A clean room pressure difference adaptive control method, device, equipment and medium

Abstract

The present application relates to the field of pressure difference control, and in particular to a method, device, equipment and medium for adaptive pressure difference control in a clean room. The method includes: the present application can accurately reflect the current air flow state of the clean room by acquiring the supply air volume data and the return air volume data in real time. The maximum pressure difference air volume determined based on these data can more accurately reflect the demand for pressure changes inside the clean room. By establishing a first leakage air volume fluctuation function corresponding to the basic pressure difference air volume fluctuation value, that is, by considering the leakage air volume caused by the sealing condition of the clean room, it is possible to consider and adapt to the slight pressure fluctuations that may exist inside the clean room, thereby improving the accuracy of the pressure difference control in the clean room.

Description

Technical Field

[0001] The present application relates to the field of pressure difference control, and in particular to a clean room pressure difference adaptive control method, device, equipment and medium. Background Art

[0002] Clean technology has been widely used in many industries such as medicine, health care, electronic manufacturing, aerospace, biosafety protection and food processing. Pressure differential control technology plays a vital role in maintaining the cleanliness inside the clean room and effectively curbing the spread of pollution. In theory, by constructing an orderly gradient pressure system between spaces of different clean levels, the core goal is to accurately manage the flow path of pollutants in the clean area. The clean room design of the positive pressure environment is to prevent external pollutants from invading the room through tiny gaps, while the negative pressure environment is used to prevent indoor pollutants from leaking to the external environment. In view of this, for environments that require high cleanliness such as pharmaceutical factories, electronics factories, operating rooms, sterile wards, etc., the relevant design specifications list in detail the recommended pressure differential range values ​​under different application scenarios. In addition, in order to ensure the operating efficiency of the clean room, it is also clearly required that the pressure differential reversal phenomenon and any factors that may interfere with the predetermined airflow direction must be prevented during operation.

[0003] However, since the clean room is usually sealed around the frame, it is difficult to completely seal the bottom, resulting in air leakage. The existing technology generally only considers the air leakage caused by the door gap, but does not consider the air leakage caused by the clean room sealing, resulting in inaccurate pressure difference control. Summary of the invention

[0004] In order to improve the accuracy of clean room pressure difference control, the present application provides a clean room pressure difference adaptive control method, device, equipment and medium.

[0005] In a first aspect, the present application provides a clean room pressure difference adaptive control method, which adopts the following technical solution:

[0006] A clean room pressure difference adaptive control method, comprising:

[0007] Obtain the current clean space supply air volume data, return air volume data and the basic pressure difference air volume fluctuation value allowed by the current clean space;

[0008] Establishing a first air leakage volume fluctuation function corresponding to the basic pressure difference air volume fluctuation value;

[0009] Based on the supply air volume data and the return air volume data, determining the maximum pressure difference air volume corresponding to the current clean space;

[0010] Determining a first air leakage volume corresponding to the current clean space based on the first air leakage volume fluctuation function and the maximum pressure difference air volume;

[0011] Based on the first air leakage volume and the maximum pressure difference air volume, a second air leakage volume corresponding to the current clean space is determined, and the opening of the air leakage volume slit valve is controlled based on the second air leakage volume.

[0012] By adopting the above technical solution, by acquiring the supply air volume data and the return air volume data in real time, the current air flow state of the clean room can be accurately reflected. The maximum pressure difference air volume determined based on these data can more accurately reflect the demand for pressure changes inside the clean room. By establishing the first leakage air volume fluctuation function corresponding to the basic pressure difference air volume fluctuation value, that is, by considering the leakage air volume caused by the sealing condition of the clean room, it is possible to consider and adapt to the small pressure fluctuations that may exist inside the clean room, thereby improving the accuracy of the pressure difference control of the clean room. Furthermore, the adaptive control method can be dynamically adjusted according to the actual state of the clean room, avoiding the problem of over-adjustment or under-adjustment that may be caused by traditional fixed control parameters. By determining the first leakage air volume and the second leakage air volume, and controlling the opening of the leakage air volume gap valve accordingly, the pressure inside the clean room can be kept stable, and the pressure fluctuations caused by external interference (such as door switching, personnel flow, etc.) can be reduced.

[0013] In a possible implementation, establishing a first air leakage volume fluctuation function corresponding to the basic pressure difference air volume fluctuation value includes:

[0014] Acquire historical clean data corresponding to the current clean space, wherein the historical clean data includes historical pressure difference air volume, historical supply air volume, historical return air volume, and historical second air leakage volume corresponding to each historical period;

[0015] Based on the historical pressure difference air volume, historical supply air volume, historical return air volume and historical second air leakage volume corresponding to each of the historical periods, the historical first air leakage volume corresponding to each of the historical periods is calculated;

[0016] Based on each of the historical differential pressure air volumes and the historical first air leakage volume corresponding to each of the historical differential pressure air volumes, a first air leakage volume fluctuation function corresponding to the basic pressure differential air volume fluctuation value is established.

[0017] By adopting the above technical solution, by obtaining the historical clean data corresponding to the current clean space, including the historical pressure difference air volume, the historical supply air volume, the historical return air volume and the historical second air leakage volume, the information in the historical data can be fully utilized, and the historical first air leakage volume corresponding to each historical period can be calculated based on these historical data, which can reveal the dynamic relationship between the pressure difference air volume and the air leakage volume. The established first air leakage volume fluctuation function can be adaptively adjusted according to the basic pressure difference air volume fluctuation value, so as to adapt to the pressure difference control requirements under different working conditions. Through the analysis of a large amount of historical data, the actual situation of air flow inside the clean room can be more accurately reflected, and the errors caused by model simplification or assumptions can be reduced. The establishment of the first air leakage volume fluctuation function is based on data from multiple historical periods, which can more comprehensively consider various possible working conditions and interference factors, thereby improving the accuracy of pressure difference control.

[0018] In a possible implementation, based on the historical pressure difference air volume, the historical supply air volume, the historical return air volume, and the historical second air leakage volume corresponding to each of the historical periods, the historical first air leakage volume corresponding to each of the historical periods is calculated, including:

[0019] Based on the historical supply air volume and the historical return air volume corresponding to each of the historical periods, determine the historical maximum pressure difference air volume corresponding to each of the historical periods;

[0020] Calculate the historical maximum pressure difference air volume and the difference between the historical pressure difference air volumes corresponding to each of the historical periods to obtain the historical air leakage volume and the historical air leakage volume corresponding to each of the historical periods;

[0021] Based on the historical air leakage amount and the historical second air leakage amount corresponding to each of the historical periods, the historical first air leakage amount corresponding to each of the historical periods is calculated.

[0022] By adopting the above technical solution, by directly using the supply air volume, return air volume, pressure difference air volume and second air leakage volume data in the historical period, the first air leakage volume of each historical period can be accurately calculated, avoiding calculation errors caused by missing data, errors or improper assumptions, and improving the accuracy and reliability of the data. The first air leakage volume calculated based on accurate historical data can provide a more solid foundation for the subsequent establishment of the first air leakage volume fluctuation function. The reliability of the model depends on the accuracy and completeness of the input data. This solution reduces the steps of data preprocessing and assumptions by directly using historical data, thereby enhancing the reliability of the model.

[0023] In a possible implementation, based on each of the historical differential pressure air volumes and the historical first air leakage corresponding to each of the historical differential pressure air volumes, a first air leakage fluctuation function corresponding to the basic pressure differential air volume fluctuation value is established, including:

[0024] Processing each of the historical differential pressure air volumes and the historical first air leakage volume corresponding to each of the historical differential pressure air volumes to obtain a historical differential pressure air volume sequence and a historical first air leakage volume sequence;

[0025] Gray processing is performed on the historical differential pressure air volume sequence and the historical first air leakage volume sequence respectively to obtain a target differential pressure air volume sequence and a target first air leakage volume sequence;

[0026] Based on the target differential pressure air volume sequence and the target first air leakage volume sequence, solving the model parameters of the grey prediction model and constructing the grey prediction model;

[0027] Based on the grey prediction model, the model parameters and the basic pressure difference air volume fluctuation value, a first air leakage volume fluctuation function is established.

[0028] By adopting the above technical solution, the historical differential pressure air volume sequence and the historical first leakage air volume sequence are smoothed by gray processing, which can remove noise and outliers in the data and improve the accuracy and consistency of the data. The gray prediction model is a prediction method suitable for small samples, poor information and uncertainty systems. It uses the cumulative generation sequence of data to explore the potential laws of the data, thereby improving the prediction accuracy. Combining historical data and the gray prediction model, the first leakage air volume under different basic pressure difference air volume fluctuation values ​​can be more accurately predicted, providing a more reliable basis for the pressure difference control of the clean room. The gray prediction model has strong adaptability and robustness, and can cope with the complex and changeable internal environment of the clean room. By continuously adjusting the model parameters, the gray prediction model can adapt to data changes under different working conditions and improve the adaptability and generalization ability of the model. The established first leakage air volume fluctuation function can be dynamically adjusted according to different basic pressure difference air volume fluctuation values ​​to achieve more accurate pressure difference control.

[0029] In a possible implementation, solving the model parameters of the grey prediction model includes:

[0030] The target differential pressure air volume sequence and the target first air leakage volume sequence are respectively accumulated to obtain a first target differential pressure air volume sequence and a first target first air leakage volume sequence, and the adjacent elements corresponding to the first target differential pressure air volume sequence and the first target first air leakage volume sequence are averaged to obtain a second target differential pressure air volume sequence and a second target first air leakage volume sequence;

[0031] Establishing a target differential equation based on the second target differential pressure air volume sequence and the second target first leakage air volume sequence;

[0032] The parameters in the target differential equation are determined by the least square method to obtain the model parameters of the grey prediction model.

[0033] By adopting the above technical solution, by accumulating the target differential pressure air volume sequence and the target first leakage air volume sequence, a smoother data sequence can be obtained, which helps to reduce random fluctuations and noise in the data and improve the accuracy and consistency of the data. Taking the average of the adjacent elements corresponding to each of the accumulated sequences can further smooth the data, reduce outliers and mutation points in the data, and improve the reliability of the data. Establishing the target differential equation based on the processed data sequence can more accurately reflect the dynamic relationship between the data. By solving the parameters in the target differential equation by the least squares method, more accurate model parameters can be obtained.

[0034] In a possible implementation, determining the first air leakage volume corresponding to the current clean space based on the first air leakage volume fluctuation function and the maximum pressure difference air volume includes:

[0035] Substituting the maximum pressure difference air volume into the first air leakage volume fluctuation function to obtain the target first air leakage volume corresponding to the maximum pressure difference air volume;

[0036] Based on the target first air leakage volume, the supply air volume data and the return air volume data, determining the target pressure difference air volume corresponding to the front clean space;

[0037] A first air leakage volume corresponding to the target pressure difference air volume is determined to obtain a first air leakage volume corresponding to the current clean space.

[0038] By adopting the above technical solution, by bringing the maximum pressure difference air volume into the first air leakage fluctuation function, the target first air leakage volume corresponding to the maximum pressure difference air volume can be obtained. By utilizing the functional relationship established in the early stage, the air leakage volume under a given pressure difference air volume can be accurately predicted, reducing the error caused by model simplification or improper assumptions. Based on the target first air leakage volume, supply air volume data, and return air volume data, the target pressure difference air volume corresponding to the current clean space can be determined, making the pressure difference control more comprehensive and accurate. By accurately controlling the pressure difference air volume, the pressure balance in the clean room can be more effectively maintained, the diffusion of pollutants can be reduced, and the cleanliness level can be improved.

[0039] In a possible implementation, controlling the opening of the air leakage gap valve based on the second air leakage amount includes:

[0040] Obtaining a target relationship function among the flow rate, pressure difference and opening degree of the air leakage gap valve;

[0041] Based on the target relationship function and the second air leakage, the opening degree of the air leakage gap valve is determined.

[0042] By adopting the above technical solution, by obtaining the target relationship function between the flow rate, pressure difference and opening of the air leakage gap valve, an accurate mathematical model can be established to describe the performance of the valve. Based on this mathematical model, the required valve opening can be accurately calculated according to the actual second air leakage demand, thereby achieving accurate control of the air leakage.

[0043] In a second aspect, the present application provides a clean room pressure difference adaptive control device, which adopts the following technical solution:

[0044] A clean room pressure difference adaptive control device, comprising:

[0045] The acquisition module is used to obtain the supply air volume data, return air volume data of the current clean space and the basic pressure difference air volume fluctuation value allowed by the current clean space;

[0046] An establishing module, used for establishing a first air leakage volume fluctuation function corresponding to the basic pressure difference air volume fluctuation value;

[0047] A first determination module, configured to determine a maximum pressure difference air volume corresponding to the current clean space based on the supply air volume data and the return air volume data;

[0048] A second determination module, configured to determine a first air leakage volume corresponding to the current clean space based on the first air leakage volume fluctuation function and the maximum pressure difference air volume;

[0049] A control module is used to determine a second air leakage volume corresponding to the current clean space based on the first air leakage volume and the maximum pressure difference air volume, and control the opening of the air leakage volume slit valve based on the second air leakage volume.

[0050] In a third aspect, the present application provides an electronic device, which adopts the following technical solution:

[0051] An electronic device, comprising:

[0052] at least one processor;

[0053] Memory;

[0054] At least one application, wherein the at least one application is stored in a memory and configured to be executed by at least one processor, and the at least one application is configured to: execute the clean room pressure difference adaptive control method described in the first aspect above.

[0055] In a fourth aspect, the present application provides a computer-readable storage medium, which adopts the following technical solution:

[0056] A computer-readable storage medium includes: a computer program that can be loaded by a processor and execute the clean room pressure difference adaptive control method described in the first aspect above.

[0057] In summary, this application includes the following beneficial technical effects:

[0058] By acquiring the supply air volume data and return air volume data in real time, the current air flow state of the clean room can be accurately reflected. The maximum pressure difference air volume determined based on these data can more accurately reflect the demand for pressure changes inside the clean room. By establishing the first leakage air volume fluctuation function corresponding to the basic pressure difference air volume fluctuation value, that is, by considering the leakage air volume caused by the sealing condition of the clean room, it is possible to consider and adapt to the small pressure fluctuations that may exist inside the clean room, thereby improving the accuracy of the pressure difference control of the clean room. Furthermore, the adaptive control method can be dynamically adjusted according to the actual state of the clean room, avoiding the problem of over-adjustment or under-adjustment that may be caused by traditional fixed control parameters. By determining the first leakage air volume and the second leakage air volume, and controlling the opening of the leakage air volume gap valve accordingly, the pressure inside the clean room can be kept stable, and the pressure fluctuations caused by external interference (such as door switching, personnel flow, etc.) can be reduced. BRIEF DESCRIPTION OF THE DRAWINGS

[0059] Figure 1 It is a flow chart of a clean room pressure difference adaptive control method provided in an embodiment of the present application;

[0060] Figure 2 It is a block diagram of a clean room pressure difference adaptive control device provided in an embodiment of the present application;

[0061] Figure 3 It is a schematic diagram of an electronic device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0062] The following is combined with Figure 1 -Attached Figure 3 This application is described in further detail.

[0063] In order to make the purpose, technical solution and advantages of the embodiments of the present application clearer, the technical solution in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0064] In order to facilitate understanding of the technical solution proposed in this application, several elements introduced in the description of this application are first introduced here. It should be understood that the following introduction is only for the convenience of understanding these elements, so as to understand the content of the embodiments of this application, and does not necessarily cover all possible situations.

[0065] The basic principle of clean room pressure difference control is to control the supply air volume, return air volume and exhaust air volume. When the air volume supplied to the clean room is appropriately greater than the return air volume and exhaust air volume, a certain positive pressure value can be maintained indoors. At this time, under the effect of the static pressure difference between indoors and outdoors, the air volume leaking out through the loose parts of the enclosure structure is equal to the difference between the mechanical inlet and outlet air volume.

[0066] The specific implementation method of clean room pressure difference control can be: ensure that the clean room air supply volume is relatively constant, and then adjust the clean room return air volume or exhaust air volume, so as to control the clean room pressure difference air volume and maintain the clean room pressure difference value.

[0067] Since the clean room is usually sealed around the frame, it is difficult to completely seal the bottom, resulting in air leakage. The existing technology generally only considers the air leakage caused by the door gap, but does not consider the air leakage caused by the clean room sealing condition, resulting in inaccurate pressure difference control.

[0068] The present application embodiment provides a clean room pressure difference adaptive control method, such as Figure 1 As shown, the method provided in the embodiment of the present application is performed by an electronic device, which can be a server or a terminal device, wherein the server can be an independent physical server, or a server cluster or distributed system composed of multiple physical servers, or a cloud server providing cloud computing services. The terminal device can be a smart phone, a tablet computer, a laptop computer, a desktop computer, etc., but is not limited thereto. The terminal device and the server can be directly or indirectly connected via wired or wireless communication, which is not limited in the embodiment of the present application. The method includes steps S101 to S105, wherein:

[0069] Step S101, obtaining the supply air volume data and return air volume data of the current clean space and the basic pressure difference air volume fluctuation value allowed by the current clean space.

[0070] The clean space may be a clean room, and the current clean space is any clean space in the current cycle. A cycle may be one day or one hour, which is not limited in the present embodiment. It is worth noting that, for the convenience of description, the current clean space described below refers to the same clean space.

[0071] The supply air volume refers to the volume of air that passes through the clean room air filtration system and is delivered to the room per unit time. The supply air volume data is measured in cubic meters per hour (m³ / h); the return air volume refers to the volume of air that is sent back to the room after being processed inside the clean room. The return air volume data is also measured in cubic meters per hour (m³ / h). Exemplarily, the supply air volume data can be 5m³ / h, and the return air volume data can be 3m³ / h. Specifically, the electronic device can directly obtain the supply air volume data and return air volume data corresponding to the current clean space.

[0072] The basic pressure difference air volume fluctuation value refers to the air volume fluctuation range allowed to maintain a specific cleanliness and pressure difference stability during the operation of the clean room. Specifically, the basic pressure difference fluctuation value is usually determined based on the clean room design specifications, cleanliness level, pressure difference requirements and actual operating conditions. The person in charge of the clean space can input the basic pressure difference air volume fluctuation value corresponding to the clean space into the electronic equipment for subsequent application.

[0073] Step S102: establishing a first air leakage volume fluctuation function corresponding to the basic pressure difference air volume fluctuation value.

[0074] The first air leakage is the air leakage caused by the sealing of the clean space. Since the greater the gas pressure in the clean space, the greater the first air leakage, the functional relationship between the basic pressure difference air volume and the first air leakage can be obtained. Specifically, the historical data corresponding to the current clean space can be obtained, wherein the historical data includes the historical basic pressure difference air volume fluctuation value corresponding to each historical period and the historical first air leakage corresponding to each historical basic pressure difference air volume.

[0075] Further, based on the historical first air leakage corresponding to each historical basic pressure difference air volume, multiple historical basic pressure difference air volumes and multiple historical first air leakage volumes are fitted by polynomial fitting to obtain a function equation with the historical basic pressure difference air volume as an independent variable and the historical first air leakage volume as a dependent variable, and based on the function equation and the basic pressure difference air volume fluctuation value, the first air leakage volume fluctuation function corresponding to the basic pressure difference air volume fluctuation value is obtained. Among them, the polynomial fitting method is a conventional technical means in this field, and the embodiments of this application will not be described in detail here.

[0076] Step S103: Determine the maximum pressure difference air volume corresponding to the current clean space based on the supply air volume data and the return air volume data.

[0077] After obtaining the supply air volume data and return air volume data corresponding to the current clean space, the actual pressure differential air volume corresponding to the current clean space can be calculated based on the supply air volume data and the return air volume data. Specifically, based on the actual pressure differential air volume = supply air volume data - return air volume data, the actual pressure differential air volume corresponding to the current clean space is obtained. Furthermore, after obtaining the actual pressure differential air volume of the current clean space, the maximum pressure differential air volume corresponding to the current clean space can be calculated based on the multiples of the actual pressure differential air volume and the maximum pressure differential air volume. Among them, the multiples of the actual pressure differential air volume and the maximum pressure differential air volume are preset in advance.

[0078] Step S104: Determine a first air leakage volume corresponding to the current clean space based on the first air leakage volume fluctuation function and the maximum pressure difference air volume.

[0079] After obtaining the first air leakage volume fluctuation function and the maximum pressure difference air volume, the maximum pressure difference air volume can be substituted into the independent variable of the first air leakage volume fluctuation function. At this time, the dependent variable corresponding to the first air leakage volume fluctuation function obtained is the first air leakage volume corresponding to the current clean space.

[0080] Step S105: determining a second air leakage volume corresponding to the current clean space based on the first air leakage volume and the maximum pressure difference air volume, and controlling the opening of the air leakage volume slit valve based on the second air leakage volume.

[0081] The second air leakage volume is the exhaust volume adjusted to adjust the pressure difference in the clean space. Generally, the exhaust volume, i.e., the second air leakage volume, is adjusted by adjusting the opening of the air leakage volume slit valve on the exhaust device.

[0082] Specifically, the absolute value of the difference between the maximum pressure difference air volume and the basic pressure difference air volume fluctuation value is calculated to obtain the sum of the first air leakage volume and the second air leakage volume, and the second air leakage volume is subtracted from the sum of the first air leakage volume and the second air leakage volume to obtain the second air leakage volume corresponding to the current clean space.

[0083] Further, after obtaining the second air leakage amount, the opening of the air leakage amount slit valve corresponding to the second air leakage amount is obtained, and based on the opening of the air leakage amount slit valve, the air leakage amount slit valve on the exhaust device is adjusted. Wherein, one second air leakage amount corresponds to one air leakage amount slit valve opening.

[0084] The embodiment of the present application provides a clean room pressure difference adaptive control method, which can accurately reflect the current air flow state of the clean room by acquiring the supply air volume data and the return air volume data in real time. The maximum pressure difference air volume determined based on these data can more accurately reflect the demand for pressure changes inside the clean room. By establishing a first leakage air volume fluctuation function corresponding to the basic pressure difference air volume fluctuation value, that is, by considering the leakage air volume caused by the sealing condition of the clean room, it is possible to consider and adapt to the small pressure fluctuations that may exist inside the clean room, thereby improving the accuracy of the clean room pressure difference control. Furthermore, the adaptive control method can be dynamically adjusted according to the actual state of the clean room, avoiding the problem of over-adjustment or under-adjustment that may be caused by traditional fixed control parameters. By determining the first leakage air volume and the second leakage air volume, and controlling the opening of the leakage air volume gap valve accordingly, the pressure inside the clean room can be kept stable, and the pressure fluctuations caused by external interference (such as door switching, personnel flow, etc.) can be reduced.

[0085] In a possible implementation of the embodiment of the present application, in the above step S102, establishing a first air leakage volume fluctuation function corresponding to the basic pressure difference air volume fluctuation value may specifically include:

[0086] Obtain the historical clean data corresponding to the current clean space, including the historical pressure difference air volume, historical supply air volume, historical return air volume and historical second air leakage volume corresponding to each historical period;

[0087] Based on the historical pressure difference air volume, historical supply air volume, historical return air volume and historical second air leakage volume corresponding to each historical period, the historical first air leakage volume corresponding to each historical period is calculated;

[0088] Based on each historical differential pressure air volume and the historical first air leakage volume corresponding to each historical differential pressure air volume, a first air leakage volume fluctuation function corresponding to the basic pressure differential air volume fluctuation value is established.

[0089] The pressure difference air volume, supply air volume, return air volume and second air leakage volume in each cycle are all recorded, and these data are recorded in a historical database for subsequent search.

[0090] Specifically, the historical clean data of the current clean space in each past historical period is extracted from the historical database, that is, the following corresponding information of the current clean space in each historical period (such as the historical pressure difference air volume, the historical supply air volume, the historical return air volume and the historical second air leakage volume) is extracted from the historical database.

[0091] Furthermore, the collected historical data is cleaned and verified to ensure the accuracy and completeness of the data. For example, check whether there are missing values, abnormal values ​​or inconsistent data records. If the data is missing or abnormal, it needs to be filled or corrected according to the specific situation.

[0092] Calculate the first historical air leakage: For each historical period, use the following formula to calculate the first air leakage: Historical first air leakage = Historical supply air volume − Historical return air volume − Historical second air leakage − Historical pressure difference air volume. That is, subtract the return air volume, the second air leakage and the pressure difference air volume (the change in air volume caused by the pressure difference) from the supply air volume to obtain the first air leakage.

[0093] Furthermore, the relationship between the calculated historical first air leakage volume and the corresponding historical pressure difference air volume is analyzed. Specifically, by drawing scatter plots, trend lines, etc., the correlation between the two is observed, and a preliminary judgment is made as to whether there is a certain functional relationship (such as linear, nonlinear, etc.). According to the results of the data analysis, a suitable mathematical model is selected to fit the relationship between the first air leakage volume and the pressure difference air volume. More specifically, if the two show a linear relationship, a linear regression model can be used; if a nonlinear relationship is shown, a more complex model such as polynomial regression or exponential regression may need to be used. Thus, the functional relationship between the basic pressure difference and the first air leakage volume is obtained, so as to obtain the first air leakage volume fluctuation function corresponding to the basic pressure difference air volume fluctuation value.

[0094] A possible implementation of the embodiment of the present application, in the above embodiment, based on the historical pressure difference air volume, the historical supply air volume, the historical return air volume and the historical second air leakage volume corresponding to each historical period, the historical first air leakage volume corresponding to each historical period is calculated, including:

[0095] Based on the historical supply air volume and the historical return air volume corresponding to each historical period, determine the historical maximum pressure difference air volume corresponding to each historical period;

[0096] Calculate the historical maximum pressure difference air volume and the difference between the historical pressure difference air volumes corresponding to each historical period to obtain the historical air leakage volume and the historical air leakage volume corresponding to each historical period;

[0097] Based on the historical air leakage volume and the historical second air leakage volume corresponding to each historical period, the historical first air leakage volume corresponding to each historical period is calculated.

[0098] Among them, in each historical period, according to the difference between the supply air volume and the return air volume, the maximum possible pressure difference air volume in the period is obtained. This is usually the maximum value of the difference between the supply air volume and the return air volume in the historical period.

[0099] Specifically, for each historical cycle, the difference between the supply air volume and the return air volume is calculated, and the maximum value of the difference in the cycle is found as the historical maximum pressure difference air volume of the cycle, and the actual historical pressure difference air volume is subtracted from the historical maximum pressure difference air volume to obtain the historical air leakage volume of the cycle. The known historical second air leakage volume is subtracted from the historical air leakage volume to obtain the historical first air leakage volume of the cycle.

[0100] A possible implementation of the embodiment of the present application, in the above embodiment, based on each historical differential pressure air volume and the historical first air leakage corresponding to each historical differential pressure air volume, a first air leakage volume fluctuation function corresponding to the basic pressure differential air volume fluctuation value is established, including:

[0101] Processing each historical differential pressure air volume and the historical first air leakage volume corresponding to each historical differential pressure air volume to obtain a historical differential pressure air volume sequence and a historical first air leakage volume sequence;

[0102] Gray processing is performed on the historical differential pressure air volume sequence and the historical first leakage air volume sequence respectively to obtain the target differential pressure air volume sequence and the target first leakage air volume sequence;

[0103] Based on the target differential pressure air volume sequence and the target first leakage air volume sequence, the model parameters of the grey prediction model are solved, and the grey prediction model is constructed;

[0104] Based on the grey prediction model, model parameters and basic pressure difference air volume fluctuation value, a first air leakage volume fluctuation function is established.

[0105] Specifically, the differential pressure air volume (denoted as xi) and the corresponding first air leakage volume (denoted as yi) of each historical period are extracted from the historical data to form a historical differential pressure air volume sequence X={x1,x2,...,xn} and a historical first air leakage volume sequence Y={y1,y2,...,yn}.

[0106] The historical differential pressure air volume sequence X and the historical first leakage air volume sequence Y are accumulated to obtain the accumulated sequences X(1)={x1(1),x2(1),...,xn(1)} and Y(1)={y1(1),y2(1),...,yn(1)}. Accumulation can reduce the randomness of the data and improve the regularity of the data.

[0107] Furthermore, in order to construct an equal-dimensional matrix of the grey prediction model, it is necessary to generate a corresponding mean sequence. For X(1) and Y(1), a sequence of adjacent mean values ​​can be generated for subsequent calculations.

[0108] Based on the cumulatively generated sequence and the mean generated sequence, an equal-dimensional matrix is ​​constructed to solve the parameters of the grey prediction model. The parameters of the grey prediction model (such as the development coefficient and the grey action amount) are solved using the least square method or other optimization methods, and a grey prediction model is constructed based on the solved parameters, which can describe the relationship between the differential pressure air volume and the first air leakage volume.

[0109] The constructed grey prediction model is used to predict the given basic pressure difference air volume fluctuation value to obtain the corresponding first air leakage volume prediction value. According to the prediction results, the variation law between the pressure difference air volume and the first air leakage volume is analyzed to establish the first air leakage volume fluctuation function.

[0110] A possible implementation of the embodiment of the present application, in the above embodiment, solving the model parameters of the grey prediction model includes:

[0111] The target differential pressure air volume sequence and the target first air leakage volume sequence are respectively accumulated to obtain a first target differential pressure air volume sequence and a first target first air leakage volume sequence, and the adjacent elements corresponding to the first target differential pressure air volume sequence and the first target first air leakage volume sequence are averaged to obtain a second target differential pressure air volume sequence and a second target first air leakage volume sequence;

[0112] Based on the second target differential pressure air volume sequence and the second target first leakage air volume sequence, establishing a target differential equation;

[0113] The parameters in the target differential equation are determined by the least square method to obtain the model parameters of the grey prediction model.

[0114] Specifically, the target differential pressure air volume sequence X(0)={x1(0),x2(0),...,xn(0)} is accumulated to obtain the first target differential pressure air volume sequence X(1)={x1(1),x2(1),...,xn(1)}, where xk(1)=∑i=1kxi(0),k=1,2,...,n. For the process of accumulating the target first leakage air volume sequence, similarly, the target first leakage air volume sequence Y(0)={y1(0),y2(0),...,yn(0)} is accumulated to obtain the first target first leakage air volume sequence Y(1)={y1(1),y2(1),...,yn(1)}.

[0115] The process of solving the mean of the first target differential pressure and air volume sequence can be as follows: taking the mean of adjacent elements in the first target differential pressure and air volume sequence X(1) to obtain the second target differential pressure and air volume sequence Z(1)={z1(1),z2(1),...,zn−1(1)}, where zk(1)=0.5(xk(1)+xk+1(1)), k=1,2,...,n−1.

[0116] The process of solving the mean of the first target first air leakage sequence can be: Similarly, take the mean of adjacent elements in the first target first air leakage sequence Y(1) to obtain the second target first air leakage sequence.

[0117] Furthermore, based on the grey system theory, we can construct the following target differential equation (also called the basic form of the GM(1,1) model): fracdx(1)(t)dt+ax(1)(t)=b, where a and b are the model parameters to be determined, and x(1)(t) is the cumulative generated value at time t. The above differential equation is converted into a differential equation form, and the relationship is established using the second target differential pressure air volume sequence Z(1) and the original target first leakage air volume sequence Y(0) (or its differential form, if the restoration from Y(1) to Y(0) is considered).

[0118] According to the form of the difference equation, a data matrix containing Z(1) and constant terms and a response vector containing Y(0) (or its appropriate form) are constructed. The linear relationship between the above data matrix and the response vector is solved by the least squares method to obtain the model parameters a and b to obtain the parameters a and b of the grey prediction model, thereby constructing a grey prediction model to predict the future differential pressure air volume or the first air leakage volume.

[0119] A possible implementation of the embodiment of the present application is that in the above step S104, based on the first air leakage fluctuation function and the maximum pressure difference air volume, determining the first air leakage volume corresponding to the current clean space includes:

[0120] Substitute the maximum pressure difference air volume into the first air leakage volume fluctuation function to obtain the target first air leakage volume corresponding to the maximum pressure difference air volume;

[0121] Determine the target pressure difference air volume corresponding to the current clean space based on the target first air leakage volume, the supply air volume data and the return air volume data;

[0122] Determine a first air leakage volume corresponding to the target pressure difference air volume to obtain a first air leakage volume corresponding to the current clean space.

[0123] Since the pressure difference in the clean space will affect the first air leakage in actual situations, after obtaining the maximum pressure difference air volume, the first air leakage corresponding to the maximum pressure difference air volume can be obtained based on the maximum pressure difference air volume, and based on the first air leakage corresponding to the maximum pressure difference air volume, the pressure difference corresponding to the current clean space is re-determined, and the first air leakage is determined based on the newly determined pressure difference, thereby improving the certainty of determining the first air leakage. After obtaining the first air leakage fluctuation function and the maximum pressure difference air volume, the maximum pressure difference air volume can be used as input and substituted into the function for determining the first air leakage fluctuation. Through function calculation, the target first air leakage corresponding to the maximum pressure difference air volume condition can be obtained.

[0124] Further, after obtaining the target first air leakage volume, the target pressure differential air volume corresponding to the current clean space is calculated based on the supply air volume data, the return air volume data and the target first air leakage volume. Specifically, based on the target pressure differential air volume = supply air volume data - return air volume data - target first air leakage volume, the target pressure differential air volume corresponding to the current clean space is obtained.

[0125] Furthermore, after obtaining the target pressure difference air volume corresponding to the current clean space, the target pressure difference air volume is substituted into the first air leakage volume fluctuation function. Through function calculation, the first air leakage volume corresponding to the target pressure difference air volume conditions can be obtained to obtain the first air leakage volume corresponding to the current clean space.

[0126] A possible implementation of the embodiment of the present application, in the above step S105, controlling the opening of the air leakage gap valve based on the second air leakage amount includes:

[0127] Obtaining the target relationship function among the flow rate, pressure difference and opening degree of the air leakage gap valve;

[0128] Based on the target relationship function and the second air leakage amount, the opening degree of the air leakage amount slit valve is determined.

[0129] Among them, the flow rate of the air leakage gap valve is the air volume that can leak out within a unit, and the opening of the air leakage gap valve is the degree of valve opening. The target relationship function describes the relationship between the opening of the air leakage gap valve and the air leakage under different pressure differences.

[0130] Specifically, the actual pressure difference air volume and the second air leakage volume corresponding to the current clean space are taken as inputs and substituted into the target relationship function, and a corresponding opening value output by the target relationship function is obtained. The opening value is the opening to which the leakage gap valve should be adjusted in order to achieve the desired second air leakage volume under the current pressure difference.

[0131] Furthermore, according to the opening value calculated by the target relationship function, the electronic device can generate an opening instruction and send the opening instruction to the controller corresponding to the air leakage gap valve. After receiving the opening instruction, the controller drives the valve actuator to adjust the opening of the air leakage gap valve; or the electronic device generates a manual opening instruction and sends the manual opening instruction to the terminal of the person in charge corresponding to the current clean space, so that the person in charge corresponding to the current clean space manually adjusts the opening of the air leakage gap valve.

[0132] The above embodiment introduces a clean room pressure difference adaptive control method from the perspective of method flow, and the following embodiment introduces a clean room pressure difference adaptive control device from the perspective of a virtual module or a virtual unit. For details, please refer to the following embodiment.

[0133] See also Figure 2The clean room pressure difference adaptive control device 20 may specifically include: an acquisition module 201, an establishment module 202, a first determination module 203, a second determination module 204 and a control module 205. Specifically:

[0134] A clean room pressure difference adaptive control device 20, comprising:

[0135] The acquisition module 201 is used to acquire the supply air volume data and return air volume data of the current clean space and the basic pressure difference air volume fluctuation value allowed by the current clean space;

[0136] Establishing module 202, used to establish a first air leakage volume fluctuation function corresponding to the basic pressure difference air volume fluctuation value;

[0137] The first determination module 203 is used to determine the maximum pressure difference air volume corresponding to the current clean space based on the supply air volume data and the return air volume data;

[0138] A second determination module 204 is used to determine a first air leakage volume corresponding to the current clean space based on the first air leakage volume fluctuation function and the maximum pressure difference air volume;

[0139] The control module 205 is used to determine the second air leakage volume corresponding to the current clean space based on the first air leakage volume and the maximum pressure difference air volume, and control the opening of the air leakage volume slit valve based on the second air leakage volume.

[0140] In a possible implementation of the embodiment of the present application, when the establishment module 202 establishes the first leakage air volume fluctuation function corresponding to the basic pressure difference air volume fluctuation value, it can be specifically used to:

[0141] Obtain the historical clean data corresponding to the current clean space, including the historical pressure difference air volume, historical supply air volume, historical return air volume and historical second air leakage volume corresponding to each historical period;

[0142] Based on the historical pressure difference air volume, historical supply air volume, historical return air volume and historical second air leakage volume corresponding to each historical period, the historical first air leakage volume corresponding to each historical period is calculated;

[0143] Based on each historical differential pressure air volume and the historical first air leakage volume corresponding to each historical differential pressure air volume, a first air leakage volume fluctuation function corresponding to the basic pressure differential air volume fluctuation value is established.

[0144] In a possible implementation of the embodiment of the present application, when the establishment module 202 calculates the historical first air leakage volume corresponding to each historical period based on the historical pressure difference air volume, the historical supply air volume, the historical return air volume and the historical second air leakage volume corresponding to each historical period, it can be specifically used to:

[0145] Based on the historical supply air volume and the historical return air volume corresponding to each historical period, determine the historical maximum pressure difference air volume corresponding to each historical period;

[0146] Calculate the historical maximum pressure difference air volume and the difference between the historical pressure difference air volumes corresponding to each historical period to obtain the historical air leakage volume and the historical air leakage volume corresponding to each historical period;

[0147] Based on the historical air leakage volume and the historical second air leakage volume corresponding to each historical period, the historical first air leakage volume corresponding to each historical period is calculated.

[0148] In a possible implementation of the embodiment of the present application, when the establishment module 202 establishes a first leakage volume fluctuation function corresponding to a basic pressure differential air volume fluctuation value based on each historical differential pressure air volume and a historical first leakage volume corresponding to each historical differential pressure air volume, it can be specifically used to:

[0149] Processing each historical differential pressure air volume and the historical first air leakage volume corresponding to each historical differential pressure air volume to obtain a historical differential pressure air volume sequence and a historical first air leakage volume sequence;

[0150] Gray processing is performed on the historical differential pressure air volume sequence and the historical first leakage air volume sequence respectively to obtain the target differential pressure air volume sequence and the target first leakage air volume sequence;

[0151] Based on the target differential pressure air volume sequence and the target first leakage air volume sequence, the model parameters of the grey prediction model are solved, and the grey prediction model is constructed;

[0152] Based on the grey prediction model, model parameters and basic pressure difference air volume fluctuation value, a first air leakage volume fluctuation function is established.

[0153] In a possible implementation of the embodiment of the present application, when the establishment module 202 solves the model parameters of the grey prediction model, it can be specifically used to:

[0154] The target differential pressure air volume sequence and the target first air leakage volume sequence are respectively accumulated to obtain a first target differential pressure air volume sequence and a first target first air leakage volume sequence, and the adjacent elements corresponding to the first target differential pressure air volume sequence and the first target first air leakage volume sequence are averaged to obtain a second target differential pressure air volume sequence and a second target first air leakage volume sequence;

[0155] Based on the second target differential pressure air volume sequence and the second target first leakage air volume sequence, establishing a target differential equation;

[0156] The parameters in the target differential equation are determined by the least square method to obtain the model parameters of the grey prediction model.

[0157] In a possible implementation of the embodiment of the present application, when the second determination module 204 determines the first air leakage volume corresponding to the current clean space based on the first air leakage volume fluctuation function and the maximum pressure difference air volume, it can be specifically used to:

[0158] Substitute the maximum pressure difference air volume into the first air leakage volume fluctuation function to obtain the target first air leakage volume corresponding to the maximum pressure difference air volume;

[0159] Determine the target pressure difference air volume corresponding to the current clean space based on the target first air leakage volume, the supply air volume data and the return air volume data;

[0160] Determine a first air leakage volume corresponding to the target pressure difference air volume to obtain a first air leakage volume corresponding to the current clean space.

[0161] In a possible implementation of the embodiment of the present application, when the control module 205 controls the opening of the air leakage gap valve based on the second air leakage amount, it can be specifically used to:

[0162] Obtaining the target relationship function among the flow rate, pressure difference and opening degree of the air leakage gap valve;

[0163] Based on the target relationship function and the second air leakage amount, the opening degree of the air leakage amount slit valve is determined.

[0164] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working processes of the systems, devices and units described above can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0165] See also Figure 3 , the application embodiment also introduces an electronic device from the perspective of a physical device, such as Figure 3 As shown, Figure 3 The electronic device 30 shown includes: a processor 301 and a memory 303. The processor 301 and the memory 303 are connected, such as through a bus 302. Optionally, the electronic device 30 may also include a transceiver 304. It should be noted that in actual applications, the transceiver 304 is not limited to one, and the structure of the electronic device 30 does not constitute a limitation on the embodiments of the present application.

[0166] The processor 301 may be a CPU (Central Processing Unit), a general-purpose processor, a DSP (Digital Signal Processor), an ASIC (Application Specific Integrated Circuit), an FPGA (Field Programmable Gate Array) or other programmable logic devices, transistor logic devices, hardware components or any combination thereof. It may implement or execute various exemplary logic blocks, modules and circuits described in conjunction with the disclosure of this application. The processor 301 may also be a combination that implements computing functions, such as a combination of one or more microprocessors, a combination of a DSP and a microprocessor, etc.

[0167] The bus 302 may include a path to transmit information between the above components. The bus 302 may be a PCI (Peripheral Component Interconnect) bus or an EISA (Extended Industry Standard Architecture) bus. The bus 302 may be divided into an address bus, a data bus, a control bus, etc. For ease of representation, Figure 3 Only one thick line is used in the diagram, but this does not mean that there is only one bus or only one type of bus.

[0168] The memory 303 may be a ROM (Read Only Memory) or other types of static storage devices that can store static information and instructions, a RAM (Random Access Memory) or other types of dynamic storage devices that can store information and instructions, or an EEPROM (Electrically Erasable Programmable Read Only Memory), a CD-ROM (Compact Disc Read Only Memory) or other optical disk storage, optical disk storage (including compressed optical disk, laser disk, optical disk, digital versatile disk, Blu-ray disk, etc.), a magnetic disk storage medium or other magnetic storage device, or any other medium that can be used to carry or store the desired program code in the form of instructions or data structures and can be accessed by a computer, but is not limited thereto.

[0169] The memory 303 is used to store the application code for executing the solution of the present application, and the execution is controlled by the processor 301. The processor 301 is used to execute the application code stored in the memory 303 to implement the contents shown in the above method embodiment.

[0170] The electronic devices include but are not limited to: mobile phones, laptop computers, digital broadcast receivers, PDAs (personal digital assistants), PADs (tablet computers), PMPs (portable multimedia players), vehicle-mounted terminals (such as vehicle-mounted navigation terminals), etc., and fixed terminals such as digital TVs, desktop computers, etc., and can also be servers, etc. Figure 3 The electronic device shown is merely an example and should not bring any limitation to the functions and scope of use of the embodiments of the present application.

[0171] An embodiment of the present application provides a computer-readable storage medium, on which a computer program is stored. When the computer-readable storage medium is run on a computer, the computer can execute the corresponding content in the aforementioned method embodiment.

[0172] It should be understood that, although the steps in the flowchart of the accompanying drawings are displayed in sequence as indicated by the arrows, these steps are not necessarily executed in sequence in the order indicated by the arrows. Unless otherwise specified herein, there is no strict order restriction on the execution of these steps, and they can be executed in other orders. Moreover, at least a part of the steps in the flowchart of the accompanying drawings may include multiple sub-steps or multiple stages, and these sub-steps or stages are not necessarily executed at the same time, but can be executed at different times, and their execution order is not necessarily sequential, but can be executed in turn or alternately with other steps or at least a part of the sub-steps or stages of other steps.

[0173] The above are only some implementation methods of the present application. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principles of the present application. These improvements and modifications should also be regarded as the scope of protection of the present application.

Claims

1. A clean room pressure difference adaptive control method, characterized in that: include: Obtain the current clean space supply air volume data, return air volume data and the basic pressure difference air volume fluctuation value allowed by the current clean space; Establishing a first air leakage volume fluctuation function corresponding to the basic pressure difference air volume fluctuation value, wherein the first air leakage volume is the air leakage volume caused by the sealing of the clean space; Based on the supply air volume data and the return air volume data, determining the maximum pressure difference air volume corresponding to the current clean space; Determining a first air leakage volume corresponding to the current clean space based on the first air leakage volume fluctuation function and the maximum pressure difference air volume; Based on the first air leakage volume and the maximum pressure difference air volume, the absolute value of the difference between the maximum pressure difference air volume and the basic pressure difference air volume fluctuation value is calculated to obtain the sum of the first air leakage volume and the second air leakage volume, and based on the sum of the first air leakage volume and the second air leakage volume minus the first air leakage volume, the second air leakage volume corresponding to the current clean space is obtained, and the opening of the air leakage volume slit valve corresponding to the second air leakage volume is obtained, so as to adjust the air leakage volume slit valve on the exhaust device based on the opening of the air leakage volume slit valve, wherein the second air leakage volume is the exhaust volume adjusted to adjust the pressure difference in the clean space; Wherein, the establishing of the first air leakage volume fluctuation function corresponding to the basic pressure difference air volume fluctuation value comprises: Acquire historical clean data corresponding to the current clean space, wherein the historical clean data includes historical pressure difference air volume, historical supply air volume, historical return air volume, and historical second air leakage volume corresponding to each historical period; Based on the historical pressure difference air volume, historical supply air volume, historical return air volume and historical second air leakage volume corresponding to each of the historical periods, the historical first air leakage volume corresponding to each of the historical periods is calculated; Based on each of the historical pressure difference air volumes and the historical first air leakage volume corresponding to each of the historical pressure difference air volumes, a first air leakage volume fluctuation function corresponding to the basic pressure difference air volume fluctuation value is established; Wherein, determining the first air leakage volume corresponding to the current clean space based on the first air leakage volume fluctuation function and the maximum pressure difference air volume includes: Substituting the maximum pressure difference air volume into the first air leakage volume fluctuation function to obtain the target first air leakage volume corresponding to the maximum pressure difference air volume; Based on the target first air leakage volume, the supply air volume data and the return air volume data, determining the target pressure difference air volume corresponding to the front clean space; Determine a first air leakage volume corresponding to the target pressure difference air volume to obtain a first air leakage volume corresponding to the current clean space; Wherein, the obtaining the opening of the air leakage gap valve corresponding to the second air leakage includes: Obtaining a target relationship function among the flow rate, pressure difference and opening degree of the air leakage gap valve; Based on the target relationship function and the second air leakage, the opening degree of the air leakage gap valve is determined.

2. The clean room pressure difference adaptive control method according to claim 1, characterized in that: The historical first air leakage volume corresponding to each historical period is calculated based on the historical pressure difference air volume, the historical supply air volume, the historical return air volume and the historical second air leakage volume corresponding to each historical period, including: Based on the historical supply air volume and the historical return air volume corresponding to each of the historical periods, determine the historical maximum pressure difference air volume corresponding to each of the historical periods; Calculate the historical maximum pressure difference air volume and the difference between the historical pressure difference air volumes corresponding to each of the historical periods to obtain the historical air leakage volume and the historical air leakage volume corresponding to each of the historical periods; Based on the historical air leakage amount and the historical second air leakage amount corresponding to each of the historical periods, the historical first air leakage amount corresponding to each of the historical periods is calculated.

3. The clean room pressure difference adaptive control method according to claim 2, characterized in that: The establishing of a first air leakage volume fluctuation function corresponding to the basic pressure difference air volume fluctuation value based on each of the historical pressure difference air volumes and the historical first air leakage volume corresponding to each of the historical pressure difference air volumes comprises: Processing each of the historical pressure difference air volumes and the historical first air leakage volume corresponding to each of the historical pressure difference air volumes to obtain a historical pressure difference air volume sequence and a historical first air leakage volume sequence; Gray processing is performed on the historical pressure difference air volume sequence and the historical first air leakage volume sequence respectively to obtain a target pressure difference air volume sequence and a target first air leakage volume sequence; Based on the target pressure difference air volume sequence and the target first air leakage volume sequence, solving the model parameters of the grey prediction model and constructing the grey prediction model; Based on the grey prediction model, the model parameters and the basic pressure difference air volume fluctuation value, a first air leakage volume fluctuation function is established.

4. The clean room pressure difference adaptive control method according to claim 3, characterized in that: The model parameters for solving the grey prediction model include: The target pressure differential air volume sequence and the target first air leakage volume sequence are respectively accumulated to obtain a first target pressure differential air volume sequence and a first target first air leakage volume sequence, and the adjacent elements corresponding to the first target pressure differential air volume sequence and the first target first air leakage volume sequence are averaged to obtain a second target pressure differential air volume sequence and a second target first air leakage volume sequence; Establishing a target differential equation based on the second target pressure difference air volume sequence and the second target first air leakage volume sequence; The parameters in the target differential equation are determined by the least square method to obtain the model parameters of the grey prediction model.

5. A clean room pressure difference adaptive control device, characterized in that: include: The acquisition module is used to obtain the supply air volume data, return air volume data of the current clean space and the basic pressure difference air volume fluctuation value allowed by the current clean space; An establishing module is used to establish a first air leakage volume fluctuation function corresponding to the basic pressure difference air volume fluctuation value, wherein the first air leakage volume is the air leakage volume caused by the sealing of the clean space; A first determination module, configured to determine a maximum pressure difference air volume corresponding to the current clean space based on the supply air volume data and the return air volume data; A second determination module, configured to determine a first air leakage volume corresponding to the current clean space based on the first air leakage volume fluctuation function and the maximum pressure difference air volume; A control module, configured to calculate the absolute value of the difference between the maximum pressure difference air volume and the basic pressure difference air volume fluctuation value based on the first air leakage volume and the maximum pressure difference air volume, obtain the sum of the first air leakage volume and the second air leakage volume, and obtain the second air leakage volume corresponding to the current clean space based on the sum of the first air leakage volume and the second air leakage volume minus the first air leakage volume, and obtain the opening of the air leakage volume slit valve corresponding to the second air leakage volume, so as to adjust the air leakage volume slit valve on the exhaust device based on the opening of the air leakage volume slit valve, wherein the second air leakage volume is the exhaust volume adjusted to adjust the pressure difference in the clean space; Wherein, when establishing the first air leakage volume fluctuation function corresponding to the basic pressure difference air volume fluctuation value, the establishing module is specifically used to: Acquire historical clean data corresponding to the current clean space, wherein the historical clean data includes historical pressure difference air volume, historical supply air volume, historical return air volume, and historical second air leakage volume corresponding to each historical period; Based on the historical pressure difference air volume, historical supply air volume, historical return air volume and historical second air leakage volume corresponding to each of the historical periods, the historical first air leakage volume corresponding to each of the historical periods is calculated; Based on each of the historical pressure difference air volumes and the historical first air leakage volume corresponding to each of the historical pressure difference air volumes, a first air leakage volume fluctuation function corresponding to the basic pressure difference air volume fluctuation value is established; Wherein, when the second determination module determines the first air leakage volume corresponding to the current clean space based on the first air leakage volume fluctuation function and the maximum pressure difference air volume, it is specifically used to: Substituting the maximum pressure difference air volume into the first air leakage volume fluctuation function to obtain the target first air leakage volume corresponding to the maximum pressure difference air volume; Based on the target first air leakage volume, the supply air volume data and the return air volume data, determining the target pressure difference air volume corresponding to the front clean space; Determine a first air leakage volume corresponding to the target pressure difference air volume to obtain a first air leakage volume corresponding to the current clean space; Wherein, when the second determination module obtains the opening of the air leakage gap valve corresponding to the second air leakage, it is specifically used to: Obtaining a target relationship function among the flow rate, pressure difference and opening degree of the air leakage gap valve; Based on the target relationship function and the second air leakage, the opening degree of the air leakage gap valve is determined.

6. An electronic device, characterized in that: The electronic device includes: at least one processor; Memory; At least one application, wherein the at least one application is stored in a memory and configured to be executed by at least one processor, and the at least one application is configured to: execute the clean room pressure difference adaptive control method according to any one of claims 1 to 4.

7. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed in a computer, the computer is caused to execute the clean room pressure difference adaptive control method according to any one of claims 1 to 4.

Images