Filter membrane constant temperature and humidity weighing method and system

Abstract

The present invention relates to the field of filter membrane weighing technology, and the present invention relates to a filter membrane constant temperature and humidity weighing method and system, the method comprising: after the humidity in a constant temperature and humidity chamber reaches a set value for the first time, recording the humidity value within a set time to form a humidity curve graph; calculating the corresponding humidity extreme time interval, summing and normalizing all humidity extreme time intervals to obtain the length of the humidity change cycle in the constant temperature and humidity chamber; based on the current moment, obtaining the relative position of the humidity at the current moment in the humidity change cycle; selecting a window with a size equal to the length of the humidity change cycle, and using a weighted average method to obtain the predicted humidity value at the next moment of the current moment; and based on the predicted humidity value at the next moment, performing humidity control on the constant temperature and humidity chamber. The present invention can perform humidity control on the constant temperature and humidity chamber in advance, reduce humidity fluctuations caused by system hysteresis, and improve the accuracy of the filter membrane weighing result.

Description

Technical Field

[0001] The invention relates to the technical field of filter membrane weighing, and also to a filter membrane constant temperature and humidity weighing method and system. Background Art

[0002] In the process of environmental monitoring and air quality analysis, accurately weighing the filter membrane is a key step, because by measuring the weight of air particles collected on the filter membrane, the air quality can be effectively evaluated. Since changes in temperature and humidity will affect the accuracy of weighing, in order to accurately evaluate air quality, it is usually necessary to weigh the filter membrane in a constant temperature and humidity chamber. The composite dehumidification technology, which combines silica gel dehumidification and molecular sieve dehumidification, is used to adjust the humidity in the constant temperature and humidity chamber to maintain the humidity in the constant temperature and humidity chamber, which can improve the accuracy of weighing the filter membrane.

[0003] At present, the patent application document with the publication number CN106908363A discloses a particle sampling and weighing system and method based on cloud computing technology, including preparing and encoding blank filter membranes, using RFID technology for unique identification; establishing a connection between the computer, the cloud and the automatic weighing system, and automatically saving the initial weight of the filter membrane to the local and cloud databases; placing the filter membrane in the sampler; remotely controlling the sampler to replace the filter membrane; weighing the filter membrane again after sampling and saving the data; using the information such as the weight before and after, environmental parameters, etc., to calculate the particle concentration through the algorithm software. Among them, the automatic weighing equipment is placed in a constant temperature and humidity control cabinet to maintain constant humidity and humidity.

[0004] The above-mentioned constant temperature and humidity control cabinet takes a certain amount of time to monitor humidity changes, complete adjustments, and stabilize the internal humidity. This hysteresis may cause the humidity inside the control cabinet to fluctuate in a short period of time, and the humidity fluctuation may affect the weight of the filter membrane, especially in the case of high-precision weighing. Therefore, the hysteresis of the constant temperature and humidity control cabinet will reduce the accuracy of the filter membrane weighing results. Summary of the invention

[0005] In order to solve the technical problem that the hysteresis of the above-mentioned constant temperature and humidity control cabinet will reduce the accuracy of the filter membrane weighing result, the present invention provides solutions in the following aspects.

[0006] In a first aspect, a filter membrane constant temperature and humidity weighing method comprises:

[0007] After the humidity in the constant temperature and humidity chamber reaches the set value for the first time, the humidity value within the set time is recorded to form a humidity curve graph;

[0008] Based on all humidity values, the corresponding humidity extreme time intervals are calculated, and all humidity extreme time intervals are summed and normalized to obtain the length of the humidity change cycle in the constant temperature and humidity chamber;

[0009] If the humidity at the current moment is in the rising stage, obtain the relative position of the humidity at the current moment in the rising part of the humidity change cycle; otherwise, obtain the relative position of the humidity at the current moment in all parts of the humidity change cycle;

[0010] A window of a size equal to the length of the humidity change cycle is selected, and a predicted humidity value at the next moment of the current moment is obtained by using a weighted average method; wherein the absolute value of the difference between the humidity value at the current moment and the humidity value at any moment before the current moment is calculated, and the absolute value is used as a weight adjustment factor of the weighted average method;

[0011] Based on the predicted humidity value at the next moment, the humidity of the constant temperature and humidity chamber is controlled.

[0012] The present invention first obtains a humidity curve graph, provides an intuitive way to observe and analyze the changing trend of humidity over time, determines the length of the humidity change cycle by analyzing the regularity of humidity changes, determines its specific position in the cycle by judging whether the current humidity is in an ascending stage or a descending stage, and uses a weighted average method and a dynamically updated weight mechanism to improve the humidity prediction accuracy at the next moment, thereby effectively solving the hysteresis problem of the constant temperature and humidity control box and improving the accuracy of filter membrane weighing.

[0013] Preferably, before forming the humidity curve graph, the method further includes: smoothing the humidity data using a Bezier curve fitting method.

[0014] By smoothing, the overall trend of humidity changes can be shown more clearly, rather than being disturbed by individual humidity fluctuations.

[0015] In one embodiment, the humidity variation cycle is:

[0016] When collecting humidity values ​​within the set time, select the first humidity rise point as the starting point of the humidity change cycle;

[0017] Starting from the starting point, it rises and falls and finally returns to the humidity level of the starting point, forming a complete humidity change cycle.

[0018] By selecting the first occurrence of a humidity rise as the start of the cycle and tracking it until the humidity returns to the starting level, a cyclical pattern in humidity change can be identified.

[0019] Preferably, the calculation of the corresponding humidity extreme value time interval further includes correcting the humidity extreme value time interval, and the corrected humidity extreme value time interval satisfies the relationship:

[0020] ; In the formula, The humidity curve is The humidity extreme value time interval after the humidity value recorded is corrected. For the The humidity value recorded is consistent with the The time interval between the adjacent minimum values ​​of the recorded humidity values, For the The humidity value recorded is consistent with the The time interval between the adjacent maximum values ​​of the recorded humidity values, The humidity curve corresponds to The slope at each recorded humidity value, is the maximum value of the slope calculated at all recorded humidity values ​​on the humidity graph, It is an exponential function with the natural constant e as its base.

[0021] By considering the rate and unevenness of humidity change and introducing an exponential function to weight the time interval, the impact of data fluctuations on the calculation of cycle length can be reduced. The weight in the exponential function is dynamically adjusted according to the relative size of the slope, so that a larger weight is given to areas with drastic humidity changes.

[0022] Preferably, the relative position of the humidity at the current moment in the humidity change cycle satisfies the relationship:

[0023] ; In the formula, is the relative position of the humidity at the current moment in the humidity change cycle, is the humidity at the current moment, is the average value of all minimum values ​​on the humidity curve. It is the average value of all the maximum values ​​on the humidity curve.

[0024] Preferably, the relative position of the humidity at the current moment in the humidity change cycle satisfies the relationship:

[0025] ; In the formula, is the relative position of the humidity at the current moment in the humidity change cycle, is the humidity at the current moment, is the average value of all minimum values ​​on the humidity curve. It is the average value of all the maximum values ​​on the humidity curve.

[0026] By distinguishing whether the current humidity is in the rising stage or the falling stage, accurate cycle position information is determined, thereby improving the accuracy and efficiency of humidity control.

[0027] Preferably, the predicted humidity value at the next moment satisfies the relationship:

[0028] ; In the formula, is the predicted humidity value at the next moment, is the size of the window, The first The relative position of the humidity at the moment in the humidity change cycle, is the relative position of the humidity at the current moment in the humidity change cycle, The first The humidity value at the moment, is an exponential function with the natural constant e as base, is the weight adjustment factor, where .

[0029] By utilizing a weighted moving average method and combining the proximity of historical humidity values ​​to the current relative position of humidity in the cycle for weighting, the forecast is dynamically adjusted based on the position in the current cycle and historical data, thereby reducing the impact of the lag of the constant temperature and humidity chamber control system on environmental stability.

[0030] In a second aspect, a filter membrane constant temperature and humidity weighing system includes: a processor and a memory, wherein the memory stores computer program instructions, and when the computer program instructions are executed by the processor, the above-mentioned filter membrane constant temperature and humidity weighing method is implemented.

[0031] Beneficial effects: The present invention can reduce humidity fluctuations in the constant temperature and humidity control box due to system lag by real-time calculation and pre-adjustment of upcoming humidity changes, thereby more accurately controlling the humidity to keep it at a set target level and improving the accuracy of filter membrane weighing. BRIEF DESCRIPTION OF THE DRAWINGS

[0032] By reading the following detailed description with reference to the accompanying drawings, the above and other objects, features and advantages of the exemplary embodiments of the present invention will become readily understood. In the accompanying drawings, several embodiments of the present invention are shown in an exemplary and non-limiting manner, and the same or corresponding reference numerals represent the same or corresponding parts, wherein:

[0033] Figure 1 It is a method flow chart of steps S1 to S5 in the constant temperature and humidity weighing method of the filter membrane in an embodiment of the present invention. DETAILED DESCRIPTION

[0034] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative work are within the scope of protection of the present invention.

[0035] The present invention discloses a constant temperature and humidity weighing method for filter membrane, referring to Figure 1 , including steps S1 to S5, which are specifically as follows:

[0036] S1: After the humidity in the constant temperature and humidity chamber reaches the set value for the first time, the humidity value within the set time is recorded to form a humidity curve graph.

[0037] Specifically, when experimental conditions need to be adjusted, such as changing the target humidity or updating the experimental settings, the constant temperature and humidity chamber needs to be changed accordingly. The humidity in the chamber is automatically adjusted through the threshold set by the built-in control system of the constant temperature and humidity chamber to ensure that the humidity is maintained near the set value.

[0038] Specifically, when the humidity in the constant temperature and humidity chamber reaches the new set value for the first time, the humidity sensor is used to start recording humidity data values ​​within a set period of S minutes (S is set to 30 minutes in the embodiment of the present invention, and can be adjusted according to experimental requirements in other embodiments). These humidity values ​​will be used to draw a humidity data line graph.

[0039] In the humidity data line chart, all the maximum and minimum values ​​are specially marked. These extreme points are the key points of humidity change and are very important for analyzing the periodicity and stability of humidity.

[0040] In order to more smoothly represent the humidity change trend, the Bezier curve fitting method is used to smooth the original humidity data line. After Bezier curve fitting, the original humidity data line becomes smoother, forming a humidity curve. This curve more clearly shows the trend of humidity change over time and reduces the impact of random fluctuations.

[0041] It should be noted that, in the embodiment of the present invention, the humidity value within 30 minutes is recorded, wherein the recording frequency is once per second.

[0042] S2: Based on all humidity values, the corresponding humidity extreme time intervals are calculated, and all humidity extreme time intervals are summed and normalized to obtain the length of the humidity change cycle in the constant temperature and humidity chamber.

[0043] After obtaining the humidity curve in step S1 above, the first humidity rise point is selected as the starting point of the humidity change cycle. Starting from the starting point, after rising and falling, the humidity level finally returns to the starting point to form a complete humidity change cycle. Observing the complete cycle from the starting point to returning to the same humidity level is helpful to analyze and understand the behavior and characteristics of humidity changes in the constant temperature and humidity chamber. Through periodic analysis, intervention can be made before the humidity reaches the set threshold, thereby reducing humidity fluctuations and improving control accuracy.

[0044] Specifically, the humidity change rate, ie, the slope, of each humidity point on the humidity curve is first calculated to reflect the speed and direction of humidity change.

[0045] Secondly, for each humidity value, calculate the time interval between it and the adjacent maximum value and the time interval between it and the adjacent minimum value. Then calculate the sum of the time intervals between it and the adjacent maximum value and minimum value, and use the sum of the time intervals as the humidity extreme time interval of the humidity value, that is, satisfy the following relationship:

[0046]

[0047] In the formula, The humidity curve is The humidity extreme time interval of the recorded humidity values, For the The humidity value recorded is consistent with the The time interval between the adjacent minimum values ​​of the recorded humidity values, For the The humidity value recorded is consistent with the The time interval between the adjacent maximum values ​​of the recorded humidity values.

[0048] Finally, for all humidity values, the corresponding time intervals are summed up, and the summed value is used as the humidity change cycle length. Then the humidity change cycle length satisfies the following relationship:

[0049]

[0050] In the formula, is the length of the humidity change cycle. , It means that a total of 1800 humidity values ​​were recorded in 30 minutes.

[0051] Ideally, the humidity in the constant temperature and humidity chamber should rise or fall evenly. However, due to the limitation of sensor accuracy, the humidity data actually collected may deviate from the true humidity. In the absence of deviation, the length of the humidity change cycle can be estimated by the above calculation method. Therefore, in order to eliminate this deviation, the length of the humidity change cycle needs to be corrected.

[0052] Specifically, calculate the The ratio of the absolute value of the slope of the humidity value recorded in the first record to the absolute value of the maximum slope among all the humidity values ​​recorded is used as the relative slope value. The larger the relative slope value, the greater the relative slope value. The more uneven the humidity changes are, the smaller the recorded humidity values ​​are.

[0053] When the slope is relatively large, it indicates that there may be deviations caused by sensor accuracy. The original humidity extreme time interval corresponding to the recorded humidity values ​​is corrected to reduce the influence of the deviation on the calculation of the humidity change cycle length.

[0054] The humidity curve The humidity extreme value time interval after the humidity value of each record is corrected satisfies the following relationship:

[0055]

[0056] In the formula, The humidity curve is The humidity extreme value time interval after the humidity value recorded is corrected. For the The humidity value recorded is consistent with the The time interval between the adjacent minimum values ​​of the recorded humidity values, For the The humidity value recorded is consistent with the The time interval between the adjacent maximum values ​​of the recorded humidity values, The humidity curve corresponds to The slope at each recorded humidity value, is the maximum value of the slope calculated at all recorded humidity values ​​on the humidity graph, It is an exponential function with the natural constant e as its base.

[0057] Then the length of the corrected humidity change cycle can be obtained, satisfying the following relationship:

[0058]

[0059] In the formula, is the length of the corrected humidity change cycle.

[0060] In other embodiments, extreme values ​​or abnormal values ​​may be replaced by using median filtering to reduce their influence on the cycle length calculation.

[0061] S3: If the humidity at the current moment is in the rising stage, obtain the relative position of the humidity at the current moment in the rising part of the humidity change cycle; otherwise, obtain the relative position of the humidity at the current moment in all parts of the humidity change cycle.

[0062] In a fixed experimental environment, the adjustment capacity of the dehumidification module of the constant temperature and humidity chamber is known and fixed. The length of the humidity change cycle obtained by analyzing historical data can reflect the regularity of humidity changes to a certain extent. By using the position of real-time humidity data in the cycle, the humidity at the next moment can be predicted to achieve advance control.

[0063] In the embodiment of the present invention, the humidity value at the current moment and the humidity value at the moment before the current moment are selected for analysis. The analysis steps are generally as follows:

[0064] Compute the average of all maxima and the average of all minima.

[0065] When the humidity value at the current moment is greater than the humidity value at the previous moment, it means that the humidity at the current moment is on an upward trend. The relative position of the humidity value at the current moment in the humidity change cycle satisfies the following relationship:

[0066]

[0067] In the formula, is the relative position of the humidity at the current moment in the humidity change cycle, is the humidity at the current moment, is the average value of all minimum values ​​on the humidity curve. It is the average value of all the maximum values ​​on the humidity curve.

[0068] It should be noted that when the humidity value at the current moment is greater than the humidity value at the previous moment, and there are multiple sets of such continuously rising data within the humidity change cycle, and the humidity value at the final moment is greater than the humidity value at the initial moment, it means that the temperature at the current moment is on an upward trend.

[0069] In another embodiment, when the humidity value at the current moment is greater than the humidity value at the previous moment, it indicates that the humidity at the current moment is on an upward trend, and the relative position of the humidity value at the current moment in the humidity change cycle also satisfies the following relationship:

[0070]

[0071] In the formula, is the relative position of the humidity at the current moment in the humidity change cycle, is the humidity at the current moment, is the maximum humidity value within the humidity change cycle, It is the minimum humidity value within the humidity change cycle.

[0072] When the humidity value at the current moment is less than the humidity value at the previous moment, it means that the humidity at the current moment is in a downward trend. The relative position of the humidity value at the current moment in the humidity change cycle satisfies the following relationship:

[0073]

[0074] In the formula, is the relative position of the humidity at the current moment in the humidity change cycle, is the humidity at the current moment, is the average value of all minimum values ​​on the humidity curve. It is the average value of all the maximum values ​​on the humidity curve.

[0075] It should be noted that when the humidity value at the current moment is less than the humidity value at the previous moment, and there are multiple sets of such continuously decreasing data within the humidity change cycle, and the humidity value at the final moment is lower than the humidity value at the initial moment, it means that the temperature at the current moment is on a downward trend.

[0076] In another embodiment, when the humidity value at the current moment is less than the humidity value at the previous moment, it indicates that the humidity at the current moment is in a downward trend, and the relative position of the humidity value at the current moment in the humidity change cycle also satisfies the following relationship:

[0077]

[0078] In the formula, is the relative position of the humidity at the current moment in the humidity change cycle, is the humidity at the current moment, is the maximum humidity value within the humidity change cycle, It is the minimum humidity value within the humidity change cycle.

[0079] At this point, we have obtained the position of the current humidity in the humidity change cycle. The closer it is to 0, the closer the humidity at the current moment is to the starting position of a complete humidity change cycle; conversely, the closer it is to 1, the closer the humidity at the current moment is to the end position of a complete humidity change cycle.

[0080] S4: Select a window whose size is the length of the humidity change cycle, and use the weighted average method to obtain the predicted humidity value at the next moment after the current moment; wherein, calculate the absolute value of the difference between the humidity value at the current moment and the humidity value at any moment before the current moment, and use the absolute value as the weight adjustment factor of the weighted average method.

[0081] The humidity change in the constant temperature and humidity chamber is periodic to a certain extent. The humidity after the current moment may have a similar change trend as the humidity at the same or similar location one cycle ago. Using this periodicity, the humidity at the next moment can be predicted based on the humidity data in the cycle before the current moment.

[0082] Specifically, a value is selected that is equal to the length of the corrected humidity change cycle. The predicted humidity value at the next moment of the current moment is obtained by using the weighted average method. The predicted humidity value at the next moment satisfies the following relationship:

[0083]

[0084] In the formula, is the predicted humidity value at the next moment, is the size of the window, The first The relative position of the humidity at the moment in the humidity change cycle, is the relative position of the humidity at the current moment in the humidity change cycle, The first The humidity value at the moment, is an exponential function with the natural constant e as base, is the weight adjustment factor, where .

[0085] Among them, by calculating To measure and The closeness of the position in the cycle, when When it is smaller, it means and The positions in the cycle are close, so The impact on the prediction is greater; otherwise, the impact is smaller.

[0086] Among them, by calculating Correction is made to take into account the proximity of the actual humidity value. When it is smaller, it means and The positions in the cycle are close, so The impact on the prediction is greater; otherwise, the impact is smaller.

[0087] S5: Based on the predicted humidity value at the next moment, the humidity of the constant temperature and humidity chamber is controlled.

[0088] In the embodiment of the present invention, when weighing the filter membrane, the general steps of controlling the humidity in the constant temperature and humidity chamber are as follows:

[0089] Place an appropriate amount of silica gel and suitable molecular sieve material (select molecular sieves with corresponding pore size and chemical properties according to the environmental characteristics of the dehumidification required) in a closed chamber as dehumidifiers;

[0090] Reasonable design of air flow channel ensures that the air can fully contact with the silica gel when flowing through the chamber, thereby improving the dehumidification efficiency;

[0091] First, use silica gel to dehumidify. When the silica gel adsorption is close to saturation or at a lower temperature level, start the molecular sieve dehumidification equipment to further reduce the humidity;

[0092] Install high-precision temperature and humidity sensors in the constant temperature and humidity chamber to monitor environmental conditions in real time, and connect the temperature and humidity sensors to the temperature controller;

[0093] According to the humidity prediction value obtained in the above step S4 and the set target humidity value, when the humidity in the constant temperature and humidity chamber is higher than the set value, a start command is issued through the temperature controller, and the vacuum pump starts working. When the temperature and humidity reach the equilibrium value, the vacuum pump stops working and the cycle repeats.

[0094] The present invention first obtains a humidity curve graph, provides an intuitive way to observe and analyze the changing trend of humidity over time, determines the length of the humidity change cycle by analyzing the regularity of humidity changes, determines its specific position in the cycle by judging whether the current humidity is in an ascending stage or a descending stage, and uses a weighted average method and a dynamically updated weight mechanism to improve the humidity prediction accuracy at the next moment, thereby effectively solving the hysteresis problem of the constant temperature and humidity control box and improving the accuracy of filter membrane weighing.

[0095] It should be noted that, according to the calculation method of the above steps S1 to S4, the predicted temperature value based on the next moment can be obtained in the same way, and then the temperature of the constant temperature and humidity chamber can be controlled accordingly.

[0096] An embodiment of the present invention further discloses a filter membrane constant temperature and humidity weighing system, comprising a processor and a memory, wherein the memory stores computer program instructions, and when the computer program instructions are executed by the processor, a filter membrane constant temperature and humidity weighing method according to the present invention is implemented.

[0097] The system also includes other components familiar to those skilled in the art, such as a communication bus and a communication interface. The configuration and functions of these components are known in the art and will not be described in detail here.

[0098] In the present invention, the aforementioned memory may be any tangible medium containing or storing a program, which may be used by or in combination with an instruction execution system, apparatus or device. For example, a computer-readable storage medium may be any appropriate magnetic storage medium or magneto-optical storage medium, such as a resistive random access memory RRAM (Resistive Random Access Memory), a dynamic random access memory DRAM (Dynamic Random Access Memory), a static random access memory SRAM (Static Random-Access Memory), an enhanced dynamic random access memory EDRAM (Enhanced Dynamic Random Access Memory), a high-bandwidth memory HBM (High-Bandwidth Memory), a hybrid memory cube HMC (Hybrid Memory Cube), etc., or any other medium that can be used to store the required information and can be accessed by an application, a module or both. Any such computer storage medium may be part of a device or accessible or connectable to a device.

[0099] In the description of this specification, "plurality" or "several" means at least two, such as two, three or more, etc., unless otherwise clearly and specifically defined.

[0100] Although this specification has shown and described a number of embodiments of the present invention, it will be apparent to those skilled in the art that such embodiments are provided by way of example only. Those skilled in the art will conceive of many modifications, changes and alternatives without departing from the ideas and spirit of the present invention. It should be understood that in the practice of the present invention, various alternatives to the embodiments of the present invention described herein may be employed.

Claims

1. A filter membrane constant temperature and humidity weighing method, characterized in that: include: After the humidity in the constant temperature and humidity chamber reaches the set value for the first time, the humidity value within the set time is recorded to form a humidity curve graph; Based on all humidity values, the corresponding humidity extreme time intervals are calculated, and all humidity extreme time intervals are summed and normalized to obtain the length of the humidity change cycle in the constant temperature and humidity chamber; If the humidity at the current moment is in the rising stage, obtain the relative position of the humidity at the current moment in the rising part of the humidity change cycle; otherwise, obtain the relative position of the humidity at the current moment in all parts of the humidity change cycle; A window of a size equal to the length of the humidity change cycle is selected, and a predicted humidity value at the next moment of the current moment is obtained by using a weighted average method; wherein the absolute value of the difference between the humidity value at the current moment and the humidity value at any moment before the current moment is calculated, and the absolute value is used as a weight adjustment factor of the weighted average method; Based on the predicted humidity value at the next moment, the humidity of the constant temperature and humidity chamber is controlled.

2. The filter membrane constant temperature and humidity weighing method according to claim 1, characterized in that: Before forming the humidity curve graph, the method further includes: drawing the recorded humidity values ​​into a humidity data line graph, and smoothing the humidity data line graph using a Bezier curve fitting method.

3. The filter membrane constant temperature and humidity weighing method according to claim 2, characterized in that: The humidity variation cycle is: When collecting humidity values ​​within the set time, select the first humidity rise point as the starting point of the humidity change cycle; Starting from the starting point, it rises and falls and finally returns to the humidity level of the starting point, forming a complete humidity change cycle.

4. The filter membrane constant temperature and humidity weighing method according to claim 3, characterized in that: The calculation of the corresponding humidity extreme value time interval also includes correcting the humidity extreme value time interval, and the corrected humidity extreme value time interval satisfies the relationship: ; In the formula, The humidity curve is The humidity extreme value time interval after the humidity value recorded is corrected. For the The humidity value recorded is consistent with the The time interval between the adjacent minimum values ​​of the recorded humidity values, For the The humidity value recorded is consistent with the The time interval between the adjacent maximum values ​​of the recorded humidity values, The humidity curve corresponds to The slope at each recorded humidity value, is the maximum value of the slope calculated at all recorded humidity values ​​on the humidity graph, It is an exponential function with the natural constant e as its base.

5. The filter membrane constant temperature and humidity weighing method according to claim 4, characterized in that: The relative position of the humidity at the current moment in the humidity change cycle satisfies the relationship: ; In the formula, is the relative position of the humidity at the current moment in the humidity change cycle, is the humidity at the current moment, is the average value of all minimum values ​​on the humidity curve. It is the average value of all the maximum values ​​on the humidity curve.

6. The filter membrane constant temperature and humidity weighing method according to claim 5, characterized in that: The relative position of the humidity at the current moment in the humidity change cycle satisfies the relationship: ; In the formula, is the relative position of the humidity at the current moment in the humidity change cycle, is the humidity at the current moment, is the average value of all minimum values ​​on the humidity curve. It is the average value of all the maximum values ​​on the humidity curve.

7. The filter membrane constant temperature and humidity weighing method according to claim 6, characterized in that: The predicted humidity value at the next moment satisfies the relationship: ; In the formula, is the predicted humidity value at the next moment, is the size of the window, The first The relative position of the humidity at the moment in the humidity change cycle, is the relative position of the humidity at the current moment in the humidity change cycle, The first The humidity value at the moment, is an exponential function with the natural constant e as base, is the weight adjustment factor, where .

8. Filter membrane constant temperature and humidity weighing system, characterized in that: include: A processor and a memory, wherein the memory stores computer program instructions, and when the computer program instructions are executed by the processor, the filter membrane constant temperature and humidity weighing method according to any one of claims 1 to 7 is implemented.

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