3360 results about "Humidity" patented technology

The invention discloses an electrical cabinet condensation defense method and system based on environmental parameter monitoring. The method comprises the following steps: acquiring temperature and humidity information of multiple points in an electrical cabinet and outside the cabinet in real time; calculating a dew point temperature and a condensation risk index in the cabinet; predicting the lowest temperature and humidity change rate in the cabinet in the next time period in the control period; based on the minimum temperature and humidity change rate prediction value in the cabinet and the current condensation risk index, whether the electrical cabinet meets the condensation risk trend criterion is judged, if yes, the electrical cabinet enters a condensation risk suppression linkage control mode, and if not, the electrical cabinet enters a condensation risk defense self-adaptive mode; and in the condensation risk suppression linkage control process, when the current condensation risk index of the electrical cabinet is lower than a condensation risk index threshold value, entering a condensation risk defense self-adaptive mode, and otherwise, entering a next control period. Data acquisition is comprehensive and accurate, the dew point temperature can be accurately calculated, the control strategy is intelligent and flexible, equipment can operate according to needs, condensation is effectively prevented, and the energy-saving effect is remarkable.

The invention relates to the technical field of environment perception, and discloses an optimization method and device for a multi-climate self-adaptive environment perception cooling fan system, and the method comprises the steps: collecting multi-point temperature, humidity and air pressure data, and carrying out the filtering processing, and obtaining an environment state vector; executing mathematical modeling of the multi-degree-of-freedom cooling system according to the environment state vector to obtain a linearized state space model; performing temperature gradient estimation and humidity compensation based on the linearized state space model to obtain an adaptive control law; inputting the adaptive control law into a model-free adaptive prediction controller to obtain a rolling optimization control sequence; weight self-adaptive adjustment and heat dissipation efficiency hierarchical prediction control are carried out on the rolling optimization control sequence based on climate conditions, fan rotating speed control and wind direction adjustment execution signals are generated, the problem that a traditional heat dissipation system is not sensitive to space temperature distribution and humidity changes is solved, and the heat dissipation control precision under different humidity conditions is improved.

The invention relates to a machine room environment intelligent regulation and control method fusing multi-source sensing information, and the method comprises the steps: collecting the temperature and humidity data of different regions in a machine room through a temperature and humidity sensor, and collecting the movement track and stay time data of a person in the machine room through a person positioning device, transmitting the collected machine room environment data and personnel activity data to a data fusion module; in the data fusion module, machine room environment data and personnel activity data are aligned according to a time sequence, wrong data and outliers are eliminated, and a data set in a unified format is obtained; a correlation coefficient matrix among the characteristic parameters of the computer room is analyzed through correlation, the characteristic parameters with correlation higher than a preset correlation threshold value are screened out, and the characteristic parameters comprise temperature, humidity, personnel access frequency and staying duration parameters.

The invention discloses a constant-temperature and constant-humidity test box temperature control system based on a multistage PID algorithm and a control method thereof. The constant-temperature and constant-humidity test box temperature control system comprises an environmental parameter detection module, an in-box parameter detection module and a multistage PID controller, wherein the environmental parameter detection module is used for collecting temperature, humidity and air pressure data outside a test box in real time; the in-box parameter detection module is used for collecting multi-dimensional environmental parameters inside the test box; when the failure of any sensor is detected, starting a fault self-diagnosis module, replacing the data of the failure sensor with a data interpolation method of a side sensor, and recording the deviation compensation amount at the same time. A multi-stage PID control architecture is adopted, and feedforward compensation, parameter adaptive optimization and fault redundancy strategies are combined, so that high-precision and anti-interference control of the temperature and humidity of the test box is realized.

The invention relates to the field of grain depot ventilation management, and discloses an automatic management system for ventilation in intelligent grain depot production, which comprises an environmental parameter monitoring module, a data processing and analysis module, an intelligent ventilation decision module, a ventilation equipment linkage control module and a dynamic feedback optimization module, the environmental parameter monitoring module is used for collecting temperature, humidity and gas concentration data in the bin in real time through the Internet of Things communication unit; the data processing and analyzing module is connected with the environment parameter monitoring module; the intelligent ventilation decision-making module receives the multi-dimensional data atlas, analyzes the temperature gradient, the humidity sensitivity index and the mildew risk value in the atlas through a dynamic classification algorithm, and fuses external meteorological data; the ventilation equipment linkage control module is used for receiving the instruction sequence of the intelligent ventilation decision module; the dynamic feedback optimization module is used for monitoring the efficiency coefficient and the grain pile environment change rate in the ventilation process; the system has the advantages that the ventilation precision and efficiency are improved, and granary environment management is optimized.

The invention relates to the technical field of sensor calibration, in particular to an environment adaptive multi-dimensional calibration method for an excavation type intelligent sensor, which comprises the following steps: acquiring temperature, humidity and gas data through environment monitoring, comparing with a threshold value, marking an abnormal state, evaluating the influence of each parameter on a sensor signal and analyzing fluctuation amplitude and intensity; combining sensor sensitivity and response rate to screen key factors, extracting factor fluctuation trend, optimizing signal disturbance weight and response path, correcting signals in real time, updating a calibration parameter set, monitoring signal values based on multi-dimensional parameters, and adjusting output to maintain a stable range. According to the invention, temperature and humidity and gas abnormity are dynamically identified through threshold comparison, a factor model is constructed based on sensitivity weight, a multi-dimensional calibration path is generated, a parameter set is updated in real time to decouple environment sudden change and sensor drift, signal self-adaptive convergence is realized through closed-loop control, multi-parameter interference errors are reduced, and the bottleneck of calibration delay is broken through. And the time-varying working condition data stability is ensured.

The invention relates to the technical field of vehicle-mounted temperature control, and discloses a method and system for intelligently controlling the temperature and humidity of a vehicle-mounted cold chain and a storage medium. The method comprises the following steps: acquiring and preprocessing temperature and humidity data through a sensor; performing state evaluation based on a three-way decision model; constructing a temperature and humidity trend analysis model to predict a change trend; constructing a control decision system by adopting multi-agent reinforcement learning; executing a multi-mode control strategy; and adaptively updating the control system according to the execution effect. According to the application, the future temperature and humidity change trend is predicted according to the historical data and the real-time state, collaborative optimization control of temperature and humidity is realized, self-learning and continuous optimization capabilities are provided, and the accuracy, stability and energy utilization efficiency of cold chain temperature and humidity control are effectively improved.

The invention provides an intelligent adjusting and dynamic defrosting method and system based on multiple sensors and a medium The method comprises the steps that firstly, monitoring data are obtained in real time according to the multi-dimensional sensors deployed in a freezer, and a multi-source data matrix is obtained through preset data processing and integration; secondly, dynamically adjusting a frost condition model weight coefficient according to monitoring data, and quantifying a frost condition coefficient based on a frost condition model in combination with a multi-source data matrix; then, executing a three-stage defrosting strategy according to the frost condition coefficient, and respectively adjusting working parameters of defrosting equipment such as a compressor, a condensation fan or a heater; and finally, precise control over the box temperature is achieved through power step soft start of a compressor and PID dynamic adjustment of an electronic expansion valve, and energy efficiency optimization is achieved by automatically optimizing the rotating speed of a condensation fan based on the environment temperature and humidity. The corresponding defrosting operation is triggered through the frost condition coefficient, and the effectiveness of defrosting and the stability of the box temperature are improved; in addition, the adaptability of special scenes is enhanced by dynamically adjusting the weight.

The invention discloses a mass concrete temperature evolution analysis model based on a multi-field coupling model. The mass concrete temperature evolution analysis model comprises the following steps: S1, establishing a concrete hydration field model containing temperature and relative humidity correction; s2, establishing a temperature field model containing common characterization of concrete matching, hydration degree and relative humidity; s3, establishing a humidity field model for correcting an early concrete water storage function and a humidity transmission coefficient based on the hydration degree; s4, establishing a water cooling model coupled with the concrete temperature field based on the non-isothermal pipeline flow; and S5, establishing an early concrete temperature rise analysis model based on hydration-heat-wet-water cooling coupling based on a finite element method. According to the method, environmental factors, material factors, construction factors and maintenance factors in the concrete hydration process are fully combined, the application scene is more comprehensive, and the accuracy is higher.

The invention provides an indoor environment monitoring method and system integrating temperature and humidity, and is applied to the field of sensing data processing. According to the method, the reading difference of the temperature sensor is collected, whether local deviation exists or not is judged, the arrangement type of the sensor is combined, a low temperature value generated by the wall-leaning sensor due to the cold bridge effect is dynamically compensated, misjudgment of an environment system is avoided, and the human body temperature is introduced as a sensing reference by constructing a temperature difference deviation function. According to the method, comprehensive temperature indexes closer to real experience can be generated, when abnormal fluctuation is detected, the space structure and heat source information are further combined, boundary conditions are constructed, dynamic heat flow and temperature and humidity distribution diagrams are simulated, temperature sensing deviation is effectively and reversely corrected, the precision, stability and energy-saving performance of an environment adjusting system are remarkably improved, and the comfort degree of a human body is improved.

The invention discloses a temperature and humidity control method for a marine energy storage container, and relates to the technical field of container temperature and humidity control, and the method comprises the following steps: monitoring the temperature and humidity in the container in real time, and obtaining the real-time environment parameters of the environment in the container through a sensor; through real-time monitoring, an intelligent algorithm and multi-level control, the system dynamically adjusts the temperature and humidity, and the accuracy and the response speed are improved. Different from traditional static setting, the system is combined with sensor data and a prediction model to cope with environment and load changes in advance, temperature and humidity are prevented from exceeding the standard, and equipment faults are reduced. The energy waste is reduced, the energy consumption distribution is optimized, the overall energy efficiency is improved, the cost is reduced, and the safe and stable operation of the equipment is ensured by a regionalized control and global optimization strategy.

The invention discloses a mine disaster prediction method based on multi-source data, and relates to the technical field of mine safety, and the method comprises the following steps: collecting original data from different types of sensors in a mine, the data types comprising gas concentration, temperature, humidity, wind speed, ground pressure, water level and vibration information; each type of data is provided with a corresponding timestamp and a spatial position identifier. According to the method, time resampling and space mapping standardization of multi-source data are realized, so that the time-space consistency of data fusion is remarkably improved, and the accuracy of disaster prediction model input is ensured. Meanwhile, a dynamic feature matrix is constructed and a high-precision position weight mechanism is introduced, so that the sensitivity of the model to key areas and key parameters is enhanced, the real-time performance and accuracy of mine disaster prediction are effectively improved, and the risk of missing report and false report of an early warning system is remarkably reduced.

The invention belongs to the technical field of intelligent control, and particularly relates to an intelligent regulation and control method for an operating environment in an SF6 ring main unit. The method comprises the following steps: firstly, acquiring temperature, gas pressure and humidity data of a plurality of sampling points in the ring main unit, and constructing a time sequence environment data set through time synchronization and missing interpolation processing; analyzing the temperature data, extracting fluctuation characteristics, determining an environment disturbance factor in combination with an electric arc trigger intensity index, and obtaining a cabinet body temperature control safety factor in combination with a dynamically adjusted temperature rise threshold and a gas insulation state; then constructing an environment equivalent thermal inertia model and a hot-pressure covariant model based on historical data, and calculating a thermal stability index of the cabinet body; and finally, whether adjustment is triggered or not is judged according to the thermal stability index and the temperature control safety factor, if yes, a temperature abnormal area is positioned through a convolutional neural network and a clustering method, the temperature control response level is calculated, a temperature control strategy library is called to be matched with adjustment parameters, and accurate control is achieved.

The invention discloses a tunnel fire position positioning and fire source risk analysis method and system, and relates to the technical field of tunnel fire detection, and the method comprises the steps: periodically collecting image, temperature, smoke, harmful gas concentration, infrared radiation and humidity data at each monitoring point in a tunnel, and dynamically adjusting the monitoring frequency according to the humidity; feature extraction is performed on the collected data, a factor set and a fuzzy evaluation set for fire judgment are constructed, and a fuzzy algorithm is utilized to calculate the membership degree of each feature to fire evaluation; a comprehensive membership value vector is generated in combination with the feature weight and is used for judging whether a fire occurs or not and performing preliminary positioning; initial monitoring equipment and front and back adjacent equipment are set, and the fire position is further accurate through fuzzy analysis of data of the front and back adjacent equipment; performing risk assessment on the fire according to the fire position and the abnormal pixel point proportion; intelligent detection, precise positioning and risk analysis of the tunnel fire are realized, and the tunnel safety management level is effectively improved.

The invention relates to the technical field of mine environment control, and discloses an intelligent environment monitoring and control method in a mine laneway. The method comprises the steps that a real-time environment parameter set of a mine laneway is collected, the set contains gas concentration data, dust concentration data and temperature and humidity data, and real-time capture of laneway environment multi-dimensional parameters is achieved; then, based on the collected real-time environment parameter set, calculating an environment safety evaluation index so as to scientifically and objectively reflect the roadway environment safety condition; a dynamic control strategy is generated according to the environmental safety evaluation indexes, and the strategy comprises ventilation equipment regulation and control parameters and early warning level parameters and can be flexibly adjusted according to environmental changes; and finally, the ventilation equipment regulation and control parameters are sent to a mine ventilation system, and roadway environment regulation and control are executed. According to the method, environmental parameters can be comprehensively monitored, safety risks can be accurately evaluated, ventilation equipment can be flexibly regulated and controlled, the early warning function can be perfected, energy waste can be reduced, labor intensity can be reduced, and underground operation safety and mining efficiency can be guaranteed.

The invention discloses a dough humidity and temperature dynamic regulation and control system based on multi-modal sensor fusion, and relates to the technical field of operation parameter regulation and control, and the method comprises the steps: carrying out the non-blind area monitoring of a three-dimensional temperature and humidity field in a fermentation box, and eliminating the local failure risk of a point-type sensor; capturing a space-time coupling relationship of temperature and humidity-carbon dioxide concentration-dough volume through a self-attention mechanism; constructing a differential equation set comprising at least one state variable; establishing a fermentation equipment thermodynamic model, optimizing refrigeration and heating time sequences through reinforcement learning, and designing an energy consumption optimization strategy based on digital twinning; performing cross-device cooperative control; constructing a hierarchical diagnosis tree containing fault features; performing microbial activity enhanced humidity regulation and control, and forming a protective layer on the surface of the dough based on a humidity gradient control algorithm of a water molecule diffusion coefficient. And by arranging the environment regulation and control module, the time compression module and the time sequence optimization module, the product quality, the production efficiency and the energy utilization rate are remarkably improved.

The invention provides a temperature and humidity compensation method and system for a gas sensor, and relates to the technical field of temperature and humidity compensation methods, and the method comprises the steps: obtaining the temperature and humidity of a space where the gas sensor is located and the time sequence data of the gas concentration output by the gas sensor at the same time, and obtaining a temperature input coefficient and a humidity input coefficient; establishing a temperature and humidity cross influence quantitative model to obtain a gas concentration error of the gas sensor caused by temperature and humidity changes; and filtering the gas concentration data output by the sensor before compensation, constructing a weighted comprehensive index of temperature and humidity changes, and compensating the filtered gas concentration data by adopting a dynamic switching compensation mode. And establishing a temperature and humidity cross influence quantitative model, inputting the temperature input coefficient and the humidity input coefficient into the established temperature and humidity cross influence quantitative model to obtain a gas concentration error, and adopting a dynamic switching compensation mode based on the gas concentration error according to the change of the environment temperature and humidity.

The invention relates to the technical field of environmental protection, in particular to a meteorological element-driven pollutant contribution degree evaluation method and system, and the method comprises the following steps: recognizing regional meteorological characteristics, calculating a wind field disturbance intensity index, predicting a pollutant propagation path, and analyzing the relation between a turbulence period and pollutant concentration attenuation. The retention time of various pollutants is predicted, the influence of humidity on the pollutants is evaluated, and the contribution degree of the pollution source is evaluated in combination with the emission characteristics of the pollution source and meteorological data. According to the method, the meteorological sudden change characteristic index is constructed, the identification capability of abnormal meteorology on the pollution process is optimized, the dynamic prediction precision of the pollutant propagation path is enhanced by combining the wind field disturbance intensity index, the judgment accuracy of the pollution residence time is improved by utilizing the relationship between the turbulence period and attenuation, and the humidity and particle size response analysis is adopted; and the evaluation of the effect of humidity on pollution is refined, and the multi-source emission characteristics and meteorological factors are fused, so that the accurate identification and source-based analysis of the pollution contribution degree are realized.

The invention relates to the technical field of gas monitoring, and discloses an air quality monitoring method based on an olfactory chip, which comprises the following steps: step 1, preparing a multi-modal sensor system which comprises an olfactory chip module, a surface enhanced Raman scattering module and a microfluidic time division multiplexing module, the sensor surface of the olfaction chip module is modified with a metal organic framework material, and the substrate of the surface enhanced Raman scattering module is made of a core-shell structure nano material; and 2, synchronously collecting resistance response data of the olfaction chip module, spectral data of the surface enhanced Raman scattering module and temperature, humidity and wind speed data of the environment sensor. According to the invention, a multi-modal sensor cooperative detection technical scheme is adopted, the high-sensitivity detection effect on low-concentration harmful gas in air is achieved, and compared with a technical scheme of a single sensor and a fixed fusion algorithm in the prior art, the defect that accurate recognition of trace gas cannot be realized under ppb-level concentration is overcome.

The invention discloses an intelligent curing method and system driven by sensing of an internal temperature and humidity field of concrete. The intelligent curing method comprises the following steps that the surface tensile strength and the elastic modulus of the concrete of the same concrete mix proportion and different ages are obtained; according to the concrete maturity theory and the concrete surface tensile strength of different ages, a fitting function of the concrete surface tensile strength is obtained; predicting a fitting function through the elastic moduli of different ages and the elastic moduli; obtaining the inner surface control temperature difference of the concrete at different ages by utilizing the relationship between the concrete surface tensile strength and the concrete surface tensile stress and combining the fitting function of the concrete surface tensile strength and the elastic modulus prediction fitting function; and the concrete curing environment temperature and humidity are intelligently controlled according to the inner surface control temperature difference of the concrete of different ages. By dynamically determining the concrete curing temperature control index and combining with the humidity requirement, the on-off of the curing equipment is controlled, and the temperature and humidity of the concrete curing environment are intelligently controlled.

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 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 relates to the technical field of digital twinning equipment management, in particular to a digital twinning scientific research equipment intelligent management system integrating the Internet of Things and artificial intelligence. The system comprises a multi-source heterogeneous data acquisition unit which is used for performing real-time information acquisition on the operation environment and the equipment state of scientific research equipment; the digital twin mapping unit constructs a temperature and humidity coupling dynamic model fusing a temperature dynamic model and a humidity dynamic model by introducing a temperature and humidity coupling coefficient, and maps data collected from multi-source equipment and a laboratory environment to the temperature and humidity coupling dynamic model; the AI multi-dimensional prediction unit predicts the future running state of the equipment and the environmental risk; and the risk early warning unit analyzes the operation state of the air conditioning equipment and the environment coupling risk thereof in real time based on the prediction result of the AI multi-dimensional prediction unit, and sends out an early warning signal before potential abnormity occurs. The method is used for predicting the equipment fault risk in advance, thereby achieving the purposes of advanced prediction and active intervention.

The invention relates to the technical field of environment control, in particular to an intelligent mildew-proof system and a mildew-proof and moisture-proof product, and the system comprises an evaporation trend monitoring module, a wet area path identification module, a retention risk identification module, a stress grade judgment module and a linkage adjustment archiving module. According to the method, through comprehensive collection and difference analysis of environment parameters of air duct nodes and superposition of air velocity and dew point change trends, humidification trend data with time sequence and spatial flow direction characteristics are constructed, wet flow direction consistency and a wind speed disturbance track in a continuous time window are combined, a wet area expansion path is identified, and a key diffusion section is positioned; through extracting deviation information between a regional equipment response state and a risk level intervention demand, linkage intervention of a fan and dehumidification is realized, accurate adjustment and dynamic recording of multi-parameter cooperative control are completed, fine identification capability of a wet region evolution and retention trend is enhanced, and initiative and adaptability of space humidity control response are improved.

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 belongs to the technical field of simulation analysis, and particularly relates to a medium-high voltage switch cabinet internal humidity inversion calculation method based on simulation analysis, which comprises the following steps: establishing a geometric model of a switch cabinet, importing the geometric model into finite element simulation software to obtain a simulation analysis model, adding each physical field and computational domain and boundary conditions thereof, and calculating the internal humidity of a medium-high voltage switch cabinet. All the physical fields are coupled, and mesh generation is carried out; performing numerical solution on the simulation analysis model by using a transient solver to obtain a temperature and humidity distribution condition in the switch cabinet; the simulation analysis model is optimized, a simulation data set is constructed, and a PINN is trained; based on the environment temperature and humidity and the operation current collected in the actual operation of the switch cabinet, the trained PINN is used for prediction, and the steady-state relative humidity of the current transformer is obtained. According to the invention, based on the limited boundary monitoring data, efficient and accurate reconstruction of the humidity field of the key area in the switch cabinet is realized, and a feasible path is provided for equipment state sensing and condensation risk early warning.

The invention relates to the field of grain storage management, and discloses an intelligent granary grain pile dew point early warning method and system, and the method comprises the steps: carrying out the continuous collection of the temperature and humidity, airflow velocity and pile density of each grain pile in a granary, and generating a humidity and heat perception graph reflecting the spatial layering characteristics; performing time sliding and spatial reconstruction analysis on the damp-heat perception graph, and constructing a damp-heat evolution mapping model; based on the damp and hot evolution mapping model, calling a multi-dimensional risk identification engine to perform aggregation judgment on the micro-region with the dew point close to a critical value, and outputting a potential condensation risk set; performing joint correction on the potential condensation risk set, real-time airflow distribution, grain pile accumulation form and ventilation response delay characteristics, and performing dynamic weight regression on different grain varieties and seasonal factors to generate dynamic stability indexes reflecting risk migration and diffusion trends; and adaptively adjusting the sensing sampling density and the early warning judgment threshold according to the dynamic stability index. The method has the advantage of improving the early warning precision of storage environment management.

The invention provides a marine meteorological data quality control method based on a cross-parameter correlation network, which belongs to the technical field of marine meteorology, and comprises the following steps: constructing a cross-parameter correlation network model comprising an air temperature and air pressure correlation rule, a humidity and air temperature linear correlation rule and a wind speed and air pressure gradient extraction correlation rule; a sliding window algorithm is adopted to calculate a correlation coefficient in real time and identify correlation abnormity, a multivariate abnormity detection mechanism of four dimensions of parameter threshold overrun, spatio-temporal change rate abnormity, probability density distribution offset and correlation verification failure is established, a fuzzy comprehensive evaluation method is adopted to calculate a comprehensive abnormity index, and data abnormity is judged. And the authenticity of the abnormal data is confirmed in combination with a multi-sensor cross validation mechanism, and finally the abnormal data is restored by adopting a virtual sensor data reconstruction algorithm based on correlation network reverse calculation, so that the technical problem of poor abnormal data detection effect in the prior art is solved.

The invention provides a method and a system for actively monitoring, regulating and controlling a clean room, which are characterized in that environmental parameters in the clean room and spatial state information of a dynamic object are acquired through cooperation of a fixedly arranged sensor and a sensor carried by a mobile device, and the environmental parameters comprise airflow velocity, temperature and humidity, pressure difference, particulate matter concentration, illuminance and the like; the dynamic objects comprise positions of the personnel and the equipment and geometric models of the personnel and the equipment. And cleaning and fusing the collected data to generate a standardized parameter sequence with a time label, and constructing a three-dimensional dynamic environment model by combining a clean room structure and dynamic object information to realize grid mapping and visual management of environment parameters in the model. And on the basis of the model, an environment state change trend is predicted, risk grade evaluation is executed, a hierarchical regulation and control instruction is generated, closed-loop regulation and control and parameter adaptive adjustment of the clean room environment are finally realized, and the intelligent and refined level of clean room environment regulation and control is improved.

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.