Explosion-proof danger-eliminating disposal equipment

Abstract

The invention provides explosion-proof danger-eliminating disposal equipment. The equipment comprises a three-layer annular protection framework and an intelligent mobile platform framework, wherein the three-layer annular protection framework comprises a sensing layer, an execution layer and a protection layer; the intelligent mobile platform architecture comprises a multi-mode mobile chassis and an environment sensing system; the sensing layer comprises a detection equipment module and an intelligent identification and evaluation module; the execution layer comprises an emergency disposal equipment module; the protective layer comprises a protective storage and transportation equipment module; the sensing layer detects and senses data and information of dangerous goods in a field environment through a detection equipment module, and carries out risk assessment judgment and execution coping strategy formulation through an intelligent identification and assessment module; and the execution layer, the protection layer and the intelligent mobile platform operate the emergency disposal equipment module to perform danger elimination action according to the execution coping strategy. According to the method, through the whole-process closed-loop design of'perception-decision-disposal-protection ', the equipment damage rate is greatly reduced while the disposal efficiency is ensured, the risk elimination success rate of a complex binding scene is improved, and the single disposal cost is remarkably reduced.

Description

Technical Field

[0001] The present invention relates to the technical field of public safety, and particularly to an explosion-proof and risk-disposal equipment that integrates intelligent recognition, adaptive disposal and dynamic protection, and is applicable to crowded places such as subway stations and railway stations. Background Art

[0002] In crowded places such as subway stations and railway stations, some existing explosion-proof devices generally lack intelligent detection, are unable to handle complex situations such as bundled explosives, and robots are prone to being damaged by explosions, resulting in high costs, as well as problems or defects such as single functions.

[0003] In the prior art, the limitations of traditional explosion-proof devices are analyzed as follows:

[0004] 1. The dimension of explosive recognition is single. For example, the Chinese invention patent application "An Intelligent Mine-Clearing Robot" with the application number 201910118591.5 is mainly aimed at the scenario of mine clearing, and its practicality in daily life scenarios is poor.

[0005] 2. Manual intervention is required during the disposal process. For example, the Chinese invention patent applications "A Portable Intelligent Explosion-Proof Robot and Working Method" with the application number 202011448668.4; "An Explosive Case Prevention System and Method" with the application number 202311636166.8; "A Flexible Explosion-Proof Barrel Support Device for an Explosion-Proof Robot" with the application number 201922085219.7. These devices are essentially mine-clearing and risk-disposal operations with remote manual operation, lacking intelligent detection and being unable to handle complex situations such as bundled explosives.

[0006] 3. The protection device cannot be reused. For example, the Chinese invention patent applications "A New Type of Explosion-Proof Robot" with the application number 201911177301.0; "A Robot with X-ray Scanning and Manipulator Bomb Disposal Functions" with the application number 202010567187.9. The core components, such as the explosion-proof barrel cover and the robot's robotic arm, are disposable in use and are prone to being damaged by explosions, resulting in high costs.

[0007] There are also some other explosion-proof and risk-disposal equipment with innovations in the prior art. The explosion-proof classification table in the prior art is as Figure 1 shown. However, the existing common explosion-proof devices also have several deficiencies: for example, using X-ray detection devices has radiation safety hazards and cannot identify non-metallic explosives. The lack of multi-modal recognition technology leads to a high false alarm rate. Manual remote operation takes a long time to dispose of complex bundled explosives. In addition, whether in experiments or actual operations, the overall equipment damage rate of this industry is relatively high, resulting in a sharp increase in development and maintenance costs. Summary of the Invention

[0008] Based on the above problems, the present application proposes an explosion-proof risk disposal equipment that integrates functions of intelligent identification, adaptive disposal, and dynamic protection.

[0009] The present invention discloses an explosion-proof risk disposal equipment, including: a three-layer annular protection architecture of a perception layer, an execution layer, and a protection layer, and an intelligent mobile platform architecture that carries the above three-layer annular protection architecture; the intelligent mobile platform architecture includes a multi-modal mobile chassis and an environment perception system; the perception layer includes a detection equipment module and an intelligent identification and evaluation module, a three-mode fusion detection array is set in the detection equipment module, and the three-mode fusion detection array includes an infrared thermal imaging module, millimeter-wave material analysis, and a laser Raman spectrometer; an AI decision computer and a supporting decision support system software are set in the intelligent identification and evaluation module; the execution layer includes an emergency disposal equipment module with dual robotic arms working in coordination, in which a main robotic arm with a force feedback device and a snake-shaped secondary robotic arm are set, and a multi-functional end effector is also set, and a laser micro-cutting head, a low-temperature plasma degumming device, and a non-contact vibration stripping device are set in the multi-functional end effector; the protection layer includes a protection storage and transportation equipment module, in which explosion-proof storage and transportation equipment and biochemical storage and transportation equipment are set, the explosion-proof storage and transportation equipment includes a dynamic explosion-proof matrix and a separable explosion-proof barrel, and the dynamic explosion-proof matrix includes 6 groups of deployable explosion-proof blankets; the perception layer detects and senses data and information of dangerous goods in the on-site environment through the detection equipment module, and the data and information of the dangerous goods are subjected to risk assessment and judgment and execution of response strategy formulation through the intelligent identification and evaluation module; the execution layer and the protection layer operate the emergency disposal equipment module according to the execution response strategy output by the intelligent identification and evaluation module to perform risk disposal actions.

[0010] According to some embodiments of the present application, omnidirectional wheels and a crawler composite drive device are set in the multi-modal mobile chassis of the intelligent mobile platform architecture; a 16-line lidar, a 360° panoramic camera array, and a sound wave positioning system are set in the environment perception system.

[0011] According to some embodiments of the present application, the dynamic explosion-proof matrix in the protection layer includes 6 groups of deployable explosion-proof blankets and a self-inflating buffer layer device, the explosion-proof blanket is a Kevlar / carbon nanotube composite material, and the expansion coefficient of the self-inflating buffer layer is 300%.

[0012] According to some embodiments of the present application, a magnetic adsorption type quick docking interface and a self-driven roller are set in the separable explosion-proof barrel in the protection layer, and an outer ceramic armor is set on the explosion-proof barrel itself, and an energy-absorbing gel layer is filled between the outer ceramic armor and the outer layer of the explosion-proof barrel.

[0013] According to some embodiments of the present application, the separable explosion-proof barrel is connected to the explosion-proof risk disposal equipment through an electromagnetic locking mechanism. The separable explosion-proof barrel is provided with an autonomous damage avoidance mechanism. In the preset response strategy, in the preset scenario, after the explosion-proof barrel is put into place, the electromagnetic locking mechanism is disconnected from the explosion-proof risk disposal equipment and actively separated within the set time threshold, and it moves to the designated position through self-driven rollers.

[0014] According to some embodiments of the present application, the AI decision computer in the intelligent identification and evaluation module uses NVIDIA Jetson AGX Orin and realizes multimode communication through 5G / WiFi6 / Starlink.

[0015] According to some embodiments of the present application, a deep learning algorithm model and a three-dimensional modeling system are set in the decision support system software in the intelligent identification and evaluation module. Among them, the training set of the deep learning algorithm model contains existing explosive thermal characteristic data to realize real-time comparison with the collected information; the three-dimensional modeling system constructs a three-dimensional model of the object through multi-eye vision + TOF depth camera and automatically marks the suspicious bundling area.

[0016] According to some embodiments of the present application, a pre-plan simulation database based on digital twin, a dynamic Bayesian network risk assessment model, a multi-agent collaborative control algorithm, and a path planning algorithm based on deep reinforcement learning are also deployed in the decision support system software in the intelligent identification and evaluation module.

[0017] According to some embodiments of the present application, the formulation of the response strategy is made by the AI decision computer in combination with the supporting decision support system software. Among them, the AI calculation model of the strategy algorithm also nests a state perception calculation model of multi-sensor fusion, monitors the stress change of the object through the force feedback device of the main robotic arm, monitors the cutting process through the macro camera set in the detection equipment module, and detects the structural integrity of the dangerous goods through the acoustic emission device set in the detection equipment module.

[0018] The technical solution disclosed by the present invention adopts a full-process closed-loop design of "perception - decision - disposal - protection", which reduces the equipment damage rate to 1 / 20 of the traditional solution while ensuring the disposal efficiency. Through simulation tests, the system achieves a success rate of 97.3% in a test set containing 12 complex bundling scenarios, and the single disposal cost is reduced to 35% of the traditional method. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the following will briefly introduce the drawings required for the description of the embodiments. By referring to the drawings and describing its exemplary embodiments in detail, the above and other objectives, features, and advantages of the present application will become more apparent.

[0020] Figure 1 In the prior art, it is a schematic diagram of the classification of explosion-proof containers;

[0021] Figure 2 It is a schematic diagram of the structural modules of the explosion-proof risk elimination device of the present invention;

[0022] Figure 3 It is a schematic diagram of the system decision-making process of the present invention;

[0023] Figure 4 In the present invention, it is a schematic diagram of the classification of replaceable and combinable modules of the explosion-proof risk elimination disposal equipment;

[0024] Figure 5 It is a schematic diagram of the comparison of the effect improvement of the present invention. Detailed implementation manners

[0025] Example embodiments will now be described more fully with reference to the accompanying drawings. However, the example embodiments can be implemented in various forms and should not be construed as limited to the embodiments set forth herein; rather, these embodiments are provided so that this application will be thorough and complete, and will fully convey the concept of the example embodiments to those skilled in the art. Identical reference numerals in the figures denote identical or similar parts, and thus their repetitive description will be omitted.

[0026] The user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data for analysis, stored data, displayed data, etc.) involved in this application are all information and data that have been authorized by the user or fully authorized by all parties, and the collection, use, and processing of the relevant data need to comply with the relevant laws, regulations, and standards of the relevant countries and regions, and corresponding operation entrances are provided for the user to select authorization or rejection.

[0027] The described features, structures, or characteristics can be combined in one or more embodiments in any suitable manner. In the following description, many specific details are provided to give a full understanding of the embodiments of the present disclosure. However, those skilled in the art will realize that the technical solutions of the present disclosure can be practiced without one or more of these specific details, or other methods, components, materials, devices, or operations, etc. can be adopted. In these cases, well-known structures, methods, devices, implementations, materials, or operations will not be shown or described in detail.

[0028] The flowcharts shown in the accompanying drawings are only illustrative, and do not necessarily include all contents and operations / steps, nor do they necessarily need to be executed in the described order. For example, some operations / steps can be decomposed, while some operations / steps can be combined or partially combined, so the actual execution order may change according to the actual situation.

[0029] In the description and claims of this application and the above-mentioned drawings, terms such as "first" and "second" are used to distinguish different objects, rather than to describe a specific order. In addition, the terms "comprising" and "having" and any variations thereof are intended to cover non-exclusive inclusion. For example, a process, method, system, product, or device that includes a series of steps or units is not limited to the listed steps or units, but may optionally further include steps or units not listed, or may optionally further include other steps or units inherent to these processes, methods, products, or devices.

[0030] In the present invention, the schematic diagram of the module composition of the explosion-proof risk disposal equipment is as Figure 2 shown. The explosion-proof risk disposal equipment disclosed in the present invention includes: a three-layer annular protection structure of a sensing layer, an execution layer, and a protection layer, and an intelligent mobile platform structure for carrying the above three-layer annular protection structure; the intelligent mobile platform structure includes a multi-modal mobile chassis and an environmental perception system; the sensing layer includes a detection equipment module and an intelligent recognition and evaluation module. A three-mode fusion detection array is provided in the detection equipment module, and the three-mode fusion detection array includes an infrared thermal imaging module, a millimeter-wave material analysis, and a laser Raman spectroscopy detector; an AI decision computer and a supporting decision support system software are provided in the intelligent recognition and evaluation module; the execution layer includes an emergency disposal equipment module for collaborative operation of dual robotic arms, in which a main robotic arm including a force feedback device and a snake-shaped secondary robotic arm are provided, and a multi-functional end effector is also provided. A laser micro-cutting head, a cryogenic plasma de-bonding device, and a non-contact vibration stripping device are provided in the multi-functional end effector; the protection layer includes a protection storage and transportation equipment module, in which an explosion-proof storage and transportation equipment and a biochemical storage and transportation equipment are provided. The explosion-proof storage and transportation equipment includes a dynamic explosion-proof matrix and a separable explosion-proof barrel, and the dynamic explosion-proof matrix includes 6 groups of deployable explosion-proof blankets. As a preferred solution, the explosion-proof blanket is made of Kevlar / carbon nanotube composite material.

[0031] The schematic diagram of the system decision-making process of the present invention is as Figure 3 shown. The sensing layer detects and senses the data and information of dangerous goods in the on-site environment through the detection equipment module, and the data and information of the dangerous goods are subjected to risk assessment and judgment and the formulation of response strategies through the intelligent recognition and evaluation module; the execution layer and the protection layer operate the emergency disposal equipment module according to the execution response strategies output by the intelligent recognition and evaluation module to perform risk elimination actions.

[0032] According to some embodiments of the present application, omnidirectional wheels and a crawler composite drive device are provided in the multi-modal mobile chassis of the intelligent mobile platform structure; a 16-line lidar, a 360° panoramic camera array, and a sound wave positioning system are provided in the environmental perception system.

[0033] According to some embodiments of the present application, the dynamic explosion-proof matrix in the protective layer includes 6 sets of deployable explosion-proof blankets and a self-inflating buffer layer device. The explosion-proof blankets are made of Kevlar / carbon nanotube composite materials, and the expansion coefficient of the self-inflating buffer layer is 300%.

[0034] According to some embodiments of the present application, the separable explosion-proof barrel in the protective layer is provided with a magnetic quick-docking interface and self-driven rollers. The explosion-proof barrel itself is provided with an outer ceramic armor, and an energy-absorbing gel layer is also filled between the outer ceramic armor and the outer layer of the explosion-proof barrel.

[0035] According to some embodiments of the present application, the separable explosion-proof barrel is connected to the explosion-proof risk disposal equipment through an electromagnetic locking mechanism. The separable explosion-proof barrel is provided with an autonomous damage avoidance mechanism. In the preset response strategy, in the preset scenario, after the explosion-proof barrel is put into place, the electromagnetic locking mechanism is disconnected from the explosion-proof risk disposal equipment and actively separated within the set time threshold, and it moves to the designated position through the self-driven rollers.

[0036] According to some embodiments of the present application, the AI decision computer in the intelligent recognition and evaluation module uses NVIDIA Jetson AGX Orin and realizes multi-mode communication through 5G / WiFi6 / Starlink.

[0037] According to some embodiments of the present application, the decision support system software in the intelligent recognition and evaluation module is provided with a deep learning algorithm model and a three-dimensional modeling system. Among them, the training set of the deep learning algorithm model contains existing explosive thermal characteristic data to realize real-time comparison with the collected information; the three-dimensional modeling system constructs a three-dimensional model of the object through multi-camera vision + TOF depth camera and automatically marks the suspicious bundling area.

[0038] According to some embodiments of the present application, the decision support system software in the intelligent recognition and evaluation module is also deployed with a scenario simulation database based on digital twin, a dynamic Bayesian network risk assessment model, a multi-agent collaborative control algorithm, and a path planning algorithm based on deep reinforcement learning.

[0039] According to some embodiments of the present application, the formulation of the response strategy is formulated by the AI decision computer in combination with the supporting decision support system software. Among them, the AI calculation model of the strategy algorithm also nests a state perception calculation model of multi-sensor fusion, monitors the stress change of the object through the force feedback device of the main robotic arm, monitors the cutting process through the macro camera set in the detection equipment module, and detects the structural integrity of the dangerous goods through the acoustic emission device set in the detection equipment module.

[0040] The infrared thermal imaging module of the present invention has outstanding effects. Most traditional dangerous goods detections rely on X-rays or metal detection, but the infrared thermal imaging module can detect abnormal temperatures, combine the different thermal characteristics of explosives with AI algorithms to reduce false alarms, and cooperate with multi-modal data fusion algorithmically to improve the accuracy of judgment with the strategy of thermal imaging + visual analysis.

[0041] In a preferred embodiment of the present invention, the infrared thermal imaging module preferably adopts design parameters with a temperature discrimination ability of 0.05 °C and a working band of 8-14 μm.

[0042] In a preferred embodiment of the present invention, the laser micro-cutting head integrated at the end of the secondary robotic arm has a beam diameter ≤ 0.1 mm.

[0043] In a preferred embodiment of the present invention, the electromagnetic locking mechanism includes a Hall sensor array and a permanent magnet group, and the separation response time < 50 ms.

[0044] In a preferred embodiment of the present invention, the input parameters of the dynamic Bayesian network risk assessment model include object material characteristics, environmental temperature and humidity, and structural stress data.

[0045] Embodiment 1: Application in the railway station scenario.

[0046] In the identification stage: an abnormal heat source (38.5 °C) is detected by infrared; in the disposal stage: the snake-shaped secondary robotic arm bypasses the column for cutting; in the protection stage: the explosion-proof blanket unfolds with a radius of 1.2 m, and the shock wave is attenuated by 92%.

[0047] Embodiment 2: Disposal of a suspected package in the subway station.

[0048] The scenario parameters include:

[0049] Environment: Exit C of Xizhimen Station on the Beijing Subway, with a passenger flow of 200 people per minute.

[0050] Target object: a black backpack (size 40×30×20 cm), with electrical tape wrapped around the surface.

[0051] The disposal process includes:

[0052] Step 1: The mobile platform (400) approaches to a safe distance of 1.5 m.

[0053] Step 2: Laser Raman spectroscopy detects the characteristic peak of TNT (1610 cm-1).

[0054] Step 3: The robotic arm (220) performs tape cutting.

[0055] Path planning time: 0.8 s.

[0056] Cutting speed: 12 mm / s.

[0057] Temperature monitoring: at the incision, ≤ 60°C.

[0058] Explosion-proof blanket deployment time: 2.3 s.

[0059] Example 3: Disposal of cylindrical explosives at a railway station.

[0060] Special situation: The explosive is tied to a steel column with a diameter of 200 mm.

[0061] Technical response:

[0062] 1. The three-dimensional modeling system identifies the stress concentration area of the contact surface.

[0063] 2. Adopt the low-temperature plasma debonding technology (-70°C frozen glue layer).

[0064] 3. Non-contact vibration peeling (27 kHz ultrasonic wave, amplitude 50 μm).

[0065] Comparison of experimental data:

[0066]

[0067] In the present invention, the classification schematic diagram of the replaceable and combinable modules of the explosion-proof and risk-disposal equipment is as Figure 4 shown. Many mature functional modules of the prior art can be combined and replaced with the device of the present application by means of nested control chip processing.

[0068] The comparison schematic diagram of the effect improvement of the present invention is as Figure 5 shown. The technical solution disclosed in the present invention adopts a full-process closed-loop design of "perception - decision - disposal - protection", which reduces the equipment damage rate to 1 / 20 of the traditional solution while ensuring the disposal efficiency. Through simulation testing, the system achieves a success rate of 97.3% in a test set containing 12 complex bundling scenarios, and the single-disposal cost is reduced to 35% of the traditional method.

[0069] The above has introduced the embodiments of the present application in detail. Specific examples are used in this article to elaborate on the principle and implementation manner of the present application. The description of the above embodiments is only used to help understand the method and its core idea of the present application. At the same time, any changes or deformations made by those skilled in the art based on the idea of the present application, within the specific implementation manner and application scope of the present application, all fall within the protection scope of the present application. In summary, the content of this specification should not be construed as a limitation to the present application.

Claims

1. An explosion-proof risk disposal equipment, characterized in that: The disposal equipment includes a three-layer circular protection architecture of a perception layer, an execution layer, and a protection layer, as well as an intelligent mobile platform architecture that carries the above three-layer circular protection architecture; The intelligent mobile platform architecture includes a multi-modal mobile chassis and an environmental perception system; The perception layer includes a detection equipment module and an intelligent identification and evaluation module. A three-mode fusion detection array is set in the detection equipment module, and the three-mode fusion detection array includes an infrared thermal imaging module, a millimeter-wave material analysis, and a laser Raman spectroscopy detector; an AI decision computer and a supporting decision support system software are set in the intelligent identification and evaluation module; The execution layer includes an emergency disposal equipment module with dual robotic arms working in coordination, in which there is a main robotic arm with a force feedback device and a snake-shaped secondary robotic arm, and a multi-functional end effector is also set. A laser micro-cutting head, a cryogenic plasma de-gluing device, and a non-contact vibration stripping device are set in the multi-functional end effector; The protection layer includes a protection storage and transportation equipment module, in which there is an explosion-proof storage and transportation equipment and a biochemical storage and transportation equipment. The explosion-proof storage and transportation equipment includes a dynamic explosion-proof matrix and a separable explosion-proof barrel. The dynamic explosion-proof matrix includes 6 groups of deployable explosion-proof blankets; The perception layer detects and perceives data and information of dangerous goods in the on-site environment through the detection equipment module, and the data and information of the dangerous goods are subjected to risk assessment and judgment and the formulation of response strategies through the intelligent identification and evaluation module; The execution layer and the protection layer operate the emergency disposal equipment module according to the execution response strategy output by the intelligent identification and evaluation module to perform risk elimination actions.

2. The explosion-proof risk disposal equipment according to claim 1, characterized in that: An omnidirectional wheel and a crawler composite drive device are set in the multi-modal mobile chassis of the intelligent mobile platform architecture; a 16-line lidar, a 360° panoramic camera array, and a sound wave positioning system are set in the environmental perception system.

3. The explosion-proof risk elimination and disposal equipment according to claim 1, characterized in that: The dynamic explosion-proof matrix in the protection layer includes 6 groups of deployable explosion-proof blankets and a self-inflating buffer layer device. The explosion-proof blanket is made of Kevlar / carbon nanotube composite material, and the expansion coefficient of the self-inflating buffer layer is 300%; 4. The explosion-proof emergency disposal equipment according to claim 1, characterized in that: A magnetic adsorption type quick docking interface and a self-driving roller are set in the separable explosion-proof barrel in the protection layer. The explosion-proof barrel itself is provided with an outer ceramic armor, and an energy-absorbing gel layer is also filled between the outer ceramic armor and the outer layer of the explosion-proof barrel.

5. The explosion-proof risk elimination and disposal equipment according to claim 4, characterized in that: The separable explosion-proof barrel is connected to the explosion-proof risk elimination disposal equipment through an electromagnetic locking mechanism. The separable explosion-proof barrel is provided with an autonomous damage avoidance mechanism. In the preset response strategy, in the preset scenario, after the explosion-proof barrel is put in, the electromagnetic locking mechanism is disconnected from the explosion-proof risk elimination disposal equipment and actively separated within the set time threshold, and moves to the designated position through the self-driving roller.

6. The explosion-proof risk disposal equipment according to claim 1, characterized in that: The AI decision computer in the intelligent identification and evaluation module uses NVIDIA Jetson AGX Orin and realizes multi-mode communication through 5G / WiFi6 / Starlink; 7. The explosion-proof risk elimination and disposal equipment according to claim 6, characterized in that: A deep learning algorithm model and a three-dimensional modeling system are set in the decision support system software in the intelligent identification and evaluation module, in which, The training set of the deep learning algorithm model includes existing explosive thermal characteristic data to realize real-time comparison with the collected information; The three-dimensional modeling system constructs a three-dimensional model of an object through multi-camera vision + TOF depth camera and automatically marks suspicious bundling areas.

8. The explosion-proof risk elimination and disposal equipment according to claim 7, wherein: In the decision support system software of the intelligent recognition and evaluation module, there are also deployed a digital twin-based pre-plan simulation database, a dynamic Bayesian network risk assessment model, a multi-agent collaborative control algorithm, and a path planning algorithm based on deep reinforcement learning.

9. The explosion-proof risk elimination and disposal equipment according to claim 1, characterized in that: The formulation of the response strategy is made by the AI decision computer in combination with the supporting decision support system software. Among them, the AI calculation model of the strategy algorithm also nests a state perception calculation model of multi-sensor fusion. The stress change of the object is monitored through the force feedback device of the main robotic arm, the cutting process is monitored through the macro camera set in the detection equipment module, and the structural integrity of the dangerous goods is detected through the acoustic emission device set in the detection equipment module.

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