High-grade biosafety laboratory environment quality control method

Abstract

The invention discloses a high-grade biosafety laboratory environment quality control method, and particularly relates to the field of biosafety, and the method comprises the following steps: S100, obtaining environment information and management information in a daily operation process of a biosafety laboratory; step S200, the environment information comprises temperature information, pressure difference information and humidity information in the biosafety laboratory, and the management information comprises personnel access spraying management information and sample access disinfection information; s300, normalizing the temperature information, the pressure difference information, the humidity information, the personnel access spraying management information and the sample access disinfection information to obtain a health state coefficient of the biosafety laboratory; and step S400, predicting the laboratory health state coefficient. According to the invention, through comprehensive monitoring, accurate analysis, prospective prediction and targeted response, a powerful guarantee is provided for safe and stable operation of a high-grade biosafety laboratory, and great significance is provided for work of biomedical research, disease prevention and control and the like.

Description

Technical Field

[0001] The present invention relates to the field of biosafety, and more specifically, to a high-level biosafety laboratory environmental quality control method. Background Art

[0002] High-level biosafety laboratories usually refer to laboratories with biosafety protection levels of level 3 (BSL-3) and level 4 (BSL-4). These laboratories mainly deal with microorganisms or viruses with high pathogenicity, high infectivity, and high toxicity. The laboratory has a high degree of physical isolation measures, including multiple airtight doors, which divide the laboratory into different areas, such as clean areas, buffer areas, and core operating areas, to limit the spread of biological factors. The air pressure difference between different areas is also strictly controlled, and the core operating area is generally negative pressure to prevent pathogens from leaking into the external environment. Equipped with an efficient ventilation system, it can effectively filter out microorganisms in the air after being filtered by a high-efficiency air filter (HEPA), and the filtration efficiency is usually as high as 99.97% or more. The ventilation system will also accurately adjust the air volume and wind speed of the supply and exhaust air according to the air pressure requirements of different areas to ensure the stability and safety of the airflow direction.

[0003] There are many shortcomings in the existing laboratory environmental control methods, such as the lack of systematic comprehensive monitoring and control means, the inability to effectively coordinate the control of physical, chemical, biological and other environmental factors, the incomplete biosafety control of personnel and sample entry and exit processes, and the inability to comprehensively consider the operating status data and basic information of the biosafety laboratory, accurately evaluate and predict the health status of the biosafety laboratory, so as to ensure the safe and stable operation of the biosafety laboratory.

[0004] In order to solve the above problems, a technical solution is now provided. Summary of the invention

[0005] In order to overcome the above-mentioned defects of the prior art, an embodiment of the present invention provides a high-level biosafety laboratory environment quality control method to solve the problems raised in the above-mentioned background technology.

[0006] To achieve the above object, the present invention provides the following technical solutions: A high-level biosafety laboratory environmental quality control method comprises the following steps: Step S100, obtaining environmental information and management information during the daily operation of the biosafety laboratory; Step S200, the environmental information includes the temperature information, pressure difference information and humidity information in the biosafety laboratory, and the management information includes the personnel entry and exit spray management information and the sample entry and exit disinfection information; Step S300, obtaining a biosafety laboratory health status coefficient by normalizing temperature information, pressure difference information, humidity information, personnel entry and exit spray management information, and sample entry and exit disinfection information; Step S400, predicting the laboratory health status coefficient to obtain a biosafety laboratory health status prediction index; Step S500, generating a safe signal, an adjustment signal or a shutdown maintenance signal based on the comparison between the biosafety laboratory health status prediction index and the biosafety laboratory health status prediction index threshold.

[0007] In a preferred embodiment, step S200 specifically includes the following contents: Temperature sensors, differential pressure sensors and humidity sensors are installed in the biosafety laboratory to obtain temperature information, differential pressure information and humidity information respectively; Install cameras in the biosafety laboratory to obtain information on personnel entry and exit spray management and sample entry and exit disinfection information; When the camera collects images, it generates a target viewpoint image function with the same content as the initial viewpoint image, which is defined as: ; in, represents the image index, Indicates that the image is The latent space representation at the iteration is: The transformation matrix representing the camera matrix of the target viewpoint and the reference viewpoint, represents the target viewpoint image function; The consistency between different views is modeled and the consistency between the reference viewpoint image and the target viewpoint image is calculated using the following formula: ; in, A function representing the consistency between the reference viewpoint image and the target viewpoint image, represents the latent space representation of the target view, represents the time step of the model; The joint image distribution of multiple views is modeled and expressed as: ; in, represents the latent space of the image set, Indicates The latent space of the image set rendered by the neural radiance field at iteration , represents the corresponding camera matrix set, and Respectively represent reference images and text prompts used to control image editing, represents a set of viewpoints, A function that represents the consistency between the reference viewpoint image and the target viewpoint image.

[0008] In a preferred embodiment, step S200 specifically further includes the following contents: Plotting the reference viewpoint image and the target viewpoint image into a curve graph; A function threshold of consistency between the reference viewpoint image and the target viewpoint image is set. In the curve graph, the function threshold of consistency between the reference viewpoint image and the target viewpoint image is used to divide the curve into two areas, which respectively represent the parts within the function threshold of consistency between the reference viewpoint image and the target viewpoint image and the parts outside the function threshold of consistency between the reference viewpoint image and the target viewpoint image; Use the camera to record the personnel entry and exit spray management information and sample entry and exit disinfection information to obtain the target viewpoint image; Importing the target viewpoint image into the curve graph and comparing it with the part within the function threshold of the consistency between the reference viewpoint image and the target viewpoint image and the part outside the function threshold of the consistency between the reference viewpoint image and the target viewpoint image, obtaining data of the part outside the function threshold of the consistency between all reference viewpoint images and the target viewpoint image and data within the function threshold of the consistency between the reference viewpoint image and the target viewpoint image; The data outside the function threshold of the consistency between the reference viewpoint image and the target viewpoint image is set as the hidden coefficient, marked as , the data within the function threshold of the consistency between the reference viewpoint image and the target viewpoint image is set as the normal coefficient, marked as .

[0009] In a preferred embodiment, step S300 specifically includes the following contents: Obtain the standard temperature information, pressure difference information, humidity information, hidden worry factor information and normal coefficient information in the biosafety laboratory, and mark the standard temperature information, pressure difference information, humidity information, hidden worry factor information and normal coefficient information as , , , and ; Get the maximum and minimum values ​​of standard temperature information, pressure difference information, humidity information, hidden worry coefficient information and normal coefficient information, marked as , , , , , , , , and , the differences between the maximum and minimum values ​​of standard temperature information, pressure difference information, humidity information, hidden worry coefficient information and normal coefficient information are marked as , , , and ; In a time period, obtain n real-time values, marked as , , , and ; After normalization, the biosafety laboratory health status coefficient is obtained, and the calculation formula is: .

[0010] In a preferred embodiment, step S400 specifically includes the following contents: The laboratory health status coefficient is predicted to obtain the biosafety laboratory health status prediction index, and the calculation formula is: ; In the formula, This is the first time that the biosafety laboratory health status coefficient has been obtained. is the biosafety laboratory health status coefficient obtained for the second time. This is the biosafety laboratory health status coefficient obtained for the third time. are respectively the preset proportional coefficients of the health status coefficient of the biosafety laboratory obtained for the first time, the health status coefficient of the biosafety laboratory obtained for the second time, and the health status coefficient of the biosafety laboratory obtained for the third time, and Both are greater than 0.

[0011] In a preferred embodiment, step S500 specifically includes the following contents: A biosafety laboratory health status prediction index threshold is set, and the biosafety laboratory health status prediction index is compared with the biosafety laboratory health status prediction index threshold.

[0012] In a preferred embodiment, step S500 specifically further includes the following contents: If the biosafety laboratory health status prediction index is less than the biosafety laboratory health status prediction index threshold, a safe signal is generated; if the biosafety laboratory health status prediction index is greater than or equal to the biosafety laboratory health status prediction index threshold, an adjustment signal or a shutdown maintenance signal is generated.

[0013] In a preferred embodiment, the maximum and minimum values ​​of the biosafety laboratory health status prediction index are obtained, which are marked as and ; Calculate the optimal index for predicting the health status of biosafety laboratories, marked as ; The calculation formula is: ; A biosafety laboratory health status prediction preferred index threshold is set. When the biosafety laboratory health status prediction preferred index is less than the biosafety laboratory health status prediction preferred index threshold, an adjustment signal is generated. If the biosafety laboratory health status prediction preferred index is greater than or equal to the biosafety laboratory health status prediction preferred index threshold, a shutdown maintenance signal is generated.

[0014] The technical effects and advantages of the high-level biosafety laboratory environmental quality control method of the present invention are as follows: 1. Comprehensively obtain the environmental information (temperature, pressure difference, humidity) and management information (spraying for personnel in and out, disinfection for samples in and out) of the biosafety laboratory, and deeply process the relevant data through image analysis technology, forming a comprehensive biosafety assurance system covering environmental monitoring, personnel management, sample management and image analysis. All links work closely together to prevent and control biosafety risks in all aspects; 2. Normalize data of different types and magnitudes to make physical quantities such as temperature, pressure difference, humidity and quantitative indicators such as hidden worry coefficient and normal coefficient comparable. When comprehensively evaluating the health status of the laboratory, the influence of various factors can be considered more fairly and accurately to avoid evaluation bias caused by differences in data magnitude. The calculated biosafety laboratory health status coefficient is a quantitative indicator that intuitively reflects the health of the laboratory at a certain moment or time period, making it convenient for managers to quickly understand the overall situation without having to analyze the original data one by one. At the same time, the hidden worry coefficient and normal coefficient obtained by image consistency analysis can be used to quantitatively evaluate image consistency, providing a basis for evaluating the operating status of the laboratory; 3. Calculate and predict the health status prediction index of the biosafety laboratory using historical health status coefficient data, so that managers can gain insight into the development trend of the laboratory health status in advance and have a rough estimate of the future health status, so as to take preventive measures in advance and achieve forward-looking management. Combine the real-time health status coefficient and the prediction index to build a dual early warning system. When both show abnormalities, it strongly indicates high risk, prompting managers to take emergency intervention measures in a timely manner, greatly improving the accuracy and timeliness of risk identification, and reducing biosafety risks and the probability of laboratory operation failures; 4. Through comprehensive monitoring, precise analysis, forward-looking prediction and targeted response, it provides strong guarantees for the safe and stable operation of high-level biosafety laboratories, which is of great significance to biomedical research, disease prevention and control and other work. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] Figure 1 The present invention is a flow chart of a high-level biosafety laboratory environmental quality control method. DETAILED DESCRIPTION

[0016] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0017] Example 1

[0018] Figure 1 The present invention provides a high-level biosafety laboratory environmental quality control method, which specifically includes the following steps: Step S100, obtaining environmental information and management information during the daily operation of the biosafety laboratory; Step S200, the environmental information includes the temperature information, pressure difference information and humidity information in the biosafety laboratory, and the management information includes the personnel entry and exit spray management information and the sample entry and exit disinfection information; Step S300, obtaining a biosafety laboratory health status coefficient by normalizing temperature information, pressure difference information, humidity information, personnel entry and exit spray management information, and sample entry and exit disinfection information; Step S400, predicting the laboratory health status coefficient to obtain a biosafety laboratory health status prediction index; Step S500, generating a safe signal, an adjustment signal or a shutdown maintenance signal based on the comparison between the biosafety laboratory health status prediction index and the biosafety laboratory health status prediction index threshold.

[0019] Step S200 specifically includes the following contents: Temperature sensors, differential pressure sensors and humidity sensors are installed in the biosafety laboratory to obtain temperature information, differential pressure information and humidity information respectively; Install cameras in the biosafety laboratory to obtain information on personnel entry and exit spray management and sample entry and exit disinfection information; When the camera collects images, it generates a target viewpoint image function with the same content as the initial viewpoint image, which is defined as: ; in, represents the image index, Indicates that the image is The latent space representation at the iteration is: The transformation matrix representing the camera matrix of the target viewpoint and the reference viewpoint, represents the target viewpoint image function; The consistency between different views is modeled and the consistency between the reference viewpoint image and the target viewpoint image is calculated using the following formula: ; in, A function representing the consistency between the reference viewpoint image and the target viewpoint image, represents the latent space representation of the target view, represents the time step of the model; The joint image distribution of multiple views is modeled and expressed as: ; in, represents the latent space of the image set, Indicates The latent space of the image set rendered by the neural radiance field at iteration , represents the corresponding camera matrix set, and Respectively represent reference images and text prompts used to control image editing, represents a set of viewpoints, A function that represents the consistency between the reference viewpoint image and the target viewpoint image.

[0020] It should be added that by generating the target viewpoint image function and modeling the consistency between different views, the image data collected by the camera can be better processed and analyzed. This has advantages in many aspects. For example, in image recognition and analysis, the recognition accuracy of scenes and objects inside the laboratory can be improved. Modeling and representing the joint image distribution of multiple views provides a basis for more in-depth image analysis and processing.

[0021] Combining the above measures, a comprehensive biosafety assurance system covering environmental monitoring, personnel management, sample management and image analysis has been formed. The cooperation and support of each link can more effectively prevent and control biosafety risks, ensure the safe operation of high-level biosafety laboratories, protect the health and safety of experimental personnel, and at the same time ensure the accuracy and reliability of experimental results, providing a solid foundation and guarantee for important work such as biomedical research and disease prevention and control.

[0022] Step S200 specifically includes the following contents: Plotting the reference viewpoint image and the target viewpoint image into a curve graph; A function threshold of consistency between the reference viewpoint image and the target viewpoint image is set. In the curve graph, the function threshold of consistency between the reference viewpoint image and the target viewpoint image is used to divide the curve into two areas, which respectively represent the parts within the function threshold of consistency between the reference viewpoint image and the target viewpoint image and the parts outside the function threshold of consistency between the reference viewpoint image and the target viewpoint image; Use the camera to record the personnel entry and exit spray management information and sample entry and exit disinfection information to obtain the target viewpoint image; Importing the target viewpoint image into the curve graph and comparing it with the part within the function threshold of the consistency between the reference viewpoint image and the target viewpoint image and the part outside the function threshold of the consistency between the reference viewpoint image and the target viewpoint image, obtaining data of the part outside the function threshold of the consistency between all reference viewpoint images and the target viewpoint image and data within the function threshold of the consistency between the reference viewpoint image and the target viewpoint image; The data outside the function threshold of the consistency between the reference viewpoint image and the target viewpoint image is set as the hidden coefficient, marked as , the data within the function threshold of the consistency between the reference viewpoint image and the target viewpoint image is set as the normal coefficient, marked as .

[0023] It should be added that drawing the reference viewpoint image and the target viewpoint image into a curve graph can present the relationship and consistency between the two in an intuitive way. This visualization method allows experimenters or managers to quickly and clearly understand the characteristics and change trends of image data without in-depth analysis of complex numerical data, greatly improving the readability and comprehensibility of information.

[0024] By setting the consistency function threshold and dividing the area in the curve graph, the different states of consistency between the reference viewpoint image and the target viewpoint image (within the threshold and outside the threshold) are clearly distinguished. This helps to quickly identify parts that may have problems or abnormalities, allowing relevant personnel to quickly focus on areas that need attention, improving work efficiency and the pertinence of problem troubleshooting.

[0025] Importing the target viewpoint image into the curve chart and comparing it with different areas can accurately obtain the data outside and inside the consistency function threshold. This data classification method facilitates subsequent analysis and processing, so that different measures can be taken for different types of data. For example, for data outside the threshold (the hidden worry coefficient part), a more in-depth investigation and analysis can be carried out to determine whether there are safety hazards or operational violations; while for data within the threshold (the normal coefficient part), it can be used as a reference and benchmark for normal operation.

[0026] The data outside the consistency function threshold is set as the worry coefficient, and the data within the threshold is set as the normal coefficient, which realizes the quantitative evaluation of the image consistency. The worry coefficient can be used as a risk indicator to intuitively reflect the possible inconsistency or abnormality in the image, and provide a quantitative basis for evaluating the operating status of the biosafety laboratory. By monitoring and analyzing the worry coefficient, potential risk factors can be discovered in time, and corresponding prevention and improvement measures can be taken to improve the safety and reliability of the laboratory.

[0027] By using cameras to record the spray management information of personnel entering and exiting and the disinfection information of samples entering and exiting, and combining it with the above-mentioned image consistency analysis method, the flow of personnel and samples can be monitored more accurately. For the spray management of personnel entering and exiting, by comparing the consistency of the target viewpoint image with the reference viewpoint image, it can be ensured that personnel perform spray disinfection in accordance with the prescribed process to prevent biosafety risks caused by human negligence or illegal operations; for the disinfection information of samples entering and exiting, it can also ensure that the samples are effectively handled when entering and leaving the laboratory, reducing the possibility of samples spreading biohazard factors.

[0028] The acquired data of hidden worry coefficient and normal coefficient and related image information can be used to trace the problem links in the process of personnel and sample management. For example, if the hidden worry coefficient is high in a certain period of time, it may mean that there are problems in the spraying of personnel entering and exiting or the disinfection of samples entering and exiting during that period of time. By viewing the corresponding images and data, the specific problems can be accurately found, and then the management process can be improved and optimized in a targeted manner, so as to continuously improve the management level and biosafety assurance capabilities of the laboratory.

[0029] These measures together constitute a relatively complete biosafety monitoring and management system. From environmental parameter monitoring to personnel and sample management, to image data analysis and processing, each link cooperates and complements each other, which can comprehensively and systematically guarantee the safe operation of the biosafety laboratory. By timely discovering and handling potential safety hazards, the risk of leakage and spread of biohazard factors is effectively reduced, the health and safety of experimenters are protected, and the accuracy and reliability of experimental results are also ensured.

[0030] Step S300 specifically includes the following contents: Obtain the standard temperature information, pressure difference information, humidity information, hidden worry factor information and normal coefficient information in the biosafety laboratory, and mark the standard temperature information, pressure difference information, humidity information, hidden worry factor information and normal coefficient information as , , , and ; Get the maximum and minimum values ​​of standard temperature information, pressure difference information, humidity information, hidden worry coefficient information and normal coefficient information, marked as , , , , , , , , and , the differences between the maximum and minimum values ​​of standard temperature information, pressure difference information, humidity information, hidden worry coefficient information and normal coefficient information are marked as , , , and ; In a time period, obtain n real-time values, marked as , , , and ; After normalization, the biosafety laboratory health status coefficient is obtained, and the calculation formula is: .

[0031] It should be added that by obtaining the maximum and minimum values ​​of various information (standard temperature, pressure difference, humidity, hidden worry coefficient, normal coefficient) in the biosafety laboratory and calculating their difference, a basis is provided for the subsequent normalization processing. Normalization processing converts data of different types and magnitudes (such as physical quantities such as temperature, pressure difference, humidity and quantitative indicators such as hidden worry coefficient and normal coefficient) into the same scale range (usually between 0 and 1), making these originally large differences in data comparable. In this way, when comprehensively evaluating the health status of the biosafety laboratory, the influence of various factors can be considered more fairly and accurately, avoiding the neglect or overemphasis of certain factors due to differences in data magnitude.

[0032] The standard temperature information, pressure difference information, humidity information, hidden worry factor information and normal factor information are all included in the calculation of the biosafety laboratory health status coefficient, realizing a comprehensive assessment of the laboratory operation status. Temperature, pressure difference and humidity are important physical factors that affect the stability of the laboratory environment and biosafety, while the hidden worry factor and normal factor reflect the situation of personnel and sample management and the potential risks reflected by image consistency. Combining these factors, we can have a more comprehensive and accurate understanding of the overall health status of the laboratory, not just limited to a single environmental parameter or management link, so as to timely discover various potential problems that may affect biosafety.

[0033] By obtaining multiple real-time values ​​within a time period and calculating the biosafety laboratory health status coefficient based on these real-time values, real-time monitoring of the laboratory status is achieved. By continuously updating the health status coefficient, the changing trend during the laboratory operation process can be tracked in real time. Once the health status coefficient fluctuates abnormally (for example, approaching or exceeding the preset threshold range), an early warning signal can be issued in time to prompt relevant personnel to check and deal with it. This real-time monitoring and early warning mechanism helps to take measures when problems just appear or are still in the embryonic stage to avoid further deterioration of the problem, thereby improving the safety and reliability of the laboratory.

[0034] The final biosafety laboratory health status coefficient is a quantitative indicator that can intuitively reflect the health of the laboratory at a certain moment or in a certain period of time. Managers can quickly understand the overall situation of the laboratory based on this quantitative result without having to analyze each raw data one by one.

[0035] Step S400 specifically includes the following contents: The laboratory health status coefficient is predicted to obtain the biosafety laboratory health status prediction index, and the calculation formula is: ; In the formula, This is the first time that the biosafety laboratory health status coefficient has been obtained. is the biosafety laboratory health status coefficient obtained for the second time. This is the biosafety laboratory health status coefficient obtained for the third time. are respectively the preset proportional coefficients of the health status coefficient of the biosafety laboratory obtained for the first time, the health status coefficient of the biosafety laboratory obtained for the second time, and the health status coefficient of the biosafety laboratory obtained for the third time, and Both are greater than 0.

[0036] It should be added that by using this formula to predict the laboratory health status coefficient and obtain the biosafety laboratory health status prediction index, it is possible to gain insight into the development trend of the laboratory health status in advance. This allows managers to no longer be limited to the current laboratory status, but to have a rough estimate of the laboratory health status in the future.

[0037] This method makes full use of historical data and takes into account the changes in the laboratory's health status in the recent period of time. The health status coefficient at different time points reflects the operating status of the laboratory at different stages. Through weighted summation, these historical information can be integrated to more comprehensively reflect the dynamic changes and trends of the laboratory's health status. For example, if the health status coefficient of the previous few times shows a gradual downward trend, and the prediction index also shows that this trend will continue, then it can be more accurately judged that there may be some gradually accumulated problems in the laboratory that need to be checked and resolved in a timely manner.

[0038] Combining the real-time monitored health status coefficient and the predicted health status prediction index, a more complete risk warning system can be constructed. When the real-time health status coefficient is abnormal and the prediction index also shows a bad trend, it can more strongly remind managers that the laboratory is facing a high risk and needs to take emergency measures to intervene immediately. This dual warning mechanism can greatly improve the accuracy and timeliness of risk identification and effectively reduce the probability of biosafety risks and laboratory operation failures.

[0039] Step S500 specifically includes the following contents: A biosafety laboratory health status prediction index threshold is set, and the biosafety laboratory health status prediction index is compared with the biosafety laboratory health status prediction index threshold.

[0040] Step S500 specifically includes the following contents: If the biosafety laboratory health status prediction index is less than the biosafety laboratory health status prediction index threshold, a safe signal is generated; if the biosafety laboratory health status prediction index is greater than or equal to the biosafety laboratory health status prediction index threshold, an adjustment signal or a shutdown maintenance signal is generated.

[0041] Get the maximum and minimum values ​​of the biosafety laboratory health status prediction index, marked as and ; Calculate the optimal index for predicting the health status of biosafety laboratories, marked as ; The calculation formula is: ; A biosafety laboratory health status prediction preferred index threshold is set. When the biosafety laboratory health status prediction preferred index is less than the biosafety laboratory health status prediction preferred index threshold, an adjustment signal is generated. If the biosafety laboratory health status prediction preferred index is greater than or equal to the biosafety laboratory health status prediction preferred index threshold, a shutdown maintenance signal is generated.

[0042] It should be added that by setting the threshold of the biosafety laboratory health status prediction index, the different risk levels of the laboratory health status can be clearly distinguished. When the prediction index is less than the threshold, a safe signal is generated, indicating that although the laboratory has not yet reached a crisis state, there may be potential risks and it needs to be treated with caution; when the prediction index is greater than or equal to the threshold, an adjustment signal or a shutdown maintenance signal is generated, indicating that the laboratory health status may be on the verge of danger or no longer meets safety requirements, and more powerful measures need to be taken. This hierarchical response mechanism helps laboratory managers accurately control the degree of risk, take corresponding and reasonable measures according to different signals, and avoid overreaction or underreaction.

[0043] The maximum and minimum values ​​of the biosafety laboratory health status prediction index are obtained to calculate the preferred index, taking into account the fluctuation range of the prediction index. This is very important for evaluating the stability and reliability of the laboratory health status. A prediction index with large fluctuations may mean that there are some unstable factors or potential failure hazards in the laboratory, and even if its average value may be within the threshold range, it still needs special attention. The preferred index can more comprehensively reflect this volatility and provide managers with a more sophisticated evaluation tool.

[0044] The entire process, from the prediction index to the optimization index, evaluates and warns the health status of the laboratory from different angles, forming a multi-dimensional safety assurance system. Through the progressive judgment and signal generation mechanism, various risk situations that may occur in the laboratory are considered as comprehensively as possible. Whether it is the potential risk shown by the prediction index or the volatility risk reflected by the optimization index, they can be captured in time and trigger corresponding safety measures. This multi-dimensional assurance mechanism helps to enhance the robustness of the laboratory system and reduce the possibility of biosafety accidents.

[0045] The above formulas are all dimensionless and numerical calculations. The formula is a formula for the most recent real situation obtained by collecting a large amount of data and performing software simulation. The preset parameters and thresholds in the formula are set by technicians in this field according to actual conditions.

[0046] The above embodiments may be implemented in whole or in part by software, hardware, firmware or any other combination thereof. When implemented by software, the above embodiments may be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions or computer programs. When the computer instructions or computer programs are loaded or executed on a computer, the process or function described in the embodiment of the present application is generated in whole or in part. The computer may be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions may be stored in a computer-readable storage medium, or may be transmitted from one computer-readable storage medium to another computer-readable storage medium. For example, the computer instructions may be transmitted from one website, computer, server or data center to another website, computer, server or data center by wired (e.g., infrared, wireless, microwave, etc.) means. The computer-readable storage medium may be any available medium that a computer can access or a data storage device such as a server or data center that contains one or more available media sets. The available medium may be a magnetic medium (e.g., a floppy disk, a hard disk, a tape), an optical medium (e.g., a DVD), or a semiconductor medium. The semiconductor medium may be a solid-state hard disk.

[0047] Those of ordinary skill in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of this application.

[0048] In the several embodiments provided in the present application, it should be understood that the disclosed methods can be implemented in other ways. For example, the device embodiments described above are only schematic, for example, the division of the units is only a logical function division, and there may be other division methods in actual implementation. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed may be through some interfaces, indirect coupling or communication connection of devices or units, which may be electrical, mechanical or other forms.

[0049] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, and may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0050] In addition, each functional unit in each embodiment of the present application may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit.

[0051] If the functions are implemented in the form of software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present application can be essentially or partly embodied in the form of a software product that contributes to the prior art. The computer software product is stored in a storage medium and includes several instructions for a computer device (which can be a personal computer, server, or network device, etc.) to perform all or part of the steps of the methods described in each embodiment of the present application. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM), random access memory (RAM), disk or optical disk, and other media that can store program codes.

[0052] The above is only a specific implementation of the present application, but the protection scope of the present application is not limited thereto. Any person skilled in the art who is familiar with the present technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be included in the protection scope of the present application. Therefore, the protection scope of the present application should be based on the protection scope of the claims.

[0053] Finally: The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the protection scope of the present invention.

Claims

1. A high-level biosafety laboratory environmental quality control method, characterized in that: The steps include: Step S100, obtaining environmental information and management information during the daily operation of the biosafety laboratory; Step S200, the environmental information includes the temperature information, pressure difference information and humidity information in the biosafety laboratory, and the management information includes the personnel entry and exit spray management information and the sample entry and exit disinfection information; Step S300, obtaining a biosafety laboratory health status coefficient by normalizing temperature information, pressure difference information, humidity information, personnel entry and exit spray management information, and sample entry and exit disinfection information; Step S400, predicting the laboratory health status coefficient to obtain a biosafety laboratory health status prediction index; Step S400 specifically includes the following contents: The laboratory health status coefficient is predicted to obtain the biosafety laboratory health status prediction index, and the calculation formula is: ； In the formula, This is the first time that the biosafety laboratory health status coefficient has been obtained. is the biosafety laboratory health status coefficient obtained for the second time. This is the biosafety laboratory health status coefficient obtained for the third time. are respectively the preset proportional coefficients of the health status coefficient of the biosafety laboratory obtained for the first time, the health status coefficient of the biosafety laboratory obtained for the second time, and the health status coefficient of the biosafety laboratory obtained for the third time, and All are greater than 0; Step S500, generating a safe signal, an adjustment signal or a shutdown maintenance signal based on the comparison between the biosafety laboratory health status prediction index and the biosafety laboratory health status prediction index threshold.

2. A high-level biosafety laboratory environmental quality control method according to claim 1, characterized in that: Step S200 specifically includes the following contents: Temperature sensors, differential pressure sensors and humidity sensors are installed in the biosafety laboratory to obtain temperature information, differential pressure information and humidity information respectively; Install cameras in the biosafety laboratory to obtain information on personnel entry and exit spray management and sample entry and exit disinfection information; When the camera collects images, it generates a target viewpoint image function with the same content as the initial viewpoint image, which is defined as: ； in, represents the image index, Indicates that the image is The latent space representation at the iteration is: The transformation matrix representing the camera matrix of the target viewpoint and the reference viewpoint, represents the target viewpoint image function; The consistency between different views is modeled and the consistency between the reference viewpoint image and the target viewpoint image is calculated using the following formula: ； in, A function representing the consistency between the reference viewpoint image and the target viewpoint image, represents the latent space representation of the target view, represents the time step of the model; The joint image distribution of multiple views is modeled and expressed as: ； in, represents the latent space of the image set, Indicates The latent space of the image set rendered by the neural radiance field at iteration , represents the corresponding camera matrix set, and Respectively represent reference images and text prompts used to control image editing, represents a set of viewpoints, A function that represents the consistency between the reference viewpoint image and the target viewpoint image.

3. A high-level biosafety laboratory environmental quality control method according to claim 2, characterized in that: Step S200 specifically includes the following contents: Plotting the reference viewpoint image and the target viewpoint image into a curve graph; A function threshold of consistency between the reference viewpoint image and the target viewpoint image is set. In the curve graph, the function threshold of consistency between the reference viewpoint image and the target viewpoint image is used to divide the curve into two areas, which respectively represent the parts within the function threshold of consistency between the reference viewpoint image and the target viewpoint image and the parts outside the function threshold of consistency between the reference viewpoint image and the target viewpoint image; Use the camera to record the personnel entry and exit spray management information and sample entry and exit disinfection information to obtain the target viewpoint image; Importing the target viewpoint image into the curve graph and comparing it with the part within the function threshold of the consistency between the reference viewpoint image and the target viewpoint image and the part outside the function threshold of the consistency between the reference viewpoint image and the target viewpoint image, obtaining data of the part outside the function threshold of the consistency between all reference viewpoint images and the target viewpoint image and data within the function threshold of the consistency between the reference viewpoint image and the target viewpoint image; The data outside the function threshold of the consistency between the reference viewpoint image and the target viewpoint image is set as the hidden coefficient, marked as , the data within the function threshold of the consistency between the reference viewpoint image and the target viewpoint image is set as the normal coefficient, marked as .

4. A high-level biosafety laboratory environmental quality control method according to claim 3, characterized in that: Step S300 specifically includes the following contents: Obtain the standard temperature information, pressure difference information, humidity information, hidden worry factor information and normal coefficient information in the biosafety laboratory, and mark the standard temperature information, pressure difference information, humidity information, hidden worry factor information and normal coefficient information as , , , and ; Get the maximum and minimum values ​​of standard temperature information, pressure difference information, humidity information, hidden worry coefficient information and normal coefficient information, marked as , , , , , , , , and , the differences between the maximum and minimum values ​​of standard temperature information, pressure difference information, humidity information, hidden worry coefficient information and normal coefficient information are marked as , , , and ; In a time period, obtain n real-time values, marked as , , , and ; After normalization, the biosafety laboratory health status coefficient is obtained, and the calculation formula is: 。 5. A high-level biosafety laboratory environmental quality control method according to claim 4, characterized in that: Step S500 specifically includes the following contents: A biosafety laboratory health status prediction index threshold is set, and the biosafety laboratory health status prediction index is compared with the biosafety laboratory health status prediction index threshold.

6. A high-level biosafety laboratory environmental quality control method according to claim 5, characterized in that: Step S500 specifically includes the following contents: If the biosafety laboratory health status prediction index is less than the biosafety laboratory health status prediction index threshold, a safe signal is generated; if the biosafety laboratory health status prediction index is greater than or equal to the biosafety laboratory health status prediction index threshold, an adjustment signal or a shutdown maintenance signal is generated.

7. A high-level biosafety laboratory environmental quality control method according to claim 6, characterized in that: Get the maximum and minimum values ​​of the biosafety laboratory health status prediction index, marked as and ; Calculate the optimal index for predicting the health status of biosafety laboratories, marked as ; The calculation formula is: ； A biosafety laboratory health status prediction preferred index threshold is set. When the biosafety laboratory health status prediction preferred index is less than the biosafety laboratory health status prediction preferred index threshold, an adjustment signal is generated. If the biosafety laboratory health status prediction preferred index is greater than or equal to the biosafety laboratory health status prediction preferred index threshold, a shutdown maintenance signal is generated.

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