Experimental task automatic execution method, system, electronic device and medium

Abstract

The embodiment of the application provides a kind of experimental task automation execution method, system, electronic equipment and medium, belong to data processing field.The method comprises: according to the experimental detection content and experimental detection period corresponding to each experimental project, bitmap coding is carried out, and project period bitmap sequence is obtained, based on the project period bitmap sequence, experimental detection content and experimental record template corresponding to each experimental project, experimental detection instruction sequence is generated, for experimental detection instruction sequence, the experimental project detection task corresponding to experimental project is generated;Experimental project detection operation is executed based on each experimental project detection task.The embodiment of the application is according to the experimental detection content, experimental record template and experimental detection period corresponding to each experimental project, carries out period bitmap coding, experimental instruction generation and experimental project task generation, realizes the automation generation and execution from experimental project to experimental task, improves experimental task execution efficiency.

Description

Technical Field

[0001] This application relates to the field of data processing, and in particular to a method, system, electronic device, and medium for automating experimental tasks. Background Technology

[0002] Currently, in the daily work of R&D laboratories, in addition to exploratory and innovative experimental tasks, there are also a large number of standardized experiments with relatively fixed procedures, such as drug stability testing, periodic material testing, and environmental compliance monitoring. It is necessary to standardize the design of standardized experiments, automatically assign tasks, and standardize the recording of experimental data to ensure the compliance of experimental procedures and the reliability of data.

[0003] In existing technologies, the execution of standardized experiments is often based directly on paper records or general electronic systems (such as LIMS). Experimenters interpret the experimental content, manually assign tasks, and record data to complete the tasks. However, this method, relying on personal experience, is prone to problems such as inconsistent data recording formats and scheduling errors. Furthermore, it struggles to automate the process from experimental design to task execution, resulting in low efficiency and difficulty in guaranteeing experimental quality. Therefore, improving the efficiency of experimental task execution while ensuring experimental quality has become a pressing technical challenge. Summary of the Invention

[0004] The main objective of this application is to propose a method, system, electronic device, and medium for automating experimental tasks, aiming to improve the efficiency of experimental task execution.

[0005] To achieve the above objectives, a first aspect of this application proposes a method for automating the execution of experimental tasks, the method comprising:

[0006] Collect multiple sets of target experimental project information corresponding to different experimental projects; wherein, each set of target experimental project information includes the experimental detection content, experimental record template and experimental detection cycle corresponding to one of the experimental projects; For each of the aforementioned experimental items, a corresponding experimental item detection task is determined: wherein, the experimental item detection task is specifically determined by the following steps: performing bitmap encoding based on the experimental detection content and experimental detection cycle corresponding to each of the aforementioned experimental items to obtain an item cycle bitmap sequence corresponding to the experimental item; generating experimental instructions based on the corresponding item cycle bitmap sequence, the experimental detection content, and the experimental record template to obtain an experimental detection instruction sequence; and generating an experimental item detection task corresponding to the experimental item for the experimental detection instruction sequence. Perform experimental item detection operations based on each of the experimental item detection tasks.

[0007] In some embodiments, the step of performing bitmap encoding based on the experimental detection content and experimental detection cycle corresponding to each experimental item to obtain an item cycle bitmap sequence corresponding to the experimental item includes: The experimental detection period corresponding to each of the aforementioned experimental items is converted into a set of periodic time points. From the set of periodic time points, select the project execution time points that match the experimental detection content corresponding to each of the experimental items; Based on the execution time of the project, the experimental detection content corresponding to each experimental project is binary encoded to obtain the project period bitmap sequence corresponding to the experimental project.

[0008] In some embodiments, the step of generating experimental instructions based on the corresponding project cycle bitmap sequence, the experimental detection content, and the experimental record template to obtain an experimental detection instruction sequence includes: Bitmap parsing is performed on the project period bitmap sequence corresponding to each of the experimental items to obtain the detection time point position of the experimental detection content; Obtain the detection start time of the experimental detection content, and perform timeline calculation on the experimental detection content based on the detection time point position and the detection start time to obtain a set of detection timestamps; The experimental detection instruction sequence is obtained by encapsulating the detection timestamp set, the experimental detection content, and the experimental record template.

[0009] In some embodiments, generating an experimental item detection task corresponding to the experimental item for the experimental detection instruction sequence includes: According to the experimental testing instruction sequence, obtain the experimental material information and experimental instrument information corresponding to the experimental testing content; Based on the set of detection timestamps, the information of experimental materials, and the information of experimental instruments in the experimental detection instruction sequence, a detection preparation task corresponding to the experimental project is generated. In response to the execution of the detection preparation task, an experimental project detection task corresponding to the experimental project is generated based on the detection timestamp set and the experimental record template.

[0010] In some embodiments, performing experimental item detection operations based on each of the experimental item detection tasks includes: Obtain the task priority of multiple experimental project detection tasks; Based on the experimental instrument information corresponding to each experimental project detection task, query the usage status of the corresponding task instrument. Execute each experimental item detection task according to the task priority and the instrument usage status to obtain initial experimental data; The initial experimental data was validated using the experimental record template to identify data standardization flaws in the initial experimental data. The data is corrected to address the data specification defects in the initial experimental data to obtain the target experimental detection data.

[0011] In some embodiments, executing each of the experimental detection tasks according to the task priority and the instrument usage status includes: Based on the task priority and the instrument usage status, the target experimental task for the current round is selected from the detection tasks of each experimental project, and the target experimental task for the current round is executed. During the execution of the target experimental task, a task risk assessment is performed for the target experimental task in the current round to obtain task risk assessment data and task risk type; In response to the fact that the risk assessment data corresponding to the target experimental task does not meet the preset risk definition conditions, after the target experimental task in the current round is completed, the target experimental task for the next round is selected from the detection tasks of each experimental item according to the task priority and the instrument usage status, and the target experimental task for the next round is executed. In response to the existence of task risk assessment data corresponding to the target experimental task that meets the preset risk definition conditions, a risk response operation is performed based on the task risk type.

[0012] In some embodiments, the collection of multiple sets of target experimental item information corresponding to different experimental items includes configuring corresponding experimental record templates for the experimental detection content, specifically including: Obtain the name of the target detection item in the experimental detection content; Based on a preset database of test item names, the test item names are checked for repeatability; wherein, the database of test item names stores alternative test item names corresponding to different experimental items. If the name of the detection item meets the preset verification pass conditions, a template query is performed in the preset experimental record template library according to the target detection item name to obtain the experimental record template; wherein, the experimental record template library stores alternative record templates corresponding to a variety of alternative detection item names.

[0013] To achieve the above objectives, a second aspect of this application proposes an automated experimental task execution system, the system comprising: The experimental project information collection module is used to collect information about the target experimental project; the target experimental project information includes the experimental testing content, experimental record template, and experimental testing cycle. The experimental project detection task generation module is used to determine the corresponding experimental project detection task for each of the experimental projects. Specifically, the experimental project detection task is determined by the following steps: bitmap encoding is performed according to the experimental detection content and experimental detection cycle corresponding to each of the experimental projects to obtain a project cycle bitmap sequence corresponding to the experimental project; experimental instructions are generated based on the corresponding project cycle bitmap sequence, the experimental detection content and the experimental record template to obtain an experimental detection instruction sequence; and experimental project detection task corresponding to the experimental project is generated for the experimental detection instruction sequence. The experimental task execution module is used to perform experimental item detection operations based on each experimental item detection task.

[0014] To achieve the above objectives, a third aspect of the present application provides an electronic device, the electronic device including a memory and a processor, the memory storing a computer program, and the processor executing the computer program to implement the method described in the first aspect.

[0015] A fourth aspect of this application provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the method of the first aspect described above.

[0016] The proposed method, system, electronic device, and medium for automated execution of experimental tasks first collect multiple sets of target experimental project information for different experimental projects. Each set of target experimental project information includes the experimental detection content, experimental record template, and experimental detection cycle corresponding to one experimental project, providing comprehensive basic data for subsequent experimental task generation and ensuring that experimental task execution is based on evidence. Second, for each experimental project, bitmap encoding is performed according to the corresponding experimental detection content and experimental detection cycle to obtain a project cycle bitmap sequence. This provides machine-readable standardized input for subsequent automated task execution, and also solves problems such as task scheduling errors and omissions. Furthermore, based on the project cycle bitmap sequence... The system generates a sequence of experimental testing instructions based on the experimental test content and experimental record template. This sequence, combined with the experimental template, addresses the issue of inconsistent experimental data recording formats. For each experimental test instruction sequence, corresponding experimental test tasks are generated, achieving automated generation from experimental projects to experimental tasks. This significantly improves the efficiency of experimental task generation and effectively avoids problems such as inconsistent experimental data recording formats and incorrect task scheduling caused by manual interpretation and arrangement in traditional methods. Finally, experimental testing operations are executed based on the generated experimental test tasks, ensuring the compliance of the experimental process and the reliability of the data. This significantly improves the efficiency of experimental task execution while guaranteeing experimental quality. Attached Figure Description

[0017] Figure 1 This is a flowchart of the automated execution method for experimental tasks provided in the embodiments of this application; Figure 2 yes Figure 1 The flowchart of step S101 in the text; Figure 3 yes Figure 1 The flowchart of step S102 in the document; Figure 4 yes Figure 1 Another flowchart of step S102 in the process; Figure 5 yes Figure 1 Another flowchart of step S102 in the process; Figure 6 yes Figure 1 The flowchart of step S103 in the process; Figure 7 yes Figure 6 The flowchart of step S603 in the process; Figure 8 This is a schematic diagram of the structure of the automated experimental task execution system provided in the embodiments of this application; Figure 9 This is a schematic diagram of the hardware structure of the electronic device provided in the embodiments of this application. Detailed Implementation

[0018] To make the objectives, technical solutions, and advantages of this application clearer, the following detailed description is provided in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the scope of this application.

[0019] It should be noted that although functional modules are divided in the system diagram and the logical order is shown in the flowchart, in some cases, the steps shown or described may be performed in a different order than the module division in the system or the order in the flowchart. The terms "first," "second," etc., in the specification, claims, and the aforementioned drawings are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence.

[0020] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs. The terminology used herein is for the purpose of describing embodiments of this application only and is not intended to limit this application.

[0021] First, let's analyze some of the terms used in this application: Standardized experiments refer to a type of deterministic experimental work in R&D activities in which the experimental plan, operation procedure, data recording format and judgment criteria are all clearly defined and unified in advance, and need to be repeated and periodically executed.

[0022] Project Cycle Bitmap Sequence: This is a binary data structure used to represent the correspondence between experimental projects and execution cycles in a standardized experiment. It transforms the execution plan of all experimental detection contents in an experimental project on the timeline into a machine-readable sequence of 0s and 1s.

[0023] Based on this, embodiments of this application provide a method, system, electronic device, and medium for automating experimental task execution, aiming to improve the efficiency of experimental task execution.

[0024] The experimental task automation execution method, system, electronic device and medium provided in the embodiments of this application are specifically described through the following embodiments. First, the experimental task automation execution method in the embodiments of this application is described.

[0025] The method for automating experimental task execution provided in this application relates to the field of data processing. This method can be applied to a terminal, a server, or software running on either a terminal or a server. In some embodiments, the terminal can be a smartphone, tablet, laptop, desktop computer, etc.; the server can be configured as an independent physical server, a server cluster or distributed system composed of multiple physical servers, or a cloud server providing basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communication, middleware services, domain name services, security services, CDN, and big data and artificial intelligence platforms; the software can be an application that implements the method for automating experimental task execution, but is not limited to the above forms.

[0026] This application can be used in a wide variety of general-purpose or special-purpose computer system environments or configurations. Examples include: personal computers, server computers, handheld or portable devices, tablet devices, multiprocessor systems, microprocessor-based systems, set-top boxes, programmable consumer electronics, network PCs, minicomputers, mainframe computers, and distributed computing environments including any of the above systems or devices. This application can be described in the general context of computer-executable instructions executed by a computer, such as program modules. Generally, program modules include routines, programs, objects, components, data structures, etc., that perform specific tasks or implement specific abstract data types. This application can also be practiced in distributed computing environments where tasks are performed by remote processing devices connected via a communication network. In distributed computing environments, program modules can reside in local and remote computer storage media, including storage devices.

[0027] Please see Figure 1 , Figure 1 This is a flowchart of the automated execution method for experimental tasks provided in the embodiments of this application. Figure 1 The method may include, but is not limited to, steps S101 to S103.

[0028] Step S101: Collect multiple sets of target experimental project information corresponding to different experimental projects; wherein, each set of target experimental project information includes the experimental detection content, experimental record template and experimental detection cycle corresponding to one experimental project.

[0029] Step S102: For each type of experimental project, determine the corresponding experimental project detection task. Specifically, the experimental project detection task is determined by the following steps: performing bitmap encoding based on the experimental detection content and experimental detection cycle corresponding to each type of experimental project to obtain the project cycle bitmap sequence corresponding to the experimental project; generating experimental instructions based on the corresponding project cycle bitmap sequence, experimental detection content, and experimental record template to obtain the experimental detection instruction sequence; and generating the experimental project detection task corresponding to the experimental project based on the experimental detection instruction sequence.

[0030] Step S103: Perform experimental item detection operations based on each experimental item detection task.

[0031] Steps S101 to S103 as shown in the embodiments of this application firstly collect multiple sets of target experimental project information for different experimental projects. Each set of target experimental project information includes the experimental detection content, experimental record template, and experimental detection cycle corresponding to one experimental project, providing comprehensive basic data for the subsequent generation of experimental tasks and ensuring that the execution of experimental tasks is based on evidence. Secondly, for each experimental project, bitmap encoding is performed according to the experimental detection content and experimental detection cycle corresponding to each experimental project to obtain a project cycle bitmap sequence. This provides machine-readable standardized input for the subsequent automated execution of tasks, and also solves problems such as task scheduling errors. Based on the project cycle bitmap sequence and the actual... The system generates experimental testing instruction sequences based on the test content and experimental record templates. This addresses the issue of inconsistent experimental data recording formats by combining the experimental templates with the test instructions. For each experimental testing instruction sequence, corresponding experimental project testing tasks are generated, achieving automated generation from experimental projects to experimental tasks. This significantly improves the efficiency of experimental task generation and effectively avoids problems such as inconsistent experimental data recording formats and incorrect task scheduling caused by manual interpretation and arrangement in traditional methods. Finally, experimental testing operations are executed based on the generated experimental project testing tasks, ensuring the compliance of the experimental process and the reliability of the data. Thus, while ensuring experimental quality, the system significantly improves the efficiency of experimental task execution.

[0032] In step S101 of some embodiments, specifically, the experimental project refers to a standardized experiment designed for the purpose of experimental research, such as stability testing of pharmaceuticals, periodic testing of materials, and environmental compliance monitoring.

[0033] Specifically, target experimental project information refers to the set of unstructured project information related to each experimental project, including the experimental testing content, experimental record template and experimental testing cycle corresponding to a certain experimental project.

[0034] Specifically, experimental testing content refers to the specific experimental data in standardized experiments, including but not limited to the testing purpose, testing object, and testing indicators.

[0035] For example, drug stability testing includes indicators for drug content and drug impurities; wild chrysanthemum testing includes indicators for chrysanthemum species identification and content detection; and road testing includes indicators for particle size distribution and compressive strength.

[0036] Specifically, the experimental record template refers to a pre-set, standardized data record form in the experimental task automation system. This form includes, but is not limited to, structured fields such as experimental purpose, experimental basis, experimental materials and equipment, experimental date, experimental sample number, test results, and experimenter's signature. This form is used to record the experimental data in a standard format after the experimental task is executed, to ensure the standardization of experimental data recording.

[0037] Specifically, the experimental testing cycle refers to the specific time points at which the experimental testing content is carried out, such as once a month or once a quarter.

[0038] Please see Figure 2 In some embodiments, step S101 may further include configuring a corresponding experimental record template for the experimental detection content, specifically including but not limited to steps S201 to S203: Step S201: Obtain the name of the target detection item in the experimental detection content; Step S202: Based on a preset test item name library, perform repeatability verification on the test item names; wherein, the test item name library stores alternative test item names corresponding to different experimental items; Step S203: If the name of the detection item meets the preset verification pass conditions, a template query is performed in the preset experimental record template library according to the target detection item name to obtain the experimental record template; wherein, the experimental record template library stores alternative record templates corresponding to multiple alternative detection item names.

[0039] In step S201 of some embodiments, specifically, the target detection item name refers to the name of the specific detection item involved in the experimental detection content, and the item name can be named for the experimental item.

[0040] For example, the names of target testing items such as component testing of drug A, fine particle size testing of road particles, or road compressive strength testing.

[0041] In step S202 of some embodiments, specifically, the detection item name library refers to a database that stores alternative detection item names for different experimental items.

[0042] Specifically, after receiving the target detection project name, the target detection project name field is compared with all alternative detection project names stored in the detection project name library to determine whether the currently input target detection project name is substantially repeated with the existing names in the detection project name library.

[0043] For example, for the target detection project name of "Detection of the composition of Drug A", the name field of the target detection project name is matched with all alternative detection project names stored in the detection project name library to determine whether the detection of the composition of Drug A is named repetitively with all alternative detection project names.

[0044] In this embodiment, based on the preset detection project name library, the repeatability verification of the detection project name is performed, which avoids errors or ambiguities caused by chaotic project names during the subsequent generation of experimental tasks, and helps to select the corresponding experimental record template for the unique detection project name in the follow-up to avoid the problem of inconsistent experimental data recording formats.

[0045] In an optional embodiment of the present application, before performing the repeatability verification of the detection project name, it further includes performing a field missing verification on the detection project name to obtain field missing verification data; wherein, the field missing verification data includes that the detection project name field is not missing and the field is missing; if the field missing verification data is that the detection project name field is missing, the detection project name is subjected to a field supplementation process to use the project name after field supplementation as the detection project name; performing a misspelled field verification on the detection project name to obtain misspelled field verification data; wherein, the misspelled field verification data includes that the detection project name field is correct and the field is incorrect; if the misspelled field verification data is that the detection project name field is incorrect, the detection project name is subjected to a field correction process to use the project name after field correction as the detection project name.

[0046] In step S203 of some embodiments, specifically, each experimental record template corresponds to a different target detection project name to meet the requirements of different experimental projects.

[0047] Specifically, the preset verification passing conditions generally include that the detection project name is exactly the same as the alternative detection project name, or it is still determined that the core words are the same after normalization processing (such as removing spaces, converting case, ignoring common suffixes such as "of", "inspection", "determination", etc.).

[0048] For example, if the target detection project name is "Fine-grained detection of road particles" and the alternative detection project name is "Fine-grained inspection of road particles", it indicates that there is a substantial repetition in the naming of the experimental project, and the name needs to be modified until the naming of the experimental project is not substantially repeated with the alternative detection project name.

[0049] Specifically, the experimental record template library is a database that stores alternative record templates corresponding to various alternative test item names.

[0050] For example, if the target test item name "bacterial endotoxin test" meets the verification conditions, then the name is used as an index to search in the experimental record template library. If the experimental record template library contains a candidate record template "bacterial endotoxin test record template", then the candidate record template is selected as the experimental record template.

[0051] In this embodiment, the arbitrary selection or creation of experimental record formats by experimental personnel can be avoided, ensuring that the structure, units, and forms of the recorded data are completely consistent and comparable when different personnel perform the same test item at different times. This is a key guarantee for achieving standardized recording of experimental data.

[0052] Please see Figure 3 In some embodiments, step S102 may include, but is not limited to, steps S301 to S303: Step S301: Convert the experimental detection cycle corresponding to each experimental item into a set of cycle time points.

[0053] Step S302: Select the execution time point of each period from the set of periodic time points that matches the experimental detection content corresponding to each experimental item.

[0054] Step S303: Based on the project execution time point, the experimental detection content corresponding to each experimental project is binary encoded to obtain the project cycle bitmap sequence corresponding to the experimental project.

[0055] In step S301 of some embodiments, the set of periodic time points refers to the set of specific time points into which the experimental detection period is decomposed.

[0056] For example, for an experimental project called "long-term stability test of active pharmaceutical ingredient", the set of time points in the cycle can be the first day of each month, i.e., January 1, February 1, March 1 to December 1.

[0057] In step S302 of some embodiments, specifically, the project execution time point refers to the specific execution time point that matches the experimental detection content in the set of periodic time points.

[0058] For example, if the time period for the experimental project "Detection of the Composition of Drug A" is January 1, April 1, July 1, and October 1, this project corresponds to the experimental testing content of "Detection of the Content of Drug A" and "Detection of Impurities in the Components of Drug A". If the "Detection of the Content of Drug A" requires a six-month interval and is completed in July, then the project execution time points for "Detection of the Content of Drug A" are selected as January 1 and July 1. If the "Detection of Impurities in the Components of Drug A" requires a six-month interval and is completed in October, then the corresponding project execution time points are April 1 and October 1.

[0059] In step S303 of some embodiments, the project cycle bitmap sequence is a binary encoded sequence used to represent the execution status of the experimental detection content at each cycle time point, wherein each "bit" represents the "execution (1)" or "non-execution (0)" status of the detection item at different time points, so as to transform the complex project scheduling plan into machine-readable code.

[0060] For example, if the experimental testing period for the experimental item "Detection of the components of drug A" is 12 months, then the corresponding item period bitmap sequence can be "1,0,0,1,0,0,1,0,0,1,0,0".

[0061] Please see Figure 4 In some embodiments, step S102 may also include, but is not limited to, steps S401 to S403: Step S401: Perform bitmap parsing on the project cycle bitmap sequence corresponding to each experimental item to obtain the detection time point position of the experimental detection content.

[0062] Step S402: Obtain the detection start time of the experimental detection content, and calculate the time axis of the experimental detection content according to the detection time point position and the detection start time to obtain the detection timestamp set.

[0063] Step S403: Encapsulate the instructions based on the detection timestamp set, the experimental detection content, and the experimental record template to obtain the experimental detection instruction sequence.

[0064] In step S401 of some embodiments, specifically, detecting the time point position means identifying the logical sequence number corresponding to the bit that needs to be executed in the bitmap sequence after decoding the project cycle bitmap sequence.

[0065] For example, for a project cycle bitmap sequence “101001” representing 6 cycles (such as months 0, 3, 6, 9, 12, and 18), the parsed detection time point positions are the 0th, 2nd, and 5th positions (counting from 0).

[0066] In step S402 of some embodiments, specifically, the detection start time refers to the date and time when each experimental item begins.

[0067] Specifically, the detection timestamp set refers to the set of specific execution time points calculated based on the detection start time and the location of the detection time point, which is used to clarify the specific execution time of each detection task.

[0068] For example, if the start time of the "Stability Test of Solution B" is "June 1, 2024, 09:00", the testing period is in months, and the testing time points of the experimental test content (such as "pH value determination") are "0, 2, 5", then after the calculation of "start time + N months", the set of test timestamps obtained can be "June 1, 2024, 09:00, August 1, 2024, 09:00, November 1, 2024, 09:00".

[0069] In this embodiment, the experimental detection content is calculated on a timeline based on the detection time point location and detection start time to obtain a set of detection timestamps. This can determine the execution time of each experimental detection content, which not only avoids the problem of experimental task scheduling errors that may occur due to manual calculation of dates, but also provides a solid data foundation for the automated generation of subsequent tasks.

[0070] In step S403 of some embodiments, specifically, the experimental detection instruction sequence refers to a series of encapsulated instructions used to guide the generation and execution of subsequent experimental project detection tasks.

[0071] Specifically, for each detection timestamp, an instruction object is created, and the detection timestamp, the specific experimental detection content being processed, and the experimental record template bound to the experimental detection content are encapsulated into the instruction object to generate an experimental detection instruction. All experimental detection instructions are then combined to obtain an experimental detection instruction sequence.

[0072] For example, for the experimental testing content "A drug content detection" corresponding to an experimental project, the experimental testing instruction can be "Test timestamp: July 1, 2024, 09:00, Experimental testing content: A drug content detection, Experimental record template: A drug content detection record template_V2.1".

[0073] In this embodiment, the instructions are encapsulated based on the detection timestamp set, experimental detection content, and experimental record template, which can generate a standardized sequence of experimental detection instructions. This ensures the standardization and consistency of experimental operations, avoids data errors caused by non-standard manual operations, and helps to improve the quality of experimental data in subsequent experimental task execution.

[0074] Please see Figure 5In some embodiments, step S102 may also include, but is not limited to, steps S501 to S503: Step S501: Obtain the experimental material information and experimental instrument information corresponding to the experimental testing content according to the experimental testing instruction sequence.

[0075] Step S502: Based on the set of detection timestamps, experimental material information, and experimental instrument information in the experimental detection instruction sequence, generate a detection preparation task corresponding to the experimental project.

[0076] Step S503: In response to the execution of the detection preparation task, an experimental project detection task corresponding to the experimental project is generated based on the detection timestamp set and the experimental record template.

[0077] In step S501 of some embodiments, specifically, experimental material information refers to the specific information of various materials and reagents required in the experimental testing process, including but not limited to the name, specifications, batch, etc. of the drugs.

[0078] Specifically, experimental instrument information refers to detailed information about the instruments and equipment used in the experiment, including but not limited to the instrument's model, serial number, calibration status, etc.

[0079] Specifically, based on the experimental testing content in the experimental testing instruction sequence, the experimental record database can be used to retrieve the corresponding experimental material information and experimental instrument information.

[0080] For example, for the experimental test content "Detection of drug A content", the experimental material information required for the experimental test content "Drug A standard, specification: 50mg / bottle, batch: 20240701" and the experimental instrument information "Ultraviolet spectrophotometer, model: UV-5678, serial number: EQP002, calibration validity period until June 2025" can be found from the experimental record database.

[0081] In step S502 of some embodiments, specifically, the test preparation task refers to the auxiliary task arranged in advance before the formal test is performed to ensure that the experiment can be carried out smoothly, which is used to complete the preparation of materials, instruments and environmental conditions before the experiment.

[0082] For example, if the set of test timestamps is "July 1, 2024, 08:00 and October 1, 2024, 08:00", the experimental material information is "water quality testing reagent, specification: 100mL / bottle, batch: 20240601", and the experimental instrument information is "water quality analyzer, model: WQ-3000, serial number: EQP003", then a test preparation task can be generated: "Prepare water quality testing reagent and water quality analyzer at 08:00 on July 1, 2024 and 08:00 on October 1, 2024".

[0083] In this embodiment, a detection preparation task corresponding to the experimental project is generated based on the set of detection timestamps, experimental material information, and experimental instrument information in the experimental detection instruction sequence. This allows for advance planning of the materials and instruments required for the experiment, ensuring the smooth progress of the experimental operation, avoiding experimental delays due to insufficient preparation, and helping to improve the efficiency of subsequent experimental tasks.

[0084] In step S503 of some embodiments, specifically, the experimental project detection task refers to a specific task generated based on the detection timestamp set and the experimental record template to guide the experimental operation after the detection preparation task is completed.

[0085] Specifically, after the test preparation task is executed, if the test timestamp set is "July 1, 2024, 08:00, October 1, 2024, 08:00" and the experimental record template is "Water Quality Test Record Template_V3.0", then the experimental project test task can be generated as follows: "At 08:00 on July 1, 2024, conduct water quality testing according to Water Quality Test Record Template_V3.0; at 08:00 on October 1, 2024, conduct water quality testing according to Water Quality Test Record Template_V3.0".

[0086] In this embodiment, based on the set of detection timestamps, experimental material information, and experimental instrument information in the experimental detection instruction sequence, the automatic generation of experimental items into experimental tasks is realized, which significantly improves the efficiency of experimental task generation. It also effectively avoids problems such as inconsistent experimental data recording formats and incorrect task scheduling caused by manual interpretation and arrangement in traditional methods, thus ensuring the quality of subsequent experimental record data.

[0087] Please see Figure 6 In some embodiments, step S103 may include, but is not limited to, steps S601 to S605: Step S601: Obtain the task priority of multiple experimental project detection tasks.

[0088] Step S602: Based on the experimental instrument information corresponding to each experimental project detection task, query the usage status of the corresponding task instrument.

[0089] Step S603: Execute the detection tasks of each experimental item according to the task priority and the instrument usage status to obtain the initial experimental data.

[0090] Step S604: Use the experimental record template to perform data standardization verification on the initial experimental data to obtain the data standardization defects that the initial experimental data has.

[0091] Step S605: Correct the data for data specification defects in the initial experimental data to obtain the target experimental test data.

[0092] In step S601 of some embodiments, specifically, task priority refers to the urgency of the experimental project detection task, and the task priority from urgent to non-urgent can be divided into three levels: "high", "medium" and "low".

[0093] Specifically, task priorities can be determined based on the nature of the experimental project, the delivery deadline, or the degree of impact on subsequent experimental procedures.

[0094] For example, if experimental task a is "detection of the content of key components of drugs" and experimental task b is "appearance inspection of drugs", the task priority of task a is determined to be "high" and the task priority of task b is "medium" based on the importance and urgency of the experimental projects.

[0095] In this embodiment, by obtaining the task priorities of multiple experimental project detection tasks, the execution order of tasks can be reasonably arranged to ensure that important tasks are completed first, thereby improving the utilization efficiency of experimental resources.

[0096] In step S602 of some embodiments, specifically, the instrument usage status refers to the availability status of the experimental instrument at a specific point in time, including whether the instrument is being used or needs maintenance.

[0097] For example, if the experimental task C requires the use of a "high performance liquid chromatograph, model: HPLC-1234, serial number: EQP001", then check the availability of the instrument before executing task C. If the instrument status shows "idle", then task C can be executed normally; if the instrument status shows "in use", then adjust the task execution time or assign other available instruments.

[0098] In this embodiment, based on the experimental instrument information corresponding to each experimental project detection task, the usage status of the corresponding task instrument is queried to ensure the reasonable scheduling and effective use of experimental instruments, avoid experimental task delays caused by instrument unavailability, and improve the efficiency of experimental task execution.

[0099] In step S603 of some embodiments, specifically, the initial experimental data refers to the raw data set that is directly output by the instrument during the execution of the experimental project detection task and has not undergone any formatting or standardization processing. It may include, but is not limited to, fields such as measured values, spectra, timestamps, ambient temperature and humidity, and operator identity.

[0100] Please see Figure 7 In some embodiments, step S603 may also include, but is not limited to, steps S701 to S704: Step S701: Based on the task priority and the instrument usage status, select the target experimental task for the current round from the detection tasks of each experimental project, and execute the target experimental task for the current round.

[0101] Step S702: During the execution of the target experimental task, a task risk assessment is performed on the target experimental task of the current round to obtain task risk assessment data and task risk type.

[0102] Step S703: In response to the fact that the task risk assessment data corresponding to the target experimental task does not meet the preset risk definition conditions, after the target experimental task of the current round is completed, the target experimental task of the next round is selected from the detection tasks of each experimental item according to the task priority and the instrument usage status, and the target experimental task of the next round is executed.

[0103] Step S704: In response to the existence of task risk assessment data corresponding to the target experimental task that meets the preset risk definition conditions, perform risk response operations based on the task risk type.

[0104] In step S701 of some embodiments, specifically, the target experimental task refers to the experimental task that is selected from the various experimental project detection tasks based on task priority and the status of instrument usage and has the conditions for execution.

[0105] Specifically, all tasks to be executed can be sorted in descending order of priority to obtain the experimental task order. Based on the experimental task order, tasks with "high" priority are given priority, and the availability of required instruments is checked. Tasks with required instruments in "in use", "under maintenance" or "calibration expired" status are eliminated to obtain the target experimental tasks that can be executed in the current round.

[0106] For example, if the experimental project detection task list contains task J (priority "high", requires instrument x) and task K (priority "medium", requires instrument y), and instrument x is currently "idle" while instrument y is "in use", then task J is the target experimental task.

[0107] In this embodiment, target experimental tasks are selected from the experimental project detection tasks based on task priority and instrument usage status. This allows for a reasonable arrangement of task execution order and avoids task delays caused by instrument unavailability. It achieves automated execution of experimental tasks and improves the efficiency of experimental task execution and resource utilization.

[0108] In step S702 of some embodiments, specifically, the task risk assessment data refers to the degree of risk after a real-time risk assessment of the target experimental task being performed.

[0109] Specifically, the risk type of the task refers to the risk category of the target experimental task, which may include, but is not limited to, instrument malfunction, environmental exceedances, data drift, and quality control failure.

[0110] Specifically, by analyzing factors such as abnormal events, instrument status, and data integrity in the execution status of the target experimental task, and comparing them with preset safety thresholds, standard operating time, or compliance requirements, a risk event is triggered if the task operation parameters exceed the allowable range, and the risk type corresponding to the risk event is identified.

[0111] For example, if the recovery rate of the quality control sample in the "content determination" task exceeds 100±5% for two consecutive points, the task risk assessment data can be generated as follows: recovery rate 107.3%, task risk type is quality control failure.

[0112] In this embodiment, by conducting a task risk assessment for the current round of the target experimental task during the execution of the target experimental task, the task execution status can be detected in real time. Potential experimental quality hazards can be discovered at the first time, preventing invalid data from flowing downstream, reducing the overall rework rate, and providing accurate input for subsequent risk response.

[0113] In step S703 of some embodiments, specifically, the risk definition conditions are a pre-set set of thresholds or rules used to determine whether the risk has reached the level requiring immediate intervention, which can be determined based on the actual scenario.

[0114] For example, temperature fluctuations of less than or equal to 1 degree Celsius, temperature exceeding limits for more than 10 minutes, or experimental delays exceeding 20% ​​of the planned time.

[0115] Specifically, if the risk assessment data corresponding to the target experimental task does not meet the preset risk definition conditions, that is, if the risk definition conditions are not met, it is considered that the risk is controllable and the normal process can continue, then after the target experimental task of the current round is completed, the target experimental task of the next round is selected from the detection tasks of each experimental project according to the task priority and the status of the instrument, and the target experimental task of the next round is executed.

[0116] In step S704 of some embodiments, specifically, risk response operation refers to corrective or compensatory measures taken in response to a confirmed high-risk event.

[0117] For example, if the risk type of the target experiment in the current round is "instrument malfunction", the risk response operation can be to pause the target experiment in the current round, set the instrument status to maintenance, and put the task back into the scheduling queue; if the risk type is "quality control failure", the risk response operation can be to add quality control retest samples and re-queue them in the same sequence; if the risk type is data drift, the risk response operation can be to automatically retest and call the calibration program, etc. After the risk response operation is completed, the next round will not continue, but the screening will be performed again from the head of the queue to ensure that subsequent tasks do not repeat the risk on the same instrument.

[0118] In this embodiment, in response to the fact that the task risk assessment data corresponding to the target experimental task meets the preset risk definition conditions, risk response operations are performed based on the task risk type. This enables automatic isolation and rapid recovery of abnormal task execution situations detected in real time, preventing risks from spreading down the task chain.

[0119] In step S604 of some embodiments, specifically, data specification defects refer to parts of the initial experimental data that do not conform to the format or standard specified in the experimental record template.

[0120] Specifically, the initial experimental data can be validated according to the pre-set validation rules in the experimental record template. By comparing the initial experimental data with the validation rules one by one, the data items that do not meet the validation rules and the types of validation rules they violate are marked and integrated to form data specification defects. The validation rules can include data type validation (such as whether it is a number), data range validation (such as whether it is within a reasonable range), logical relationship validation (such as the relationship between sample weight and consumption), and mandatory field validation.

[0121] For example, if the validation rule of the experimental record template is that the "pH value" field should be a value between 6.0 and 8.0, but the initial experimental data is 9.5, it constitutes a defective factor of "value out of range"; if the validation rule of the experimental record template is that the "experimenter's signature" field cannot be empty, but the initial experimental data is not filled in, it constitutes a defective factor of "missing required field".

[0122] In this embodiment, the experimental record template is used to perform data standardization verification on the initial experimental data. This can identify and mark data that does not conform to the experimental record template specifications, providing a basis for subsequent data standardization correction, ensuring the standardization and consistency of experimental data, and avoiding analytical bias caused by data format errors.

[0123] In step S605 of some embodiments, specifically, the target experimental test data refers to the valid experimental data after correcting all data specification defects identified in the initial experimental data.

[0124] For example, the initial experimental data was corrected from a flawed factor, pH 9.5, to the actual measured value of 7.8, and the missing experimenter signature was added to obtain the corrected target experimental test data.

[0125] In this embodiment, data correction is performed to address data specification defects in the initial experimental data, thereby generating target experimental detection data that conforms to the template specification. This converts unstructured target experimental project information into structured target experimental detection data, ensuring not only the quality of experimental data but also improving the efficiency of experimental task execution.

[0126] In one optional embodiment of this application, the method for automating the execution of experimental tasks further includes: storing the experimental record operation log and experimental data during the experimental operation process by using version snapshot technology, so as to retain the traces of experimental operations and thereby realize the tracking of experimental data during the execution of experimental tasks.

[0127] For example, when modifying experimental task data or adjusting experimental parameters, version snapshot technology can be used to record the specific content, timestamp, and operator information of the experimental project detection operation in real time, and generate a version snapshot of the experimental data change. The version snapshot of the experimental data change can be reviewed at any time so that the real-time status and change process of the experimental project detection operation can be viewed when needed.

[0128] Furthermore, for experimental testing operations, multi-level review processes, access control, and anomaly handling procedures can be combined to ensure that every step of the experimental testing operation is under control.

[0129] For example, after acquiring the target experimental test data, a multi-level review process can be triggered, with different levels of reviewers conducting reviews sequentially. The operation permissions of different experimental personnel are strictly controlled, and only personnel with the corresponding permissions can perform specific operations. Furthermore, an anomaly handling procedure is implemented for the experimental project testing operations to detect and handle abnormal situations (such as data anomalies, operation timeouts, etc.) during the experimental project testing operations, and to promptly issue alarms to notify relevant personnel. This ensures the standardization of experimental operations and the accuracy of data, avoiding quality problems caused by human error or system failure.

[0130] In this embodiment, by automatically recording experimental operation logs and changes in experimental operation data, combined with multi-level review processes, access control, and exception handling procedures, it is possible to achieve full monitoring and quality assurance of experimental project testing operations. This not only ensures the reliability and traceability of experimental data generated during the execution of experimental tasks, but also ensures the standardization and controllability of experimental operations.

[0131] This application first collects multiple sets of target experimental project information for different experimental projects. Each set of target experimental project information includes the experimental detection content, experimental record template, and experimental detection cycle corresponding to one experimental project, providing comprehensive basic data for the subsequent generation of experimental tasks and ensuring that the execution of experimental tasks is based on evidence. Second, for each experimental project, bitmap encoding is performed according to the experimental detection content and experimental detection cycle corresponding to each experimental project to obtain a project cycle bitmap sequence. This provides machine-readable standardized input for the subsequent automated execution of tasks and also solves problems such as task scheduling errors. Based on the project cycle bitmap sequence, experimental detection content, and experimental record template, an experimental detection instruction sequence is generated. This can solve the problem of inconsistent experimental data recording formats by combining experimental templates. For the experimental detection instruction sequence, experimental project detection tasks corresponding to the experimental projects are generated, realizing the automated generation from experimental projects to experimental tasks. This significantly improves the efficiency of experimental task generation and effectively avoids problems such as inconsistent experimental data recording formats and task scheduling errors caused by manual interpretation and arrangement in traditional methods. Finally, experimental detection operations are performed based on the generated experimental project detection tasks to ensure the compliance of the experimental process and the reliability of the data. This significantly improves the efficiency of experimental task execution while ensuring experimental quality.

[0132] Please see Figure 8 This application also provides an automated experimental task execution system, which can implement the above-mentioned automated experimental task execution method. The system includes: The experimental project information collection module is used to collect information about the target experimental project; the target experimental project information includes the experimental testing content, experimental record template, and experimental testing cycle. The experimental project detection task generation module is used to determine the corresponding experimental project detection task for each experimental project. Specifically, the experimental project detection task is determined by the following steps: bitmap encoding is performed according to the experimental detection content and experimental detection cycle corresponding to each experimental project to obtain the project cycle bitmap sequence corresponding to the experimental project; experimental instructions are generated based on the corresponding project cycle bitmap sequence, experimental detection content and experimental record template to obtain the experimental detection instruction sequence; and experimental project detection task corresponding to the experimental project is generated based on the experimental detection instruction sequence. The experiment task execution module is used to perform the experiment detection operations based on each experiment detection task.

[0133] The specific implementation of the automated execution system for experimental tasks is basically the same as the specific implementation of the automated execution method for experimental tasks described above, and will not be repeated here.

[0134] This application also provides an electronic device, which includes a memory and a processor. The memory stores a computer program, and the processor executes the computer program to implement the above-described method for automating the experimental task. This electronic device can be any smart terminal, including tablet computers, in-vehicle computers, etc.

[0135] Please see Figure 9 , Figure 9 The hardware structure of an electronic device according to another embodiment is illustrated. The electronic device includes: The processor 901 can be implemented using a general-purpose CPU (Central Processing Unit), microprocessor, application-specific integrated circuit (ASIC), or one or more integrated circuits, and is used to execute relevant programs to implement the technical solutions provided in the embodiments of this application. The memory 902 can be implemented as a read-only memory (ROM), a static storage device, a dynamic storage device, or a random access memory (RAM). The memory 902 can store the operating system and other application programs. When the technical solutions provided in the embodiments of this specification are implemented through software or firmware, the relevant program code is stored in the memory 902 and is called by the processor 901 to execute the automated execution method for experimental tasks in the embodiments of this application. The input / output interface 903 is used to implement information input and output; The communication interface 904 is used to enable communication and interaction between this device and other devices. Communication can be achieved through wired means (such as USB, Ethernet cable, etc.) or wireless means (such as mobile network, WIFI, Bluetooth, etc.). Bus 905 transmits information between various components of the device (e.g., processor 901, memory 902, input / output interface 903, and communication interface 904); The processor 901, memory 902, input / output interface 903, and communication interface 904 are connected to each other within the device via bus 905.

[0136] Memory, as a non-transitory computer-readable storage medium, can be used to store non-transitory software programs and non-transitory computer-executable programs. Furthermore, memory may include high-speed random access memory, and may also include non-transitory memory, such as at least one disk storage device, flash memory device, or other non-transitory solid-state storage device. In some embodiments, memory may optionally include memory remotely located relative to the processor, and these remote memories can be connected to the processor via a network. Examples of such networks include, but are not limited to, the Internet, intranets, local area networks, mobile communication networks, and combinations thereof.

[0137] The embodiments described in this application are for the purpose of more clearly illustrating the technical solutions of the embodiments of this application, and do not constitute a limitation on the technical solutions provided by the embodiments of this application. As those skilled in the art will know, with the evolution of technology and the emergence of new application scenarios, the technical solutions provided by the embodiments of this application are also applicable to similar technical problems.

[0138] Those skilled in the art will understand that the technical solutions shown in the figures do not constitute a limitation on the embodiments of this application, and may include more or fewer steps than shown, or combine certain steps, or different steps.

[0139] The system embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs.

[0140] Those skilled in the art will understand that all or some of the steps in the methods disclosed above, as well as the functional modules / units in the systems and devices, can be implemented as software, firmware, hardware, or suitable combinations thereof.

[0141] The terms “first,” “second,” “third,” etc. (if present) in the specification and accompanying drawings of this application are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of this application described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms “comprising” and “having,” and any variations thereof, are intended to cover a non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0142] It should be understood that in this application, "at least one (item)" means one or more, and "more than" means two or more. "And / or" is used to describe the relationship between related objects, indicating that three relationships can exist. For example, "A and / or B" can represent three cases: only A exists, only B exists, and both A and B exist simultaneously, where A and B can be singular or plural. The character " / " generally indicates that the preceding and following related objects are in an "or" relationship. "At least one (item) of the following" or similar expressions refer to any combination of these items, including any combination of single or plural items. For example, at least one (item) of a, b, or c can represent: a, b, c, "a and b", "a and c", "b and c", or "a and b and c", where a, b, and c can be single or multiple.

[0143] In the embodiments provided in this application, it should be understood that the disclosed systems and methods can be implemented in other ways. For example, the system embodiments described above are merely illustrative; for instance, the division of the units described above is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. The coupling or direct coupling or communication connection between the shown or discussed units may be through some interfaces, and the indirect coupling or communication connection between the system or units may be electrical, mechanical, or other forms.

[0144] The units described above as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0145] Furthermore, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0146] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes multiple instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods of the various embodiments of this application. The aforementioned storage medium includes various media capable of storing programs, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0147] The preferred embodiments of the present application have been described above with reference to the accompanying drawings, but this does not limit the scope of the claims of the present application. Any modifications, equivalent substitutions, and improvements made by those skilled in the art without departing from the scope and substance of the embodiments of the present application shall be within the scope of the claims of the present application.

Claims

1. A method for automated execution of experimental tasks, characterized in that, The method includes: Collect multiple sets of target experimental project information corresponding to different experimental projects; wherein, each set of target experimental project information includes the experimental detection content, experimental record template and experimental detection cycle corresponding to one of the experimental projects; For each of the aforementioned experimental items, a corresponding experimental item detection task is determined: wherein, the experimental item detection task is specifically determined by the following steps: performing bitmap encoding based on the experimental detection content and experimental detection cycle corresponding to each of the aforementioned experimental items to obtain an item cycle bitmap sequence corresponding to the experimental item; generating experimental instructions based on the corresponding item cycle bitmap sequence, the experimental detection content, and the experimental record template to obtain an experimental detection instruction sequence; and generating an experimental item detection task corresponding to the experimental item for the experimental detection instruction sequence. Perform experimental item detection operations based on each of the experimental item detection tasks.

2. The method of claim 1, wherein, The step involves bitmap encoding based on the experimental detection content and experimental detection cycle corresponding to each experimental item to obtain an item cycle bitmap sequence corresponding to the experimental item, including: The experimental detection period corresponding to each of the aforementioned experimental items is converted into a set of periodic time points. From the set of periodic time points, select the project execution time points that match the experimental detection content corresponding to each of the experimental items; Based on the execution time of the project, the experimental detection content corresponding to each experimental project is binary encoded to obtain the project period bitmap sequence corresponding to the experimental project.

3. The method according to claim 1, characterized in that, The experimental instructions are generated based on the corresponding project cycle bitmap sequence, the experimental detection content, and the experimental record template to obtain an experimental detection instruction sequence, including: Bitmap parsing is performed on the project period bitmap sequence corresponding to each of the experimental items to obtain the detection time point position of the experimental detection content; Obtain the detection start time of the experimental detection content, and perform timeline calculation on the experimental detection content based on the detection time point position and the detection start time to obtain a set of detection timestamps; The experimental detection instruction sequence is obtained by encapsulating the detection timestamp set, the experimental detection content, and the experimental record template.

4. The method according to claim 3, characterized in that, The step of generating an experimental project detection task corresponding to the experimental project for the experimental detection instruction sequence includes: According to the experimental testing instruction sequence, obtain the experimental material information and experimental instrument information corresponding to the experimental testing content; Based on the set of detection timestamps, the information of experimental materials, and the information of experimental instruments in the experimental detection instruction sequence, a detection preparation task corresponding to the experimental project is generated. In response to the execution of the detection preparation task, an experimental project detection task corresponding to the experimental project is generated based on the detection timestamp set and the experimental record template.

5. The method according to claim 4, characterized in that, The step of performing experimental item detection operations based on each experimental item detection task includes: Obtain the task priority of multiple experimental project detection tasks; Based on the experimental instrument information corresponding to each experimental project detection task, query the usage status of the corresponding task instrument. Execute each experimental item detection task according to the task priority and the instrument usage status to obtain initial experimental data; The initial experimental data was validated using the experimental record template to identify data standardization flaws in the initial experimental data. The data is corrected to address the data specification defects in the initial experimental data to obtain the target experimental detection data.

6. The method according to claim 5, characterized in that, The execution of each experimental item detection task according to the task priority and the instrument usage status includes: Based on the task priority and the instrument usage status, the target experimental task for the current round is selected from the detection tasks of each experimental project, and the target experimental task for the current round is executed. During the execution of the target experimental task, a task risk assessment is performed for the target experimental task in the current round to obtain task risk assessment data and task risk type; In response to the fact that the risk assessment data corresponding to the target experimental task does not meet the preset risk definition conditions, after the target experimental task in the current round is completed, the target experimental task for the next round is selected from the detection tasks of each experimental item according to the task priority and the instrument usage status, and the target experimental task for the next round is executed. In response to the existence of task risk assessment data corresponding to the target experimental task that meets the preset risk definition conditions, a risk response operation is performed based on the task risk type.

7. The method according to any one of claims 1 to 6, characterized in that, The collection of multiple sets of target experimental project information corresponding to different experimental projects includes configuring corresponding experimental record templates for the experimental detection content, specifically including: Obtain the name of the target detection item in the experimental detection content; Based on a preset database of test item names, the test item names are checked for repeatability; wherein, the database of test item names stores alternative test item names corresponding to different experimental items. If the name of the detection item meets the preset verification pass conditions, a template query is performed in the preset experimental record template library according to the target detection item name to obtain the experimental record template; wherein, the experimental record template library stores alternative record templates corresponding to a variety of alternative detection item names.

8. An automated experimental task execution system, characterized in that, The system includes: The experimental project information collection module is used to collect information about the target experimental project; the target experimental project information includes the experimental testing content, experimental record template, and experimental testing cycle. The experimental project detection task generation module is used to determine the corresponding experimental project detection task for each of the experimental projects. Specifically, the experimental project detection task is determined by the following steps: bitmap encoding is performed according to the experimental detection content and experimental detection cycle corresponding to each of the experimental projects to obtain a project cycle bitmap sequence corresponding to the experimental project; experimental instructions are generated based on the corresponding project cycle bitmap sequence, the experimental detection content and the experimental record template to obtain an experimental detection instruction sequence; and experimental project detection task corresponding to the experimental project is generated for the experimental detection instruction sequence. The experimental task execution module is used to perform experimental item detection operations based on each experimental item detection task.

9. An electronic device, characterized in that, The electronic device includes a memory and a processor. The memory stores a computer program, and the processor executes the computer program to implement the automated experimental task execution method according to any one of claims 1 to 7.

10. A computer-readable storage medium storing a computer program, characterized in that, When the computer program is executed by the processor, it implements the experimental task automation execution method according to any one of claims 1 to 7.

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