Laboratory maintenance management system

Abstract

The invention relates to the technical field of laboratory maintenance management. The invention relates to a laboratory maintenance management system. The system comprises an experimental equipment determination unit, an experimental feedback unit, an experimental equipment model setting unit, an experimental equipment maintenance unit and a model maintenance updating unit. The experimental equipment determination unit is used for acquiring an experimental equipment list in a laboratory and then acquiring parameter data of each experimental equipment according to the equipment list; the experiment feedback unit is used for collecting experiment records, monitoring operation data of the experiment equipment and then combining the experiment records with the operation data to carry out experiment feedback collection so as to obtain use feedback data of each experiment equipment; by collecting the list of the experimental equipment in the laboratory and combining the network big data to obtain the parameter data of each experimental equipment, the basic characteristics and performance indexes of the equipment can be comprehensively known, and accurate basic information is provided for subsequent equipment management and maintenance.

Description

Technical Field

[0001] The present invention relates to the technical field of laboratory maintenance management, and in particular to a laboratory maintenance management system. Background Art

[0002] Laboratory equipment maintenance management plays a vital role in scientific research, teaching experiments and other fields. Basic management and maintenance of experimental equipment is carried out to ensure that the experimental equipment can operate normally and meet the needs of the experiment, thereby improving the availability and reliability of the experimental equipment, extending the service life of the equipment, and ensuring the smooth progress of the experiment.

[0003] At present, the management of experimental equipment mainly relies on manual records and regular inspections. Experimenters register before and after using the equipment, and managers regularly inspect and maintain the equipment. However, manual records and inspections are prone to omissions and errors, and it is impossible to accurately grasp the operating status of the equipment in real time, which may lead to equipment failures not being discovered in time, affecting the progress and results of the experiment. In addition, there is a lack of intelligent analysis of the equipment, and equipment failures cannot be predicted in advance. Repairs are often carried out only after the equipment fails, resulting in long equipment downtime and affecting the work efficiency of the laboratory. A laboratory maintenance management system is proposed. Summary of the invention

[0004] The object of the present invention is to provide a laboratory maintenance management system to solve the problems raised in the above background technology.

[0005] To achieve the above-mentioned purpose, a laboratory maintenance management system is provided, which includes an experimental equipment determination unit, an experimental feedback unit, an experimental equipment model setting unit, an experimental equipment maintenance unit and a model maintenance and updating unit;

[0006] The experimental equipment determination unit is used to collect a list of experimental equipment in the laboratory, and then obtain parameter data of each experimental equipment according to the equipment list;

[0007] The experimental feedback unit is used to collect experimental records and monitor the operating data of the experimental equipment, and then collect experimental feedback by combining the experimental records with the operating data, so as to obtain the usage feedback data of each experimental equipment;

[0008] The experimental equipment model setting unit is used to establish an experimental equipment model for each experimental equipment, and when the experimental equipment is put into use for the first time, the obtained usage feedback data is subjected to process detection, and the usage feedback data that passes the process detection is combined with parameter data to initialize the experimental equipment model;

[0009] The experimental equipment maintenance unit is used to perform maintenance analysis on the experimental equipment model, thereby setting the maintenance node of the experimental equipment model, and then simulate the use and update of the experimental equipment model according to the use feedback data obtained by the experimental feedback unit, and at the same time, perform qualified analysis on the experimental equipment model in combination with the maintenance node, and mark the experimental equipment for maintenance according to the analysis results;

[0010] The model maintenance and update unit is used to monitor the experimental equipment marked by the experimental equipment maintenance unit, and notify the experimental equipment management end to perform maintenance. At the same time, it collects maintenance feedback from the experimental equipment after maintenance, sends the maintenance data to the experimental equipment model setting unit, and completes the maintenance and update of the experimental equipment model initialization.

[0011] As a further improvement of the present technical solution, the experimental equipment determination unit establishes a data transmission channel with the laboratory management end to obtain the data collected by the laboratory management end, and then collects the list of experimental equipment used in the laboratory from the laboratory management end, and extracts parameter data for each experimental equipment based on the experimental equipment list combined with network big data.

[0012] As a further improvement of the technical solution, the experiment feedback unit collects real-time experiment records of the experimenters by monitoring the experimenter record module of the laboratory management end. When the experimenter clocks out of the laboratory, the experiment record collection is initiated to the experimenter, so as to collect the experiment records fed back by the experimenter;

[0013] At the same time, the experimental feedback unit can use the laboratory management terminal to actively initiate experimental record collection to the experimenters.

[0014] As a further improvement of the technical solution, the experimental feedback unit includes an operation status monitoring module and a feedback data integration module;

[0015] The operation status monitoring module is used to divide the experimental equipment into online and offline states. When the experimental equipment is in use, the experimental equipment is considered to be in online state, and operation data of the experimental equipment in the online state is collected until the experimental equipment enters the offline state, and then the operation data is saved according to the collection period as a label;

[0016] When the experimental equipment is not in use, it is considered to be in an offline state;

[0017] The feedback data integration module is used to perform experimental equipment usage detection based on the experimental records feedback by the experimenters, obtain the corresponding experimental equipment and operation records in the experimental records, and extract the operation data saved in the corresponding period of the experimental records, and then combine the operation data corresponding to each experimental equipment with the operation records as usage feedback data.

[0018] As a further improvement of the technical solution, the experimental equipment model setting unit includes a model building module and an initialization setting module;

[0019] The model building module is used to build an experimental equipment model for each experimental equipment according to parameter data;

[0020] The initialization setting module is used to perform simulation precondition detection and analysis on the experimental equipment, so as to obtain the preconditions of the experimental equipment simulation. Later, when the experimental equipment is put into use for the first time, the usage feedback data fed back by the experimenter is combined with the preconditions to perform process detection. When the usage feedback data meets the preconditions, the experimental equipment model is initialized and set according to the usage feedback data. Conversely, when the usage feedback data does not meet the preconditions, the experimenter is asked to collect and supplement the missing preconditions.

[0021] As a further improvement of the technical solution, the formula of the initialization setting module is as follows:

[0022]

[0023] Among them, F is the result of using feedback data to meet the preconditions, P is the precondition set, and D is the feedback data set used. Indicates that the feedback data set is completely contained in the precondition set. Indicates that the feedback data set is not completely contained in the precondition set.

[0024] As a further improvement of the technical solution, the experimental equipment maintenance unit includes a maintenance node setting module and a maintenance detection module;

[0025] The maintenance node setting module is used to perform maintenance analysis according to the experimental equipment model after initialization setting, and to set maintenance nodes for the experimental equipment model;

[0026] The maintenance detection module is used to simulate the use of operation records in conjunction with the experimental equipment model, and at the same time update the data of the experimental equipment model based on the simulated usage data, and then combine the updated experimental equipment model with the maintenance node for qualification analysis. When the experimental equipment model meets the maintenance node, the experimental equipment is marked as requiring maintenance on the laboratory management end. Conversely, when the experimental equipment model does not meet the maintenance node, monitoring continues.

[0027] As a further improvement of the present technical solution, the formulas of the maintenance node setting module and the maintenance detection module are as follows:

[0028]

[0029] Among them, M is the setting result of the maintenance node, I is the maintenance indicator set, and D is the equipment model data set;

[0030] Simulation use:

[0031] M ′ =simulate(M,O)

[0032] Data update:

[0033] U=update(M ′ ,data)

[0034] Qualification Analysis:

[0035]

[0036] Among them, M is the experimental equipment model, O is the operation record, U is the updated model, N is the maintenance node, S is the equipment status, simulate is the simulation function, and M ′ is the model after simulation, and update is the update function.

[0037] As a further improvement of the technical solution, the model maintenance and updating unit sends the maintenance data to the experimental equipment model setting unit, replacing the feedback data, thereby completing the initialization update of the experimental equipment model through the maintenance data.

[0038] Compared with the prior art, the present invention has the following beneficial effects:

[0039] 1. In this laboratory maintenance management system, by collecting the list of experimental equipment in the laboratory and combining it with network big data to obtain the parameter data of each experimental equipment, it is possible to fully understand the basic characteristics and performance indicators of the equipment, and provide accurate basic information for subsequent equipment management and maintenance. At the same time, based on the feedback records and operation records of the experimenters, combined with the operation data, usage feedback data is generated to make the use of the equipment clearer.

[0040] 2. In this laboratory maintenance management system, by establishing a model for each experimental equipment and performing process detection and initialization settings when it is put into use for the first time, the accuracy and reliability of the equipment model are ensured. At the same time, by performing maintenance analysis on the experimental equipment model and setting maintenance nodes, the maintenance needs of the equipment can be predicted in advance. By combining the use of feedback data for simulated usage updates and qualification analysis, the equipment is marked for maintenance, thereby realizing intelligent and precise maintenance management.

[0041] 3. In this laboratory maintenance management system, by monitoring the marked experimental equipment and notifying the management end to perform maintenance, and collecting maintenance feedback data to initialize and update the equipment model, a closed-loop maintenance management system is formed. The equipment model can be continuously optimized, the stability of the equipment can be improved, and unnecessary maintenance work can be reduced, and maintenance costs can be reduced. Through predictive maintenance and reasonable maintenance plans, the service life of the equipment can be extended, the cost of equipment updates can be reduced, and resource utilization can be maximized while ensuring the normal operation of the equipment. BRIEF DESCRIPTION OF THE DRAWINGS

[0042] Figure 1 It is the overall structural principle diagram of the present invention.

[0043] The meaning of each number in the figure is:

[0044] 10. Experimental equipment determination unit; 20. Experimental feedback unit; 30. Experimental equipment model setting unit; 40. Experimental equipment maintenance unit; 50. Model maintenance and update unit. DETAILED DESCRIPTION

[0045] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0046] See also Figure 1 As shown, the purpose of this embodiment is to provide a laboratory maintenance management system, including an experimental equipment determination unit 10, an experimental feedback unit 20, an experimental equipment model setting unit 30, an experimental equipment maintenance unit 40 and a model maintenance update unit 50;

[0047] The experimental equipment determination unit 10 is used to collect a list of experimental equipment in the laboratory, and then obtain parameter data of each experimental equipment according to the equipment list;

[0048] The experimental equipment determination unit 10 establishes a data transmission channel with the laboratory management end to obtain the data collected by the laboratory management end, and then collects the list of experimental equipment used in the laboratory from the laboratory management end, and extracts parameter data for each experimental equipment based on the experimental equipment list combined with network big data. The specific steps are as follows:

[0049] Establishing a data transmission channel: Selecting a suitable communication protocol, such as HTTP, TCP / IP, etc., to ensure the stability and security of data transmission, respectively configuring corresponding communication interfaces on the experimental equipment determination unit 10 and the laboratory management end for data transmission, and then establishing a connection between the experimental equipment determination unit 10 and the laboratory management end through the configured communication interface;

[0050] Acquiring data collected by the laboratory management end: the experimental equipment determination unit 10 sends a data request to the laboratory management end, requesting to obtain the data collected by the laboratory management end. The laboratory management end responds to the request and sends the collected data to the laboratory maintenance management system. Then, the experimental equipment determination unit 10 parses the received data and extracts useful information.

[0051] Collect the list of experimental equipment used in the laboratory: Analyze the data structure obtained from the laboratory management end, determine the location of the experimental equipment list, and then extract the list of experimental equipment used in the laboratory from the obtained data based on the data structure;

[0052] Combine network big data to extract parameter data for each experimental equipment: clarify the type of experimental equipment parameters that need to be extracted, use network search engines or professional databases to search according to the equipment names in the experimental equipment list, obtain relevant network big data, filter the searched network big data, extract information related to the experimental equipment parameters, and finally integrate the parameter data extracted from the network big data with the data obtained from the laboratory management end to form complete experimental equipment parameter data.

[0053] The experiment feedback unit 20 is used to collect experiment records and monitor the operation data of the experiment equipment, and then collect experiment feedback by combining the experiment records with the operation data, so as to obtain the usage feedback data of each experiment equipment;

[0054] The experiment feedback unit 20 collects the experiment records of the experimenters in real time by monitoring the experimenter record module of the laboratory management end. When the experimenter clocks out of the laboratory, the experiment record collection is initiated to the experimenter, so as to collect the experiment records fed back by the experimenter.

[0055] At the same time, the experiment feedback unit 20 can use the laboratory management terminal to actively initiate the collection of experiment records to the experimenter. The specific steps are as follows:

[0056] Monitoring the experimenter recording module: Monitor the experimenter recording module by real-time data reading, and identify the experimenter's experimental operation by analyzing the data changes in the recording module;

[0057] Collecting records when the experimenter clocks out: Integrate with the laboratory's clock-in system to monitor the experimenter's clock-in status in real time. When the experimenter clocks out of the laboratory, the experiment record collection process is automatically triggered, and then a request for experiment record collection is sent to the experimenter. The experimenter can provide experiment record feedback according to the request through pop-up windows, text messages, or push notifications. The experiment feedback unit 20 receives and stores this feedback information.

[0058] The experimental feedback unit 20 includes an operation status monitoring module and a feedback data integration module;

[0059] The operation status monitoring module is used to divide the experimental equipment into online and offline states. When the experimental equipment is in use, it is considered to be in online state, and the operation data of the experimental equipment in the online state is collected until the experimental equipment enters the offline state, and then the operation data is saved according to the collection period as a label;

[0060] When the experimental equipment is not in use, it is considered to be in offline state. The specific steps are as follows:

[0061] Determine the device status judgment standard: Use the device power on or the sensor detecting that the device is running as the device usage feature. If no device usage feature is detected, the device is considered to be offline.

[0062] Monitor device status: Continuously monitor the device status signal through sensors, monitoring systems or software interfaces connected to the device, and determine in real time whether the device is online or offline based on the status judgment criteria;

[0063] Online status data collection: When the device is judged to be in online status, the operation data collection program is started to continuously collect the operation data of the device, including but not limited to the operation parameters, performance indicators, usage time, etc. of the device, and the start and end time of data collection are recorded at the same time;

[0064] Offline data preservation: When the device changes from online to offline, stop running data collection, determine the collection period based on the start and end time of the collection, and then save the running data to the database using the collection period as a label.

[0065] The feedback data integration module is used to perform experimental equipment usage detection based on the experimental records fed back by the experimenters, obtain the corresponding experimental equipment and operation records in the experimental records, and extract the operation data saved in the corresponding period of the experimental records, and then combine the operation data corresponding to each experimental equipment with the operation records as the usage feedback data. The specific steps are as follows:

[0066] Receive experimental records: perform text analysis or data parsing on the experimental records, identify the names or numbers of the experimental equipment involved, and organize and classify the extracted experimental equipment information;

[0067] Obtain operation records: Further analyze the experimental records to extract the specific operation steps and process descriptions of the experimenters during the experiment. Natural language processing technology can be used to extract keywords from the operation records to better understand the experimental operations.

[0068] Determine the corresponding time period: According to the time information in the experimental record, determine the time period of the experiment, and find the experimental equipment operation data saved in this time period;

[0069] Extract operation data: Filter the experimental equipment operation data corresponding to the experimental records from the database according to the time period;

[0070] Integrate usage feedback data: By associating and integrating the operating data corresponding to each experimental device with the operation records, a structured data format containing experimental device information, operation records and operating data can be created as usage feedback data.

[0071] The experimental equipment model setting unit 30 is used to establish an experimental equipment model for each experimental equipment, and when the experimental equipment is put into use for the first time, the obtained usage feedback data is subjected to process detection, and the usage feedback data that passes the process detection is combined with parameter data to initialize the experimental equipment model;

[0072] The experimental equipment model setting unit 30 includes a model building module and an initialization setting module;

[0073] The model building module is used to build an experimental equipment model for each experimental equipment according to parameter data;

[0074] The initialization setting module is used to perform simulation precondition detection and analysis on the experimental equipment, so as to obtain the preconditions for the simulation of the experimental equipment. After that, when the experimental equipment is put into use for the first time, the feedback data fed back by the experimenter is combined with the preconditions for process detection. When the feedback data meets the preconditions, the experimental equipment model is initialized according to the feedback data. On the contrary, when the feedback data does not meet the preconditions, the missing preconditions are collected and supplemented from the experimenter. The specific steps are as follows:

[0075] Establishing experimental equipment model based on parameter data: Using modeling tools or programming languages, mathematical models or simulation models of experimental equipment are constructed based on parameter data. The model can describe the behavior, performance and characteristics of the equipment.

[0076] Simulation precondition detection and analysis: Determine the preconditions required for the normal operation of the experimental equipment, such as the initial state of the equipment, environmental requirements, input parameter range, etc., and detect and analyze these preconditions by simulating the operating environment and operation process of the experimental equipment. Numerical simulation, simulation software or theoretical calculation methods can be used to evaluate whether the preconditions are met;

[0077] Process detection when the experimental equipment is put into use for the first time: When the experimental equipment is put into use for the first time, the feedback data from the experimental personnel is collected, including the actual operation process of the equipment, operation results, problems encountered, etc., and then the feedback data is compared with the preconditions to conduct process detection to check whether the feedback data meets the requirements of the preconditions;

[0078] Initialization setting or collection supplement: If the feedback data used meets the preconditions, the experimental equipment model is initialized based on these data, and the actual usage is reflected in the model, so that the model can more accurately reflect the actual status of the equipment;

[0079] If the feedback data does not meet the preconditions, analyze the missing preconditions. Collect and supplement the missing information from the experimenters. The required precondition information can be obtained through questionnaires, on-site observations, or communication with the experimenters. The formula is as follows:

[0080]

[0081] Among them, F is the result of using feedback data to meet the preconditions, P is the precondition set, and D is the feedback data set used. Indicates that the feedback data set is completely contained in the precondition set, that is, the feedback data meets all preconditions. Indicates that the usage feedback data set is not completely included in the precondition set, that is, the usage feedback data does not meet the precondition.

[0082] The experimental equipment maintenance unit 40 is used to perform maintenance analysis on the experimental equipment model, thereby setting the maintenance node of the experimental equipment model, and then simulate the use and update of the experimental equipment model according to the use feedback data obtained by the experimental feedback unit 20, and at the same time, perform qualified analysis on the experimental equipment model in combination with the maintenance node, and mark the experimental equipment for maintenance according to the analysis results;

[0083] The experimental equipment maintenance unit 40 includes a maintenance node setting module and a maintenance detection module;

[0084] The maintenance node setting module is used to perform maintenance analysis based on the experimental equipment model after initialization setting, and to set maintenance nodes for the experimental equipment model. The specific steps are as follows:

[0085] Collecting experimental equipment model data after initialization: obtaining various parameters and performance index data of the experimental equipment model after initialization;

[0086] Determine maintenance indicators: Determine key indicators used to measure the maintenance needs of experimental equipment, such as equipment failure rate, performance degradation, component life, etc. These indicators can be determined based on the equipment manufacturer's recommendations, industry standards, or previous maintenance experience;

[0087] Analyze equipment model data: Analyze the collected experimental equipment model data to evaluate the current operating status of the equipment and potential maintenance needs;

[0088] Setting maintenance nodes: According to the maintenance indicators and equipment model data analysis results, set the maintenance nodes of the experimental equipment. The formula is as follows:

[0089]

[0090] Among them, M is the setting result of the maintenance node, I is the maintenance indicator set, and D is the equipment model data set;

[0091] For each maintenance index i∈I, define a judgment function f i (D), used to determine whether the equipment model data meets the maintenance index;

[0092] As long as one maintenance indicator is not met, the maintenance node is set as requiring maintenance.

[0093] The maintenance detection module is used to simulate the use of the operation records combined with the experimental equipment model, and update the experimental equipment model according to the simulated use data. Then, the updated experimental equipment model is combined with the maintenance node for qualification analysis. When the experimental equipment model meets the maintenance node, the experimental equipment is marked as requiring maintenance on the laboratory management end. Conversely, when the experimental equipment model does not meet the maintenance node, it continues to be monitored. The specific steps are as follows:

[0094] Combine operation records for simulated use: obtain the operation records of the experimental equipment, including operation steps, parameter settings, usage time and other information, and then input these operation records into the experimental equipment model to simulate the operating status of the equipment under actual use. Simulation software or mathematical models can be used for simulation;

[0095] Data update: According to the results of the simulation, collect the data generated during the simulation, such as changes in equipment performance indicators, component wear, etc., and update these data to the experimental equipment model so that the model can more accurately reflect the actual status of the equipment;

[0096] Perform qualification analysis in conjunction with maintenance nodes: obtain the set conditions of the maintenance node, compare the updated experimental equipment model with the maintenance node, and determine whether the equipment meets the requirements of the maintenance node;

[0097] Mark or continue monitoring: If the experimental equipment model meets the maintenance node, the experimental equipment is marked as requiring maintenance on the laboratory management end, which can be marked by sending notifications, changing the equipment status mark, etc.

[0098] If the experimental equipment model does not meet the maintenance node, continue to monitor the equipment and repeat the above steps regularly to ensure the normal operation of the equipment. The formula is as follows:

[0099] Simulation use:

[0100] M ′ =simulate(M,O)

[0101] Data update:

[0102] U=update(M ′ ,data)

[0103] Qualification Analysis:

[0104]

[0105] Among them, M is the experimental equipment model, O is the operation record, U is the updated model, N is the maintenance node, S is the equipment status that needs maintenance ("1") and continues monitoring ("0"), and simulate is the simulation function. The operation record and the model are combined for simulation to obtain the simulated model M. ′ , update is the update function, which updates the data generated by the simulation to the model to obtain the updated model U. If the updated model meets the maintenance node N, the equipment status is maintenance required 1, otherwise it is continued monitoring 0.

[0106] The model maintenance and update unit 50 is used to monitor the experimental equipment marked by the experimental equipment maintenance unit 40, and notify the experimental equipment management end to perform maintenance. At the same time, it collects maintenance feedback for the experimental equipment after maintenance, and sends the maintenance data to the experimental equipment model setting unit 30 to complete the maintenance and update of the experimental equipment model initialization.

[0107] The model maintenance and updating unit 50 sends the maintenance data to the experimental equipment model setting unit 30, and replaces the feedback data, thereby completing the initialization update of the experimental equipment model through the maintenance data. The specific steps are as follows:

[0108] Maintenance feedback collection: After the equipment maintenance is completed, the maintenance feedback of the maintained experimental equipment is collected. The collected feedback information should include the maintenance content, parts used, maintenance time, current status of the equipment, etc.

[0109] Replace usage feedback data: Use maintenance feedback data as new feedback information to replace previous usage feedback data. This ensures that the experimental equipment model is updated based on the latest equipment status.

[0110] Complete initialization update: According to the parameters and status of the equipment after maintenance, adjust the relevant parameters and variables in the model for initialization update to ensure that the model can accurately reflect the current performance and status of the equipment, providing a more accurate basis for subsequent equipment monitoring and maintenance.

[0111] The above shows and describes the basic principles, main features and advantages of the present invention. Those skilled in the art should understand that the present invention is not limited by the above embodiments. The above embodiments and descriptions are only preferred examples of the present invention and are not intended to limit 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. The scope of protection of the present invention is defined by the attached claims and their equivalents.

Claims

1. A laboratory maintenance management system, characterized in that: It includes an experimental equipment determination unit (10), an experimental feedback unit (20), an experimental equipment model setting unit (30), an experimental equipment maintenance unit (40) and a model maintenance and updating unit (50); The experimental equipment determination unit (10) is used to collect a list of experimental equipment in the laboratory, and then obtain parameter data of each experimental equipment according to the equipment list; The experimental feedback unit (20) is used to collect experimental records and monitor the operating data of the experimental equipment, and then collect experimental feedback by combining the experimental records with the operating data, so as to obtain the usage feedback data of each experimental equipment; The experimental equipment model setting unit (30) is used to establish an experimental equipment model for each experimental equipment, and when the experimental equipment is put into use for the first time, a process detection is performed on the usage feedback data obtained, and the usage feedback data detected through the process is combined with parameter data to initialize the experimental equipment model; The experimental equipment maintenance unit (40) is used to perform maintenance analysis on the experimental equipment model, thereby setting the maintenance node of the experimental equipment model, and then simulate the use and update of the experimental equipment model according to the use feedback data obtained by the experimental feedback unit (20), and at the same time, perform qualification analysis on the experimental equipment model in combination with the maintenance node, and mark the experimental equipment for maintenance according to the analysis result; The model maintenance and updating unit (50) is used to monitor the experimental equipment marked by the experimental equipment maintenance unit (40), and notify the experimental equipment management end to perform maintenance, and at the same time collect maintenance feedback for the experimental equipment after maintenance, and send the maintenance data to the experimental equipment model setting unit (30), thereby completing the maintenance and updating of the experimental equipment model initialization.

2. A laboratory maintenance management system according to claim 1, characterized in that: The experimental equipment determination unit (10) establishes a data transmission channel with the laboratory management end to obtain data collected by the laboratory management end, then collects a list of experimental equipment used in the laboratory from the laboratory management end, and extracts parameter data for each experimental equipment based on the experimental equipment list combined with network big data.

3. A laboratory maintenance management system according to claim 1, characterized in that: The experiment feedback unit (20) collects real-time experiment records of the experimenters by monitoring the experimenter record module of the laboratory management end. When the experimenter clocks out of the laboratory, the experiment record collection is initiated to the experimenter, thereby collecting the experiment records fed back by the experimenter; At the same time, the experiment feedback unit (20) can use the laboratory management terminal to actively initiate the collection of experiment records to the experimenters.

4. A laboratory maintenance management system according to claim 1, characterized in that: The experimental feedback unit (20) comprises an operation status monitoring module and a feedback data integration module; The operation status monitoring module is used to divide the experimental equipment into online and offline states. When the experimental equipment is in use, the experimental equipment is considered to be in online state, and operation data of the experimental equipment in the online state is collected until the experimental equipment enters the offline state, and then the operation data is saved according to the collection period as a label; When the experimental equipment is not in use, it is considered to be in an offline state; The feedback data integration module is used to perform experimental equipment usage detection based on the experimental records feedback by the experimenters, obtain the corresponding experimental equipment and operation records in the experimental records, and extract the operation data saved in the corresponding period of the experimental records, and then combine the operation data corresponding to each experimental equipment with the operation records as usage feedback data.

5. A laboratory maintenance management system according to claim 1, characterized in that: The experimental equipment model setting unit (30) includes a model building module and an initialization setting module; The model building module is used to build an experimental equipment model for each experimental equipment according to parameter data; The initialization setting module is used to perform simulation precondition detection and analysis on the experimental equipment, so as to obtain the preconditions of the experimental equipment simulation. Later, when the experimental equipment is put into use for the first time, the usage feedback data fed back by the experimenter is combined with the preconditions to perform process detection. When the usage feedback data meets the preconditions, the experimental equipment model is initialized and set according to the usage feedback data. Conversely, when the usage feedback data does not meet the preconditions, the experimenter is asked to collect and supplement the missing preconditions.

6. A laboratory maintenance management system according to claim 5, characterized in that: The formula for the initialization setting module is as follows: Among them, F is the result of using feedback data to meet the preconditions, P is the precondition set, and D is the feedback data set used. Indicates that the feedback data set is completely contained in the precondition set. Indicates that the feedback data set is not completely contained in the precondition set.

7. A laboratory maintenance management system according to claim 1, characterized in that: The experimental equipment maintenance unit (40) includes a maintenance node setting module and a maintenance detection module; The maintenance node setting module is used to perform maintenance analysis according to the experimental equipment model after initialization setting, and to set maintenance nodes for the experimental equipment model; The maintenance detection module is used to simulate the use of operation records in conjunction with the experimental equipment model, and at the same time update the data of the experimental equipment model based on the simulated usage data, and then combine the updated experimental equipment model with the maintenance node for qualification analysis. When the experimental equipment model meets the maintenance node, the experimental equipment is marked as requiring maintenance on the laboratory management end. Conversely, when the experimental equipment model does not meet the maintenance node, monitoring continues.

8. A laboratory maintenance management system according to claim 7, characterized in that: The formulas of the maintenance node setting module and the maintenance detection module are as follows: Among them, M is the setting result of the maintenance node, I is the maintenance indicator set, and D is the equipment model data set; Simulation use: M ′ =simulate(M,O) Data update: U=update(M ′ ,data) Qualification Analysis: Among them, M is the experimental equipment model, O is the operation record, U is the updated model, N is the maintenance node, S is the equipment status, simulate is the simulation function, and M ′ is the model after simulation, and update is the update function.

9. A laboratory maintenance management system according to claim 1, characterized in that: The model maintenance and updating unit (50) sends the maintenance data to the experimental equipment model setting unit (30) and replaces the feedback data, thereby completing the initialization update of the experimental equipment model through the maintenance data.

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