Intelligent system for safety risk identification and hidden danger investigation

Abstract

This invention discloses an intelligent system for safety risk identification and hazard investigation, comprising a data acquisition module, a data preprocessing module, a risk identification and hazard investigation module, an early warning and response module, and a data analysis and decision support module. The data acquisition module includes a sensor network, a mobile terminal, and a third-party data interface. The data preprocessing module includes a data cleaning module and a feature extraction module. The data cleaning module cleans the collected raw data; the feature extraction module extracts features related to safety risks and hazards from the cleaned data. The risk identification and hazard investigation module includes a knowledge base, an intelligent matching and analysis module, and a risk assessment model. The early warning and response module sets different levels of early warning thresholds based on the risk assessment results and pushes early warning information. The data analysis and decision support module discovers the evolution trend of safety risks and hazards and establishes a decision support model. This invention can accurately and intelligently predict safety hazards and issue timely alerts.

Description

Technical Field

[0001] This invention relates to the field of safety management technology, specifically to an intelligent system for safety risk identification and hidden danger investigation. Background Technology

[0002] In various production and business activities and social environments, safety risk identification and hazard investigation are crucial for ensuring the safety of personnel and property, as well as maintaining normal production order. Traditional safety risk identification and hazard investigation work mainly relies on manual labor, which has many limitations.

[0003] On the one hand, manual inspections are inefficient, especially in large enterprises, complex locations, or over wide areas, requiring significant manpower, resources, and time, and making it difficult to conduct comprehensive and timely inspections. On the other hand, manual inspections are limited by subjective factors and the level of professional knowledge, making them prone to oversights and misjudgments, resulting in some safety risks and hidden dangers not being discovered and addressed in a timely manner, thus creating potential safety hazards.

[0004] With the development of information technology, some security management systems based on information technology have emerged. However, most of these systems have relatively limited functions and lack intelligent analysis and early warning capabilities. For example, some systems only digitize security inspection records and cannot automatically identify potential security risk patterns; while some systems can perform simple statistical analysis of historical data, they struggle to make accurate risk assessments and hazard warnings based on real-time data and complex scenarios.

[0005] Therefore, there is an urgent need for an intelligent system that can overcome the above problems, achieve efficient, accurate, and intelligent identification of safety risks and investigation of potential hazards, improve the level of safety management, and prevent the occurrence of safety accidents. Summary of the Invention

[0006] In view of this, the purpose of this invention is to provide an intelligent system for safety risk identification and hidden danger investigation, so as to solve the problems of low efficiency, poor accuracy and insufficient intelligence in the existing safety risk identification and hidden danger investigation work, realize automated and intelligent safety risk assessment and hidden danger early warning, and improve the scientificity and effectiveness of safety management.

[0007] This invention is achieved through the following technical solution:

[0008] An intelligent system for safety risk identification and hazard investigation includes a data acquisition module, a data preprocessing module, a risk identification and hazard investigation module, an early warning and response module, and a data analysis and decision support module.

[0009] The data acquisition module includes a sensor network, a mobile terminal, and a third-party data interface. The sensor network includes various types of sensors deployed in the target area. The mobile terminal is used by inspectors to take photos, record audio, and input text on-site and upload it in real time. The third-party data interface is used to enable the intelligent system to interconnect and share data with the enterprise's internal management system and external data sources.

[0010] The data preprocessing module includes a data cleaning module and a feature extraction module. The data cleaning module cleans the collected raw data; the feature extraction module uses data mining and machine learning techniques to extract key features related to security risks and hidden dangers from the cleaned data.

[0011] The risk identification and hazard investigation module includes a knowledge base, an intelligent matching and analysis module, and a risk assessment model. The knowledge base includes safety regulations, standards, and specifications. The intelligent matching and analysis module intelligently matches and analyzes pre-processed data with the knowledge base. The risk assessment model is based on a multi-factor risk assessment model to quantitatively assess the identified safety risks.

[0012] The early warning and response module sets different levels of early warning thresholds based on the risk assessment results. When the identified safety risks or hidden dangers reach the corresponding early warning level, the system pushes early warning information.

[0013] The data analysis and decision support module performs in-depth mining and analysis of a large amount of historical security data accumulated by the system, discovers the distribution patterns and evolution trends of security risks and hidden dangers, and establishes a decision support model based on the results of historical data mining and real-time risk assessment information.

[0014] Furthermore, the sensor network includes smoke sensors, temperature sensors, humidity sensors, pressure sensors, vibration sensors, and gas concentration sensors. All sensors are integrated on a sensing assembly, which also includes an upper mounting body and a lower mounting body. The upper mounting body has a ring array of several mounting holes. Each mounting hole has an elastic support plate that normally extends into the mounting hole installed in the side wall. Each mounting hole has a shielding plate above it, which is elastically damped and hinged to the upper part of the upper mounting body.

[0015] The lower mounting body can rotate relative to the upper mounting body. The lower mounting body has a seat hole and an electromagnet located below the seat hole. A slider is vertically and elastically installed in the seat hole. The slider is attracted by the electromagnet so that a sensor carrier can be inserted into the seat hole. A curved arm is connected to one side of the slider. The top of the curved arm extends through the axial direction of the upper mounting body and a push block is fixed thereon.

[0016] When the mounting hole rotates to directly below the corresponding mounting hole, the electromagnet is de-energized. The sensor carrier inside the mounting hole is pushed into the mounting hole by the upward movement of the slider, pushing out the original sensor carrier in the mounting hole. During the upward movement of the slider, the push block moves upward through the curved arm, causing the corresponding shielding plate to deflect at an angle, so as to quickly and completely expose the corresponding mounting hole.

[0017] Furthermore, when the sensor carrier springs into the mounting hole, the elastic support piece is pressed into the side wall of the mounting hole. After passing the elastic support piece, the elastic support piece returns to the mounting hole and applies an upward pushing force to the sensor carrier. Together with the shielding plate that has rotated back to its original position at this time, the sensor is fixed in the mounting hole.

[0018] Furthermore, the crank arm includes a horizontal rod segment, a vertical rod segment, and an L-shaped crank segment. The horizontal rod segment is fixed to the side wall of the slider and can move vertically within the sliding cavity on one side of the hole wall of the seat hole. The vertical rod segment is coaxially located on the axial direction of the two mounting bodies. The crank segment is located outside the top of the upper mounting body and is fixed to the push block.

[0019] Furthermore, the shielding plate includes a fan-shaped plate and a drive arm; several arc-shaped baffles are provided at the edge of the upper mounting body, the top of each baffle is slidably engaged with the fan-shaped plate, and the center of the baffle falls on the axis of the hinge shaft between the shielding plate and the upper mounting body; the drive arm is used to contact the push block to realize the swing of the shielding plate.

[0020] The upper mounting body also has a placement hole with a diameter larger than that of the seat hole. When the lower mounting body is rotated to the point where the placement hole and the seat hole are coaxially aligned, the sensor can be inserted into the seat hole through the placement hole. By pressing the top of the sensor and rotating the lower mounting body at the same time, the sensor can be completely pressed into the seat hole.

[0021] Furthermore, the mobile terminal includes smartphones and tablets to upload target problems, equipment status, and on-site environmental information discovered during the inspection process in real time, and the mobile terminal integrates GPS positioning function to record the location information of the inspectors; the enterprise internal management system includes an equipment management system, a production scheduling system, and a personnel management system, and the external data source includes the regulatory database of government safety supervision departments and the industry accident case database.

[0022] Furthermore, the data cleaning module can filter noise in video surveillance images and correct or remove abnormal data collected by sensors.

[0023] The extraction objects of the feature extraction module include:

[0024] The video image data includes the extraction of personnel behavior features and the extraction of equipment appearance features. The personnel behavior features include whether a safety helmet is being worn and whether there are any violations of operating procedures. The equipment appearance features include whether the equipment is damaged and whether the equipment is operating normally.

[0025] Sensor data, which includes the changing trends of sensor-collected data and the extraction of threshold deviation data;

[0026] Text data, which includes extracted keywords and key phrases.

[0027] Furthermore, the knowledge base includes the types, characteristics, and manifestations of safety risks in different scenarios, as well as the corresponding judgment rules. For chemical enterprises, the knowledge base includes the storage and use specifications for various hazardous chemicals, as well as the corresponding risk identification points.

[0028] Furthermore, the intelligent matching and analysis module utilizes natural language processing technology to perform semantic understanding and matching of text data, employs image recognition algorithms to perform pattern recognition of video images, and uses data analysis models to perform real-time monitoring and anomaly detection of sensor data.

[0029] Furthermore, the early warning and response module promptly sends early warning information to relevant personnel via SMS, email, or APP push notifications, informing them of the risk type, location, and severity. Through the mobile terminal and system platform, the response process is tracked and recorded in real time, and the results of hazard handling are fed back and reviewed, forming a closed-loop management system.

[0030] The beneficial effects of this invention are as follows:

[0031] This intelligent system for safety risk identification and hidden danger investigation improves work efficiency: the invention greatly reduces the workload and time cost of manual data collection by automatically collecting data in real time through a sensor network and convenient data uploading via a smart mobile terminal. At the same time, it designs a specially made sensing component that allows for flexible adjustment of sensor types to meet the design requirements of the invention.

[0032] Furthermore, the intelligent system in this invention has rapid data processing and analysis capabilities, enabling it to assess and judge a large amount of security information in a short time, significantly improving the efficiency of security risk identification and hidden danger investigation.

[0033] Enhanced accuracy: Multi-source data fusion and advanced data analysis technologies enable the system to comprehensively and meticulously analyze the security situation from multiple dimensions, avoiding the subjectivity and bias of manual investigation. Through precise matching and intelligent analysis with the security risk knowledge base, it can accurately identify various potential security risks and hidden dangers, improving the accuracy of investigation results.

[0034] Intelligent early warning: The system possesses real-time monitoring and dynamic risk assessment capabilities, enabling it to issue timely warnings based on changes in risk, allowing relevant personnel to take proactive measures to prevent safety accidents. This intelligent early warning mechanism transforms the traditional reactive approach to safety management, achieving proactive prevention and control of safety risks.

[0035] A complete safety management closed loop has been established: from risk identification and early warning to hazard handling, the entire process is tracked and feedback is provided, forming a complete safety management closed loop. Through the review of handling results and data analysis, safety management strategies and measures are continuously optimized, thereby continuously improving the company's safety management level.

[0036] Providing Decision Support: In-depth data mining and analysis provide strong data support for enterprise security management decisions. Based on scientific decision support models, enterprises can allocate security resources more rationally, formulate targeted security management plans, and improve the scientific nature and effectiveness of security management decisions.

[0037] Other advantages, objectives, and features of the invention will be set forth in part in the description which follows, and in part will be apparent to those skilled in the art from the following examination, or may be learned from practice of the invention. The objectives and other advantages of the invention can be realized and obtained through the following description. Attached Figure Description

[0038] Figure 1 This is a schematic diagram of the system structure of the present invention;

[0039] Figure 2 This is a simplified top view of the sensing component of the present invention;

[0040] Figure 3 for Figure 2 A simplified cross-sectional view of the KK direction in the diagram;

[0041] Figures 4-6 These are three schematic diagrams showing the cooperation between the jacking block and the drive arm of the present invention.

[0042] In the diagram: Upper mounting body 1, Lower mounting body 2, Mounting hole 3, Seat hole 4, Shielding plate 5, Fan-shaped plate 501, Drive arm 502, Slider 6, Sensor carrier 7, Elastic support plate 8, Crank arm 9, Horizontal rod segment 901, Vertical rod segment 902, Crank rod segment 903, Sliding cavity 10, Compression spring 11, Hinge shaft 12, Push block 13, Baffle 14, Throwing hole 15, Guide ring 16. Detailed Implementation

[0043] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. The components of the embodiments of the present invention described and shown in the accompanying drawings can generally be arranged and designed in various different configurations.

[0044] Therefore, the following detailed description of the embodiments of the invention provided in the accompanying drawings is not intended to limit the scope of the claimed invention, but merely to illustrate selected embodiments of the invention. All other embodiments obtained by those skilled in the art based on the embodiments of the invention without inventive effort are within the scope of protection of the invention.

[0045] It should be noted that similar labels and letters in the following figures indicate similar items. Therefore, once an item is defined in one figure, it does not need to be further defined and explained in subsequent figures.

[0046] This invention provides a technical solution: an intelligent system for safety risk identification and hidden danger investigation, which, in terms of its composition, includes... Figure 1 As shown, the system mainly includes the following modules: First, a data acquisition module, which has a sensor network deployed in the target area, such as factory workshops, construction sites, and commercial complexes, using various types of sensors, including but not limited to video surveillance cameras, smoke sensors, temperature sensors, pressure sensors, vibration sensors, and gas concentration sensors. These sensors collect environmental data, equipment operation data, and personnel behavior data in real time, comprehensively acquiring safety-related information. In addition, there is a mobile terminal acquisition module, equipping safety inspectors with smart mobile terminals, such as smartphones and tablets. Inspectors can use the mobile terminals' functions such as taking photos, recording audio, and inputting text to upload information such as problems found during the inspection, equipment status, and the on-site environment in real time. Simultaneously, the mobile terminals can also integrate GPS positioning functionality to record the location information of inspectors for real-time tracking and management of the inspection work. Finally, a dedicated third-party data interface is also provided. The intelligent system in this embodiment is equipped with interfaces with other internal management systems of the enterprise, such as equipment management system, production scheduling system, personnel management system, etc., as well as external relevant data sources, such as the regulatory database of government safety supervision departments and industry accident case database, etc., to realize data interconnection and sharing. By acquiring data from these systems, the information sources for safety risk identification and hidden danger investigation are enriched.

[0047] In the above embodiments, the sensor network is the most fundamental and critical component for on-site risk warning in the environment. Specifically, this sensor network includes smoke sensors, temperature sensors, humidity sensors, pressure sensors, vibration sensors, gas concentration sensors, etc. To facilitate installation and use, and to enhance the flexibility of risk warning target selection, it is best to integrate all sensors onto a single sensing component, allowing for the configuration of corresponding sensor types as needed. Specifically, such as... Figures 2-3 As shown, the sensing component in this embodiment also includes an upper mounting body 1 and a lower mounting body 2, both of which can be frustum structures. The upper mounting body 1 has a number of mounting holes 3 arranged in a ring. Each mounting hole 3 has a receiving groove (not shown in the figure) in the side wall. An elastic support piece 8 that can normally extend into the mounting hole 3 can be installed obliquely outward in the receiving groove. In addition, a shielding plate 5 is provided above each mounting hole 3. The shielding plate 5 is elastically damped and hinged to the upper part of the upper mounting body 1. That is, the shielding plate 5 rotates when the external force is twisted and quickly returns to its original position when the external force is removed.

[0048] Continue reading Figures 2-3 In this embodiment, the lower mounting body 2 can rotate relative to the upper mounting body 1. Specifically, it can be connected and installed using an annular guide ring 16. The lower mounting body 2 has a seat hole 4, and below the seat hole 4 is an automatically controllable electromagnet. A slider 6 is vertically and elastically installed within the seat hole 4, for example, connected to the slider 6 via a compression spring 11. The slider 6 is attracted downwards by the energized electromagnet, allowing a sensor carrier 7 to be inserted into the seat hole 4. Here, the sensor carrier 7 mainly refers to a component for mounting sensors. For example, the sensor carrier 7 can be a cylindrical hollow part with open sidewalls around its top to communicate with the outside. Various sensors can be installed in the internal cavity of this component; that is, the corresponding sensor is installed inside the sensor carrier 7. In addition, in this embodiment, a curved arm 9 is connected to one side of the slider 6. The top of the curved arm 9 extends through the axial direction of the upper mounting body 1 and a push block 13 is fixed thereon. This push block 13 drives the shielding plate 5 to rotate to expose the mounting hole 3, so that the original sensor carrier 7 pops out of the mounting body, or when the shielding plate 5 is driven to reset, it presses down the newly entered sensor carrier 7 into the mounting hole 3 to achieve fixation.

[0049] like Figure 2As shown, the shielding plate 5 in this embodiment includes a fan-shaped plate 501 and a drive arm 502. Several arc-shaped baffles 14 are provided at the edge of the upper mounting body 1. The top of each baffle 14 slides in conjunction with the fan-shaped plate 501, and the center of the baffle 14 lies on the axis of the hinge shaft 12 between the shielding plate 5 and the upper mounting body 1. This allows the shielding plate 5 to rotate flexibly and stably. Specifically, the drive arm 502 mentioned above is used to contact the push block 13 to achieve the aforementioned rotation or swing of the shielding plate 5.

[0050] To allow additional or new sensor carriers 7 to be placed inside the lower mounting body 2 and moved accordingly, specifically, they can be mounted on the upper mounting body 1, such as... Figure 2 A placement hole 15, larger in diameter than the seat hole 4, is provided. The sensor carrier 7 can be inserted through this hole. When the lower mounting body 2 rotates until the placement hole 15 and the seat hole 4 are coaxially aligned, the sensor can be inserted into the seat hole 4 through the placement hole 15. Simultaneously pressing down the top of the sensor and rotating the lower mounting body 2 allows the sensor to be fully pressed into the seat hole 4 and then rotated to the corresponding mounting hole 3. In practice, corresponding scale lines can be set to indicate whether the seat hole 4 and the mounting hole 3 are aligned. For example, scale lines can be set on the side walls of both mounting bodies. When the scale lines of the two mounting bodies are aligned, it indicates that a certain mounting hole 3 and seat hole 4 are aligned.

[0051] During use, when the seat hole 4 rotates with the lower mounting body 2 to directly below the corresponding mounting hole 3, the electromagnet is de-energized, the compression spring 11 pushes the slider 6, and the slider 6 pushes the sensor carrier 7. That is, the sensor carrier 7 in the seat hole 4 is pushed into the mounting hole 3 by the upward movement of the slider 6, and then pushes the original sensor carrier 7 out of the mounting body. Moreover, during the upward movement of the slider 6, that is, when it just enters the bottom of the mounting hole 3, the crank arm 9 will also move the push block 13 upward synchronously. Then the push block 13 moves upward. The structure of the push block 13 can be as follows: Figures 4-6 As shown, the corresponding shielding plate 5 is deflected at an angle to quickly and completely expose the corresponding mounting hole 3, for example, with Figures 4-5 As shown in the diagram, during this process, the drive arm 502 will move to the right, that is... Figure 2 In the middle, the drive arm 502 deflects upward, and the corresponding shielding plate 5 rotates counterclockwise around the hinge shaft 12 by an angle to expose the corresponding mounting hole 3. The original sensor carrier 7 pops out, so that the new sensor carrier 7 can be inserted.

[0052] In the above embodiments, specifically, during the process of inserting the sensor carrier 7 into the mounting hole 3, such as... Figure 3As shown on the left, the elastic support plate 8 is pressed into the side wall of the mounting hole 3, and after passing over the elastic support plate 8 under the ejection action of the compression spring 11, the elastic support plate 8 returns to the mounting hole 3 and applies an upward pushing force to the sensor carrier 7. Together with the shielding plate 5, which has now returned to its original position, the two ends of the sensor are held in place, and then the sensor is fixed in the mounting hole 3.

[0053] In this embodiment, as Figure 3 As shown, the crank arm 9 includes a horizontal rod segment 901, a vertical rod segment 902, and an L-shaped crank segment 903. The horizontal rod segment 901 is fixed to the side wall of the slider 6 and can move vertically within the sliding cavity 10 on one side of the hole wall of the seat hole 4. This sliding cavity 10 can be a very narrow, flat cavity, mainly to guide the vertical movement of the crank arm 9. The vertical rod segment 902 is coaxially located on the axial direction of the two mounting bodies. The crank segment 903 is located outside the top of the upper mounting body 1 and is fixed to the push block 13. The reason why the crank segment 903 is L-shaped is that when the lower mounting body 2 rotates, the push block 13 can only contact the only corresponding shielding plate 5, so the push block 13 cannot be set in the center.

[0054] Concurrently, a data preprocessing module is included. Specifically, this module includes a data cleaning module, which cleans the large amount of raw data collected, removing duplicate, erroneous, and incomplete data records, standardizing data formats, and improving data quality. For example, it filters noise in video surveillance images and corrects or removes abnormal data collected by sensors. Furthermore, the feature extraction module utilizes data mining and machine learning techniques to extract key features related to safety risks and hazards from the cleaned data. For video image data, it extracts personnel behavior features, such as whether safety helmets are worn and whether there are violations of operating procedures; for equipment appearance features, such as whether the equipment is damaged and whether it is operating normally; for sensor data, it extracts features such as data change trends and threshold deviations; and for text data, it extracts semantic features such as keywords and key phrases.

[0055] The risk identification and hazard investigation module primarily consists of a knowledge base. This knowledge base collects and organizes various safety regulations, standards, specifications, and industry experience to construct a safety risk knowledge base. The knowledge base includes information such as the types of safety risks, risk characteristics, hazard manifestations, and corresponding judgment rules in different scenarios. For example, for chemical enterprises, the knowledge base records detailed storage and usage specifications for various hazardous chemicals, as well as corresponding risk identification points. It also includes an intelligent matching and analysis module, which intelligently matches and analyzes pre-processed data with the safety risk knowledge base. Natural language processing technology is used for semantic understanding and matching of text data, image recognition algorithms are used for pattern recognition of video images, and a data analysis model is used for real-time monitoring and anomaly detection of sensor data. For example, if a video surveillance image identifies personnel not wearing protective equipment as required, or if a sensor detects that the operating parameters of a device exceed a safety threshold, the system will automatically determine that a safety risk or hazard exists. In practice, it can also include a risk assessment model, establishing a multi-factor-based risk assessment model that comprehensively considers factors such as the probability of risk occurrence and the degree of impact to quantitatively assess the identified safety risks. For example, regarding fire risk, the model will consider factors such as the types and quantities of flammable materials in the premises, the availability of fire-fighting facilities, and the unobstructedness of personnel evacuation routes to calculate the level of fire risk (such as high, medium, or low).

[0056] The early warning and response module itself includes an early warning mechanism that sets different levels of warning thresholds based on risk assessment results. When an identified safety risk or hazard reaches the corresponding warning level, the system promptly sends warning information to relevant personnel, such as safety managers, company leaders, and on-site workers, through various means including SMS, email, and app push notifications, informing them of the risk type, location, severity, and other details. It also includes a response process tracking feature. For each identified safety hazard, the system automatically generates a detailed response task sheet, clearly defining the responsible personnel, response measures, and deadlines. The response process is tracked and recorded in real time via mobile terminals and the system platform to ensure timely and effective handling of hazards. Simultaneously, the system provides feedback and audits on the hazard response results, forming a closed-loop management system.

[0057] Finally, the data analysis and decision support module of this intelligent system first focuses on historical data mining, deeply mining and analyzing the large amount of historical safety data accumulated by the system. Using techniques such as association rule mining and trend analysis, it discovers the distribution patterns, evolution trends, and potential causal relationships of safety risks and hazards. For example, analysis may reveal that the probability of a safety accident caused by a specific equipment failure is high within a certain time period, or that specific types of safety violations are prone to occur under certain working environments. As for the decision support model in this embodiment, it is built based on the results of historical data mining and real-time risk assessment information, providing a scientific basis for enterprise safety management decisions, such as formulating safety management systems, optimizing safety resource allocation, and planning safety training programs. For example, if data analysis reveals that a certain area frequently experiences falls from height risks, the decision support model can recommend strengthening the construction of safety protection facilities and personnel training in that area.

[0058] In the above description of the present invention, it should be noted that the terms "one side," "the other side," etc., indicate the orientation or positional relationship based on the orientation or positional relationship shown in the accompanying drawings, or the orientation or positional relationship in which the product of the invention is conventionally placed during use. These terms are used only for the convenience of describing the present invention and for simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation. Therefore, they should not be construed as limitations on the present invention. Furthermore, the terms "first," "second," etc., are used only to distinguish descriptions and should not be construed as indicating or implying relative importance.

[0059] Furthermore, terms such as "identical" do not imply that components must be absolutely identical; minor differences are permissible. The term "perpendicular" simply means that the positional relationship between components is more perpendicular than "parallel," not that the structure must be perfectly perpendicular; a slight tilt is acceptable.

[0060] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit it. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention, and all such modifications or substitutions should be covered within the scope of the claims of the present invention.

Claims

1. A security risk identification and hidden danger investigation intelligent system, characterized in that: The system comprises a data acquisition module, a data preprocessing module, a risk identification and hidden danger investigation module, an early warning and disposal module, and a data analysis and decision support module. ​ The data acquisition module comprises a sensor network, a mobile terminal, and a third-party data interface. The data preprocessing module comprises a data cleaning module and a feature extraction module. The risk identification and hidden danger investigation module comprises a knowledge base, an intelligent matching and analysis module, and a risk assessment model. The early warning and disposal module sets different levels of early warning thresholds according to the risk assessment results. The data analysis and decision support module deeply mines and analyzes a large amount of historical safety data accumulated by the system to find the distribution law and evolution trend of safety risks and hidden dangers. The sensor network comprises a smoke sensor, a temperature sensor, a humidity sensor, a pressure sensor, a vibration sensor, and a gas concentration sensor. The lower mounting body (2) can rotate relative to the upper mounting body (1), and has a seat hole (4) and an electromagnet below the seat hole (4). The sliding block (6) is connected with a curved arm (9) on one side, and the top end of the curved arm (9) penetrates through the axial direction of the upper mounting body (1) and is fixed with a jacking block (13). When the seat hole (4) rotates with the lower mounting body (2) to the position directly below the corresponding mounting hole (3), the electromagnet is powered off, the sensor carrier (7) in the seat hole (4) is pushed into the mounting hole (3) under the upward pushing action of the slider (6), and the original sensor carrier (7) in the mounting hole (3) is pushed out, and in the process of upward movement of the slider (6), the curved arm (9) moves upward with the pushing block (13), the pushing block (13) deflects the corresponding shielding plate (5) by an angle, and the corresponding mounting hole (3) is quickly and completely exposed. 2.The intelligent system for safety risk identification and hidden danger elimination according to claim 1, characterized in that: When the sensor carrier (7) is pushed into the mounting hole (3), the elastic support sheet (8) is pressed into the side wall of the mounting hole (3), and after passing the elastic support sheet (8), the elastic support sheet (8) is reset in the mounting hole (3) to exert an upward pushing force on the sensor carrier (7), and the sensor carrier (7) is fixed in the mounting hole (3) together with the shielding plate (5) which is rotated to the original position at this time. 3.The intelligent system for safety risk identification and hidden danger elimination according to claim 2, characterized in that: The curved arm (9) includes a horizontal rod segment (901), a vertical rod segment (902), and an L-shaped elbow segment (903), the horizontal rod segment (901) is fixed on the side wall of the slider (6) and can move vertically in the sliding cavity (10) on one side of the hole wall of the seat hole (4), the vertical rod segment (902) is coaxially located in the axial direction of the two mounting bodies, and the elbow segment (903) is located outside the top of the upper mounting body (1) and is fixed with the pushing block (13). 4.The intelligent system for safety risk identification and hidden danger elimination according to claim 1, characterized in that: The shielding plate (5) includes a sector plate (501) and a driving arm (502), the edge of the upper mounting body (1) is provided with a plurality of arc-shaped baffles (14), the top end of each baffle (14) is in sliding cooperation with the sector plate (501), and the center of the baffle (14) falls on the axis of the hinge shaft (12) between the shielding plate (5) and the upper mounting body (1), and the driving arm (502) is used to contact the pushing block (13) to realize the swinging of the shielding plate (5). The upper mounting body (1) further has a placement hole (15) with a hole diameter larger than that of the seat hole (4), when the lower mounting body (2) rotates to the coaxial alignment of the placement hole (15) and the seat hole (4), the sensor carrier (7) can be inserted into the seat hole (4) through the placement hole (15), and the sensor carrier (7) is pressed at the top end while the lower mounting body (2) is rotated, so that the sensor carrier (7) is completely pressed into the seat hole (4). 5.The intelligent system for safety risk identification and hidden danger elimination according to claim 1, characterized in that: The mobile terminal includes a smart phone and a tablet computer, which can upload target problems, equipment states and on-site environment information found in the inspection process in real time, and the mobile terminal is integrated with a GPS positioning function to record the position information of the inspection personnel; the enterprise internal management system includes a device management system, a production scheduling system and a personnel management system, and the external data source includes a regulation database of a government safety supervision department and an industry accident case library. 6.The intelligent system for safety risk identification and hidden danger elimination according to claim 1, characterized in that: The data cleaning module can filter noise in the video monitoring image and correct or exclude abnormal data collected by the sensor; The extraction object of the feature extraction module includes: Video image data, including extraction of personnel behavior features and extraction of equipment appearance features, wherein the personnel behavior features include whether to wear a safety helmet and whether to operate in violation of rules, and the equipment appearance features include whether the equipment appearance is damaged and whether the equipment is normally running; Sensor data, including a change trend of sensor collected data and extraction of threshold deviation data; Text data, including extraction of set keywords and key sentences.

7. The intelligent system for safety risk identification and hidden danger elimination according to claim 1, characterized in that: The knowledge base contains safety risk types, risk features, hidden danger forms, and corresponding judgment rules in different scenarios, wherein, for a chemical enterprise, the knowledge base includes storage and use specifications of various dangerous chemicals and corresponding risk identification points. 8.The intelligent system for safety risk identification and hidden danger elimination according to claim 1, characterized in that: The intelligent matching and analysis module uses natural language processing technology to perform semantic understanding and matching on the text data, uses an image recognition algorithm to perform pattern recognition on the video image, and performs real-time monitoring and abnormality judgment on the sensor data through a data analysis model. 9.The intelligent system for safety risk identification and hidden danger elimination according to claim 1, characterized in that: The early warning and disposal module sends early warning information to relevant personnel in time through any of the following forms: short message, email, and APP push, and informs the risk type, location, and severity; Through the mobile terminal and the system platform, the disposal process is tracked and recorded in real time, and the hidden danger disposal result is fed back and audited, forming a closed-loop management.

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