Excavation construction safety training system and method

Abstract

The invention provides an excavation construction safety training system and method. The system comprises a data acquisition module which is used for acquiring data by adopting intelligent equipment; the communication module is used for constructing a real-time network by adopting field communication, realizing data integration and transmitting instructions; the intelligent identification module is used for performing subject identification and risk identification through artificial intelligence; and the central processing module is used for making a decision and generating a control instruction by integrating data. The training method comprises the steps that a training scene is constructed, intelligent equipment is provided for constructors, and the construction environment and personnel operation are monitored in real time; the trainee firstly reads the operation instruction and the safety manual of the construction process, and enters practical simulation assessment after the operation instruction and the safety manual are qualified through pen test assessment; before the training is started, simulating an unexcavated state by shielding a part of scenes; a camera and intelligent equipment are combined with an artificial intelligence technology to identify the identity and operation action of a constructor in real time; in the construction operation process, trainees and other personnel trigger various accident points and trigger corresponding punishment measures in the intelligent helmet, and the effectiveness of construction safety training and the safety management level of a construction site are improved.

Description

Technical Field

[0001] The invention relates to the field of construction process safety training, and in particular to an excavation construction safety training system and method. Background Art

[0002] In the field of construction safety training, traditional training methods have some significant deficiencies, which seriously affect the training effect and the safety of the construction site. First, the safety awareness of construction workers is generally insufficient, which is mainly because the traditional training methods are too theoretical and lack training combined with actual operations. Secondly, due to the lack of high-tech auxiliary tools, such as intelligent equipment and artificial intelligence technology, the existing training and monitoring methods cannot capture the dynamic changes of the construction site in real time, resulting in insufficient response to illegal operations and potential risks. In addition, risk assessment usually relies on subjective judgment and experience, lacking objectivity and precision. The existing feedback mechanism is not perfect, and construction workers rarely get immediate feedback on the correctness of their operations. The application of technology in training is far behind, and modern data analysis and processing capabilities are not fully utilized, which makes the training content and methods update slowly and cannot reflect the latest developments in the industry in a timely manner. The existing assessment mechanism is also not perfect, lacking standardized assessment processes and automated tools, making the assessment of construction workers' skills inaccurate and inconsistent. Therefore, there is an urgent need for an excavation construction safety training system that adopts innovative methods and advanced technologies to improve the effectiveness of construction safety training and the safety management level of the construction site. Summary of the invention

[0003] In order to solve the technical problems in the above background, the present invention provides an excavation construction safety training system, including a data acquisition module, a communication module, an intelligent identification module and a central processing module; The data acquisition module is used to acquire data using intelligent equipment; The communication module is used to build a real-time network using on-site communication, realize data integration, and convey instructions; The intelligent identification module is used to identify subjects and risks through artificial intelligence; The central processing module is used to integrate data, make decisions and generate control instructions.

[0004] In a preferred solution, the intelligent identification module includes a positioning and posture unit and a risk identification unit; The positioning and posture unit includes intelligent equipment, and the risk identification unit includes sensors and cameras.

[0005] In a preferred solution, the smart equipment includes a smart helmet, a positioning bracelet and a positioning foot ring; The smart helmet is equipped with an AR display system. In the preferred solution, the smart helmet is also provided with a GPS or Beidou positioning chip to receive geographic location information, and the smart helmet is also provided with a posture sensor, including a gyroscope and an acceleration sensor, to correct the positioning information and collect posture information, namely, three-dimensional coordinates (X, Y, Z) and three-dimensional rotation angle, roll angle, yaw angle and pitch angle; The smart helmet also has binocular vision, which is used to locate the position and posture of the hands within the field of view, and is also used to collect real scenes; The smart helmet is also equipped with a distance locator, which is a signal receiver. There are two signal receivers for receiving information sent by the positioning bracelet and positioning foot ring, and calculating the position of the hands and feet.

[0006] In the preferred solution, a punishment system is also provided in the smart helmet, including a vibration device, a heat sensing device, a strong light simulation, a blindness simulation, a needle pricking device and a noise device; The vibration device is used to make the user slightly dizzy. The vibration device uses a variable frequency vibrator, which is placed near the ear. The cochlea feels dizzy by using a specific vibration frequency. The vibration device is used to simulate the state of being hit by falling rocks; The thermal sensing device is a resistance heating device with a limit temperature of 45 degrees Celsius for 30 seconds. The thermal sensing device is used to simulate the state of fire; The strong light simulation uses AR full white mode for about 5 seconds. The strong light device is used in combination with the thermal device to simulate the state of the explosion. The blindness simulation uses AR in full black for 30 seconds to simulate being buried; The acupuncture device has electrodes placed close to the skin inside the smart helmet, which simulate the effect of acupuncture by discharging electrodes, and is used to simulate the state of being hit by sharp energy; The noise device uses white noise or argument sounds to simulate the state of an argument with the victim or other parties after an accident, which lasts for 30 seconds.

[0007] In a preferred embodiment, the smart helmet is also provided with an otolith stimulation device, which simulates the effect of otolith movement by gently shaking or vibrating the user's head to produce a feeling of dizziness.

[0008] In the preferred solution, risk identification includes on-site identification, in-depth identification and pipeline identification.

[0009] In the preferred solution, the identification of the hand position and posture first takes the head position as a reference and the maximum distance between the hand and the head as a range; Within the field of view, the hand position and posture are mainly corrected by binocular vision image recognition, supplemented by the distance measurement of the signal receiver; Outside the field of view, the positioning bracelet sends a signal with a timestamp. After the two distance locators receive the signal, they calculate the distance between them and the positioning bracelet based on the time difference, and use the triangulation algorithm to obtain the coordinates of the positioning bracelet. Based on whether it is within the field of view, the specific position of the hand is determined; The positioning of the positioning foot ring is the same as that of the positioning wrist ring; The positioning wristband and positioning footband send signals respectively in a differential manner.

[0010] A training method using an excavation construction safety training system comprises the following steps: S1. Build training scenarios and equip construction workers with intelligent equipment to monitor the construction environment and personnel operations in real time; S2. The trainees first read the operating procedures and safety manual of the construction process, and then enter the practical simulation assessment after passing the written examination; S3. In the initial state, the construction trench, construction ramp, and various pipelines are real scenes. Before the training begins, the construction trench, construction ramp, and various pipelines are shielded by the AR display device to simulate the unexcavated state; S4. Use cameras and smart equipment combined with artificial intelligence technology to identify the identity and operation actions of construction workers in real time; S5. During the construction operation, various accident points are triggered by trainers and other personnel, and corresponding punishment measures in the smart helmet are triggered.

[0011] In the preferred solution, the training scene includes a construction trench, in which water supply pipes, gas pipes and cable pipes are arranged, as well as optical fiber and sewage pipes. A construction ramp is arranged at one end of the construction trench, a supporting device is arranged in the construction trench, and virtual guardrails are arranged around the construction trench.

[0012] In the preferred solution, the image data captured by the camera is analyzed by a deep learning model to identify the identity of the construction workers; the data obtained by the smart equipment is processed by a machine learning algorithm to trigger corresponding punishment measures in the smart helmet.

[0013] In the preferred solution, the practical simulation assessment has several accident points, and the number of times the assessment is passed is the number of accident points + n, where n is 1 to 5, to ensure that the trainees have experienced all accident points and the same accident will not occur repeatedly.

[0014] In the preferred solution, other virtual personnel are arranged around the construction trench, including other construction personnel and onlookers; When the trainer fails to trigger an accident, other virtual personnel, including other construction workers or other onlookers, are controlled to trigger corresponding accidents.

[0015] In a preferred solution, the training personnel perform construction according to the construction operation procedures, and during the construction process, the AR display device gradually releases the shielded real scene, and the AR display device also gradually displays virtual facilities.

[0016] In the preferred scheme, the severity of the accident is divided into two types: triggered by the training personnel themselves and triggered by other personnel. The severity is judged based on the relative position between the training personnel and the accident point. The relative position is divided into three levels, which constitute 6 levels of severity. Each level of severity is combined with the on-site conditions and corresponds to different punishment measures.

[0017] In the preferred solution, each accident point includes but is not limited to: Falling accidents due to the lack of guardrails trigger the vibration device, blindness simulation, acupuncture device, or any combination of the three, depending on the severity; Improper excavation operation or failure to conduct pipeline inspection, or inaccurate inspection, resulting in the pipeline being cut, triggering the vibration device, thermal sensing device, strong light simulation, noise device or any combination of the four depending on the severity; If the fire source is not controlled at the scene, resulting in fire or explosion, the vibration device, heat sensing device, strong light simulation, acupuncture device, noise device or any combination of the five will be triggered according to the severity; Failure to properly set up support devices results in the collapse of the slope and burial. Depending on the severity, the vibration device, blindness simulation, acupuncture device or any combination of the three is triggered.

[0018] The beneficial effects of the present invention are as follows: the present invention adopts a training measure that combines real scenes and virtual scenes, so that the trainees can experience the construction process in an immersive way, monitor the construction environment and personnel operations in real time, identify unsafe behaviors and potential risks in a timely manner, and provide instant feedback through intelligent equipment. Various accidents that occur during the construction process, as well as the corresponding consequences brought about by the accidents, greatly improve the effect of excavation construction safety training, improve construction safety awareness, and reduce the probability of subsequent accidents during the construction process. By setting accident points and combining punishment measures, safety training for trainees can be achieved, thereby greatly improving the training effect. The system also integrates a variety of advanced technologies such as smart helmets, positioning bracelets, positioning foot rings, GPS and Beidou positioning, reflecting technological innovation in the field of construction safety training. By reducing the occurrence of safety accidents, construction interruptions and delays caused by accidents can be avoided, thereby improving construction efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] Figure 1 is a schematic diagram of a training scenario of the present invention; Figure 2 It is a system structure diagram of the present invention; Figure 3 is a flow chart of the method of the present invention; In the figure, there are training personnel (1), guardrails (2), construction ramps (3), support devices (4), construction trenches (5), water supply pipelines (6), gas pipelines (7), cable pipelines (8), and other personnel (9). DETAILED DESCRIPTION

[0020] like Figures 1 to 3 A system and method for training safety in excavation construction is shown.

[0021] Example 1 1. Construct a training scenario. The training scenario includes a construction trench 5. A water supply pipe 6, a gas pipe 7 and a cable pipe 8 are arranged in the construction trench 5. Optical fiber, sewage pipes and other facilities may also be added. A construction ramp 3 is arranged at one end of the construction trench 5. A supporting device 4 is arranged in the construction trench 5. A virtual guardrail 2 is arranged around the construction trench 5, and other virtual personnel 9 are arranged around it. The other personnel 9 include other construction personnel and onlookers.

[0022] 2. Smart equipment: Smart equipment includes smart helmets, positioning bracelets and positioning foot rings. The smart helmet is equipped with an AR display system.

[0023] Positioning and attitude module, the smart helmet is equipped with a GPS or Beidou positioning chip to receive geographic location information. The smart helmet is also equipped with an attitude sensor, including a gyroscope and an accelerometer, to correct the positioning information and collect attitude information, namely three-dimensional coordinates (X, Y, Z) and three-dimensional angles, roll angle, deflection angle and pitch angle. The smart helmet is also equipped with binocular vision, which is used to locate the position and attitude of the hands in the field of view. Binocular vision is also used to collect real scenes. The smart helmet is also equipped with a distance locator, which is a signal receiver. There are two signal receivers, which are used to receive information sent by the positioning bracelet and the positioning foot ring, and calculate the position of the hands and feet. Hand posture and position recognition first takes the head position as the reference and the maximum distance between the hand and the head as the range. Within the field of view, the hand position and posture are mainly corrected by binocular vision image recognition, supplemented by the ranging of the signal receiver. Outside the field of view, the positioning bracelet sends a signal with a timestamp. After the two distance locators receive the signal, they calculate the distance to the positioning bracelet based on the time difference, and use the triangulation algorithm to obtain the coordinates of the positioning bracelet. Based on whether it is within the field of view, the specific position of the hand is determined. The positioning of the positioning foot ring is the same as that of the positioning bracelet. To avoid interference, the positioning bracelet and the positioning foot ring use a differential method to send signals separately. For example, the interval time between each positioning bracelet and positioning foot ring is 200ms, and the sending time between each other is staggered.

[0024] There is also a penalty system in the smart helmet, including 1. A vibration device is used to make the user feel slightly dizzy. The vibration device uses a variable frequency vibrator, which is placed near the ear. It uses a specific vibration frequency to make the cochlea feel dizzy. The vibration device is used to simulate the state of being hit by falling rocks.

[0025] There are many ways to produce dizziness. The following methods or devices can be used to produce dizziness in virtual experience scenes: (1) Visual stimulation: Using visual illusions or fast-moving images to stimulate the brain, thereby producing a sense of dizziness. For example, a rapidly rotating or swaying pattern can visually induce dizziness.

[0026] (2) Head tracking: Using head tracking technology, the user's head movement is mapped to the virtual environment in real time. When the head movement is not synchronized with the visual feedback, dizziness may occur.

[0027] (3) Otolith stimulation device: Although it is difficult to directly stimulate the otoliths, a device can be designed to simulate the effect of the movement of the otoliths by gently shaking or vibrating the user's head, thereby producing a sense of dizziness to a certain extent.

[0028] (4) Directional sound: Using directional sound technology, a sound environment is created in which the sound seems to move in space. This mismatched auditory information may cause dizziness in users.

[0029] Specific software algorithms can also be developed to adjust the intensity and type of stimulation in the virtual environment by analyzing the user's physiological reactions (such as eye movements, heart rate, etc.) to achieve more precise control of dizziness.

[0030] 2. Thermal sensing device: The thermal sensing device is a resistance heating device with a temperature limit of 45 degrees Celsius and lasts for 30 seconds. The thermal sensing device is used to simulate a fire condition.

[0031] 3. Strong light simulation, using AR all-white simulation, lasts for about 5 seconds. The strong light device is used in combination with the thermal sensing device to simulate the state of the explosion.

[0032] 4. Blindness simulation, using AR full black mode for 30 seconds to simulate the state of being buried.

[0033] 5. Acupuncture device: electrodes are installed in the smart helmet close to the skin, which uses electrode discharge to simulate the effect of acupuncture and is used to simulate the state of being hit by sharp air.

[0034] 6. Noise device: Use white noise or quarrel sounds to simulate the state of quarreling with the victim or other parties after the accident, which lasts for 30 seconds.

[0035] 3. Training steps: 1. The trainees shall first read the operating procedures and safety manual of the construction process, and then enter the practical simulation assessment after passing the written examination.

[0036] 2. There are multiple accident points in the practical simulation assessment. The number of times the assessment is passed is the number of accident points + n, where n is (1-5), to ensure that the trainees have experienced all accident points and the same accident will not occur repeatedly. If the trainees do not trigger an accident, the control system controls other virtual personnel 9, including other construction workers or other onlookers, to trigger the corresponding accident.

[0037] 3. In the initial state, the construction trench 5, construction ramp 3, and various pipelines are real scenes. Before the training starts, the construction trench 5, construction ramp 3, and various pipelines are shielded by the AR display device to simulate the un-excavated state.

[0038] The trainee 1 performs construction according to the construction operation procedures, and during the construction process, the AR display device gradually releases the shielded real scene, such as gradually opening the shielding of the construction trough 5, the construction ramp 3, and various pipelines. As the construction progresses, the AR display device also gradually displays virtual facilities, such as guardrails 2, support devices 4, and other personnel 9. During the construction operation, the trainee 1 and other personnel 9 trigger various accident points and trigger corresponding punishment measures in the smart helmet.

[0039] 4. Accident points include but are not limited to: 4.1. A fall accident caused by failure to install guardrail 2 triggers 1. a vibration device, 4. a blindness simulation, and 5. acupuncture device according to the severity. Trigger one or a combination of these.

[0040] 4.2. Improper excavation operation or failure to conduct pipeline inspection, or inaccurate inspection, resulting in the breaking of the pipeline, triggers 1. vibration device, 2. thermal sensing device, 3. strong light simulation and 6. noise device according to the severity. Trigger one or more combinations of them.

[0041] 4.3. If the fire source is not controlled on site, resulting in fire or explosion, according to the severity, trigger 1. vibration device, 2. thermal device, 3. strong light simulation, 5. acupuncture device and 6. noise device. Trigger one or more of the combinations.

[0042] 4.4. Failure to properly set up the support device 4 results in the collapse of the slope and burial. Depending on the severity, 1. the vibration device, 4. the blindness simulation and 5. the acupuncture device are triggered. One or more combinations thereof are triggered.

[0043] 4.5. Improper operation of construction equipment leads to casualties of oneself or others. According to the severity, trigger 1. vibration device, 4. blindness simulation, 5. acupuncture device, 6. noise device. Trigger one or more combinations thereof.

[0044] The severity of the accident is divided into self-triggered by training personnel 1 and triggered by other personnel 9. The severity is judged based on the relative position between training personnel 1 and the accident point. The relative position is divided into three levels, which constitute 6 levels of severity. Each level of severity corresponds to different punishment measures based on the on-site conditions.

[0045] Through the above steps, safety training for trainees can be achieved. Since trainees experience the punishment measures brought about by various accident points, the training effect is greatly improved.

[0046] Example 2 An excavation construction safety training system includes a data acquisition module, a communication module, an intelligent identification module, a central processing module and a training content setting module; The data acquisition module is responsible for acquiring data using intelligent equipment; The communication module is responsible for building a real-time network using on-site communications, achieving data integration, and conveying instructions; The intelligent identification module is responsible for subject identification and risk identification through artificial intelligence; The central processing module is responsible for integrating data, making decisions and generating control instructions; The training content setting module is responsible for setting standard operations and illegal operations, and providing operation guidance and feedback.

[0047] Preferably, the intelligent identification module includes a subject identification unit, an action identification unit, a location identification unit and a risk identification unit; Among them, the subject recognition unit includes cameras and intelligent equipment, the action recognition unit includes cameras, the location recognition unit includes cameras, Beidou satellite navigation system and near-field detection system, and the risk recognition unit includes sensors and cameras; Preferably, the camera is responsible for capturing real-time images of construction personnel, the Beidou satellite navigation system provides geographic positioning information, and the near-field detection system detects the relative position between construction personnel and construction equipment through wireless signals; The camera, BeiDou satellite navigation system and near-field detection system work together through an integrated data fusion algorithm.

[0048] Preferably, risk identification includes on-site identification, depth identification and pipeline identification.

[0049] Preferably, the smart equipment includes a smart helmet and AR equipment.

[0050] Preferably, it also includes an assessment module, which is responsible for setting up an assessment system and consolidating the effect of safety education by improving physical memory.

[0051] Preferably, the instructions that the central processing module may convey include the following types: Operation correction instructions: When the intelligent recognition module detects that the construction worker's operation is inconsistent with the preset standard operating procedures, the central processing module will issue instructions for correcting the operation; Safety warning: When potential safety risks or violations are identified, such as approaching a dangerous area or improper equipment operation, the central processing module will issue a safety warning; Emergency stop command: When the system detects a serious violation of safety regulations or an imminent major safety accident, the central processing module will issue an emergency stop command for all related operations; Support instructions: When the excavation reaches a certain depth, the central processing module will issue support instructions according to the preset program; Equipment control instructions: For automated or remote-controlled construction equipment, the central processing module can issue instructions to start, stop or adjust equipment operating parameters; Training content update instructions: Based on the construction personnel's operating performance and safety accident records, the central processing module can issue instructions to update the training content and methods; Assessment feedback instructions: After the construction personnel complete an operation or a stage of construction, the central processing module can issue assessment feedback based on the assessment results; Recording and reporting instructions: The central processing module can also instruct the system to record specific events and generate corresponding security reports for further analysis.

[0052] The above instructions are conveyed to the intelligent equipment or construction personnel through the communication module to ensure the safety and efficiency of the construction process. The design of the central processing module should ensure the timeliness, accuracy and executability of these instructions.

[0053] Preferably, the sensors of the risk identification unit include the following types: Motion sensors: monitor the movement of construction workers and equipment operation to ensure that no dangerous areas are entered or unsafe actions are performed; Proximity sensor: detects the distance between construction workers and dangerous equipment or areas, and issues a warning when the distance is too close; Pressure sensor: used to monitor pressure changes in soil, rock or other materials to prevent landslides or collapse; Vibration sensor: detects abnormal vibration during equipment operation to prevent equipment failure or operational errors; Sound sensors: Analyze sound patterns in the construction environment and identify abnormal sounds, such as signs of equipment failure; Visual sensor: Use cameras to capture visual information and use image recognition technology to analyze the behavior of construction workers and environmental conditions; Ultrasonic sensor: used to measure the distance between objects and prevent collisions between construction equipment; Electromagnetic field sensor: detects the strength of the electromagnetic field in a specific environment to prevent electromagnetic interference from affecting equipment or personnel; GPS / Beidou positioning sensor: provides precise geographic location information to ensure that construction personnel and equipment are in a safe location.

[0054] The above sensors can be used individually or in combination to provide comprehensive construction environment monitoring. By integrating sensors into the risk identification unit, the system can collect data in real time and analyze it through artificial intelligence algorithms, thereby timely identifying and warning of potential safety risks.

[0055] Example 3 The implementation steps of an excavation construction safety training method are as follows: The implementation steps of construction site safety monitoring and training include: 1. Deploy smart helmets and AR equipment at the construction site to provide construction workers with real-time construction environment and operation guidance; 2. The camera of the smart helmet captures the operation process of the construction workers, and the AR equipment displays standard operation steps and safety tips; 3. The central processing module analyzes the data collected from the intelligent equipment and monitors the changes in the construction environment and whether the personnel operations meet the safety standards in real time; 4. If the intelligent recognition module detects illegal operations or potential risks, the system will immediately issue an alarm through intelligent equipment and provide correct operation guidance; 5. After the construction is completed, the construction personnel’s operations will be evaluated through the assessment module, and rewards or punishments will be implemented based on the evaluation results.

[0056] Underground pipeline detection and support operation training includes the following steps: 1. Before construction, use intelligent equipment to detect and locate underground pipelines and synchronize the data to the central processing module; 2. Construction workers receive pipeline location information through AR equipment and follow the support operation instructions provided by the system during excavation; 3. When the construction depth reaches the preset value, the intelligent equipment automatically prompts the construction personnel to perform support operations to ensure construction safety; 4. The intelligent identification module monitors the support process to ensure that the operation complies with safety regulations and corrects any deviations in real time.

[0057] The implementation steps of construction safety training include: 1. Use intelligent equipment to identify risks and provide safety education to construction workers; 2. Use the Beidou satellite navigation system and near-field detection system to locate construction personnel and equipment in real time to avoid entering dangerous areas; 3. The intelligent identification module analyzes the construction environment, identifies possible compound risks, and promptly notifies construction personnel to take preventive measures; 4. The central processing module adjusts the construction plan based on real-time data to ensure that construction activities are carried out under safe conditions.

[0058] The implementation steps for construction personnel assessment and skills improvement are as follows: 1. Use the training content setting module to provide construction personnel with personalized safety operation training plans.

[0059] 2. In actual operation, intelligent equipment records the operation data of construction workers and conducts real-time analysis through the central processing module.

[0060] 3. Based on the construction personnel’s operating performance, the assessment module automatically generates an assessment report and provides improvement suggestions.

[0061] 4. For construction personnel who are evaluated as excellent, implement a reward mechanism to encourage them to continue to maintain high standards of operation; for construction personnel who need improvement, provide additional training and guidance.

[0062] Example 5 In the excavation construction safety training system, the training mode and the assessment mode are two key links, which together ensure that construction personnel can master the necessary safety knowledge and skills, and verify the training effect through assessment. The following is the division of labor of each module in the system in the two modes of training and assessment: 1. Training mode: The data collection module collects basic information about the construction environment and the operation data of construction personnel, providing real-time feedback for training; Smart equipment (smart helmets, AR equipment) provides construction workers with the training information and guidance they need, such as standard operating procedures, safety tips, etc.

[0063] A network of sensors monitors the construction environment and the movements of construction workers to ensure a safe training environment.

[0064] The communication module transmits training data and guidance information in real time to ensure timely updating of information.

[0065] The central processing module analyzes training data, provides personalized training suggestions and adjusts training content.

[0066] The intelligent recognition module identifies the construction workers' operations and provides instant feedback on the correctness of the operations.

[0067] The training content setting module sets the training courses, simulation scenarios and operation steps to ensure the comprehensiveness and pertinence of the training content.

[0068] The user interface displays training information and provides an operation interface, enabling construction personnel to receive training content and feedback.

[0069] 2. Assessment mode: The data collection module collects data from construction workers during actual operations to evaluate whether their operations meet safety standards.

[0070] Smart equipment (smart helmets, AR equipment) provides assessment guidance and operational requirements during the assessment process.

[0071] The sensor network monitors the construction workers' operations and the construction environment to ensure the accuracy and safety of the assessment.

[0072] The communication module transmits the assessment data to the central processing module for evaluation and recording.

[0073] The central processing module analyzes the assessment data to determine whether the construction personnel's operations comply with safety regulations.

[0074] The intelligent recognition module identifies and evaluates the operations of construction personnel and provides a basis for assessment results.

[0075] The training content setting module adjusts the training content according to the assessment results to ensure that the training is closely integrated with actual operations.

[0076] The assessment module sets assessment standards and procedures, and records and evaluates the construction personnel's operational performance.

[0077] The user interface displays assessment results and feedback, allowing construction personnel to understand their performance and areas for improvement.

[0078] The combined use of the above two modes can ensure that construction workers can work safely and effectively in actual operations.

[0079] Example 6 The excavation construction safety training system can also have a course learning module, which aims to deepen the construction personnel's understanding and mastery of safety knowledge through systematic education and theoretical learning. The system includes courses and courseware, which can continuously update and expand its teaching resources. The system will also count the increase in the monthly study hours of the staff members, and provide a study time chart over time to help understand the dynamic trend of learning activities. Statistics on course completion data, study time data, department ranking data and personal ranking data.

[0080] Develop and update course content, including safety regulations, operating standards, accident case analysis, risk assessment methods, etc.

[0081] Use a variety of media forms such as video, animation, charts and text to improve the richness and attractiveness of teaching materials.

[0082] Courses are delivered through an online learning management system (LMS), allowing construction workers to learn at any time and place.

[0083] The course design includes interactive sessions such as question-and-answer sessions, simulated scenarios and role-playing to enhance learning enthusiasm and effectiveness.

[0084] Provide personalized learning suggestions and progress tracking according to the different levels and needs of construction workers.

[0085] Supports access to course content through mobile devices such as smartphones and tablets, increasing learning flexibility.

[0086] Provide online testing and self-assessment tools to give construction workers instant feedback and provide coaching as needed.

[0087] Establish online communities and forums to encourage communication and discussion among construction workers and promote knowledge sharing.

[0088] Course content is updated regularly to ensure that training content is consistent with the latest safety standards and technological developments.

[0089] For construction personnel who have completed the course, an electronic certificate or certification is provided to prove their learning outcomes.

[0090] Combine course learning with practical operations to ensure that theoretical knowledge can be applied in actual operations.

[0091] The system's course learning module can effectively manage and track employees' learning progress, while providing rich course content to meet the learning needs of different trainees. The system's statistical function also provides management with valuable data to evaluate training effects and make corresponding strategic adjustments.

[0092] The above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit the same. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that the technical solutions described in the aforementioned embodiments may still be modified, or some of the technical features may be replaced by equivalents. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. An excavation construction safety training system, characterized by: It includes data acquisition module, communication module, intelligent identification module and central processing module; The data acquisition module is used to acquire data using intelligent equipment; The communication module is used to build a real-time network using on-site communication, realize data integration, and convey instructions; The intelligent identification module is used to identify subjects and risks through artificial intelligence; The central processing module is used to integrate data, make decisions and generate control instructions.

2. According to claim 1, the excavation construction safety training system is characterized by: The intelligent identification module includes a positioning and posture unit and a risk identification unit; The positioning and posture unit includes intelligent equipment, and the risk identification unit includes sensors and cameras.

3. According to claim 2, an excavation construction safety training system is characterized by: Smart equipment includes smart helmets, positioning bracelets and positioning foot rings; The smart helmet is equipped with an AR display system.

4. According to claim 3, the excavation construction safety training system is characterized by: The smart helmet is also equipped with a GPS or Beidou positioning chip to receive geographic location information. The smart helmet is also equipped with a posture sensor, including a gyroscope and an acceleration sensor, to correct the positioning information and collect posture information, namely three-dimensional coordinates (X, Y, Z) and three-dimensional rotation angle, roll angle, yaw angle and pitch angle; The smart helmet also has binocular vision, which is used to locate the position and posture of the hands within the field of view, and is also used to collect real scenes; The smart helmet is also equipped with a distance locator, which is a signal receiver. There are two signal receivers for receiving information sent by the positioning bracelet and positioning foot ring, and calculating the position of the hands and feet.

5. According to claim 3, the excavation construction safety training system is characterized by: There is also a punishment system in the smart helmet, including a vibration device, a heat sensing device, a strong light simulation, a blindness simulation, a needle device and a noise device; The vibration device is used to make the user slightly dizzy. The vibration device uses a variable frequency vibrator, which is placed near the ear. The cochlea feels dizzy by using a specific vibration frequency. The vibration device is used to simulate the state of being hit by falling rocks; The thermal sensing device is a resistance heating device with a limit temperature of 45 degrees Celsius for 30 seconds. The thermal sensing device is used to simulate the state of fire; The strong light simulation uses AR full white mode for about 5 seconds. The strong light device is used in combination with the thermal device to simulate the state of the explosion. The blindness simulation uses AR in full black for 30 seconds to simulate being buried; The acupuncture device has electrodes placed close to the skin inside the smart helmet, which simulate the effect of acupuncture by discharging electrodes, and is used to simulate the state of being hit by sharp energy; The noise device uses white noise or argument sounds to simulate the state of an argument with the victim or other parties after an accident, which lasts for 30 seconds.

6. According to claim 2, the excavation construction safety training system is characterized by: The smart helmet is also equipped with an otolith stimulation device, which simulates the effect of otolith movement by gently shaking or vibrating the user's head, creating a feeling of dizziness.

7. The excavation construction safety training system according to claim 2 is characterized by: Risk identification in the risk identification unit includes site identification, depth identification and pipeline identification.

8. The excavation construction safety training system according to claim 4 is characterized by: The recognition of hand position and posture first takes the head position as the reference and the maximum distance between the hand and the head as the range; Within the field of view, the hand position and posture are mainly corrected by binocular vision image recognition, supplemented by the distance measurement of the signal receiver; Outside the field of view, the positioning bracelet sends a signal with a timestamp. After the two distance locators receive the signal, they calculate the distance between them and the positioning bracelet based on the time difference, and use the triangulation algorithm to obtain the coordinates of the positioning bracelet. Based on whether it is within the field of view, the specific position of the hand is determined; The positioning of the positioning foot ring is the same as that of the positioning wrist ring; The positioning wristband and positioning footband send signals respectively in a differential manner.

9. A training method using the excavation construction safety training system according to any one of claims 1 to 8, characterized in that: The following steps are involved: S1. Build training scenarios and equip construction workers with intelligent equipment to monitor the construction environment and personnel operations in real time; S2. The trainees first read the operating procedures and safety manual of the construction process, and then enter the practical simulation assessment after passing the written examination; S3. In the initial state, the construction trench (5), the construction ramp (3), and various pipelines are real scenes. Before the training begins, the construction trench (5), the construction ramp (3), and various pipelines are shielded by the AR display device to simulate the unexcavated state; S4. Use cameras and smart equipment combined with artificial intelligence technology to identify the identity and operation actions of construction workers in real time; S5. During the construction operation, the training personnel (1) and other personnel (9) trigger various accident points and trigger corresponding punishment measures in the smart helmet.

10. The training method of the excavation construction safety training system according to claim 9, characterized in that: The training scenario includes a construction trench (5), in which a water supply pipeline (6), a gas pipeline (7) and a cable pipeline (8) are arranged, as well as optical fiber and sewage pipelines. A construction ramp (3) is arranged at one end of the construction trench (5), a supporting device (4) is arranged in the construction trench (5), and a virtual guardrail (2) is arranged around the construction trench (5).

11. The training method of the excavation construction safety training system according to claim 9, characterized in that: The image data captured by the camera is analyzed through a deep learning model to identify the identity of the construction workers; the data obtained by the smart equipment is processed through a machine learning algorithm to trigger corresponding punishment measures in the smart helmet.

12. The training method of the excavation construction safety training system according to claim 9, characterized in that: There are several accident points in the practical simulation assessment. The number of times the assessment is passed is the number of accident points + n, where n is 1 to 5. This ensures that the trainees have experienced all accident points and the same accident will not occur repeatedly.

13. The training method of the excavation construction safety training system according to claim 12, characterized in that: There are virtual other personnel (9) around the construction slot (5), and the other personnel (9) include other construction personnel and onlookers; When the trainee fails to trigger an accident, the trainee controls other virtual personnel (9), including other construction workers or other onlookers, to trigger a corresponding accident.

14. The training method of the excavation construction safety training system according to claim 9, characterized in that: The training personnel (1) perform construction according to the construction operation procedures. During the construction process, the AR display device gradually releases the shielded real scene and gradually displays virtual facilities.

15. The training method of the excavation construction safety training system according to claim 12, characterized in that: The severity of the accident is divided into two types: the training personnel (1) triggering it themselves and the other personnel (9) triggering it. The severity is determined by the relative position between the training personnel (1) and the accident point. The relative position is divided into three levels, which constitutes 6 levels of severity. Each level of severity corresponds to different punishment measures according to the on-site conditions.

16. The training method of the excavation construction safety training system according to claim 12, characterized in that: The various accident points include but are not limited to: A fall accident caused by the lack of guardrails (2) triggers the vibration device, blindness simulation, acupuncture device or any combination of the three, depending on the severity; Improper excavation operation or failure to conduct pipeline inspection, or inaccurate inspection, resulting in the pipeline being cut, triggering the vibration device, thermal sensing device, strong light simulation, noise device or any combination of the four depending on the severity; If the fire source is not controlled at the scene, resulting in fire or explosion, the vibration device, heat sensing device, strong light simulation device, acupuncture device, noise device or any combination of the five will be triggered according to the severity; Failure to properly set up the support device (4) results in the collapse of the slope and burial. Depending on the severity, the vibration device, blindness simulation, acupuncture device or any combination of the three is triggered.

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