5379 results about "Moisture sensor" patented technology

The invention relates to a power supply switching control optimization method and system, and the method comprises the steps: constructing a multi-dimensional data fusion monitoring system, integrating a real-time voltage ripple coefficient detection module of a main power supply, a load transient response analysis module and an environment temperature and humidity sensor array, and generating a dynamic health degree index; the method comprises the following steps: establishing a fault prediction model based on transfer learning, pre-training through multi-scene failure data in a historical database, receiving a health degree index in real time, outputting a reliability attenuation curve, and activating a dual verification mechanism when the slope of the attenuation curve exceeds a preset threshold; extracting characteristic energy distribution of a frequency band of 0.1-10 kHz; executing a transient load impact test, and measuring dynamic response parameters of voltage recovery time and overshoot amplitude; and generating a switching confidence score based on cross processing of the dual verification result and the attenuation curve, and triggering a hierarchical switching instruction. The accuracy of the switching time of the main power supply and the standby power supply can be improved.

The invention relates to the technical field of bridge structure safety monitoring and maintenance, and discloses a road bridge real-time monitoring and maintenance system based on intelligent perception, which comprises a data acquisition module used for acquiring multi-dimensional data of a bridge operation state through a deployed multi-source sensor, the multi-source sensor comprises a vibration sensor, a strain sensor, a temperature and humidity sensor and image acquisition equipment; the data preprocessing module is used for carrying out cleaning, synchronization and feature extraction on the collected multi-dimensional data to obtain dynamic features, environment features and visual features; and a data fusion module. According to the method, the comprehensiveness and accuracy of bridge monitoring are improved through multi-source data fusion, the reliability of an evaluation result is ensured in combination with physical constraint optimization, health trend prediction and early warning functions are realized based on a time sequence model, scientific decision support is provided for bridge maintenance, and the monitoring and management efficiency is improved.

The invention relates to the technical field of air conditioner energy-saving operation control, and discloses a central air conditioner energy-saving operation control method and system. The method comprises the following steps: acquiring and processing data through a temperature and humidity sensor to obtain a temperature and humidity distribution index; calculating load values according to the indexes and the personnel density to form a distribution diagram; regulating and controlling cold and heat source equipment according to the distribution map to obtain operation parameters; adjusting the water pump fan based on the parameters to form balance data; adjusting the end equipment according to the data to generate a control instruction; and the system state is adjusted in real time according to instructions and comfort feedback to realize energy-saving operation. The problem of energy waste caused by decentralized control of subsystems of a traditional central air conditioning system is solved. By constructing a complete closed-loop control system from environmental perception, load prediction to equipment regulation and control, the operation efficiency of the system under partial load conditions is improved. And meanwhile, refined control is achieved according to different requirements of different areas, and energy consumption is reduced to the maximum extent on the premise that the comfort level of the user is guaranteed.

The invention discloses an intelligent control method and system for tunnel loudspeakers, and relates to the technical field of tunnel audio control, environmental parameters in a tunnel are collected by adopting a mode of deploying sampling equipment in a distributed manner, and data preprocessing is performed in a targeted manner for different environmental parameters; a sound propagation model is established, and attenuation and delay of sound in different environments are simulated. According to the intelligent control method and system for the tunnel loudspeakers, various temperature and humidity sensors are arranged in the tunnel, and the absolute humidity is calculated in combination with the air pressure data, so that the sound velocity is accurately corrected, and the phase difference of the multiple loudspeakers is reduced; an adaptive Kalman filtering algorithm is adopted to process wind speed data, and reliable input is provided for a sound propagation model; a deep reinforcement learning algorithm is used to carry out collaborative optimization on parameters such as amplitudes and directional angles of multiple loudspeakers, a Bayesian network is used to detect loudspeaker faults, and Delaunay triangulation and a distributed consistency algorithm are combined to realize rapid fault reconstruction.

The invention relates to the technical field of environment regulation, in particular to a corn cultivation environment intelligent regulation method based on multi-sensor control, which comprises the following steps: S1, generating a soil moisture three-dimensional distribution diagram in real time through humidity sensor arrays arranged at different depths of a corn root zone; s2, combining infrared temperature data of the canopy and the three-dimensional distribution diagram of the soil moisture, and calculating a moisture motion mismatch degree through transpiration-permeation conduction collaborative analysis; s3, generating a user-defined irrigation mode based on the water movement mismatch degree, and controlling the irrigation duration, the stop interval and the water flow rate. According to the method, coupling modeling is carried out on the plant physiological water demand behavior and the soil moisture supply characteristic, the limitation that a traditional irrigation system only depends on a soil humidity threshold value or meteorological index judgment is broken through, and the biological adaptability and the aging responsiveness of field moisture regulation and control are improved.

The invention relates to the technical field of control and regulation systems, in particular to a photovoltaic module anomaly recognition method based on laser detection, which comprises the following steps: generating a clock signal synchronous with a laser scanning time sequence through a hardware synchronous trigger, and driving a temperature and humidity sensor, a salt mist sensor and an illumination intensity sensor to collect environmental parameters; and constructing a multi-source data set containing the salt crystallization trend and the environmental interference level. And based on a temperature and humidity segmented compensation reflectivity base line, a salt mist mode switching optimization dust retention judgment threshold value, and illumination correlation sensitivity adjustment hot spot detection parameters, dynamic model correction is realized. And a fault database is matched to trigger a grading alarm mechanism, and a decision tree classifier is combined to verify time continuity to generate a diagnosis report. A dynamic detection path is constructed through spiral path planning, a multi-machine contract network protocol and wind disturbance trajectory correction, data feedback is executed to form closed-loop control logic, and the problems of misjudgment and missing detection in high salt mist, temperature change and illumination fluctuation environments are effectively solved.

A piled granular material management robot comprises an auger-based drive system, a memory, a moisture sensor, and a processor coupled with the memory and with the moisture sensor. The processor is configured to control movement of the robot via augers of the auger-based drive system. The processor is also configured to direct a traversal, by the robot, of a portion of a surface of piled granular material in a bulk store. The processor is also configured to capture, via the moisture sensor, a moisture measurement of the portion of the piled granular material during the traversal of the portion of the piled granular material by the robot.

The invention discloses an agricultural irrigation area water resource intelligent management system and method, and relates to the field of intelligent management, and the method comprises the steps: building a correlation model of a crop growth stage and a basic irrigation threshold value through real-time collection of original weather station data, future 24-hour weather forecast, crop types, planting dates and other multi-dimensional data; and in combination with soil humidity sensor data and a channel pump station state, the basic irrigation starting threshold is dynamically adjusted by using an FAO formula or a deep learning algorithm to form a dynamic irrigation decision threshold. And then multi-source data is input into an irrigation decision module, an irrigation starting and stopping instruction is generated by judging the relation between the irrigation state and the soil humidity threshold value, and closed-loop management is achieved. Thus, the limitation of traditional irrigation static threshold management is broken through, and through meteorological data dynamic adaptation and multi-source data fusion decision making, on the premise of guaranteeing crop growth water demand, the water resource allocation efficiency is optimized, and the intelligent management level of an agricultural irrigation area is improved.

The invention relates to the technical field of cables, and particularly discloses a cable terminal simulation and state evaluation method and system in a humid environment, multiple types of sensor arrays are deployed, distributed temperature and humidity sensors are installed at key parts of a cable terminal, and aiming at the technical problems of one-sided single-dimensional monitoring, simulation model solidification and insufficient static weight adaptation, the cable terminal simulation and state evaluation method and system are provided. Cooperative acquisition of multiple parameters such as temperature and humidity, partial discharge and corrosion current is achieved through deployment of multiple types of sensor arrays, the nonlinear interaction relation between humidity permeation and electric field distortion is dynamically reflected in combination with a multi-physics field coupling simulation model, the one-sidedness of single parameter monitoring is solved, and the risk misjudgment rate is reduced by 40% or above; a dynamic water film thickness model is adopted to update interface parameters of the sealing ring in real time, a simulation result is updated per hour in combination with a finite element-boundary element hybrid algorithm, an electric field distortion simulation error is controlled within 12%, and the simulation precision is improved by more than one time compared with a fixed boundary condition.

The invention discloses a base station air conditioner energy consumption management energy storage method and system, and the method comprises the steps: collecting multi-source data in real time according to the load data of a temperature sensor, a humidity sensor, an air conditioner operation state monitoring device and a communication device in a base station room, and generating a multi-source fusion data set; for the multi-source fusion data set, dynamic refrigeration requirements in a future time window are predicted, and a dynamic optimization model of air conditioner energy consumption is constructed through an energy consumption efficiency curve; according to the prediction result of the dynamic refrigeration demand and the energy consumption optimization model, the operation mode, the wind speed and the temperature set value of the air conditioner are dynamically adjusted, the energy storage scheduling strategy is optimized, and a combined optimization scheme of air conditioner operation and energy storage scheduling is generated; and monitoring the operation state of the air conditioner in real time, dynamically adjusting the joint optimization scheme, and generating a final base station air conditioner energy consumption management scheme. By utilizing the embodiment of the invention, the energy consumption management of the air conditioner has real-time performance and accuracy, and more efficient energy consumption control and energy storage scheduling optimization can be realized.

The invention provides a three-dimensional simulation and infection scene decision optimization system and method based on digital twinning, and relates to the technical field of intelligent medical treatment and digital twinning crossing technologies. The three-dimensional simulation and infection scene decision optimization system and method based on digital twinborn comprises the following modules: a data acquisition module, a path optimization module, a risk analysis module, a disinfection scheduling module and a collaborative prevention and control module, by arranging an air microorganism sampler, ultra-wideband positioning equipment and a temperature and humidity sensor, pathogen concentration, personnel trajectory and environmental parameters are collected in real time. Through a multi-source sensor fusion algorithm and a space-time attention mechanism, weight fusion and noise filtering are carried out on pathogen concentration, personnel tracks and environmental parameters in a hospital environment, the problems of information isolation and noise interference in traditional data collection are solved, and the space-time relevance of multi-modal data is remarkably enhanced.

The invention relates to the technical field of agricultural product distribution, and discloses an agricultural product distribution system based on the Internet of Things, and the system comprises an Internet of Things sensing layer which is provided with various sensors, including but not limited to a temperature sensor, a humidity sensor, an infrared sensor and an RFID tag; the data transmission layer is used for transmitting the data acquired by the sensing layer to a cloud server in real time by utilizing a 4G / 5G and Wi-Fi wireless communication technology; and the cloud computing and big data processing layer adopts a high-performance cloud computing platform and integrates a big data analysis engine. According to the invention, the accuracy and real-time performance of original data are ensured by optimizing the sensor configuration and the data acquisition frequency of the Internet of Things sensing layer and adopting an advanced wireless communication technology, so that the accuracy of agricultural product quality prediction, freshness evaluation and transportation path optimization is remarkably improved; mass data can be processed and analyzed by means of a high-performance platform of cloud computing and a big data processing layer.

The invention discloses a temperature and humidity adaptive control system and method for drying flower traditional Chinese medicinal materials, and the system comprises a humidity gradient monitoring module which is used for deploying a 12-channel capacitive humidity sensor spiral array and a laser radar, generating a three-dimensional humidity field thermodynamic diagram in combination with a Kriging interpolation method, calculating a humidity gradient change rate in real time, and carrying out the early warning of local abnormality; the heat-humidity ratio regulation and control module is used for integrating humidity gradient monitoring data and a real-time result of the evaporation latent heat calculation module based on a fuzzy PID algorithm, dynamically adjusting the heating power and the rotating speed of a dehumidification fan, and meanwhile, integrating a PVDF piezoelectric film sensor to monitor petal stress; the evaporation latent heat calculation module is used for predicting a future evaporation rate by combining an LSTM neural network based on an edge calculation unit and providing key parameters for the energy supply matching module; the energy supply matching module is used for outputting a combined control instruction of the heating power and the air door opening degree; and the air volume balance optimization module is used for dynamically adjusting air volume distribution according to the humidity gradient monitoring data.

The invention discloses a simple evaluation method and device for the insulation state of an electric cabinet based on cooperative detection of three sensors, and the method comprises the steps: employing a digital temperature sensor, a capacitive humidity sensor and a leakage current sensor to synchronously collect the temperature, humidity and leakage current parameters in the electric cabinet, and calculating a condensation risk index, a surface dirt coefficient and an insulation deterioration degree through a processor; an insulation diagnosis conclusion is obtained in combination with the three-dimensional judgment matrix, the state of the sensor is judged through a self-checking mechanism of temperature-humidity consistency checking and leakage current reference checking, and the upper computer displays the result and generates a report. According to the scheme, reliable insulation detection and early warning are achieved through a low-cost sensor, and the method is suitable for the marine high-humidity variable-temperature environment.

The invention relates to a lithium battery charging system, and relates to the technical field of battery charging, the lithium battery charging system comprises a charging module, a detection module and a data processing module, and also comprises a battery health assessment module used for collecting battery cycle index, internal resistance and capacity attenuation parameters, and constructing a battery health state assessment model; the power grid interaction module is used for acquiring real-time electricity price data and a power grid load state; the environment sensing module comprises an environment temperature and humidity sensor and is used for collecting environment temperature and humidity parameters; and the AI prediction module is constructed based on a deep learning network and is used for predicting a battery state change trend. According to the invention, the battery health evaluation module is arranged to collect parameters such as cycle index, internal resistance and capacity fading rate to construct the SOH evaluation model, the problem of single dimension of battery health state evaluation in the prior art is solved, the aging degree of the battery can be accurately identified, and the risk of overcharge and undercharge of the aged battery due to improper power adaptation is avoided.

The invention relates to the technical field of safety management, in particular to a mine safety production risk prevention and control method based on multi-source data fusion, and the method comprises the following steps: constructing a coupling parameter set through a micro-seismic sensor and a temperature and humidity sensor, detecting and extracting displacement points through Bayesian regression, and drawing a deformation diagram; determining a displacement area, counting an airflow velocity gradient, extracting a main fracture direction, generating an airflow path diagram, calculating a curvature change rate, positioning a sudden change area, extracting a thermal strain rate and an axial strain rate, generating a smooth curve, identifying a risk point, and expanding a boundary when the overlapping rate exceeds 60%, and redrawing a mine thermal-mechanical coupling risk map. According to the method, a multi-parameter analysis framework is constructed through micro-seismic and temperature and humidity data coupling to extract a deformation active band, difference statistics airflow velocity gradient is combined with a crack direction to correct an airflow path, a sudden change area is positioned based on a curvature change rate mean threshold, and thermal strain and axial strain are extracted to screen risk points. And constructing thermal variable amplitude mapping to represent the rock mass instability risk.

The invention discloses an intelligent dehumidification and heat dissipation type high-low voltage switch cabinet, and belongs to the technical field of switch cabinets, the intelligent dehumidification and heat dissipation type high-low voltage switch cabinet comprises a cabinet body, a sealing strip is fixedly installed on the front side of the cabinet body, a sealing cabinet door is hinged to the front side of the cabinet body, and a temperature sensor, a humidity sensor, a controller and a control assembly are arranged in the cabinet body; a ventilation assembly, a condensation mechanism, a water collection mechanism and a heat exchange mechanism are sequentially arranged on one side of the cabinet body from top to bottom, and a ventilation assembly is arranged at the bottom of the other side of the cabinet body. Forced ventilation can be achieved through the arranged ventilation mechanism, the ventilation speed can be adjusted according to the temperature, the flow direction of air in the switch cabinet can be changed according to needs, uniform and controllable heat dissipation is achieved, heat dissipation is achieved while dehumidification is achieved through the arranged condensation mechanism, heat dissipation work is further conducted through condensate water, and the dehumidification and heat dissipation effect is improved.

According to the intelligent imaging generation system and method, parameters of a spraying mechanical arm and imaging equipment are adjusted in a linkage mode in real time through a dynamic parameter adjusting module, and closed-loop control over the spraying quality is achieved in combination with a defect prediction and optimization decision module and a multi-modal process knowledge base. A high-resolution visual sensor, a capacitive thickness detector and a temperature and humidity sensor are integrated in the system, multi-source data are fused through a Kalman filtering algorithm, and the mechanical arm speed, the nozzle pressure and the imaging gain coefficient are dynamically adjusted. The defect prediction module simulates a coating defect form based on a physical constraint generative adversarial network and generates a process optimization instruction set through reinforcement learning. The multi-modal process knowledge base stores a correlation model of material characteristics, environmental data and defect modes, and supports incremental learning and historical data attenuation updating. And through dynamic parameter collaborative optimization, defect prediction preposition and multi-modal data fusion, the spraying quality detection efficiency and the coating consistency are improved, and the rework rate is reduced.

The invention relates to the technical field of drying equipment, in particular to a low-consumption constant-temperature dehumidification device and a control method, and achieves an efficient and energy-saving constant-temperature dehumidification effect. The heat recovery module recovers heat in the condensation and regeneration process, the collaborative optimization module coordinates operation of all the modules, the energy utilization efficiency is remarkably improved, and energy consumption is reduced. The control system module dynamically adjusts the state of each module according to the real-time data of the temperature and humidity sensor, ensures the stability of the environment temperature and humidity, and further improves the control precision by adopting a dynamic decoupling control strategy. The regeneration module utilizes recovered heat energy to efficiently regenerate adsorbents and cooperates with novel composite adsorbents, the service life of the adsorbents is prolonged, and the dehumidification performance is improved. The air circulation module forms uniform airflow, and local temperature and humidity unevenness is avoided. A user can set parameters through the interaction unit, the system is controlled to automatically adjust the operation strategy, intelligent operation is achieved, and the system performance is optimized.

The invention relates to a construction early warning system and method for a subsurface tunnel. The system comprises a data sensing unit and an intelligent analysis unit, and the data sensing unit comprises a first monitoring part which is arranged at each monitoring point of a monitoring section along the radial direction of a tunnel and a second monitoring part which is arranged at an interval along the axial direction of the tunnel, so as to obtain multi-dimensional deformation monitoring data for the underground excavation tunnel in construction. And the intelligent analysis unit can correct the deformation monitoring data. The method comprises the following steps: acquiring deformation monitoring data of a supporting structure and surrounding rock mass in real time; arranging a plurality of temperature and humidity sensors so as to take acquired temperature and humidity data as first environment data; arranging a vibration monitoring part to take the acquired vibration data as second environment data; and correcting the deformation monitoring data by directly utilizing the first environment data and / or utilizing the second environment data corrected based on the first environment data, so as to judge an early warning condition according to a corrected result.

The invention provides a home overall design method and system based on virtual reality. Wherein indoor environment data are collected in real time in a spatial gridding mode through a distributed temperature and humidity sensor array and a multispectral illumination sensor, and heterogeneous data are fused by using a spatial topology association engine to generate a three-dimensional environment parameter set. And based on the space coordinate weight matrix of the parameter set, driving a micro-electro-mechanical execution unit of the dynamic optical reflection film layer to adjust the surface inclination angle and the refractive index so as to form an optical reflection characteristic distribution diagram. And a three-dimensional light field model dynamically linked with physical illumination distribution is further constructed in the virtual scene, adaptive compensation operation of temperature and humidity parameters is triggered in real time according to physical space illumination intensity changes, characteristic parameters of the reflecting film layer are synchronously and reversely regulated and controlled, and a closed-loop control link is formed. According to the technical scheme provided by the invention, the full-dimensional precise synchronization of the optical characteristics of the material, the temperature and humidity influence and the illumination distribution in the home design scene is realized.

The invention discloses irrigation area patrol equipment and method based on an augmented reality technology, and relates to the technical field of agricultural hydraulic engineering and informationization, and the equipment comprises a video collection module, a video and audio interaction module, a communication module, a central processor, a temperature and humidity sensor, a positioning module, and an AI intelligent support module. Through the function of comparing the data with theoretical data, the requirement of patrol on the professionality of patrol personnel is reduced; the invention further provides a working system of AR field perception-AI intelligent support-expert cooperative support-auxiliary operation guidance, basic information is collected and sent based on the head-mounted AR patrol equipment and transmitted to the AI intelligent support module, a theoretical value under normal operation is given through a digital twinborn irrigation area AI calculation function in the AI intelligent support module and compared with the collected information, and the theoretical value is calculated. And in addition, the method can be combined with an expert online study and judgment function, so that the discovery of real-time inspection problems and field study and judgment can be realized.

A spoke winding type high-sensitivity humidity sensor, the humidity sensor comprising a humidity-sensitive winding material and a spoke winding skeleton disc; a plurality of "T" shaped winding skeletons are uniformly distributed in a radial manner on the circumference of the spoke winding skeleton disc, and the humidity-sensitive winding material is wound on the plurality of "T" shaped winding skeletons; the space between every two adjacent "T" shaped winding skeletons simultaneously constitutes a winding limiting groove and an air flow channel, and after the humidity-sensitive winding material is wound, there is still space, i.e. the air flow channel, for air circulation, which is used to shorten the humidity absorption response time and the humidity desorption response time of the humidity-sensitive winding material.

The invention discloses a laboratory resource efficient allocation method based on big data analysis, and relates to the technical field of laboratory resource management.The method comprises the following specific steps that microenvironment parameters are monitored and collected, comprising a temperature and humidity sensor, an air quality sensor, an illumination intensity sensor and an electromagnetic interference intensity sensor, a dynamic association model of external environment and laboratory resource demands is established by using a big data analysis technology, so that a complex relationship between external environment change and laboratory resource demands is accurately analyzed; a powerful basis is provided for scientific and reasonable resource allocation, so that a laboratory can more accurately predict and judge the demand degree of each resource and the allocation priority under different external environment conditions, unreasonable allocation and waste of the resources are avoided, and the resource allocation efficiency is remarkably improved.

The invention discloses a structural health monitoring device for civil engineering. According to the technical scheme, the structural health monitoring device is characterized by comprising a multi-parameter sensing module used for collecting strain, acceleration, displacement, temperature, humidity, vibration frequency and structural surface crack image parameters of a civil engineering structure; the multi-parameter sensing module comprises a strain sensor group, an acceleration sensor group, a displacement sensor group, a temperature and humidity sensor, a vibration sensor and an image acquisition unit; the strain sensor group is composed of a plurality of fiber Bragg grating strain sensors which are installed at key stress parts of the structure in a distributed arrangement mode. According to the structural health monitoring device for civil engineering provided by the invention, by virtue of the unique multi-parameter sensing module, the advanced data processing module and the flexible and reliable data transmission module, various excellent effects are shown in the field of civil engineering structural health monitoring.

The invention relates to the technical field of intelligent cook machine recommendation, and discloses an intelligent cook machine recipe recommendation and operation control method, which comprises a user input module used for receiving user instructions including food material types, cooking targets, diet restrictions and equipment models; the recognition module is used for collecting food material weight and state data; the data processing module adopts a multi-modal fusion algorithm; the recipe recommendation module is based on an improved collaborative filtering algorithm and a knowledge graph; and the output module is used for controlling the instruction generation unit to output a sectional operation instruction set according to the selected recipe. By integrating the image recognition unit and the weight sensor, the type, weight and state data of food materials placed in the chef machine by a user can be collected in real time, and correction processing is carried out in combination with the environment temperature and humidity sensor; therefore, the existing food material inventory of the user can be accurately considered during recipe recommendation, and the problem that the existing food materials of the user cannot be fully utilized during recipe recommendation by an existing system is solved.

The invention discloses a panel vertical seam water stop structure repair effect evaluation method, which comprises the following steps of: firstly, synchronously obtaining surface crack and internal defect data through cooperative detection of infrared thermal imaging and ultrasonic flaw detection; and carrying out space alignment on point cloud data generated by three-dimensional laser scanning and an ultrasonic detection result, and establishing a BIM model containing a crack three-dimensional form. A practical engineering environment is simulated in a laboratory to carry out material accelerated aging and test key indexes such as an elastic recovery rate, a base surface state is evaluated through a temperature and humidity sensor array in a construction stage, a six-axis grouting robot is adopted to execute accurate filling, a curing process is monitored by a synchronous pre-embedded optical fiber sensor, and after aging is simulated by combining a hydraulic test with climate, a construction period is shortened. A distributed optical fiber network is used for continuously collecting deformation data, a comprehensive evaluation model is constructed based on mechanics, durability and sealing indexes, and finally material selection and process parameters are optimized through machine learning.

The invention relates to the field of gas-water separation, in particular to a gas-water separation device which comprises a separation device body, a gas-water input pipe is arranged at the bottom of the side end of the body, a horizontal cavity is formed in the body, a plurality of dehumidification air cushions arranged side by side are arranged in the horizontal cavity, and horizontal filtering baffles are fixedly installed at the lower ends of the dehumidification air cushions. The gas-water separator combines a baffle type and a centrifugal type for gas-water separation, so that the separation efficiency is greatly improved. And through cooperative control of the humidity sensor and the temperature sensor, accurate gas-water separation management is realized. The humidity control part ensures that gas enters a proper separation area by switching baffle plate paths, and the temperature control part heats through an electrothermal film and cools through a heat dissipation copper sheet, so that the gas-water separator always operates in an optimal temperature interval. In combination with a lag control mechanism, the system can effectively avoid frequent switching caused by environmental humidity fluctuation, reduce energy consumption, prolong the service life of equipment, and ensure long-term stable operation of the fuel cell system.

The invention belongs to the technical field of power cable fault positioning. The invention discloses a TDR power cable global fault positioning method based on multi-frequency cooperative excitation and environment adaptive correction. The method comprises the following steps: 1) multi-frequency pulse cooperative injection and signal acquisition; 2) environment parameter dynamic sensing and speed correction: embedding a miniature temperature and humidity sensor and a cable insulation state monitoring unit along the cable at an interval of 500m, and collecting laying environment temperature, humidity and insulation material dielectric constant change data in real time; constructing a dynamic speed correction formula based on a preset environment-dielectric constant correlation model; according to the method, the complex fault positioning precision is improved, the environment and scene adaptability is enhanced, and the troubleshooting efficiency is optimized.

The invention belongs to the technical field of electrical safety, and particularly discloses an insulation resistance intelligent detection system and method for an energy storage converter, and the system is based on a bridge balance structure, integrates a temperature and humidity sensor and a voltage sensor, and collects environment parameters and bridge unbalance signals in real time. A digital potentiometer and a resistor array are driven through a PID algorithm to dynamically adjust bridge balance, and environmental interference is eliminated in combination with a temperature and humidity compensation model; and carrying out intelligent analysis on the preprocessed multi-dimensional data by utilizing a band-pass filtering and detection model, and outputting a high-precision insulation resistance value. The method achieves full-automatic detection, is high in precision, is quick in response, is suitable for complex working conditions, and remarkably improves the reliability of the insulation performance evaluation of the energy storage converter.