404 results about "Dangerous goods" patented technology

The invention discloses a visual and three-dimensional modeling luggage automatic identification method, equipment, a medium and a product. The method comprises the following steps: firstly, carrying out dynamic multi-view scanning on luggage entering a scanning area of a conveyor belt to obtain a multi-view image, carrying out deep learning to obtain three-dimensional point cloud data, and fusing the three-dimensional point cloud data with X-ray transmission density data to form a preliminary three-dimensional model; whether the model is complete or not is judged by combining geometric closure and material density continuity, and if not, features are extracted through an adversarial generative network, and occlusion area point cloud data are predicted for complementation; and finally, matching the complementation model features with a dangerous goods feature library, and judging whether the dangerous goods are dangerous goods or not. By implementing the technical scheme provided by the invention, the information of the articles in the luggage can be comprehensively obtained, the complete and accurate three-dimensional model can be constructed, whether the articles are dangerous articles or not can be efficiently and accurately judged, and the efficiency and the safety of aviation security inspection are improved.

The invention discloses a traffic safety early warning method and device for a dangerous cargo transport vehicle, and the method comprises the steps: S1, monitoring the operation state of the dangerous cargo transport vehicle in real time, and collecting environment data in real time; and S2, based on the collected data, establishing a risk assessment model by using a convolutional neural network algorithm, analyzing the influence of extreme weather and complex terrains on the safety of the dangerous cargo transport vehicle, developing a risk assessment algorithm, and according to a risk assessment result, the risk assessment model established by using the convolutional neural network algorithm in the invention can be used for evaluating the safety of the dangerous cargo transport vehicle. And specific influences of extreme weather and complex terrains on vehicle safety can be deeply analyzed. The risk assessment model can learn various risk factors in a complex environment and comprehensively assess the risk factors, so that the accuracy and reliability of risk assessment are improved. The system can continuously monitor the change condition of the risk, timely adjust the early warning strategy according to the actual condition, and continuously improve the adaptive capacity and the early warning effect.

The invention discloses a highway hazardous chemical substance liquid leakage accident monitoring method and a highway hazardous chemical substance liquid leakage accident monitoring system based on computer vision. The method comprises the following steps: arranging and installing an identifier configured for hazardous chemical substance vehicle identification on a vehicle for loading and transporting hazardous chemical substances; the identifier comprises an optical identifier configured to be used for improving the visual identification degree of the dangerous goods vehicle and a digital identifier configured to realize encrypted storage and quick reading of vehicle information; on the basis of an existing road monitoring system, a lightweight identification model configured for detecting the states of an optical identifier and a digital identifier in real time is deployed and loaded in the existing road monitoring system; performing visual positioning on the road surface projection pattern through a camera, and calculating the real-time position of the vehicle by combining map coordinates so as to supplement the positioning blind area of the GPS in the tunnel mountain area; accident probability calculation is carried out based on the identification state to determine whether the vehicle is suspected to have an accident; and when the accident is judged to be suspected, triggering an accident response process. And the accident response efficiency is obviously improved.

The invention belongs to the technical field of data analysis, and relates to a port ship berthing dynamic risk prediction and pilot intelligent matching method. According to the invention, by quantitatively calculating the comprehensive qualification score and dividing the grade, dynamic matching of the pilot and the task risk grade is realized, an evaluation mode dominated by artificial experience is broken, the accuracy of pilot qualification evaluation is improved, and the operation error rate caused by insufficient personnel qualification is reduced; by dynamically simulating the berthing process and calculating risk indexes such as the offset rate and the collision energy, the berthing risk is pre-judged and graded, the berthing risk identification accuracy is improved, equipment operation parameters, dangerous goods states and meteorological data are analyzed in real time, risks such as faults, leakage and extreme weather are accurately identified, corresponding measures are triggered, and the safety of berthing is improved. Targeted management of berthing risks is facilitated, and accident loss and port operation interruption risks are effectively reduced.

The invention relates to the technical field of dangerous cargo management, in particular to an intelligent compliance verification system for dangerous cargo boxing operation. Comprising a data acquisition preprocessing unit; the law and regulation graph construction iteration unit is used for extracting a'law and regulation term number-verification dimension-constraint condition 'triple of the law and regulation in the dangerous cargo boxing field and introducing an improved three-dimensional dynamic weight conflict resolution algorithm according to the efficacy level, the release subject and the application range indexing; a multi-agent collaborative verification unit; a risk early warning report generation unit; and a man-machine cooperation closed loop unit. According to the method, the problems of lagging of laws and regulations and clause conflicts are solved by adopting triple extraction of'laws and regulations clause numbers-verification dimensions-constraint conditions', a three-dimensional dynamic weight conflict resolution algorithm based on laws and regulations effectiveness-scene matching degree-release time and a technical means of periodically optimizing weight parameters through a reinforcement learning model.

The invention discloses an automatic wharf cold dangerous cargo storage yard layout simulation method and system considering manual and unmanned mixed operation, and belongs to the field of automatic wharf cold dangerous cargo storage yard layout. Firstly, data are collected to generate an overall layout set A; secondly, randomly selecting one overall layout from A to obtain a first-stage optimization model, and solving the first-stage optimization model by using a genetic algorithm; then, constructing a second-stage physical model, and recording the second-stage physical model as a simulation model set; and finally, evaluating, comparing and selecting different simulation models to obtain an optimal layout and scale combination. The automatic wharf cold dangerous cargo storage yard layout simulation system comprises a data acquisition module, a layout mode generation module, a scale optimization module, a simulation model construction module, a comprehensive evaluation module and a judgment module. According to the method, layout and scale collaborative optimization is achieved through two-stage optimization and simulation, the port operation efficiency, the resource utilization rate and safety can be improved, meanwhile, energy consumption and carbon emission are reduced, and scientific decision support is provided for port design.

The invention discloses a metro dangerous goods terahertz detection method based on adaptive downsampling and a multi-dimensional attention mechanism. The metro dangerous goods terahertz detection method comprises the following steps: acquiring a terahertz image data set; building a deep learning network model, wherein the deep learning network model comprises a backbone feature extraction network, a check feature extraction network, a down-sampling module, a fusion channel and space attention module, a space attention module and a YoloHead detection head which are connected in sequence; performing dual-path processing on the input feature map through parallel pooling and convolution operation; in the fusion channel and space attention module, global context modeling is carried out on the feature map; in the space attention module, long-range context dependence is captured through a strip-shaped pooling layer; inputting the multi-scale feature map output by the check network into a YoloHead detection head, and outputting a target detection frame; a redundant detection frame is removed through a non-maximum suppression algorithm, and a detection result with the highest confidence coefficient is reserved.

The invention relates to the technical field of X-ray hazardous article detection, and discloses an X-ray hazardous article detection algorithm based on improved YOLOv8-seg, which can detect the types and specific areas of hazardous articles in disordered security check articles. The method comprises the steps that a multi-channel interactive convolution module is designed, and based on a channel decoupling and recombination mechanism and a heterogeneous convolution kernel collaborative optimization strategy, the multi-scale feature discrimination capability is enhanced while calculation redundancy is reduced; the method comprises the following steps: constructing an SPPF-LSKA (Space Purpose Pooling Function-Learning SKA) composite module, and effectively improving the boundary retention degree of an occluded target through deep fusion of a large-kernel space attention mechanism and adaptive pyramid pooling.

The invention discloses a container terminal truck intelligent scheduling method and system based on multiple driving modes. The method comprises the steps that a whole-process system architecture integrating a central scheduling platform, a vehicle-mounted intelligent terminal and a sensing and communication network is constructed; the method comprises the following steps: acquiring basic data of vehicles, tasks, road networks and environments, constructing a multi-objective optimization function, establishing a dangerous goods risk integral model, respectively setting mathematical constraints for task assignment, path planning, hybrid driving coordination, dynamic path tracking and mode switching, and forming a multi-dimensional mathematical model; an improved non-dominated sorting genetic algorithm is adopted to solve the model, and a personalized scheduling scheme including vehicle-task assignment, path planning, time requirements and risk control rules is generated; through cooperation of the central scheduling platform and the vehicle-mounted intelligent terminal, MPC dynamic path tracking is adopted for the unmanned vehicle, visual and voice dual-mode guidance is provided for the artificial vehicle, and hybrid driving cooperative management and control are implemented, so that the vehicle operation efficiency and the dangerous goods transportation safety are guaranteed.

The invention discloses a security declaration file generation method and device, a medium and a product, and relates to the field of data processing. The method comprises the following steps: receiving a dangerous goods transportation voucher of a target dangerous goods provided by a freight station; carrying out digital preprocessing on the dangerous goods transportation voucher to obtain a standardized digital file; extracting a plurality of dangerous article field information from the standardized digital file; based on the OCR recognition accuracy, the semantic matching degree and the field integrity, determining the confidence score of the field information of each dangerous article; key field information is determined according to the confidence score; generating a potential risk score based on the key field information and the aviation dangerous goods knowledge graph; generating a comprehensive evaluation value according to the confidence score and the potential risk score; and when the comprehensive evaluation value is higher than or equal to a preset evaluation value threshold value, generating a security declaration file based on a preset airline template and the standardized digital file. The problem that the security declaration file generated by the related technology is not accurate and reliable enough can be relieved.

The invention discloses a toll station special situation emergency processing system integrated with a localized AI large model, and belongs to the technical field of toll station management and control. Comprising an edge computing device, a multi-element sensing module, a localization AI large model engine, a dynamic rule engine and an execution control interface. The edge computing device is responsible for being deployed in a toll station site and is embedded hardware with AI acceleration computing power, and the multi-source sensing module is responsible for being connected with a camera, a millimeter wave radar and an ETC-RSU device. According to the invention, by deploying the lightweight large model in the edge server, millisecond-level identification and automatic disposal of special situations such as vehicle card punching and dangerous goods leakage are realized. The system adopts a multi-modal data fusion technology, and is combined with a dynamic plan engine, so that the operation of core functions can still be ensured in an off-network environment, and the emergency response efficiency and safety of the toll station are remarkably improved.

The invention discloses a digital dangerous cargo transportation supervision system and method, belongs to the technical field of vehicle supervision, and aims to solve the problems that in digital dangerous cargo transportation, loading and unloading links are insufficient in authenticity verification, abnormal fluctuation in the transportation process is difficult to recognize in real time, and abnormal handling response is delayed. After a dangerous cargo transportation electronic waybill is obtained, loading and unloading scene verification is completed by delimiting a compliance area, shooting an initial scene image and dynamically constructing an image flow sequence, and a carrying password is generated for cargo encryption storage and unloading unlocking; a passing route is segmented, a vehicle operation base line is established based on historical data, data delay and loss are distinguished by monitoring the conformity and transmission interval of transportation data and the base line, abnormal fluctuation is recognized, and early warning is triggered; and during early warning, a target verification position is selected based on positioning, and the vehicle is guided to the verification area to complete abnormity verification. And cheating behaviors in loading and unloading links are avoided, transportation risks are identified, abnormities are quickly handled, and dangerous cargo transportation safety and supervision efficiency are effectively improved.

The invention discloses an intelligent paid waste recovery system, which relates to the technical field of waste recovery and comprises an intelligent recovery box main body, a central control module, a user interaction module, a settlement module and a user side applet, the intelligent recycling bin main body comprises a single recycling bin door, an independent identification channel, a sorting execution module and a double-category sorting bin body; the double-category sorting cabin body comprises a paper-plastic cabin body and a fabric cabin body, electric sorting gates are arranged at the tops of the paper-plastic cabin body and the fabric cabin body, and weighing settlement units are arranged at the bottoms of the paper-plastic cabin body and the fabric cabin body; a dangerous goods detection module, a delivery quantity limiting module, an overlapping recognition module, an overlapping goods dispersing module and a self-adaptive illumination category recognition module are sequentially integrated in the independent recognition channel in the goods conveying direction; according to the scheme, identification precision fluctuation can be improved, and a stable and reliable classification effect is formed.

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.

The utility model relates to the field of dangerous goods transportation protection, and discloses a protective device for chemical liquid storage tank transportation, which comprises a fixed plate, a vehicle plate, a fixed rod, an air cylinder, a rotating piece, a rotating rod, a long connecting rod, a short connecting rod and a protective plate, when the protective device is used, the fixed plate is fixed on the vehicle plate, and when chemical liquid is infused or sundries fall on the protective plate, the air cylinder is started to stretch a piston rod; the lower end of the rotating rod rotates in the direction away from the air cylinder to drive the two long connecting rods to move and drive the rotating piece to rotate, and the short connecting rod rotates upwards and drives the two protection plates to rotate upwards along the fixing column. When transportation is started, the piston rod of the air cylinder is shrunk, the lower end of the rotating rod is driven to rotate reversely, the two connecting rods move reversely, and therefore the rotating piece is driven to rotate reversely, the short connecting rod is driven to rotate downwards, and the two protection plates rotate downwards along the fixing columns till being flatly placed above the storage tank. The storage tank has the advantages of being not prone to water accumulation, convenient to use and easy to clean, and the service life of the storage tank is prolonged.

The invention provides a ship lock intelligent scheduling method and system considering ship classification and dangerous goods isolation, and the method comprises the steps: S1, obtaining the information of a to-be-scheduled ship and the information of a lock chamber, and constructing a conventional ship information list ListN and a dangerous ship information list ListD based on the danger level of the to-be-scheduled ship; s2, according to the management method of the hydro-junction where the lock chamber is located, the danger level of independent lockage is obtained, and the safety size of the ship needing independent lockage in the ListD is modified so that the lock chamber can be fully occupied by the ship; and S3, respectively taking the ListN and the ListD as an input list ListI, calculating a global highest scheduling score of the ListI based on the safety size, the arrival time and the type of the ship, and selecting a global optimal scheduling scheme corresponding to the higher global highest scheduling score in the ListN and the ListD as a final scheduling scheme. The united targets of improving the utilization rate of the lock chamber, reducing the waiting time of the ship, weighing the priority of the ship and isolating the dangerous goods ship are achieved.

The invention discloses a temperature on-line monitoring and early warning system for fire protection clothing, which relates to the technical field of fire protection monitoring and early warning and comprises a data collection module, a data preprocessing module, a calculation processing module and an early warning execution module. Wherein the calculation processing module comprises a dynamic temperature risk unit, a comprehensive environment risk unit and a safety prediction unit. The dynamic temperature risk unit fuses temperature, a safety threshold value, a change rate, material aging, humidity and a heat reflection attenuation coefficient, outputs a dynamic temperature risk coefficient and reflects a safety margin, and the comprehensive environment risk unit introduces gas concentration, the number of hazardous articles, smoke attenuation and an action intensity coefficient based on the dynamic temperature risk coefficient, constructs an environment coupling risk index, and finally performs the safety analysis on the environment coupling risk index. And the safety prediction unit integrates a basic safety time constant, an environment coupling risk index, a dynamic temperature risk coefficient, a heat flux density and an oxygen concentration correction coefficient, outputs a residual safety time prediction value, and guides an evacuation decision of a fireman.

The invention discloses a container dangerous mark identification method and system, a storage medium and a program product, and relates to the field of general image data processing, and the method comprises the steps: identifying a UN number region and a plurality of dangerous mark candidate regions in a container image; determining a probability distribution list containing all possible categories of each dangerous standard candidate area to generate a preliminary recognition result; determining a serial number identification result of the UN serial number area, and querying a corresponding standard dangerous standard set; generating a virtual anchor point coordinate set according to the position coordinates of the UN numbered region and a preset layout rule; according to the probability distribution list, combining the due risk mark type and the risk mark candidate area, and generating a plurality of groups of candidate allocation hypotheses; determining a harmony score of the candidate allocation hypothesis; and determining an optimal allocation scheme with the highest harmony degree score, correcting the preliminary identification result based on the optimal allocation scheme, and generating a dangerous mark identification report of the target container. According to the invention, the identification accuracy of the hazardous article mark can be improved.

The application discloses a kind of digital dangerous goods transport supervision system and method, belong to vehicle supervision technical field, to solve the authenticity of digital dangerous goods transport in loading and unloading link is insufficient, transport process abnormal fluctuation is difficult real-time identification and abnormal disposal response lag problem.After obtaining dangerous goods transport electronic transport note, by demarcating compliance area, shooting initial scene image, dynamic construction image flow sequence is completed loading and unloading scene verification, generates carrying password for goods encryption storage and unloading unlocking;To the section of route, establish vehicle operation baseline based on historical data, by monitoring the compliance of transport data and baseline and transmission interval, distinguish data delay and loss and identify abnormal fluctuation, trigger early warning;In early warning, based on positioning selection target check position, guide vehicle to check area to complete abnormal check.Eliminate the cheating behavior of loading and unloading link, identify transport risk and dispose abnormality quickly, effectively improve dangerous goods transport safety and supervision efficiency.

The invention provides an unattended operation method and system based on the Internet of Things technology, and the method comprises the steps: carrying out the multi-band scanning of a target substance through a tunable laser spectrum device of a distributed laser detection node, generating an original spectrum signal, carrying out the dynamic wavelength modulation and adaptive noise filtering processing, and carrying out the detection of the original spectrum signal. And matching and outputting a preliminary recognition result in combination with the dangerous substance feature library. And performing confidence evaluation and correction on the result by using a local federal learning model, generating a parameter update quantity through correlation analysis, and uploading the parameter update quantity to a central server. And dynamically updating a local model and laser scanning parameters based on the issued federal global model parameter weight distribution, and realizing accurate identification of the dangerous substances. According to the invention, the accuracy of dangerous substance identification and the self-adaptive capability of the system are improved.

The invention discloses a self-identification and early-warning method for abnormal high temperature of a vehicle in a free flow state, and the method achieves the precise identification of vehicle tire overheating and fire hazards through the fusion of thermal imaging analysis and a dynamic scene modeling technology. The method comprises the following steps: firstly, positioning a tire area in a thermal imaging image in real time by using a Yov11 model, segmenting an axle and a tread through a clustering algorithm in combination with temperature distribution and position characteristics, calculating a local average temperature and quantifying an abnormal index; meanwhile, environmental interference is eliminated by adopting a dynamic background modeling technology based on statistical analysis, efficient classification is performed on smoke areas in combination with a full convolutional neural network, and a smoke probability is output. Furthermore, the system dynamically evaluates the comprehensive risk level by fusing the temperature abnormal data and the smoke detection result, and links a grading early warning mechanism. According to the method, the detection precision and the response speed in a complex free flow scene are remarkably improved, the method can be widely applied to the fields of logistics transportation, dangerous goods vehicle monitoring and the like, and intelligent guarantee is provided for driving safety.

The invention discloses a dangerous cargo package drop-stacking composite test integrated detection system, which relates to the technical field of dangerous cargo package detection and integrates a rack, a lifting module, a drop test module, a stacking test module, a control module, a detection module and a display terminal. Compared with a traditional mode of separately carrying out falling and stacking tests, the integrated design greatly reduces the occupied area of equipment, and the detection cost is reduced; the test process is simplified, the detection efficiency is remarkably improved, and manpower and time cost are saved; the device can simulate the complex condition that the dangerous cargo package is subjected to falling impact and stacking pressure in an actual scene, enables the detection result to be more accurate and reliable, and comprehensively evaluates the real performance and safety of the package.

The invention discloses an electronic waybill submission system and method applied to dangerous goods road transportation, and relates to the technical field of data security, and the method comprises the steps: collecting structured submission data, and carrying out the field renaming, type conversion and legality detection; executing normalized coding to obtain an idempotent check key; carrying out sampling and smoothing processing based on an idempotent check key, and calculating an event commitment value to form a space-time commitment chain; calculating a trajectory quality base score and a space-time consistency base score according to the space-time commitment chain to generate a quality threshold pass token; screening a minimum disclosure field set according to the token and executing hashing and block encryption to generate a signature message; and completing repeated retrieval and verification based on the signature message, and generating an audit log. Through a linkage mechanism of the space-time commitment chain and the quality evaluation module, quality grading and space-time consistency quantitative checking of the vehicle trajectory data are realized.

The utility model discloses a leakage-proof device for transporting dangerous chemicals, which is characterized in that a sealing groove is formed in the end face of a discharging pipe, a sealing gasket is arranged on the end face of the sealing groove, a threaded ring is arranged on the surface of the discharging pipe, a cavity is formed in the surface of the threaded ring, sealing oil is injected into the cavity, a sealing plate is arranged on the surface of a sealing pipe, and a bottom plate is arranged on the surface of the sealing plate. Positioning grooves are formed in the surface of the bottom plate; the device has the beneficial effects that firstly, the sealing plate is in threaded connection in the threaded ring, the cavity is formed in the threaded ring, and when the sealing pipe is matched with the threaded ring to be fixed in the discharging pipe, on one hand, the discharging pipe can be sealed through extrusion of one end of the sealing pipe on the sealing gasket; and on the other hand, sealing oil is injected into the cavity, so that sealing of the discharging pipe can be further improved, and safety is improved.

The utility model discloses an anti-collision structure for dangerous goods transportation, which relates to the technical field of dangerous goods transportation and comprises a blocking rod inserted into a positioning top frame. The use position of the positioning assembly in the positioning top frame can be freely adjusted and controlled for use, the positioning and fixing device can adapt to positioning and fixing use of hazardous article packages of various different outer diameter specifications, a transport frame does not need to be independently designed for hazardous articles of various specifications, the cost is greatly saved, and when the positioning assembly is in a reset state, the positioning assembly can be locked in the positioning top frame, so that the use is convenient. Therefore, the dangerous goods and packages thereof are stably supported, protected and positioned, the dangerous goods are prevented from being collided, damaged and the like during transportation, and the problems that according to an existing dangerous goods transportation placing frame, the dangerous goods packages are separated and positioned through isolation rods at fixed intervals, and due to the fact that the dangerous goods are various in variety, the dangerous goods are difficult to transport are solved. The difference between the packaging size and the outer diameter specification parameter is large, and the fixed distance between the spacer bars is often difficult to meet the diversified requirements.

The invention discloses a method and system for identifying dangerous goods at the bottom of a vehicle in an airport flight area, and the method comprises the steps: obtaining the vehicle type of a to-be-detected vehicle, transmitting a detection wave to the bottom of the to-be-detected vehicle, and synchronously collecting a reflection sequence of the detection wave at the bottom of the to-be-detected vehicle in real time; performing differential processing on the reflection sequence to generate a maximum response deviation value, calculating an abnormal fusion response intensity value according to the maximum response deviation value, and identifying a plurality of areas at the bottom of the to-be-detected vehicle as abnormal areas according to the abnormal fusion response intensity value; and constructing a physical property response vector of each abnormal region, and searching a dangerous goods physical property response vector corresponding to the physical property response vector of the abnormal region in a dangerous goods database, thereby determining the dangerous goods category of the abnormal region.

This invention discloses an automatic multi-view security inspection image recognition method based on deep learning. Bags containing a mixture of known dangerous and non-dangerous goods are passed through a security inspection device equipped with multi-view probes, generating security inspection images of each bag from multiple perspectives. These images are then labeled to create a dataset. A network model is trained using the training set and deployed in the security inspection device. During actual detection, the acquired multi-view security inspection images are input into the network model. The images undergo preprocessing, feature extraction, perspective transformation, and feature fusion within the network model. Finally, the fused features are input into a classifier for classification, determining whether the object to be detected contains dangerous goods. If dangerous goods are found, their category is determined. This invention solves the problems of missed detections due to blind spots in security inspection angles and the heavy reliance on manual inspection, as well as the related issues.

The invention discloses a low-sensitivity activator as well as a preparation method and application thereof, and belongs to the technical field of gas fracturing. Potassium perchlorate is used as an oxidizing agent of the low-sensitivity activator, flour is used as a combustible agent of the low-sensitivity activator, and the mass ratio of the potassium perchlorate to the flour in the low-sensitivity activator is (50-70): (10-20). The low-sensitivity activator provided by the invention has the advantages that the mechanical sensitivity, flame sensitivity and static sensitivity of the low-sensitivity activator are at extremely low levels, and the low-sensitivity activator has excellent stability and higher ignition temperature; related tests carried out according to the Program on Dangerous Goods Transport of the United National further show that the activator not only has remarkable gas production rate, but also shows extremely low sensitivity to shock waves, the insensitive characteristic of the activator is even superior to that of a conventional insensitive explosive, and practical application verification shows that the cracking effect of the activator is completely not lower than the level of a metal powder activator.

The invention provides a mixed double-source luggage security inspection machine, which belongs to the technical field of security inspection equipment, and comprises a delivery conveyor belt, a detection box covers the upper part of one side of the delivery conveyor belt, a back scattering detector is arranged in the detection box, transmission detectors are arranged around the back scattering detector, and the transmission detectors are arranged on the back scattering detector. And a detection terminal is arranged at the end part of the delivery conveyor belt. The luggage security inspection machine has the effect of solving the technical problem that the luggage security inspection machine is difficult to fully detect dangerous goods.

The multi-terrain load robot comprises an integrated load platform, at least eight supporting transmission rods are arranged at the bottom of the integrated load platform in a sliding fit mode, a bidirectional sliding rail is arranged at the bottom of the integrated load platform, and the eight supporting transmission rods are all arranged in the bidirectional sliding rail in a sliding fit mode; the integrated load platform comprises a load bearing platform base and a master control processor embedded in the load bearing platform base, a horizontal and distance monitoring mechanism is arranged on the load bearing platform base, the master control processor is electrically connected with the horizontal and distance monitoring mechanism, and a driving mechanism matched with the two-way sliding rail is arranged at the top end of the supporting transmission rod. A hydraulic supporting rod is arranged at the bottom end of the supporting transmission rod. Through the arrangement of the integrated load platform, the supporting transmission rods and the hydraulic supporting rods, high load can be achieved through the multiple hydraulic supporting rods, meanwhile, the integrated load platform can keep horizontal in the transportation process, and the platform is suitable for high-precision instrument or equipment transportation and can be used for dangerous goods transportation.