186results about How to "Reduce property damage" patented technology

The invention relates to the technical field of earthquake monitoring, in particular to a geological disaster early warning device based on earthquake waveform recognition, which comprises an earthquake data receiving module, an earthquake wave type analysis module, a disaster mode recognition module, an early warning signal construction module, a risk judgment module and an early warning information issuing module. According to the invention, through identifying and analyzing the seismic waveform data, the characteristics of the earthquake and the type of the caused disaster, such as landslide, rock collapse, debris flow, ground fissure, surface collapse and the like, are rapidly judged, and through comprehensively evaluating the emergency and the influence range of the earthquake event, the targeted early warning information is generated and issued in time. The geological disaster response speed and efficiency can be remarkably improved, earthquake monitoring is not limited to recording of earthquake activities, disaster risks can be evaluated in real time, more accurate disaster prediction and early warning can be provided, for areas where geological disasters frequently occur, the early warning accuracy and timeliness can be remarkably improved, casualties and property losses can be reduced, and the economic benefit is improved. And the method has extremely high practical value and social significance.

The invention belongs to the technical field of fire detection, and discloses a method and a system for artificial intelligence identification, research and judgment of fire alarm, and the method comprises the following steps: carrying out the framing of input video data, converting a video stream into continuous image frames frame by frame, carrying out the timestamp marking of each frame of image, and obtaining a framed image; according to the method, flames are positioned by analyzing red and orange tones of the images, early signs of a fire can be more accurately captured by analyzing flame shapes and diffusion behaviors, the area change rate of flames and smoke in continuous frames can be analyzed, the dynamic change of flame diffusion speed and smoke coverage can be beneficially understood, and the method is suitable for popularization and application. The fire hazard early warning is more timely and accurate, the fire hazard risk level is evaluated according to the flame dynamic model, and the system is allowed to adjust the sensitivity and threshold of the early warning signal according to the real-time data, so that the fire hazard early warning scheme is more targeted and effective, faster response can be provided at the initial stage of the fire hazard, and casualties and property loss are greatly reduced.

The invention discloses a distributed optical fiber monitoring system for monitoring a rock mass change state, relates to the field of monitoring equipment, is applied to an underground cavity and can monitor axial and radial fracture signals of the underground cavity at the same time so as to facilitate three-dimensional positioning of a seismic source at a fracture occurrence position. The distributed optical fiber monitoring system comprises a first optical fiber and a second optical fiber. The first optical fibers are arranged on the cavern wall in the axial direction of the underground cavern and can monitor fracture signals distributed in the axial direction of the underground cavern; the second optical fiber is mainly composed of a peripheral side optical fiber section and a reversing transition section, and the peripheral side optical fiber section is used for being arranged on the cavern wall along the cross section contour of the cavern wall and can monitor fracture signals distributed in the radial direction of the underground cavern. Therefore, the distributed optical fiber monitoring system can simultaneously monitor the axial and radial fracture signals of the underground cavern, realizes the space monitoring of the underground cavern, and facilitates the more accurate three-dimensional positioning of a seismic source at the fracture occurrence position.

The invention belongs to the technical field of automobile information safety fuzzy testing, discloses an automobile information safety fuzzy testing method based on a large model, and develops optimization application research of LLMs in an automobile software fuzzy testing scene by utilizing the advantages of an artificial intelligence technology in the aspects of data processing, natural language interaction, generalization ability and the like. The concealment and effectiveness of the test set generated by the fuzz test are optimized, and the fuzz test process efficiency is improved. Through the implementation of the invention, related key technologies are applied to the fuzz test of the automobile, and other related products and enterprises in China are radiated by writing technical standards, so that the fuzz test system can be used as an application demonstration and sample plate of the fuzz test of the intelligent driving automobile. According to market analysis, fuzzy test calculation is carried out on 100 thousand automobiles every year according to the method, and the data safety and the system safety are improved.

The invention relates to the technical field of coal mine safety, in particular to a coal mine major disaster risk prevention and control system and method based on artificial intelligence, and the system comprises a data collection module, a data transmission module, a data processing module, a disaster prediction module, a decision support module and a user interaction module. The data transmission module transmits collected environment data to a ground control center, the data processing module ensures the accuracy and consistency of data through data preprocessing, data fusion and anomaly detection, the disaster prediction module predicts potential disasters and generates a risk assessment report, and the decision support module determines the risk assessment report according to the prediction result. According to the system, multiple intelligent technologies are integrated, comprehensive prevention and control of major disasters of the coal mine are achieved, and the safety management level of the coal mine is improved.

The invention relates to the technical field of power load analysis, and discloses an intelligent ammeter power load analysis system and method, and the method comprises the steps: obtaining the current overall power consumption of a user, judging whether the power consumption of the user is abnormal or not, forming abnormal analysis data, and carrying out the corresponding abnormal prompt for the user according to the abnormal analysis data. According to the intelligent electric meter power load analysis system and method, whether the electric equipment is abnormal or not is judged according to the power utilization data collected by the electric meter, the abnormal reason of the electric equipment is judged according to the power utilization data, and a user is timely notified to carry out adjustment according to the abnormal reason of the electric equipment; therefore, the service life of the electric equipment is prevented from being shortened due to the fact that the use condition of the electric equipment cannot be adjusted in time, the equipment is prevented from being damaged due to the fact that equipment abnormity cannot be perceived in time, the service life of the equipment is prolonged, property loss of a user is reduced, fire catching of the electric equipment is reduced, and personal injury to personnel due to fire disasters is avoided.

An indoor fire hazard flashover risk prediction method based on a flame form and remote sensing data comprises the following steps: using fire hazard simulation software to simulate fire hazard data, and constructing a fire hazard data set; ignition is conducted, an indoor fire flame image is obtained through a high-definition camera, and the obtained image is processed; outputting the real-time heat release rate HRR of a fire point from the processed image through a residual network Resnet model; a methane laser remote sensing detector is used for monitoring and acquiring methane gas concentration data of an indoor flue gas layer at a specific height in real time; and building a fire hazard flashover risk prediction model based on the fire source heat release rate and the methane gas concentration, and predicting the flashover risk in advance. According to the invention, accurate identification and prediction of the flashover risk of the fire in the early stage of fire development are realized, and an early warning signal is sent when the fire is about to enter the flashover stage, so that casualties and property loss caused by the fire are reduced.

The invention provides a maritime traffic accident severity prediction method based on feature engineering, and the method comprises the steps: constructing a maritime accident risk influence factor data set according to risk influence factors and accident severity in historical data, and carrying out the preprocessing of the data; coupling the influence factors through a feature fusion algorithm, and mining association rules; carrying out data balance analysis by using an SVM-SMOTE oversampling method, and balancing the sample proportion of serious accidents and non-serious accidents; the original influence factors are trained by using multiple machine learning models, and key influence factor subsets are screened out by calculating the importance degrees of the influence factors; and S4, evaluating an optimal model in the machine learning model through a UAR evaluation index, and predicting the severity of the marine traffic accident by using the optimal model and combining the key influence factor subset in the S4. By reasonably matching the combination of the prediction model and the oversampling method, the model performance is remarkably improved, and a comprehensive and profound insight is provided for predicting the severity of the marine accident.

The invention belongs to the technical field of mountain torrent disaster monitoring, and discloses a mountain torrent disaster monitoring data source fusion processing method and system based on deep learning. The method comprises the steps of multi-source rainfall data collection, multi-source data fusion and fusion processing of multiple monitoring data sources, including data integration, data alignment, data fusion algorithm and other operations, and through fusion processing of the multiple monitoring data sources, a high-precision rainfall monitoring result is obtained. Analyzing rainfall data, and predicting the probability and range of mountain torrent disasters possibly occurring in the future according to an analysis result; and releasing mountain torrent early warning information. Based on a multi-source data fusion technology, the rainfall condition can be monitored more accurately, and the accuracy and reliability of early warning are improved. Early warning information is sent out 2 hours in advance, enough time can be provided for relevant mountain torrent defense departments to take countermeasures, and casualties and property losses are reduced.

The utility model discloses a battery car storage battery charging cabinet with an automatic fire extinguishing device, which comprises a cabinet body, a plurality of battery cabins are longitudinally arranged on two sides in the cabinet body, a battery falling channel is formed between two rows of battery cabins, and an isolation cabin communicated with the battery falling channel is arranged at the bottom of the cabinet body. A hot aerosol fire extinguishing device is installed at the top end in the isolation bin, a charging socket and a separation mechanism are installed on the inner wall of the battery bin, a smoke sensing alarm is installed at the top end in the battery bin, an electric control unit is installed at the bottom end in the battery bin, and a discharging opening communicated with a battery falling channel is formed in one side of the battery bin. According to the storage battery automatic fire extinguishing device, the storage battery which is spontaneously combusted can be isolated and automatically extinguished, the influence of the fire behavior on other storage batteries is reduced, and potential safety hazards and property loss are reduced.

The invention discloses a flood inundation area prediction method based on land survey data, and relates to the technical field of flood inundation area prediction.The method comprises the steps that when a dam breach risk coefficient of a target dam is not smaller than a preset dam breach risk coefficient, a plurality of preliminary inundation sub-areas are simulated according to flood water flow; obtaining a first flood water storage capacity of each preliminary submerging sub-region; taking the current vegetation density, underground water level height and soil permeability coefficient of each preliminary submerging sub-region as a data set, and clustering the data set to determine a water storage capacity influence index of each preliminary submerging sub-region; the second flood storage capacity is obtained according to the water storage capacity influence index and the first flood storage capacity, and the final flood inundation area is determined according to the second flood storage capacity, so that the flood inundation area in the future period can be predicted, the flood control plan and the emergency plan are normal, flood can be effectively prevented and evacuated before the flood comes, and the flood inundation efficiency is improved. And casualties and property loss are reduced.

The invention relates to the technical field of electro-hydraulic control, and discloses an emulsion pump station frequency conversion control system which comprises an emulsion pump station, a pump station initialization subsystem, a fault detection subsystem, a pressure sensor, a controller, a frequency conversion device, an emulsion pump station switching subsystem, an emulsion pressure setting subsystem and an emulsion main pipeline. The invention further provides an application method of the emulsion pump station frequency conversion control system. The application method comprises the following steps that S1, a program is initialized; the emulsion supply efficiency of the fully mechanized coal mining face of the coal mine can be improved, the liquid supply pressure can be stabilized, the power consumption in the liquid supply system can be reduced, the service life of frequency conversion control system equipment of the emulsion pump station can be prolonged, automatic control of the emulsion pump station can be realized, the labor cost can be reduced, and the working efficiency and reliability can be improved; unnecessary property loss is reduced, and important technical guarantee is provided for efficient and safe production of the coal industry and stable development of the coal industry.

The invention discloses a coal dust influence suppression method for coal mine gas laser detection and a detection device, and the method comprises the steps: extracting gas in a coal mine goaf through a gas pump and a beam tube of the coal mine gas laser detection device, and detecting a characteristic absorption spectrum of the gas in the goaf by adopting a TDLAS technology; correcting a second harmonic signal and a peak value in the characteristic absorption spectrum by considering the attenuation influence of the coal dust in the goaf gas on the second harmonic signal of the laser penetrating through the goaf gas; and obtaining the accurate concentration value of each component gas in the goaf gas by using the corrected second harmonic signal peak value. According to the invention, the influence of coal dust on gas concentration detection can be greatly reduced, the sensitivity of gas detection is improved, and good detection effect and precision can be achieved.

The invention relates to the technical field of slope disaster monitoring, in particular to a high and steep slope geological disaster monitoring method and system based on multi-source data fusion. The method comprises the following steps: tracking surface deformation through PS-InSAR time sequence analysis and atmospheric phase correction to obtain surface deformation characteristics; identifying the apparent diseases of the slope, and extracting spatial and temporal distribution characteristics of the apparent diseases of the slope; analyzing spatio-temporal evolution characteristics under geologic structure constraints by utilizing slope rock mass structure characteristics and the earth surface deformation characteristics; according to underground water level dynamic and potential sliding surface weakening features and the slope apparent disease spatial and temporal distribution features, extracting disaster-causing key factor features after cooperative correction; and combining the disaster-causing key factor characteristics, the true three-dimensional geological environment background characteristics and the spatio-temporal evolution characteristics to analyze the comprehensive early warning grade and the potential instability mode of the landslide. Scientific support is provided for high and steep slope geological disaster prevention and control, and engineering construction and operation safety can be guaranteed.

The invention discloses a fire-fighting processing method, an electronic device, a storage medium and a program product. The method is applied to the energy storage device, the energy storage device comprises an energy storage cabinet body, at least one battery pack is arranged in the energy storage cabinet body, and the method comprises the steps of obtaining first state information and second state information, the first state information is obtained based on predetermined environmental parameters in a space defined by the interior of an energy storage cabinet and the exterior of the battery pack, and the second state information is obtained based on predetermined environmental parameters of the internal space of the battery pack; generating a first system-level fire-fighting instruction according to the first state information, wherein the first system-level fire-fighting instruction is used for instructing the energy storage device to carry out fire fighting on the interior of the energy storage cabinet body; and according to the second state information, generating a battery pack level fire-fighting instruction corresponding to a target level in a plurality of preset battery pack fire-fighting levels, wherein the battery pack level fire-fighting instruction is used for instructing the energy storage device to carry out fire fighting on the interior of the battery pack.

The fire-extinguishing flame-retardant explosion-proof battery storage bag composite structure comprises a heat transfer layer, a cooling explosion-proof layer, a fire-extinguishing barrier layer and a waterproof and fireproof layer which are sequentially arranged from inside to outside, a heat transfer layer, a cooling explosion-proof layer, a fire-extinguishing barrier layer and a waterproof and fireproof layer which are sequentially arranged from inside to outside form a fire-extinguishing flame-retardant explosion-proof battery storage bag composite structure; the heat transfer layer is used for conducting heat generated by batteries in the battery storage bag to the cooling explosion-proof layer; the cooling explosion-proof layer is used for cooling and extinguishing the fire of the batteries in the battery storage bag; the fire extinguishing barrier layer is used for extinguishing and blocking fire of batteries in the battery storage bag; the waterproof and fireproof layer is used for preventing external fire sources and water sources from invading the batteries in the battery storage bag. The explosion-proof battery can prevent internal fire sources from leaking out, can also prevent external fire sources, water sources and the like from invading, can be applied to various protection products needing to be used for charging batteries, is good in fire extinguishing, flame-retardant and explosion-proof performance, guarantees personnel safety, and reduces property loss.

The utility model discloses a snow falling prevention device suitable for a bridge totally-enclosed sound barrier, which comprises steel stand columns and a steel camber beam, the lower surface of the steel camber beam is symmetrically and fixedly connected with the steel stand columns, the steel camber beam and the steel stand columns form the complete totally-enclosed sound barrier, the upper surface of the steel camber beam is symmetrically and fixedly connected with steel support base plates, and the steel support base plates are fixedly connected with the steel support base plates. The upper surface of the steel support bottom plate is fixedly connected with a square steel pipe in an inner cavity of the steel support vertical plate, and the outer wall of the square steel pipe is fixedly connected with a baffle. Through physical blocking, accumulated snow is effectively prevented from sliding from the sound barrier, the traffic accident risk caused by accumulated snow sliding is greatly reduced, and therefore the safety of road traffic is guaranteed, the structure is stable, durability is high, if the device is made of high-strength and corrosion-resistant materials, it can be better guaranteed that the device can be kept stable under various severe weather conditions, and the service life of the device is prolonged. In addition, the structural design is also elaborately optimized, so that it is ensured that the device can still keep stable when bearing accumulated snow pressure and wind and snow impact.

The invention discloses a fire-fighting processing method, an electronic device, a readable storage medium and a computer program product. The method is applied to the energy storage device, the energy storage device comprises a cabinet body and at least one battery pack arranged in the cabinet body, and the method comprises the steps that first state information and second state information are obtained, the first state information is used for representing the thermal runaway degree of the energy storage device, and the second state information is used for representing the thermal runaway degree of the energy storage device; the second state information is used for representing the thermal runaway degree of the battery pack; generating a system-level fire-fighting strategy according to the first state information, wherein the system-level fire-fighting strategy is used for indicating the energy storage device to carry out fire fighting on the internal space of a cabinet body of the energy storage device; and generating a battery pack level fire-fighting strategy according to the second state information, wherein the battery pack level fire-fighting strategy is used for indicating the energy storage device to carry out fire fighting on the interior of the battery pack.

The invention belongs to the technical field of traffic meteorology, and provides a highway agglomerate fog detection method, which comprises the following steps: step 1, detecting layout including a first electrode, a second electrode, an environment conductivity sensor and a background server; 2, electrode signal time and conductivity information of the first electrode and the second electrode and conductivity information of the environment conductivity sensor are collected, and data are uploaded to a background server; step 3, acquiring a continuous change conductivity data curve through conductivity information acquired by the first electrode, the second electrode and the environment conductivity sensor; 4, judging and extracting agglomerate fog inducement conductivity change data through the conductivity change duration, and performing agglomerate fog prediction; and 5, uploading the agglomerate fog prediction information to the fog disaster risk zoning model, and starting agglomerate fog early warning. Accuracy and timeliness of agglomerate fog prediction are improved, timely and effective information is provided for related departments and drivers, and traffic accidents are reduced.

The invention discloses a positioning fire extinguishing system based on aerosol and perfluorohexanone, relates to the technical field of fire safety, and solves the problems that the specific accuracy of fire extinguishing coverage has related differences and the accuracy of the fire extinguishing coverage needs to be enhanced. The method comprises the following steps: determining a corresponding contour line, determining a related contour point location based on the corresponding contour line, locking a point location coordinate of the contour point location from a two-dimensional coordinate system, enabling the injected perfluorohexanone to accurately reach a specified fire source center point through an angle adjustment mode, and fully extinguishing a related fire source region around the fire source center point. And a better fire extinguishing treatment effect is achieved, and the fire extinguishing accuracy and range are fully guaranteed.

The invention belongs to the technical field of fire-fighting monitoring, and particularly relates to a fire-fighting monitoring and early warning system based on project fire analysis. The fire-fighting monitoring and early warning system comprises a data acquisition module, a data transmission module, a fire behavior analysis module, an early warning and alarm module, a user interface module, a data storage and management module, a remote monitoring and control module, a system integration and expansion module and a safety and authority management module. Through the advanced data acquisition, analysis and management functions, the accuracy and efficiency of fire detection and response are improved, the user interaction experience and the system compatibility are enhanced, powerful support is provided for fire safety management, the comprehensiveness, the safety and the flexibility are realized, and meanwhile, the safety of the system is improved. And the total operation cost and the safety risk are reduced.

The invention relates to the technical field of bridge construction, in particular to a self-adaptive intelligent catwalk steel wire rope. Comprising a central strand and a plurality of ordinary strands, and the central strand comprises a core strand located at the axis and a plurality of transmission strands surrounding the outer side of the core strand in the circumferential direction; an optical fiber sensor which is arranged in a full-length manner and is used for monitoring the steel wire rope penetrates through the core strand; the transmission strand is in transmission connection with the core strand and drives the core strand to rotate around the axis under the action of external torsion; the ordinary strands surround the outer side of the center strand in the circumferential direction to form a steel wire rope structure, and the center strand can be connected among the ordinary strands in the mode of rotating around the axis of the center strand. The catwalk steel wire rope is simple in structure and very easy to install, manufacture and assemble, the steel wire rope can be monitored in real time, early warning can be given out in time, a user is reminded, safety accidents are avoided, meanwhile, the catwalk steel wire rope can adapt to torsional deformation of the steel wire rope, the internal optical fiber sensor is not prone to damage, and the service life is long.

The invention belongs to the technical field of grounding wires, and discloses an intelligent short-circuit grounding wire monitoring device and method based on multiple sensors and a block chain. The device comprises a multi-sensor module, a Beidou positioning module, a sensor data acquisition module, a positioning data acquisition module, an artificial intelligence algorithm module, a data fusion algorithm module, a main control module, a sound-light alarm module and an NB-IoT communication module, wherein the multi-sensor module is used for acquiring use state data of the short-circuit grounding wire; the Beidou positioning module is used for acquiring positioning data of the short-circuit grounding wire; the system comprises an Internet of Things network platform, a background server, a block chain system, a monitoring platform, a terminal and a power supply module. The system is suitable for monitoring the intelligent short-circuit grounding wire through a multi-sensor and block chain system, carrying out the electricity verification of a line, and monitoring whether the short-circuit grounding wire is firmly hung and the position of the short-circuit grounding wire, thereby greatly improving the intelligent degree and informatization degree of the power grid maintenance work, and improving the operation efficiency and safety.

The invention discloses a brand-new fire emergency command system and method, which comprehensively applies advanced technologies such as artificial intelligence, multi-source perception, Internet of Things communication and man-machine interaction. The system achieves the functions of fire early-stage accurate recognition, fire risk level-to-level management, visual interactive alarm, intelligent linkage equipment control, efficient communication cooperation, visual command and information feedback, and can comprehensively improve the fire emergency response capability. The method comprises the steps of multi-source detection, artificial intelligence identification and early warning, hierarchical intelligent alarm and active visual alarm, equipment linkage control, interactive visual cooperative command, and emergency response whole-process recording and process optimization. The system can be widely applied to industrial emergency management of various mines, mines, chemical plants and the like, emergency command of natural disasters, emergency management of urban operation and other scenes, can realize early accurate disaster discovery, quick response and cooperative command and disposal, and greatly improves the emergency response speed and the processing efficiency.

The embodiment of the invention discloses a forest fire monitoring method and device and an unmanned aerial vehicle nest forest fire monitoring system. The mountain fire monitoring method comprises the following steps: receiving mountain fire early warning information emitted by a satellite; controlling the unmanned aerial vehicle to detect a fire point according to the forest fire early warning information, and collecting forest fire information at the fire point; and according to the forest fire information, determining a forest fire type and whether early warning information is sent. According to the technical scheme provided by the embodiment of the invention, the forest fire can be timely and accurately found, the position of the forest fire can be determined, the cause of the forest fire is speculated, whether the forest fire belongs to natural fire or artificial fire is judged, the type of the forest fire is accurately determined, and the corresponding forest fire early warning information is sent at the first time. Therefore, related personnel can take corresponding fire extinguishing measures, the precision and efficiency of forest fire detection are improved, and the property loss is reduced.

The invention discloses an automatic balancing and attitude adjusting type underwater robot, relates to the field of underwater robot control, and aims to solve the problem that an underwater robot is difficult to give consideration to the functions of automatic buoyancy adjustment, attitude control and rapid floating at present. The device comprises a main machine body, a power unit, a control unit, a detection unit, a buoyancy regulation and control unit and a standby power supply, according to the technical scheme, the buoyancy regulation and control unit is regulated in real time through PID control on the basis of attitude data and depth gauge information, buoyancy autonomous balancing of the underwater robot under different loads is ensured, and the tedious balancing weight adjusting process in traditional manual balancing is avoided. During high-speed movement, the automatic balancing and attitude adjusting system can finely adjust the pitch angle and the roll angle of the underwater robot, stably maintain high-speed operation and cooperate with the propeller system to achieve better dynamic response. In addition, the system further has the function of quickly floating through the standby power supply and the buoyancy regulation and control unit under the out-of-control or power-off condition, and the safety of the robot is guaranteed.

The invention provides an intelligent fishpond oxygenation monitoring system based on the Internet of Things. The intelligent fishpond oxygenation monitoring system based on the Internet of Things comprises a power supply module, an on-site monitoring module, a cloud service module and a user terminal power supply module. According to the intelligent fishpond oxygenation monitoring system based on the Internet of Things, the abnormal response speed is increased, the breeding risk is reduced, the video analysis algorithm unit reduces the manual patrol cost and prevents the property safety risk in time, and the instruction forwarding unit guarantees information circulation of all modules of the system and supports remote control and alarm pushing; the data visualization interface of the user terminal reduces the data understanding threshold and improves the management efficiency, the alarm management unit shortens the abnormal response time and reduces the breeding and property loss, the equipment control unit gives consideration to the intellectualization and manual intervention requirements and improves the management flexibility, and the historical data query unit provides a data basis for breeding scheme optimization and risk pre-judgment. And fine breeding is assisted.

The invention relates to the technical field of shaft construction structures, and discloses a freezing method shaft sinking shaft water intercepting device which comprises an annular device shell, a through opening is formed in the middle of the inner side of the annular device shell, welding columns are evenly distributed on the inner side face of the annular device shell, and lifting rings are installed at the upper ends of the welding columns. A plurality of sets of hydraulic supporting structures are evenly installed in the annular device shell outwards, and a hydraulic oil cylinder is horizontally fixed in the annular device shell. According to the freezing method shaft sinking shaft water intercepting device, an air pump is used for inflating the annular water intercepting air bag through the air guide pipe, so that the annular water intercepting air bag begins to expand after being inflated and becomes an annular ring body, and an expansion telescopic part obviously expands outwards till the annular periphery abuts against the shaft wall; the sealing ring is fully attached to the wall of the shaft to form annular sealing, the sealing effect is good, and when leaking water of the shaft flows downwards along the wall of the shaft, the leaking water is blocked by the annular water intercepting air bag in time.

The invention provides an electric vehicle modal analysis and balance control method, system and device and a storage medium, and the method comprises the steps: solving a characteristic value based on the rigidity and quality of an electric vehicle through employing a finite element method when the inherent frequency of the electric vehicle meets the design index requirements; when the inherent frequency of the electric vehicle does not meet the design index requirement, the characteristic value sensitivity of the electric vehicle is obtained based on a finite element perturbation formula of the characteristic value sensitivity, the inherent frequency of the electric vehicle is adjusted according to the characteristic value sensitivity of the electric vehicle, and a characteristic value is obtained. According to the method, the most sensitive part of the electric vehicle can be directly found out, the inherent frequency of the electric vehicle is greatly improved through small modification, and the balance of the electric vehicle is rapidly achieved; repeated calculation can be avoided, the speed is high, and the method is simple and low in cost; the stability is high, the safety is high, and the application range is wide.