420 results about "Rockfall" patented technology

The invention discloses a high and steep slope dangerous rock falling intelligent monitoring and early warning method and system, and the method comprises the following steps: S1, collecting and preprocessing real-time monitoring data, and generating a standardized input sample set; s2, constructing a long-term prediction network model, and outputting a state prediction sequence of multiple time steps in the future; s3, optimizing structure parameters and training parameters of the prediction network model based on a bald eagle search algorithm; s4, executing multi-step state prediction by using the optimized model, and outputting a crack trend, a displacement trend and an abnormal probability value; s5, constructing an early warning risk scoring function, and fusing multiple prediction indexes to generate a risk scoring value; and S6, setting a multi-level early warning threshold value, outputting an early warning level, and issuing the early warning level in linkage with voice, a terminal and a platform. According to the invention, through constructing the intelligent monitoring and early warning method fusing the long-term prediction network model and the bald eagle search algorithm, accurate prediction and multi-stage linkage early warning of the high and steep slope dangerous rock falling risk are realized.

The invention discloses a slope collapse rockfall monitoring method, and relates to the technical field of slope rockfall monitoring, and the method comprises the following steps: arranging multiple types of monitoring sensors in a slope region, and covering a key monitoring region in combination with a camera to form a multi-source data collection network; according to the method, false alarms caused by natural interference and non-dangerous interference are effectively reduced through real-time monitoring of a multi-source sensor and a signal filtering technology based on an environmental noise model, and the authenticity of risk signals is verified from multiple dimensions by combining sensor data with camera images through a multi-modal data fusion algorithm, so that the reliability of the system is improved. In combination with a dynamically updated slope collapse feature library and an intelligent algorithm, the system can accurately identify key parameters of slope instability and predict risks, flexibly responds based on a graded early warning mechanism, improves the disaster prevention and control capability, reduces resource waste caused by false alarm, reduces threats of disasters to life and property, and improves the safety and reliability of the system. And sufficient time is provided for managers to take measures.

The invention relates to the technical field of intelligent traffic and road safety monitoring, and discloses a 4D imaging millimeter wave radar-based slope deformation monitoring and identification method, which comprises the following steps of: acquiring a continuous point cloud; carrying out voxel modeling on the point cloud in a three-dimensional space; selecting three continuous frames of point clouds, and identifying mutant voxels by calculating the point number variation of each voxel in adjacent frames; performing spatial clustering on the mutant voxels to obtain an obstacle region; performing feature extraction on the obstacle area, wherein the extracted features comprise the height difference, the average reflection intensity and the centroid drift of the obstacle area; carrying out linear weighted fusion on the extracted features, and constructing a landslide mutation index; and judging whether an obstacle target exists in an obstacle area or not according to a preset condition, and performing risk grading identification according to the landslide sudden change index. According to the invention, all-weather, structured and high-reliability perception of major traffic potential safety hazards such as landslide / rockfall is realized, and a new basic capability is provided for a traffic safety system.

The invention relates to the technical field of slope disaster early warning, in particular to a mine slope landslide disaster early warning method and system based on multi-modal data, and the method comprises the following steps: monitoring a surface mine slope through radar equipment, and obtaining a radar data sequence corresponding to slope rockfall and rock-soil loosening conditions; extracting a meteorological data sequence at the same moment as the radar data sequence from meteorological equipment; and calling a pre-established slope disaster early warning model through the cloud server, and predicting a landslide occurrence area and landslide occurrence time of the surface mine slope by using the radar data sequence and the meteorological data sequence. According to the method, radar data and meteorological data of rockfall and rock-soil loosening in the initial stage of the slope disaster are utilized to predict the occurrence area and occurrence time of the landslide in the outbreak period of the slope disaster, the early warning timeliness is met, and the neural network structure model is utilized to predict the occurrence area and occurrence time of the landslide on the basis of multi-modal data. And the prediction accuracy of the landslide disaster is improved.

The invention relates to the technical field of slope simulation tests, in particular to a high and steep embankment slope soil engineering simulation test device and method.The high and steep embankment slope soil engineering simulation test device comprises a multi-degree-of-freedom vibration table, a slope assembly, an airflow assembly and a driving assembly, the slope assembly is installed on the multi-degree-of-freedom vibration table, and the airflow assembly is installed on the driving assembly; the airflow assembly is located above the side slope assembly, and the driving assembly is connected with the multi-degree-of-freedom vibration table, the side slope assembly and the airflow assembly; the shifting piece is connected with the frame unit and is used for driving the inclination of the frame unit to change; the data acquisition system is used for monitoring the motion characteristics and collapse deformation of the slope model in the simulation process in real time and collecting data information generated in the test process; the problems that a traditional slope test device cannot dynamically simulate gradient gradual change caused by earthquake collapse, and the multi-disaster coupling effect of rockfall impact and hydrological airflow disturbance is difficult to reproduce are solved.

The invention discloses a reinforcing device before dangerous rock removal and treatment, which comprises at least two pairs of fixed anchor rods, the two pairs of fixed anchor rods are arranged in a matrix, the two pairs of fixed anchor rods are embedded in dangerous rock, the two pairs of fixed anchor rods are externally connected with a protective net, and the reinforcing device further comprises a pair of traction anchor rods arranged between the two pairs of fixed anchor rods. The invention relates to the technical field of dangerous rock reinforcement, the drilling, cooling and grouting functions are integrated through the hollow anchor rod, and the rock mass damage risk is reduced through single-point construction; the flexible connection system can effectively resolve the rock mass displacement stress; a gapless interception system is formed by the double-layer structure of the protective net and the blocking net, and falling stone impact energy is dissipated by the hydraulic buffer device in a grading manner; according to the design of the split type positioning hanging rings and the quick-release pins, modularized quick replacement of the protective net is achieved, the construction complexity is reduced through the standardized anchor rod assembly, the requirement for the number of anchoring points is reduced through cooperative bearing of the traction anchor rods and the fixed anchor rods, and the dangerous rock reinforcing safety and the construction efficiency are remarkably improved.

The utility model relates to the technical field of landslide collapse protection, and discloses a landslide collapse protection device which comprises a protection net. The supporting part is arranged on one side of the protective net, the supporting part is connected with the protective net, and a pressure sensor is arranged in the supporting part; the fixing part comprises a plurality of air cylinders and fixing seats, the fixing seats are arranged on the lower portions of the protective net, the supporting part and the air cylinders correspondingly, and the ends, away from the fixing seats, of the air cylinders are fixed to the sides, away from the protective net, of the supporting part; the controller is arranged on the supporting part, and the controller is electrically connected with the pressure sensor and the air cylinder. The supporting part is arranged on one side of the protective net, and meanwhile the fixing part is arranged, so that the supporting force of the device on a slope body can be improved, and high-strength impact can be well resisted; and secondly, a pressure sensor is arranged in the supporting part, pressure data of the slope body on the protective net are monitored in real time, when the pressure data exceed a preset pressure value, a controller controls an air cylinder to extend so as to enhance falling stone blocking, and practicability is high.

The invention discloses a dangerous rock falling motion feature analysis method based on discrete element simulation, and belongs to the technical field of engineering geology. Comprising the steps that dangerous rock data are collected through multiple means and preprocessed, and a three-dimensional visual dangerous rock mass initial model is constructed; based on the three-dimensional visual dangerous rock mass initial model, constructing a discrete element model, defining contact types and parameters among joint units by adopting a Hertz-mindlin contact theory, and determining normal contact force; based on the discrete element model and the normal contact force, a discrete element simulation technology is adopted, multi-physical field factors are considered to simulate dangerous rock falling movement, a discrete element model simulation result is obtained, a dynamic updating method is adopted for joint failure judgment, and the discrete element model is verified through an indoor physical model test and field monitoring data. And designing and implementing a prevention project according to a simulation result, thereby effectively preventing dangerous rock falling disasters and ensuring project safety.

The invention discloses a mountain state real-time monitoring and identification method and system based on deep learning. The method comprises the following steps: performing multi-angle dynamic image acquisition through a PTZ camera; training a dual-target detection network based on a YOLOv7 framework, constructing a rockfall-crack detection model, and synchronously outputting bounding box coordinates of a rockfall target and position information of a crack region; constructing a rockfall trajectory prediction model through a DeepSORT multi-target tracking algorithm, and obtaining rockfall movement trajectory data; pixel-level semantic segmentation is carried out on the crack area, a crack mask graph is generated, and a crack main direction vector is extracted; carrying out registration and difference calculation on the image to obtain a crack width variation and an extension length, identifying a newly-added crack region and marking spatial distribution of the newly-added crack region; and constructing a multistage alarm mechanism which comprises multistage alarm signals of an on-site audible and visual alarm device and a cloud platform. The mountain disaster monitoring and early warning system has the advantages that efficient and real-time monitoring and early warning of mountain disasters are achieved through rockfall detection and tracking and crack analysis and prediction.

The present application discloses a method for measuring impact force of debris flow and application, and a design method for barrier energy dissipation pile array. The method for measuring vertical impact force of debris flow measures the tangential velocity of debris flow at the impact point to measure the vertical impact force distribution of debris flow on the impact point. Further, the design method for pile array simplifies the free section of energy dissipation pile as a cantilever beam, which generates a bending resistance when impacted by debris flow, and the bending resistance continuously works to dissipate the impact kinetic energy of debris flow. According to the motion characteristics of debris flow, the impact time and distance parameters are further derived to solve the problems of measuring and designing the stability parameters of single energy dissipation pile, the energy dissipation parameters of barrier energy dissipation pile array, and the number parameters of barrier energy dissipation pile array. The present application also provides the application of each measuring and designing method. The present application provides a more scientific and perfect solution for the energy dissipation design of barrier energy dissipation pile array to resist the impact damage of rockfall and debris flow caused by landslide disaster.

The invention discloses a hydropower engineering extra-high steep slope online dynamic prevention and control method. The method comprises the steps that S1, data dynamic coupling and abnormity elimination are carried out; s2, carrying out space-time matching on the data; s3, optimizing a displacement early warning value; s4, carrying out safety prevention and control multi-modal analysis; and S5, performing result feedback and closed-loop control. According to the online dynamic prevention and control method for the ultra-high and steep slope in the hydropower engineering, rapid and accurate fusion of multi-source heterogeneous spatio-temporal data can be realized, the false alarm rate of slope early warning is reduced, and online closed-loop analysis of automatic identification of dangerous rock body hidden danger, real-time analysis of rockfall trajectory speed and pre-consolidation range and anchoring differentiation decision of the high and steep slope is realized; and a scientific, accurate and timely decision basis is provided for safety management of the high and steep slope.

The invention relates to the technical field of video image intelligent analysis, in particular to a rockfall detection and early warning method and system based on videos. According to the method, a suspected rockfall target is recognized and judged by collecting a road or side slope monitoring video and combining target detection and motion trail analysis; and after the rockfall is judged, generating early warning information containing the position, time and danger level, storing the early warning information in a database, and triggering an early warning prompt of a user side at the same time. The system is composed of a video acquisition module, a detection and judgment module, an early warning generation module, a log storage module and a front-end interaction module, and all the modules achieve cooperation through data interfaces. Compared with the prior art, the method can still keep high detection accuracy and real-time performance in a complex environment, has the advantages of high automation degree and high expandability, can be widely applied to scenes such as highways, railways and mining areas, and remarkably improves the traffic and engineering safety level.

The invention provides a high and steep slope dangerous rock mass instability mode judgment method and system, and belongs to the field of rock mass engineering, dangerous rock mass point cloud data of a target area is obtained, neighborhood point searching is performed on point clouds at different positions of a slope according to coordinate information in the dangerous rock mass point cloud data, plane fitting and coplanarity testing are performed on neighborhood points, and a dangerous rock mass instability mode judgment result is obtained. And merging the coplanar point sets, and calculating to obtain the inclination and the inclination angle of the structural plane according to the point sets. And clustering and grouping the structural surfaces, fitting the structural surfaces and performing intersection calculation. Point-surface calculation and analysis are carried out by combining topographic features of the high and steep slope, geometric morphology of the rock mass and development conditions of structural surfaces, the dangerous rock mass is positioned, the damage mode of the dangerous rock mass is identified, the judgment accuracy is improved, the damage mode of the slope rock mass is finely divided, and disaster prevention and reduction work of rockfall disasters of the high and steep slope is facilitated.

The invention discloses a design method of a slope flexible protection system in an extra-high and steep environment. The number of flexible protection nets is determined based on terrain parameters of a high and steep slope and parameters of the flexible protection nets; the arrangement position of each flexible protective net is determined according to the movement track of the rolling rocks and the falling rocks; determining the height of the flexible protective net based on the arrangement position of the flexible protective net; the length of each flexible protective net is determined according to the envelope line of the projection range of the rolling and falling rock bouncing trajectory; and based on the number of the flexible protection nets and the arrangement position, height and length of each flexible protection net, the ultra-high steep environment slope flexible protection system is designed. According to the method, the number of tracks is determined by dynamically matching the kinetic energy of rolling stones and falling stones and the energy level of the protective net, the protective net is arranged by combining the vertex of the bouncing track, the length of the protective net is determined based on the track projection range, the problems that a traditional method depends on experience, a protective blind area exists and resources are wasted are solved, and the method has the advantages of scientific quantification and accurate protection.

The invention discloses a valley-type ice rock collapse clastic flow disaster chain danger range prediction method, system and device and a storage medium, and belongs to the field of clastic flow disaster prevention and control, and the method comprises the steps: obtaining the average width of a valley; determining the volume and the ice content of the hidden danger body; the ratio H / L of the predicted vertical height difference H to the horizontal distance L in the whole movement process of the ice rock collapse clastic flow is obtained; the ratio Ht / Lt of the vertical height difference Ht and the horizontal distance Lt from the position of the hidden danger body to the position of each point of the gully is obtained, and when the first value smaller than H / L appears in the Ht / Lt, the position is determined to be the maximum danger range boundary of the ice rock collapse clastic flow disaster in the gully. The invention provides a set of efficient, quantitative and spatialized scheme, the static distribution information of the ice rock clastic flow hidden danger can be accurately quantified into visual and available geographic space information of the maximum danger range in combination with the dynamic influence of the valley terrain, and the risk assessment and emergency decision of ice rock collapse clastic flow disasters can be more scientifically supported.

The invention relates to the technical field of slope monitoring, in particular to a mine field slope instability trend-based radar monitoring and early warning method and system, and the method comprises the following steps: recognizing a slope region with an instability risk on a geological image through a pre-trained Fast R CNN model, and taking the slope region as an instability risk region; scanning the instability risk area in real time through a slope radar to obtain a radar image sequence of the instability risk area; and acquiring a geological image sequence of the instability risk area with the same time sequence as the radar image sequence, determining an instability trend of the instability risk area based on the radar image sequence and the geological image sequence, and then allocating an early warning level according to the instability trend. According to the method, locking of instability factors in advance is realized on the basis of the Fast R CNN model, falling rock and soil loosening sliding track trends are quickly analyzed in real time on the actual falling rock and soil loosening track obtained through multi-modal data solution on the basis of the LSTM network, and thus integrated display, focusing monitoring and graded early warning of mining area risk points are realized.

The invention discloses measuring equipment for a tunnel construction site, and relates to the field of construction measuring equipment, the measuring equipment comprises a measuring vehicle, a driving arm is rotatably mounted on the measuring vehicle, and two measuring instruments are movably mounted on the driving arm; the device also comprises an impact rebound protection device, and the impact rebound protection device is disposed on the measuring vehicle. It needs to be explained that falling rocks can be effectively bounced off through the arrangement of the side impact plates and the front impact plate; if the falling rockfall is too large, the measuring instrument can be stored in the measuring vehicle to be protected, the rotary storage shaft drives the synchronous supporting rotating frame to rotate, the measuring vehicle is lifted, the rockfall slides away, safety of equipment on the measuring vehicle is further guaranteed, the synchronous supporting rotating frame can be pushed to move, and then the supporting area of the measuring vehicle is enlarged; in addition, when falling rocks fall on the front impact plate, the active cleaning strip moves transversely to pull away the falling rocks on the front side of the measuring vehicle, and cleanliness of the advancing path of the measuring vehicle is guaranteed.

The invention relates to the technical field of high and steep slope dangerous rock mass exploration, in particular to a dangerous rock risk rapid quantitative evaluation method based on probability calculation. Comprising the following steps: S1, constructing a multi-level evaluation factor system of dangerous rock dangerousness, including three factor types of a basic geological environment factor, a dangerous rock falling rock collapse development factor and an induction factor; s2, performing quantitative analysis or qualitative analysis on the multi-level evaluation factor indexes according to the evaluation factor types, establishing a comprehensive evaluation system with subjective and objective fusion based on a system interaction analysis method, and calculating the weight of each evaluation factor; s3, constructing a dangerous rock danger calculation model based on a risk triangle theory, and inputting the weight of each evaluation factor into the dangerous rock danger calculation model to calculate a danger value; and S4, dividing danger levels of the dangerous rock mass according to the danger values, and outputting a visual evaluation result. According to the quantitative evaluation method provided by the invention, the danger of the high and steep slope can be quantified more accurately, and a basis is provided for engineering construction safety.

The present invention relates to the field of slope monitoring technology, and more specifically to a radar monitoring and early warning method and system based on the instability trend of mine slopes. The method comprises the following steps: using a pre-trained Fast R-CNN model to identify slope areas at risk of instability on a geological image as instability risk areas; using a slope radar to scan the instability risk areas in real time to obtain a radar image sequence of the instability risk areas; obtaining a geological image sequence of the instability risk areas that is co-sequential with the radar image sequence, and determining the instability trend of the instability risk areas based on the radar image sequence and the geological image sequence, and then assigning an early warning level based on the instability trend. The present invention uses the Fast R-CNN model to achieve early locking of instability factors, and based on the LSTM network, quickly and in real time analyzes the sliding trajectory trends of falling rocks and loose soil based on the actual trajectory of falling rocks and loose soil obtained by solving multimodal data, thereby achieving integrated display of risk points in the mining area, focused monitoring, and graded early warning.

The invention discloses a rockfall detection method, device and equipment, a storage medium and a product, and relates to the technical field of machine vision, and the rockfall detection method comprises the steps that a monitoring picture of rockfall of a road side slope is acquired; performing static background removal processing on the monitoring picture to obtain a background reconstruction image, and performing region labeling on a dynamic target in the monitoring picture to obtain a dynamic region of the dynamic target; inputting the background reconstruction image into a preset YOLO algorithm to obtain a first detection result of the dynamic target, and inputting the dynamic region into a preset classification network to obtain a second detection result of the dynamic target; and the falling point of the rockfall is determined based on the first detection result and the second detection result, that is, the rockfall detection efficiency is improved by improving the rockfall detection rate and the rockfall point detection accuracy.

The invention provides a slope rockfall monitoring and early warning method, device and equipment based on dynamic depth estimation and a medium. Relates to the technical field of civil engineering operation maintenance. The method comprises the following steps: S1, acquiring a video sequence image; s2, performing dynamic target detection on the video sequence image by adopting a frame difference method; s3, based on a pre-trained rockfall identification model, identifying rockfall in the target frame; s4, based on a depth-pro monocular image depth estimation model, performing depth estimation on the rockfall in the target frame to obtain a rockfall position distance; s5, performing feature analysis on the rockfall in combination with the depth data to obtain feature parameters; s6, performing tracking and trajectory identification on the rockfall; and S7, performing alarm reminding according to tracking and trajectory recognition results. According to the method, the extracted features are trained to identify the slope rockfall, the position and the size of the rockfall can be identified more accurately, a sharp measurement depth map is rapidly provided, and the dynamic change of the slope rockfall is captured in time.

The invention provides a rockfall slope geology early warning device and method based on digital twinning, and relates to the technical field of slope geology early warning. According to the invention, slope multi-dimensional physical parameters are obtained through the perception acquisition module, standardized processing and multi-protocol transmission are completed nearby through the edge transmission module, and the cloud load is reduced. The digital twinborn module constructs a mechanical twinborn model, dynamically updates and forms a digital twinborn body in combination with standard data, and accurately copies the slope state; and the early warning decision module realizes graded early warning through a risk assessment system. A full-link closed loop of sensing, transmission, modeling and early warning is integrally formed, the problems that traditional early warning data are fragmented, manual dependence is high, and static modeling is disjointed with reality are solved, conversion from passive response to active pre-judgment is achieved, on-site rapid response and global accurate analysis are balanced, and the accuracy, real-time performance and actual combat performance of early warning of the rockfall slope are improved.

The invention provides a collapsed rockfall accurate identification and monitoring method and device based on AI and machine vision, and relates to the technical field of geological disaster monitoring, and the method comprises the steps: collecting the multi-modal visual data and environmental parameters of a collapse hidden danger region through a cooperative collection system; performing recognition, contour extraction and spatial parameter calculation on the multi-modal visual data through the recognition and positioning model to obtain a contour sequence, a volume sequence, a spatial coordinate sequence and a spatial attitude sequence of the collapsed rockfall; on the basis of the space coordinate sequence, the space attitude sequence and the multi-modal visual data, predicting the movement track and the speed sequence of the collapsed rockfall through a mixed time sequence AI model; inputting the environment parameters, the contour sequence, the volume sequence, the motion trail and the speed sequence into a kinetic energy calculation model, and calculating to obtain the impact energy of the collapsed rockfall; according to the contour sequence, the volume sequence, the motion trail, the speed sequence and the impact energy of the collapsed rockfall, the collapsed rockfall risk level is obtained through calculation.

The invention discloses an operation high-speed rail tunnel exit tall slope collapse rockfall construction method and system, relates to the technical field of rockfall protection, and is applied to an operation mountain with a structure denudation type high and steep high mountain and hill landform at an operation high-speed rail tunnel exit. The distribution and characteristics of the dangerous rock mass can be accurately presented; the model is subjected to region division to obtain a plurality of dangerous rock risk regions, so that detailed distinguishing of different risk regions can be realized; carrying out slope stability evaluation on each dangerous rock risk area and determining a risk level, so as to clearly quantify a risk condition; corresponding slope protection components are matched according to the risk levels, so that selection of the protection components is more targeted; and finally, scaffold platforms of all dangerous rock risk areas are built, operation is carried out through protection components, effective implementation of protection work is guaranteed, then pertinence and reliability of slope protection can be improved, and safety risks and resource waste caused by improper protection are avoided.

The present invention relates to the technical field of slope rockfall protection, and provides a rockfall pre-sensing active avoiding type steel column supporting system which comprises a rotatable column foot, a deflection steel column, a pulley node, a pre-sensing upper pulling anchor rope and a connecting piece. A bottom lug plate of the deflection steel column is provided with a hole, the fit tolerance of a diameter of the hole and a diameter of a pin shaft is large, so as to help the steel column to rotate in a horizontal direction. The pulley node is provided with double pulleys, a pre-sensing pull-up anchor rope is wound on each of the two pulleys, two anchor points of each rope are distributed on two sides of a projection line (hereinafter referred to as the projection line) of an initial axis of the steel column on a slope surface, one anchor point is near the projection line, and the other anchor point is far away from the projection line. Before falling rocks impact the steel column, the pull-up anchor rope on one side near the projection line is firstly impacted, and the steel column deflects towards the other side under the action of a resultant force of the pull-up anchor rope, so that falling rock impact can be avoided or impact damage of the steel column can be reduced. The protection problem that falling rocks directly impact the steel columns is solved, and the impact resistance reliability and disaster prevention toughness of the passive nets are greatly improved.

The invention discloses an accurate control blasting construction method for a high and steep slope of a surface mine, and relates to the field of blasting operation. The accurate control blasting construction method for the high and steep slope of the surface mine is outstanding in safety benefit, and the long-term stability of the slope is greatly improved by forming the high-quality flat slope, so that the risks of landslide and rockfall are fundamentally reduced, and the safety of personnel and equipment below is guaranteed; the economic benefit is remarkable, overexcavation and underexcavation of the side slope are reduced, the stripping amount is close to a design value, the cost is saved, a steeper slope angle can be adopted for stabilizing the side slope, the total rock stripping amount is reduced, recoverable resources are increased, and the service life of a mine is prolonged; the technical benefit is obvious, the half-hole rate is improved, the surrounding rock damage and blasting vibration are reduced, and a better foundation is provided for slope supporting operation such as follow-up anchor rod and anchor cable installation; environmental and operation benefits are improved, environmental damage caused by slope instability is reduced, drainage system arrangement and daily safety inspection are better facilitated through slope leveling, and long-term maintenance cost is reduced.

The invention relates to the technical field of transformers, and discloses a transformer protection structure which comprises a protection shell, two supporting rods are fixedly connected to the top of the protection shell, fixing cylinders are fixedly connected to the left sides and the right sides of the two supporting rods correspondingly, and spring extrusion rods are slidably connected to the inner walls of the four fixing cylinders correspondingly; when falling rocks in mountainous regions fall and make contact with the blocking assembly, the rocks collide with the blocking assembly, so that the blocking assembly is pushed to rotate, part of impact force is converted into rotation kinetic energy, impact force directly transmitted to the transformer is reduced, meanwhile, gas is compressed through the absorption assembly, residual energy is absorbed, and after the gas is exhausted along with increase of gas pressure, the residual energy is reduced. And the process is repeated, so that the opportunity of absorbing energy for multiple times is formed, the impact of broken stones is reduced, the vibration borne by the sliding plate is reduced, and the situation that the transformer generates large vibration due to the fact that the stone blocks impact the sliding plate and transmit the large vibration to the protective shell is effectively prevented.

The invention relates to the technical field of computer vision, in particular to a motion perception rockfall intelligent monitoring method and device based on deep learning. The method comprises the following steps: receiving a monitoring video from a monitoring area; constructing a rockfall detection and tracking framework based on a YOLOv8 target detection network and a ByteTrack target tracking algorithm; preprocessing the monitoring image, inputting the monitoring image into a YOLOv8 detection network to carry out moving target feature extraction, and outputting a rockfall detection result; and track matching is carried out by using a ByteTrack algorithm in combination with Euclidean distance and motion direction constraint, and a rockfall motion track is generated. According to the method, a traditional image algorithm and a deep learning algorithm are combined, moving target detection and multi-target tracking are constructed, and rockfall in a complex rock background is accurately captured from multiple dimensions; according to the method, the space coordinate position of the rockfall target can be accurately obtained, a complete movement track can be generated for each rockfall target, statistical information of rockfall events is effectively obtained, and a reliable basis is provided for disaster grade evaluation and early warning.

The invention relates to an intelligent multi-mode collaborative reservoir unmanned aerial vehicle inspection system, and the system comprises a data enhancement module which is used for generating an enhanced training data set; the multi-scale feature fusion module is used for generating a corresponding multi-scale fusion model; the loss function optimization module is used for calling a preset multi-task loss function, evaluating and optimizing a calculation result obtained by calculation of the multi-scale fusion model, and generating a corresponding optimized fusion model; the detection module is used for generating a corresponding candidate target area; and the judgment module is used for carrying out multi-stage rockfall detection judgment on the dynamic target in the candidate target area based on the optimization fusion model so as to execute corresponding early warning operation. By integrating multiple technical means of data enhancement, depth feature fusion, loss optimization, multi-stage intelligent discrimination and the like, high-precision and high-robustness recognition and early warning can be carried out on a rockfall target in a complex and changeable reservoir mountain slope environment.

The invention discloses a landslide disaster site safety risk assessment decision-making method and system, and belongs to the technical field of geological disaster risk assessment and emergency rescue. According to the invention, through multi-source monitoring data fusion processing, potential rockfall risk release points on a landslide site are identified, and attributes and release probabilities of the potential rockfall risk release points are quantified; a data-driven rockfall simulation model parameter intelligent optimization system is constructed, and self-adaptive adjustment of simulation parameters is achieved; and a scene-driven five-factor risk assessment system is provided, risk assessment of the operation area is completed by integrating disaster risk and disaster-bearing body sensitivity, and finally a visual risk distribution map is generated and dynamic updating is realized. According to the method, the defects of static performance, parameter solidification and single index of a traditional assessment method are overcome, dynamic and high-precision assessment of the landslide disaster risk is realized, the accuracy and the real-time performance of risk assessment are remarkably improved, and scientific and reliable decision support is provided for landslide emergency rescue operation.