Laboratory detection data acquisition management system and method

Abstract

The invention belongs to the technical field of data management, and relates to a laboratory detection data acquisition management system and method, and the method specifically comprises the steps: monitoring a reaction substance surface image of a reaction kettle liner and gas data in a fuming cupboard in real time; screening historical laboratory detection data matched with the mixing proportion data of each compound in the experiment on a historical laboratory detection data storage management platform; obtaining the first detection data reliability and the second detection data reliability of the detection data of the experiment; and evaluating the data reliability level of the experimental detection data, and calibrating the data reliability level of the experimental detection data to a historical laboratory detection data storage management platform. The problems that in the prior art, the daily processing data volume load of a laboratory is large, the quality of detection data is uneven, and the effective data volume ratio is low are solved.

Description

Technical Field

[0001] The present invention relates to the technical field of data management, and is concerned with a laboratory testing data collection management system and method. Background Art

[0002] In the fields of chemistry, biology, materials science, etc., laboratory test data collection and management are important components of experimental research. Laboratory test data not only include key parameters such as reaction conditions, reactant concentration, temperature, pressure, time, etc. during the experiment, but also include microscopic information such as the surface morphology, chemical composition, and crystal structure of the reactants. These data are of great significance for analyzing experimental results, verifying experimental hypotheses, and guiding experimental design. Good data management can ensure the accuracy and reliability of data and provide a basis for scientific research and production practice. However, traditional laboratory test data management methods have problems such as backward data collection methods, irregular data storage management, limited data analysis capabilities, and low efficiency in the use of historical data. Faced with the huge amount of daily experimental test data in the laboratory, how to improve data management efficiency and increase the proportion of effective data are important problems that need to be overcome.

[0003] In the existing disclosed invention technologies, for example, the patent with application publication number CN110781725A discloses a laboratory data acquisition and management system, including: a laboratory data acquisition system, a laboratory data management system and a cloud server, wherein: the laboratory data acquisition system includes an identification module, a robot and a robot acquisition module, the identification module identifies the laboratory personnel, laboratory instruments or equipment and laboratory materials; the robot acquisition module controls the movement of the robot, collects the data of the laboratory personnel identified by the identification module during the experiment or the data of the laboratory materials, obtains the collected data, and uploads it to the cloud server for storage in real time; the laboratory data management system is used to manage the collected data.

[0004] Although the above patents are used to manage collected data, if the system is limited to data storage and basic management and lacks advanced data analysis and intelligent processing capabilities, it may not be possible to fully tap the potential value in the data. Summary of the invention

[0005] The technical problem to be solved by the present invention is to propose a laboratory test data collection management system and method in view of the problems in the prior art that the laboratory has a large daily data processing load, the quality of test data is uneven, and the proportion of effective data is low.

[0006] In order to achieve the above-mentioned purpose, the technical scheme of the laboratory test data collection management method of the present invention comprises the following steps:

[0007] S1: Place the reactor liner of this experiment after heating and pressurization on the table of the fume hood, and monitor the surface image of the reaction material in the reactor liner and the gas data in the fume hood in real time;

[0008] S2: extracting the ratio data of each compound in the initial reaction solution of this experiment, and screening the historical laboratory test data matching the mixing ratio data of each compound in this experiment on the historical laboratory test data storage management platform;

[0009] S3: When multiple identical historical laboratory test data are matched, the first test data reliability evaluation strategy is executed to obtain the first test data reliability of the current experimental test data;

[0010] S4: When a plurality of similar historical laboratory test data are matched, the second test data reliability evaluation strategy is executed to obtain the second test data reliability of the current experimental test data;

[0011] S5: Based on S3-S4, evaluate the data reliability level of the test data of this experiment, and calibrate the data reliability level of the test data of this experiment to the historical laboratory test data storage management platform.

[0012] Specifically, S1 includes the following specific steps:

[0013] S11: Place the reactor liner of this experiment evenly on the fume hood table with an interval of 10 cm after the heating and pressurizing treatment;

[0014] S12: collecting a surface image of the reaction material in the reactor liner in real time from a top view of each reactor liner through a camera device;

[0015] S13: The gas type data and concentration data of each type of gas in the fume hood are collected in real time through the gas sensor inside the fume hood.

[0016] Specifically, in S3, the first detection data reliability assessment strategy includes:

[0017] S31: importing the surface image of the reaction material into the image processing software, obtaining the pixel value information of each pixel point in the surface image of the reaction material, and simultaneously identifying the crystallization area in the reaction material through the image segmentation algorithm;

[0018] S32: According to S1, calculate and obtain the crystal image verification value h 1 , the specific calculation strategy is:

[0019]

[0020] Among them, t is a subscript, indicating the time point of data collection, T is the total time of the reactor liner being placed in the fume hood for ventilation treatment; n t is a subscript, indicating that at the data acquisition time point t, the nth t The number of crystalline regions, N t It represents the total number of crystallized areas in the surface image of the reaction material at the data collection time point t;

[0021] is the nth image of the surface of the reaction material at the data acquisition time point t. t The pixel sum of the used pixels in each crystal region; is the number of N in the surface image of the reaction substance at the data acquisition time point t. t The average value of the pixels and of the crystalline regions.

[0022] Specifically, in S3, the first detection data reliability assessment strategy further includes:

[0023] S33: Extract the gas data in the fume hood and calculate the reaction gas verification value h 2 , the specific calculation strategy is:

[0024]

[0025] Among them, m t is a subscript, indicating that at the data collection time point t, the mth t Gas, M t It indicates the total number of gas types contained in the gas in the fume hood at the data collection time point t;

[0026] is the mth value of the gas in the fume hood at the data collection time point t. t The gas concentration of the gas; is the M in the gas in the fume hood at the data collection time point t. t The mean gas concentration of the gas;

[0027] S34: Based on S31-S33, the reliability of the first detection data is evaluated by integration, specifically:

[0028] kd 1 =exph 1 +exph 2 ;

[0029] Among them, kd 1 is the reliability of the first detection data, and exp is the exponential operation.

[0030] Specifically, in S4, the second detection data reliability assessment strategy includes:

[0031] S41: extracting pixel value information of each pixel point in the surface image of the reaction material, and calculating the pixel difference between the maximum pixel value point and the minimum pixel value point;

[0032] S42: According to S41, calculate the crystal component verification value g 1 , the specific calculation strategy is:

[0033]

[0034] Among them, cz t It represents the pixel difference in the surface image of the reaction material at the data acquisition time point t;

[0035] cz max ,cz min They are respectively the maximum pixel difference and the minimum pixel difference in the surface image of the reaction material at the data collection time point t in multiple similar historical laboratory test data.

[0036] Specifically, in S4, the second detection data reliability assessment strategy further includes:

[0037] S43: Prioritize the extraction of gas type data in the fume hood, and compare the gas type data of this experiment with the target gas type data of this experimental reaction theory. When a new gas type appears in the gas type data of this experiment, directly execute step S5 to determine that the data reliability level of the test data of this experiment is a particularly abnormal level; otherwise, execute step S44;

[0038] S44: Extract the gas release rate collected by the gas flow meter built into the fume hood and calculate the gas release rate verification value g 2 , specifically:

[0039]

[0040] Among them, sl t represents the gas release rate at the data collection time point t;

[0041] sl max ,sl min They are respectively the maximum value and the minimum value of the gas release rate at the data collection time point t in multiple similar historical laboratory test data;

[0042] S45: Based on S41-S44, the reliability of the second detection data is evaluated by integration, specifically:

[0043] kd 2 =expg 1 +expg 2 ;

[0044] Among them, kd 2 is the reliability of the second detection data.

[0045] Specifically, S5 includes the following specific steps:

[0046] S51: extracting the reliability of the first detection data and the reliability of the second detection data, and calculating the comprehensive reliability of the detection data, wherein the calculation strategy of the comprehensive reliability of the detection data is specifically:

[0047] KD=α 1 ×kd 1 +α 2 ×kd 2 ;

[0048] Among them, α 1 ,α 2 are comprehensive contribution factors of the reliability of the first detection data and the reliability of the second detection data respectively;

[0049] S52: Evaluate the data reliability level of the test data of this experiment according to the comprehensive reliability of the test data. The data reliability level of the test data of this experiment according to the comprehensive reliability of the test data is evaluated, which specifically includes: presetting different level evaluation thresholds Q of the data reliability level of the test data of the experiment 1 ,Q 2 ,Q 3 ;

[0050] When 0≤KD≤Q 1 When the data reliability level of the experimental test data is judged to be particularly reliable;

[0051] When Q 1 <KD≤Q 2 When the data reliability level of the experimental test data is judged to be a general reliability level;

[0052] When Q 2 <KD≤Q 3 When the data reliability level of the experimental test data is judged to be a particularly abnormal level;

[0053] S53: Calibrate the data reliability level of the experimental test data to the historical laboratory test data storage management platform, and simultaneously send the experimental test data with a particularly abnormal reliability level to the laboratory manager, and the laboratory manager confirms to save or delete the experimental test data on the historical laboratory test data storage management platform.

[0054] In addition, the laboratory test data collection and management system of the present invention includes the following modules:

[0055] A data acquisition module, a historical data matching module, a first detection data reliability calculation module, a second detection data reliability calculation module, and a data reliability level evaluation module;

[0056] The data acquisition module places the reactor liner of this experiment after the heating and pressurization treatment on the fume hood table, and monitors the surface image of the reaction material in the reactor liner and the gas data in the fume hood in real time;

[0057] The historical data matching module is used to extract the ratio data of each compound in the initial reaction solution of this experiment, and to screen the historical laboratory test data that matches the mixing ratio data of each compound in this experiment on the historical laboratory test data storage management platform;

[0058] The first detection data reliability calculation module is used to execute the first detection data reliability evaluation strategy to obtain the first detection data reliability of the detection data of this experiment;

[0059] The second detection data reliability calculation module is used to execute the second detection data reliability evaluation strategy to obtain the second detection data reliability of the detection data of this experiment;

[0060] The data reliability level evaluation module is used to evaluate the data reliability level of the test data of this experiment, and calibrate the data reliability level of the test data of this experiment to the historical laboratory test data storage management platform.

[0061] A storage medium stores instructions, and when a computer reads the instructions, the computer executes the laboratory test data collection and management method.

[0062] An electronic device comprises a memory, a processor and a computer program stored in the memory and executable on the processor, wherein the processor implements the above-mentioned laboratory test data acquisition management method when executing the computer program.

[0063] Compared with the prior art, the technical effects of the present invention are as follows:

[0064] 1. The present invention significantly improves the accuracy and reliability of experimental test data by real-time monitoring of multiple key data in the reaction process, such as the surface image of the reaction material and the gas data in the fume hood, and comparing and analyzing with historical laboratory test data. Through the first and second test data reliability evaluation strategies, the credibility of the experimental data can be more comprehensively evaluated, thereby guiding subsequent experiments or production activities.

[0065] 2. The present invention realizes intelligent data management of laboratory data. Faced with a large amount of experimental data, traditional processing methods are inefficient and prone to errors. The present invention introduces intelligent data management means, which significantly improves the efficiency and accuracy of data processing. This not only improves the efficiency of data processing, but also reduces the possibility of human operation errors, providing more convenient and efficient data support for scientific researchers.

[0066] 3. The present invention calibrates the data reliability level of experimental test data to the historical laboratory test data storage and management platform. This technical solution provides strong support for the optimization of experimental processes. Researchers can adjust the experimental plan or make more scientific decisions based on the reliability level of the data, thereby improving the efficiency and success rate of the experiment.

[0067] 4. The implementation of the present invention can not only significantly improve the collection quality of laboratory test data, but also provide guarantee for the reliability and accuracy of experimental results through intelligent data analysis and comprehensive data reliability evaluation. At the same time, through the comparison and analysis of historical data, scientific research efficiency can be improved, repeated experiments can be avoided, and scientific research resources can be saved. BRIEF DESCRIPTION OF THE DRAWINGS

[0068] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings required for use in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other accompanying drawings can be obtained based on these accompanying drawings without paying creative labor.

[0069] in:

[0070] Figure 1 It is a flow chart of the laboratory test data collection management method of the present invention;

[0071] Figure 2 It is a structural schematic diagram of the laboratory test data acquisition and management system of the present invention. DETAILED DESCRIPTION

[0072] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, the specific implementation methods of the present invention are described in detail below in conjunction with the accompanying drawings.

[0073] In the following description, many specific details are set forth to facilitate a full understanding of the present invention, but the present invention may also be implemented in other ways different from those described herein, and those skilled in the art may make similar generalizations without violating the connotation of the present invention. Therefore, the present invention is not limited to the specific embodiments disclosed below.

[0074] Secondly, the term "one embodiment" or "embodiment" as used herein refers to a specific feature, structure, or characteristic that may be included in at least one implementation of the present invention. The term "in one embodiment" that appears in different places in this specification does not necessarily refer to the same embodiment, nor does it refer to a separate or selective embodiment that is mutually exclusive with other embodiments.

[0075] Embodiment 1:

[0076] like Figure 1 As shown, the laboratory test data collection and management method of the embodiment of the present invention is as follows: Figure 1 As shown, the specific steps are as follows:

[0077] S1: Place the reactor liner of this experiment after heating and pressurization on the table of the fume hood, and monitor the surface image of the reaction material in the reactor liner and the gas data in the fume hood in real time;

[0078] S1 includes the following specific steps:

[0079] S11: Place the reactor liner of this experiment evenly on the fume hood table with an interval of 10 cm after the heating and pressurizing treatment;

[0080] S12: collecting a surface image of the reaction material in the reactor liner in real time from a top view of each reactor liner through a camera device;

[0081] S13: The gas type data and concentration data of each type of gas in the fume hood are collected in real time through the gas sensor inside the fume hood.

[0082] S2: extracting the ratio data of each compound in the initial reaction solution of this experiment, and screening the historical laboratory test data matching the mixing ratio data of each compound in this experiment on the historical laboratory test data storage management platform;

[0083] Exemplarily, in this embodiment, a specific implementation strategy for matching historical laboratory test data through a historical laboratory test data storage and management platform in S2 is provided, specifically: the historical laboratory test data that matches the mixing ratio data of each compound in this experiment is screened on the historical laboratory test data storage and management platform, and the specific matching strategy is: extracting the ratio data of the main reaction compounds in the initial reaction solution of this experiment, and arranging them in descending order according to the ratio data of each main reaction compound, taking the molar amount of the reaction compounds of the top three in the ranking of the proportion content of the main reaction compounds in the initial reaction solution as the matching standard, screening the historical laboratory test data with the same molar amount of the reaction compounds of the top three in the ranking of this experiment, and matching to obtain the same historical laboratory test data; conversely, if there are one or two reaction compound molar amounts in the screened historical laboratory test data that are the same as the molar amounts of the reaction compounds of the top three in the ranking of this experiment but the types of reaction compounds are the same, matching to obtain similar historical laboratory test data.

[0084] S3: When multiple identical historical laboratory test data are matched, the first test data reliability evaluation strategy is executed to obtain the first test data reliability of the current experimental test data;

[0085] In S3, the first detection data reliability assessment strategy includes:

[0086] S31: importing the surface image of the reaction material into the image processing software, obtaining the pixel value information of each pixel point in the surface image of the reaction material, and simultaneously identifying the crystallization area in the reaction material through the image segmentation algorithm;

[0087] S32: According to S1, calculate and obtain the crystal image verification value h 1 , the specific calculation strategy is:

[0088]

[0089] Among them, t is a subscript, indicating the time point of data collection, T is the total time of the reactor liner being placed in the fume hood for ventilation treatment; n t is a subscript, indicating that at the data acquisition time point t, the nth t The number of crystalline regions, N t It represents the total number of crystallized areas in the surface image of the reaction material at the data collection time point t;

[0090] is the nth image of the surface of the reaction material at the data acquisition time point t. t The pixel sum of the used pixels in each crystal region; is the number of N in the surface image of the reaction substance at the data acquisition time point t.t The average value of the pixels and of the crystalline regions.

[0091] In S3, the first detection data reliability assessment strategy further includes:

[0092] S33: Extract the gas data in the fume hood and calculate the reaction gas verification value h 2 , the specific calculation strategy is:

[0093]

[0094] Among them, m t is a subscript, indicating that at the data collection time point t, the mth t Gas, M t It indicates the total number of gas types contained in the gas in the fume hood at the data collection time point t;

[0095] is the mth value of the gas in the fume hood at the data collection time point t. t The gas concentration of the gas; is the M in the gas in the fume hood at the data collection time point t. t The mean gas concentration of the gas;

[0096] S34: Based on S31-S33, the reliability of the first detection data is evaluated by integration, specifically:

[0097] kd 1 =exph 1 +exph 2 ;

[0098] Among them, kd 1 is the reliability of the first detection data, and exp is the exponential operation.

[0099] S4: When a plurality of similar historical laboratory test data are matched, the second test data reliability evaluation strategy is executed to obtain the second test data reliability of the current experimental test data;

[0100] In S4, the second detection data reliability assessment strategy includes:

[0101] S41: extracting pixel value information of each pixel point in the surface image of the reaction material, and calculating the pixel difference between the maximum pixel value point and the minimum pixel value point;

[0102] S42: According to S41, calculate the crystal component verification value g 1 , the specific calculation strategy is:

[0103]

[0104] Among them, cz t It represents the pixel difference in the surface image of the reaction material at the data acquisition time point t;

[0105] cz max ,cz min They are respectively the maximum pixel difference and the minimum pixel difference in the surface image of the reaction material at the data collection time point t in multiple similar historical laboratory test data.

[0106] In S4, the second detection data reliability assessment strategy further includes:

[0107] S43: Prioritize the extraction of gas type data in the fume hood, and compare the gas type data of this experiment with the target gas type data of this experimental reaction theory. When a new gas type appears in the gas type data of this experiment, directly execute step S5 to determine that the data reliability level of the test data of this experiment is a particularly abnormal level; otherwise, execute step S44;

[0108] S44: Extract the gas release rate collected by the gas flow meter built into the fume hood and calculate the gas release rate verification value g 2 , specifically:

[0109]

[0110] Among them, sl t represents the gas release rate at the data collection time point t;

[0111] sl max ,sl min They are respectively the maximum value and the minimum value of the gas release rate at the data collection time point t in multiple similar historical laboratory test data;

[0112] S45: Based on S41-S44, the reliability of the second detection data is evaluated by integration, specifically:

[0113] kd 2 =expg 1 +expg 2 ;

[0114] Among them, kd 2 is the reliability of the second detection data.

[0115] S5: Based on S3-S4, evaluate the data reliability level of the test data of this experiment, and calibrate the data reliability level of the test data of this experiment to the historical laboratory test data storage management platform.

[0116] S5 includes the following specific steps:

[0117] S51: extracting the reliability of the first detection data and the reliability of the second detection data, and calculating the comprehensive reliability of the detection data, wherein the calculation strategy of the comprehensive reliability of the detection data is specifically:

[0118] KD=α 1 ×kd 1 +α 2 ×kd 2 ;

[0119] Among them, α 1 ,α 2 are comprehensive contribution factors of the reliability of the first detection data and the reliability of the second detection data respectively;

[0120] S52: Evaluate the data reliability level of the test data of this experiment according to the comprehensive reliability of the test data. The data reliability level of the test data of this experiment according to the comprehensive reliability of the test data is evaluated, which specifically includes: presetting different level evaluation thresholds Q of the data reliability level of the test data of the experiment 1 ,Q 2 ,Q 3 ;

[0121] When 0≤KD≤Q 1 When the data reliability level of the experimental test data is judged to be particularly reliable;

[0122] When Q 1 <KD≤Q 2 When the data reliability level of the experimental test data is judged to be a general reliability level;

[0123] When Q 2 <KD≤Q 3 When the data reliability level of the experimental test data is judged to be a particularly abnormal level;

[0124] S53: Calibrate the data reliability level of the experimental test data to the historical laboratory test data storage management platform, and simultaneously send the experimental test data with a particularly abnormal reliability level to the laboratory manager, and the laboratory manager confirms to save or delete the experimental test data on the historical laboratory test data storage management platform.

[0125] Embodiment 2:

[0126] like Figure 2 As shown, the laboratory test data collection and management system of the embodiment of the present invention is as follows: Figure 2 As shown, it includes the following modules:

[0127] A data acquisition module, a historical data matching module, a first detection data reliability calculation module, a second detection data reliability calculation module, and a data reliability level evaluation module;

[0128] The data acquisition module places the reactor liner of this experiment after the heating and pressurization treatment on the fume hood table, and monitors the surface image of the reaction material in the reactor liner and the gas data in the fume hood in real time;

[0129] The historical data matching module is used to extract the ratio data of each compound in the initial reaction solution of this experiment, and to screen the historical laboratory test data that matches the mixing ratio data of each compound in this experiment on the historical laboratory test data storage management platform;

[0130] The first detection data reliability calculation module is used to execute the first detection data reliability evaluation strategy to obtain the first detection data reliability of the detection data of this experiment;

[0131] The second detection data reliability calculation module is used to execute the second detection data reliability evaluation strategy to obtain the second detection data reliability of the detection data of this experiment;

[0132] The data reliability level evaluation module is used to evaluate the data reliability level of the test data of this experiment, and calibrate the data reliability level of the test data of this experiment to the historical laboratory test data storage management platform.

[0133] Embodiment three:

[0134] This embodiment provides an electronic device, including: a processor and a memory, wherein the memory stores a computer program that can be called by the processor;

[0135] The processor executes the above-mentioned laboratory test data collection and management method by calling the computer program stored in the memory.

[0136] The electronic device may have relatively large differences due to different configurations or performances, and may include one or more processors (Central Processing Units, CPU) and one or more memories, wherein at least one computer program is stored in the memory, and the computer program is loaded and executed by the processor to implement the laboratory test data acquisition management method provided by the above method embodiment. The electronic device may also include other components for implementing the functions of the device, for example, the electronic device may also have components such as a wired or wireless network interface and an input and output interface, so as to input and output data. This embodiment will not be described in detail here.

[0137] Embodiment 4:

[0138] This embodiment provides a computer-readable storage medium having a rewritable computer program stored thereon;

[0139] When the computer program runs on a computer device, the computer device executes the above-mentioned laboratory test data collection and management method.

[0140] For example, the computer readable storage medium can be a read-only memory (ROM), a random access memory (RAM), a compact disc (CD-ROM), a magnetic tape, a floppy disk, an optical data storage device, etc.

[0141] It should be understood that in the various embodiments of the present application, the size of the serial numbers of the above-mentioned processes does not mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present application.

[0142] It should be understood that determining B based on A does not mean determining B only based on A. B can also be determined based on A and / or other information.

[0143] The above embodiments can be implemented in whole or in part by software, hardware, firmware or any other combination. When implemented by software, the above embodiments can 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 a computer instruction or computer program is loaded or executed on a computer, a process or function according to an embodiment of the present invention is generated in whole or in part. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. Computer instructions can be stored in a computer-readable storage medium, or transmitted from one computer-readable storage medium to another computer-readable storage medium. For example, computer instructions can be transmitted from one website site, computer, server or data center to another website site, computer, server or data center through a wired network or / and a wireless network. The computer-readable storage medium can 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 can be a magnetic medium (for example, a floppy disk, a hard disk, a tape), an optical medium (for example, a DVD), or a semiconductor medium. The semiconductor medium can be a solid-state hard disk.

[0144] Those skilled in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed in the present invention 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 the present invention.

[0145] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working processes of the systems, devices and units described above can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0146] In the several embodiments provided by the present invention, it should be understood that the disclosed systems, devices and methods can be implemented in other ways. For example, the device embodiments described above are only schematic, for example, the division of units is only one, and there may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms.

[0147] 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, that is, they 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.

[0148] In addition, each functional unit in each embodiment of the present invention 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.

[0149] In the description of this specification, the description with reference to the terms "one embodiment", "example", "specific example", etc. means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present invention. In this specification, the schematic representation of the above terms does not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described can be combined in any one or more embodiments or examples in a suitable manner.

[0150] In summary, compared with the prior art, the technical effects of the present invention are as follows:

[0151] 1. The present invention significantly improves the accuracy and reliability of experimental test data by real-time monitoring of multiple key data in the reaction process, such as the surface image of the reaction material and the gas data in the fume hood, and comparing and analyzing with historical laboratory test data. Through the first and second test data reliability evaluation strategies, the credibility of the experimental data can be more comprehensively evaluated, thereby guiding subsequent experiments or production activities.

[0152] 2. The present invention realizes intelligent data management of laboratory data. Faced with a large amount of experimental data, traditional processing methods are inefficient and prone to errors. The present invention introduces intelligent data management means, which significantly improves the efficiency and accuracy of data processing. This not only improves the efficiency of data processing, but also reduces the possibility of human operation errors, providing more convenient and efficient data support for scientific researchers.

[0153] 3. The present invention calibrates the data reliability level of experimental test data to the historical laboratory test data storage and management platform. This technical solution provides strong support for the optimization of experimental processes. Researchers can adjust the experimental plan or make more scientific decisions based on the reliability level of the data, thereby improving the efficiency and success rate of the experiment.

[0154] 4. The implementation of the present invention can not only significantly improve the collection quality of laboratory test data, but also provide guarantee for the reliability and accuracy of experimental results through intelligent data analysis and comprehensive data reliability evaluation. At the same time, through the comparison and analysis of historical data, scientific research efficiency can be improved, repeated experiments can be avoided, and scientific research resources can be saved.

[0155] The above shows and describes the basic principles and main features of the present invention and the advantages of the present invention. It should be understood by those skilled in the art that the present invention is not limited to the above embodiments. The above embodiments and descriptions are only for explaining the principles of the present invention. Without departing from the spirit and scope of the present invention, the present invention may have various changes and improvements, which fall within the scope of the present invention to be protected. The scope of protection of the present invention is defined by the attached claims and their equivalents.

Claims

1. A laboratory test data collection management method, characterized in that: The method comprises the following specific steps: S1: Place the reactor liner of this experiment, which has been heated and pressurized, on the table of the fume hood, and monitor the surface image of the reaction material in the reactor liner and the gas data in the fume hood in real time; S2: extracting the ratio data of each compound in the initial reaction solution of this experiment, and screening the historical laboratory test data matching the mixing ratio data of each compound in this experiment on the historical laboratory test data storage management platform; S3: When multiple identical historical laboratory test data are matched, the first test data reliability evaluation strategy is executed to obtain the first test data reliability of the current experimental test data; S4: When a plurality of similar historical laboratory test data are matched, the second test data reliability evaluation strategy is executed to obtain the second test data reliability of the current experimental test data; S5: Based on S3-S4, evaluate the data reliability level of the experimental test data, and calibrate the data reliability level of the experimental test data to the historical laboratory test data storage management platform.

2. The laboratory test data collection and management method according to claim 1, characterized in that: In S3, the first detection data reliability assessment strategy includes: S31: importing the surface image of the reaction material into the image processing software, obtaining the pixel value information of each pixel point in the surface image of the reaction material, and simultaneously identifying the crystallization area in the reaction material through the image segmentation algorithm; S32: According to S1, the crystallization image verification value h1 is calculated and obtained. The specific calculation strategy is: Among them, t is a subscript, indicating the time point of data collection, T is the total time of the reactor liner being placed in the fume hood for ventilation treatment; n t is a subscript, indicating that at the data acquisition time point t, the nth t The number of crystalline regions, N t It represents the total number of crystallized areas in the surface image of the reaction material at the data collection time point t; is the nth image of the surface of the reaction material at the data acquisition time point t. t The pixel sum of the used pixels in each crystal region; is the number of N in the surface image of the reaction substance at the data acquisition time point t. t The average value of the pixels and of the crystalline regions.

3. The laboratory test data collection and management method according to claim 2, characterized in that: In S3, the first detection data reliability assessment strategy further includes: S33: Extract the gas data in the fume hood and calculate the reaction gas verification value h2. The specific calculation strategy is: Among them, m t is a subscript, indicating that at the data collection time point t, the mth t Gas, M t It indicates the total number of gas types contained in the gas in the fume hood at the data collection time point t; is the mth value of the gas in the fume hood at the data collection time point t. t The gas concentration of the gas; is the M in the gas in the fume hood at the data collection time point t. t The mean gas concentration of the gas; S34: Based on S31-S33, the reliability of the first detection data is evaluated by integration, specifically: kd1=exph1+exph2; Wherein, kd1 is the reliability of the first detection data, and exp is the exponential operation.

4. The laboratory test data collection and management method according to claim 3, characterized in that: In S4, the second detection data reliability assessment strategy includes: S41: extracting pixel value information of each pixel point in the surface image of the reaction material, and calculating the pixel difference between the maximum pixel value point and the minimum pixel value point; S42: According to S41, calculate the crystal component verification value g1, the specific calculation strategy is: Among them, cz t It represents the pixel difference in the surface image of the reaction material at the data acquisition time point t; cz max ,cz min They are respectively the maximum pixel difference and the minimum pixel difference in the surface image of the reaction material at the data collection time point t in multiple similar historical laboratory test data.

5. The laboratory test data collection and management method according to claim 4, characterized in that: In S4, the second detection data reliability assessment strategy further includes: S43: Prioritize the extraction of gas type data in the fume hood, and compare the gas type data of this experiment with the target gas type data of this experimental reaction theory. When a new gas type appears in the gas type data of this experiment, directly execute step S5 to determine that the data reliability level of the test data of this experiment is a particularly abnormal level; otherwise, execute step S44; S44: extract the gas release rate collected by the gas flow meter built into the fume hood, and calculate the gas release rate verification value g2, which is specifically: Among them, sl t represents the gas release rate at the data collection time point t; sl max ,sl min They are respectively the maximum value and the minimum value of the gas release rate at the data collection time point t in multiple similar historical laboratory test data; S45: Based on S41-S44, the reliability of the second detection data is evaluated by integration, specifically: kd2=expg1+expg2; Wherein, kd2 is the reliability of the second detection data.

6. The laboratory test data collection and management method according to claim 5, characterized in that: S5 includes the following specific steps: S51: extracting the reliability of the first detection data and the reliability of the second detection data, and calculating the comprehensive reliability of the detection data, wherein the calculation strategy of the comprehensive reliability of the detection data is specifically: KD = α1 × kd1 + α2 × kd2; Among them, α1 and α2 are the comprehensive contribution factors of the reliability of the first detection data and the reliability of the second detection data respectively; S52: evaluating the data reliability level of the test data of this experiment according to the comprehensive reliability of the test data, wherein the evaluating the data reliability level of the test data of this experiment according to the comprehensive reliability of the test data specifically includes: presetting different level evaluation thresholds Q1, Q2, Q3 of the data reliability level of the test data of the experiment; When 0≤KD≤Q1, the data reliability level of the experimental test data is judged to be particularly reliable; When Q1<KD≤Q2, the data reliability level of the experimental test data is judged to be a general reliability level; When Q2<KD≤Q3, the data reliability level of the experimental test data is judged to be a particularly abnormal level; S53: Calibrate the data reliability level of the experimental test data to the historical laboratory test data storage management platform, and simultaneously send the experimental test data with a particularly abnormal reliability level to the laboratory manager, and the laboratory manager confirms to save or delete the experimental test data on the historical laboratory test data storage management platform.

7. The laboratory test data collection and management method according to claim 1, characterized in that: S1 includes the following specific steps: S11: Place the reactor liner of this experiment evenly on the fume hood table with an interval of 10 cm after the heating and pressurizing treatment; S12: collecting a surface image of the reaction material in the reactor liner in real time from a top view of each reactor liner through a camera device; S13: The gas type data and concentration data of each type of gas in the fume hood are collected in real time through the gas sensor inside the fume hood.

8. A laboratory test data collection and management system, which is implemented based on the laboratory test data collection and management method according to any one of claims 1 to 7, characterized in that: The system includes the following modules: A data acquisition module, a historical data matching module, a first detection data reliability calculation module, a second detection data reliability calculation module, and a data reliability level evaluation module; The data acquisition module places the reactor liner of this experiment after the heating and pressurization treatment on the fume hood table, and monitors the surface image of the reaction material in the reactor liner and the gas data in the fume hood in real time; The historical data matching module is used to extract the ratio data of each compound in the initial reaction solution of this experiment, and to screen the historical laboratory test data that matches the mixing ratio data of each compound in this experiment on the historical laboratory test data storage management platform; The first detection data reliability calculation module is used to execute the first detection data reliability evaluation strategy to obtain the first detection data reliability of the detection data of this experiment; The second detection data reliability calculation module is used to execute the second detection data reliability evaluation strategy to obtain the second detection data reliability of the detection data of this experiment; The data reliability level evaluation module is used to evaluate the data reliability level of the test data of this experiment, and calibrate the data reliability level of the test data of this experiment to the historical laboratory test data storage management platform.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the laboratory test data collection and management method as described in any one of claims 1 to 7 is implemented.

10. An electronic device, characterized in that: include: A memory for storing instructions; The processor is used to execute the instruction so that the device performs the operation of implementing the laboratory test data collection management method as described in any one of claims 1-7.

Images