A laboratory air safety management system based on big data

Abstract

The present invention discloses a laboratory air safety management system based on big data, including an environmental parameter acquisition module, a regional big data sorting and optimization module, an exhaust control management module, an experimental data information input module, a simulation prediction analysis module, a data optimization processing module and an intelligent prediction warning terminal. The present invention analyzes the gas concentration in each area in the laboratory, analyzes the central diffusion area corresponding to each gas type and the spread trajectory of each gas type, can accurately judge the propagation trend of the gas, and frequency-converts and adjusts the laboratory fume hoods in the area according to the propagation trend of the gas, so as to realize adaptive adjustment of the frequency of the laboratory fume hoods according to the different gas concentrations in the area, can reasonably and effectively discharge the harmful gas types diffused in the laboratory in time, improve the utilization of energy, accelerate the discharge of harmful gases from the room, and realize the intelligentization of air safety management.

Description

Technical Field

[0001] The present invention belongs to the technical field of laboratory air management and relates to a laboratory air safety management system based on big data. Background Art

[0002] The chemical laboratory is an important place for providing chemical experimental conditions and conducting scientific research. A large number of instruments and chemical reagents are stored in it. During the relevant experimental operations in the chemical laboratory, toxic, harmful, flammable and explosive gases will be generated. At the same time, since chemical reagents are extremely volatile substances, they will also diffuse into the laboratory during the storage process, causing the laboratory air to be filled with harmful gases. The existing laboratory ventilation devices all ventilate the entire laboratory, and it is impossible to analyze the initial generation location of toxic, harmful or flammable and explosive gases generated during the experiment, and it is impossible to analyze the spread trajectory of the generated gases in the laboratory.

[0003] At present, during the experiment, once harmful gases are generated, the laboratory is ventilated as a whole, which will cause the scope of diffusion of harmful gases to expand, and increase the time to completely exhaust the harmful gases in the laboratory, resulting in low emission efficiency and waste of electricity. For some laboratories, fume hoods are used for exhaust. Since the trajectory of the spread of harmful gases cannot be obtained, the fume hoods in the laboratory cannot be adaptively started and stopped, and the working frequency cannot be controlled. There are problems such as low emission efficiency, long emission time and poor indoor air safety performance, and it is impossible to conduct prior prediction and assessment of the degree of danger of the air in the laboratory before the experimental operation. Summary of the invention

[0004] The purpose of the present invention is to provide a laboratory air safety management system based on big data, which solves the problems existing in the prior art.

[0005] The purpose of the present invention can be achieved through the following technical solutions:

[0006] A laboratory air safety management system based on big data, including an environmental parameter acquisition module, a regional big data sorting and optimization module, and an exhaust control management module;

[0007] The environmental parameter collection module includes a plurality of environmental parameter collection units, which are evenly distributed at various preset positions in the laboratory. The environmental parameter collection units collect the concentration information of various gas types in the area where the environmental parameter collection units are located in real time, and send the concentration information of various gas types in the area collected by each environmental parameter collection unit to the regional big data sorting and optimization module;

[0008] The regional big data sorting and optimization module is used to obtain the concentration of each gas type in the area where each environmental parameter collection unit is located, optimize the concentration of each gas type collected in each area, analyze the central diffusion area corresponding to each gas type, and perform data analysis on the gas concentration of each gas type in each area to obtain the spread trajectory of each gas type;

[0009] The exhaust control management module is used to obtain the central diffusion area corresponding to each gas concentration analyzed by the regional big data sorting and optimization module and the gas diffusion trajectory of the central diffusion area, control the ventilation control unit in the central diffusion area and the area through which the gas diffusion trajectory passes, and at the same time obtain the gas concentration in the central diffusion area and the area through which the gas diffusion trajectory passes, and perform frequency conversion adjustment on the laboratory fume hoods in the area according to the gas concentration.

[0010] Furthermore, the regional big data sorting and optimization module analyzes the concentration of each gas type in each region, including the following steps:

[0011] Step 1: Compare the concentration of each gas type in the area where each environmental parameter collection unit is located with the set concentration threshold of each gas type, and screen out the gas type whose gas concentration is greater than the gas concentration threshold corresponding to the gas type, denoted as Ci j,i=1,2,3,...,n,j=1,2,3,...,m,Ci j is the gas concentration of the jth gas type in the area where the i environmental parameter collection unit is located, n is the total number of areas divided in the laboratory, and m is the number of gas types contained in the harmful gas;

[0012] Step 2: Filter out the gas concentrations of the gas types in each area whose gas concentrations are greater than the gas concentration threshold, perform data differentiation comparison on the gas concentrations corresponding to the gas types in each area, and obtain the area with the largest gas concentration of the same gas type in each area;

[0013] Step 3: The area with the highest gas concentration for the same gas is taken as the central diffusion area of ​​the gas;

[0014] Step 4: Compare the gas concentration in each central diffusion area with the gas concentration in the area where other environmental parameter acquisition units are located, and analyze the spread trajectory of the gas from the central diffusion area.

[0015] Furthermore, a method for analyzing the spreading trajectory of gas in the central diffusion region includes the following steps:

[0016] Step B1, performing location association on the areas where the environmental parameter collection units in the laboratory are located;

[0017] That is, establish the adjacent position relationship of each environmental parameter collection unit, such as Figure 1 As shown, it can be seen that the areas adjacent to each area are numbered for the convenience of displaying the areas.

[0018] Step B2, sequentially extracting the gas concentrations corresponding to the gas types in the area where the environmental parameter acquisition units adjacent to the central diffusion area are located and the gas concentration in the central diffusion area is higher than that in other areas, and screening out the adjacent areas where the gas concentration is greater than the set threshold;

[0019] Step B3, sequentially taking each adjacent area whose gas concentration is greater than the set threshold value screened out in step B2 as the first diffusion area, sequentially extracting the gas concentration corresponding to the gas type in the area where the environmental parameter acquisition unit adjacent to each first diffusion area is located, and screening out the adjacent area whose gas concentration corresponding to the gas type adjacent to each first diffusion area is greater than the set threshold value as the second diffusion area;

[0020] Step B4, screening out adjacent areas adjacent to the second diffusion area where the gas concentration corresponding to the gas type is greater than a set threshold as the third diffusion area, and repeating step 4 until all areas are screened;

[0021] Step B5, taking the central diffusion area, the first diffusion area, the second diffusion area connected to the first diffusion area, and the third diffusion area connected to the second diffusion area as diffusion trajectories in turn, to obtain the diffusion and spread trajectories of each gas type in the laboratory.

[0022] Furthermore, in the process of performing the spreading trajectory analysis for the same gas type, the region position numbers corresponding to the central diffusion region, the first diffusion region, the second diffusion region and the third diffusion region are different.

[0023] Furthermore, the laboratory air safety management system also includes an experimental data information input module, a simulation prediction analysis module, a data optimization processing module and an intelligent prediction warning terminal;

[0024] The experimental data information input module is used to manually input the chemical reagents to be used for the experimental operation in the laboratory, and send the input chemical reagent information to the simulation prediction analysis module;

[0025] The simulation prediction analysis module is used to extract the chemical reagent information input by the laboratory and the gas concentration data in the current indoor air, analyze the harmful gases generated by the chemical reagent information input by the current laboratory and the gas quality of the generated harmful gases through the constructed dangerous reaction model set, and predict the experimental environmental hazard coefficient caused by the harmful gases generated by the chemical reagent reaction input under the gas type concentration in the current indoor air to the air in the laboratory;

[0026] The data optimization processing module is used to obtain the gas quality of the harmful gas predicted by the simulation prediction analysis module and predict the experimental environment hazard coefficient caused by the harmful gas to the air in the laboratory, compare the experimental environment hazard coefficient with the experimental environment hazard coefficient range corresponding to the set different hazard levels one by one, determine the experimental hazard level, and screen out the emergency protection strategy corresponding to the experimental hazard level, and transmit the experimental hazard level and emergency protection strategy to the intelligent early warning display terminal;

[0027] The intelligent prediction and warning terminal is used to display the experimental hazard level corresponding to the air in the laboratory and the emergency protection strategy corresponding to the experimental hazard level.

[0028] Furthermore, the calculation formula of the experimental environment risk factor is:

[0029] e is a natural number, wj1 is the minimum gas mass of the j-th gas type that reaches the condition of poisoning people, wj2 is the minimum gas mass of the j-th gas type that reaches the condition of flammability and explosion, gas mass = molar mass of gas × gas volume ÷ molar volume of gas, Wj is the gas mass corresponding to the j-th gas type produced by the mixed chemical reaction, λj1 is the toxicity hazard ratio sub-coefficient of the j-th gas type, λj2 is the flammability and explosion hazard ratio sub-coefficient of the j-th gas type, and Q is the derived hazard coefficient of the gas types generated during the experiment and the existing gas types in the laboratory for the laboratory air.

[0030] Furthermore, the formula for calculating the derived environmental hazard factor generated by the mixture of the gas species generated during the experiment and the existing gas species in the laboratory is: f and k belong to j, and their specific value range is between 1-m. The minimum harmful gas mass produced by the reaction of the gas mass wf of the f-th gas type produced in the experiment with the gas mass wk of the k-th gas type existing in the laboratory, z(wf,wk) min The minimum mass of gas produced by the reaction of the f-th gas type with the k-th gas type under poisonous or flammable and explosive conditions.

[0031] Furthermore, the laboratory air safety management system also includes a quality update assessment module, which is used to extract the experimental environment hazard factor corresponding to the current indoor air predicted by the simulation prediction and analysis module, and determine whether the experimental environment hazard factor is greater than the set control factor threshold U. If it is greater than the set control factor threshold, the gas spread trajectory analyzed by the regional big data sorting and optimization module is extracted, and the exhaust control management module is started to control the opening of the fume hood, and the time T required for air renewal management in the laboratory is evaluated.

[0032] Furthermore, the time required for laboratory air renewal management is the mass of gas exhausted per unit time by the fume hood in the i-th area at the frequency level y, β y is the experimental environment hazard factor corresponding to the mass of gas exhausted from the fume hood at frequency level y, y is equal to level 1, level 2 and level 3, and the corresponding values ​​of β1, β2, and β3 are 0.62, 0.85, and 0.98 respectively.

[0033] Beneficial effects of the present invention:

[0034] The laboratory air safety management system based on big data provided by the present invention analyzes the gas concentration in each area of ​​the laboratory, analyzes the central diffusion area corresponding to each gas type and the spread trajectory of each gas type, can accurately judge the propagation trend of the gas, and intelligently control whether the ventilation equipment in each area is turned on in the later stage.

[0035] The present invention performs frequency conversion regulation on laboratory fume hoods in each central diffusion area and the area passed by the gas diffusion trajectory, so as to realize adaptive regulation of the frequency of the laboratory fume hood according to the different gas concentrations in the area, and can reasonably and effectively discharge the types of harmful gases diffused in the laboratory in a timely manner, thereby improving energy utilization, accelerating the discharge of harmful gases from the room, reducing the harm of harmful gases to laboratory personnel, and improving the harm removal effect. The frequency conversion regulation method can maximize the emission efficiency while saving energy, realize the intelligent emission of air in the laboratory, and can adjust the balance between the laboratory gas emission efficiency and energy consumption.

[0036] The present invention analyzes the gas quality of harmful gases generated by chemical reagents required for experimental operations through a simulation prediction and analysis module to predict the experimental environmental hazard coefficient caused by the concentration of gas types existing in the room to the air in the laboratory. It can accurately predict and simulate the hazard level of laboratory air, avoid single analysis of the product, and greatly improve the accuracy of prediction and evaluation of the hazard level of laboratory air.

[0037] The present invention performs gas renewal management on the predicted experimental environment hazard factor in the laboratory, and combines the gas spreading trajectory to control the opening of the fume hood by the exhaust control management module, and predicts the time required for the renewal of harmful gases in the laboratory, which can accelerate the discharge of toxic gases out of the room, reduce the harm of harmful gases to laboratory personnel, improve the harm removal effect, improve the safety of laboratory air quality and the intelligence of air quality management, maximize the protection of the health of experimental personnel, and realize the intelligence of air safety management. BRIEF DESCRIPTION OF THE DRAWINGS

[0038] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings required for describing the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other accompanying drawings can be obtained based on these accompanying drawings without paying creative work.

[0039] Figure 1 Schematic diagram of the distribution of various areas in the laboratory of the present invention. DETAILED DESCRIPTION

[0040] 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.

[0041] A laboratory air safety management system based on big data includes an environmental parameter acquisition module, a regional big data sorting and optimization module, an exhaust control management module, an experimental data information input module, a simulation prediction and analysis module, a data optimization processing module and an intelligent prediction warning terminal.

[0042] The environmental parameter collection module includes a plurality of environmental parameter collection units, which are evenly distributed at various preset positions of the laboratory, and a mapping relationship between the environmental parameter collection units and the preset positions where the environmental parameter collection units are located is established.

[0043] In order to ensure the ventilation effect, a fume hood is set at the location of the environmental parameter collection unit, which is convenient for discharging toxic or flammable and explosive gases in the area detected by the environmental parameter collection unit, thereby improving the efficiency of gas discharge.

[0044] The environmental parameter collection unit collects the concentration information of each gas type in the area where the environmental parameter collection unit is located in real time, and sends the concentration information of each gas type in the area collected by each environmental parameter collection unit to the regional big data sorting and optimization module.

[0045] The environmental parameter collection unit collects the concentrations of various types of gases in the laboratory. The types of gases that need to be collected include carbon dioxide, chlorine, ammonia, nitrogen oxides, hydrogen fluoride, sulfur dioxide, sulfur trioxide, dimethyl sulfate, nitrogen, methane, ethane, ethylene, carbon monoxide, nitrobenzene vapor, hydrogen cyanide, hydrogen sulfide, etc. When people inhale the above gases, they will cause poisoning, etc. At the same time, if hydrogen, carbon monoxide, methane, acetylene, ethylene, propane, butane, propylene, propyne, 1,3-butadiene, butyne, hydrogen sulfide and other gases appear in the laboratory, they will explode once they encounter open flames.

[0046] The regional big data sorting and optimization module is used to obtain the concentration of each gas type in the area where each environmental parameter collection unit is located, optimize the concentration of each gas type collected in each area, analyze the central diffusion area corresponding to each gas type, and perform data analysis on the gas concentration of each gas type in each area to obtain the spread trajectory of each gas type.

[0047] Specifically, the regional big data sorting and optimization module analyzes the concentration of each gas type in each region, including the following steps:

[0048] Step 1: Compare the concentration of each gas type in the area where each environmental parameter collection unit is located with the set concentration threshold of each gas type, and screen out the gas type whose gas concentration is greater than the gas concentration threshold corresponding to the gas type, denoted as Ci j,i=1,2,3,...,n,j=1,2,3,...,m,Ci j is the gas concentration of the jth gas type in the area where the i environmental parameter collection unit is located, n is the total number of areas divided in the laboratory, and m is the number of gas types contained in the harmful gas;

[0049] Step 2: Filter out the gas concentrations of the gas types in each area whose gas concentrations are greater than the gas concentration threshold, perform data differentiation comparison on the gas concentrations corresponding to the gas types in each area, and obtain the area with the largest gas concentration of the same gas type in each area;

[0050] Step 3: The area with the highest gas concentration for the same gas is taken as the central diffusion area of ​​the gas;

[0051] Step 4: Compare the gas concentration in each central diffusion area with the gas concentration in the area where other environmental parameter acquisition units are located, and analyze the spread trajectory of the gas from the central diffusion area.

[0052] A method for analyzing the spreading trajectory of gas in a central diffusion region comprises the following steps:

[0053] Step B1, performing location association on the areas where the environmental parameter collection units in the laboratory are located;

[0054] That is, establish the adjacent position relationship of each environmental parameter collection unit, such as Figure 1 As shown, it can be seen that the areas adjacent to each area are numbered for the convenience of displaying the areas.

[0055] Step B2, sequentially extracting the gas concentrations corresponding to the gas types in the area where the environmental parameter acquisition units adjacent to the central diffusion area are located and the gas concentration in the central diffusion area is higher than that in other areas, and screening out the adjacent areas where the gas concentration is greater than the set threshold;

[0056] Step B3, sequentially taking each adjacent area whose gas concentration is greater than the set threshold value screened out in step B2 as the first diffusion area, sequentially extracting the gas concentration corresponding to the gas type in the area where the environmental parameter acquisition unit adjacent to each first diffusion area is located, and screening out the adjacent area whose gas concentration corresponding to the gas type adjacent to each first diffusion area is greater than the set threshold value as the second diffusion area;

[0057] Step B4, screening out adjacent areas adjacent to the second diffusion area where the gas concentration corresponding to the gas type is greater than a set threshold as the third diffusion area, and repeating step 4 until all areas are screened;

[0058] In the process of performing the spreading trajectory analysis for the same gas type, the area position numbers corresponding to the central diffusion area, the first diffusion area, the second diffusion area and the third diffusion area are different.

[0059] Step B5, taking the central diffusion area, the first diffusion area, the second diffusion area connected to the first diffusion area, and the third diffusion area connected to the second diffusion area as diffusion trajectories in turn, to obtain the diffusion and spread trajectories of each gas type in the laboratory.

[0060] By analyzing the diffusion and spread of gas types in the laboratory that are greater than the set threshold, the trajectory of gas diffusion can be obtained, which can accurately determine the propagation trend of the gas, facilitate the subsequent control of the ventilation equipment in the area where the environmental parameter collection unit is located, and effectively remove the gas passing through the environmental parameter collection unit to avoid energy waste caused by turning on all the ventilation equipment in the laboratory at the same time. At the same time, once all the ventilation equipment in the laboratory is turned on, the diffusion trajectory of the gas types that are greater than the set threshold will be disturbed, increasing the diffusion range of the gas type and the difficulty of gas emission, and reducing the speed of completely discharging harmful gases generated in the laboratory.

[0061] The exhaust control management module is used to obtain the central diffusion area corresponding to each gas concentration analyzed by the regional big data collation and optimization module and the gas diffusion trajectory of the central diffusion area, control the ventilation control unit in the central diffusion area and the area through which the gas diffusion trajectory passes, and at the same time obtain the gas concentration in the central diffusion area and the area through which the gas diffusion trajectory passes, and perform frequency conversion adjustment on the laboratory fume hoods in the area according to the gas concentration, so as to realize adaptive adjustment of the frequency of the laboratory fume hoods according to different gas concentrations in the area.

[0062] By adaptively adjusting the frequency conversion of the fume hoods in each area, the types of harmful gases diffused in the laboratory can be reasonably and effectively discharged in a timely manner, thereby improving energy utilization, accelerating the discharge of harmful gases from the room, reducing the harm of harmful gases to laboratory personnel, and improving the harm removal effect. It is avoided that if the ventilation frequency of the fume hoods is the maximum, it will lead to waste of electric energy. If the ventilation frequency of the fume hoods is the minimum, the ventilation time will be long and the risk of harmful gases not being able to be discharged in time and effectively will occur. The use of frequency conversion regulation can maximize the emission efficiency while saving energy, and realize the intelligent emission of air in the laboratory.

[0063] Among them, the exhaust control management module includes several ventilation control units, each of which is connected to the laboratory fume hood and is used to control the frequency conversion and start and stop operations of the laboratory fume hood located in the area where the environmental parameter collection unit is located.

[0064] The experimental data information input module is used to manually input chemical reagents that are about to be used in the laboratory for experimental operations, and send the input chemical reagent information to the simulation prediction analysis module.

[0065] The simulation prediction and analysis module is used to extract the chemical reagent information input into the laboratory (the chemical reagent information includes the type of chemical reagent and the dosage of the input chemical reagent) and the gas concentration data in the current indoor air, and analyze the harmful gases generated by the chemical reagent information input into the current laboratory and the gas quality of the generated harmful gases through the constructed hazardous reaction model set, and predict the experimental environmental hazard coefficient caused by the harmful gases generated by the chemical reagent reaction input under the gas type concentration in the current indoor air to the air in the laboratory. The experimental environmental hazard coefficient is a comprehensive assessment of the harmful gases to the laboratory environmental hazards.

[0066] The hazardous reaction model set stores several groups of chemical reaction equations and the gas mass of harmful gases produced by reactions of set doses of chemical reagents. Each group of chemical reaction equations is trained by at least two reactions of the same chemical reagent. The specific training method is to record the gas mass of harmful gases produced by two or more chemical reagents to be mixed in the training experiment operation process. The harmful gases include flammable and explosive gases and toxic gases.

[0067] Among them, the calculation formula of the experimental environment risk factor is:

[0068] e is a natural number, wj1 is the minimum gas mass of the j-th gas type under the condition of poisoning people, wj2 is the minimum gas mass of the j-th gas type under the condition of flammability and explosion, gas mass = gas molar mass × gas volume ÷ gas molar volume, Wj is the gas mass corresponding to the j-th gas type produced by the mixed chemical reaction, λj1 is the toxicity hazard ratio coefficient of the j-th gas type, if the j-th gas type can poison people, then the corresponding λj1 is equal to 1, if it will not poison people, then the corresponding λj1 is equal to 0, λj2 is The j-th gas type is the flammable and explosive hazard ratio coefficient. If the j-th gas type is flammable and explosive, the corresponding λj2 is equal to 1. If it is not flammable and explosive, the corresponding λj2 is equal to 0. Q is the derived hazard coefficient of the laboratory air caused by the mixture of the gas types generated during the experiment and the existing gas types in the laboratory. The gas type concentration uses the mass of harmful gas in each cubic meter of air as the gas concentration corresponding to the gas type, and then the gas mass in each area is equal to the product of the concentration of the gas type in the area and the volume corresponding to the area.

[0069] Since the types of gases generated during the experiment include toxic gases, flammable and explosive gases, and there is also the possibility that the gases generated during the experiment will react chemically with the gas components diffused into the air from the chemical reagents stored in the laboratory, further deriving harmful gases that pollute the laboratory air quality, by predicting the hazard factors of the experimental products and the gas components stored in the laboratory air, it is possible to accurately simulate and predict the degree of hazard of laboratory air, avoid single analysis of the products, and reduce the accuracy of the prediction.

[0070] The calculation formula for the derived environmental hazard factor generated by the mixture of the gas types generated during the experiment and the existing gas types in the laboratory is: f and k belong to j, and their specific value range is between 1-m. The minimum harmful gas mass produced by the reaction of the gas mass wf of the f-th gas type produced in the experiment with the gas mass wk of the k-th gas type existing in the laboratory, z(wf,wk) m i n The minimum mass of gas produced by the reaction of the f-th gas type with the k-th gas type under poisonous or flammable and explosive conditions.

[0071] The data optimization processing module is used to obtain the gas quality of harmful gases predicted by the simulation prediction and analysis module and predict the experimental environment hazard coefficient caused by harmful gases to the air in the laboratory, compare the experimental environment hazard coefficient with the experimental environment hazard coefficient range corresponding to the set different hazard levels one by one, determine the experimental hazard level, and screen out the emergency protection strategy corresponding to the experimental hazard level, and transmit the experimental hazard level and emergency protection strategy to the intelligent early warning display terminal.

[0072] The intelligent prediction and warning terminal is used to display the experimental hazard level corresponding to the air in the laboratory and the emergency protection strategy corresponding to the experimental hazard level, reminding the experimenters of the dangers during the experiment in advance, facilitating emergency treatment, and reducing the harm caused to the experimenters by toxic substances in the laboratory.

[0073] In addition, the present embodiment also discloses a quality update assessment module, which is used to extract the experimental environment hazard factor corresponding to the current indoor air predicted by the simulation prediction and analysis module, and determine whether the experimental environment hazard factor is greater than the set control factor threshold U. If it is greater than the set control factor threshold, the gas spread trajectory analyzed by the regional big data sorting and optimization module is extracted, and the exhaust control management module is started to control the opening of the fume hood, and the time T required for air renewal management in the laboratory is evaluated, so as to facilitate timely prediction and update of the air quality of laboratories that produce harmful gases, thereby improving the safety of laboratory air quality, maximizing the protection of the health of experimental personnel, and realizing the intelligentization of air safety management.

[0074] Among them, the time required for laboratory air renewal management is the mass of gas exhausted per unit time by the fume hood in the i-th area at the frequency level y, β y is the experimental environment hazard factor corresponding to the gas mass exhausted from the fume hood at frequency level y, y is equal to level 1, level 2 and level 3, and the corresponding values ​​of β1, β2, and β3 are 0.62, 0.85, and 0.98, respectively, and different update times are determined by selecting the frequency level of the fume hood.

[0075] When there is only toxic gas in the laboratory and the gas mass of toxic gas is less than or there is only flammable and explosive gas in the laboratory and the gas mass of flammable and explosive gas is less than, the experimental environment hazard coefficient is less than e+1. When the gas types generated during the experiment react with the existing gas types in the laboratory to produce poisoning or flammable and explosive conditions that are less than the minimum gas mass, the minimum experimental environment hazard coefficient in the three cases is screened out as the control coefficient threshold U, that is, the control coefficient threshold U is taken as.

[0076] The quality update assessment module obtains the gas spread trajectory analyzed by the regional big data collation and optimization module, controls the opening of the fume hood by the exhaust control management module, and predicts the time required to update the harmful gases in the laboratory. This can accelerate the discharge of toxic gases from the room, reduce the harm of harmful gases to laboratory personnel, improve the detoxification effect, and improve the safety of laboratory air quality and the intelligence of air quality management.

[0077] The above contents are merely examples and explanations of the concept of the present invention. The technicians in this technical field may make various modifications or additions to the specific embodiments described or replace them in a similar manner. As long as they do not deviate from the concept of the invention or exceed the scope defined by the claims, they should all fall within the protection scope of the present invention.

Claims

1. A laboratory air safety management system based on big data, characterized by: It includes environmental parameter acquisition module, regional big data sorting and optimization module and exhaust control management module; The environmental parameter collection module includes environmental parameter collection units, which are evenly distributed at various preset positions in the laboratory. The environmental parameter collection units collect concentration information of various gas types in the area where the environmental parameter collection units are located in real time, and send the concentration information of various gas types in the area collected by each environmental parameter collection unit to the regional big data sorting and optimization module; The regional big data sorting and optimization module is used to obtain the concentration of each gas type in the area where each environmental parameter collection unit is located, optimize the concentration of each gas type collected in each area, analyze the central diffusion area corresponding to each gas type, and perform data analysis on the gas concentration of each gas type in each area to obtain the spread trajectory of each gas type; The exhaust control management module is used to obtain the central diffusion area corresponding to each gas concentration analyzed by the regional big data sorting and optimization module and the gas diffusion trajectory of the central diffusion area, control the ventilation control unit in the central diffusion area and the area passed by the gas diffusion trajectory, and obtain the gas concentration in the central diffusion area and the area passed by the gas diffusion trajectory, and perform frequency conversion adjustment on the laboratory fume hoods in the area according to the gas concentration; The regional big data sorting and optimization module analyzes the concentration of each gas type in each area, including the following steps: Step 1: Compare the concentration of each gas type in the area where each environmental parameter collection unit is located with the set concentration threshold of each gas type, and screen out the gas type whose gas concentration is greater than the gas concentration threshold corresponding to the gas type, denoted as Cij,i=1,2,3,..., n,j=1,2,3,..., m,Cij is the gas concentration of the jth gas type in the area where the i environmental parameter collection unit is located, n is the total number of areas divided in the laboratory, and m is the number of gas types contained in the harmful gas; Step 2: Filter out the gas concentrations of the gas types in each area whose gas concentrations are greater than the gas concentration threshold, perform data differentiation comparison on the gas concentrations corresponding to the gas types in each area, and obtain the area with the largest gas concentration of the same gas type in each area; Step 3: The area with the highest gas concentration for the same gas is taken as the central diffusion area of ​​the gas; Step 4: Compare the gas concentration in each central diffusion area with the gas concentration in the area where other environmental parameter acquisition units are located, and analyze the spread trajectory of the gas from the central diffusion area; A method for analyzing the spreading trajectory of gas in a central diffusion region comprises the following steps: Step B1, performing location association on the areas where the environmental parameter collection units in the laboratory are located; That is, the adjacent position relationship of each environmental parameter collection unit is established, and each area is numbered for the convenience of displaying the area; Step B2, sequentially extracting the gas concentrations corresponding to the gas types in the area where the environmental parameter acquisition units adjacent to the central diffusion area are located and the gas concentration in the central diffusion area is higher than that in other areas, and screening out the adjacent areas where the gas concentration is greater than the set threshold; Step B3, sequentially taking each adjacent area whose gas concentration is greater than the set threshold value screened out in step B2 as the first diffusion area, sequentially extracting the gas concentration corresponding to the gas type in the area where the environmental parameter acquisition unit adjacent to each first diffusion area is located, and screening out the adjacent area whose gas concentration corresponding to the gas type adjacent to each first diffusion area is greater than the set threshold value as the second diffusion area; Step B4, screening out adjacent areas adjacent to the second diffusion area where the gas concentration corresponding to the gas type is greater than a set threshold as the third diffusion area, and repeating step 4 until all areas are screened; Step B5, taking the central diffusion area, the first diffusion area, the second diffusion area connected to the first diffusion area, and the third diffusion area connected to the second diffusion area as diffusion trajectories in turn, to obtain the diffusion and spread trajectories of each gas type in the laboratory.

2. A laboratory air safety management system based on big data according to claim 1, characterized in that: In the process of performing spreading trajectory analysis on the same gas type, the area position numbers corresponding to the central diffusion area, the first diffusion area, the second diffusion area and the third diffusion area are different.

3. A laboratory air safety management system based on big data according to claim 2, characterized in that: The laboratory air safety management system also includes an experimental data information input module, a simulation prediction analysis module, a data optimization processing module and an intelligent prediction warning terminal; The experimental data information input module is used to manually input the chemical reagents to be used for the experimental operation in the laboratory, and send the input chemical reagent information to the simulation prediction analysis module; The simulation prediction analysis module is used to extract the chemical reagent information input by the laboratory and the gas concentration data in the current indoor air, analyze the harmful gases generated by the chemical reagent information input by the current laboratory and the gas quality of the generated harmful gases through the constructed dangerous reaction model set, and predict the experimental environmental hazard coefficient caused by the harmful gases generated by the chemical reagent reaction input under the gas type concentration in the current indoor air to the air in the laboratory; The data optimization processing module is used to obtain the gas quality of the harmful gas predicted by the simulation prediction analysis module and predict the experimental environment hazard coefficient caused by the harmful gas to the air in the laboratory, compare the experimental environment hazard coefficient with the experimental environment hazard coefficient range corresponding to the set different hazard levels one by one, determine the experimental hazard level, and screen out the emergency protection strategy corresponding to the experimental hazard level, and transmit the experimental hazard level and emergency protection strategy to the intelligent early warning display terminal; The intelligent prediction and warning terminal is used to display the experimental hazard level corresponding to the air in the laboratory and the emergency protection strategy corresponding to the experimental hazard level.

4. A laboratory air safety management system based on big data according to claim 3, characterized in that: The calculation formula of the experimental environment risk factor is: , e is a natural number, The minimum gas mass of the jth gas type that can cause poisoning to humans is: The minimum gas mass for the jth gas type to reach the flammable and explosive conditions, gas mass = gas molar mass × gas volume ÷ gas molar volume, is the gas mass corresponding to the jth gas type produced by the mixed chemical reaction, is the toxicity hazard ratio coefficient of the jth gas type, is the flammable and explosive hazard ratio coefficient of the jth gas type, and Q is the derived hazard coefficient of the laboratory air caused by the mixture of the gas types generated during the experiment and the existing gas types in the laboratory.

5. A laboratory air safety management system based on big data according to claim 4, characterized in that: The formula for calculating the derived environmental hazard factor generated by the mixture of the gas types generated during the experiment and the existing gas types in the laboratory is: , f and k belong to j, and their specific values ​​range from 1 to m. The minimum harmful gas mass produced by the reaction between the gas mass wf of the f-th gas type produced in the experiment and the gas mass wk of the k-th gas type existing in the laboratory, The minimum mass of gas produced by the reaction of the f-th gas type with the k-th gas type under poisonous or flammable and explosive conditions.

6. A laboratory air safety management system based on big data according to claim 5, characterized in that: The laboratory air safety management system also includes a quality update assessment module, which is used to extract the experimental environment hazard factor corresponding to the current indoor air predicted by the simulation prediction and analysis module, and determine whether the experimental environment hazard factor is greater than the set control factor threshold U. If it is greater than the set control factor threshold, the gas spread trajectory analyzed by the regional big data sorting and optimization module is extracted, and the exhaust control management module is started to control the opening of the fume hood, and the time T required for air renewal management in the laboratory is evaluated.

7. A laboratory air safety management system based on big data according to claim 6, characterized in that: The time required for laboratory air renewal management , is the mass of gas exhausted per unit time by the fume hood in the i-th area at the frequency level y, is the experimental environment hazard factor corresponding to the gas mass exhausted by the fume hood at frequency level y, where y is equal to level 1, level 2 and level 3. The corresponding values ​​are 0.62, 0.85, and 0.98 respectively.

Images