A comprehensive cleanroom cleanliness analysis system and method

Abstract

This invention provides a comprehensive cleanroom cleanliness analysis system and method. The system includes a data preprocessing module for preprocessing multi-source environmental parameters to obtain target environmental parameters; a coupling analysis module for determining the influence of each environmental parameter individually and in interaction on cleanliness based on the target environmental parameters, and obtaining cleanliness analysis results based on the influence patterns; a dynamic optimization module for generating a control optimization strategy for the cleanroom environment based on the cleanliness analysis results; and a control execution module for outputting control commands to the cleanroom's environmental control equipment according to the control optimization strategy to adjust the cleanroom's cleanliness. This system can accurately quantify the independent and interactive influences of multiple environmental factors on cleanliness, and achieve accurate prediction of cleanliness change trends.

Description

Technical Field

[0001] This invention relates to the field of intelligent monitoring technology for cleanrooms, and in particular to a comprehensive cleanroom cleanliness analysis system and method. Background Technology

[0002] Cleanrooms are critical production environments in high-end manufacturing fields such as electronics, new energy, and pharmaceuticals, and their cleanliness directly impacts product quality and yield. Traditional cleanroom cleanliness control often relies on the independent monitoring and adjustment of single environmental parameters, such as localized adjustments to temperature, humidity, or particulate matter concentration, lacking a systematic analysis of the interactions and coupling effects between multiple environmental parameters. This single-dimensional control method fails to accurately reflect the dynamic changes in cleanliness under complex operating conditions, easily leading to over-adjustment or under-control, resulting in problems such as high energy consumption, poor environmental stability, and high cleanliness maintenance costs.

[0003] Existing cleanliness monitoring systems typically only perform data acquisition and threshold alarm functions. They cannot deeply reveal the comprehensive impact mechanism of multiple factors (such as airflow, temperature and humidity, pressure difference, particulate matter concentration, etc.) on cleanliness. They lack adaptive optimization capabilities based on multi-source data coupling analysis and cannot accurately control the cleanliness of cleanrooms. Summary of the Invention

[0004] This invention provides a comprehensive cleanroom cleanliness analysis system and method to solve the technical problem in the prior art where cleanroom cleanliness control relies on the independent adjustment of a single parameter, resulting in inaccurate control.

[0005] On one hand, the present invention provides a comprehensive cleanroom cleanliness analysis system, comprising: The data acquisition module is used to collect multi-source environmental parameters related to cleanliness within the cleanroom. The data preprocessing module is used to preprocess the multi-source environmental parameters to obtain the target environmental parameters; The coupling analysis module is used to determine the influence of each environmental parameter individually and in interaction on cleanliness based on the target environmental parameters, and to obtain cleanliness analysis results based on the influence rules. The dynamic optimization module is used to generate control optimization strategies for the cleanroom environment based on the cleanliness analysis results. The control execution module is used to output control commands to the environmental conditioning equipment of the cleanroom according to the control optimization strategy, so as to adjust the cleanliness of the cleanroom.

[0006] On the other hand, a comprehensive cleanroom cleanliness analysis method provided by the present invention includes: Collect multi-source environmental parameters related to cleanliness within the cleanroom; The multi-source environmental parameters are preprocessed to obtain the target environmental parameters; Based on the target environmental parameters, the influence of each environmental parameter individually and in combination on cleanliness is determined, and cleanliness analysis results are obtained based on the influence patterns. Based on the cleanliness analysis results, a control optimization strategy for the cleanroom environment is generated. Based on the control optimization strategy, control commands are output to the environmental control equipment of the cleanroom to adjust the cleanliness of the cleanroom.

[0007] This invention provides a comprehensive cleanroom cleanliness analysis system and method. By determining the influence of individual and interactive environmental parameters on cleanliness, and obtaining cleanliness analysis results based on the influence patterns, it breaks through the limitations of traditional cleanroom control that relies on experience or single parameter feedback. It can accurately quantify the independent and interactive influence of multiple environmental factors on cleanliness, achieve accurate prediction of cleanliness change trends, and solve the problems of inaccuracy and lag in response of traditional cleanroom control methods. Attached Figure Description

[0008] To more clearly illustrate the technical solutions in this invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of this invention. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0009] Figure 1 This is a schematic diagram of the structure of the cleanroom cleanliness comprehensive analysis system provided in an embodiment of the present invention; Figure 2 This is a schematic diagram of the coupling analysis module provided in an embodiment of the present invention; Figure 3 This is a flowchart illustrating the comprehensive cleanliness analysis method for cleanrooms provided in this embodiment of the invention. Figure 4 This is a schematic diagram of the structure of the electronic device provided in an embodiment of the present invention. Detailed Implementation

[0010] To make the objectives, technical solutions, and advantages of this invention clearer, the technical solutions of this invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of this invention. All other embodiments obtained by those skilled in the art based on the embodiments of this invention without creative effort are within the scope of protection of this invention.

[0011] Figure 1This is a schematic diagram of the structure of the cleanroom cleanliness comprehensive analysis system provided in an embodiment of the present invention; Figure 2 This is a schematic diagram of the coupling analysis module provided in an embodiment of the present invention.

[0012] See Figure 1 and Figure 2 A cleanroom cleanliness comprehensive analysis system 10 includes a data acquisition module 110, a data preprocessing module 120, a coupling analysis module 130, a dynamic optimization module 140, and a control execution module 150.

[0013] Data acquisition module 110 is used to collect multi-source environmental parameters related to cleanliness within the cleanroom; Cleanliness refers to the permissible number of suspended particles or the concentration of microorganisms per unit volume of air in a cleanroom, typically classified according to international or industry standards such as ISO 14644-1. Multi-source environmental parameters refer to various types of real-time monitoring data that affect cleanliness, and may include at least two of the following: airborne particulate matter concentration, temperature, relative humidity, pressure difference (indoor / outdoor or between areas), airflow velocity, wind speed and direction, and air exchange rate.

[0014] The data preprocessing module 120 is used to preprocess multi-source environmental parameters to obtain target environmental parameters.

[0015] Specifically, the preprocessing includes at least one of the following: Data cleaning, data alignment, and data normalization.

[0016] Data cleaning refers to the process of identifying, correcting, or removing outliers, errors, duplicates, or invalid values ​​from raw, multi-source environmental parameters. For example, removing extreme values ​​caused by momentary sensor malfunctions. Data alignment involves unifying environmental parameter data from different sources, with different collection frequencies, or different timestamps to the same time base or data format to ensure consistency across time in subsequent analysis. For example, aligning temperature data collected every minute with particulate matter data collected every five seconds to a single second time point through interpolation or aggregation. Data normalization involves converting environmental parameter data with different dimensions and orders of magnitude into dimensionless values ​​of a uniform scale or order of magnitude through mathematical transformation. Preprocessing can effectively improve the quality of raw data.

[0017] The coupling analysis module 130 is used to determine the influence of each environmental parameter individually and in interaction on cleanliness based on the target environmental parameters, and to obtain cleanliness analysis results based on the influence rules. Individual effects refer to the impact of a single environmental parameter (such as temperature) on cleanliness (such as particulate matter settling rate) when it changes independently. Interactions (coupling effects) refer to the phenomenon where two or more environmental parameters (such as temperature and humidity, airflow and pressure difference) change together, resulting in synergistic enhancement, cancellation, or nonlinear effects.

[0018] The dynamic optimization module 140 is used to generate control optimization strategies for the cleanroom environment based on the cleanliness analysis results; The control optimization strategy refers to a set of instructions generated based on the cleanliness analysis results to guide the operation of environmental control equipment, aiming to maintain the target cleanliness with better energy consumption. For example, the key environmental parameters currently affecting cleanliness (with 0.5μm particulate matter concentration as the main indicator) are ranked by their influence coefficient as follows: airflow velocity > pressure difference > personnel activity frequency > humidity. A positive synergistic effect between airflow velocity and pressure difference is identified. That is, simultaneously and appropriately increasing both airflow velocity and pressure difference has a greater effect on particulate matter removal (cleanliness improvement) than the sum of the effects of adjusting either one individually. Based on the current equipment status and personnel schedule, it is predicted that within the next 30 minutes, due to the start-up of production line equipment, the cleanliness level may drop from ISO 5 to ISO 6. The following control optimization strategy instruction set is generated, for example, increasing the airflow velocity of the fan filter unit; increasing the pressure difference between the cleanroom and the adjacent corridor.

[0019] For example, the analysis results indicate that the combination of temperature and humidity has little impact on the current cleanliness index. Furthermore, the analysis found that under summer conditions, excessive dehumidification (reducing humidity) slightly weakens the positive effect of low temperature on particle settling (a negative mutual weakening). The current system is operating in a high-energy-consumption mode with low temperature and low humidity. The following control optimization strategies (instruction sets) are generated, such as increasing the indoor temperature setpoint and increasing the indoor relative humidity setpoint. When a negative weakening parameter combination is identified, it indicates that investing excessively strict control resources (energy) on this combination is inefficient. By moderately relaxing the control of temperature and humidity (while still within permissible ranges), the energy consumption of air conditioning and dehumidifiers can be significantly reduced with minimal impact on core cleanliness indicators, thus achieving energy savings while meeting key performance indicators.

[0020] The control execution module 150 is used to output control commands to the environmental control equipment of the cleanroom according to the control optimization strategy, so as to adjust the cleanliness of the cleanroom; Environmental control equipment refers to devices used in cleanrooms to regulate environmental parameters, such as fan filter units, air conditioning units, humidifiers, dehumidifiers, differential pressure control valves, and fresh air systems. These devices regulate the cleanliness of the cleanroom to ultimately ensure that it meets pre-defined cleanliness standards.

[0021] In this embodiment, by determining the influence of each environmental parameter individually and in interaction on cleanliness, and obtaining cleanliness analysis results based on the influence patterns, the limitations of traditional cleanroom control relying on experience or single parameter feedback are overcome. It can accurately quantify the independent and interactive influence of multiple environmental factors on cleanliness, achieve accurate prediction of cleanliness change trends, and solve the problems of inaccuracy and lag in response of traditional cleanroom control methods.

[0022] In one embodiment of this specification, the coupling analysis module 130 includes a single-factor analysis unit 131, a multi-factor interaction unit 132, a pattern extraction unit 133, a cleanliness prediction unit 134, and a result output unit 135.

[0023] The single-factor analysis unit 131 is used to determine the impact of any single environmental parameter change on cleanliness based on the target environmental parameters, and to obtain the single-factor influence relationship. For example, by changing the supply air velocity alone and observing its impact on cleanliness, a univariate mapping relationship between supply air velocity and cleanliness can be established.

[0024] The multi-factor interaction unit 132 is used to determine the impact of at least two environmental parameters changing together on cleanliness based on the target environmental parameters, and to obtain the multi-factor influence relationship. For example, by simultaneously changing the combination of wind speed and temperature and humidity, the combined effect of these factors on cleanliness can be analyzed to establish a multi-factor influence relationship.

[0025] The pattern extraction unit 133 is used to determine the influence patterns of each environmental parameter on cleanliness based on single-factor influence relationships and multi-factor influence relationships; The cleanliness prediction unit 134 is used to determine the trend of cleanliness change of the cleanroom under the current environmental parameter conditions based on the influence law; Specifically, the cleanliness prediction unit 134 achieves trend prediction based on a pre-constructed quantitative model of influence patterns. The construction of the quantitative model of influence patterns includes: the system analyzes and determines the unit influence coefficient of cleanliness when each environmental parameter changes individually, using historical operational data and controlled experiments; furthermore, the system conducts coupling tests on various parameter combinations, identifying and quantifying significant interactions by comparing the actual combined effect with the linear sum of the independent influence coefficients of each parameter. Ultimately, a structured mathematical model containing independent influence terms and key interaction correction terms for each parameter can be formed. During operation, the prediction unit collects current environmental parameters in real time and incorporates known future work plans (such as equipment start-up and shutdown, personnel entry and exit, etc.) to deduce the temporal change sequence of each parameter. The temporal change sequence is input into the aforementioned influence pattern model, and the amount of cleanliness change caused by the combined independent influence and interaction at each moment is calculated sequentially, thus accumulating to generate a cleanliness change prediction curve for a future period. By analyzing the cleanliness change prediction curve, the cleanliness prediction unit 134 can predict the cleanliness compliance status, risk points, and change trends in advance.

[0026] The results output unit 135 is used to integrate single-factor influence relationships, multi-factor influence relationships, influence patterns and trends to generate cleanliness analysis results. Specifically, the result output unit 135 is responsible for structuring and integrating the data generated by the aforementioned units (including single-factor influence relationships, multi-factor influence relationships, influence patterns, and change trends) to form cleanliness analysis results that can be displayed, stored, or used for decision-making. These results are typically presented in the form of visual reports, scoring indicators, etc.

[0027] In this embodiment, through single-factor analysis, multi-factor interaction, pattern extraction, prediction and result output, not only can key influencing factors be identified, but also the synergistic or weakening effects between parameters can be accurately determined, thereby achieving high-precision cleanliness trend prediction.

[0028] In one embodiment of this specification, the pattern extraction unit 133 is further configured to: Step 1: For each environmental parameter, based on its corresponding single-factor influence relationship, determine the unit influence coefficient of the environmental parameter on the change in cleanliness. The unit influence coefficient refers to the change in cleanliness caused by a unit change in a certain environmental parameter. For example, it represents the percentage increase in the concentration of 0.5μm particles caused by a 1°C increase in temperature. The unit influence coefficient characterizes the independent strength and direction (positive or negative) of the parameter's influence on cleanliness.

[0029] Step 2: For any parameter combination consisting of at least two environmental parameters, determine the joint influence coefficient of the parameter combination on the change in cleanliness based on its corresponding multi-factor influence relationship; This includes parameter combinations, such as temperature and humidity, or airflow velocity, pressure difference, and personnel density. The combined influence coefficient refers to the comprehensive impact on cleanliness when all parameters in a given parameter combination undergo a unit change simultaneously. The combined influence coefficient reflects the actual total effect when multiple parameters work together.

[0030] Step 3: Subtract the sum of the unit influence coefficients of each environmental parameter in the parameter combination from the combined influence coefficient of the parameter combination to obtain the difference. Step 4: If the difference exceeds the preset difference threshold, determine that there is an interaction between the environmental parameters in the corresponding parameter combination; Step 5: Determine the type and strength of the interaction; The types of interactions can include positive synergistic enhancement (the combined effect is stronger than the sum of the independent effects) and negative mutual weakening (the combined effect is weaker than the sum of the independent effects).

[0031] Step 6: Based on the unit influence coefficients of all environmental parameters, and the type and intensity of the effects of all interacting parameter combinations, generate the influence laws.

[0032] In this embodiment, by introducing a comparison mechanism between the unit influence coefficient and the joint influence coefficient, it is possible to identify whether there is a significant interaction between environmental parameters, and further determine its type and intensity level, thereby accurately characterizing the impact of multi-factor coupling on cleanliness, avoiding the simplification of complex interaction effects into linear superposition, and significantly improving the accuracy of cleanliness analysis.

[0033] In one embodiment of this specification, determining the type and strength of the interaction includes: When the difference is greater than the preset difference threshold, it is determined that the corresponding parameter combination has a positive synergistic enhancement effect on cleanliness. Specifically, positive synergistic enhancement refers to the combined effect of two or more environmental parameters on cleanliness when they change together, exceeding the sum of the individual effects of each parameter. In other words, they mutually promote and amplify the positive effects on cleanliness. For example, appropriately increasing wind speed and decreasing humidity may together significantly improve particulate matter removal efficiency.

[0034] When the difference is less than zero and the absolute value is greater than the preset difference threshold, it is determined that the corresponding parameter combination has a negative mutual weakening effect on cleanliness. Specifically, negative mutual attenuation refers to the combined effect of multiple environmental parameters being less than the sum of the individual effects of each parameter; that is, they cancel each other out or inhibit each other's impact on cleanliness. For example, while high wind speeds are beneficial for diluting particles, if they simultaneously intensify turbulence, they may disturb the deposited particles and weaken the overall purification effect.

[0035] When the absolute value of the difference is less than or equal to the preset difference threshold, it is determined that there is no interaction between the corresponding parameter combinations; The intensity level of the interaction is determined based on the absolute value of the difference; the larger the absolute value of the difference, the stronger the interaction.

[0036] In this embodiment, by clearly distinguishing between the two fundamentally different types of effects, positive synergistic enhancement and negative mutual weakening, the system can take drastically different countermeasures when formulating optimization strategies. For example, it can focus on suppressing or decoupling dangerous combinations with positive synergy, while considering reasonable utilization of combinations with negative weakening to reduce control costs.

[0037] In one embodiment of this specification, an influence law is generated based on the unit influence coefficients of all environmental parameters and the type and intensity of influence of all interacting parameter combinations, including: Step 1: Generate the corresponding coupling correction term based on the action type and strength of each parameter combination with interaction; Step 2: Take the unit influence coefficient of each environmental parameter as the basic influence term, and add the basic influence term to all coupled correction terms to obtain the influence expression of the cleanliness change, which is taken as the influence law.

[0038] In this embodiment, for example, the unit influence coefficient of temperature on cleanliness is +0.3 (increased temperature leads to increased particle concentration); the unit influence coefficient of humidity is +0.2; and the combination of temperature and humidity has a positive synergistic enhancement effect, with a coupling correction term of +0.15. Taking the independent effects of temperature and humidity (+0.3 and +0.2) as the basic influence terms, and their synergistic effect (+0.15) as the coupling correction term, the final expression for the influence of cleanliness change is constructed as: Cleanliness change ≈ 0.3 × temperature change + 0.2 × humidity change + 0.15 × (temperature and humidity synergistic term). In summary, when temperature and humidity increase simultaneously, the prediction result not only includes their individual effects but also their cumulative effect, making the prediction closer to reality.

[0039] In this embodiment, by taking the independent effects of each parameter as the basic term, the significant interactions are transformed into coupling correction terms, and the two are added together to form a unified effect expression. This not only preserves the main effect of the single factor, but also explicitly incorporates the contribution of multi-factor interactions, significantly improving the accuracy of the model.

[0040] In one embodiment of this specification, a corresponding coupling correction term is generated based on the interaction type and strength of each parameter combination with interaction, including: Step 1: Based on the intensity level of the interaction, look up the corresponding baseline correction value from the preset correction value mapping table; the correction value mapping table records the correspondence between different intensity levels and baseline correction values. Step 2: If the interaction type is positive synergistic enhancement, use the baseline correction value as the coupling correction term corresponding to the parameter combination; Step 3: If the interaction type is negative mutual weakening, then the negative of the baseline correction value is used as the coupling correction term corresponding to the parameter combination.

[0041] In this embodiment, the intensity level of the interaction is converted into a specific benchmark correction value through a preset correction value mapping table, and the sign of the coupling correction term is determined according to the interaction type, which avoids manual setting deviation and improves the consistency of influence law modeling.

[0042] In one embodiment of this specification, the joint influence coefficient is determined in the following manner: For any combination of parameters, each environmental parameter is adjusted from its current operating value to its corresponding preset disturbance step size to obtain the change in cleanliness, which is used as the joint influence coefficient. The unit influence coefficient is determined in the following way: For any environmental parameter, the same preset disturbance step size is adjusted from its current operating value to obtain the change in cleanliness, which is used as the unit influence coefficient.

[0043] In this embodiment, the preset perturbation step size refers to a fixed value set for making minor adjustments to the environmental parameter in order to calculate the influence coefficient. For example, the perturbation step size for temperature is set to ±1℃, and the perturbation step size for humidity is ±5%RH. The preset perturbation step size is the same whether the same environmental parameter is adjusted independently or as a combination of parameters. This embodiment uses a uniform preset perturbation step size for parameter perturbation experiments, ensuring consistency in the calculation process of the influence coefficient and improving the accuracy and repeatability of the coupling analysis.

[0044] In one embodiment of this specification, the cleanroom cleanliness comprehensive analysis system further includes: Display module 160 is used to display cleanliness analysis results and control optimization strategies.

[0045] In this embodiment, the display module 160 refers to a hardware and / or software component used to present the information generated by the system to the operator or management platform in a visual form, such as a touch screen, a web interface, or a mobile terminal application. The display module 160 is used to display the cleanliness analysis results and control optimization strategies, so that relevant personnel can understand the status of the cleanroom in a timely and clear manner.

[0046] Based on the same general inventive concept, this invention also protects a comprehensive method for analyzing the cleanliness of a cleanroom, such as... Figure 3 As shown, Figure 3 This is a flowchart illustrating the comprehensive cleanroom cleanliness analysis method provided in this embodiment of the invention. The following describes the comprehensive cleanroom cleanliness analysis method provided by this invention. The cleanroom cleanliness analysis method described below can be referred to in correspondence with the cleanroom cleanliness analysis system described above. The comprehensive cleanroom cleanliness analysis method can be applied to the cleanroom cleanliness analysis system in any of the above embodiments.

[0047] The comprehensive analysis method for cleanroom cleanliness includes the following steps.

[0048] Step 301: Collect multi-source environmental parameters related to cleanliness in the cleanroom.

[0049] Step 302: Preprocess the multi-source environmental parameters to obtain the target environmental parameters.

[0050] Step 303: Based on the target environmental parameters, determine the influence of each environmental parameter individually and in combination on cleanliness, and obtain the cleanliness analysis results based on the influence patterns.

[0051] Step 304: Based on the cleanliness analysis results, generate a control optimization strategy for the cleanroom environment.

[0052] Step 305: Based on the control optimization strategy, output control commands to the cleanroom's environmental control equipment to adjust the cleanliness of the cleanroom.

[0053] Figure 4 This is a schematic diagram of the structure of the electronic device provided in an embodiment of the present invention.

[0054] like Figure 4 As shown, the electronic device may include a processor 410, a communication interface 420, a memory 430, and a communication bus 440. The processor 410, communication interface 420, and memory 430 communicate with each other via the communication bus 440. The processor 410 can call logical instructions from the memory 430 to execute a comprehensive cleanroom cleanliness analysis method.

[0055] Furthermore, the logical instructions in the aforementioned memory 430 can be implemented as software functional units and, when sold or used as independent products, can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art, or a part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of the present invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0056] On the other hand, the present invention also provides a computer program product, which includes a computer program that can be stored on a non-transitory computer-readable storage medium. When the computer program is executed by a processor, the computer is able to execute the comprehensive cleanroom cleanliness analysis method provided by the above methods.

[0057] In another aspect, the present invention also provides a non-transitory computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, is implemented to perform the comprehensive cleanroom cleanliness analysis method provided by the methods described above.

[0058] The device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs. Those skilled in the art can understand and implement this without any creative effort.

[0059] Through the above description of the embodiments, those skilled in the art can clearly understand that each embodiment can be implemented by means of software plus necessary general-purpose hardware platforms, and of course, it can also be implemented by hardware. Based on this understanding, the above technical solutions, in essence or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, magnetic disk, optical disk, etc., and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute the methods described in the various embodiments or some parts of the embodiments.

[0060] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A comprehensive cleanroom cleanliness analysis system, characterized in that, include: The data acquisition module is used to collect multi-source environmental parameters related to cleanliness within the cleanroom. The data preprocessing module is used to preprocess the multi-source environmental parameters to obtain the target environmental parameters; The coupling analysis module is used to determine the influence of each environmental parameter individually and in interaction on cleanliness based on the target environmental parameters, and to obtain cleanliness analysis results based on the influence rules. The dynamic optimization module is used to generate control optimization strategies for the cleanroom environment based on the cleanliness analysis results. The control execution module is used to output control commands to the environmental conditioning equipment of the cleanroom according to the control optimization strategy, so as to adjust the cleanliness of the cleanroom.

2. The cleanroom cleanliness comprehensive analysis system according to claim 1, characterized in that, The coupling analysis module includes: The single-factor analysis unit is used to determine the impact of any single environmental parameter change on cleanliness based on the target environmental parameters, and to obtain the single-factor influence relationship; The multi-factor interaction unit is used to determine the impact of at least two environmental parameters changing together on cleanliness based on the target environmental parameters, and to obtain the multi-factor influence relationship; The pattern extraction unit is used to determine the influence patterns of each environmental parameter on cleanliness based on the single-factor influence relationship and the multi-factor influence relationship; The cleanliness prediction unit is used to determine the trend of cleanliness change of the cleanroom under the current environmental parameter conditions based on the influence law. The results output unit is used to integrate the single-factor influence relationship, the multi-factor influence relationship, the influence law, and the change trend to generate cleanliness analysis results.

3. The cleanroom cleanliness comprehensive analysis system according to claim 2, characterized in that, The pattern extraction unit is also used for: For each environmental parameter, based on its corresponding single-factor influence relationship, determine the unit influence coefficient of the environmental parameter on the change in cleanliness; For any combination of parameters consisting of at least two environmental parameters, the joint influence coefficient of the parameter combination on the change in cleanliness is determined based on its corresponding multi-factor influence relationship. The difference is obtained by subtracting the sum of the unit influence coefficients of each environmental parameter in the parameter combination from the joint influence coefficient of the parameter combination. If the difference exceeds a preset difference threshold, it is determined that there is an interaction between the environmental parameters in the corresponding parameter combination; Determine the type and strength of the interaction; The influence law is generated based on the unit influence coefficients of all environmental parameters, as well as the type and intensity of the effects of all parameter combinations that interact.

4. The cleanroom cleanliness comprehensive analysis system according to claim 3, characterized in that, Determining the type and strength of the interaction includes: When the difference is greater than the preset difference threshold, it is determined that the corresponding parameter combination has a positive synergistic enhancement effect on cleanliness. When the difference is less than zero and the absolute value is greater than the preset difference threshold, it is determined that the corresponding parameter combination has a negative mutual weakening effect on cleanliness. When the absolute value of the difference is less than or equal to the preset difference threshold, it is determined that there is no interaction between the corresponding parameter combinations; The intensity level of the interaction is determined based on the absolute value of the difference; where the larger the absolute value of the difference, the higher the intensity of the interaction.

5. The cleanroom cleanliness comprehensive analysis system according to claim 3, characterized in that, The influence law is generated based on the unit influence coefficients of all environmental parameters, and the type and intensity of influence of all interacting parameter combinations, including: Based on the type and strength of the interaction of each parameter combination, a corresponding coupling correction term is generated; The unit influence coefficient of each environmental parameter is used as the basic influence term, and the basic influence term is added to all coupled correction terms to obtain the influence expression of the change in cleanliness, which is used as the influence law.

6. The cleanroom cleanliness comprehensive analysis system according to claim 5, characterized in that, The step of generating a corresponding coupling correction term based on the interaction type and strength of each interacting parameter combination includes: Based on the intensity level of the interaction, the corresponding baseline correction value is retrieved from a preset correction value mapping table; wherein, the correction value mapping table records the correspondence between different intensity levels and baseline correction values; If the interaction type is positive synergistic enhancement, the baseline correction value is used as the coupling correction term corresponding to the parameter combination; If the interaction type is negative mutual weakening, then the negative of the baseline correction value is used as the coupling correction term corresponding to the parameter combination.

7. The cleanroom cleanliness comprehensive analysis system according to claim 3, characterized in that, The joint impact coefficient is determined in the following manner: For any combination of parameters, each environmental parameter is adjusted from its current operating value to its corresponding preset disturbance step size to obtain the change in cleanliness, which is used as the joint influence coefficient. The unit influence coefficient is determined in the following way: For any environmental parameter, the same preset disturbance step size is adjusted from its current operating value to obtain the change in cleanliness, which is used as the unit influence coefficient.

8. The cleanroom cleanliness comprehensive analysis system according to claim 1, characterized in that, The preprocessing includes at least one of the following: Data cleaning, data alignment, and data normalization.

9. The cleanroom cleanliness comprehensive analysis system according to claim 1, characterized in that, Also includes: The display module is used to display the cleanliness analysis results and the control optimization strategy.

10. A comprehensive analysis method for cleanroom cleanliness, characterized in that, include: Collect multi-source environmental parameters related to cleanliness within the cleanroom; The multi-source environmental parameters are preprocessed to obtain the target environmental parameters; Based on the target environmental parameters, the influence of each environmental parameter individually and in combination on cleanliness is determined, and cleanliness analysis results are obtained based on the influence patterns. Based on the cleanliness analysis results, a control optimization strategy for the cleanroom environment is generated. Based on the control optimization strategy, control commands are output to the environmental control equipment of the cleanroom to adjust the cleanliness of the cleanroom.

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