CN115206042B - Intelligent monitoring method, device, equipment and medium for industrial control safety - Google Patents
Intelligent monitoring method, device, equipment and medium for industrial control safety Download PDFInfo
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Abstract
The invention discloses an intelligent monitoring method, device, equipment and medium for industrial control safety, which comprises the following steps: detecting whether a person enters an identification area corresponding to an industrial control scene; when detecting that a person enters the identification area, collecting target information corresponding to the identification area, wherein the target information comprises at least one of personnel information corresponding to the target person in the identification area, behavior information of the target person in the identification area, working state of intelligent equipment corresponding to the identification area and environment parameters corresponding to the identification area; inputting the target information into a predetermined safety coefficient identification model, and determining the safety coefficient of the target personnel in the identification area according to the model output result; and performing matched intelligent operation according to the safety coefficient. Therefore, the intelligent monitoring system can realize intelligent monitoring of industrial control safety, and is beneficial to improving the safety of cooperative work of people and intelligent equipment.
Description
Technical Field
The invention relates to the technical field of industrial control safety, in particular to an intelligent monitoring method, device, equipment and medium for industrial control safety.
Background
Along with the rapid development of related technologies such as artificial intelligence and the Internet of things, many scenes gradually replace manpower through intelligent equipment, so that the labor cost can be saved, and the corresponding efficiency, such as the production efficiency and the processing efficiency, can be improved. In practical application, because some problems (such as equipment strikes or damages caused by too high working temperature for a long time) or limitations of some environmental conditions exist in the working process of the intelligent equipment, the intelligent equipment cannot completely realize automation, and a small amount of personnel are needed to participate in the operation under the condition, so that the working reliability of the intelligent equipment can be improved to a certain extent while the labor cost is saved and the efficiency is improved through the cooperation of a small amount of manpower and the intelligent equipment.
However, in some scenes with complex environments or low safety factors, the personnel involved in the control process of the intelligent equipment can have some dangers, and the safety of the cooperation of the personnel and the intelligent equipment is reduced. It is important to realize intelligent monitoring of industrial control safety to improve the safety of cooperative work between people and intelligent equipment.
Disclosure of Invention
The invention provides an intelligent monitoring method, device, equipment and medium for industrial control safety, which can realize intelligent monitoring of industrial control safety so as to improve the safety of cooperative work of people and intelligent equipment.
The first aspect of the invention discloses an intelligent monitoring method for industrial control safety, which comprises the following steps:
detecting whether a person enters an identification area corresponding to an industrial control scene;
when a person is detected to enter an identification area, collecting target information corresponding to the identification area, wherein the target information comprises at least one of person information corresponding to a target person in the identification area, behavior information of the target person in the identification area, working state of intelligent equipment corresponding to the identification area and environment parameters corresponding to the identification area;
inputting the target information into a predetermined safety coefficient identification model, and determining the safety coefficient of the target person in the identification area according to a model output result;
and executing matched intelligent operation according to the safety coefficient.
The second aspect of the invention discloses an intelligent monitoring device for industrial control safety, which comprises:
the detection module is used for detecting whether a person enters an identification area corresponding to the industrial control scene;
the acquisition module is used for acquiring target information corresponding to the identification area when the detection module detects that a person enters the identification area, wherein the target information comprises at least one of personnel information corresponding to the target person in the identification area, behavior information of the target person in the identification area, working state of intelligent equipment corresponding to the identification area and environment parameters corresponding to the identification area;
the safety coefficient determining module is used for inputting the target information into a predetermined safety coefficient identification model and determining the safety coefficient of the target personnel in the identification area according to a model output result;
and the industrial control module is used for executing matched intelligent operation according to the safety coefficient.
The third aspect of the invention discloses another industrial control safety intelligent monitoring device, which comprises:
a memory storing executable program code;
a processor coupled to the memory;
the processor calls the executable program code stored in the memory to execute part or all of the steps in the intelligent monitoring method for industrial control safety disclosed in the first aspect of the invention.
In a fourth aspect, the present invention discloses a computer storage medium, where computer instructions are stored, where the computer instructions are used to execute part or all of the steps in the intelligent monitoring method for industrial control security disclosed in the first aspect of the present invention when the computer instructions are called.
Compared with the prior art, the invention has the following beneficial effects:
detecting whether a person enters an identification area corresponding to an industrial control scene; when detecting that a person enters the identification area, collecting target information corresponding to the identification area, wherein the target information comprises at least one of personnel information corresponding to the target person in the identification area, behavior information of the target person in the identification area, working state of intelligent equipment corresponding to the identification area and environment parameters corresponding to the identification area; inputting the target information into a predetermined safety coefficient identification model, and determining the safety coefficient of the target personnel in the identification area according to the model output result; and performing matched intelligent operation according to the safety coefficient. Therefore, the intelligent monitoring system can realize intelligent monitoring of industrial control safety, and is beneficial to improving the safety of cooperative work of people and intelligent equipment; in addition, the matched operation can be executed according to the determined safety coefficient, specifically, when the safety coefficient is smaller, the protection operation is intelligently executed, and when the safety coefficient is not smaller, the potential risk factor early warning operation is executed, so that the intelligent monitoring control function of industrial control safety is further enriched, the safety of an identification area can be ensured when the safety coefficient is lower, the potential risk factor can be early warned when the safety coefficient is not lower, the safety accident occurrence probability in an industrial control scene is reduced, and the safety of the industrial control scene is further improved; in addition, the matched operation can be further executed according to the controllable influence factors or the uncontrollable influence factors, so that the reliability of industrial control safety is improved; in addition, the potential risk factors matched with the target personnel can be screened out from all the analyzed risk factors, so that the accuracy of the determined potential risk factors can be improved while the comprehensiveness of the potential risk factors is ensured; in addition, the safety coefficient can be determined based on the model output result of the safety coefficient identification model matched with the target personnel, so that the targeted personalized determination of the safety coefficient can be realized, and the accuracy of the determined safety coefficient of the industrial control scene can be further improved; in addition, when a plurality of persons exist in the identification area, the target person can be determined based on the behavior leading proportion, so that the reliability of the determined target person is improved, and the accuracy of the safety coefficient is improved; in addition, the behavior leading ratio can be analyzed based on the relevant parameters of the behavior leading ratio, so that an intelligent determination mode of the behavior leading ratio is provided, the accuracy of the behavior leading ratio is improved, and the accuracy of the safety coefficient is improved.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings required for the description of the embodiments will be briefly described below, and it is apparent that the drawings in the following description are only some embodiments of the present invention, and other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
FIG. 1 is a schematic flow chart of an intelligent monitoring method for industrial control safety, disclosed in the embodiment of the invention;
FIG. 2 is a schematic flow chart of another intelligent monitoring method for industrial control safety according to an embodiment of the present invention;
FIG. 3 is a schematic structural diagram of an intelligent monitoring device for industrial control safety according to an embodiment of the present invention;
fig. 4 is a schematic structural diagram of another industrial control safety intelligent monitoring device according to an embodiment of the present invention.
Detailed Description
In order that those skilled in the art will better understand the present invention, a technical solution in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in which it is apparent that the described embodiments are only some embodiments of the present invention, 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.
The terms first, second and the like in the description and in the claims and in the above-described figures are used for distinguishing between different objects and not necessarily for describing a sequential or chronological order. Furthermore, the terms "comprise" and "have," as well as any variations thereof, are intended to cover a non-exclusive inclusion. For example, a process, method, apparatus, article, port, or end that comprises a list of steps or elements is not limited to only those listed steps or elements but may include other steps or elements not listed or inherent to such process, method, article, port, or end.
Reference herein to "an embodiment" means that a particular feature, structure, or characteristic described in connection with the embodiment may be included in at least one embodiment of the invention. The appearances of such phrases in various places in the specification are not necessarily all referring to the same embodiment, nor are separate or alternative embodiments mutually exclusive of other embodiments. Those of skill in the art will explicitly and implicitly appreciate that the embodiments described herein may be combined with other embodiments.
The invention discloses an intelligent monitoring method and device for industrial control safety, which can realize intelligent monitoring for industrial control safety and is beneficial to improving the safety of cooperative work of people and intelligent equipment; in addition, the matched operation can be executed according to the determined safety coefficient, so that the safety of the industrial control scene is further guaranteed. The following will describe in detail.
Example 1
Referring to fig. 1, fig. 1 is a schematic flow chart of an intelligent monitoring method for industrial control safety according to an embodiment of the invention. The method described in fig. 1 may be applied to an industrial control safety monitoring device, where the industrial control safety monitoring device may be integrated in an intelligent device in an industrial control scene, or may be integrated in a management server corresponding to the industrial control scene, where the management server may be a local server or a cloud server, and the embodiment of the present invention is not limited. As shown in fig. 1, the intelligent monitoring method for industrial control safety may include the following operations:
s101, detecting whether a person enters an identification area corresponding to the industrial control scene.
The identification area corresponding to the industrial control scene can be any identification area corresponding to the industrial control scene, or can be any identification area in a key identification area (such as an identification area with potential safety hazard or an identification area where people and intelligent equipment are required to work cooperatively) corresponding to the industrial control scene.
S102, when a person is detected to enter the identification area, acquiring target information corresponding to the identification area.
The target information includes at least one of personnel information (such as personnel gender, personnel name, etc.) corresponding to the target personnel in the identification area, behavior information of the target personnel in the identification area, working state of intelligent equipment corresponding to the identification area, and environmental parameters (such as temperature, gas concentration, etc.) corresponding to the identification area.
The target person in the identification area may be any person, part of the person or all the person in the identification area, and the number and the determination manner of the target person are not limited in the embodiment of the invention.
S103, inputting the target information into a predetermined safety coefficient identification model, and determining the safety coefficient of the target personnel in the identification area according to the model output result.
The safety coefficient identification model is a pre-trained model. Alternatively, the security factor may be a security score or a security level. The model output result may be the security coefficient itself or identification data having an association relationship with the security coefficient, and the corresponding security coefficient may be determined according to the association relationship.
The safety coefficient identification model is obtained by training a preset machine learning model based on target information corresponding to different sample identification areas and corresponding standard safety coefficients. The sample identification area may be the same as or different from the collected identification area, which is not limited in any way in the embodiment of the present invention. The standard safety coefficient can be obtained by manual labeling of a technician. The machine learning model can be obtained by adopting at least one model combination in the prior art, and the network structure of the machine learning model is not limited in the embodiment of the invention.
For example, the same safety coefficient recognition model can be trained and obtained aiming at the target personnel in the same category; different safety coefficient recognition models are trained and obtained aiming at different types of target personnel, so that the accuracy of the safety coefficient determination result of the safety coefficient recognition model aiming at a certain type of target personnel is improved.
Correspondingly, when the same safety coefficient recognition model is obtained by training the same class of target personnel, only the target information generated by the same class of personnel as the target personnel in the sample area can be used as a training sample, the corresponding standard safety coefficient is used as a training label, the pre-constructed machine learning model is trained, and the trained machine learning model is used as the safety coefficient recognition model corresponding to the class of target personnel.
It should be noted that the corresponding machine learning models of different safety factor recognition models in the training phase may be the same or different, which is not limited in any way by the embodiment of the present invention.
Correspondingly, selecting a safety coefficient identification model corresponding to the target personnel according to personnel information corresponding to the target personnel; and inputting the target information into a safety coefficient identification model corresponding to the target personnel, and determining the safety coefficient according to the output result of the model.
The embodiment of the invention can determine the safety coefficient based on the safety coefficient identification model matched with the target personnel, is beneficial to realizing the targeted and personalized determination of the safety coefficient determination result, and can also improve the accuracy of the safety coefficient of the industrial control scene.
S104, performing matched intelligent operation according to the safety coefficient.
Therefore, the method described by the embodiment of the invention can realize intelligent monitoring of industrial control safety, and is beneficial to improving the safety of cooperative work of people and intelligent equipment; in addition, the matched operation can be executed according to the determined safety coefficient.
In an alternative embodiment, the above-mentioned intelligent operation of performing matching according to the security coefficient may include: if the safety coefficient is smaller than or equal to a preset safety coefficient threshold value, determining an influence factor influencing the safety coefficient, and executing matched protection operation according to the influence factor; if the safety coefficient is larger than a preset safety coefficient threshold value, determining potential risk factors in the identification area, and outputting early warning prompts corresponding to the potential risk factors.
The preset safety coefficient threshold value can be set or adjusted by a technician according to requirements. The invention does not limit the value of the preset safety coefficient threshold value.
Wherein, the influencing factor can be understood as a factor which can influence safety but usually does not have safety accidents; the potential risk factor may be understood as a factor that can affect safety and has a high probability of occurrence of a safety accident.
It can be seen that this optional embodiment can also be when factor of safety is less (if aforesaid is less than or equal to preset factor of safety threshold value), intelligent execution protection operation, when factor of safety is great (if aforesaid is greater than preset factor of safety threshold value), carry out potential risk factor early warning operation, further richen the intelligent monitoring control function of industrial control safety, not only can guarantee the security of discernment region when factor of safety is less, can also carry out the early warning to potential risk factor when factor of safety is great, reduce the incident probability of occurrence in the industrial control scene, be favorable to further improving the security of industrial control scene.
In this optional embodiment, further optionally, performing the matched protection operation according to the impact factor may include: if the influence factor is a controllable influence factor, outputting a dangerous early warning and/or adjusting working parameters of corresponding intelligent equipment and/or starting auxiliary intelligent equipment in the environment where the identification area is located;
if the influence factor is an uncontrollable influence factor, when the security level is smaller than or equal to the security level threshold, starting an industrial control security mechanism corresponding to the environment where the identification area is located, for example, closing the industrial control security mechanisms of all intelligent devices, or opening the regional barrier industrial control security mechanism.
It can be seen that this alternative embodiment can further perform the matching operation according to the controllable influence factor or the uncontrollable influence factor, which is beneficial to improving the reliability of industrial control safety.
In this alternative embodiment, still further alternatively, the determining the potential risk factor in the identified area may include: determining an intelligent equipment set in a working state in an environment where an identification area is located; determining each risk factor in the environment where the identification area is located according to the current working state of each intelligent device in the intelligent device set; and selecting potential risk factors corresponding to the target personnel from the risk factors according to at least one of personnel information corresponding to the target personnel, behavior information of the target personnel in the identification area and environment parameters corresponding to the identification area.
For example, the current operating state of the intelligent device may include an operating state and a non-operating state. Wherein, the non-working state can be an idle state, a power-off state, a maintenance state and the like; the working state may include an intermittent working state, a continuous working state, and the like. Correspondingly, adding the intelligent equipment in the working state in the environment where the identification area is located into an intelligent equipment set, and aiming at each intelligent equipment in the intelligent equipment set, taking factors which possibly generate potential safety hazards as dangerous factors when the intelligent equipment works in the environment where the identification area is located; according to personnel information such as the work types of the target personnel, corresponding behavior information such as the working behaviors of the target personnel in the identification area and environmental parameters such as the placed articles and weather conditions in the identification area, potential risk factors threatening the safety of the target personnel are selected from at least one risk factor, so that the determined potential risk factors have more personnel pertinence. Specifically, the association relationship between the personnel information, the behavior information and the environment parameters of the identification area of different target personnel and the potential risk factors can be preset, and the potential risk factors matched with the personnel information, the behavior information and the environment parameters of the identification area of the target personnel can be determined according to the association relationship.
It can be seen that the alternative embodiment can also screen out potential risk factors matched with the target person from all the analyzed risk factors, so that the accuracy of the determined potential risk factors can be improved while the comprehensiveness of the potential risk factors is ensured.
Example two
Referring to fig. 2, fig. 2 is a flow chart of another intelligent monitoring method for industrial control security according to an embodiment of the present invention. The method described in fig. 2 may be applied to an industrial control safety monitoring device, where the industrial control safety monitoring device may be integrated in an intelligent device in an industrial control scene, or may be integrated in a management server corresponding to the industrial control scene, where the management server may be a local server or a cloud server, and the embodiment of the present invention is not limited. As shown in fig. 2, the intelligent monitoring method of industrial control safety may include the following operations:
s201, detecting whether a person enters an identification area corresponding to the industrial control scene.
S202, when detecting that a person enters the identification area, determining the number of persons of all persons entering the identification area.
Wherein, the target detection technology can be adopted to determine the personnel number of all personnel entering the identification area; or the number of passing people can be counted by arranging a sensor at the entrance. Of course, the number of people may be determined in other manners in the prior art, and the comparison of the embodiment of the present invention is not limited in any way.
And S203, when the number of the personnel is greater than or equal to a preset number threshold, determining the behavior leading proportion of each personnel in the identification area.
Wherein the behavior dominance is used to represent the importance of the person's behavior in the recognition area.
S204, determining one person with the largest behavior dominant ratio in the identification area as a target person.
S205, collecting target information corresponding to the identification area.
The target information comprises at least one of personnel information corresponding to target personnel in the identification area, behavior information of the target personnel in the identification area, working states of intelligent equipment corresponding to the identification area and environment parameters corresponding to the identification area.
S206, inputting the target information into a predetermined safety factor identification model, and determining the safety factor of the target personnel in the identification area according to the model output result.
S207, performing matched intelligent operation according to the safety coefficient.
Therefore, when a plurality of persons exist in the identification area, the method can determine the target person based on the behavior leading ratio, and is beneficial to improving the reliability of the determined target person and further beneficial to improving the accuracy of the safety coefficient.
In an alternative embodiment, the determining the dominant ratio of the behaviors of each person in the identification area may include: for each person, collecting target parameters for determining the dominant ratio of the behavior of the person in the identification area, wherein the target parameters comprise at least one of a person type corresponding to the person, a time length for entering the identification area, a frequency for entering the identification area in a preset time period, a time period in which the current time is positioned, and intelligent equipment information in a working state in an environment in which the identification area is positioned; and determining the behavior leading proportion of the person in the identification area according to the target parameters corresponding to the person.
For example, a corresponding duty grade score may be set for each target parameter, and a weighted sum of the duty grade scores corresponding to different target parameters may be used as the final determined dominant duty parameter. The highest duty ratio grade score of different target parameters can be preset by a technician according to the needs or experience values, and the scores of the highest duty ratio grade scores of different regions are set according to different grades.
It can be seen that the optional embodiment can also analyze the behavior dominance based on the relevant parameters of the behavior dominance, which not only provides an intelligent determination mode of the behavior dominance, but also is beneficial to improving the accuracy of the behavior dominance, and further is beneficial to improving the accuracy of the safety coefficient.
Example III
Referring to fig. 3, fig. 3 is a schematic structural diagram of an intelligent monitoring device for industrial control safety according to an embodiment of the present invention. The device described in fig. 3 may be integrated in an intelligent device in an industrial control scene, or may be integrated in a management server corresponding to the industrial control scene, where the management server may be a local server or a cloud server, and the embodiment of the present invention is not limited. As shown in fig. 3, the intelligent monitoring device for industrial control safety may include:
the detection module 301 is configured to detect whether a person enters an identification area corresponding to an industrial control scene;
the acquisition module 302 is configured to acquire, when the detection module 301 detects that a person enters the identification area, target information corresponding to the identification area, where the target information includes at least one of person information corresponding to a target person in the identification area, behavior information of the target person in the identification area, a working state of an intelligent device corresponding to the identification area, and an environmental parameter corresponding to the identification area;
the safety factor determining module 303 is configured to input the target information to a predetermined safety factor recognition model, and determine a safety factor of the target person in the recognition area according to a model output result;
and the industrial control module 304 is used for executing matched intelligent operation according to the safety coefficient.
Therefore, the implementation of the device described in fig. 3 can realize intelligent monitoring of industrial control safety, and is beneficial to improving the safety of cooperative work of people and intelligent equipment; in addition, the matched operation can be executed according to the determined safety coefficient.
In an alternative embodiment, the industrial control module 304 may include:
the influence factor determining unit is used for determining an influence factor influencing the safety coefficient if the safety coefficient is smaller than or equal to a preset safety coefficient threshold value and executing matched protection operation according to the influence factor;
the potential risk factor determining unit is used for determining potential risk factors in the identification area and outputting early warning prompts corresponding to the potential risk factors if the safety coefficient is larger than a preset safety coefficient threshold value.
Therefore, the optional embodiment intelligently executes the protection operation when the safety coefficient is smaller, executes the potential risk factor early warning operation when the safety coefficient is not smaller, further enriches the intelligent monitoring control function of industrial control safety, not only can ensure the safety of the identification area when the safety coefficient is lower, but also can early warn the potential risk factor when the safety coefficient is not lower, reduces the occurrence probability of safety accidents in the industrial control scene, and is beneficial to further improving the safety of the industrial control scene.
In this alternative embodiment, a further alternative influence factor determining unit may include:
the controllable response subunit is used for outputting dangerous early warning and/or adjusting working parameters of corresponding intelligent equipment and/or starting auxiliary intelligent equipment in the environment where the identification area is located if the influence factor is the controllable influence factor;
and the uncontrollable response subunit is used for starting an industrial control safety mechanism corresponding to the environment where the identification area is located when the safety level is smaller than or equal to the safety level threshold value if the influence factor is the uncontrollable influence factor.
It can be seen that this alternative embodiment can further perform the matching operation according to the controllable influence factor or the uncontrollable influence factor, which is beneficial to improving the reliability of industrial control safety.
Further alternatively, the potential risk factor determining unit may include:
the intelligent equipment set determining subunit is used for determining an intelligent equipment set in a working state in an environment where the identification area is located;
the risk factor determining subunit is used for determining each risk factor in the environment where the identification area is located according to the current working state of each intelligent device in the intelligent device set;
the potential risk factor selecting subunit is configured to select, from the risk factors, a potential risk factor corresponding to the target person according to at least one of personnel information corresponding to the target person, behavior information of the target person in the identification area, and environmental parameters corresponding to the identification area.
It can be seen that the alternative embodiment can also screen out potential risk factors matched with the target person from all the analyzed risk factors, so that the accuracy of the determined potential risk factors can be improved while the comprehensiveness of the potential risk factors is ensured.
In another alternative embodiment, the security coefficient determining module 303 may include:
the model selecting unit is used for selecting a safety coefficient identification model corresponding to the target personnel according to personnel information corresponding to the target personnel;
and the model use unit is used for inputting the target information into the safety coefficient identification model corresponding to the target personnel.
Therefore, the optional embodiment can also determine the safety coefficient based on the safety coefficient identification model matched with the target personnel, thereby being beneficial to realizing the targeted and personalized determination of the safety coefficient and further improving the accuracy of the determined safety coefficient of the industrial control scene.
In yet another alternative embodiment, the apparatus may further include:
and the personnel number determining module is used for determining the personnel number of all personnel entering the identification area after detecting that the personnel enter the identification area.
The behavior leading duty ratio determining module is used for determining the behavior leading duty ratio of each person in the identification area when the number of the persons is larger than or equal to a preset number threshold value;
and the personnel determining module is used for determining one of the personnel with the largest behavior dominant ratio in the identification area as the target personnel.
It can be seen that, this optional embodiment can also be when there are a plurality of personnel in the discernment region, can confirm the target personnel based on the dominant ratio of behavior, is favorable to improving the reliability of the target personnel who confirms, and then is favorable to improving factor of safety's accuracy.
In yet another alternative embodiment, the behavior dominance duty cycle determination module may include:
the data acquisition unit is used for acquiring target parameters for determining the behavior leading ratio of each person in the identification area, wherein the target parameters comprise at least one of a person type corresponding to the person, duration of entering the identification area, frequency of entering the identification area in a preset time period, time period of the current time and intelligent equipment information in a working state in an environment of the identification area;
and the behavior leading duty ratio determining subunit is used for determining the behavior leading duty ratio of the person in the identification area according to the target parameter corresponding to the person.
It can be seen that the optional embodiment can also analyze the behavior dominance based on the relevant parameters of the behavior dominance, which not only provides an intelligent determination mode of the behavior dominance, but also is beneficial to improving the accuracy of the behavior dominance, and further is beneficial to improving the accuracy of the safety coefficient.
Example IV
Referring to fig. 4, fig. 4 is a schematic structural diagram of another industrial control safety intelligent monitoring device according to an embodiment of the present invention. The device described in fig. 4 may be integrated in an intelligent device in an industrial control scene, or may be integrated in a management server corresponding to the industrial control scene, where the management server may be a local server or a cloud server, and the embodiment of the present invention is not limited. As shown in fig. 4, the intelligent monitoring device for industrial control safety may include:
a memory 401 storing executable program codes;
a processor 402 coupled with the memory 401;
the processor 402 invokes executable program codes stored in the memory 401 to perform some or all of the steps in the intelligent monitoring method for industrial control security disclosed in the first or second embodiment of the present invention.
Example five
The embodiment of the invention discloses a computer storage medium which stores computer instructions, wherein the computer instructions are used for executing part or all of the steps in the intelligent monitoring method for industrial control safety disclosed in any embodiment of the invention when the computer instructions are called.
The apparatus embodiments described above are merely illustrative, wherein the modules illustrated as separate components may or may not be physically separate, and the components shown as modules may or may not be physical, i.e., may be located in one place, or may be distributed over a plurality of network modules. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of this embodiment. Those of ordinary skill in the art will understand and implement the present invention without undue burden.
From the above detailed description of the embodiments, it will be apparent to those skilled in the art that the embodiments may be implemented by means of software plus necessary general hardware platforms, or of course by means of hardware. Based on such understanding, the foregoing technical solutions may be embodied essentially or in part in the form of a software product that may be stored in a computer-readable storage medium including Read-Only Memory (ROM), random-access Memory (Random Access Memory, RAM), programmable Read-Only Memory (Programmable Read-Only Memory, PROM), erasable programmable Read-Only Memory (Erasable Programmable Read Only Memory, EPROM), one-time programmable Read-Only Memory (OTPROM), electrically erasable programmable Read-Only Memory (EEPROM), compact disc Read-Only Memory (Compact Disc Read-Only Memory, CD-ROM) or other optical disc Memory, magnetic disc Memory, tape Memory, or any other medium that can be used for computer-readable carrying or storing data.
Finally, it should be noted that: the embodiment of the invention discloses an industrial control safety intelligent monitoring method and device, which are disclosed by the embodiment of the invention only as a preferred embodiment of the invention, and are only used for illustrating the technical scheme of the invention, but not limiting the technical scheme; although the invention has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art will understand that; the technical scheme recorded in the various embodiments can be modified or part of technical features in the technical scheme can be replaced equivalently; such modifications and substitutions do not depart from the spirit and scope of the corresponding technical solutions.
Claims (8)
1. An intelligent monitoring method for industrial control safety is characterized by comprising the following steps:
detecting whether a person enters an identification area corresponding to an industrial control scene;
when detecting that a person enters an identification area, collecting target information corresponding to the identification area, wherein the target information comprises personnel information corresponding to a target person in the identification area, behavior information of the target person in the identification area, working states of intelligent equipment corresponding to the identification area and environment parameters corresponding to the identification area;
inputting the target information into a predetermined safety coefficient identification model, and determining the safety coefficient of the target person in the identification area according to a model output result;
performing matched intelligent operation according to the safety coefficient;
wherein the method further comprises:
after detecting that a person enters the identification area, determining the number of persons of all persons entering the identification area;
when the number of the personnel is greater than or equal to a preset number threshold, collecting target parameters for determining the behavior leading proportion of the personnel in the identification area for each personnel, wherein the target parameters comprise the personnel type corresponding to the personnel, the duration of entering the identification area, the frequency of entering the identification area in a preset time period, the time period of the current time and the intelligent equipment information in a working state in the environment of the identification area;
taking the weighted sum of the corresponding duty grade scores of different target parameters of the person as the dominant duty parameters of the person in the identification area, and determining the dominant duty of the behavior based on the dominant duty parameters of the behavior;
and determining one of the persons with the largest behavior dominant ratio in the identification area as a target person.
2. The intelligent monitoring method for industrial control safety according to claim 1, wherein the performing the matched intelligent operation according to the safety factor comprises:
if the safety coefficient is smaller than or equal to a preset safety coefficient threshold value, determining an influence factor influencing the safety coefficient, and executing matched protection operation according to the influence factor;
if the safety coefficient is larger than the preset safety coefficient threshold, determining potential risk factors in the identification area, and outputting early warning prompts corresponding to the potential risk factors.
3. The intelligent monitoring method of industrial control safety according to claim 2, wherein the performing the matched guard operation according to the influence factor comprises:
if the influence factor is a controllable influence factor, outputting a danger early warning and/or adjusting working parameters of corresponding intelligent equipment and/or starting auxiliary intelligent equipment in the environment where the identification area is located;
if the influence factor is an uncontrollable influence factor, when the safety coefficient is smaller than or equal to the preset safety coefficient threshold value, starting an industrial control safety mechanism corresponding to the environment where the identification area is located.
4. The intelligent monitoring method of industrial control safety according to claim 2, wherein the determining potential risk factors in the identification area comprises:
determining an intelligent equipment set in a working state in an environment where the identification area is located;
determining each risk factor in the environment where the identification area is located according to the current working state of each intelligent device in the intelligent device set;
and selecting potential risk factors corresponding to the target personnel from the risk factors according to at least one of personnel information corresponding to the target personnel, behavior information of the target personnel in the identification area and environment parameters corresponding to the identification area.
5. The intelligent monitoring method of industrial control safety according to any one of claims 1 to 4, wherein the inputting the target information into a predetermined safety factor recognition model comprises:
selecting a safety coefficient identification model corresponding to the target personnel according to personnel information corresponding to the target personnel; and inputting the target information into a safety coefficient identification model corresponding to the target personnel.
6. An intelligent monitoring device for industrial control safety, characterized in that the device comprises:
the detection module is used for detecting whether a person enters an identification area corresponding to the industrial control scene;
the acquisition module is used for acquiring target information corresponding to the identification area when the detection module detects that a person enters the identification area, wherein the target information comprises personnel information corresponding to the target person in the identification area, behavior information of the target person in the identification area, working states of intelligent equipment corresponding to the identification area and environment parameters corresponding to the identification area;
the safety coefficient determining module is used for inputting the target information into a predetermined safety coefficient identification model and determining the safety coefficient of the target personnel in the identification area according to a model output result;
the industrial control module is used for executing matched intelligent operation according to the safety coefficient;
wherein the apparatus further comprises:
the personnel number determining module is used for determining the personnel number of all personnel entering the identification area after detecting that the personnel enter the identification area;
the system comprises a behavior leading proportion determining module, a data acquisition unit, a data processing unit and a data processing unit, wherein the behavior leading proportion determining module is used for acquiring target parameters for determining the behavior leading proportion of each person in an identification area when the number of the persons is greater than or equal to a preset number threshold, wherein the target parameters comprise the type of the person corresponding to the person, the duration of entering the identification area, the frequency of entering the identification area in a preset time period, the time period in which the current time is located and intelligent equipment information in a working state in the environment in which the identification area is located;
the behavior leading duty ratio determining subunit in the behavior leading duty ratio determining module is used for taking the weighted sum of the corresponding duty ratio grade scores of different target parameters of the person as the leading duty ratio parameter of the person in the identification area and determining the behavior leading duty ratio based on the behavior duty ratio parameter;
and the personnel determining module is used for determining one of the personnel with the largest behavior leading proportion in the identification area as the target personnel.
7. An intelligent monitoring device for industrial control safety, the device comprising:
a memory storing executable program code;
a processor coupled to the memory;
the processor invokes the executable program code stored in the memory to perform the intelligent monitoring method of industrial control safety as claimed in any one of claims 1 to 5.
8. A computer storage medium storing computer instructions which, when invoked, are adapted to perform the intelligent monitoring method of industrial control security as claimed in any one of claims 1 to 5.
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