Industrial production safety risk assessment equipment based on deep learning

Abstract

The invention discloses industrial production safety risk assessment equipment based on deep learning, and the equipment comprises detection equipment which is used for carrying industrial production safety risk factor collection hardware. The acquisition assembly comprises an environment acquisition assembly and a display assembly, and the environment acquisition assembly and the display assembly are matched to perform data acquisition on the industrial production safety risk; and the control algorithm performs risk assessment on the acquisition assembly through a neural network algorithm and outputs an assessment report, and relates to the technical field of industrial production safety risk assessment. Environmental safety data in the industrial production process are collected through an environment collection assembly in the collection assembly, then neural network learning is carried out on the environment collection data through a control algorithm, existing factors in the environment can be recognized, and then safety evaluation is carried out on the existing factors based on the neural network algorithm, so that the safety of the industrial production process is improved. The safety coefficient of the collected environmental objects can be evaluated, and personnel can be reminded of safe production.

Description

Technical Field

[0001] The present invention relates to the technical field of industrial production safety risk assessment, and in particular to an industrial production safety risk assessment device based on deep learning. Background Art

[0002] In industrial production, due to the involvement of various equipment, processes, materials and other factors, there are various potential safety risks, such as fire, explosion, chemical leakage, mechanical injury, etc. Through safety risk assessment, industrial production safety risk assessment refers to the process of systematically identifying, analyzing and evaluating various safety risks that may occur in the industrial production process. Its main purpose is to prevent accidents and reduce the probability of accidents, ensure the safety of production personnel and equipment, and protect the safety of the environment. It can systematically analyze and evaluate the severity, possibility and scope of impact of these potential risks, so as to formulate corresponding safety management measures and preventive measures to reduce the possibility of accidents and improve the safety and reliability of the production process.

[0003] The patent with publication number CN116094830A discloses a risk assessment method, device and readable storage medium. The patent specifically discloses that "the present application relates to a risk assessment method, device and readable storage medium. The risk assessment method comprises the following steps: constructing a domain library, the domain library is used to divide the object to be evaluated into at least one security domain according to the security identification data of the object to be evaluated, the security identification data includes at least one of the security name, security attribute and positioning; presetting multiple risk scenarios, the risk scenarios are obtained by classifying the network security incidents that have occurred; presetting the matching relationship between the risk scenario and the security domain, each security domain matches at least one risk scenario;" the technical scheme realizes "dividing the object to be evaluated into at least one security domain according to the domain library; identifying the risk elements of the risk scenario matched by each security domain in the object to be evaluated, the risk elements include threat sources, vulnerabilities and the effectiveness of security measures; evaluating the risk of the object to be evaluated according to the risk elements. The present application has the technical effect of being able to intuitively display security threats and having a larger evaluation granularity."

[0004] However, this patent cannot be effectively applied in industrial production and cannot be quickly replaced and applied in industrial production.

[0005] Therefore, the patent with publication number CN114629674A discloses an industrial control network security risk assessment method based on the attention mechanism. The patent specifically discloses the following technical scheme: "The present invention discloses an industrial control network security risk assessment method based on the attention mechanism. First, various data information in the industrial control network to be tested is obtained, and structured processing is performed on it to form a structured database; based on the structured database, the industrial control network nodes are defined, and the association relationship between the nodes is established to form a security risk assessment graph database containing various information of the industrial control network; the attention mechanism is used to establish a risk assessment model for various industrial control network scenarios; the data of the security risk assessment graph database is input into the established risk assessment model to obtain the key elements and comprehensive risk scores of the industrial control network to be tested, so as to realize the security risk assessment of the industrial control network to be tested." The technical effect of "the above method can actively analyze the security risks existing in the network, and take appropriate measures to reduce the security risks of the network according to the analysis results, and can take reasonable protection measures and repair methods."

[0006] However, in actual use, the patent adopts a means of safety risk control based on attention, which is a passive and subsequent safety risk control method. The patent cannot actively intervene in the work safety environment of personnel to conduct preemptive safety risk warnings, and there is room for improvement. Summary of the invention

[0007] The purpose of the present invention is to provide an industrial production safety risk assessment device based on deep learning to solve the problems raised in the above background technology.

[0008] To achieve the above-mentioned purpose, the present invention provides the following technical solutions: an industrial production safety risk assessment device based on deep learning, comprising a detection device, which is used to carry hardware for collecting industrial production safety risk factors; a collection component, which includes an environment collection component and a display component, and the environment collection component and the display component cooperate to collect data on industrial production safety risks; and a control algorithm, which performs risk assessment on the collection component through a neural network algorithm and outputs an assessment report.

[0009] Methods for using industrial production safety risk assessment equipment based on deep learning, including

[0010] Step S1: The detection device enters the industrial production site, and adjusts the angle of the environment collection component through the activity of the transmission component or the mechanical adjustment group, so that the environment collection component can collect environmental data from different spatial positions;

[0011] Step S2: the environment collection component analyzes the collected environment data through a control algorithm;

[0012] Step S3: The control algorithm generates a data report of the environment acquisition component.

[0013] As a further solution of the present invention: an industrial production safety risk assessment device based on deep learning, the detection device includes a device base and a mechanical adjustment group, the mechanical adjustment group is rotatably connected to the device base through a transmission component, and the environment collection component or the display component is fixedly connected to the mechanical adjustment group.

[0014] As a further solution of the present invention: an industrial production safety risk assessment device based on deep learning, the mechanical adjustment group includes a first connecting plate, a hinge, a second connecting plate, a sleeve and an equipment seat, the second connecting plate is hinged to the first connecting plate by a hinge, the sleeve is movably connected to the second connecting plate, the equipment seat is fixedly connected to the sleeve, the environment collection component is fixedly connected to the second connecting plate, and the display component is fixedly connected to the equipment seat.

[0015] As a further solution of the present invention: an industrial production safety risk assessment device based on deep learning, the transmission assembly includes a rotating shaft, a sleeve, a driven gear, a driving gear, a connecting shaft and a servo motor 1, the rotating shaft is rotatably connected to the equipment base, the sleeve is fixedly connected to the rotating shaft, the driven gear is fixedly connected to the rotating shaft, the servo motor 1 is fixedly installed on one side of the equipment base, the output end of the servo motor 1 passes through the equipment base and is fixedly connected to the connecting shaft, the driving gear is fixedly connected to the connecting shaft, and the driving gear is meshingly connected to the driven gear.

[0016] As a further solution of the present invention: the industrial production safety risk assessment equipment based on deep learning also includes a stabilizing component, which includes a stabilizing seat, a contact rod, a lead screw, a lead screw nut and a mounting plate, the mounting plate is fixedly connected to the equipment base, one end of the lead screw is rotatably connected to the mounting plate, and the other end is rotatably connected to the equipment base, the lead screw nut is fixedly connected to the stabilizing seat, the lead screw nut is movably connected to the lead screw, the contact rod is fixedly connected to the stabilizing seat, and the contact rod is movably connected to the first connecting plate.

[0017] As a further solution of the present invention: the industrial production safety risk assessment equipment based on deep learning also includes a display adjustment component, which includes a rotating gear, a rack and a servo motor 2. The servo motor 2 is fixedly connected to the second connecting plate, and the output end of the servo motor 2 is fixedly connected to the rotating gear, one end of the rack is fixedly connected to the sleeve, and the other end is movably connected to the second connecting plate, and the rotating gear is meshingly connected to the rack.

[0018] As a further solution of the present invention: the industrial production safety risk assessment equipment based on deep learning also includes a planning component, which is arranged on one side of the equipment base and provides a collision alarm when the equipment base is moving.

[0019] As a further solution of the present invention: an industrial production safety risk assessment device based on deep learning, wherein one side of the device base is rotatably connected to a walking wheel.

[0020] Compared with the prior art, the present invention has the following beneficial effects:

[0021] 1. This application collects environmental safety data in the industrial production process through the environmental collection component in the collection component, and then uses the control algorithm to perform neural network learning on the environmental collection data, which can identify the factors in the environment, and then through the safety assessment of the factors based on the neural network algorithm, the safety factor of the collected environmental objects can be evaluated to remind personnel to work safely;

[0022] 2. Use the environment acquisition component to simulate and evaluate objects in the three-dimensional space of the production process, including processing equipment, processing objects, roads, movable and fixed objects in the space where personnel are located, and personnel positions, and score the evaluated objects. The higher the score, the safer it is (scoring includes priority, movable objects have lower scores than fixed objects, and small objects have lower scores than large objects). Then, use the scoring to conduct a safety assessment of the space mainly near personnel, and generate an assessment report to remind personnel to pay attention to environmental safety. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] Figure 1 It is a schematic diagram of the structure of the equipment in the industrial production safety risk assessment equipment based on deep learning of the present invention;

[0024] Figure 2 It is a structural schematic diagram of a transmission component in an industrial production safety risk assessment device based on deep learning of the present invention;

[0025] Figure 3 It is a structural schematic diagram of a stabilizing component in an industrial production safety risk assessment device based on deep learning of the present invention;

[0026] Figure 4 It is a structural schematic diagram of the equipment base in the industrial production safety risk assessment equipment based on deep learning of the present invention;

[0027] Figure 5 The present invention is an industrial production safety risk assessment device based on deep learning Figure 4 The enlarged view of point A in the middle;

[0028] Figure 6The present invention is an industrial production safety risk assessment device based on deep learning Figure 3 The enlarged view of point B in the middle;

[0029] In the figure: 1. Equipment base; 2. Mechanical adjustment component; 21. First connecting plate; 22. Hinge; 23. Second connecting plate; 24. Sleeve; 25. Equipment base; 3. Environment acquisition component; 4. Display component; 5. Planning component; 6. Traveling wheel; 7. Transmission component; 71. Rotating shaft; 72. Sleeve; 73. Driven gear; 74. Driving gear; 75. Connecting shaft; 76. Servo motor one; 8. Stabilizing component; 81. Stabilizing seat; 82. Contact rod; 83. Screw; 84. Screw nut; 85. Mounting plate; 9. Display adjustment component; 91. Rotating gear; 92. Rack; 93. Servo motor two. DETAILED DESCRIPTION

[0030] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0031] In the description of the present invention, it should be noted that the terms "center", "upper", "lower", "left", "right", "vertical", "horizontal", "inside", "outside" and the like indicate positions or positional relationships based on the positions or positional relationships shown in the drawings, which are only for the convenience of describing the present invention and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore cannot be understood as limiting the present invention. In addition, the terms "first", "second", and "third" are only used for descriptive purposes and cannot be understood as indicating or implying relative importance. In the description of the present invention, it should be noted that, unless otherwise clearly specified and limited, the terms "installed", "connected", "connected", and "set" should be understood in a broad sense, for example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be directly connected, or indirectly connected through an intermediate medium, or it can be the internal connection of two elements. For those of ordinary skill in the art, the specific meanings of the above terms in the present invention can be understood according to specific circumstances. The following is an explanation of an embodiment of the present invention based on the overall structure of the present invention.

[0032] See also Figures 1 to 6In an embodiment of the present invention, an industrial production safety risk assessment device based on deep learning includes a detection device, which is used to carry hardware for collecting industrial production safety risk factors; a collection component, which includes an environment collection component 3 and a display component 4, and the environment collection component 3 and the display component 4 cooperate to collect data on industrial production safety risks; and a control algorithm, which performs risk assessment on the collection component through a neural network algorithm and outputs an assessment report.

[0033] The present application collects environmental safety data in the industrial production process through the environmental collection component 3 in the collection component, and then uses the control algorithm to perform neural network learning on the environmental collection data, so as to identify the factors existing in the environment. Then, by performing a safety assessment of the existing factors based on the neural network algorithm, the safety factor of the collected environmental objects can be evaluated to remind personnel to work safely.

[0034] Methods for using industrial production safety risk assessment equipment based on deep learning, including

[0035] Step S1: The detection device enters the industrial production site, and adjusts the angle of the environment collection component 3 through the activity of the transmission component 7 or the mechanical adjustment group 2, so that the environment collection component 3 can collect environmental data from different spatial positions;

[0036] Step S2: the environment collection component 3 analyzes the collected environment data through a control algorithm;

[0037] Specifically, the environment acquisition component 3 is used to simulate and evaluate the objects in the three-dimensional space of the production process, including processing equipment, processing objects, roads, movable and fixed objects in the space where personnel are located, and personnel positions, and the evaluated objects are scored. The higher the score, the safer it is. The scoring includes priority, movable objects have lower scores than fixed objects, and small objects have lower scores than large objects. Then, the space mainly near personnel is evaluated for safety through scoring, and an evaluation report is generated.

[0038] Step S3: The control algorithm generates a data report of the environment acquisition component.

[0039] As a further solution of the present invention: an industrial production safety risk assessment device based on deep learning, the detection device includes a device base 1 and a mechanical adjustment group 2, the mechanical adjustment group 2 is rotatably connected to the device base 1 through a transmission component 7, and the environment collection component 3 or the display component 4 is fixedly connected to the mechanical adjustment group 2.

[0040] As a further solution of the present invention: an industrial production safety risk assessment device based on deep learning, the mechanical adjustment group 2 includes a first connecting plate 21, a hinge 22, a second connecting plate 23, a sleeve 24 and an equipment seat 25, the second connecting plate 23 is hinged to the first connecting plate 21 through the hinge 22, the sleeve 24 is movably connected to the second connecting plate 23, the equipment seat 25 is fixedly connected to the sleeve 24, the environment collection component 3 is fixedly connected to the second connecting plate 23, and the display component 4 is fixedly connected to the equipment seat 25.

[0041] As a further solution of the present invention: an industrial production safety risk assessment device based on deep learning, the transmission assembly 7 includes a rotating shaft 71, a sleeve 72, a driven gear 73, a driving gear 74, a connecting shaft 75 and a servo motor 76, the rotating shaft 71 is rotatably connected to the equipment base 1, the sleeve 72 is fixedly connected to the rotating shaft 71, the driven gear 73 is fixedly connected to the rotating shaft 71, the servo motor 76 is fixedly installed on one side of the equipment base 1, the output end of the servo motor 76 passes through the equipment base 1 and is fixedly connected to the connecting shaft 75, the driving gear 74 is fixedly connected to the connecting shaft 75, and the driving gear 74 is meshingly connected to the driven gear 73.

[0042] As a further solution of the present invention: the industrial production safety risk assessment equipment based on deep learning also includes a stabilizing component 8, which includes a stabilizing seat 81, a contact rod 82, a screw 83, a screw nut 84 and a mounting plate 85, wherein the mounting plate 85 is fixedly connected to the equipment base 1, one end of the screw 83 is rotatably connected to the mounting plate 85, and the other end is rotatably connected to the equipment base 1, the screw nut 84 is fixedly connected to the stabilizing seat 81, the screw nut 84 is movably connected to the screw 83, the contact rod 82 is fixedly connected to the stabilizing seat 81, and the contact rod 82 is movably connected to the first connecting plate 21.

[0043] As a further solution of the present invention: the industrial production safety risk assessment equipment based on deep learning also includes a display adjustment component 9, which includes a rotating gear 91, a rack 92 and a servo motor 93. The servo motor 93 is fixedly connected to the second connecting plate 23, and the output end of the servo motor 93 is fixedly connected to the rotating gear 91. One end of the rack 92 is fixedly connected to the sleeve 24 and the other end is movably connected to the second connecting plate 23. The rotating gear 91 is meshingly connected to the rack 92.

[0044] As a further solution of the present invention: the industrial production safety risk assessment equipment based on deep learning also includes a planning component 5, which is arranged on one side of the equipment base 1 and provides a collision alarm for the equipment base 1 when it is moving.

[0045] As a further solution of the present invention: an industrial production safety risk assessment device based on deep learning, one side of the device base 1 is rotatably connected to a walking wheel 6.

[0046] The working principle of the present invention is: the present application collects environmental safety data in the industrial production process through the environmental collection component 3 in the collection component, and then performs neural network learning on the environmental collection data through the control algorithm, so as to identify the factors existing in the environment, and then performs safety assessment based on the neural network algorithm on the existing factors, so as to evaluate the safety factor of the collected environmental objects and remind personnel to work safely;

[0047] The environment acquisition component 3 is used to simulate and evaluate the objects in the three-dimensional space of the production process, including processing equipment, processing objects, roads, movable and fixed objects in the space where personnel are located, and personnel positions, and the evaluated objects are scored. The higher the score, the safer it is. The scoring includes priority, movable objects have lower scores than fixed objects, and small objects have lower scores than large objects. Then, the space mainly near personnel is evaluated for safety through scoring, and an evaluation report is generated to remind personnel to pay attention to environmental safety.

[0048] What is described above is only a preferred specific implementation manner of the present invention, but the protection scope of the present invention is not limited thereto. Any technician familiar with the technical field can make equivalent replacements or changes according to the technical scheme and inventive concept of the present invention within the technical scope disclosed by the present invention, which should be covered by the protection scope of the present invention.

Claims

1. Industrial production safety risk assessment equipment based on deep learning, characterized in that: It includes detection equipment, which is used for the hardware for collecting industrial production safety risk factors; A collection component, the collection component comprising an environment collection component (3) and a display component (4), the environment collection component (3) and the display component (4) cooperate to collect data on industrial production safety risks; as well as A control algorithm performs risk assessment on the acquisition component through a neural network algorithm and outputs an assessment report.

2. The industrial production safety risk assessment device based on deep learning according to claim 1 is characterized in that: The detection device comprises a device base (1) and a mechanical adjustment group (2); the mechanical adjustment group (2) is rotatably connected to the device base (1) via a transmission component (7); and the environment collection component (3) or the display component (4) is fixedly connected to the mechanical adjustment group (2).

3. The industrial production safety risk assessment device based on deep learning according to claim 2 is characterized in that: The mechanical adjustment group (2) comprises a first connecting plate (21), a hinge (22), a second connecting plate (23), a sleeve (24) and a device seat (25); the second connecting plate (23) is hinged to the first connecting plate (21) via the hinge (22); the sleeve (24) is movably connected to the second connecting plate (23); the device seat (25) is fixedly connected to the sleeve (24); the environment collection component (3) is fixedly connected to the second connecting plate (23); and the display component (4) is fixedly connected to the device seat (25).

4. The industrial production safety risk assessment device based on deep learning according to claim 3 is characterized in that: The transmission assembly (7) comprises a rotating shaft (71), a sleeve (72), a driven gear (73), a driving gear (74), a connecting shaft (75) and a servo motor (76); the rotating shaft (71) is rotatably connected to the device base (1); the sleeve (72) is fixedly connected to the rotating shaft (71); the driven gear (73) is fixedly connected to the rotating shaft (71); the servo motor (76) is fixedly mounted on one side of the device base (1); an output end of the servo motor (76) passes through the device base (1) and is fixedly connected to the connecting shaft (75); the driving gear (74) is fixedly connected to the connecting shaft (75); and the driving gear (74) is meshingly connected to the driven gear (73).

5. The industrial production safety risk assessment device based on deep learning according to claim 4 is characterized in that: The device also comprises a stabilizing assembly (8), the stabilizing assembly (8) comprising a stabilizing seat (81), a contact rod (82), a lead screw (83), a lead screw nut (84) and a mounting plate (85), the mounting plate (85) being fixedly connected to the device base (1), one end of the lead screw (83) being rotatably connected to the mounting plate (85) and the other end being rotatably connected to the device base (1), the lead screw nut (84) being fixedly connected to the stabilizing seat (81), the lead screw nut (84) being movably connected to the lead screw (83), the contact rod (82) being fixedly connected to the stabilizing seat (81), and the contact rod (82) being movably connected to the first connecting plate (21).

6. The industrial production safety risk assessment device based on deep learning according to claim 5 is characterized in that: The display adjustment component (9) further comprises a rotating gear (91), a rack (92) and a second servo motor (93), wherein the second servo motor (93) is fixedly connected to the second connecting plate (23), an output end of the second servo motor (93) is fixedly connected to the rotating gear (91), one end of the rack (92) is fixedly connected to the sleeve (24) and the other end is movably connected to the second connecting plate (23), and the rotating gear (91) is meshingly connected to the rack (92).

7. The industrial production safety risk assessment device based on deep learning according to claim 6 is characterized in that: It also comprises a planning component (5), which is arranged on one side of the equipment base (1) and provides a collision alarm when the equipment base (1) is moving.

8. The industrial production safety risk assessment device based on deep learning according to claim 7 is characterized in that: One side of the equipment base (1) is rotatably connected to a running wheel (6).

9. The method for using the deep learning-based industrial production safety risk assessment device according to claim 8, characterized in that: include Step S1: the detection device enters the industrial production site, and adjusts the angle of the environment collection component (3) through the activity of the transmission component (7) or the mechanical adjustment group (2), so that the environment collection component (3) can collect environmental data from different spatial positions; Step S2: the environment acquisition component (3) analyzes the collected environment data through a control algorithm; Step S3: The control algorithm generates a data report of the environment acquisition component.

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