature and humidity control system of a test chamber generally adopts a single-point or a few-point temperature and humidity detection mode, and adjusts the operation of a heater, a cooler, a humidifier and a dehumidifier through a simple PID control algorithm. This control mode can meet the basic temperature and humidity control requirements at the beginning of design, but as the test standards become more stringent and the volume of the test chamber increases, its inherent defects are gradually exposed: single-point detection cannot accurately reflect the overall temperature and humidity state inside the chamber, especially in a large-volume test chamber, due to uneven air distribution and the complexity of heat transfer, there are often significant temperature and humidity gradients, and single-point control is easy to cause local overheating or overcooling. Secondly, the traditional control system lacks effective monitoring and adjustment of the air flow state inside the chamber, and unreasonable air flow organization leads to extremely uneven temperature and humidity distribution, which seriously affects the accuracy and repeatability of test results. SUMMARY

[0003] Therefore, it is necessary to provide a temperature and humidity control method and system for a test chamber and a medium to solve at least one of the above technical problems.

[0004] To achieve the above-mentioned purpose, a temperature and humidity control method for a test chamber comprises the following steps: Step S1: A plurality of tangential air inlets are arranged in a circumferential distribution at the top of the test chamber, and a spiral flow field is formed from top to bottom in the chamber by adjusting the air speed and direction of each air inlet; Step S2: A plurality of measuring points are arranged along the air flow path of the spiral flow field, each measuring point measures the air speed, temperature and humidity at the current position, and the temperature and humidity readings are corrected according to the measured air speed to obtain corrected temperature and humidity data; Step S3: The corrected temperature and humidity data are weighted according to the volume weight of the test chamber where they are located, and the overall temperature and humidity state of the chamber is calculated; the humidity difference between the air inlet and the air outlet is measured and combined with the air speed to calculate the water content change in the chamber; Step S4: The heater power, cooler power and chamber wall temperature difference are combined with the overall temperature and humidity state of the chamber to predict the power input curve of the heater and cooler required to reach the target temperature; Step S5: control the heater and the refrigerator according to the power input curve, and control the humidifier and the dehumidifier according to the water content change in the cabinet, so as to realize stable control of the temperature and humidity in the test cabinet.

[0005] The application also provides a test cabinet temperature and humidity control system for executing the test cabinet temperature and humidity control method as described above, and the test cabinet temperature and humidity control system comprises: A flow field generation module is configured to set a plurality of tangential air inlets in a circumferential distribution on the top of the test cabinet, and form a spiral flow field from top to bottom in the cabinet by adjusting the air speed and direction of each air inlet. A data correction module is configured to arrange a plurality of measurement points along the airflow path of the spiral flow field, each measurement point measuring the air speed, temperature and humidity at the current position; correct the temperature and humidity readings according to the measured air speed to obtain corrected temperature and humidity data. A state analysis module is configured to weight the corrected temperature and humidity data according to the volume weight of the test cabinet in which the data is located, and calculate the overall temperature and humidity state of the cabinet; measure the humidity difference of the air inlet and the air outlet and calculate the water content change in the cabinet in combination with the air speed. A power prediction module is configured to predict the power input curve of the heater and the refrigerator required to reach the target temperature by combining the overall temperature and humidity state of the cabinet with the real-time monitored heater power, refrigerator power and cabinet wall temperature difference. An equipment control module is configured to control the heater and the refrigerator according to the power input curve, and control the humidifier and the dehumidifier according to the water content change in the cabinet, so as to realize stable control of the temperature and humidity in the test cabinet.

[0006] The application also provides a computer storage medium storing a computer program, which is executed to realize the test cabinet temperature and humidity control method as described above.

[0007] The beneficial effects are: The present application realizes the systematic improvement of the uniformity of temperature and humidity, the stability of control and the sensitivity of response by introducing the configuration of spiral flow field and the mechanism of dynamic correction. Firstly, multiple tangential air inlets are arranged on the top of the test chamber, and a spiral flow field is formed from top to bottom by adjusting the air speed and direction, which can break the vertical stratification or local stagnation problem existing in the traditional test chamber, and make the air flow path more fully cover the entire chamber space. This flow field structure lays a foundation for the subsequent collection and correction of temperature and humidity distribution. Multiple measurement points are arranged uniformly on the spiral flow field path, and the wind speed, temperature and humidity of each measurement point are dynamically collected. At the same time, the measurement stability is judged based on the wind speed variation, which helps to filter out the measurement noise caused by flow field fluctuation interference. Under the condition of stable wind speed, the correction coefficient of wind speed to temperature and humidity is introduced by table lookup method, and the original measurement value is further corrected, so that the temperature and humidity reflect the real air state more closely. This correction model not only considers the direct influence of wind speed on temperature and humidity readings, but also introduces the correlation factor of temperature and humidity coupling, which improves the accuracy of humidity estimation by temperature-related correction. After obtaining the corrected temperature and humidity data of multiple measurement points, the system combines the spatial position relationship between each measurement point and the center axis of the test chamber, calculates the volume weight coefficient according to the volume of the cylindrical ring, so that the data weighting is more precise, which can effectively reflect the influence of different regions on the overall environment. The overall temperature and humidity state of the chamber obtained after weighting not only improves the scientificity of multi-point data fusion in the chamber, but also enables the system to identify the trend of overall environmental state change. In order to ensure that the temperature and humidity control is not limited to simply tracking the average value, this method also introduces a humidity difference comparison mechanism for the inlet and outlet air inlets. By combining three layers of humidity sensors, a three-dimensional monitoring capability for the water transmission path in the airflow is formed. According to the arrangement of different humidity differences, the system can judge the dominant direction of humidification and judge the uniformity and stability of the current chamber water vapor distribution according to the difference fluctuation, preventing the formation of local saturated or dry areas. This mechanism provides accurate basis for the humidity control strategy, making the action of humidifier or dehumidifier more targeted and directional. Combined with temperature control, the system takes the real-time output power of the heater and the cooler as the basis, considers the wall temperature difference and the surface area of the test chamber to calculate the heat dissipation power, and then obtains the energy balance state. On this basis, combined with the deviation of the current temperature and the target temperature, the power input curve of the heating and cooling equipment is generated to realize the advance response and dynamic compensation of the temperature change trend. At the same time, the humidity control strategy is also matched and controlled based on the real-time dominant and distribution state judgment matrix, so that appropriate humidification mode can be adopted in different water vapor dynamic scenarios. In addition, the system also establishes a stability judgment mechanism, which judges whether the overall temperature and humidity change amplitude is lower than the set threshold for three times in a row. Once the stable state is reached, the control instruction execution frequency is automatically reduced to avoid excessive intervention and resource waste. This control logic not only ensures the rapid approach of the target state, but also guarantees the optimization of system resources and reasonable control rhythm in the maintenance process. BRIEF DESCRIPTION OF DRAWINGS

[0008] Other features, objects, and advantages of the application will become more apparent from the following detailed description when read in connection with the following drawings: Fig. 1 A flow chart of a method for controlling temperature and humidity of a test chamber according to the present application is shown in Fig. 1. Fig. 2 A module diagram of a system for controlling temperature and humidity of a test chamber according to the present application is shown in Fig. 2. Fig. 3 A control interface diagram of a temperature and humidity coordinated and stable control system of an environmental test chamber according to an embodiment of the present application is shown in Fig. 3. DETAILED DESCRIPTION

[0009] The technical method of the present application will be described clearly and completely below in conjunction with the drawings. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all the embodiments. Based on the embodiments of the present application, all other embodiments obtained by those skilled in the art without creative work fall within the scope of the present application.

[0010] In addition, the drawings are only schematic illustrations of the present application, and are not necessarily drawn to scale. Identical reference numerals in the drawings represent identical or similar parts, and thus repeated descriptions thereof will be omitted. Some of the block diagrams shown in the drawings are functional entities, and do not necessarily correspond to physically or logically independent entities. The functional entities can be implemented in the form of software, or in one or more hardware modules or integrated circuits, or in different network and / or processor methods and / or microcontroller methods.

[0011] It should be understood that although the terms "first", "second", etc. can be used herein to describe various elements, these elements should not be limited by these terms. These terms are only used to distinguish one element from another. For example, without departing from the scope of the example embodiments, a first element can be called a second element, and similarly, a second element can be called a first element. The term "and / or" as used herein includes any and all combinations of one or more of the associated listed items.

[0012] To achieve the above-mentioned object, the present application provides a method for controlling temperature and humidity of a test chamber, which comprises the following steps: Figs. 1 to 3 The method comprises the following steps: Step S1: A plurality of tangential air inlets are arranged on the top of the test chamber in a circumferential distribution, and a spiral flow field from top to bottom is formed in the chamber by adjusting the air speed and direction of each air inlet. Step S2: arranging multiple measuring points along the airflow path of the spiral flow field, each measuring point measuring the wind speed, temperature and humidity at the current position; correcting the temperature and humidity readings according to the measured wind speed to obtain corrected temperature and humidity data; Step S3: weighting the corrected temperature and humidity data according to the volume weight of the test chamber it is in to calculate the overall temperature and humidity state of the chamber; measuring the humidity difference between the inlet and outlet and combining the wind speed to calculate the water content change in the chamber; Step S4: predicting the power input curve of the heater and the refrigerator required to reach the target temperature by combining the real-time monitored heater power, refrigerator power and chamber wall temperature difference with the overall temperature and humidity state of the chamber; Step S5: controlling the heater and the refrigerator according to the power input curve, and controlling the humidifier and the dehumidifier according to the water content change in the chamber to achieve stable control of the temperature and humidity in the test chamber.

[0013] Especially important is that step S1 is specifically: A plurality of tangential air inlets with an angle of 15°-45° with the horizontal plane are arranged at the top of the test chamber, and a spiral flow field with an axial velocity component of 0.2-0.8 m / s and a tangential velocity inversely proportional to the radius is formed by adjusting the wind speed of each air inlet; In some embodiments, 6-12 tangential air inlets are uniformly installed at the top of the test chamber, each air inlet has an angle of 15°-45° with the horizontal plane, and a preferred angle of 30° is preferred to obtain the best spiral flow field effect. For example, in a circular test chamber with a diameter of 2 meters, an air inlet is installed every 30° along the circumference, a total of 12 air inlets, each air inlet has a diameter of 80mm, and the wind speed of each air inlet is adjusted in the range of 1-5m / s by an adjustable fan. The wind speed of each air inlet is adjusted by a PLC control system, so that the wind speed of the air inlet near the center of the chamber is higher and the wind speed of the air inlet near the chamber wall is lower, forming a spiral flow field with a tangential velocity inversely proportional to the radius, and the axial velocity component is controlled between 0.2-0.8m / s.

[0014] It should be noted that the number of air inlets can be adjusted according to the size of the test chamber. For small test chambers with a diameter of less than 1 meter, 6 air inlets can meet the requirements, while for large test chambers with a diameter of more than 3 meters, the number of air inlets needs to be increased to 16-20 to ensure the uniformity of the flow field.

[0015] Further, step S2 includes the following steps: A plurality of measuring points are arranged along the airflow path of the spiral flow field, data collection is performed at each measuring point every preset time, the current wind speed value, temperature value and humidity value are recorded in turn, and the collected data is temporarily stored in the data buffer area of the measuring point, and each buffer area retains the latest 20 measurement records; The latest 5 consecutive wind speed measurement values in the measurement point data buffer area are taken out, the average value of the 5 wind speed measurement values is calculated, and the difference between the maximum value and the minimum value is recorded as the wind speed average value and the wind speed difference value; When the wind speed difference value is greater than or equal to 10% of the wind speed average value, wait for the next measurement period to determine again; When the wind speed difference value is less than 10% of the wind speed average value, it is determined that the current wind speed is stable, and a correction operation is performed on the current temperature measurement value and humidity measurement value to obtain the corrected temperature and humidity data.

[0016] In some embodiments, the measurement point arrangement scheme is determined according to the airflow characteristics of the spiral flow field, and a hierarchical radial arrangement method is generally used, i.e. the box is divided into three height layers of upper, middle and lower, and 3-5 measurement points are arranged at equal intervals along the radial direction in each layer to ensure that the measurement points are located on the main airflow path. For example, in a cylindrical test box with a height of 3 meters and a diameter of 2 meters, 4 measurement points are arranged on the upper layer (0.8 meters from the top), the middle layer (1.5 meters from the top), and the lower layer (2.2 meters from the top), respectively, at radial positions of 0.2 meters, 0.5 meters, 0.7 meters, and 0.9 meters from the center axis, for a total of 12 measurement points. Each measurement point is equipped with an integrated environmental sensor that can simultaneously measure wind speed, temperature, and humidity. The sensor is connected to the central data collector through a digital signal bus. The system sets a preset time interval of 10 seconds, i.e. every 10 seconds, a complete data collection is performed on all measurement points, and each time the values are recorded in the order of wind speed, temperature, and humidity. The entire collection process takes about 2-3 seconds. The collected data is immediately stored in the dedicated data buffer area of the corresponding measurement point. Each buffer area uses a first-in, first-out (FIFO) circular queue structure, and the latest 20 measurement records are fixedly retained. When new data is written, the earliest data record is automatically overwritten.

[0017] It should be noted that the selection of the preset time interval needs to consider the system response speed and data processing load. For rapidly changing working conditions, it can be shortened to 5 seconds, while for long-term tests with low stability requirements, it can be extended to 30 seconds, but it is not recommended to exceed 60 seconds to avoid missing important environmental changes.

[0018] In another embodiment, during the wind speed stability determination phase, after each data collection step, the system automatically extracts the five most recent consecutive wind speed measurements from the buffer at each measurement point for analysis. For a particular measurement point, the five most recent wind speed values ​​are 2.1 m / s, 2.3 m / s, 2.0 m / s, 2.2 m / s, and 2.4 m / s, respectively. The system first calculates the arithmetic mean of these five values: (2.1 + 2.3 + 2.0 + 2.2 + 2.4) ÷ 5 = 2.2 m / s, which is recorded as the mean wind speed value. The difference between the maximum and minimum values ​​is then calculated: 2.4 - 2.0 = 0.4 m / s, which is recorded as the wind speed difference. Next, a stability determination is performed, calculating the percentage of the wind speed difference to the mean wind speed value: 0.4 ÷ 2.2 × 100% = 18.2%. Because this percentage is greater than the set threshold of 10%, the system determines that the current wind speed is unstable and temporarily does not perform temperature and humidity correction. Instead, the system waits for the next measurement cycle (after 10 seconds) to re-determine wind speed stability. Only when the wind speed difference is less than 10% of the average wind speed, for example, the wind speed difference is 0.15m / s, accounting for 0.15÷2.2×100%=6.8%, will the system determine that the current wind speed is stable. At this time, the temperature and humidity correction program is immediately triggered to correct the wind speed impact on the temperature and humidity values ​​currently collected at the measurement point.

[0019] It should be noted that the 10% stability threshold is an empirical value derived from a large amount of experimental data. It can be adjusted to 5% for situations with extremely high precision requirements, and can be relaxed to 15% for general industrial applications. However, a threshold that is too low will cause the system to be unable to enter the correction state for a long time, and a threshold that is too high may cause correction when the wind speed is unstable, affecting data accuracy.

[0020] It should be noted that in actual engineering applications, the response time and accuracy characteristics of the sensor itself also need to be considered. The response time of a wind speed sensor is usually 1-3 seconds, and the response time of a temperature and humidity sensor is 10-30 seconds. Therefore, the preset time interval should be greater than the maximum response time of the sensor to ensure that the collected data truly reflects the current environmental status.

[0021] Furthermore, the correction operation performed on the current temperature measurement value and humidity measurement value is specifically as follows: According to the average wind speed value of the current measurement point, the correction parameter comparison table pre-established at the measurement point is searched and located, and the corresponding temperature correction coefficient and humidity preliminary correction coefficient are extracted; Multiply the temperature correction coefficient by the difference between the current temperature measurement and 20°C to obtain the temperature correction value; add the temperature correction value to the current temperature measurement to obtain the corrected temperature value; The humidity preliminary correction coefficient is multiplied by the difference between the current humidity measurement value and 50% relative humidity to obtain a humidity wind speed correction amount, and the humidity wind speed correction amount is added to the current humidity measurement value to obtain a wind speed preliminary correction humidity value; The temperature correlation correction coefficient is matched with a preset humidity temperature correlation correction table according to the corrected temperature value to obtain a temperature correlation correction coefficient; The temperature correlation correction coefficient is multiplied by the difference between the corrected temperature value and 25℃ to obtain a humidity temperature correction amount, and the humidity temperature correction amount is added to the wind speed preliminary correction humidity value to obtain a corrected humidity value; The corrected humidity value and the corrected temperature value are taken as the corrected temperature and humidity data of the measurement point.

[0022] In some embodiments, a correction parameter reference table is established, which is established according to a large amount of calibration experimental data and covers correction coefficients every 0.1 m / s in the range of 0.1 m / s to 5.0 m / s of wind speed. For example, when the average wind speed is 2.2 m / s, the system finds the corresponding temperature correction coefficient 1.02 and humidity preliminary correction coefficient 0.98 in the reference table. In the temperature correction process, assuming that the temperature measurement value of the current measurement point is 28.5℃, first, the difference between the temperature value and the reference temperature 20℃ is calculated, i.e. 28.5-20=8.5℃, then the temperature correction coefficient 1.02 is multiplied by the difference to obtain the temperature correction amount: 1.02×8.5=8.67℃, and finally the temperature correction amount is added to the original temperature measurement value to obtain the corrected temperature value: 8.67+28.5=37.17℃. However, it should be noted that the correction amount is calculated logically, and actually it should be: corrected temperature value=original temperature value+correction coefficient×(original temperature value-20℃), i.e. 28.5+(1.02×8.5)=28.5+8.67=37.17℃.

[0023] It should be noted that 20℃ is set as the reference temperature for temperature correction because most sensors have the best linearity and stability at this temperature, but for special applications such as low-temperature test boxes, the reference temperature can be adjusted to 0℃ or-10℃ to obtain more accurate correction effect, which is not limited by the present application.

[0024] The humidity correction process adopts a two-step correction method, first the wind speed influence correction, and then the temperature correlation correction. Assuming that the current measurement point humidity measurement value is 65% RH, and the humidity preliminary correction coefficient is 0.98, first calculate the difference between the humidity measurement value and the reference humidity 50% RH: 65-50=15% RH, then calculate the humidity wind speed correction amount: 0.98x15=14.7% RH, add the wind speed correction amount to the original humidity measurement value to get the wind speed preliminary correction humidity value: 65+14.7=79.7% RH. Next, the temperature correlation correction is performed, and the correction temperature value 37.17°C is calculated according to the previous calculation, and the corresponding temperature correlation correction coefficient is found in the preset humidity temperature correlation correction table. The correction table is established based on the characteristic curve of the humidity sensor at different temperatures, for example, the temperature correlation correction coefficient corresponding to 37.17°C is -0.02. Then calculate the difference between the corrected temperature value and the reference temperature 25°C: 37.17-25=12.17°C, calculate the humidity temperature correction amount: -0.02x12.17=-0.24% RH, and finally add the humidity temperature correction amount to the wind speed preliminary correction humidity value to get the corrected humidity value: 79.7+(-0.24)=79.46% RH.

[0025] It should be noted that 50% RH is selected as the wind speed correction reference and 25°C is selected as the temperature correlation correction reference in the humidity correction process, because most humidity sensors have good linear response characteristics under these conditions, but in actual application, these reference values can be adjusted according to the sensor specification book and the on-site calibration results, and the present application does not limit them.

[0026] Among them, the establishment of the correction parameter table and the humidity temperature correlation correction table needs to be completed through a large number of calibration experiments. The calibration process is usually carried out in a standard environment laboratory, and the response characteristics of the sensor under different wind speeds, temperatures and humidity conditions are measured using high-precision reference standard, and the function relationship between the correction coefficient and the environmental parameters is established. For example, for the temperature correction coefficient, under the condition of wind speed 2.0 m / s, the sensor response is tested at 10°C, 20°C, 30°C and 40°C respectively, and it is found that the sensor reading is low at high temperature, so the correction coefficient is set to be greater than 1.0 to compensate; while at low temperature, the reading is high, and the correction coefficient is less than 1.0. For humidity correction, the influence of wind speed on the air flow around the sensor and the influence of temperature on the characteristics of the humidity sensor sensitive element need to be considered, and the correction model is established through multiple regression analysis.

[0027] It should be noted that the correction parameters of sensors of different models and manufacturers will have significant differences, so each system needs to be specially calibrated and tabled, and the correction parameters of other systems cannot be simply applied, otherwise the corrected data may deviate further from the true value.

[0028] It should be noted that the present application also needs to perform boundary check on the corrected temperature value, to ensure that the temperature value is within the range of -40℃ to 85℃, and if it exceeds the range, it will be limited to the boundary value; the boundary check is also performed on the corrected humidity value, to ensure that the humidity value is within the range of 0%RH (relative humidity) to 100%RH, and if it exceeds the range, it will be limited to the boundary value; the number of occurrence of each boundary limiting operation is recorded, and when a certain measurement point appears boundary limitation for 10 times in succession, it is marked that the correction parameter of the measurement point needs to be recalibrated.

[0029] Further, in step S3, the corrected temperature and humidity data are weighted according to the volume weight of the spiral flow field position where they are located, and the overall temperature and humidity state of the box body is calculated, including: The height and inner diameter of the inner cavity of the test box are measured, and the total volume of the box body is calculated; The radial distance of each measurement point to the central axis is measured with the vertical central axis of the box body as the reference; The cylindrical ring volume represented by each measurement point is calculated according to the radial distance of each measurement point to the central axis; wherein the calculation formula of the cylindrical ring volume is: In the formula, is the cylindrical ring volume represented by each measurement point, is the radial distance of the central axis of the test box, is a fixed offset, is the thickness of the height layer where the measurement point is located; The ratio of the cylindrical ring volume to the total volume of the box body is calculated as the volume weight coefficient of each measurement point; The overall temperature and humidity state of the box body is calculated by using the corrected temperature and humidity data and the volume weight coefficient.

[0030] In some embodiments, the physical size parameters of the test box are determined by precise measurement tools, including the inner cavity height H and the inner diameter D, so as to calculate the total volume of the box body . For example, for a cylindrical test box with a height of 3 meters and an inner diameter of 2 meters, the total volume is cubic meters. Next, the spatial position coordinates of each measurement point are determined, a coordinate system is established with the vertical central axis of the box body as the reference, and the radial distance of each measurement point to the central axis is accurately measured by using a laser range finder or a coordinate measuring instrument . For example, the radial distances of the 4 measurement points in the upper layer are 0.2 meters, 0.5 meters, 0.7 meters and 0.9 meters respectively, and the radial distances of the measurement points in the middle and lower layers are the same. Then the thickness of each height layer is determined according to the vertical distribution of the measurement points , which usually adopts equal division, i.e. For the case of 3 layers, the thickness of each layer is 3 / 3=1 meter. The fixed offset is The selection needs to consider the representativeness of the measurement points and the calculation accuracy, usually set as half of the radial distance difference between adjacent measurement points, for example, when the distance difference between adjacent measurement points is 0.3 meters, 0.15 meters, ensuring that the cylindrical ring area represented by each measurement point can completely cover the internal space of the box without overlapping.

[0031] The calculation of the volume of the cylindrical ring uses the method of subtracting the inner cylinder from the outer cylinder, and the formula is . Taking the measurement point with a radial distance of 0.5 meters as an example, when = 0.15 meters, = 1 meter, the volume of the cylindrical ring represented by this measurement point is cubic meters. It needs to be noted that for the central measurement point with a radial distance of 0, its representative volume should be calculated as a solid cylinder, i.e. , not a cylindrical ring. For the outermost measurement point, it needs to ensure that the outer cylinder radius does not exceed the box radius, i.e. D / 2, if it exceeds, it needs to adjust the value or use a sector correction. The volume weight coefficient calculation formula of each measurement point is = / , for example, the weight coefficient of the aforementioned 0.5-meter radial distance measurement point is 0.94 / 9.42 = 0.10, indicating that this measurement point represents 10% of the volume of the box. It needs to be noted that the sum of the weight coefficients of all measurement points should be equal to 1, if there is a deviation, it needs to be normalized, i.e. each weight coefficient is divided by the total weight coefficient, to ensure the accuracy of the weight distribution.

[0032] The calculation of the overall temperature and humidity state of the box uses the weighted average method, the overall temperature state value , and the overall humidity state value , where and are the corrected temperature and humidity values of each measurement point, respectively. For example, the corrected temperature values of the 12 measurement points are 25.1℃, 25.3℃, 24.9℃, etc., and the corresponding weight coefficients are 0.08, 0.10, 0.09, etc., then the overall temperature state value is the cumulative result of 25.1×0.08+25.3×0.10+24.9×0.09+.... In order to improve the calculation accuracy, the system updates the overall temperature and humidity state value every 30 seconds, and compares it with the previous calculation result, when the change amplitude of the continuous three calculation results is less than the set threshold (temperature 0.1℃, humidity 1%RH), it is determined that the system reaches a stable state.

[0033] It should be noted that once the weight coefficient is determined, it usually does not need to be adjusted frequently, but when the measurement point position changes or the box structure is modified, the radial distance must be measured again and the weight coefficient must be recalculated, otherwise it will cause the overall state value calculation deviation. For long-term running system, it is recommended to check the accuracy of the measurement point position once a year to ensure that the weight distribution is consistent with the actual spatial distribution, especially after long-term use in high temperature and high humidity environment, the measurement point support may be caused by thermal expansion and cold contraction, which will cause the position deviation and affect the accuracy of weight calculation.

[0034] Further, the overall temperature and humidity state of the box calculated by using the corrected temperature and humidity data and the volume weight coefficient is specifically: The sum of the volume weight coefficients corresponding to all measurement points in the test box is calculated, and the absolute difference between the sum of the volume weight coefficients and 1 is measured to verify the coverage degree of the cylindrical ring volume represented by the measurement point. If the absolute difference is less than the preset threshold, the weighted calculation is performed, otherwise the weight abnormality alarm is issued; The weighted calculation is specifically: The difference between the maximum value and the minimum value of the corrected temperature value of each measurement point is calculated as the temperature distribution range, and the difference between the maximum value and the minimum value of the corrected humidity value of each measurement point is calculated as the humidity distribution range. When the temperature distribution range exceeds 3℃, adjust the air speed distribution ratio of each air inlet of the spiral flow field, so that the air speed of the radial inner air inlet increases and the air speed of the radial outer air inlet decreases, and the total air inlet amount remains unchanged; When the humidity distribution range exceeds 8% relative humidity, adjust the humidifier nozzle to the area where the humidity value is higher than the average level; The corrected temperature value of each measurement point is multiplied by the corresponding volume weight coefficient and summed to obtain the overall temperature state value of the box. The corrected humidity value of each measurement point is multiplied by the corresponding volume weight coefficient and summed to obtain the overall humidity state value of the box. The overall temperature state value of the box and the overall humidity state value of the box are calculated every 30 seconds; When the change amplitude of the overall temperature state value of the box is less than 0.1℃ and the change amplitude of the overall humidity state value of the box is less than 1% relative humidity for three times in a row, the system stability flag is set, and the overall temperature and humidity state of the box is obtained.

[0035] In some embodiments, the volume weight coefficients of all measurement points are accumulated and verified, for example, the weight coefficients of 12 measurement points are 0.08, 0.10, 0.09, 0.11, 0.07, 0.12, 0.08, 0.09, 0.10, 0.08, 0.09, 0.11, respectively, and the cumulative sum is 1.12, and the absolute difference from the theoretical value 1 is |1.12-1|=0.12. The threshold value preset by the system is usually 0.05, since 0.12>0.05, the system will issue a weight abnormality alarm, prompting that there is a problem with the measurement point arrangement or weight calculation, which needs to be rechecked for the measurement point position or the fixed offset ∆r is adjusted. Only when the absolute difference value is less than the preset threshold value, the system will perform subsequent weighted calculation, otherwise the calculation will be suspended and the on-site inspection is required by the operation and maintenance personnel. After the weight verification is passed, the system starts to perform the weighted calculation process, first analyzes the distribution characteristics of the corrected temperature and humidity data of each measurement point, and calculates the temperature distribution range and the humidity distribution range. For example, the corrected temperature values of 12 measurement points are 24.8℃, 25.2℃, 25.5℃, 24.9℃, 25.8℃, 24.6℃, 25.1℃, 25.4℃, 24.7℃, 25.6℃, 25.0℃, 25.3℃, among which the maximum value is 25.8℃, the minimum value is 24.6℃, and the temperature distribution range is 25.8-24.6=1.2℃; the humidity values are 63%RH, 58%RH, 65%RH, 61%RH, 67%RH, 59%RH, 62%RH, 64%RH, 60%RH, 66%RH, 61%RH, 63%RH, among which the maximum value is 67%RH, the minimum value is 58%RH, and the humidity distribution range is 67-58=9%RH.

[0036] It should be noted that the setting of the preset threshold value needs to be adjusted according to the accuracy requirement of the test chamber and the number of measurement points. For high-precision environmental test chambers, the threshold value can be set to 0.02, while for general industrial test chambers, the threshold value can be relaxed to 0.10.

[0037] When the temperature distribution range exceeds 3°C, the system will automatically start the flow field uniformity adjustment program by adjusting the air speed distribution ratio of each inlet to improve the uniformity of temperature distribution. The specific adjustment strategy is to increase the air speed of the radial inner inlet, while reducing the air speed of the radial outer inlet, but keep the total air volume unchanged. For example, when the temperature distribution range reaches 3.5°C, the system will increase the air speed of the inner 4 inlets from the original 2.5 m / s to 2.8 m / s, and reduce the air speed of the outer 4 inlets from 2.5 m / s to 2.2 m / s, while the middle 4 inlets remain at 2.5 m / s, which not only keeps the total air volume unchanged, but also enhances the airflow mixing effect in the central area. When the humidity distribution range exceeds 8% relative humidity, the system will adjust the direction of the humidifier nozzle, turning the nozzle towards the area where the humidity value is lower than the average level. For example, when the humidity distribution range reaches 9% RH and the average humidity is calculated to be 62% RH, the system will identify the positions of the measurement points with humidity values lower than 62% RH, and then control the adjustable nozzle to turn towards these areas, increasing the local humidification intensity to reduce the humidity distribution difference.

[0038] It should be noted that the temperature distribution threshold of 3°C and the humidity distribution threshold of 8% RH are set based on the uniformity requirements of most test standards.

[0039] The calculation of the overall temperature and humidity state value of the box adopts a strict weighted average algorithm. The overall temperature state value , the overall humidity state value where the summation covers all valid measurement points. For example, using the aforementioned data of 12 measurement points, assuming the weight coefficients are normalized to 0.083, 0.089, 0.085, 0.091, 0.078, 0.095, 0.083, 0.087, 0.089, 0.082, 0.087, 0.091 respectively, then the overall temperature state value is 24.8x0.083+25.2x0.089+25.5x0.085+...=25.12℃, and the overall humidity state value is 63x0.083+58x0.089+65x0.085+...=62.3%RH. The system performs a complete calculation process every 30 seconds, including data acquisition, correction, weight verification, distribution range check, adjustment execution and overall state value calculation, forming a complete control cycle. The calculation results are compared with the previous results, and the change amplitude of the temperature and humidity state values is recorded. When the change amplitudes of the overall temperature state value and the overall humidity state value are less than 0.1℃ and 1%RH respectively for three consecutive calculation results, for example, the three temperature calculation results are 25.12℃, 25.14℃, 25.11℃, the change amplitudes are 0.02℃, 0.03℃ respectively, both of which are less than the 0.1℃ threshold; the three humidity calculation results are 62.3%RH, 62.6%RH, 62.4%RH, the change amplitudes are 0.3%RH, 0.2%RH respectively, both of which are less than the 1%RH threshold, the system will set the system stable flag, indicating that the test chamber has reached a stable temperature and humidity state.

[0040] It should be noted that the entire calculation process requires a large number of numerical operations, especially in large test chambers with a large number of measurement points. It is recommended to use an industrial computer or a PLC system with floating-point operation capability to ensure calculation accuracy and response speed, and to avoid affecting the real-time performance of the control system due to calculation delay.

[0041] Further, the humidity difference between the inlet and outlet in step S3 is measured and combined with the air speed to calculate the water content change in the chamber, including: Humidity sensors are installed on the upper, middle and lower layers in the vertical direction of the inlet, and the same configuration is used for the outlet; Start the time controller, sample alternately every 5 seconds, read the upper layer data of the inlet and the lower layer data of the outlet as the first humidity difference, read the middle layer data of the inlet and the middle layer data of the outlet as the second humidity difference, and read the lower layer data of the inlet and the upper layer data of the outlet as the third humidity difference; When the first humidity difference is greater than the second humidity difference and the second humidity difference is greater than the third humidity difference, set it as the upper layer dominant humidification mode, when the third humidity difference is greater than the second humidity difference and the second humidity difference is greater than the first humidity difference, set it as the lower layer dominant humidification mode, otherwise there is no obvious dominance, generate a dominance judgment; When the difference between the maximum and minimum of the three humidity difference values is less than 2% relative humidity, it is set to the uniform distribution mode, when the amplitude of change of any difference value in 10 consecutive measurements exceeds the average by 30% or the amplitude of change of two or more difference values simultaneously exceeds the average by 20%, it is set to the oscillation mode, otherwise it is in the normal state, and the distribution state judgment is generated; A two-dimensional judgment matrix is generated according to the dominant judgment and the distribution state judgment as the moisture change in the box.

[0042] In some embodiments, three layers of humidity sensor arrays are installed in the vertical direction of the air inlet and outlet respectively, the air inlet sensors are located at the upper, middle and lower three height positions respectively, which are 0.2 meters inward from the air inlet plane, and the outlet sensors are located at the corresponding positions respectively, which are 0.2 meters inward from the air outlet plane, to ensure that the sensors can accurately monitor the humidity change in the airflow without being affected by the boundary effect. For example, in a test box with a height of 3 meters, the upper layer sensor of the air inlet is located at 0.3 meters from the top of the box, the middle layer sensor is located at 1.5 meters from the top of the box, and the lower layer sensor is located at 2.7 meters from the top of the box, and the outlet sensor uses the same height configuration. Each sensor uses a fast response humidity sensor with a response time of less than 3 seconds and an accuracy of better than ±2%RH, and is equipped with a protective cover to avoid direct airflow impact on measurement accuracy. The system starts a dedicated time sequence controller and strictly follows a 5-second cycle for alternating sampling, with the sampling sequence designed as follows: the first second samples the upper layer of the air inlet and the lower layer of the outlet, the second second samples the middle layer of the air inlet and the middle layer of the outlet, the third second samples the lower layer of the air inlet and the upper layer of the outlet, and the fourth and fifth seconds are for data processing and storage, and then the next cycle begins. This alternating sampling method is based on the physical characteristics of the airflow path in the spiral flow field, that is, the airflow at the upper layer of the air inlet mainly flows out from the lower layer of the outlet after spiral motion, the airflow at the lower layer of the air inlet mainly flows out from the upper layer of the outlet after spiral upward, and the middle layer airflow is relatively stable and flows out from the middle layer. By this cross-paired sampling method, the system can truly track the complete humidity change process of the same airflow from entering to flowing out, avoiding the systematic error caused by the mismatch of airflow path in the traditional same layer comparison method.

[0043] The three humidity difference values in the embodiment are calculated as follows: the first humidity difference value = the upper inlet humidity - the lower outlet humidity, the second humidity difference value = the middle inlet humidity - the middle outlet humidity, and the third humidity difference value = the lower inlet humidity - the upper outlet humidity. For example, the sampling results show that the upper, middle and lower inlet humidities are 60% RH, 58% RH and 62% RH, and the lower, middle and upper outlet humidities are 65% RH, 63% RH and 67% RH, respectively. The three humidity difference values are -5% RH, -5% RH and -5% RH, respectively. A negative value indicates that the humidity increases during the airflow through the box, and a positive value indicates that the humidity decreases. Based on the three difference values, the dominant judgment is made. When the first humidity difference value is greater than the second humidity difference value and the second humidity difference value is greater than the third humidity difference value, i.e. -5 > -5 and -5 > -5, the condition is not met, so it is not an upper dominant mode. When the third humidity difference value is greater than the second humidity difference value and the second humidity difference value is greater than the first humidity difference value, i.e. -5 > -5 and -5 > -5, the condition is also not met, so it is not a lower dominant mode, and it is determined that there is no obvious dominant. If the measurement results are 2% RH, 0% RH and -3% RH for the first humidity difference value, the second humidity difference value and the third humidity difference value, respectively, the condition 2 > 0 and 0 > -3 is met, and it is determined that the upper dominant humidification mode is met, indicating that the upper airflow path has the strongest dehumidification effect, the middle layer is the second, and the lower layer is the weakest or even humidification occurs.

[0044] It should be noted that the logic of the dominant judgment is based on the different interaction degrees of airflow at different heights in the spiral flow field and the heat and humidity sources inside the box. The upper dominant usually indicates that there is a strong heat source or dehumidification device in the upper part of the box, and the lower dominant indicates that there is a strong humidity source or humidification device in the lower part of the box.

[0045] The distribution state judgment adopts a double-checking mechanism. Firstly, the maximum-minimum difference of the three humidity differences is calculated. When the difference is less than 2% relative humidity, it is set as a uniform distribution mode. For example, the three differences are 1.8% RH, 2.1% RH and 1.9% RH, the maximum-minimum difference is 2.1-1.8=0.3% RH<2% RH, and it is determined as a uniform distribution mode, indicating that the humidity change trends of the air flows of each layer are basically consistent, and the humidity distribution in the box is relatively uniform. Secondly, the oscillation state is checked. The system records 10 consecutive measurement results, calculates the average value of each difference in the 10 measurements, and calculates the change amplitude of each measurement value relative to the average value. For example, the average value of the first humidity difference in 10 measurements is 2.0% RH, and the measurement value is 3.2% RH, and the change amplitude is |3.2-2.0| / 2.0x100%=60%, which exceeds the threshold of 30%, and is marked as single-point oscillation. When two or more differences simultaneously have a change amplitude exceeding 20%, it is determined as an oscillation mode. For example, the first difference change amplitude is 25%, and the second difference change amplitude is 22%, both of which exceed 20%, and it is determined as an oscillation mode, indicating that the humidity distribution in the box is in an unstable state, and there may be air flow turbulence or equipment operation abnormality. In addition to the uniform distribution and oscillation modes, other cases are classified as normal state.

[0046] The generation of the two-dimensional judgment matrix in the method combines the dominant judgment and the distribution state judgment to form a 3x3 matrix structure. The dominant judgment includes upper layer dominance, lower layer dominance, and no obvious dominance. The distribution state judgment includes uniform distribution, oscillation, and normal state. The two are combined to form nine possible working condition modes. For example, the judgment result of one time is upper layer dominance+uniform distribution, which is marked as (1, 1) in the matrix, indicating that the upper air flow path dominates the overall humidity change and the distribution is relatively uniform. Another judgment result is no obvious dominance+oscillation, which is marked as (3, 2) in the matrix, indicating that there is no obvious difference in the humidity change of each layer of air flow, but the overall state is unstable. The system will count the frequency of occurrence of various working condition modes within a certain time window (such as 10 minutes) to form a dynamic working condition distribution map, which provides a basis for subsequent control strategy selection. When a certain working condition mode appears continuously for more than a set number of times, the system will trigger the corresponding automatic adjustment program. For example, when the upper layer dominance+normal state appears continuously for 5 times, the lower humidifier is started to balance the humidity distribution; when the oscillation mode appears continuously for 3 times, the spiral flow field parameters are adjusted to stabilize the air flow state.

[0047] Further, step S4 includes the following steps: Step S41: measure the heater output power, the cooler output power and the box wall temperature difference every 15 seconds. The heater power is recorded as a positive value, the cooler power is recorded as a negative value, and the sum of the two is the current net input power; In some embodiments, a multi-path power monitoring system is employed to synchronously collect real-time power data of the heater and the refrigerator and the temperature data of the inner and outer walls of the box every 15 seconds. The heater power is directly measured by a high-precision power meter, including the total power output of various heating devices such as resistance heaters and infrared heaters, and the measurement accuracy is required to be ±1% to ensure the calculation accuracy. For example, a certain measurement shows that the resistance heater outputs 1.8 kW and the infrared heater outputs 0.7 kW, so the total power of the heater is 2.5 kW, which is recorded as a positive value +2.5 kW in the system. The measurement of the refrigerator power is relatively complex, which needs to be calculated by the compressor current, voltage and system efficiency coefficient to obtain the actual refrigeration power output, or by the refrigerant flow and temperature difference to calculate the refrigeration capacity. For example, the input electric power of the compressor is 1.2 kW, and the system refrigeration efficiency coefficient COP is 3.0, so the actual refrigeration power output is 1.2x3.0=3.6 kW, which is recorded as a negative value -3.6 kW in the system. The temperature difference of the box wall is measured by high-precision temperature sensors attached to the inner and outer walls of the box, the sensors should be platinum resistance temperature sensors with response time less than 5 seconds and accuracy better than ±0.1℃, and should be arranged at multiple positions to obtain the average temperature difference value. For example, the average temperature of the inner wall of the box is 25.2℃, and the average temperature of the outer wall is 22.8℃, so the temperature difference of the box wall is 25.2-22.8=2.4℃. The calculation formula of the current net input power is: net input power=heater power+refrigerator power, i.e. 2.5+(-3.6)=-1.1kW, the negative value indicates that the refrigeration power is greater than the heating power, and the system as a whole is in the refrigeration state.

[0048] Step S42: calculate the heat dissipation power of the box according to the temperature difference of the box wall and the pre-acquired surface area of the box, add the current net input power and the heat dissipation power of the box to obtain the energy balance state, when the energy balance state is positive, it indicates that the temperature inside the box tends to rise, when the energy balance state is negative, it indicates that the temperature inside the box tends to fall, and when the energy balance state is close to zero, it indicates that the temperature tends to be stable; In some embodiments, the heat dissipation power calculation is based on the basic principles of heat transfer, and the formula is: heat dissipation power=heat transfer coefficientxbox surface areaxbox wall temperature difference. The surface area of the box needs to be accurately measured in advance and stored in the system parameters, including all the outer surface area of the box, for a cylindrical test box, the surface area is , where r is the radius and h is the height. For example, a cylindrical test box with a radius of 1 meter and a height of 3 meters, the surface area is . The heat transfer coefficient needs to be determined according to the box material, the thickness of the insulation layer, the environmental conditions and other factors, which is usually obtained by field calibration, generally in the range of 2-8 W / (m 2 ·℃). Assuming that the heat transfer coefficient is 4 W / (m 2For example, if the net input power is 1.5 kW and the heat dissipation power is 0.3 kW, the energy balance state is 1.5 + 0.3 = 1.8 kW, indicating that the temperature in the box tends to rise. When the energy balance state is close to zero, such as in the range of -0.05 kW to +0.05 kW, it indicates that the heat input and output are basically balanced, and the temperature tends to be stable.

[0049] Step S43: Subtract the box overall temperature state value in the box overall temperature and humidity state from the target temperature value to obtain a temperature deviation; generate a power input curve in combination with the energy balance state and the temperature deviation.

[0050] In some embodiments, the box overall temperature state value is compared with a preset target temperature value, for example, the box overall temperature state value is 25.12°C and the target temperature value is 25.00°C, then the temperature deviation is 25.12-25.00 = +0.12°C, the positive value indicates that the actual temperature is higher than the target temperature, and the refrigeration needs to be increased or the heating needs to be reduced. The generation of the power input curve comprehensively considers various factors such as the current energy balance state, the temperature deviation, the historical control effect, and the system response characteristics. The system uses a predictive control algorithm, predicts the temperature change trend based on the current energy balance state, determines the required adjustment intensity based on the temperature deviation, and corrects the control parameters based on historical data. For example, the current energy balance state is -0.86 kW (temperature decreasing trend), and the temperature deviation is +0.12°C (temperature needs to be reduced), and the two directions are consistent, indicating that the current control direction is correct but the intensity may be insufficient. The system will calculate the additional refrigeration power required to reach the target temperature, assuming that about 3 kW of power adjustment is required for every 1°C temperature difference, then the additional refrigeration power required is 0.12 x 3 = 0.36 kW. Considering that there is already a refrigeration trend of 0.86 kW, the system can maintain the current power setting or slightly reduce the refrigeration power to avoid over-adjustment. The power input curve usually predicts the power demand for the next 10-15 minutes, with one time node per minute, forming a piecewise linear power change curve. For example, the generated curve can show that the refrigerator power is maintained at 3.6 kW for the first 3 minutes, reduced to 3.2 kW for the next 3 minutes, and further reduced to 2.8 kW for the next 3 minutes, and the heater power remains at 2.5 kW throughout the process.

[0051] It should be noted that the generation of the power input curve needs to consider the thermal inertia and response delay of the system. The heating system usually responds quickly (30-60 seconds), while the refrigeration system responds slowly (60-180 seconds), so the corresponding time needs to be adjusted in the design of the curve to avoid overshoot caused by control lag.

[0052] It should also be noted that the generation of the power input curve also needs to consider the device operation constraints and safety limits. For example, the compressor of the refrigerator cannot be frequently started and stopped, and the minimum running time is usually 5 minutes and the minimum downtime is 3 minutes, so the power curve needs to avoid generating too frequent switching actions. Although the heater responds quickly, excessive power changes will cause temperature fluctuations, so the power change rate is usually limited to no more than 10% of the total power per minute. When the temperature deviation is large (such as more than 1℃), the system will start the fast adjustment mode, allowing larger power change amplitude and shorter adjustment period; when the temperature deviation is small (such as less than 0.2℃), the system will switch to the fine adjustment mode, using a small amplitude, gradual power adjustment strategy. For different types of test boxes, the generation strategy of the power input curve will also be different, for example, the constant temperature and humidity test chamber needs to consider the coupling effect of temperature and humidity, the high and low temperature impact test chamber needs to consider the power demand of rapid temperature change, and the long-term stability test chamber pays more attention to energy saving and equipment life. It should be noted that the power input curve is a dynamic prediction result, which will be recalculated and updated according to the latest measurement data every control period. This rolling prediction method enables the control system to respond to environmental changes and load disturbances in a timely manner, significantly improving the accuracy and stability of temperature control. Compared with the traditional PID control method, this prediction control method based on energy balance analysis can reduce overshoot and oscillation, and shorten the time to reach a stable state.

[0053] Further, step S5 comprises the following steps: Adjusting the output power of the heater and the refrigerator based on the time node of the power input curve to generate temperature control execution instructions; In some embodiments, the generation of temperature control execution instructions is strictly in accordance with the power input curve, and the system establishes a precise time node control mechanism, checking the power setting value corresponding to the current time every minute and comparing it with the actual device output power. For example, the power input curve shows that the heater should output 2.2kW and the chiller should output 3.0kW at the 5th minute, while the actual measurement shows that the heater outputs 2.3kW and the chiller outputs 2.8kW, and the system will immediately generate power adjustment instructions: reduce the heater power by 0.1kW to 2.2kW and increase the chiller power by 0.2kW to 3.0kW. Temperature control execution instructions contain device number, target power value, adjustment time, priority and other information, which are sent to the corresponding execution device through the industrial communication bus. For multiple groups of heaters or chillers, the system will allocate power load according to the location distribution and control accuracy requirements of each group of devices, for example, allocate 2.2kW of heating demand to 3 groups of heaters: 0.8kW in the upper layer, 0.7kW in the middle layer, and 0.7kW in the lower layer, to ensure the uniformity of temperature distribution.

[0054] It should be noted that the execution of power adjustment instructions needs to consider the response characteristics of different devices, and the response time of resistance heater is about 30 seconds, and the response time of compressor chiller is about 90 seconds, so the instruction sending time needs to be advanced by the corresponding response time to ensure that the power adjustment corresponds to the time node accurately.

[0055] According to the change of water content in the box, humidification and dehumidification control is executed, the lower humidifier is started when the display shows that the lower layer is dominant and uniformly distributed, the power of the humidifier and the dehumidifier is adjusted when the display shows oscillation state, and the humidifier and the dehumidifier are adjusted to balance control when the display shows oscillation state, generating humidity control execution instructions; In some embodiments, the generation of the humidity control execution instruction is based on a two-dimensional judgment matrix, and the system selects a corresponding control strategy according to the combined results of the dominant judgment and the distribution state judgment. When the judgment matrix shows that the upper layer is dominant and uniformly distributed, it means that the dehumidification effect of the upper air flow path is the strongest, and the system will start the upper dehumidifier to enhance the dehumidification effect, while reducing the power of the lower dehumidifier or starting the lower humidifier for balance adjustment. For example, the power of the upper dehumidifier is set to 120% of the standard power, the power of the lower humidifier is set to 80% of the standard power, and the middle layer equipment maintains normal power operation. When it shows that the lower layer is dominant and uniformly distributed, it means that the humidity change of the lower air flow path is the most significant, and the system will adjust the operating parameters of the lower equipment accordingly, and start the lower humidifier or dehumidifier to compensate according to the humidity change direction. When it shows an oscillation state, it means that the humidity distribution in the box is in an unstable state, and the system will adjust the power of the humidifier and dehumidifier at the same time to achieve dynamic balance control, for example, all humidifiers are reduced to 60% of the standard power, all dehumidifiers are reduced to 70% of the standard power, and the response frequency of the equipment start-stop is increased, and through fast and small adjustment, the humidity distribution is stabilized. When it shows no obvious dominant and normal state, the system maintains the current operating state of each device, and only fine tunes according to the overall humidity deviation.

[0056] Based on the overall temperature and humidity state of the box, the system stability is judged, and the system stability symbol is obtained; In some embodiments, the system stability determination is based on the change characteristics of the overall temperature and humidity state of the chamber, and a multi-parameter comprehensive evaluation method is adopted. The system continuously monitors the change range of the overall temperature and humidity state values of the chamber. When the continuous three calculation results show that the temperature change range is less than 0.1°C and the humidity change range is less than 1%RH, the system stability flag is generated. For example, the temperature state values of the last three times are 25.02°C, 25.04°C and 25.01°C, and the change ranges are 0.02°C, 0.03°C, respectively, which are less than the 0.1°C threshold. The humidity state values are 60.2%RH, 60.5%RH and 60.1%RH, and the change ranges are 0.3%RH and 0.4%RH, respectively, which are less than the 1%RH threshold. The system sets the stability flag to "stable" state. In addition to the change range judgment, the system also analyzes the change trend of the temperature and humidity state values. When a continuous rising or falling trend is found, even if the change range is within the threshold range, the setting of the stability flag will be delayed to avoid misjudgment as a stable state during the change process. The system also considers the energy balance state and the stability of the two-dimensional judgment matrix. When the energy balance state fluctuates within ±0.1kW and the two-dimensional judgment matrix continuously shows the same mode for more than 10 minutes, the system stability is further confirmed. Once the stability flag is set, it will be maintained for at least 5 minutes to avoid frequent switching caused by accidental disturbance. When the temperature and humidity state deviates from the target value by more than the set threshold (temperature ±0.3°C, humidity ±2%RH), the system will immediately reset the stability flag and re-enter the fast regulation mode.

[0057] When the system stability flag shows stable, the execution frequency of the temperature control execution instruction and the humidity control execution instruction is reduced, otherwise the temperature control execution instruction and the humidity control execution instruction are executed at the original frequency to achieve coordinated and stable control of the temperature and humidity in the test chamber.

[0058] In some embodiments, when the system stability flag shows stable, the execution frequency of temperature control execution instructions is reduced from the standard of once per minute to once every 2 minutes, the execution frequency of humidity control execution instructions is reduced from once per minute to once every 3 minutes, and the power adjustment amplitude is reduced to 50% of the normal state. In the stable state, the heater power adjustment amplitude is limited from ±0.2 kW to ±0.1 kW, and the refrigerator power adjustment amplitude is limited from ±0.3 kW to ±0.15 kW, reducing unnecessary power fluctuations. The data acquisition frequency is also reduced accordingly, from once every 15 seconds to once every 30 seconds, reducing the system computing load. When the system stability flag shows unstable, all control instructions are executed at the original frequency to ensure fast response capability. The system also has an emergency mode, when the temperature and humidity deviation exceeds the emergency threshold (temperature ±1℃, humidity ±5%RH), the control frequency is increased to once every 30 seconds, and the power adjustment amplitude is increased to 150% of the normal state, achieving rapid correction. The frequency adjustment process uses gradual switching to avoid sudden frequency changes affecting system stability, for example, when adjusting from once per minute to once every 2 minutes, it will first go through 90-second and 120-second intermediate transition stages.

[0059] The present application also provides a test chamber temperature and humidity control system for executing the test chamber temperature and humidity control method as described above, the test chamber temperature and humidity control system comprising: a flow field generation module for setting a plurality of tangential air inlets in a circumferential distribution on the top of the test chamber, and forming a spiral flow field from top to bottom in the chamber by adjusting the air speed and direction of each air inlet; a data correction module for arranging a plurality of measurement points along the airflow path of the spiral flow field, each measurement point measuring the air speed, temperature and humidity at the current position; correcting the temperature and humidity readings according to the measured air speed to obtain corrected temperature and humidity data; a state analysis module for weighting the corrected temperature and humidity data according to the volume weight of the test chamber it is in to calculate the overall temperature and humidity state of the chamber; measuring the humidity difference between the air inlet and the air outlet and combining the air speed to calculate the water content change in the chamber; a power prediction module for predicting the heater and refrigerator power input curve required to reach the target temperature by real-time monitoring of the heater power, refrigerator power and chamber wall temperature difference combined with the overall temperature and humidity state of the chamber; an equipment control module for controlling the heater and refrigerator according to the power input curve, and controlling the humidifier and dehumidifier according to the water content change in the chamber to achieve stable control of the temperature and humidity in the test chamber.

[0060] Reference is made to Fig. 3As shown, in this embodiment, the spiral flow field multi-point measurement and intelligent control system V2.1 displays that the current temperature is 25.25℃, the current humidity is 62.0%RH, the temperature deviation is +0.25℃ and the humidity deviation is +2.0%RH, relative to the target temperature 25.00℃ and the target humidity 60.0%RH. The system stability monitoring shows a stable state, and the progress bar is displayed in full green, indicating that the change range of the temperature and humidity state values for three consecutive times is within the set threshold range. The test chamber structure diagram shows that the 12-point spiral distribution of the measurement points is arranged, wherein the temperature distribution range is 1.2℃, which does not exceed the set threshold of 3℃, and the humidity distribution range is 9%RH, which exceeds the set threshold of 8%RH and is marked as an out-of-standard state. The sensor state monitoring shows that the temperature sensor #1 reads 24.8℃, the temperature sensor #2 reads 25.2℃, the humidity sensor #1 reads 63%RH, and the humidity sensor #2 reads 58%RH, and the operation state of each sensor is normal. The moisture change judgment matrix area shows that the dominant judgment is "no obvious dominance", the distribution state judgment is "oscillation mode", and the three humidity difference values are all-5%RH, i.e. the humidity difference values of the upper, upper-middle, and lower-upper airflow paths are equal, which meets the judgment condition of no obvious dominance. Due to the out-of-standard humidity distribution, the system automatically switches to the oscillation mode processing. The power input curve prediction shows that the heater power is set to 2.5kW, the cooler power is set to-3.6kW, and the current energy balance state is-0.86kW, indicating that the system as a whole is in a cooling state. The control execution instruction panel shows that the adjustment of heating, cooling, humidification and dehumidification four control options are in the operable state, the execution frequency is set to every 2 minutes, and the control mode is stable mode. The equipment operation state shows that the current output power of the upper heater is 0.8kW, and the system automatically adjusts the operation parameters of each device according to the current two-dimensional judgment matrix state, realizing the intelligent temperature and humidity coordinated control based on multi-parameter comprehensive judgment.

[0061] The application further provides a computer storage medium storing a computer program, which, when executed, implements the test chamber temperature and humidity control method of any one of the above.

[0062] Therefore, from any point of view, the embodiments should be regarded as exemplary and non-limiting, the scope of the application being defined by the appended claims rather than the above description, and it is intended to encompass all variations falling within the meaning and scope of the equivalent elements of the application file.

[0063] The foregoing is considered as illustrative only of the principles of the application. Numerous modifications and changes will readily occur to those skilled in the art, and it is intended to embrace all such modifications and changes that fall within the scope of the application. Accordingly, the application is not to be restricted in scope to the specific embodiments disclosed herein but is to be accorded the full scope that the principles and novel features request appropriately granted.

Claims

1. A method for controlling temperature and humidity in a test chamber, characterized in that: The following steps are involved: Step S1: multiple circumferentially distributed tangential air inlets are provided on the top of the test chamber, and a spiral flow field from top to bottom is formed in the chamber by adjusting the wind speed and direction of each air inlet; Step S2: Arranging multiple measurement points along the airflow path of the spiral flow field, each measuring point measures the wind speed, temperature, and humidity at the current location; correcting the temperature and humidity readings based on the measured wind speed to obtain corrected temperature and humidity data; Step S3: Weighting the corrected temperature and humidity data according to the volume weight of the test chamber in which it is located to calculate the overall temperature and humidity status of the chamber; measuring the humidity difference between the air inlet and the air outlet and calculating the moisture change in the chamber in combination with the wind speed; Step S4: Predicting the power input curves of the heater and cooler required to achieve the target temperature by combining the real-time monitored heater power, cooler power, and box wall temperature difference with the overall temperature and humidity status of the box; Step S5: Control the heater and the cooler according to the power input curve, and control the humidifier and the dehumidifier according to the change of moisture in the box to achieve stable control of the temperature and humidity in the test box.

2. The method for controlling temperature and humidity in a test chamber according to claim 1, wherein: Step S2 includes the following steps: Multiple measurement points are arranged along the airflow path of the spiral flow field. Data is collected at each measurement point at preset intervals. The current wind speed, temperature, and humidity values ​​are recorded in sequence and temporarily stored in the data buffer of the measurement point. Each buffer retains the most recent 20 measurement records. Take out the five most recent consecutive wind speed measurements from the measurement point data buffer, calculate the average value of the five wind speed measurements and the difference between the maximum and minimum values, and record them as the wind speed mean and wind speed difference; When the wind speed difference is greater than or equal to 10% of the average wind speed, wait for the next measurement cycle to make another judgment; When the wind speed difference is less than 10% of the average wind speed, the current wind speed is determined to be stable, and a correction operation is performed on the current temperature and humidity measurement values ​​to obtain the corrected temperature and humidity data.

3. The method for controlling temperature and humidity in a test chamber according to claim 2, wherein: The correction operation for the current temperature measurement value and humidity measurement value is specifically performed as follows: According to the average wind speed value of the current measurement point, the correction parameter comparison table pre-established at the measurement point is searched and located, and the corresponding temperature correction coefficient and humidity preliminary correction coefficient are extracted; Multiply the temperature correction coefficient by the difference between the current temperature measurement and 20°C to obtain the temperature correction value; Add the temperature correction amount to the current temperature measurement value to obtain the corrected temperature value; Multiply the humidity initial correction coefficient by the difference between the current humidity measurement value and 50% relative humidity to obtain the humidity wind speed correction value, and add the humidity wind speed correction value to the current humidity measurement value to record it as the wind speed initial correction humidity value; According to the corrected temperature value, the preset humidity-temperature correlation correction table is matched to obtain the temperature correlation correction coefficient; Multiply the temperature correlation correction coefficient by the difference between the corrected temperature value and 25°C to obtain the humidity temperature correction value, and add the humidity temperature correction value to the initial wind speed correction humidity value to obtain the corrected humidity value; The corrected humidity value and the corrected temperature value are used as the corrected temperature and humidity data of the measuring point.

4. The method for controlling temperature and humidity in a test chamber according to claim 3, wherein: In step S3, the corrected temperature and humidity data are weighted according to the volume weight of the spiral flow field position where the data is located, and the overall temperature and humidity state of the box is calculated to include: Measure the height and inner diameter of the test chamber and calculate the total volume of the chamber; Taking the vertical center axis of the box as the reference, measure the radial distance from each measuring point to the center axis; The volume of the cylindrical ring represented by each measuring point is calculated based on the radial distance from each measuring point to the central axis. The calculation formula for the cylindrical ring volume is: Where, is the volume of the cylindrical ring represented by each measurement point, The radial distance from each measuring point to the center axis of the test chamber, is a fixed offset, is the thickness of the height layer at each measuring point; Calculate the ratio of the volume of the cylindrical ring to the total volume of the box as the volume weight coefficient of each measuring point; The overall temperature and humidity status of the box is calculated using the corrected temperature and humidity data and the volume weight coefficient.

5. The method for controlling temperature and humidity in a test chamber according to claim 4, wherein: The overall temperature and humidity state of the box is calculated using the corrected temperature and humidity data and the volume weight coefficient as follows: Calculate the sum of the volume weight coefficients corresponding to all measurement points in the test chamber, and verify the coverage of the cylindrical ring volume represented by the measurement point based on the absolute difference between the sum of the volume weight coefficients and 1. If the absolute difference is less than the preset threshold, perform weighted calculation, otherwise issue a weight abnormality alarm; The weighted calculation is as follows: The difference between the maximum and minimum values ​​of the corrected temperature value of each measuring point is calculated as the temperature distribution range, and the difference between the maximum and minimum values ​​of the corrected humidity value of each measuring point is calculated as the humidity distribution range; When the temperature distribution range exceeds 3°C, adjust the wind speed distribution ratio of each air inlet of the spiral flow field so that the wind speed of the radial inner air inlet increases and the wind speed of the radial outer air inlet decreases, while keeping the total air intake unchanged; When the humidity distribution range exceeds 8% relative humidity, adjust the humidifier nozzle to the area where the humidity value is higher than the average level; Multiply the corrected temperature value of each measuring point by the corresponding volume weight coefficient and sum them to obtain the overall temperature state value of the box; multiply the corrected humidity value of each measuring point by the corresponding volume weight coefficient and sum them to obtain the overall humidity state value of the box; calculate the overall temperature state value and overall humidity state value of the box every 30 seconds; When the change amplitude of the overall temperature state value of the cabinet is less than 0.1℃ and the change amplitude of the overall humidity state value of the cabinet is less than 1% relative humidity for three consecutive times, the system stability flag is set and the overall temperature and humidity state of the cabinet is obtained.

6. The method for controlling temperature and humidity in a test chamber according to claim 5, characterized in that: In step S3, the difference in humidity between the air inlet and the air outlet is measured and the moisture change in the box is calculated based on the wind speed. The steps include: Humidity sensors are installed on the upper, middle and lower layers of the air inlet in the vertical direction, and the same configuration is used for the air outlet; Start the timing controller and alternately sample at a 5-second cycle. Read the upper layer data of the air inlet and the lower layer data of the air outlet as the first humidity difference, read the middle layer data of the air inlet and the middle layer data of the air outlet as the second humidity difference, and read the lower layer data of the air inlet and the upper layer data of the air outlet as the third humidity difference. When the first humidity difference is greater than the second humidity difference and the second humidity difference is greater than the third humidity difference, the upper layer dominant humidification mode is set; when the third humidity difference is greater than the second humidity difference and the second humidity difference is greater than the first humidity difference, the lower layer dominant humidification mode is set; otherwise, there is no obvious dominance, and a dominant judgment is generated; When the difference between the maximum and minimum values ​​of the three humidity differences is less than 2% relative humidity, it is set to uniform distribution mode. When the change amplitude of any difference value exceeds 30% of the average value in 10 consecutive measurements, or the change amplitude of two or more differences exceeds 20% of the average value at the same time, it is set to oscillation mode. Otherwise, it is normal and the distribution state judgment is generated. A two-dimensional judgment matrix is ​​generated based on the dominant judgment and distribution state judgment as the moisture change situation in the box.

7. The method for controlling temperature and humidity in a test chamber according to claim 6, wherein: Step S4 includes the following steps: Step S41: Measure the heater output power, the refrigerator output power, and the temperature difference between the cabinet and the wall every 15 seconds, record the heater power as a positive value and the refrigerator power as a negative value, and add the two to obtain the current net input power; Step S42: Calculate the heat dissipation power of the cabinet based on the cabinet wall temperature difference and the pre-acquired cabinet surface area. Add the current net input power to the cabinet heat dissipation power to obtain the energy balance state. When the energy balance state is positive, it indicates that the temperature inside the cabinet tends to rise. When the energy balance state is negative, it indicates that the temperature inside the cabinet tends to fall. When the energy balance state is close to zero, it indicates that the temperature tends to be stable. Step S43: subtracting the overall temperature state value of the cabinet in the overall temperature and humidity state of the cabinet from the target temperature value to obtain a temperature deviation; and generating a power input curve by combining the energy balance state and the temperature deviation.

8. The method for controlling temperature and humidity in a test chamber according to claim 7, characterized in that: Step S5 includes the following steps: Adjust the output power of the heater and the cooler based on the time nodes of the power input curve and generate temperature control execution instructions; Execute humidification and dehumidification control according to the moisture changes in the box. When the lower layer is dominant and evenly distributed, start the lower layer humidifier. When the display shows an oscillation state, adjust the power of the humidifier and dehumidifier at the same time. When the display shows an oscillation state, adjust the humidifier and dehumidifier at the same time for balance control and generate humidity control execution instructions. Determine the system stability based on the overall temperature and humidity status of the box and obtain the system stability mark; When the system stability mark shows stable, reduce the execution frequency of the temperature control execution instruction and the humidity control execution instruction. Otherwise, execute the temperature control execution instruction and the humidity control execution instruction at the original frequency to achieve coordinated and stable control of the temperature and humidity in the test chamber.

9. A temperature and humidity control system for a test chamber, characterized in that: Used to execute the test chamber temperature and humidity control method according to claim 1, the test chamber temperature and humidity control system comprises: The flow field generation module is used to set multiple circumferentially distributed tangential air inlets on the top of the test chamber, and to form a top-down spiral flow field in the chamber by adjusting the wind speed and direction of each air inlet; A data correction module is used to arrange multiple measurement points along the airflow path of the spiral flow field, each measuring point measuring the wind speed, temperature and humidity at the current location; the temperature and humidity readings are corrected according to the measured wind speed to obtain corrected temperature and humidity data; The state analysis module is used to weight the corrected temperature and humidity data according to the volume weight of the test chamber to calculate the overall temperature and humidity state of the chamber; measure the humidity difference between the air inlet and outlet and calculate the moisture change in the chamber based on the wind speed; The power prediction module is used to predict the power input curves of the heater and cooler required to achieve the target temperature by combining the real-time monitored heater power, cooler power and box wall temperature difference with the overall temperature and humidity status of the box; The equipment control module is used to control the heater and cooler according to the power input curve, and control the humidifier and dehumidifier according to the changes in moisture in the box to achieve stable control of temperature and humidity in the test chamber.

10. A computer storage medium storing a computer program, characterized in that: When the computer program is executed, the method for controlling temperature and humidity in a test chamber according to any one of claims 1 to 8 is implemented.

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