An artificial intelligence-based laboratory environment adaptive adjustment system and method

Abstract

The present invention discloses a laboratory environment adaptive adjustment system and method based on artificial intelligence, belonging to the field of artificial intelligence technology. The present invention monitors the environmental state of the laboratory, generates an environmental characteristic parameter set by detecting real-time environmental data in the laboratory; processes the real-time environmental characteristic parameters in the laboratory, predicts the environmental characteristic parameter values, analyzes the environmental state in the laboratory based on the environmental characteristic parameter prediction values, and judges whether there is an adjustment demand for the environmental state in the laboratory; analyzes the environmental adjustment demand in the laboratory, establishes a connection with laboratory-related equipment based on a communication protocol, formats the adjustment instructions and sends them to laboratory-related equipment, and controls the laboratory-related equipment to adjust the environment in the laboratory. By real-time monitoring of the environmental changes in the laboratory, the need for manual troubleshooting of interference items is reduced, the efficiency of laboratory management is improved, and the accuracy and reliability of the experiment are ensured.

Description

Technical Field

[0001] The present invention relates to the field of artificial intelligence technology, and in particular to an artificial intelligence-based laboratory environment adaptive adjustment system and method. Background Art

[0002] In a laboratory environment, electromagnetic interference can have a certain negative impact on electronic equipment and experimental results. At the same time, many experimental equipment in the laboratory are very sensitive to electromagnetic interference, such as precision instruments, electronic measurement equipment, and communication equipment. Electromagnetic interference may cause these devices to work abnormally and may also affect the stability of laboratory data transmission.

[0003] Electronic devices generate electromagnetic waves during operation, which may interfere with the operation of other sensitive equipment, causing errors in experimental data or even damage to equipment. In addition, for laboratories without electromagnetic shielding environments, external electromagnetic waves will also enter the laboratory, affecting the accuracy and reliability of the experiment.

[0004] In order to ensure the stability of the laboratory environment and the accuracy of the experimental results, most laboratories currently use equipment with strong anti-interference capabilities and conduct regular electromagnetic environment detection to solve electromagnetic interference problems to reduce the impact of electromagnetic interference. However, the source of electromagnetic interference may change at any time, and regular electromagnetic environment detection cannot detect electromagnetic environment problems in a timely manner; some high-precision experimental equipment requires specially customized anti-interference versions, and at the same time, the requirements for the electromagnetic environment during operation are higher, and the operating time may be longer. Without a stable electromagnetic environment guarantee, the experimental progress of researchers may be seriously affected; and the construction and maintenance of electromagnetic shielding rooms or shielding facilities require special space and resources, which limits the flexibility of researchers in using laboratory space. Summary of the invention

[0005] The purpose of the present invention is to provide a laboratory environment adaptive adjustment system and method based on artificial intelligence to solve the problems raised in the above background technology.

[0006] In order to solve the above technical problems, the present invention provides the following technical solutions: a method for adaptively adjusting a laboratory environment based on artificial intelligence, comprising the following steps:

[0007] Step S1: Acquire laboratory-related data, detect real-time environmental data in the laboratory, process real-time environmental characteristic parameters in the laboratory, and generate an environmental characteristic parameter set;

[0008] Step S2: construct an environmental characteristic parameter prediction model, predict the development trend of the environmental characteristic parameters in the laboratory according to the environmental characteristic parameter set, and output the predicted value of the environmental characteristic parameters in the laboratory;

[0009] Step S3: Analyze the environmental status in the laboratory to determine whether there is a need to adjust the environmental status in the laboratory. If there is a need to adjust the environmental status in the laboratory, execute step S4;

[0010] Step S4: Analyze the environmental adjustment requirements in the laboratory, generate a data set to be adjusted, establish a connection with laboratory-related equipment based on a communication protocol, and format and encode the adjustment instructions before sending them to laboratory-related equipment;

[0011] Step S5: After receiving the adjustment instruction, the laboratory-related equipment responds and returns confirmation information and execution status.

[0012] Furthermore, the laboratory-related data includes laboratory layout data and laboratory equipment data; the real-time environmental data in the laboratory includes equipment operation data and environmental detection data; the equipment operation data includes equipment status information, equipment parameters and maintenance records;

[0013] The environmental detection data is collected by an environmental detection device, which includes an electromagnetic field probe and a spectrum analyzer; the collected data is preprocessed, including removing noise, filtering interference signals and normalizing data, and the processed data is recorded to generate an environmental characteristic parameter set;

[0014] The environmental characteristic parameter set is denoted as EC i ={c1|p1,c2|p2,...,c n |p n}, where EC i represents the set of environmental characteristic parameters generated corresponding to the i-th time node, i is the time node code, i∈[1,N], N represents the total number of time node codes; c1, c2, ..., c n p1, p2, ..., p2 represent the first environmental characteristic parameter values ​​collected and processed by the 1st, 2nd, ..., nth environmental detection devices, respectively, and n represents the number of the first environmental characteristic parameter values ​​collected and processed by the environmental detection devices; p1, p2, ..., p n represent the second environmental characteristic parameter values ​​collected and processed by the 1st, 2nd, ..., nth environmental detection devices, respectively, c n |p n Represents the value of the first environmental characteristic parameter c at the i-th time node n And the corresponding second environmental characteristic parameter value p n .

[0015] Furthermore, in step S2, the following steps are specifically included:

[0016] S2-1: Construct an environmental characteristic parameter prediction model. The specific calculation formula is as follows:

[0017]

[0018] Among them, α∈[1,n], c α (N+k) represents the predicted value of the αth first environmental characteristic parameter in the environmental characteristic parameter set at the N+kth time node, and k is the number of prediction steps; c α (k) represents the first value of the accumulated sequence generated after k-time accumulation of the data sequence consisting of the αth first environmental characteristic parameter values ​​in the environmental characteristic parameter set corresponding to N time nodes; Indicates the αth first environmental characteristic parameter value in the environmental characteristic parameter set corresponding to the first time node; represents the average value of the αth first environmental characteristic parameter value in the environmental characteristic parameter set corresponding to N time nodes; β i is the grey relational degree; represents the αth first environmental characteristic parameter value in the environmental characteristic parameter set corresponding to the jth time node; represents the αth first environmental characteristic parameter value in the environmental characteristic parameter set corresponding to the j+1th time node; λ is the gray coefficient, which is selected by relevant personnel through the least squares method during model training;

[0019] S2-2: Input the first environmental characteristic parameter value in the environmental characteristic parameter set into the environmental characteristic parameter prediction model, and output the predicted value of the first environmental characteristic parameter in the environmental characteristic parameter set at the N+kth time node in the laboratory.

[0020] Furthermore, in the step S3, the following steps are specifically included:

[0021] S3-1: Analyze the state stability of the laboratory at the N+k'th time node, and calculate the state stability Z of the laboratory according to the following formula:

[0022]

[0023] Among them, c α (N+k′) represents the first environmental characteristic parameter value in the environmental characteristic parameter set at the N+k′th time node; ε1 and ε2 are stability coefficients, which are preset by relevant personnel; max(p α ) represents the maximum value of the αth second environmental characteristic parameter value in the environmental characteristic parameter set corresponding to the N+k' time node, min(p α ) represents the minimum value of the αth second environmental characteristic parameter value in the environmental characteristic parameter set corresponding to the N+k' time node; represents the average value of the αth second environmental characteristic parameter value in the environmental characteristic parameter set corresponding to the N+k' time nodes; k'<k;

[0024] S3-2: Determine whether there is any need to adjust the environmental state in the laboratory based on the laboratory's state stability. When the laboratory's state stability does not exceed the stability threshold ω preset by relevant personnel, determine that there is no need to adjust the environmental state in the current laboratory; when the laboratory's state stability exceeds the stability threshold ω preset by relevant personnel, determine that there is a need to adjust the environmental state in the current laboratory, and execute step S4.

[0025] Furthermore, in step S4, analyzing the environmental adjustment requirements in the laboratory to generate a data set to be adjusted includes:

[0026] S4-1: Set a discrimination threshold u based on the laboratory equipment data to determine whether the difference is greater than the normal range; set the initial search range to [1, N+k'] to determine the range of the mutation point;

[0027] S4-2: Calculate the difference R according to the following formula α :

[0028]

[0029] in, represents the αth first environmental characteristic parameter value in the environmental characteristic parameter set corresponding to the i-th time node; when the difference R α When it is greater than the discrimination threshold u, the first environmental characteristic parameter value collected and processed by the αth environmental detection device is determined to be the data to be adjusted;

[0030] S4-3: extracting the data to be adjusted based on step S4-2, marking the environmental detection equipment corresponding to the data to be adjusted, establishing a connection with the laboratory equipment corresponding to the environmental detection equipment based on the communication protocol, and formatting and encoding the adjustment instruction and sending it to the laboratory equipment;

[0031] In step S5, after receiving the adjustment instruction, the laboratory-related equipment responds, controls the laboratory-related equipment, returns confirmation information and execution status, and records the entire process of the equipment executing the adjustment instruction.

[0032] An artificial intelligence-based laboratory environment adaptive adjustment system, comprising: a laboratory environment monitoring module, an environmental data analysis module and a central control module;

[0033] The laboratory environment monitoring module is used to monitor the environmental status of the laboratory and generate an environmental characteristic parameter set by detecting real-time environmental data in the laboratory;

[0034] The environmental data analysis module is used to process the real-time environmental characteristic parameters in the laboratory, predict the values ​​of the environmental characteristic parameters, analyze the environmental status in the laboratory based on the predicted values ​​of the environmental characteristic parameters, and determine whether there is a need to adjust the environmental status in the laboratory;

[0035] The central control module is used to analyze the environmental adjustment requirements in the laboratory, establish a connection with laboratory-related equipment based on a communication protocol, format and encode the adjustment instructions and send them to the laboratory-related equipment, and control the laboratory-related equipment to adjust the environment in the laboratory.

[0036] Further, the laboratory environment monitoring module includes an equipment data acquisition unit and a laboratory data detection unit;

[0037] The equipment data acquisition unit is used to monitor the operating status of the equipment in the laboratory and obtain the operating status data of each equipment in the laboratory;

[0038] The laboratory data detection unit is used to detect the environmental status in the laboratory and obtain the electromagnetic environment data in the laboratory.

[0039] Further, the environmental data analysis module includes an environmental change analysis unit, a laboratory status analysis unit and an environmental status determination unit;

[0040] The environmental change analysis unit is used to analyze the changes in environmental data in the laboratory and predict the changes in environmental characteristic parameter values ​​according to the environmental characteristic parameter set;

[0041] The laboratory state analysis unit is used to analyze the state stability of the laboratory and output the state stability of the laboratory through the environmental state simulator;

[0042] The environmental state determination unit is used to determine the environmental state requirements of the laboratory according to the state stability output by the environmental detection model, and if it is determined that there is a need to adjust the environmental state in the laboratory, a signal is transmitted to the central control module.

[0043] Furthermore, the central control module includes an intelligent optimization unit and an adaptive adjustment unit;

[0044] The intelligent optimization unit is used to respond to the adjustment requirements of the laboratory environment according to the output data of the environmental data analysis module, generate adjustment instructions, establish a connection with laboratory-related equipment based on the communication protocol, and format and encode the adjustment instructions before sending them to the laboratory-related equipment;

[0045] The adaptive adjustment unit is used to control laboratory-related equipment, record the entire process of the equipment executing adjustment instructions, detect the environmental characteristic parameter values ​​in the laboratory, check parameter deviations through the environmental data analysis module, and feed back equipment adjustment data.

[0046] A laboratory environment adjustment control device, the control device implements the steps of the laboratory environment adaptive adjustment method based on artificial intelligence.

[0047] Compared with the prior art, the beneficial effects achieved by the present invention are:

[0048] By monitoring the electromagnetic environment in the laboratory in real time, changes in the electromagnetic environment in the laboratory can be discovered more promptly, helping experimenters to eliminate environmental anomalies, avoid equipment damage, and ensure the accuracy and reliability of the experiment.

[0049] Through intelligent prediction models, experimenters can understand the changing trends of environmental conditions in the laboratory, reduce the risk of environmental abnormalities, and improve the efficiency of laboratory management.

[0050] By analyzing the environmental adjustment needs within the laboratory, the need for manual troubleshooting of interference items is reduced. The laboratory can locate the interference source based on the mutation point, reduce manual troubleshooting time, and improve the efficiency of environmental maintenance within the laboratory.

[0051] By analyzing the stability of the laboratory's state, we can determine whether the laboratory's current state can meet the experimental needs. By adaptively adjusting the laboratory's environment, we can help the laboratory implement long-term experimental plans. BRIEF DESCRIPTION OF THE DRAWINGS

[0052] The accompanying drawings are used to provide a further understanding of the present invention and constitute a part of the specification. Together with the embodiments of the present invention, they are used to explain the present invention and do not constitute a limitation of the present invention. In the accompanying drawings:

[0053] Figure 1 It is a structural schematic diagram of a laboratory environment adaptive adjustment system based on artificial intelligence of the present invention;

[0054] Figure 2 It is a flow chart of a method for adaptively adjusting a laboratory environment based on artificial intelligence of the present invention. DETAILED DESCRIPTION

[0055] 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.

[0056] See also Figure 1 , in the first embodiment: a laboratory environment adaptive adjustment system based on artificial intelligence is provided, comprising: a laboratory environment monitoring module, an environment data analysis module and a central control module;

[0057] The laboratory environment monitoring module is used to monitor the environmental status of the laboratory and generate an environmental characteristic parameter set by detecting real-time environmental data in the laboratory; it specifically includes an equipment data acquisition unit and a laboratory data detection unit;

[0058] Among them, the equipment data acquisition unit is used to monitor the operating status of the equipment in the laboratory and obtain the operating status data of each device in the laboratory; the laboratory data detection unit is used to detect the environmental status in the laboratory and obtain the electromagnetic environment data in the laboratory.

[0059] The environmental data analysis module is used to process the real-time environmental characteristic parameters in the laboratory, predict the values ​​of the environmental characteristic parameters, analyze the environmental status in the laboratory based on the predicted values ​​of the environmental characteristic parameters, and determine whether there is a need to adjust the environmental status in the laboratory; specifically, it includes an environmental change analysis unit, a laboratory status analysis unit, and an environmental status determination unit;

[0060] The environmental change analysis unit is used to analyze the changes in environmental data in the laboratory and predict the changes in environmental characteristic parameter values ​​through the environmental characteristic parameter prediction model;

[0061] Among them, the specific calculation formula of the environmental characteristic parameter prediction model is as follows:

[0062]

[0063] Among them, α∈[1,n], c α (N+k) represents the predicted value of the αth first environmental characteristic parameter in the environmental characteristic parameter set at the N+kth time node, and k is the number of prediction steps; c α (k) represents the first value of the accumulated sequence generated after k-time accumulation of the data sequence consisting of the αth first environmental characteristic parameter values ​​in the environmental characteristic parameter set corresponding to N time nodes; Indicates the αth first environmental characteristic parameter value in the environmental characteristic parameter set corresponding to the first time node; represents the average value of the αth first environmental characteristic parameter value in the environmental characteristic parameter set corresponding to N time nodes; β i is the grey relational degree; represents the αth first environmental characteristic parameter value in the environmental characteristic parameter set corresponding to the jth time node; represents the αth first environmental characteristic parameter value in the environmental characteristic parameter set corresponding to the j+1th time node; λ is the gray coefficient, which is selected by relevant personnel through the least squares method during model training;

[0064] The laboratory state analysis unit is used to analyze the state stability of the laboratory. Specifically, the state stability Z of the laboratory at the N+k'th time node can be calculated according to the following formula:

[0065]

[0066] Among them, c α (N+k′) represents the first environmental characteristic parameter value in the environmental characteristic parameter set at the N+k′th time node; ε1 and ε2 are stability coefficients, which are preset by relevant personnel; max(p α ) represents the maximum value of the αth second environmental characteristic parameter value in the environmental characteristic parameter set corresponding to the N+k' time node, min(p α ) represents the minimum value of the αth second environmental characteristic parameter value in the environmental characteristic parameter set corresponding to the N+k' time node; represents the average value of the αth second environmental characteristic parameter value in the environmental characteristic parameter set corresponding to the N+k' time nodes;

[0067] The environmental state determination unit is used to determine the environmental state requirements of the laboratory according to the state stability output by the environmental detection model. If it is determined that there is a need for adjustment of the environmental state in the laboratory, the signal is transmitted to the central control module.

[0068] The central control module is used to analyze the environmental adjustment requirements in the laboratory, establish a connection with laboratory-related equipment based on the communication protocol, encode the adjustment instructions in a format and send them to the laboratory-related equipment, and control the laboratory-related equipment to adjust the environment in the laboratory; specifically, it includes an intelligent optimization unit and an adaptive adjustment unit;

[0069] The intelligent optimization unit is used to respond to the adjustment needs of the laboratory environment according to the output data of the environmental data analysis module, generate adjustment instructions according to the difference value of the mutation point, establish a connection with the laboratory-related equipment based on the communication protocol, and format the adjustment instructions and send them to the laboratory-related equipment; the adaptive adjustment unit is used to control the laboratory-related equipment, record the entire process of the equipment executing the adjustment instructions, detect the environmental characteristic parameter values ​​in the laboratory, check the parameter deviation through the environmental data analysis module, and feedback the equipment adjustment data.

[0070] See also Figure 2 In the second embodiment, a method for adaptively adjusting a laboratory environment based on artificial intelligence is provided, comprising the following steps:

[0071] Step S1: Acquire laboratory-related data, including laboratory layout data and laboratory equipment data; detect real-time environmental data in the laboratory, including equipment operation data and environmental detection data; among which, equipment operation data includes equipment status information, equipment parameters and maintenance records; such as power-on, standby, operation, fault and other status information, temperature setting, speed, power and other equipment parameters; collect environmental detection data through electromagnetic field probes and spectrum analyzers, pre-process the collected data, including removing noise, filtering interference signals and normalizing data, record the processed data, and generate an environmental characteristic parameter set, recorded as EC i ={c1|p1,c2|p2,...,c n |p n}, where EC i represents the set of environmental characteristic parameters generated corresponding to the i-th time node, i is the time node code, i∈[1,N], N represents the total number of time node codes; c1, c2, ..., c n p1, p2, ..., p2 represent the first environmental characteristic parameter values ​​collected and processed by the 1st, 2nd, ..., nth environmental detection devices, respectively, and n represents the number of the first environmental characteristic parameter values ​​collected and processed by the environmental detection devices; p1, p2, ..., p n represent the second environmental characteristic parameter values ​​collected and processed by the 1st, 2nd, ..., nth environmental detection devices, respectively, c n |p n Represents the value of the first environmental characteristic parameter c at the i-th time node n And the corresponding second environmental characteristic parameter value p n .

[0072] The first environmental characteristic parameter value and the second environmental characteristic parameter value are respectively environmental characteristic parameter values ​​collected and processed by an electromagnetic field probe and a spectrum analyzer;

[0073] Step S2: construct an environmental characteristic parameter prediction model, predict the development trend of the environmental characteristic parameters in the laboratory according to the environmental characteristic parameter set, and output the predicted value of the environmental characteristic parameters in the laboratory;

[0074] S2-1: Construct an environmental characteristic parameter prediction model. The specific calculation formula is as follows:

[0075]

[0076] Among them, α∈[1,n], c α (N+k) represents the predicted value of the αth first environmental characteristic parameter in the environmental characteristic parameter set at the N+kth time node, and k is the number of prediction steps; c α (k) represents the first value of the accumulated sequence generated after k-time accumulation of the data sequence consisting of the αth first environmental characteristic parameter values ​​in the environmental characteristic parameter set corresponding to N time nodes; Indicates the αth first environmental characteristic parameter value in the environmental characteristic parameter set corresponding to the first time node; represents the average value of the αth first environmental characteristic parameter value in the environmental characteristic parameter set corresponding to N time nodes; β i is the grey relational degree; represents the αth first environmental characteristic parameter value in the environmental characteristic parameter set corresponding to the jth time node; represents the αth first environmental characteristic parameter value in the environmental characteristic parameter set corresponding to the j+1th time node; λ is the gray coefficient, which is selected by relevant personnel through the least squares method during model training; e is the base of the natural logarithm;

[0077] S2-2: Input the first environmental characteristic parameter value in the environmental characteristic parameter set into the environmental characteristic parameter prediction model, and output the predicted value of the first environmental characteristic parameter in the environmental characteristic parameter set at the N+kth time node in the laboratory.

[0078] Step S3: Analyze the environmental status in the laboratory to determine whether there is a need to adjust the environmental status in the laboratory. If there is a need to adjust the environmental status in the laboratory, execute step S4;

[0079] S3-1: Analyze the predicted value of the first environmental characteristic parameter in the environmental characteristic parameter set at the N+kth time node based on the second environmental characteristic parameter value in the environmental characteristic parameter set at the N+kth time node;

[0080] Construct a laboratory environment state simulator, input the predicted value of the first environmental characteristic parameter in step S2 into the environment state simulator, analyze the state stability of the laboratory at the N+k'th time node, and calculate the state stability Z of the laboratory according to the following formula:

[0081]

[0082] Among them, c α (N+k′) represents the first environmental characteristic parameter value in the environmental characteristic parameter set at the N+k′th time node; ε1 and ε2 are stability coefficients, which are preset by relevant personnel; max(p α ) represents the maximum value of the αth second environmental characteristic parameter value in the environmental characteristic parameter set corresponding to the N+k' time node, min(p α ) represents the minimum value of the αth second environmental characteristic parameter value in the environmental characteristic parameter set corresponding to the N+k' time node; represents the average value of the αth second environmental characteristic parameter value in the environmental characteristic parameter set corresponding to the N+k' time nodes;

[0083] S3-2: Determine whether there is any need to adjust the environmental state in the laboratory based on the laboratory's state stability. When the laboratory's state stability does not exceed the stability threshold ω preset by relevant personnel, determine that there is no need to adjust the environmental state in the current laboratory; when the laboratory's state stability exceeds the stability threshold ω preset by relevant personnel, determine that there is a need to adjust the environmental state in the current laboratory, and execute step S4.

[0084] Exemplarily, an electromagnetic field probe is used to collect electromagnetic field strength data at different locations in the laboratory, and a spectrum analyzer is used to collect spectrum characteristic data of the signal in the laboratory; ensuring that the data collection time of the electromagnetic field probe and the spectrum analyzer are synchronized for subsequent analysis and comparison.

[0085] Combine the electromagnetic field probe data with the spectrum analyzer data to analyze the relationship between the electromagnetic field strength and the electromagnetic interference frequency; determine whether the area with higher electromagnetic field strength is related to the electromagnetic interference source.

[0086] Step S4: Analyze the environmental adjustment requirements in the laboratory, generate a data set to be adjusted, establish a connection with laboratory-related equipment based on a communication protocol, and format and encode the adjustment instructions before sending them to laboratory-related equipment;

[0087] S4-1: Set a discrimination threshold u based on the laboratory equipment data to determine whether the difference is greater than the normal range; set the initial search range to [1, N+k'] to determine the range of the mutation point;

[0088] S4-2: Calculate the difference R according to the following formula α :

[0089]

[0090] in, represents the αth first environmental characteristic parameter value in the environmental characteristic parameter set corresponding to the i-th time node; when the difference R α When it is greater than the discrimination threshold u, the first environmental characteristic parameter value collected and processed by the αth environmental detection device is determined to be the data to be adjusted;

[0091] S4-3: extracting the data to be adjusted based on step S4-2, marking the environmental detection equipment corresponding to the data to be adjusted, establishing a connection with the laboratory equipment corresponding to the environmental detection equipment based on the communication protocol, and formatting and encoding the adjustment instruction and sending it to the laboratory equipment;

[0092] It should be noted that the laboratory equipment corresponding to the environment detection equipment in step S4-3 may be the laboratory equipment detected by the electromagnetic field probe.

[0093] Step S5: After receiving the adjustment instruction, the laboratory-related equipment responds, controls the laboratory-related equipment, returns confirmation information and execution status, and records the entire process of the equipment executing the adjustment instruction.

[0094] Exemplarily, the operating state of laboratory equipment that affects the laboratory electromagnetic environment is adjusted; the location of laboratory equipment that affects the laboratory electromagnetic environment is adjusted;

[0095] It should be noted that, in this article, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device.

[0096] Finally, it should be noted that the above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art can still modify the technical solutions described in the aforementioned embodiments or replace some of the technical features therein by equivalents. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. A method for adaptively adjusting laboratory environment based on artificial intelligence, characterized in that: The following steps are involved: Step S1: Acquire laboratory-related data, detect real-time environmental data in the laboratory, process real-time environmental characteristic parameters in the laboratory, and generate an environmental characteristic parameter set; Step S2: construct an environmental characteristic parameter prediction model, predict the development trend of the environmental characteristic parameters in the laboratory according to the environmental characteristic parameter set, and output the predicted value of the environmental characteristic parameters in the laboratory; Step S3: Analyze the environmental status in the laboratory to determine whether there is a need to adjust the environmental status in the laboratory. If there is a need to adjust the environmental status in the laboratory, execute step S4; Step S4: Analyze the environmental adjustment requirements in the laboratory, generate a data set to be adjusted, establish a connection with laboratory-related equipment based on a communication protocol, and format and encode the adjustment instructions before sending them to laboratory-related equipment; Step S5: After receiving the adjustment instruction, the laboratory-related equipment responds and returns confirmation information and execution status; In step S2, specifically The following steps are involved: S2-1: Construct an environmental characteristic parameter prediction model. The specific calculation formula is as follows: Among them, α∈[1,n], c α (N+k) represents the predicted value of the αth first environmental characteristic parameter in the environmental characteristic parameter set at the N+kth time node, and k is the number of prediction steps; c α (k) represents the first value of the accumulated sequence generated after k-time accumulation of the data sequence consisting of the αth first environmental characteristic parameter values ​​in the environmental characteristic parameter set corresponding to N time nodes; Indicates the αth first environmental characteristic parameter value in the environmental characteristic parameter set corresponding to the first time node; represents the average value of the αth first environmental characteristic parameter value in the environmental characteristic parameter set corresponding to N time nodes; β i is the grey relational degree; represents the αth first environmental characteristic parameter value in the environmental characteristic parameter set corresponding to the jth time node; represents the αth first environmental characteristic parameter value in the environmental characteristic parameter set corresponding to the j+1th time node; λ is the gray coefficient; S2-2: Input the first environmental characteristic parameter value in the environmental characteristic parameter set into the environmental characteristic parameter prediction model, and output the predicted value of the first environmental characteristic parameter in the environmental characteristic parameter set at the N+kth time node in the laboratory.

2. The method for adaptively adjusting a laboratory environment based on artificial intelligence according to claim 1, characterized in that: The laboratory-related data includes laboratory layout data and laboratory equipment data; the real-time environmental data in the laboratory includes equipment operation data and environmental detection data; the equipment operation data includes equipment status information, equipment parameters and maintenance records; the environmental detection data is collected by environmental detection equipment, the collected data is preprocessed, the processed data is recorded, and an environmental characteristic parameter set is generated; The environmental characteristic parameter set is denoted as EC i ={c1|p1,c2|p2,...,c n |p n }, where EC i represents the set of environmental characteristic parameters generated corresponding to the i-th time node, i is the time node code, i∈[1,N], N represents the total number of time node codes; c1, c2, ..., c n respectively represent the first environmental characteristic parameter values ​​collected and processed by the 1st, 2nd, ..., nth environmental detection devices, and n represents the number of the first environmental characteristic parameter values ​​collected and processed by the environmental detection devices; p1, p2, ..., p n represent the second environmental characteristic parameter values ​​collected and processed by the 1st, 2nd, ..., nth environmental detection devices, respectively, c n |p n Represents the value of the first environmental characteristic parameter c at the i-th time node n And the corresponding second environmental characteristic parameter value p n .

3. The method for adaptively adjusting a laboratory environment based on artificial intelligence according to claim 1, characterized in that: In the step S3, the following steps are specifically included: S3-1: Analyze the state stability of the laboratory at the N+k'th time node, and calculate the state stability Z of the laboratory according to the following formula: Among them, c α (N+k') represents the first environmental characteristic parameter value in the environmental characteristic parameter set at the N+k'th time node; ε1 and ε2 are stability coefficients, which are preset by relevant personnel; max(p α ) represents the maximum value of the αth second environmental characteristic parameter value in the environmental characteristic parameter set corresponding to the N+k' time node, min(p α ) represents the minimum value of the αth second environmental characteristic parameter value in the environmental characteristic parameter set corresponding to the N+k' time node; represents the average value of the αth second environmental characteristic parameter value in the environmental characteristic parameter set corresponding to the N+k' time nodes; S3-2: Determine whether there is any need to adjust the environmental state in the laboratory based on the laboratory's state stability. When the laboratory's state stability does not exceed the stability threshold ω preset by relevant personnel, determine that there is no need to adjust the environmental state in the current laboratory; when the laboratory's state stability exceeds the stability threshold ω preset by relevant personnel, determine that there is a need to adjust the environmental state in the current laboratory, and execute step S4.

4. The method for adaptively adjusting a laboratory environment based on artificial intelligence according to claim 1, characterized in that: In step S4, analyzing the environmental adjustment requirements in the laboratory to generate a data set to be adjusted includes: S4-1: Set the discrimination threshold u based on the laboratory equipment data; set the initial search range to [1, N+k']; S4-2: Calculate the difference R according to the following formula α : in, represents the αth first environmental characteristic parameter value in the environmental characteristic parameter set corresponding to the i-th time node; when the difference R α When it is greater than the discrimination threshold u, the first environmental characteristic parameter value collected and processed by the αth environmental detection device is determined to be the data to be adjusted; S4-3: extracting the data to be adjusted based on step S4-2, marking the environmental detection equipment corresponding to the data to be adjusted, establishing a connection with the laboratory equipment corresponding to the environmental detection equipment based on the communication protocol, and formatting and encoding the adjustment instruction and sending it to the laboratory equipment; In step S5, after receiving the adjustment instruction, the laboratory-related equipment responds, controls the laboratory-related equipment, returns confirmation information and execution status, and records the entire process of the equipment executing the adjustment instruction.

5. An artificial intelligence-based laboratory environment adaptive adjustment system, which executes an artificial intelligence-based laboratory environment adaptive adjustment method as claimed in any one of claims 1 to 4, characterized in that: include: Laboratory environment monitoring module, environmental data analysis module and central control module; The laboratory environment monitoring module is used to monitor the environmental status of the laboratory and generate an environmental characteristic parameter set by detecting real-time environmental data in the laboratory; The environmental data analysis module is used to process the real-time environmental characteristic parameters in the laboratory, predict the values ​​of the environmental characteristic parameters, analyze the environmental status in the laboratory based on the predicted values ​​of the environmental characteristic parameters, and determine whether there is a need to adjust the environmental status in the laboratory; The central control module is used to analyze the environmental adjustment requirements in the laboratory, establish a connection with laboratory-related equipment based on a communication protocol, format and encode the adjustment instructions and send them to the laboratory-related equipment, and control the laboratory-related equipment to adjust the environment in the laboratory.

6. The laboratory environment adaptive adjustment system based on artificial intelligence according to claim 5 is characterized in that: The laboratory environment monitoring module includes an equipment data acquisition unit and a laboratory data detection unit; The equipment data acquisition unit is used to monitor the operating status of the equipment in the laboratory and obtain the operating status data of each equipment in the laboratory; The laboratory data detection unit is used to detect the environmental status in the laboratory and obtain the electromagnetic environment data in the laboratory.

7. The laboratory environment adaptive adjustment system based on artificial intelligence according to claim 5 is characterized by: The environmental data analysis module includes an environmental change analysis unit, a laboratory status analysis unit and an environmental status determination unit; The environmental change analysis unit is used to analyze the changes in environmental data in the laboratory and predict the changes in environmental characteristic parameter values ​​according to the environmental characteristic parameter set; The laboratory state analysis unit is used to analyze the state stability of the laboratory and output the state stability of the laboratory; The environmental state determination unit is used to determine the environmental state requirements of the laboratory according to the state stability output by the environmental detection model, and if it is determined that there is a need to adjust the environmental state in the laboratory, a signal is transmitted to the central control module.

8. The laboratory environment adaptive adjustment system based on artificial intelligence according to claim 5 is characterized by: The central control module includes an intelligent optimization unit and an adaptive adjustment unit; The intelligent optimization unit is used to respond to the adjustment requirements of the laboratory environment according to the output data of the environmental data analysis module, generate adjustment instructions, establish a connection with laboratory-related equipment based on the communication protocol, and format and encode the adjustment instructions before sending them to the laboratory-related equipment; The adaptive adjustment unit is used to control laboratory-related equipment, record the entire process of the equipment executing adjustment instructions, detect the environmental characteristic parameter values ​​in the laboratory, check parameter deviations through the environmental data analysis module, and feed back equipment adjustment data.

9. A laboratory environment adjustment and control device, characterized in that: The control device implements an artificial intelligence-based adaptive adjustment method for a laboratory environment as described in any one of claims 1 to 4.

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