CN116128682A - Intelligent laboratory safety monitoring management method and system based on AI technology - Google Patents
Intelligent laboratory safety monitoring management method and system based on AI technology Download PDFInfo
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Abstract
The invention relates to the field of laboratory safety monitoring management, and particularly discloses an intelligent laboratory safety monitoring management method and system based on an AI technology, wherein the method comprises the following steps: the invention can find potential safety hazards of laboratory miniaturization, further reduce potential operation safety risks of the laboratory, not only can provide reliable data support guarantee for safe and stable operation of the laboratory, but also can improve timeliness of response processing of the potential safety hazards of the laboratory, reduce incidence rate of laboratory safety accidents, avoid personnel injury to a certain extent, improve efficiency of the laboratory in safety management, and be favorable for providing scientific and reasonable support foundation for scientific research results of the laboratory.
Description
Technical Field
The invention relates to the technical field of laboratory safety monitoring management, in particular to an intelligent laboratory safety monitoring management method and system based on an AI technology.
Background
In recent years, the continuous development of scientific technology and education fields is integrated, so that laboratory construction of each university is promoted to have huge vitality and vitality, laboratory construction investment of each university is continuously increased, and along with the expansion of laboratory scale and the increase of laboratory quantity, the use frequency of the laboratory is continuously increased, and accordingly, various potential safety hazards of the laboratory are generated.
At present, the management of the laboratory in the colleges and universities by the technology at the existing level has a series of limitations, which are embodied as follows: (1) Most of the prior art only carries out safety management on a laboratory according to fixed laboratory management staff, so that systematic and intensive management is lacked, manual management not only needs high management cost, but also is influenced by human subjective factors, so that the management staff is difficult to find potential safety hazards of laboratory miniaturization, the potential operation safety risk of the laboratory is further increased, reliable data support guarantee cannot be provided for safe and stable operation of the laboratory, timeliness of response processing on the potential safety hazards of the laboratory is restrained to a large extent, and the incidence rate of laboratory safety accidents is further increased.
(2) The prior art is relatively lack to carry out accurate safety monitoring to specific personnel's action in the laboratory, there is the phenomenon that pertinence analysis level is not enough and the dimension is comparatively single in the monitoring consideration, because the personnel flow volume in laboratory is great, therefore there is some potential risk actions inevitably, simultaneously, because the difference of laboratory attribute, the same action can produce the security effect of different degree in different laboratories, obviously, lack the accurate safety monitoring to personnel's action, not only can produce negative effect to the steady operation in laboratory, simultaneously, still can cause personnel's injury to a certain extent, and greatly reduced the efficiency of laboratory in the aspect of safety management, be unfavorable for providing scientific and reasonable support basis for the scientific research result in laboratory.
Disclosure of Invention
In order to overcome the defects in the background technology, the embodiment of the invention provides an intelligent laboratory safety monitoring management method and system based on the AI technology, which can effectively solve the problems related to the background technology.
The aim of the invention can be achieved by the following technical scheme: the first aspect of the invention provides an AI technology-based intelligent laboratory safety monitoring management method, which comprises the following steps: s1, obtaining by a target laboratory: each target laboratory was obtained, wherein the target laboratory was the laboratory actually put into use.
S2, acquiring target laboratory properties: the attributes of each target laboratory are obtained.
S3, basic parameter monitoring of a target laboratory: and monitoring basic parameters of each target laboratory according to the attribute of each target laboratory, wherein the basic parameters comprise environmental parameters, personnel behavior parameters and equipment application parameters.
S4, basic parameter analysis of a target laboratory: according to the basic parameters of each target laboratory, the corresponding safety indexes of the environmental parameters, the personnel behavior parameters and the equipment application parameters of each target laboratory are further calculated.
S5, comprehensive safety analysis of a target laboratory: and comprehensively analyzing the comprehensive safety indexes of each target laboratory according to the safety indexes corresponding to the environmental parameters, the personnel behavior parameters and the equipment application parameters of each target laboratory.
S6, safety management prompt of a target laboratory: and screening to obtain each risk operation laboratory according to the comprehensive safety index of each target laboratory, and carrying out safety management prompt according to the risk operation laboratory.
S7, uploading risk laboratory data: and constructing a data set of each risk operation laboratory according to each risk operation laboratory obtained by screening, and uploading the data set to an experimental data storage platform.
As a further method, the environmental parameters of each target laboratory are monitored, and the specific process is as follows: environmental parameters of each target laboratory are monitored, wherein the environmental parameters include gas parameters and environmental base parameters.
According to the gas parameters of each target laboratory, wherein the gas parameters comprise each gas concentration and each gas category, and further the gas concentrations of each category of each target laboratory are obtained by normalization, and according to the attribute of each target laboratory, the gas allowable concentration of each category corresponding to each laboratory attribute stored in the experimental cloud database is further obtainedThe degree is matched to obtain the allowable concentration of each class of gas in each target laboratory, and then the safety index corresponding to the gas parameter of each target laboratory is compared and calculated, and the calculation formula is as follows:
wherein sigma j Expressed as safety index, Δn, corresponding to the gas parameter of the jth target laboratory jd Class d gas allowable concentration, N, expressed as j-th target laboratory jd "the concentration of the gas of the (d) th class, delta, expressed as the (j) th target laboratory 1 The safety correction value corresponding to the set gas parameter is expressed as j, j=1, 2, and n, d, and d=1, 2, and f, respectively.
According to the environment basic parameters of each target laboratory, wherein the environment basic parameters comprise temperature, humidity and air flow rate, and according to the attributes of each target laboratory, the environment basic parameters are matched with environment suitable basic parameters corresponding to various laboratory attributes stored in an experimental cloud database, so as to obtain the environment suitable basic parameters of each target laboratory, wherein the environment suitable basic parameters comprise: the appropriate temperature, the appropriate humidity and the appropriate air flow rate are compared and calculated according to the appropriate temperature, the appropriate humidity and the appropriate air flow rate, and the corresponding safety index of the basic environmental parameters of each target laboratory is recorded as omega j 。
As a further method, the safety index corresponding to the environmental parameter of each target laboratory is calculated by the following formula:
wherein->
Expressed as a safety index corresponding to the environmental parameter of the jth target laboratory, a 1 And a 2 The safety evaluation weight factors corresponding to the set gas parameters and the environment basic parameters are respectively expressed, and e is expressed as a natural constant.
As a further method, the monitoring of personnel behavior parameters of each target laboratory is carried out byThe body process is as follows: the method comprises the steps of identifying personnel of each target laboratory, further obtaining each personnel belonging to each target laboratory, matching the attribute of each target laboratory with each type of risk behavior corresponding to each laboratory attribute stored in a laboratory cloud database to obtain each type of risk behavior of each target laboratory, further identifying whether each personnel belonging to each target laboratory has risk behaviors through a set risk behavior identification mechanism, extracting the type and duration of each risk behavior of each target laboratory if the risk behaviors belong to each target laboratory, further matching the type and duration of each risk behavior with the safety influence factor of the unit duration corresponding to each set risk behavior type to obtain the safety influence factor of the unit duration corresponding to each risk behavior of each target laboratory, and accordingly calculating the safety index corresponding to the personnel behavior of each target laboratory, wherein the calculation formula is as follows: 
Wherein mu j Expressed as a safety index, t, corresponding to the personnel behaviour of the jth target laboratory ji Duration of the ith risk action expressed as jth target laboratory, +.>
Security influencing factor, expressed as the unit duration of the type to which the ith risk behavior of the jth target laboratory belongs,/->
The safety correction value corresponding to the set personnel behavior is represented by i, i=1, 2, & k, each risk behavior is represented by i. />
Identifying the dangerous sources of each target laboratory according to the set dangerous source identification model, further obtaining the dangerous source positions of each target laboratory, further extracting the distances between the personnel belonging to each target laboratory and the dangerous sources of the corresponding target laboratory, recording the distances as the reference distances between the personnel belonging to each target laboratory and the dangerous sources, and comparing the distances according to the reference safety distances of the dangerous sources stored in the experimental cloud databaseThe safety index of the personnel corresponding to the dangerous source distance of each target laboratory is calculated, and the calculation formula is as follows:
wherein eta j Expressed as the safety index L of the personnel corresponding to the dangerous source distance of the jth target laboratory jp m is expressed as the reference distance delta L of the jth target laboratory corresponding to the mth hazard source of the jth personnel 0 Expressed as a hazard reference safety distance, +.>
The safety correction factor corresponding to the set distance between the danger sources is expressed, p is expressed as the number of each person, p=1, 2, & gt, z, m is expressed as the number of each danger source, m=1, 2, & gt, u.
As a further method, the safety index corresponding to the personnel behavior parameters of each target laboratory is calculated by the following formula:
wherein ε is j Safety index, κ, expressed as the corresponding personnel behavior parameters of the jth target laboratory 1 And kappa (kappa) 2 And respectively representing the set personnel behaviors and the safety evaluation weight occupation ratio corresponding to the personnel corresponding dangerous source distance.
As a further method, the monitoring of the equipment application parameters of each target laboratory comprises the following specific processes: and monitoring equipment application parameters of each target laboratory, wherein the equipment application parameters comprise the number of experimental equipment, the position of each experimental equipment, the opening time of each electric equipment and the total electric consumption of the electric equipment.
According to the initial number of experimental equipment and the initial position of each experimental equipment of each laboratory stored in the experimental cloud database, extracting the initial number of experimental equipment and the initial position of each experimental equipment of each target laboratory from the initial number of experimental equipment and the initial position of each experimental equipment, extracting and obtaining the movement interval of each experimental equipment of each target laboratory according to each experimental equipment position of each target laboratory, and according to various experimental equipment stored in the experimental cloud database The allowable movement interval of the experimental equipment of each target laboratory is extracted, the allowable movement interval of the experimental equipment of each target laboratory is obtained, the use safety index corresponding to the experimental equipment of each target laboratory is calculated according to the allowable movement interval, and the calculation formula is as follows:
wherein alpha is j Corresponding safety in use index, ΔA, of the laboratory equipment expressed as the jth target laboratory j0 Initial quantity of laboratory equipment expressed as j-th target laboratory, A j "number of laboratory instruments, ΔJG, expressed as j-th target laboratory jb The b-th laboratory equipment, denoted as the j-th target laboratory, belongs to the allowed movement interval, JG jb "the b-th laboratory equipment movement interval expressed as the j-th target laboratory,">
And->
The weight ratio of the safety used weights corresponding to the set number of the experimental devices and the moving interval of the experimental devices is represented by b, and b=1, 2, & g.
According to the opening time of each electric equipment of each target laboratory, and then the electric equipment is matched with the electric consumption of the corresponding unit opening time of each electric equipment stored in the experimental cloud database, the electric consumption of the corresponding unit opening time of each electric equipment of each target laboratory is obtained, the total electric consumption of the electric equipment of each target laboratory is extracted, and accordingly, the use safety index corresponding to the electric equipment of each target laboratory is calculated, wherein the calculation formula is as follows: 
Wherein beta is j The corresponding use safety index of the electric equipment expressed as the j-th target laboratory, D j0 Total power consumption, dl, of powered equipment expressed as j-th target laboratory jr Use of the corresponding unit on-time of the r-th consumer expressed as the j-th target laboratoryElectric quantity, SC jr "the power-on duration of the (r) electric equipment expressed as the (j) target laboratory, lambda 1 The usage safety correction factor corresponding to the set electricity consumption of the electric equipment is represented by r, wherein r is the number of each electric equipment, and r=1, 2.
As a further method, the safety index corresponding to the equipment application parameter of each target laboratory is calculated by the following formula:
wherein θ is j Safety index, Φ, expressed as the corresponding equipment application parameters of the jth target laboratory 1 And phi is 2 And the safety weight values are respectively indicated as the safety weight values corresponding to the set experimental equipment and the electric equipment.
As a further method, the comprehensive safety index of each target laboratory is calculated by the following formula:
wherein psi is j Expressed as the integrated safety index, phi, of the jth target laboratory 1 、φ 2 And phi 3 Respectively expressed as the corresponding weight factors of the environment parameter, the personnel behavior parameter and the equipment application parameter.
As a further method, the screening results in each risk operation laboratory, which comprises the following specific processes: and comparing the comprehensive safety index of each target laboratory with a set comprehensive safety index threshold, and if the comprehensive safety index of a certain target laboratory is lower than the comprehensive safety index threshold, marking the target laboratory as a risk operation laboratory, and further counting each risk operation laboratory.
The second aspect of the present invention provides an AI technology-based intelligent laboratory security monitoring management system, comprising: and the target laboratory acquisition module is used for acquiring each target laboratory, wherein the target laboratory is an actually-put-into-use laboratory.
And the target laboratory attribute acquisition module is used for acquiring the attribute of each target laboratory.
And the target laboratory basic parameter monitoring module is used for monitoring basic parameters of each target laboratory according to the attribute of each target laboratory, wherein the basic parameters comprise environmental parameters, personnel behavior parameters and equipment application parameters.
And the target laboratory basic parameter analysis module is used for calculating the safety indexes corresponding to the environmental parameters, the personnel behavior parameters and the equipment application parameters of each target laboratory according to the basic parameters of each target laboratory.
And the comprehensive safety analysis module of the target laboratory is used for comprehensively analyzing the comprehensive safety indexes of the target laboratories according to the safety indexes corresponding to the environmental parameters, the personnel behavior parameters and the equipment application parameters of the target laboratories.
And the target laboratory safety management prompt module is used for screening and obtaining each risk operation laboratory according to the comprehensive safety index of each target laboratory and carrying out safety management prompt according to the risk operation laboratory.
And the risk laboratory data uploading module is used for constructing a data set of each risk operation laboratory according to each risk operation laboratory obtained by screening and uploading the data set to the experimental data storage platform.
And the experimental data storage platform is used for storing data sets of all risk operation laboratories.
The experimental cloud database is used for storing environment suitable basic parameters, gas allowable concentration of each type and risk behaviors of each type corresponding to various laboratory attributes, storing dangerous source reference safety intervals, storing initial quantity of experimental equipment and initial positions of the experimental equipment in each laboratory, storing allowable movement intervals of the various experimental equipment, and storing electricity consumption of unit opening time corresponding to various electric equipment.
Compared with the prior art, the embodiment of the invention has at least the following advantages or beneficial effects: (1) The intelligent laboratory safety monitoring management method and system based on the AI technology provided by the invention realize systematic and centralized management of the laboratory, effectively make up for the defect that the prior art mostly only carries out safety management on the laboratory according to fixed laboratory management staff, slow down the high management cost of manual management, avoid the influence of human subjective factors, find the potential safety hazard of the laboratory microminiaturization, further reduce the potential operation safety risk of the laboratory, not only provide reliable data support guarantee for the safe and stable operation of the laboratory, but also improve the timeliness of response processing on the potential safety hazard of the laboratory to a great extent, and further reduce the incidence rate of laboratory safety accidents.
(2) According to the invention, the type and the duration of each risk behavior of each target laboratory are acquired, and the reference distance of each risk source corresponding to each personnel to which each target laboratory belongs is acquired, so that the safety index corresponding to the personnel behavior parameter of each target laboratory is calculated, the defect that the prior art is deficient in carrying out accurate safety monitoring on specific personnel behaviors in the laboratory is effectively overcome, the pertinence analysis level is improved, the monitoring consideration dimension is rich and various, and the invention considers the fact that the personnel flow of the laboratory is large and the laboratory has different attributes, so that the personnel behaviors of each target laboratory are accurately and safely monitored, the negative influence on the stable operation of the laboratory is greatly reduced, meanwhile, the personnel injury to a certain extent is avoided, the safety management efficiency of the laboratory is greatly improved, and the scientific and reasonable support foundation is provided for the scientific research results of the laboratory.
Drawings
The invention will be further described with reference to the accompanying drawings, in which embodiments do not constitute any limitation of the invention, and other drawings can be obtained by one of ordinary skill in the art without inventive effort from the following drawings.
FIG. 1 is a flow chart of the method steps of the present invention.
Fig. 2 is a schematic diagram of system configuration connection according to the present invention.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
Referring to fig. 1, a first aspect of the present invention provides an intelligent laboratory security monitoring management method based on AI technology, including: s1, obtaining by a target laboratory: each target laboratory was obtained, wherein the target laboratory was the laboratory actually put into use.
S2, acquiring target laboratory properties: the attributes of each target laboratory are obtained.
The properties of each target laboratory include physical, chemical and biological properties.
S3, basic parameter monitoring of a target laboratory: and monitoring basic parameters of each target laboratory according to the attribute of each target laboratory, wherein the basic parameters comprise environmental parameters, personnel behavior parameters and equipment application parameters.
Specifically, the environmental parameters of each target laboratory are monitored, and the specific process is as follows: environmental parameters of each target laboratory are monitored, wherein the environmental parameters include gas parameters and environmental base parameters.
According to the gas parameters of each target laboratory, wherein the gas parameters comprise each gas concentration and each gas category, each class of gas concentration of each target laboratory is obtained through normalization, each class of gas allowable concentration corresponding to each class of laboratory attribute stored in the experimental cloud database is matched according to the attribute of each target laboratory, each class of gas allowable concentration of each target laboratory is obtained, and the safety index corresponding to the gas parameters of each target laboratory is calculated through comparison, wherein the calculation formula is as follows:
wherein sigma j Expressed as safety index, Δn, corresponding to the gas parameter of the jth target laboratory jd Class d gas allowable concentration, N, expressed as j-th target laboratory jd "is denoted as j-thClass d gas concentration, delta for target laboratory 1 The safety correction value corresponding to the set gas parameter is expressed as j, j=1, 2, and n, d, and d=1, 2, and f, respectively.
It should be noted that, the above gas categories include flammable and explosive gases and toxic and harmful gases, and the specific used monitoring devices are: the gas sensor is used for detecting harmful gas and flammable and explosive gas which exist, the harmful gas detector is used for detecting the concentration of the harmful gas, and the flammable and explosive gas detector is used for detecting the concentration of the flammable and explosive gas.
According to the environment basic parameters of each target laboratory, wherein the environment basic parameters comprise temperature, humidity and air flow rate, and according to the attributes of each target laboratory, the environment basic parameters are matched with environment suitable basic parameters corresponding to various laboratory attributes stored in an experimental cloud database, so as to obtain the environment suitable basic parameters of each target laboratory, wherein the environment suitable basic parameters comprise: the appropriate temperature, the appropriate humidity and the appropriate air flow rate are compared and calculated according to the appropriate temperature, the appropriate humidity and the appropriate air flow rate, and the corresponding safety index of the basic environmental parameters of each target laboratory is recorded as omega j 。
It should be noted that, the specific calculation formula of the safety index corresponding to the environmental basic parameters of each target laboratory is:
wherein T is j0 、M j0 And V j0 Respectively expressed as the j-th target laboratory proper temperature, proper humidity and proper air flow rate, t j 、m j And v j Expressed as jth target laboratory temperature, humidity and air flow rate, χ, respectively 1 、χ 2 And χ (x) 3 The safety evaluation correction factors are respectively expressed as the set temperature, humidity and air flow rate.
It should be noted that, the above-mentioned temperature, humidity and air flow rate of each target laboratory specifically uses the monitoring device as follows: temperature sensor, humidity transducer and air flow rate sensor, wherein temperature sensor is used for monitoring temperature, and humidity sensor is used for monitoring humidity, and air flow rate sensor is used for monitoring the air flow rate.
Specifically, the monitoring of the personnel behavior parameters of each target laboratory comprises the following specific processes: the method comprises the steps of identifying personnel of each target laboratory, further obtaining each personnel belonging to each target laboratory, matching the attribute of each target laboratory with each type of risk behavior corresponding to each laboratory attribute stored in a laboratory cloud database to obtain each type of risk behavior of each target laboratory, further identifying whether each personnel belonging to each target laboratory has risk behaviors through a set risk behavior identification mechanism, extracting the type and duration of each risk behavior of each target laboratory if the risk behaviors belong to each target laboratory, further matching the type and duration of each risk behavior with the safety influence factor of the unit duration corresponding to each set risk behavior type to obtain the safety influence factor of the unit duration corresponding to each risk behavior of each target laboratory, and accordingly calculating the safety index corresponding to the personnel behavior of each target laboratory, wherein the calculation formula is as follows: 
Wherein mu j Expressed as a safety index, t, corresponding to the personnel behaviour of the jth target laboratory ji Duration of the ith risk action expressed as jth target laboratory, +.>
Security influencing factor, expressed as the unit duration of the type to which the ith risk behavior of the jth target laboratory belongs,/->
The safety correction value corresponding to the set personnel behavior is represented by i, i=1, 2, & k, each risk behavior is represented by i.
The above-mentioned personnel identification is performed on each target laboratory, and the specifically used monitoring device is a human infrared sensor.
As one example, the types of risk behaviors of the chemical laboratory include those of unworn masks, unworn protective clothing, unworn chemical protective gloves, and the like, and the types of risk behaviors of the physical laboratory include unworn goggles, unworn barrier clothing, and the like.
Identifying the dangerous sources of each target laboratory according to a set dangerous source identification model, further obtaining the dangerous source positions of each target laboratory, further extracting the distance between the personnel belonging to each target laboratory and the dangerous sources of the corresponding target laboratory, marking the distance as the reference distance between the personnel belonging to each target laboratory and the dangerous sources, and comparing and calculating the safety indexes of the distances between the personnel belonging to each target laboratory and the dangerous sources according to the reference safety distances of the dangerous sources stored in the experimental cloud database, wherein the calculation formula is as follows: 
Wherein eta j Expressed as the safety index L of the personnel corresponding to the dangerous source distance of the jth target laboratory jp m is expressed as the reference distance delta L of the jth target laboratory corresponding to the mth hazard source of the jth personnel 0 Expressed as a hazard reference safety distance, +.>
The safety correction factor corresponding to the set distance between the danger sources is expressed, p is expressed as the number of each person, p=1, 2, & gt, z, m is expressed as the number of each danger source, m=1, 2, & gt, u.
The dangerous sources include dangerous chemicals, power sources, strong electric devices, pressure devices and the like.
The specific extraction process is as follows: scanning all persons belonging to each target laboratory through a high-definition scanner, extracting and obtaining body posture images of all persons belonging to each target laboratory, positioning head center points of all persons belonging to each target laboratory from the body posture images, extracting and obtaining all dangerous source position center points of all target laboratory according to all dangerous source positions of all target laboratory, respectively connecting the head center points of all persons belonging to each target laboratory with all dangerous source position center points of corresponding target laboratory in a straight line, extracting the length of a connecting straight line, obtaining the distance between all persons belonging to each target laboratory and all dangerous sources of corresponding target laboratory, and taking the distance as the reference distance between all persons belonging to each target laboratory and all dangerous sources.
Specifically, the monitoring of the equipment application parameters of each target laboratory comprises the following specific processes: and monitoring equipment application parameters of each target laboratory, wherein the equipment application parameters comprise the number of experimental equipment, the position of each experimental equipment, the opening time of each electric equipment and the total electric consumption of the electric equipment.
According to the initial number of experimental equipment and the initial position of each experimental equipment of each laboratory stored in the experimental cloud database, extracting the initial number of experimental equipment and the initial position of each experimental equipment of each target laboratory from the initial number of experimental equipment and the initial position of each experimental equipment, further extracting and obtaining each experimental equipment movement interval of each target laboratory according to each experimental equipment position of each target laboratory, extracting and obtaining each experimental equipment belonging allowable movement interval of each target laboratory according to each experimental equipment belonging allowable movement interval stored in the experimental cloud database, and accordingly calculating the corresponding use safety index of the experimental equipment of each target laboratory, wherein the calculation formula is as follows:
wherein alpha is j Corresponding safety in use index, ΔA, of the laboratory equipment expressed as the jth target laboratory j0 Initial quantity of laboratory equipment expressed as j-th target laboratory, A j "number of laboratory instruments, ΔJG, expressed as j-th target laboratory jb The b-th laboratory equipment, denoted as the j-th target laboratory, belongs to the allowed movement interval, JG jb "the b-th laboratory equipment movement interval expressed as the j-th target laboratory,">
And->
The weight ratio of the safety used weights corresponding to the set number of the experimental devices and the moving interval of the experimental devices is represented by b, and b=1, 2, & g.
The moving interval of each experimental equipment in each target laboratory is described, and the specific extraction process is as follows: according to the positions of the experimental equipment of each target laboratory, further extracting the center points of the positions of the experimental equipment of each target laboratory, extracting the center points of the initial positions of the experimental equipment of each target laboratory, further connecting the center points of the initial positions of the experimental equipment of each target laboratory with the center points of the initial positions of the corresponding experimental equipment of the corresponding target laboratory in a straight line, and extracting the length of the straight line of connection, thereby obtaining the moving interval of each experimental equipment of each target laboratory.
According to the opening time of each electric equipment of each target laboratory, and then the electric equipment is matched with the electric consumption of the corresponding unit opening time of each electric equipment stored in the experimental cloud database, the electric consumption of the corresponding unit opening time of each electric equipment of each target laboratory is obtained, the total electric consumption of the electric equipment of each target laboratory is extracted, and accordingly, the use safety index corresponding to the electric equipment of each target laboratory is calculated, wherein the calculation formula is as follows: 
Wherein beta is j The corresponding use safety index of the electric equipment expressed as the j-th target laboratory, D j0 Total power consumption, dl, of powered equipment expressed as j-th target laboratory jr The electricity consumption corresponding to the unit on time length of the (r) electric equipment of the (j) target laboratory, SC jr "the power-on duration of the (r) electric equipment expressed as the (j) target laboratory, lambda 1 The usage safety correction factor corresponding to the set electricity consumption of the electric equipment is represented by r, wherein r is the number of each electric equipment, and r=1, 2.
S4, basic parameter analysis of a target laboratory: according to the basic parameters of each target laboratory, the corresponding safety indexes of the environmental parameters, the personnel behavior parameters and the equipment application parameters of each target laboratory are further calculated.
Specifically, the calculation formula of the safety index corresponding to the environmental parameters of each target laboratory is as follows:
wherein->
Expressed as a safety index corresponding to the environmental parameter of the jth target laboratory, a 1 And a 2 The safety evaluation weight factors corresponding to the set gas parameters and the environment basic parameters are respectively expressed, and e is expressed as a natural constant.
Specifically, the safety index corresponding to the personnel behavior parameters of each target laboratory is calculated according to the following formula: 
Wherein ε is j Safety index, κ, expressed as the corresponding personnel behavior parameters of the jth target laboratory 1 And kappa (kappa) 2 And respectively representing the set personnel behaviors and the safety evaluation weight occupation ratio corresponding to the personnel corresponding dangerous source distance.
In a specific embodiment, the invention effectively overcomes the defect that the prior art is deficient in accurately and safely monitoring specific personnel behaviors in the laboratory by acquiring the type and duration of each risk behavior of each target laboratory and acquiring the reference distance of each risk source corresponding to each personnel belonging to each target laboratory, thereby effectively overcoming the defect that the prior art is deficient in accurately and safely monitoring the specific personnel behaviors in the laboratory, improving the pertinence analysis level, and ensuring that the monitoring dimension is rich and various, and further accurately and safely monitoring the personnel behaviors of each target laboratory by considering the large personnel flow quantity and the different properties of the laboratory, thereby greatly reducing the negative influence on the stable operation of the laboratory, avoiding personnel injury to a certain extent, further greatly improving the efficiency of the laboratory in the aspect of safety management, and being beneficial to providing a scientific and reasonable support foundation for the scientific research results of the laboratory.
Specifically, the safety index corresponding to the equipment application parameters of each target laboratory is calculated according to the following formula:
wherein θ is j Safety index, Φ, expressed as the corresponding equipment application parameters of the jth target laboratory 1 And phi is 2 And the safety weight values are respectively indicated as the safety weight values corresponding to the set experimental equipment and the electric equipment.
S5, comprehensive safety analysis of a target laboratory: and comprehensively analyzing the comprehensive safety indexes of each target laboratory according to the safety indexes corresponding to the environmental parameters, the personnel behavior parameters and the equipment application parameters of each target laboratory.
Specifically, the comprehensive safety index of each target laboratory is calculated by the following formula:
wherein psi is j Expressed as the integrated safety index, phi, of the jth target laboratory 1 、φ 2 And phi 3 Respectively expressed as the corresponding weight factors of the environment parameter, the personnel behavior parameter and the equipment application parameter.
S6, safety management prompt of a target laboratory: and screening to obtain each risk operation laboratory according to the comprehensive safety index of each target laboratory, and carrying out safety management prompt according to the risk operation laboratory.
Specifically, the screening results in each risk operation laboratory, and the specific process is as follows: and comparing the comprehensive safety index of each target laboratory with a set comprehensive safety index threshold, and if the comprehensive safety index of a certain target laboratory is lower than the comprehensive safety index threshold, marking the target laboratory as a risk operation laboratory, and further counting each risk operation laboratory.
S7, uploading risk laboratory data: and constructing a data set of each risk operation laboratory according to each risk operation laboratory obtained by screening, and uploading the data set to an experimental data storage platform.
It should be noted that, the data set of each risk operation laboratory includes the environmental parameter, personnel behavior parameter and equipment application parameter that specifically monitor, uploads it to the experiment data storage platform, and then is convenient for carry out reasonable effective response processing to the safety control of risk operation laboratory, provides the reliability foundation for the follow-up improvement in laboratory.
Referring to fig. 2, a second aspect of the present invention provides an intelligent laboratory security monitoring management system based on AI technology, including: the system comprises a target laboratory acquisition module, a target laboratory attribute acquisition module, a target laboratory basic parameter monitoring module, a target laboratory basic parameter analysis module, a target laboratory comprehensive safety analysis module, a target laboratory safety management prompt module, a risk laboratory data uploading module, a laboratory data storage platform and a laboratory cloud database.
The system comprises a target laboratory acquisition module, a target laboratory attribute acquisition module, a target laboratory basic parameter monitoring module, a target laboratory basic parameter analysis module, a target laboratory comprehensive safety analysis module, a target laboratory safety management prompt module, a risk laboratory data uploading module and an experiment data storage platform.
The target laboratory acquisition module is used for acquiring each target laboratory, wherein the target laboratory is an actual laboratory in use.
The target laboratory attribute acquisition module is used for acquiring the attribute of each target laboratory.
The basic parameter monitoring module of the target laboratory is used for monitoring basic parameters of each target laboratory according to the attribute of each target laboratory, wherein the basic parameters comprise environmental parameters, personnel behavior parameters and equipment application parameters.
The basic parameter analysis module of the target laboratory is used for calculating the corresponding safety indexes of the environmental parameters, the personnel behavior parameters and the equipment application parameters of each target laboratory according to the basic parameters of each target laboratory.
The comprehensive safety analysis module of the target laboratory is used for comprehensively analyzing the comprehensive safety index of each target laboratory according to the safety indexes corresponding to the environmental parameters, the personnel behavior parameters and the equipment application parameters of each target laboratory.
The target laboratory safety management prompt module is used for screening and obtaining each risk operation laboratory according to the comprehensive safety index of each target laboratory and carrying out safety management prompt according to the risk operation laboratory.
The risk laboratory data uploading module is used for constructing a data set of each risk operation laboratory according to each risk operation laboratory obtained through screening and uploading the data set to the experimental data storage platform.
The experimental data storage platform is used for storing data sets of all risk operation laboratories.
The experimental cloud database is used for storing environment suitable basic parameters, various gas allowable concentrations and various risk behaviors corresponding to various laboratory attributes, storing dangerous source reference safety intervals, storing initial numbers of experimental equipment and initial positions of the experimental equipment in each laboratory, storing allowable movement intervals of various experimental equipment, and storing electricity consumption of various electric equipment corresponding to unit opening time.
In a specific embodiment, the intelligent laboratory safety monitoring management method and system based on the AI technology provided by the invention realize systematic and centralized management of the laboratory, effectively make up for the defect that the prior art is mainly based on safety management of the laboratory by fixed laboratory management staff, slow down the high management cost of manual management, avoid the influence of human subjective factors, discover the potential safety hazards of the laboratory, further reduce the potential operation safety risk of the laboratory, not only provide reliable data support guarantee for the safe and stable operation of the laboratory, but also greatly improve the timeliness of response processing on the potential safety hazards of the laboratory, and further reduce the incidence rate of the laboratory safety accidents.
The foregoing is merely illustrative of the structures of this invention and various modifications, additions and substitutions for those skilled in the art can be made to the described embodiments without departing from the scope of the invention or from the scope of the invention as defined in the accompanying claims.
Claims (10)
1. An intelligent laboratory safety monitoring management method based on an AI technology is characterized by comprising the following steps:
s1, obtaining by a target laboratory: acquiring each target laboratory, wherein the target laboratory is a laboratory which is actually put into use;
s2, acquiring target laboratory properties: acquiring the attribute of each target laboratory;
s3, basic parameter monitoring of a target laboratory: according to the attribute of each target laboratory, further monitoring basic parameters of each target laboratory, wherein the basic parameters comprise environmental parameters, personnel behavior parameters and equipment application parameters;
s4, basic parameter analysis of a target laboratory: according to the basic parameters of each target laboratory, further calculating the corresponding safety indexes of the environmental parameters, the personnel behavior parameters and the equipment application parameters of each target laboratory;
s5, comprehensive safety analysis of a target laboratory: according to the safety indexes corresponding to the environmental parameters, the personnel behavior parameters and the equipment application parameters of each target laboratory, further comprehensively analyzing the comprehensive safety indexes of each target laboratory;
S6, safety management prompt of a target laboratory: according to the comprehensive safety index of each target laboratory, screening to obtain each risk operation laboratory, and carrying out safety management prompt according to the risk operation laboratory;
s7, uploading risk laboratory data: and constructing a data set of each risk operation laboratory according to each risk operation laboratory obtained by screening, and uploading the data set to an experimental data storage platform.
2. The AI-technology-based intelligent laboratory security monitoring management method of claim 1, wherein: the environmental parameters of each target laboratory are monitored, and the specific process is as follows:
monitoring environmental parameters of each target laboratory, wherein the environmental parameters comprise gas parameters and environmental basic parameters;
according to the gas parameters of each target laboratory, wherein the gas parameters comprise each gas concentration and each gas category, each class of gas concentration of each target laboratory is obtained through normalization, each class of gas allowable concentration corresponding to each class of laboratory attribute stored in the experimental cloud database is matched according to the attribute of each target laboratory, each class of gas allowable concentration of each target laboratory is obtained, and the safety index corresponding to the gas parameters of each target laboratory is calculated through comparison, wherein the calculation formula is as follows: 
Wherein sigma j Expressed as safety index, Δn, corresponding to the gas parameter of the jth target laboratory jd Class d gas allowable concentration, N, expressed as j-th target laboratory jd "the concentration of the gas of the (d) th class, delta, expressed as the (j) th target laboratory 1 The safety correction value corresponding to the set gas parameter is expressed as j, j=1, 2, & n, d, d=1, 2, & f;
according to the environment basic parameters of each target laboratory, wherein the environment basic parameters comprise temperature, humidity and air flow rate, and according to the attributes of each target laboratory, the environment basic parameters are matched with environment suitable basic parameters corresponding to various laboratory attributes stored in an experimental cloud database, so as to obtain the environment suitable basic parameters of each target laboratory, wherein the environment suitable basic parameters comprise: suitable temperature,The safety index corresponding to the basic environmental parameters of each target laboratory is calculated by comparing the proper humidity and the proper air flow rate and is recorded as omega j 。
3. The AI-technology-based intelligent laboratory security monitoring management method of claim 2, wherein: the safety index corresponding to the environmental parameters of each target laboratory is calculated according to the following formula: 
Wherein the method comprises the steps of
Expressed as a safety index corresponding to the environmental parameter of the jth target laboratory, a 1 And a 2 The safety evaluation weight factors corresponding to the set gas parameters and the environment basic parameters are respectively expressed, and e is expressed as a natural constant.
4. The intelligent laboratory safety monitoring and management method based on AI technology of claim 3, wherein: the personnel behavior parameters of each target laboratory are monitored, and the specific process is as follows:
the method comprises the steps of identifying personnel of each target laboratory, further obtaining each personnel belonging to each target laboratory, matching the attribute of each target laboratory with each type of risk behavior corresponding to each laboratory attribute stored in a laboratory cloud database to obtain each type of risk behavior of each target laboratory, further identifying whether each personnel belonging to each target laboratory has risk behaviors through a set risk behavior identification mechanism, extracting the type and duration of each risk behavior of each target laboratory if the risk behaviors belong to each target laboratory, further matching the type and duration of each risk behavior with the safety influence factor of the unit duration corresponding to each set risk behavior type to obtain the safety influence factor of the unit duration corresponding to each risk behavior of each target laboratory, and accordingly calculating the safety index corresponding to the personnel behavior of each target laboratory, wherein the calculation formula is as follows: 
Wherein mu j Expressed as a safety index, t, corresponding to the personnel behaviour of the jth target laboratory ji Duration of the ith risk action expressed as jth target laboratory, +.>
Security influencing factor, expressed as the unit duration of the type to which the ith risk behavior of the jth target laboratory belongs,/->
The safety correction value corresponding to the set personnel behavior is represented by i, i=1, 2, & k, each risk behavior is represented by a number;
identifying the dangerous sources of each target laboratory according to a set dangerous source identification model, further obtaining the dangerous source positions of each target laboratory, further extracting the distance between the personnel belonging to each target laboratory and the dangerous sources of the corresponding target laboratory, marking the distance as the reference distance between the personnel belonging to each target laboratory and the dangerous sources, and comparing and calculating the safety indexes of the distances between the personnel belonging to each target laboratory and the dangerous sources according to the reference safety distances of the dangerous sources stored in the experimental cloud database, wherein the calculation formula is as follows:
wherein eta j Expressed as the safety index L of the personnel corresponding to the dangerous source distance of the jth target laboratory jp m is expressed as the reference distance delta L of the jth target laboratory corresponding to the mth hazard source of the jth personnel 0 Expressed as a hazard reference safety distance, +.>
The safety correction factor corresponding to the set distance between the danger sources is expressed, p is expressed as the number of each person, p=1, 2, & gt, z, m is expressed as each dangerNumber of risk sources, m=1, 2,..u.
5. The AI-technology-based intelligent laboratory security monitoring management method of claim 4, wherein: the safety index corresponding to the personnel behavior parameters of each target laboratory is calculated according to the following formula:
wherein ε is j Safety index, κ, expressed as the corresponding personnel behavior parameters of the jth target laboratory 1 And kappa (kappa) 2 And respectively representing the set personnel behaviors and the safety evaluation weight occupation ratio corresponding to the personnel corresponding dangerous source distance.
6. The AI-technology-based intelligent laboratory security monitoring management method of claim 5, wherein: the specific process of monitoring the equipment application parameters of each target laboratory is as follows:
monitoring equipment application parameters of each target laboratory, wherein the equipment application parameters comprise the number of experimental equipment, the position of each experimental equipment, the opening time of each electric equipment and the total electric consumption of the electric equipment;
according to the initial number of experimental equipment and the initial position of each experimental equipment of each laboratory stored in the experimental cloud database, extracting the initial number of experimental equipment and the initial position of each experimental equipment of each target laboratory from the initial number of experimental equipment and the initial position of each experimental equipment, further extracting and obtaining each experimental equipment movement interval of each target laboratory according to each experimental equipment position of each target laboratory, extracting and obtaining each experimental equipment belonging allowable movement interval of each target laboratory according to each experimental equipment belonging allowable movement interval stored in the experimental cloud database, and accordingly calculating the corresponding use safety index of the experimental equipment of each target laboratory, wherein the calculation formula is as follows: 
Wherein alpha is j Corresponding use of laboratory equipment denoted j-th target laboratoryWith safety index, deltaA j0 Initial quantity of laboratory equipment expressed as j-th target laboratory, A j "number of laboratory instruments, ΔJG, expressed as j-th target laboratory jb The b-th laboratory equipment, denoted as the j-th target laboratory, belongs to the allowed movement interval, JG jb "the b-th laboratory equipment movement interval expressed as the j-th target laboratory,">
And->
The weight ratio of the safety used weights corresponding to the set number of the experimental devices and the moving interval of the experimental devices is represented by b, the numbers of the experimental devices are represented by b=1, 2, & g;
according to the opening time of each electric equipment of each target laboratory, and then the electric equipment is matched with the electric consumption of the corresponding unit opening time of each electric equipment stored in the experimental cloud database, the electric consumption of the corresponding unit opening time of each electric equipment of each target laboratory is obtained, the total electric consumption of the electric equipment of each target laboratory is extracted, and accordingly, the use safety index corresponding to the electric equipment of each target laboratory is calculated, wherein the calculation formula is as follows:
wherein beta is j The corresponding use safety index of the electric equipment expressed as the j-th target laboratory, D j0 Total power consumption, dl, of powered equipment expressed as j-th target laboratory jr The electricity consumption corresponding to the unit on time length of the (r) electric equipment of the (j) target laboratory, SC jr "the power-on duration of the (r) electric equipment expressed as the (j) target laboratory, lambda 1 The usage safety correction factor corresponding to the set electricity consumption of the electric equipment is represented by r, wherein r is the number of each electric equipment, and r=1, 2.
7. The AI-technology-based intelligent implementation of claim 6The laboratory safety monitoring and managing method is characterized in that: the safety index corresponding to the equipment application parameters of each target laboratory is calculated according to the following formula:
wherein θ is j Safety index, Φ, expressed as the corresponding equipment application parameters of the jth target laboratory 1 And phi is 2 And the safety weight values are respectively indicated as the safety weight values corresponding to the set experimental equipment and the electric equipment.
8. The AI-technology-based intelligent laboratory security monitoring management method of claim 7, wherein: the comprehensive safety index of each target laboratory is calculated by the following formula:
wherein psi is j Expressed as the integrated safety index, phi, of the jth target laboratory 1 、φ 2 And phi 3 Respectively expressed as the corresponding weight factors of the environment parameter, the personnel behavior parameter and the equipment application parameter.
9. The AI-technology-based intelligent laboratory security monitoring management method of claim 1, wherein: the screening is carried out to obtain each risk operation laboratory, and the specific process is as follows: and comparing the comprehensive safety index of each target laboratory with a set comprehensive safety index threshold, and if the comprehensive safety index of a certain target laboratory is lower than the comprehensive safety index threshold, marking the target laboratory as a risk operation laboratory, and further counting each risk operation laboratory.
10. An AI technology-based intelligent laboratory safety monitoring management system is characterized in that: comprising the following steps:
the target laboratory acquisition module is used for acquiring each target laboratory, wherein the target laboratory is an actually put-to-use laboratory;
the target laboratory attribute acquisition module is used for acquiring the attribute of each target laboratory;
the basic parameter monitoring module of the target laboratory is used for monitoring basic parameters of each target laboratory according to the attribute of each target laboratory, wherein the basic parameters comprise environmental parameters, personnel behavior parameters and equipment application parameters;
the basic parameter analysis module of the target laboratory is used for calculating the corresponding safety indexes of the environmental parameters, the personnel behavior parameters and the equipment application parameters of each target laboratory according to the basic parameters of each target laboratory;
The comprehensive safety analysis module of the target laboratory is used for comprehensively analyzing the comprehensive safety indexes of each target laboratory according to the safety indexes corresponding to the environmental parameters, the personnel behavior parameters and the equipment application parameters of each target laboratory;
the target laboratory safety management prompt module is used for screening to obtain each risk operation laboratory according to the comprehensive safety index of each target laboratory and carrying out safety management prompt according to the risk operation laboratory;
the risk laboratory data uploading module is used for constructing a data set of each risk operation laboratory according to each risk operation laboratory obtained through screening and uploading the data set to the experimental data storage platform;
the experimental data storage platform is used for storing data sets of all risk operation laboratories;
the experimental cloud database is used for storing environment suitable basic parameters, gas allowable concentration of each type and risk behaviors of each type corresponding to various laboratory attributes, storing dangerous source reference safety intervals, storing initial quantity of experimental equipment and initial positions of the experimental equipment in each laboratory, storing allowable movement intervals of the various experimental equipment, and storing electricity consumption of unit opening time corresponding to various electric equipment.
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