2696 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 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 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 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 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 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 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 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.

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 provides an intelligent agricultural system and an agricultural greenhouse humidity intelligent control method. The method comprises the following steps: firstly, acquiring a humidity sampling data sequence in a specified monitoring time window before a current regulation and control period in an agricultural greenhouse, and calculating a humidity change trend index; comparing the humidity change trend index with a dynamic trend threshold value, distributing a weight for each humidity sampling point, and performing weighted fusion based on the weights to obtain a weighted fusion result; and then generating a humidity regulation and control reference value of the current regulation and control period based on the weighted fusion result, the current real-time humidity and the external environment parameters. And finally, the deviation between the target humidity of the crop growth model and the current real-time humidity and the humidity regulation and control reference value are input into a controller to generate a dynamic regulation and control instruction, and operation parameters of a humidity execution mechanism are regulated according to the dynamic regulation and control instruction. According to the scheme, the robustness of accurate regulation and control of the humidity of the agricultural greenhouse can be improved.

The invention provides a thermal imager intelligent temperature measurement method based on a neural network, and relates to the technical field of thermal imaging temperature measurement, and the method comprises the steps: firstly collecting an infrared image and a visible light image of a target object, and environment temperature and humidity data; then, the infrared image is preprocessed; then calculating an initial temperature value through a temperature compensation formula, correcting energy attenuation by utilizing humidity data, and processing an abnormal heating signal in combination with the visible light image and the humidity data; and finally, related data are analyzed by means of a neural network, and a corrected temperature value is output. According to the method, a temperature compensation formula combining heat exchange and atmospheric radiation difference is constructed, correction factors are adjusted according to humidity and atmospheric pressure, a visible light image is used for identifying the dirt accumulation level, infrared image features are analyzed in combination with a neural network, and multi-source data fusion and environmental factor dynamic compensation are achieved. The interference of environmental factors on the temperature measurement of the thermal imager is effectively overcome, and the temperature measurement precision and the equipment defect detection accuracy in a complex environment are improved.

The invention relates to the technical field of intelligent archival repository management, and discloses an intelligent archival repository management method and system based on multiple modules. The method comprises the following steps: acquiring environment monitoring data such as storehouse temperature and humidity distribution and air quality indexes, and generating an environment state feature vector through feature extraction; inputting the data into an archive storage risk assessment model, outputting a risk level, and generating an environment regulation and control instruction set containing temperature and humidity regulation and air purification parameters according to the risk level; monitoring access request data containing file numbers and access timestamps in real time, and constructing an access frequency matrix to calculate file thermodynamic diagram distribution; a warehouse partition regulation strategy is generated by combining the thermodynamic diagram and the regulation instruction set, and the high-frequency access file is dynamically migrated to an environment stable area; incremental learning is adopted periodically to update model parameters, and risk prediction precision is optimized. The method can improve the intelligent degree of warehouse management and guarantee the safety of file storage.

The invention relates to the field of dehumidification control, in particular to a control method, device and equipment of a heat recovery rotating wheel dehumidification system and a storage medium. The method comprises the following steps: collecting real-time temperature and humidity parameters of a target indoor area, carrying out temperature and humidity position distribution interpolation calculation, and constructing a temperature and humidity distribution fluctuation diagram; performing indoor and outdoor humidity difference calculation and dehumidification demand prediction according to the temperature and humidity distribution fluctuation diagram to obtain a dehumidification demand prediction result; full-cycle operation state monitoring is conducted on the heat recovery rotary wheel dehumidification system, and the dehumidification load intensity of a moisture absorption area and the temperature recovery efficiency of a regeneration area are obtained; historical information of a runner material is extracted based on a dehumidification system operation log, the effective adsorption ratio and regeneration efficiency of the material are dynamically estimated, and a dehumidification performance attenuation index is generated. The dehumidification energy consumption is minimized, and the efficient and comfortable indoor adaptive dehumidification effect is achieved.

The invention discloses a multi-dimensional environment coupling aging test box and a self-adaptive control method thereof.The multi-dimensional environment coupling aging test box comprises a box body, a multi-dimensional environment coupling system and a self-adaptive control system.The box body is internally provided with a test cavity, the multi-dimensional environment coupling system is arranged in the test cavity, and the self-adaptive control system is arranged in the test cavity; and the multi-dimensional environment coupling system is connected with the adaptive control system. A multi-physics coupling environment is constructed by integrating four environment simulation modules of temperature and humidity, illumination, vibration and gas. The sensor group acquires environmental parameters (temperature and humidity, irradiance, acceleration and gas concentration) and state data of a test object in real time, and transmits the environmental parameters and the state data to the data processing unit. Based on a multi-physics field coupling model (such as finite element analysis or an empirical formula), the contribution degree of each environmental factor to material aging is calculated, a dynamic control instruction is generated, output parameters of each module are synchronously adjusted through an execution mechanism, and closed-loop control over environmental conditions is achieved.

The invention relates to the technical field of constructional engineering, in particular to a tunnel construction safety monitoring and automatic spraying dust fall method, which comprises the following steps: acquiring sensing data of a construction area, the sensing data at least comprising dust concentration data, humidity data and airflow data at each detection position; according to the dust concentration data, determining a high dust concentration area and predicted dust concentration data of the high dust concentration area at a future moment; according to the dust concentration data, the predicted dust concentration data, the current position of a spraying device and the position of the high-dust-concentration area, the humidity data and the airflow data are combined, and spraying control logic is determined; according to the spraying control logic, a spraying device is controlled to spray water to the high-dust-concentration area for dust falling. By monitoring the sensing data of the construction area and processing the sensing data to determine the appropriate spraying control logic, the dust falling effect is effectively improved.

The invention relates to the technical field of bridge engineering structure health monitoring, in particular to a service life prediction method and system for a bridge connection part, and the method comprises the steps: collecting the strain of a grouting sleeve, a reinforcement-grouting interface ultrasonic reflection signal and environment temperature and humidity data through a distributed sensor array; a three-dimensional dynamic void rate model is generated through fusion of a spatial topological mapping algorithm, a correlation function of load circulation and void expansion is established, the dynamic void rate is input into a bond strength coupling degradation model, after strength attenuation is quantized in combination with steel bar corrosion data and bond failure early warning is triggered, stress redistribution is calculated through multi-physics coupling simulation, and the dynamic void rate is obtained. Early warning is taken as a starting node, the actual load spectrum and temperature and humidity data are combined, Monte Carlo sampling is adopted to simulate rigidity degradation and output the residual life probability, the system comprises a multi-source collaborative sensing unit, a micro-void evolution analysis unit and a life prediction decision unit, and the safety control precision of bridge connection parts is improved.

The invention discloses a tunnel dew formation and icing rapid monitoring method and system based on a space-time phase change cooperation mechanism, and relates to the technical field of tunnel engineering safety monitoring and freeze injury prevention and control. Establishing a tunnel geometric model and a heat-humidity-turbulence multi-field coupling physical model; synchronously acquiring heat and humidity physical property parameters and outdoor hourly meteorological parameters; taking the outdoor hourly meteorological parameters as Dirichlet boundary conditions and initial conditions of a heat-humidity-turbulence multi-field coupling physical model; determining a heat and humidity exchange coupling process of the tunnel wall surface and the internal environment, and defining heat and humidity transfer parameters under an unsteady state boundary; performing discretization processing on the tunnel geometric model by adopting a grid division strategy; by setting a dew point temperature threshold value and an icing temperature threshold value, a condensation risk area is judged, dynamic changes of the thickness of an ice layer are quantified, and monitoring of tunnel condensation and icing is achieved. The method can effectively reflect the distribution rule of multiple physical fields on the surface and in the tunnel in any time, accurately judge the risk area and quantify the thickness of the ice layer.

The invention discloses an intelligent constant-humidity control FFU integrated system and a dust-free workshop application method thereof, and relates to the technical field of workshop application, and the method comprises an environment sensing unit which is used for collecting internal and external environment parameters and equipment operation states of a workshop in real time; the prediction unit is used for training and generating a model with a time sequence prediction capability by fusing historical production data and real-time environment fluctuation characteristics so as to output a temperature and humidity change trend and a key adjustment time window of each partition of the workshop in a future time period; the decision-making unit is used for dynamically selecting a target operation strategy from a process priority mode, an energy-saving mode and an emergency mode based on real-time production process requirements, an environment sensitivity threshold value and an energy consumption constraint condition; the parameter optimization unit is used for performing wind field parameter adjustment on the FFU unit under the target operation strategy, and minimizing system energy consumption while maintaining uniform distribution of temperature and humidity; adjustment comprises fan rotating speed gradient configuration, air outlet angle cooperative control and airflow circulation path optimization.

The invention relates to the technical field of automatic control, and discloses an automatic process intelligent control method and system for paper packaging. The method comprises the following steps: acquiring humidity fluctuation data and a material surface moisture content index in a production environment in real time, matching a preset moisture absorption model based on a humidity fluctuation grade, calculating a material physical property change amplitude and an influence of the material physical property change amplitude on pressure distribution, and obtaining a pressure distribution deviation value; calculating the target temperature adjustment amount of the heating equipment and updating the power setting of the humidity adjusting equipment according to the incidence relation between the deviation value and the equipment cooperation parameters, and generating a cooperation control instruction; driving equipment performs linkage adjustment and monitors pressure data, and key control parameters are extracted in a stable state for dynamic process adjustment; product appearance and packaging data are collected, whether the quality meets the standard or not is judged, and process parameters are automatically corrected. According to the method, multi-parameter intelligent cooperative control over humidity, temperature and pressure is achieved, and the stability, consistency and automation level of the paper product packaging production process are improved.

The invention relates to a test system and method for simulating different working conditions of a relay, and the system is characterized in that the system comprises an environment simulation region and a dynamic load simulation region, and the dynamic load simulation region comprises an electrical simulation region, a data collection region, and a data processing and control module; the environment simulation area is used for simulating working environment parameters of the relay, including temperature, humidity and mechanical stress; the environment simulation area is provided with a shell, and heating devices located on the top, the bottom and the side face of the shell are arranged in the shell and used for accurately adjusting the internal temperature. A ventilation opening is formed for adjusting air circulation; a temperature sensor and a humidity sensor are installed and used for monitoring environment temperature and humidity parameters in real time. According to the test system and the test method for simulating different working conditions of the relay, various environmental stresses can be synchronously applied, load changes can be dynamically simulated, data fusion analysis can be realized, and the accuracy of reliability verification of the relay can be improved.