Intelligent exploration early warning safety helmet capable of modeling and simulating in real time

Abstract

The invention relates to the technical field of safety construction, and provides an intelligent exploration early warning safety helmet capable of modeling and simulating in real time, which comprises a safety helmet main body and a camera shooting assembly, and further comprises HMD equipment, a GPS positioning device, a communication module and an intelligent assembly, the intelligent assembly carries a 2D-to-3D algorithm based on a diffusion model and a GPU accelerated substance point method; the camera component realizes 2D-3D conversion of a collected multi-view-angle omnibearing image through a diffusion model in the intelligent component to generate a three-dimensional point cloud model; the three-dimensional point cloud model is imported into a GPU acceleration material point method through a self-compiled python interface to achieve analog simulation of the current working condition, a simulation result is obtained, and a safety report is returned. According to the invention, multi-view omnibearing images can be collected, an accurate surrounding geologic body point cloud model can be built, a high-precision simulation result can be rapidly obtained, and rapid acquisition of a mine operation environment and accurate early warning of disaster risks can be realized.

Description

Technical Field

[0001] This invention relates to the field of safe construction technology, specifically to an intelligent exploration and early warning safety helmet capable of real-time modeling and simulation. Background Technology

[0002] Traditional safety helmets primarily function to protect workers' heads from impacts by falling objects. Their structure typically consists of a shell, liner, and strap, and the main materials are HDPE, ABS plastic, and fiberglass. Traditional safety helmets only protect the worker's head and lack the ability to monitor the surrounding environment and provide early warnings of hazards. This prevents workers from anticipating and avoiding disasters in a timely manner, thus posing a significant safety risk.

[0003] To address the shortcomings of traditional safety helmets in environmental monitoring, several helmets designed for ambient environmental monitoring have emerged on the market. However, these helmets can only monitor the current environmental conditions and cannot provide a complete and clear analysis of the exploration environment, assess safety, or accurately predict risks. Furthermore, there are delays in data collection and feedback response, making it difficult for workers and managers to make timely and accurate assessments of the work environment.

[0004] For example, in mining engineering operations, workers often need to survey environmental factors such as terrain and landforms in advance. However, most safety helmets on the market have limited functions and are severely inadequate in terms of exploration and disaster early warning. Among existing technologies, the intelligent random-shooting safety helmet for monitoring engineering construction processes, disclosed in patent publication number CN11949588A, can be used to monitor work activities and improve management efficiency, but it has limited functions, lacks disaster early warning capabilities, and can still suffer serious consequences due to communication delays caused by on-site network problems. The intelligent safety helmet with voice function disclosed in patent publication number CN220212055U can simultaneously capture images from both the front and rear of the user during use, enhancing work recording capabilities and enabling signal transmission via a remote communication module. However, in practical applications, it falls short in terms of early warning, communication, and positioning, and it cannot monitor the environment in 360 degrees, failing to provide comprehensive protection for workers.

[0005] Furthermore, during on-site surveys in rugged mountainous areas, it is necessary to combine the survey environment with modeling and simulation analysis to conduct a detailed analysis of the safety of the soil and rock masses. However, the surveying by technicians and the modeling by engineers consume a significant amount of time. To save time on modeling and simulation, most studies choose to simplify 3D scenes to 2D for modeling, but this fails to reflect actual working conditions and sacrifices simulation accuracy. Moreover, data obtained through manual on-site surveys may lack the accuracy required for modeling due to various objective factors. Combined with complex or dangerous environments, these factors increase the safety risks for surveyors. Summary of the Invention

[0006] The purpose of this invention is to provide an intelligent exploration and early warning safety helmet that can be modeled and simulated in real time, in order to solve the problems mentioned in the background art, such as the single function of traditional safety helmets, the inability to provide exploration and early warning, the inefficiency of traditional exploration methods, and the inaccuracy of environmental monitoring.

[0007] To achieve the above objectives, the present invention provides the following technical solution: an intelligent exploration and early warning safety helmet capable of real-time modeling and simulation, comprising a helmet body and a camera component. The intelligent exploration and early warning safety helmet further includes an HMD device, a GPS positioning device, a communication module, and intelligent components. The intelligent components are equipped with a 2D-to-3D algorithm based on a diffusion model and a GPU-accelerated material point method. The camera component converts the acquired multi-view, all-around images from 2D to 3D using the diffusion model in the intelligent components, generating a 3D point cloud model. The 3D point cloud model is imported into the GPU-accelerated material point method through a self-developed Python interface to simulate the current working conditions and obtain simulation results.

[0008] As a further embodiment of the present invention, the camera components are respectively located on the front, left and right sides and top of the helmet body, the HMD device is installed at the bottom edge of the helmet body, the GPS positioning device is installed on the top of the helmet body, the communication module is located on the top of the helmet body, and the smart components are mounted on a cloud platform.

[0009] As a further aspect of the present invention, the camera component, HMD device, GPS positioning device and communication module are electrically connected; the communication module and intelligent component interact with each other via electrical signals.

[0010] As a further aspect of the present invention, the camera assembly consists of four cameras to achieve comprehensive collection of environmental information; the camera assembly has two shooting modes: one is to collect images at a certain frequency, and the other is to collect images by manually pressing the shutter button.

[0011] As a further aspect of the present invention, the simulation results can be returned to the user terminal in the form of a security report. The user terminal is an HMD device and a mobile APP, and the user can view the security report from the HMD device and the mobile APP.

[0012] As a further embodiment of the present invention, a light is installed on the main body of the safety helmet.

[0013] As a further aspect of the present invention, the multi-view omnidirectional image is transmitted to an intelligent component deployed on a cloud platform via a communication module. The intelligent component performs preprocessing on the multi-view omnidirectional image, including noise reduction, subject segmentation, and resolution improvement.

[0014] As a further aspect of the present invention, the GPU-accelerated material point method employs a GPU-accelerated architecture to improve computational efficiency. By iterating over each material point and each background grid node, a series of GPU threads are allocated to solve the problem in parallel.

[0015] As a further aspect of the present invention, a lightweight rechargeable lithium battery is installed in the main body of the safety helmet.

[0016] As a further aspect of the present invention, the communication module integrates 5G and Wi-Fi technologies, enabling the real-time transmission of the generated 3D point cloud model data to a remote server.

[0017] In summary, the beneficial effects of this invention are: Capable of acquiring multi-view, all-around images, the intelligent components are equipped with a 2D-to-3D algorithm based on a diffusion model and a GPU-accelerated material point method, enabling the construction of accurate point cloud models of the surrounding environment and obtaining simulation results. This achieves rapid acquisition of the mining operation environment and accurate early warning of disaster risks, effectively helping mining workers avoid disaster risks and improving work efficiency. Attached Figure Description

[0018] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort, wherein: Figure 1 This is a schematic diagram of the structure of an intelligent exploration early warning safety helmet capable of real-time modeling and simulation, according to an embodiment of the present invention.

[0019] Figure 2 This is a schematic diagram illustrating the working principle of an intelligent exploration early warning safety helmet capable of real-time modeling and simulation, according to an embodiment of the present invention.

[0020] Figure 3 This is a schematic diagram illustrating the effect of an intelligent exploration early warning safety helmet capable of real-time modeling and simulation, according to an embodiment of the present invention.

[0021] Reference numerals: 1-Helmet body, 2-Camera assembly, 3-HMD device, 4-GPS positioning device, 5-Communication module, 6-Smart component. Detailed Implementation

[0022] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to the accompanying drawings and specific embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the invention.

[0023] The specific implementation of the present invention will be described in detail below with reference to specific embodiments.

[0024] Please see Figures 1-3 This invention provides an intelligent exploration and early warning safety helmet capable of real-time modeling and simulation, comprising a helmet body 1 and a camera component 2. The intelligent exploration and early warning safety helmet also includes an HMD device 3, a GPS positioning device 4, a communication module 5, and an intelligent component 6. The intelligent component 6 is equipped with a 2D-to-3D algorithm based on a diffusion model and a GPU-accelerated material point method. The camera component 2 collects multi-view, omnidirectional images and converts them from 2D to 3D through the diffusion model in the intelligent component 6 to generate a three-dimensional point cloud model. The three-dimensional point cloud model is imported into the GPU-accelerated material point method through a self-developed Python interface to simulate the current working condition and obtain simulation results.

[0025] In this embodiment of the invention, the camera component 2 is located on the front, left and right sides and top of the helmet body 1, the HMD device 3 is installed at the bottom edge of the helmet body 1, the GPS positioning device 4 is installed on the top of the helmet body 1, the communication module 5 is located on the top of the helmet body 1, and the smart component 6 is mounted on a cloud platform.

[0026] In this embodiment of the invention, the camera component 2, HMD device 3, GPS positioning device 4 and communication module 5 are electrically connected; the communication module 5 and intelligent component 6 interact with each other via electrical signals.

[0027] In this embodiment of the invention, the camera assembly 2 consists of four cameras to achieve comprehensive environmental information collection. The camera assembly 2 has two shooting modes: one is to capture images at a certain frequency, and the other is to manually capture images by pressing the shutter button. The timed shooting function in this embodiment uses a real-time clock and calculator inside the camera to shoot at intervals of 1s to 99h59m59s set by the user, ensuring continuous image capture and reducing errors. In addition, a manual shooting function is provided, increasing the flexibility of the helmet's use. By installing high-definition cameras on the front, sides, and top of the helmet, and employing autofocus and image stabilization technology, the captured 2D images are ensured to be clear. The front camera is responsible for recording the main scene directly in front, the side cameras are responsible for acquiring lateral information, and the top camera is used to capture images of the area above the head, reducing blind spots and ensuring that image data can be collected from all directions.

[0028] In this embodiment of the invention, the simulation results can be returned to the user terminal in the form of a safety report. The user terminal is an HMD device 3 and a mobile APP. Users can view the safety report from the HMD device 3 and the mobile APP, thereby providing timely and accurate early warning information for operators and effectively reducing the safety risks to operators.

[0029] In this embodiment of the invention, a light is installed on the main body 1 of the safety helmet to adapt to dim and complex environments such as mines. A lightweight, high-capacity rechargeable lithium battery is installed in the main body 1 to provide stable power to the various modules of the safety helmet, ensuring sufficient battery life.

[0030] In this embodiment of the invention, the multi-view omnidirectional images are transmitted to the intelligent component 6 deployed on the cloud platform via the communication module 5. The intelligent component 6 preprocesses the multi-view omnidirectional images, including noise reduction, subject segmentation, and resolution improvement. The intelligent safety helmet of this embodiment is equipped with an adjustable high-definition HMD, which can present the 3D model generated in the cloud to the surveyors in real time, prompting them to identify which environmental details need to be photographed. This provides a solid guarantee for the safety of subsequent workers by enabling them to conduct comprehensive and accurate surveys of the working environment. Simultaneously, it provides workers with operational guidelines and managers with a model for familiarizing themselves with the working environment, greatly improving both operational and management efficiency.

[0031] In this embodiment of the invention, the GPU-accelerated material point method employs a GPU-accelerated architecture to improve computational efficiency. By iterating over each material point and each background mesh node, a series of GPU threads are allocated to solve the problem in parallel, significantly improving computational efficiency. Compared to mesh-based methods such as the finite element method, the iterative information mapping between material points and the background mesh effectively avoids mesh distortion, giving it a natural advantage in handling large deformation problems. This provides a powerful tool for analyzing mine disasters such as spoil heap instability and landslides, and mine collapses. The communication module 5 integrates 5G and Wi-Fi technologies, enabling real-time transmission of the generated 3D point cloud model data to a remote server for easy data storage and backup.

[0032] The working process of this invention is as follows: First, the four cameras of the camera component 2 capture multi-view, all-around environmental images; then, the environmental images are uploaded to the intelligent component 6 deployed on the cloud platform via the communication module 5; the intelligent component 6 first performs preprocessing on the images, such as noise reduction, subject segmentation, and resolution improvement, and then converts the multi-view 2D images into 3D point cloud models using a diffusion model, and imports them into a GPU-accelerated material point method program for calculation and simulation; finally, the material point method simulation results are output locally and can be viewed using HMD devices and APPs. Through the four-stage closed-loop solution of "environmental photography → 2D to 3D modeling → material point method simulation analysis → user terminal obtaining safety reports", the rapid acquisition of the mining operation environment and accurate early warning of disaster risks are realized, effectively helping mine workers avoid disaster risks and improving work efficiency. It has broad application prospects in the field of mine safety and has great potential for promotion to other fields such as disaster prevention and mitigation.

[0033] While several embodiments and examples of the present invention have been described for those skilled in the art, these embodiments and examples are provided as examples and are not intended to limit the scope of the invention. These new embodiments can be implemented in various other ways, and various omissions, substitutions, and modifications can be made without departing from the spirit of the invention. These embodiments and their variations are included within the scope and spirit of the invention, and are included within the scope of the invention as described in the claims and its equivalents.

[0034] Furthermore, it should be understood that although this specification describes embodiments, not every embodiment contains only one independent technical solution. This narrative style is merely for clarity. Those skilled in the art should consider the specification as a whole, and the technical solutions in each embodiment can also be appropriately combined to form other embodiments that can be understood by those skilled in the art.

Claims

1. A smart exploration early warning safety helmet capable of real-time modeling and simulation, comprising a helmet body (1) and a camera assembly (2), characterized in that, The intelligent exploration early warning safety helmet also includes an HMD device (3), a GPS positioning device (4), a communication module (5), and an intelligent component (6). The intelligent component (6) is equipped with a 2D to 3D algorithm based on a diffusion model and a GPU-accelerated material point method. The camera component (2) converts the multi-view all-around images it collects into 2D to 3D through the diffusion model in the intelligent component (6) to generate a three-dimensional point cloud model. The three-dimensional point cloud model is used to simulate the current working condition by importing the GPU-accelerated material point method through a self-developed Python interface to obtain simulation results.

2. The intelligent exploration early warning safety helmet capable of real-time modeling and simulation according to claim 1, characterized in that, The camera components (2) are located on the front, left and right sides and top of the helmet body (1), the HMD device (3) is installed at the bottom edge of the helmet body (1), the GPS positioning device (4) is installed on the top of the helmet body (1), the communication module (5) is located on the top of the helmet body (1), and the smart component (6) is mounted on the cloud platform.

3. The intelligent exploration early warning safety helmet capable of real-time modeling and simulation according to claim 1, characterized in that, The camera component (2), HMD device (3), GPS positioning device (4) and communication module (5) are electrically connected; the communication module (5) and intelligent component (6) interact with each other through electrical signals.

4. The intelligent exploration early warning safety helmet capable of real-time modeling and simulation according to claim 1, characterized in that, The camera component (2) consists of four cameras to achieve comprehensive collection of environmental information; the camera component (2) has two camera modes: one is to collect images at a certain frequency, and the other is to collect images by manually pressing the shutter button.

5. The intelligent exploration early warning safety helmet capable of real-time modeling and simulation according to claim 1, characterized in that, The simulation results can be returned to the user terminal in the form of a security report. The user terminal is the HMD device (3) and the mobile APP. The user can view the security report on the HMD device (3) and the mobile APP.

6. The intelligent exploration early warning safety helmet capable of real-time modeling and simulation according to claim 1, characterized in that, The helmet body (1) is equipped with a light.

7. The intelligent exploration early warning safety helmet capable of real-time modeling and simulation according to claim 1, characterized in that, The multi-view omnidirectional images are transmitted to the intelligent component (6) deployed on the cloud platform through the communication module (5). The intelligent component (6) will preprocess the multi-view omnidirectional images, including noise reduction, subject segmentation and resolution improvement.

8. The intelligent exploration early warning safety helmet capable of real-time modeling and simulation according to claim 1, characterized in that, The GPU-accelerated material point method employs a GPU-accelerated architecture to improve computational efficiency. It solves the problem in parallel by iterating over each material point and each background grid node, and allocating the solution to a series of GPU threads.

9. The intelligent exploration early warning safety helmet capable of real-time modeling and simulation according to claim 1, characterized in that, The helmet body (1) is equipped with a lightweight rechargeable lithium battery.

10. The intelligent exploration early warning safety helmet capable of real-time modeling and simulation according to claim 1, characterized in that, The communication module (5) integrates 5G and Wi-Fi technologies, enabling it to transmit the generated 3D point cloud model data to a remote server in real time.

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