63 results about "Moisture gradient" patented technology

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 field of performance testing of road engineering materials, and discloses an emulsified asphalt in-situ cold-recycled mixture high-temperature creep test method which comprises the following steps: preparing a test piece: presetting an old material-emulsified asphalt standard test piece, and embedding a moisture regulation and control device to generate a controllable gradient; multi-field loading: coupling an unsteady-state temperature field, a moisture gradient field and a time-varying attenuation stress field to construct a composite loading environment; synchronously aligning data: synchronously acquiring macro strain and micropore data, and realizing cross-scale alignment through a space-time matrix; performing parameter inversion: inverting nonlinear constitutive parameters by combining macro and micro data, and constraining a solution space by using a thermodynamic equation; and intelligent termination output: triggering a termination mechanism based on a multi-dimensional criterion and outputting damage evolution data. Through multi-field coupling loading, cross-scale data fusion and intelligent criterion cooperation, the problems of traditional test environment distortion, parameter deviation and criterion lag are solved, and accurate analysis of the high-temperature creep behavior of the emulsified asphalt reclaimed material and reliable prediction of the performance degradation law are achieved.

The invention discloses an intelligent agricultural water-saving irrigation system and a control method, and relates to the technical field of agricultural irrigation. Comprising the following steps: a land area planning module performs equal-area division on a farmland, sets a detection node array, and monitors water retention conditions of different soil depths; the moisture gradient characterization module calculates the vertical moisture gradient and the direction of the vertical moisture gradient of the evaluation area in real time through edge calculation. And the irrigation water amount correction module fuses and generates a target water-holding capacity based on the leaf stomatal conductance signal and the moisture gradient. The irrigation circulation termination control module uses pulse type infiltrating irrigation, and sets double termination conditions of the water-holding capacity change rate and the permeability. The closed-loop feedback adjustment module detects the soil water content after irrigation, characterizes the water leakage risk and feeds back and adjusts the irrigation water amount, closed-loop control is formed, and effective utilization of water resources is ensured.

The invention discloses a tunnel pavement concrete early-age strength prediction method based on multi-network fusion modeling. The method comprises the following steps: S1, continuously and equally dividing a tunnel center line according to a certain interval; s2, only keeping a left-right adjacent segment relation for the segment, and calculating a direction weighted thermal gradient, a direction weighted humidity gradient and a direction weighted traffic disturbance gradient based on the state vector; s3, writing the state vector of each segment into a sliding window with a set time length at a fixed sampling period; s4, inputting the dynamic graph input tensor into a space-time diagram neural network; s5, comparing the prediction sequence with a preset strength threshold value, identifying potential weak segments, and calculating risk confidence in combination with the gating coefficient; and S6, writing the maintenance instruction packet into a corresponding PLC channel. Potential weak sections can be recognized, spraying, heat preservation curtains and ventilation equipment can be linked, and local precise maintenance and batch open traffic unified management are achieved.

The invention provides an intelligent and accurate baking layering adjusting method for humidity gradient control, and belongs to the technical field of tobacco leaf baking. Humidity data in the vertical and horizontal directions are obtained through a sensor array, granularity ambiguity is calculated after an initial measurement matrix is established, sharpening preprocessing is performed, granularity stability of each layer is calculated based on a processing result, and the granularity stability of each layer is calculated. Analyzing and establishing a game equilibrium model in combination with a humidity mass transfer kinetic equation, outputting a coupling iteration degree, dynamically adjusting a sequence length parameter of a humidity gradient prediction model to generate a tobacco leaf baking humidity index, and generating a humidity distribution map to identify a key region and a time node according to the index; and constructing a tobacco leaf curing humidity floating matrix to record the humidity change track of each layer, performing trend prediction by adopting the adjusted prediction model, finally adjusting the temperature and humidity parameters of each layer in real time through an intelligent control algorithm to realize layered accurate control, continuously monitoring the humidity gradient change and dynamically optimizing a control strategy until a preset curing quality standard is reached.

The invention provides a monascus drying degree real-time control method which comprises the following steps: monitoring the surface moisture content, internal metabolic activity index and pigment content change of mycelium in a monascus drying process, and generating a mycelium state distribution diagram; extracting moisture gradient characteristics and metabolic activity parameters from the mycelium state distribution diagram, analyzing a relationship between a moisture evaporation rate and mycelium activity, and determining a dynamic trend of moisture gradient and activity change; analyzing the dynamic trend of the moisture gradient and the activity change, determining the relationship between the moisture gradient and the activity change through a fitting curve, and predicting the change trend of the moisture and the activity of the mycelium in different drying stages; aiming at a moisture distribution non-uniformity index, the uniform distribution of heat in the red yeast rice is improved by optimizing an air supply mode, so that the moisture evaporation rate deviation is reduced, and a temperature and humidity control sequence is obtained.

The invention discloses a seed humidity gradient packaging and freezer graded storage method, and relates to the technical field of graded storage, and the method comprises the following steps: S1, establishing a multi-dimensional initial state file containing the indexes; s2, dividing the pre-adjusting process of the water content of the seeds into a plurality of stages; s3, dividing seed storage risk grades based on the multi-dimensional initial state file; s4, dividing storage sub-regions according to spatial positions and packaging types; and S5, when the parameters exceed the preset threshold value, the operation parameters of the freezer are regulated in a linkage mode, and cold supply is optimized according to the sub-area sensitivity priority in combination with the operation scene. According to the method, a multi-dimensional state file is established by detecting the initial moisture content, the energy reserve and the physical integrity of the seeds, then the risk levels are divided based on the file, and the differentiated packaging humidity and the pre-adjustment strategy are matched, so that the lower packaging humidity is adopted for the seeds with the high initial moisture content to inhibit mold breeding; excessive drying is avoided for seeds with low initial moisture content.

The invention relates to the technical field of concrete electric pole manufacturing, and discloses a method and system for manufacturing a centrifugal electric pole based on high-performance steel fiber reinforced anti-crack concrete. The method comprises the following steps: collecting raw material performance index data including concrete rheological characteristics, steel fiber distribution and matrix strength data; an electric pole forming multi-scale coupling model is constructed through a material simulation platform; identifying fiber orientation characteristics according to steel fiber distribution data, comparing the fiber orientation characteristics with a fiber distribution-doping demand mapping table, judging whether to adjust a fiber doping strategy or not, and starting a manufacturing parameter decision process if the fiber doping strategy needs to be adjusted; stirring, centrifugal forming and maintenance parameters are extracted from preset rules in combination with performance index data, and details such as the fiber feeding time sequence, the rotating speed and the temperature and humidity gradient are determined; the model is used for simulating the whole manufacturing process, related indexes are output to evaluate the proportion, parameters and quality stability, an instruction optimization process is generated, and the manufacturing scientificity is improved.

The invention discloses a suspension bridge main cable dehumidification system and dehumidification method based on distributed humidity monitoring, and belongs to the field of suspension bridge main cable humidity monitoring and dehumidification. The suspension bridge main cable dehumidification system comprises a three-dimensional humidity monitoring network, an optical fiber demodulator, an intelligent control module and a distributed dehumidification module which are implanted or embedded into a suspension bridge main cable; the three-dimensional humidity monitoring network is electrically connected with the optical fiber demodulator through an outgoing line, the optical fiber demodulator is electrically connected with the input end of the intelligent control module, and the output end of the intelligent control module is connected with the distributed dehumidification module. By the adoption of the suspension bridge main cable dehumidification system and method based on distributed humidity monitoring, the problems that the internal humidity gradient of a large-section main cable is large, single-point monitoring is inaccurate, dehumidification control is extensive and the like are solved, visual early warning and linkage precise protection of the internal corrosion environment of the main cable can be achieved, and the durability and safety of the suspension bridge main cable are remarkably improved.

The invention discloses an intelligent adjustment method and system for a corrugated paper production line, and relates to the technical field of intelligent control adjustment, and the method comprises the steps: monitoring and recognizing the position of corrugated paper through a sensor array disposed at a key node of the production line, and extracting technological characteristic parameters; the method comprises the following steps: constructing a process state characteristic data set through a sensor array deployed at a key node of a production line, analyzing the moisture content of the surface and the inner core layer of corrugated paper to obtain an internal humidity gradient value of a paperboard, and calculating evaporation rates under different humidity gradients in combination with drying plate temperature data and drying time to obtain a temperature evaporation rate set; the paperboard deformation change rate analysis is carried out based on the drying temperatures of the paperboard under different water contents, an adjustment decision model for controlling the drying board temperature during hot pressing is constructed by determining the safety deformation risk probability and obtaining a paperboard preliminary risk intervention data set, and the adjustment decision model is converted into an equipment execution command based on a collaborative regulation strategy. And transmitting to production line intelligent equipment for real-time adjustment.

The application relates to the technical field of industrial automation control, and discloses a multivariable intelligent prediction control system for a konjac rice drying process, which comprises the following modules: a multimodal perception and soft measurement field construction module, which is used for collecting and fusing data to construct a dynamic soft measurement field; a twin dynamics characterization module, which is used for establishing a model and predicting a future material state based on the soft measurement field; a physical field-virtual field mapping and abnormality tracing module, which is used for comparing a real state with a predicted state to diagnose an abnormality root cause; an adaptive reinforcement learning prediction control module, which is used for integrating all information to generate an optimal control action; and a dynamic edge computing and model collaborative deployment module, which provides calculation and resource scheduling for the aforementioned modules. The application adopts a technical scheme in which multimodal perception data and deep learning are fused, a dynamic soft measurement field is constructed, and therefore key states such as a material internal moisture gradient and a surface crust degree can be quantified in real time and nondestructively.

The application discloses a kind of based on flavoromics's sun vinegar aging period flavor dynamic change analysis method, it is related to flavoromics technical field, to solve the current concentration rainstorm causes the temperature and humidity gradient of inner and outer wall of pottery jar to increase dramatically, causes the technical problem that pottery jar astringency is generated, including the following steps: S100, real-time monitoring and risk assessment of heat and humidity stress;S200, rainstorm event fusion early warning;S300, dynamic deduction and strategy optimization based on digital twinning;S400, dynamic microenvironment blocking control execution;S500, closed-loop feedback based on proxy index;S600, post-evaluation and model optimization.The application realizes early quantitative perception to astringency risk by real-time monitoring and calculating heat and humidity stress index representing ion precipitation driving force, combined with the research and judgment model of early warning confidence of fusion meteorological forecast and real-time data, starts the blocking control system, carries out physical intervention to pottery jar, guarantees the quality stability of sun vinegar in rainy season.

The invention discloses a grading diagnosis and evaluation method for insulation resistance of a mutual inductor, and relates to the technical field of mutual inductors. The method comprises the following steps: acquiring real-time data of a mutual inductor; a humidity gradient value is determined according to the humidity data, whether the humidity gradient is larger than a preset threshold value or not is determined, if the humidity gradient is larger than the preset threshold value, the mutual inductor is divided into five layers in the set height direction, and the temperature weight of each layer and the humidity weight of each layer are determined; temperature and humidity effective compensation parameters are determined based on the temperature weight, the temperature data, the humidity weight and the humidity data of each layer; and determining a target compensation mode according to the equipment aging factor value, compensating the insulation resistance original value according to the temperature effective compensation parameter, the humidity effective compensation parameter and the target compensation mode, and determining a data quality score of the mutual inductor according to the humidity gradient and the electromagnetic interference value. The method has the remarkable advantages of high environmental adaptability, excellent anti-interference capability, low operation and maintenance cost and the like, and can effectively prolong the service life and improve the reliability of equipment.

The invention provides a plant capsule storage temperature and humidity cooperative control method, system and device and a medium, and relates to the technical field of storage management and control, and the method comprises the steps: carrying out the non-intervention digital twin simulation iteration simulation of a plant capsule warehouse, and obtaining the multi-working-condition coupling temperature and humidity monitoring data covering a whole storage scene; performing temperature and humidity gradient feature analysis to obtain a three-dimensional temperature and humidity gradient field; performing temperature and humidity sensor density self-adaptive deployment, and constructing a temperature and humidity sensing network; performing capsule moisture content conversion based on the moisture absorption isotherm piecewise function model, and outputting a full-bin capsule moisture content thermodynamic diagram; generating a distributed dehumidification task, executing dehumidification equipment energy consumption minimum strategy optimization, and outputting a distributed dehumidification instruction set; and space weight collaborative dehumidification is executed. According to the invention, the technical problem that the accuracy of humidity control is affected due to the fact that the humidity distribution complexity of a warehouse cannot be flexibly adapted to because fixed sensor layout and dehumidification equipment calling are generally adopted in the storage management and control in the prior art is solved.

The application relates to the technical field of pre-diagnosis and health management, and discloses a primary and secondary fusion ring network box fault diagnosis method and system. The method comprises the following steps: acquiring the micro-water content, gas pressure and local discharge amplitude in the air chamber of a ring network box, and performing time sequence arrangement to obtain a first multi-dimensional state sequence; then performing time sequence correlation analysis to obtain micro-water gas pressure discharge historical track features and condensation phenomenon features. When the condensation phenomenon exists, the cabinet door state data is acquired and abnormality is determined to obtain abnormal opening determination features; then humidity difference quantization is performed to obtain a humidity gradient, and the external humidity inflow duration is calculated. Subsequently, insulation deterioration input features are generated, and insulation performance deterioration degree values are mapped. Finally, hidden danger identification mapping and trend prediction are performed to obtain hidden danger type matching features, serious level mapping features and trend prediction results. The method can solve the problem of early hidden danger identification lag.

The invention discloses a warp-knitted single-needle-bed double-jacquard fabric. The warp-knitted single-needle-bed double-jacquard fabric comprises a bottom layer supporting structure of the fabric, the effect layer is located above the base layer, two jacquard combs weave different weave structures according to preset patterns, and differential moisture gradient partitions are formed by adjusting offset signal combinations of the two jacquard combs. The method has the characteristics of simplified process, customizable functions and high production efficiency, and is suitable for the fields of sportswear and the like.

The application discloses a kind of based on AI dynamic proportioning's fungus mushroom residue fermentation ingredient control method and ingredient device, it is related to biological fermentation technical field.The application includes: S1: multi-modal data acquisition: by near infrared spectrometer, metal oxide semiconductor gas sensor array and microwave resonance moisture sensor, obtain cellulose / lignin spatial distribution, spoilage characteristic and humidity gradient;S2: parameter determination: according to target threshold value, the three-dimensional feature of original fungus mushroom residue pile and time sequence result, determine the optimal parameter;S3: adjustment control: according to the optimal solution, real-time adjustment is carried out to fermentation temperature, auxiliary material addition and aeration amount.The application combines spatial feature and time sequence data, realizes the digital twin modeling of fermentation process, simultaneously by the three-dimensional target space of composting degree-conversion rate-energy consumption constructed, in combination with K-means clustering algorithm and B spline curvature optimization, determine the optimal parameter, shorten the fermentation parameter adjustment response time.

The invention provides a mildew-proof and moisture-proof method for an inner wall of a building in a coastal high-humidity environment, which belongs to the technical field of building construction and comprises the following steps of: establishing a dynamic prediction model for humidity distribution in a wall body by using a humidity gradient optimization diffusion algorithm, and automatically matching a corresponding moisture-permeable material according to a moisture content interval; designing a gradient moisture-proof layer composite structure comprising a moisture-proof layer transition layer and a humidity-regulating layer with the vapor permeation resistance greater than 200MNs per gram, identifying a key area susceptible to salt damage by adopting a shortest salt migration path algorithm, and determining a cold bridge risk position in combination with infrared thermal imaging; the method comprises the following steps: constructing a local reinforced insulating layer in a high-risk area, installing an electric heating film system to realize active temperature regulation, establishing a life prediction model based on damage mechanics, and automatically starting electric heating and local ventilation treatment measures according to relative humidity duration and a temperature difference value; the technical problem that inner walls of coastal buildings are prone to mildewing or being affected with damp is solved.

This invention relates to the field of automated control in food processing, specifically a temperature and humidity PID control system for the ripening process of alum-free wide rice noodles. The system includes: a sensing interface module, which receives environmental state data including air temperature and air humidity; physical characterization data including real-time sample weight and sample surface temperature; a kinetic analysis module, which, in conjunction with the sample surface temperature and the drying weight loss rate, calculates the humidity gradient index characterizing the difference between the center moisture content and surface moisture content of the wide rice noodle sample; a strategy decision module, which determines dynamic correction setpoints for air temperature and air humidity; and an execution control module, which drives the temperature and humidity adjustment mechanism to perform heating, humidification, or dehumidification actions, so that the actual temperature and humidity in the ripening chamber approach the dynamic correction setpoints. This invention effectively solves the problem of monitoring blind spots caused by neglecting the physical evolution of the sample.

The present application provides a method and system for evaluating the moisture permeability of concrete. The method first obtains moisture gradient change data within the concrete and performs moving average processing on the data to generate smoothed moisture diffusion data. Secondly, based on the diffusion data, the frequency offset data caused by humidity influence is measured in the microwave frequency band, and diffusion features are extracted from the offset data using phase locking technology. The diffusion features are then subjected to spatiotemporal correlation processing to identify hotspot patterns. Finally, pattern clustering processing is performed on the hotspot patterns, grouping them into multiple levels and outputting the concrete permeability rating. The technical solution provided by the present application not only ensures real-time and lossless capture of the microscopic dynamics of moisture migration, but also achieves zero-delay analysis of the true permeability dynamics, fundamentally resolving problems such as manual experience misjudgment and offline simulation inaccuracy.

The invention provides a method for accurately controlling fermentation parameters of truffle steamed stuffed buns, and belongs to the technical field of fermentation of the truffle steamed stuffed buns. An ultrasonic atomization humidification system and a circulating fan linkage device are configured to carry out spatialized environment adjustment based on a humidity gradient distribution model, a thermal imaging device and a high-resolution image acquisition device are installed to monitor temperature distribution and morphological change of the surface of the dough in real time, and a carbon dioxide concentration detection system is deployed to monitor gradient distribution of fermentation metabolites; dynamic optimization of the fermentation environment is achieved by executing self-adaptive parameter adjustment control, a fermentation end point judgment mechanism based on double indexes of the dough expansion rate and the carbon dioxide generation rate is established, and the technical problem that in the prior art, due to the fact that multi-dimensional parameter cooperative control precision is insufficient in the fermentation process, fermentation end point judgment is inaccurate is solved.

The invention provides a moisture-proof and dehumidification mining explosion-proof transformer, and relates to the technical field of explosion-proof transformers. The damp-proof and dehumidification mining explosion-proof transformer comprises a controller, a temperature sensor, a transformer body and an explosion-proof shell located on the outer wall of the transformer body. A double-circulation dehumidification system is constructed through the first dehumidification box and the second dehumidification box, and the problem that humidity is out of control due to saturation failure of a traditional static drying agent is solved. The two dehumidification boxes alternately execute a moisture absorption mode and a regeneration mode and are activated and regenerated through an anti-explosion PTC heating pipe, when the sealing performance of the shell is reduced or the external humidity suddenly changes, the internal humidity gradient is adjusted in real time, and the situation that the insulation performance is accelerated to be degraded due to long-term humidity is avoided; during maintenance, only the maintenance door needs to be opened, the old dehumidification box is pulled out along the sliding rail and replaced, the manual operation intensity in the underground narrow space is remarkably reduced, and meanwhile the situation that due to frequent disassembly and assembly, the air tightness of the anti-explosion shell is reduced is avoided.

The application discloses a kind of integrated grain low-temperature circulation continuous drying method, belong to grain drying technical field, comprising: feeding and homogenization;Low-temperature circulation drying and on-line identification drying stage;Obtain moisture removal efficiency of each round of drying;According to surface moisture change rate and speed reduction stage, judge the necessity of slow recovery;In slow recovery section, adopt database matching method, with grain variety, cycle round, internal moisture gradient and drying stage as query key, retrieve and correct output initial slow recovery duration;Through multi-round closed loop feedback, according to last round moisture removal efficiency, adjust actual slow recovery duration and drying parameters of this round;Cooling and discharging.The application is based on real-time moisture change and drying stage self-adaptive trigger slow recovery, utilizes database matching and round feedback dynamic optimization slow recovery duration, realizes the intelligent closed loop control of drying-slow recovery timing, effectively reduces grain breakage rate and burst rate, improves drying efficiency and multi-species applicability.

The present application relates to the technical field of chemical material storage stability simulation, in particular to a carbonic acid ethylene storage stability simulation method based on digital twinning, aiming to solve the problem that traditional evaluation cannot deeply couple dynamic factors such as moisture penetration, temperature and humidity change and product accumulation, cannot accurately restore the moisture gradient balance and product accumulation law in the container, and is difficult to predict the evolution of key quality indicators and failure boundaries, by constructing a digital twinning body basic model containing molecular structure and hydrolysis kinetics parameters, embedding dynamic moisture adsorption and reaction kinetics modules, calculating parameters such as moisture diffusion and penetration rate, integrating temperature and humidity sensor data, forming feedback by coupling heat and mass transfer and reaction kinetics equations, outputting stability attenuation risk index, predicting acid value, moisture content, color evolution trend and identifying failure threshold, and iteratively correcting model parameters combined with actual detection data to improve simulation accuracy.

The invention relates to the technical field of industrial automation control, and discloses a multivariable intelligent prediction control system for a dry konjak rice drying process, and the system comprises a multi-mode sensing and soft measurement field construction module which is used for collecting fusion data to construct a dynamic soft measurement field; the twin dynamics characterization module is used for establishing a model based on the soft measurement field and predicting a future material state; the physical field-virtual field mapping and anomaly tracing module is used for comparing a real state with a prediction state so as to diagnose an anomaly root cause; the adaptive reinforcement learning prediction control module is used for integrating all information to generate an optimal control action; and the dynamic edge calculation and model collaborative deployment module is used for providing calculation and resource scheduling for the above modules. According to the method, a dynamic soft measurement field is constructed by adopting a technical scheme of fusing multi-modal sensing data and deep learning, so that key states such as the internal moisture gradient and the surface crusting degree of the material can be quantified in a real-time and lossless manner.

The invention discloses a large biomass baking furnace feeding device, which belongs to the field of biomass dry distillation, and comprises a first feeding part and a second feeding part, the first feeding part comprises a first shell, a first feeding part rotationally connected into the first shell, a first gas interlayer formed in the first shell, a first exhaust end, a first gas inlet end, a first feeding port and a first discharging port, wherein the first exhaust end and the first gas inlet end are formed in the upper end and the lower end of the first shell correspondingly and communicate with the first gas interlayer, and the first feeding port and the first discharging port are formed in the upper end and the lower end of the first shell correspondingly. The first driving part is used for driving the first feeding part to rotate; after two-stage low-temperature treatment, part of moisture and part of oligomer in straw fibers are removed, cellulose and lignin networks are shrunk, materials become brittle, the temperature and humidity gradients inside and on the surface of the materials are reduced, the materials almost reach a physical equilibrium state before entering a main furnace, reaction is more uniform, and therefore temperature fluctuation of equipment is remarkably reduced.

The invention relates to the technical field of mushroom cultivation, in particular to a moderate intelligent control method for an edible mushroom and pleurotus eryngii cultivation workshop, which comprises a sensing grid unit, an execution unit, a control unit and a man-machine interaction unit, and further comprises the following steps: S1, partitioning and initializing; s2, data acquisition and monitoring; s3, performing partition decision and control; s4, performing stage conversion and linkage early warning; and S5, alarming and data recording. The workshop is divided into a plurality of independent control areas, and longitudinal and transverse sensor grids are deployed in each area, so that the defect that the whole workshop is regarded as a single and uniform environment in a traditional method is overcome, the system can sense and eliminate temperature and humidity gradients at different positions, independent and accurate regulation and control of the microenvironment of each area are realized, and the control accuracy of the whole workshop is improved. All mushrooms can grow under the optimal condition, and the uniformity, the commodity rate and the overall quality of the pleurotus eryngii are greatly improved.

This invention relates to the field of tobacco processing technology and discloses a method for moisture control and homogenization in tobacco sheet processing using a papermaking process. This method involves pre-treating tobacco leaves and tobacco sheets separately, pre-loosening and cutting the tobacco leaves into blocks, and independently controlling the moisture content of the tobacco sheets to a preset value that matches the tobacco leaves. The mixture is then uniformly blended according to a preset ratio to obtain a mixed tobacco material, and finally, after loosening and rehydration, it is shredded. This method solves the problems of large differences in physical properties and hygroscopicity between tobacco leaves and tobacco sheets in existing synchronous shredding processes, leading to moisture gradients, easy sheet slippage, low shredding rate, uneven moisture content in tobacco shreds, and difficulty in controlling cigarette quality. It achieves matching of moisture content between tobacco leaves and tobacco sheets, synchronized and unified processing characteristics, improves shredding rate, balances tobacco moisture content, reduces internal and external quality risks in cigarette products, and stabilizes cigarette production quality.

The invention relates to the technical field of agricultural intellectualization, in particular to an intelligent regulation and control method, system and equipment for a rare fungus planting room and a storage medium. The method comprises the following steps: acquiring multi-dimensional coupling environmental parameters in a planting room, wherein the parameters integrate environmental data such as temperature and humidity gradients and matrix conductivity of different areas and hypha activity-microenvironment coupling parameters such as mushroom stick ATP content and hypha density; comparing the dynamic growth model library with a dynamic growth model library integrating multi-strain data and historical feedback; and outputting multi-dimensional cooperative regulation and control instructions for fan vortex intensity, light supplementing phase difference, spraying time sequence, nutrient solution compensation coefficient and the like in different areas according to the result. Accurate coupling regulation and control of environment and biological activity are achieved, the yield stability and quality uniformity of rare fungus planting are effectively improved, energy consumption per unit yield is reduced, and technical support is provided for large-scale standardized planting.