387 results about "Fire hazard" patented technology

The invention, which relates to the technical field of fire safety, discloses a multi-modal intelligent identification method for fire-fighting hidden troubles based on a large model, comprising the following steps: S1, acquiring multi-source heterogeneous feature data through a sensor network deployed in a fire-fighting water pump room to obtain an initial feature set; s2, performing unified scale conversion on the initial feature set, calculating heterogeneous bridging parameters according to the environmental parameters and the equipment operation data, constructing a fusion feature vector, inputting the fusion feature vector into a preset neural network for feature weight adaptive adjustment, and outputting an adjusted weight vector; according to the fire-fighting hidden danger intelligent identification method based on the large-model multi-mode, intelligent closed loop from hidden danger identification to prevention and control decision making is realized, and the intelligent, dynamic and precise management level of a fire-fighting safety system is comprehensively improved.

The invention discloses a community fire risk dynamic assessment method and system based on AI prediction, and belongs to the technical field of fire prevention and control, and the method comprises the steps: S1, collecting and preprocessing multi-source data of a community, and constructing a comprehensive risk factor database; s2, constructing a risk prediction model, taking the preprocessed multi-source data as input, identifying a key risk factor, and outputting a fire risk probability; s3, calculating the dynamic weight of each index by fusing the static expert experience and the real-time risk contribution degree; s4, based on the dynamic weight and the risk probability, calculating a comprehensive risk value and dividing risk levels; s5, constructing a prevention and control strategy library based on the risk level and the key risk factor; according to the community fire risk dynamic assessment method and system based on AI prediction, the change rule of the fire risk factors in the community can be captured in real time, potential fire hazards can be predicted in advance, and a targeted prevention and control strategy can be automatically generated.

The invention discloses a fire early warning cooperative system composed of a thermal imaging double-spectrum intelligent ball, an intelligent analysis platform and a fire extinguishing unmanned aerial vehicle, which is applied to the technical field of fire early warning, and comprises the thermal imaging double-spectrum intelligent ball, an integrated visible light sensor and a thermal imaging sensor, and a double-spectrum fusion monitoring technology is adopted to carry out omnibearing and all-weather monitoring; the intelligent analysis platform simulates a fire spreading path based on a fire spreading prediction model of a fluid dynamics and machine learning algorithm, generates a three-dimensional fire danger thermodynamic diagram, and completes a whole-process response from regional early warning to command center decision making to unmanned aerial vehicle cluster task distribution through a multi-level early warning mechanism; the fire extinguishing unmanned aerial vehicle adopts a multi-model collaborative operation system to meet the fire extinguishing requirements of different fire scenes. According to the invention, in a complex and changeable fire scene, the fire hazard can be quickly and accurately identified, and the efficient disposal of fire extinguishing operation is realized.

The invention relates to the technical field of intelligent safety monitoring, and discloses a fire hazard identification method and system based on a multi-modal large model. According to the method, standardized preprocessing is carried out on field multi-modal data through a unified timestamp system and a quality evaluation mechanism; vision, text and sensor features are extracted and aligned by using a pre-trained deep learning model, adaptive feature fusion is realized by using an attention mechanism of scene perception, hidden danger recognition and confidence evaluation are completed through a hierarchical classification network and an uncertainty quantification method, and structured rectification suggestions are generated based on template matching and multi-target optimization. And progressive model updating of experience playback and collaborative management of RESTful API (Application Program Interface) are supported. According to the invention, the accuracy and efficiency of fire hazard identification can be effectively improved, and intelligent decision support is provided for safety management.

The invention discloses an intelligent fire-fighting hidden danger identification method based on multi-modal fusion, and the method comprises the steps: collecting multi-source heterogeneous data in a building environment, and carrying out the unified processing of the data, and obtaining standardized multi-modal original input data; event anchor point detection is carried out on the multi-modal input, key events are extracted, and a corresponding multi-modal event sequence is generated; constructing an event graph containing time and causal edges, and outputting an alignment event stream by using a space-time coupling causal alignment module; importing BIM and air duct structure information to establish a spatial topological graph, and fusing event streams to generate spatial constraint features; constructing a self-evolution semantic decision map based on the fusion features, and dynamically adjusting node weights and edge connection relationships; and carrying out hidden danger identification and grade division on the real-time data by using the decision map, and outputting an early warning signal and positioning information. According to the method, high-precision identification and intelligent early warning of fire-fighting hidden dangers are realized through space-time causal alignment, spatial topology fusion and self-evolution semantic decision of multi-modal data.

Multispectral imaging and related techniques are provided to detect fire hazards and alerts that are false positive indicators of the fire hazards. The embodiments are directed to systems for identifying pre-fire hazards using thermal images, visual images, and different rules corresponding to temperature configuration levels. The embodiment are also directed to identifying false positive indicators of fire hazards using regions of interest in the thermal and visual images, identifying objects that have hot components which may generate a false positive indicator for a fire hazard, and identifying sun reflections which may generate a false positive indicator for the fire hazard.

The present disclosure relates to a method of fire hazard plant control of a processing plant (100), wherein the processing plant (100) is provided with a transporting arrangement (101) for transporting items to a detection zone (IZ) and a classification arrangement (102) configured to classify items present in said detection zone based on at least one feature of the item and optionally to sort items based on item classification. The method comprises a step of detecting at least one item as a fire hazard (FH). The method comprises a step of initiating, in response to said fire hazard detection, a fire hazard response action. A control unit (103) and a processing plant (100) is also provided.

The invention relates to the technical field of unmanned aerial vehicles, and particularly discloses an unmanned aerial vehicle take-off and landing cabin which is characterized in that cabin doors are symmetrically arranged above a cabin body and connected with the two sides of the cabin body, and the two cabin doors are closed at the top of the cabin body to cover the cabin body; a stop two-dimensional code is arranged on the top and / or the side surface of the cabin door The parking platform is arranged in the cabin body, and a lifting mechanism is arranged at the bottom of the cabin body; a guiding two-dimensional code is arranged in the cabin body, and the express cabinet and the storage room are connected to the lower portion of the cabin body. The management system carries out real-time monitoring and data statistics on the use state, energy supply and unmanned aerial vehicle access records of the take-off and landing cabin. The cabin body is made of a high-strength waterproof material and a sealing structure and is matched with a cabin door closing design, so that severe environments such as wind, rain and dust can be effectively resisted, and the unmanned aerial vehicle is prevented from being interfered by the environment in the taking-off, landing and parking processes; smoke, temperature and vibration sensors are integrated, fire hazards, temperature abnormity and illegal invasion are detected in real time, alarm and emergency measures are automatically triggered when abnormity occurs, and the safety of equipment and the unmanned aerial vehicle is guaranteed.

The invention relates to a cable tunnel bridge fire prediction method and device, electronic equipment and a storage medium. The cable tunnel bridge fire hazard prediction method comprises the following steps: establishing a cable tunnel bridge fire hazard numerical simulation model, establishing a cable tunnel bridge fire hazard simulation model based on FDS software, obtaining key parameters such as heat release rate, temperature distribution and flame spread boundary under different working conditions, and constructing a multi-time sequence sample data set; performing state discretization on continuous variables such as temperature and a spreading range, and estimating a node prior probability in combination with a statistical frequency; constructing a dynamic Bayesian network topological structure according to a causal relationship among a heat source, temperature and spread, and setting a cross-time slice node dependence path to realize time sequence modeling; inputting a training sample and performing parameter learning to generate a conditional probability table; in the prediction stage, multi-step reasoning is achieved through forward propagation, flame spreading range probability distribution and interval estimation of multiple time steps in the future are obtained, and the specific position where the flame arrives is predicted.

The invention relates to the technical field of electrical fire intelligent early warning, in particular to an electrical fire intelligent early warning and handling method based on multi-source data fusion, which comprises a data acquisition system, and the output end of the data acquisition system is connected with a multi-source data fusion platform. The output end of the multi-source data fusion platform is provided with an intelligent analysis and early warning system, the output end of the intelligent analysis and early warning system is provided with a disposal decision system, the output end of the disposal decision system is provided with a feedback optimization system, and the multi-source data fusion platform, the intelligent analysis and early warning system, the disposal decision system and the feedback optimization system are integrated. The processing decision-making system and the feedback optimization system are both in communication connection with the data acquisition system. According to the invention, through the data acquisition-fusion analysis-intelligent early warning-decision processing-feedback optimization closed-loop system, the whole-process intelligent management of electrical fire prevention and control is realized, the cooperation work of each component breaks through the limitation of single parameter monitoring, and the three-dimensional acquisition of video data provides multi-dimensional data support for fire hazard identification.

The invention discloses a phosphorus-nitrogen synergistic flame-retardant benzoxazine / epoxy resin composite material and a preparation method thereof. Firstly, a phenolic compound and DOPO react to generate an intermediate product, and then the intermediate product, an amine compound and paraformaldehyde are subjected to a dehydration condensation reaction to generate the phosphorus-nitrogen synergistic flame retardant benzoxazine. The phosphorus-nitrogen synergistic flame-retardant benzoxazine is added into epoxy resin for thermocuring to obtain the composite material. The prepared benzoxazine flame retardant contains phosphorus and nitrogen elements, the nitrogen-based flame retardant has the advantages of low pollution, low smoke, good compatibility with EP and the like, and a quenching effect, a dilution effect and a carbon layer barrier effect can be generated in the combustion process to prevent further combustion of flames. The composite material has better flame retardant property, can effectively reduce the risk of fire hazard caused by overheating or short circuit of equipment, and ensures the safe and stable operation of energy equipment.

The invention discloses a fire alarm inspection system and method based on big data, and relates to the technical field of intelligent fire protection and public safety. The problems that a traditional fire fighting system is serious in data island phenomenon, single in risk perception dimension, static and rigid in early warning model, high in false alarm rate and low in inspection efficiency are solved. According to the method, a fire-fighting theme database is constructed, and based on a multi-dimensional dynamic analysis model, comprehensive analysis of space aggregation risks, time sequence evolution trends and equipment linkage logic is realized, and dynamic fire danger hidden danger indexes are calculated; a key monitoring object is positioned through a visual thermodynamic diagram, grading alarm is triggered, differentiated inspection tasks and an optimal route are generated based on the intelligence, and emergency disposal linkage is supported; closed-loop management from global risk perception, intelligent analysis and early warning to precise inspection treatment is realized, and early recognition and early warning accuracy and resource scheduling efficiency of fire hazards are remarkably improved.

The invention discloses an intelligent control system and method for an active fire extinguishing device of a high-voltage switch cabinet, and the system comprises the steps: collecting multi-source heterogeneous environmental parameters in the cabinet, carrying out the LoRa wireless transmission, introducing a dynamic thermal drift compensation mechanism based on an Arrhenius model, and carrying out the zero drift correction and sensitivity dual compensation of the original data of a sensor. A high-fidelity physical monitoring value is reconstructed through high-order polynomial nonlinear mapping, and the risk of false alarm and missing alarm caused by thermal-sensitive coupling is eliminated. After a fire hazard is recognized, the block type fire extinguishing device is excited in a linkage mode, inert gas and free radical groups are instantaneously released through an oxidation-reduction reaction to conduct total flooding type suppression, negative feedback adjustment and automatic termination of the reaction rate are achieved according to the environment temperature change, and therefore accurate early warning is ensured, and meanwhile the safety of the fire hazard is improved. Efficient blocking and reset safety protection of live-line fire disasters are realized.

The invention provides a multi-mode linkage control and remote state monitoring system for fire-fighting equipment. The multi-mode linkage control and remote state monitoring system is characterized in that multi-mode data of the fire-fighting equipment is acquired in real time through a sensor array; building a building digital twin model based on the three-dimensional point cloud data and a BIM model, training in combination with a generative adversarial network GANs, performing analog simulation on the fire development trend, and performing grade division and risk assessment on the fire; formulating a dynamic linkage rule of the fire-fighting equipment, and respectively controlling linkage of different fire-fighting equipment according to different risk degrees of the fire and states of the fire-fighting equipment; optimizing the linkage rule of the fire fighting equipment based on a reinforcement learning algorithm; the state of the fire-fighting equipment is remotely monitored in real time, and timely processing is performed if the state is judged to be abnormal. The fire hazard identification accuracy is improved through multi-modal data linkage, the processing efficiency is improved based on digital twin dynamic mapping, the linkage rule is intelligently adjusted according to the fire hazard and the equipment state, and multi-modal linkage control and remote state monitoring of the fire-fighting equipment are realized.

The invention relates to the technical field of fire monitoring, in particular to a fire hidden danger recognition method and system based on image enhancement. Comprising the steps that thermal images are synchronously collected through an infrared thermal imager array arranged at the top of the inner side wall of a silo, a panoramic thermal image sequence is formed through registration and splicing, enhancement processing is carried out, and candidate hot spot areas are extracted accordingly; the space-time dynamic evolution characteristics of the hot spot area are obtained through cross-frame tracking, the space-time dynamic evolution characteristics and the spatial form characteristics are subjected to weighted fusion to obtain a comprehensive confidence coefficient score, and finally the smoldering hidden danger is judged in combination with smoldering physical diffusion model verification. According to the method, by fusing the dynamic evolution characteristics of the hot spot region and physical model verification, early-stage and accurate recognition of the smoldering hidden danger in the silo is achieved, and the problems that a traditional static temperature threshold value monitoring method is high in false alarm rate and lags in early warning are effectively solved.

The invention provides a high-orbit satellite and low-orbit satellite cooperative fire hazard monitoring method and system. Belongs to the technical field of space remote sensing and space situation awareness. The problems of response lag and resource waste exist in the prior art. According to the method provided by the invention, a low-orbit fine observation task scheduling model driven by high-orbit macroscopic early warning is adopted, the response speed to ground emergencies is improved, intelligent distribution of remote sensing resources is realized, the data utilization efficiency and monitoring precision are improved, and a space-based dynamic situation awareness system is constructed.

The utility model discloses a data center high-speed airflow environment air-breathing type smoke-sensing fire hazard detector, which relates to the field of smoke-sensing fire hazard detectors and comprises a sampling unit module, a detector module, an airflow adjusting module and a fire extinguishing linkage module. The data acquisition unit is electrically connected with the data processor through a wire, the data acquisition unit and the data processor are electrically connected with the central controller through a wire, and antistatic PVC (polyvinyl chloride) pipelines are adopted, are arranged at the top of the cabinet and under the raised floor and are provided with a plurality of sampling holes; according to the utility model, the performance index of the air-breathing smoke-sensing fire detector in a high-speed airflow environment of a data center is comprehensively improved by optimizing a detection technology, airflow control and an intelligent algorithm, micron-sized particles are captured through the high-efficiency particle air filter, and the concentration is detected through the scattering effect of smoke particles on an LED (Light Emitting Diode).

The invention relates to the technical field of photovoltaic safety monitoring, and discloses a photovoltaic power station fire hazard monitoring system based on computer vision. The system comprises an image acquisition unit, a visual feature extraction unit, a feature fusion unit, a hidden danger weight distribution unit and a hidden danger tracing unit. The image acquisition unit acquires real-time visible light image data and infrared thermal imaging data; a visual feature extraction unit extracts a visual space feature vector and a heat distribution feature vector; the feature fusion unit performs multi-modal fusion on the two types of vectors to generate a fusion monitoring feature set; the hidden danger weight distribution unit calculates a hidden danger association degree score set through a pre-trained convolutional neural network model, wherein the set comprises association strength of abnormal heat distribution and visual abnormality of different regions; and the hidden danger tracing unit generates a fire hidden danger positioning result based on association intensity distribution joint positioning. The system can comprehensively capture the state of the photovoltaic power station, improves the accuracy and comprehensiveness of fire hazard monitoring, and assists the safe operation of the photovoltaic power station.

The invention discloses a textile setting machine flue gas waste heat recovery adaptive control system and method, and the method comprises the steps: firstly carrying out the global state estimation of multi-mode sensor data through a graph neural network, so as to precisely sense the hidden states, such as the scaling distribution, in a heat exchanger, and then introducing a causal inference technology to carry out the active risk assessment, a dynamic safety control constraint is generated by analyzing causal association between variables, so that traditional passive threshold alarm is replaced. In the safety boundary, the system utilizes multi-target reinforcement learning to formulate a macroscopic operation strategy giving consideration to both energy efficiency and process stability, and realizes accurate trajectory tracking and execution of a set point in combination with model prediction control. In this way, deep perception and active risk defense of complex flue gas working conditions can be achieved, the waste heat recovery energy efficiency is maximized on the premise that the intrinsic safety of the system is guaranteed, and the operation and maintenance cost and fire hazards are remarkably reduced.

The invention discloses a pyrolytic particle detection device, which relates to the technical field of fire detection and comprises an air pump, a heating cavity, a conducting electromagnetic valve, a refrigeration cavity, a laser detection cavity, an exhaust electromagnetic valve, a weak photoelectric pulse signal processing unit, a comprehensive control and data processing unit and an RS485 communication unit. The sucking pump, the heating cavity, the conduction electromagnetic valve, the refrigeration cavity, the laser detection cavity and the exhaust electromagnetic valve are sequentially connected through 8 mm silica gel air pipes to form a complete air path system; the invention provides a pyrolytic particle detection device which can accurately detect pyrolytic particles in air in real time, can digitally display the content of the detected pyrolytic particles, can avoid interference of environmental factors such as dust, water mist, strong light and electromagnetism, and provides an effective detection device for extremely early warning of a fire hazard. And sufficient favorable time for several hours is provided to control combustion conditions, so that event expansion is avoided.

The invention discloses a building electrical fire hazard intelligent monitoring system and a monitoring method thereof. The system comprises an infrared thermal imaging module, a current harmonic analysis module, an edge computing node, a self-healing protection module and a user interaction terminal. The infrared thermal imaging module collects temperature field data and dynamically adjusts an alarm threshold value. The current harmonic analysis module collects harmonic characteristic data and identifies load abnormity. The edge computing node fuses the multi-dimensional data based on a random forest algorithm to generate a risk level and a fault type; the self-healing protection module adopts a three-stage tripping strategy to realize graded protection, and improves the handling capacity through closed-loop verification and fire-fighting linkage; and the user interaction terminal realizes fault information visualization. Through multi-dimensional data perception, intelligent analysis and hierarchical active protection strategies, a whole-process closed-loop management system from hidden danger detection, risk assessment to self-healing treatment is constructed, and the problems of high false alarm rate, response lag and management fragmentation in the prior art are solved.

This invention provides a circuit emergency protection device for high-voltage switchgear, belonging to the technical field of circuit emergency protection equipment. The device includes a switchgear body, an internal mounting frame, a leakage current protection mechanism mounted on the top of the mounting frame, an inspection light mounted on the top of the switchgear body, a temperature sensor mounted inside the switchgear body, a cooling mechanism mounted at the bottom of the switchgear body, a ventilation mechanism mounted on the top of the switchgear body, and a leakage current protector mounted on the top of the mounting frame. The leakage current protector contains a magnetic ring, with a copper wire sleeved on its outer wall. A connecting wire is attached to the top of the copper wire, and the top of the connecting wire is connected to a circuit board. This invention can quickly detect abnormal current and cut off the power supply, providing more direct protection for operators. By monitoring leakage current, it can cut off the power supply before a fire hazard occurs, significantly reducing the risk.

The application discloses a comprehensive linkage alarm system for fire hazards and structure instability of timber buildings, and relates to the technical field of timber safety monitoring, which comprises the following modules: a multi-dimensional heterogeneous signal acquisition module for collecting data and constructing real-time state monitoring data sets; a structure spectrum benchmark modeling module for constructing a thermal-rigidity attenuation theoretical model; a thermal-frequency correlation analysis module for generating a thermal-frequency deviation degree index; a structure state determination module for identifying timber pyrolysis states and structure instability risks; a cascade response module for executing corresponding fixed-point spraying control, evacuation path planning and alarm output; and a self-adaptive feedback correction module for warehousing data and correcting thermal aging parameters. The application establishes a correlation model of thermal and rigidity by fusing thermal imaging and vibration data, effectively eliminates environmental wind load noise, realizes accurate identification of internal hazards of timber buildings, and improves the accuracy of building monitoring and the efficiency of emergency response.

This application relates to the field of conveyor belt fire technology, and provides a method and system for assessing the fire hazard of conveyor belts based on surface elemental analysis. In this method, the degradation degree index of the target conveyor belt is calculated by analyzing the changes in the content of surface constituent elements over wear time. Once the degradation degree index passes reliability verification, a constructed degradation-combustion prediction model is used to calculate the fire risk index of the target conveyor belt over wear time. This avoids interference from environmental factors such as underground dust and humidity in traditional assessment methods, enabling full life-cycle assessment and diagnosis of conveyor belts under different wear states before a fire occurs, overcoming the lag in traditional early warning methods.

The invention belongs to the technical field of wind power plant fire assessment, and discloses a multi-modal fusion wind power plant fire hazard multi-source data space-time synchronous assessment method and system, and the method is characterized in that a reference calibration module builds a digital twin simulation, double closed-loop dynamic calibration and credibility quantification three-in-one mechanism; the time synchronization adopts a triple strategy of GPS time service, local clock compensation and transmission delay prediction, and the transmission delay is compensated in advance in combination with an LSTM network; the space calibration depends on a three-dimensional digital twin model of the fan, and mounting deviation and vibration drift are corrected through visual identification and coordinate matching; the quality grading module is used for constructing a three-dimensional quality model, distributing weights according to data quality grading, and reducing evaluation deviation caused by data heterogeneity; the feature fusion module adopts a spatial-temporal feature, modal feature and quality weight cross fusion mechanism; and capturing data time sequence association through an overlapped time window, and mining spatial association in combination with a digital twin spatial topological relation.

The invention relates to the technical field of refrigerating systems, and discloses a single-machine double-system type hot fluorine defrosting refrigerating system which comprises a main machine refrigerating system, an auxiliary machine refrigerating system and two gas-liquid separators, the main machine refrigerating system comprises a first-stage compressor, a first-stage condenser, a first-stage expansion valve and a first-stage evaporator, and the auxiliary machine refrigerating system comprises a second-stage compressor, a second-stage condenser, a second-stage expansion valve and a second-stage evaporator; the auxiliary machine refrigeration system comprises a second-stage compressor, a second-stage condenser, a second-stage expansion valve, a second-stage evaporator, a third-stage condenser, a third-stage expansion valve and a third-stage evaporator. According to the technical scheme, the double refrigeration circulation paths are introduced into the refrigeration system, during refrigeration, the main machine refrigeration system is responsible for refrigeration, the auxiliary machine refrigeration system supplies liquid to the main machine refrigeration system for undercooling, the heat load is relieved, and the unit refrigeration capacity is improved; in the defrosting process, the auxiliary machine refrigeration system is adopted for generating high-temperature and high-pressure hot fluorine for defrosting, the energy consumption of hot defrosting is reduced, fire hazards caused by aging of electric heating elements are avoided, and the safety coefficient of system operation is improved.

The present invention relates to a fire suppression composition and system designed to extinguish challenging fires, such as Class B fires involving lithium batteries as well as Class A, B, and D fire scenarios. The composition includes a mineral component, a water-based liquid propellant, and a synergistic blend of additives. This innovative combination enables the composition to float on liquid surfaces and adhere to burning materials, effectively suppressing and extinguishing fires. The composition's ability to form a barrier on burning materials prevents fire spread and re-ignition, making it highly effective for both vehicle fires and industrial settings. This advancement offers a versatile and robust solution to modern fire hazards, suitable for use in various delivery systems.

This utility model relates to the field of medical device technology, and more specifically, to a device for treating moxa stick ash, comprising: a clamping member, a first scraper and a second scraper respectively connected to two clamping ends of the clamping member, and a side plate connected to the first scraper or the second scraper. The first scraper and the second scraper are respectively provided with a first abutting surface and a second abutting surface. The clamping member drives the first scraper and the second scraper to approach and abut against each other or move away from each other. When the first scraper and the second scraper abut against each other, the first abutting surface and the second abutting surface fit together, and the first scraper, the second scraper, and the side plate form a sealed cavity. The clamping member drives the first scraper and the second scraper to clamp relative to each other, thereby clamping them onto an external fixing post for fixing the moxa stick. When scraping the moxa stick ash, the first scraper, the second scraper, and the side plate all block the moxa stick ash, preventing it from falling everywhere, eliminating fire hazards, and preventing medical personnel from being burned by the moxa stick ash, making the operation safer.

The utility model discloses an electric roller. The electric roller comprises a roller body, a cable connecting end located on the roller body and a first connecting assembly, wherein the first connecting assembly is used for installing the electric roller on a rack; the connecting assembly comprises a first installation shaft and a conductive installation sleeve which is arranged on the first installation shaft in a sleeving mode so as to limit the installation position of the electric roller. A cavity for a cable to penetrate through is formed in the first mounting shaft, and the end, connected with the rack, of the first mounting shaft is of a prism structure. The first mounting shaft of the prism-shaped structure enables the contact area between the surface of the first mounting shaft and the rack to be increased, stress concentration is reduced, the connection strength of the mounting assembly is improved, and the stability of connection between the first mounting shaft and the rack is guaranteed; a certain distance can be kept between the rack and the roller body through the conductive mounting sleeve on the first mounting shaft, and the conductive mounting sleeve has certain conductive performance, so that static electricity is prevented from being generated in the transportation process, the static electricity generated in the transportation process is prevented from damaging the electric roller and transported goods, and fire hazards are prevented; after the installation assembly is assembled, the safety performance of the whole transportation process is improved.

The invention discloses electrical automatic measurement and control analysis equipment which comprises a shell, a supporting shell is fixedly connected to the interior of the shell, a motor is fixedly connected to the supporting shell, the output end of the motor is fixedly connected with a fourth bevel gear, and the fourth bevel gear is in meshed connection with a third bevel gear. The risk that external humid air intrudes into the equipment in the box opening and replacing process is avoided, the sealing performance of the equipment operation environment is guaranteed, element aging and overheating fire hazards caused by heating and dehumidification can be avoided through the pure physical moisture absorption characteristic of the moisture-proof plate, and the service life of the equipment is prolonged. The problems of condensate water leakage short circuit and easy failure depending on electric drive in semiconductor condensation dehumidification are solved, the moisture-proof stability and the service life of equipment are improved, multiple moisture-proof plates are stored through modular design, automatic replacement is achieved through mechanical structure linkage, the failure moisture-proof plates can be recycled and regenerated after being collected in a centralized mode, and the energy-saving and environment-friendly effects are achieved. And the operation and maintenance difficulty and the consumable cost are greatly reduced.