101 results about "Moisture gradient" patented technology

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 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 provides a concrete regulation and control system and method integrating heat recovery, spraying and gradient control, and relates to the technical field of concrete curing, and the concrete regulation and control system comprises a temperature sensing element and a humidity sensing element which are mounted on reinforcing steel bars in a concrete structure in a layered manner in the depth direction; the cooling water circulating system comprises a water pump and a cooling water pipe, and the cooling water pipe is arranged in the mass concrete structure and externally connected with a variable frequency circulating pump; the double-water-tank system is matched with the heater to realize graded regulation of water temperature; the automatic spraying system is connected with the integrated electric heating module; the heat recovery and circulation assembly is connected with an outlet of a cooling water pipe in the concrete, recovers concrete hydration heat brought out by the cooling water pipe, and transfers heat of high-temperature cooling water with the temperature being 50 DEG C or above to the phase change heat storage tank; the central control unit continuously receives and records monitoring data of the temperature sensor and the humidity sensor and analyzes the monitoring data in real time, and when the temperature gradient or the humidity gradient exceeds the limit, a gradient field control instruction is automatically triggered to achieve energy efficiency maximization.

The invention relates to the technical field of industrial control, and discloses a real-time dynamic tuning system for a microwave drying process, which is characterized in that temperature distribution, microwave power intensity, humidity gradient and material deformation parameters in a drying cavity are acquired in real time, and time-space alignment and noise suppression are carried out on data of a multi-source sensor based on a Kalman filtering algorithm; generating a drying state matrix, generating a three-dimensional regulation and control instruction containing microwave emission frequency, power partition and drying time according to the drying state matrix by adopting a mixed algorithm of model predictive control and fuzzy logic, and taking the deviation between a final moisture content detection value of the material and a model predictive value as a loss function through an online error back propagation model. The weight coefficient of the microwave-thermal-mass transfer coupling model is dynamically corrected, the microwave energy ratio is optimized based on the improved particle swarm optimization, and the three-dimensional gradient field intensity distribution matched with the material morphology is generated according to the three-dimensional regulation and control instruction, so that the efficiency of the microwave drying process during real-time dynamic regulation and optimization is improved.

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 discloses a temperature and humidity sensor data association analysis method based on deep learning, and relates to the technical field of data association analysis. Comprising the following steps: calculating a temperature and humidity gradient difference value of any two adjacent nodes based on a continuous temperature and humidity data sequence acquired by a sensor, and performing partition division in combination with a geographic distance; constructing a correlation coefficient matrix based on a historical time window for all sensor nodes in the same partition, and dividing the nodes into a plurality of correlation groups with high correlation; dividing a master node and a slave node for each association group; and generating a redundancy substitution matrix based on the correlation coefficient matrix, and when the main node is in an abnormal state, screening a standby node as a new main node in combination with the real-time data difference degree, and maintaining the stability of an inference link. The method effectively reduces the node energy consumption and communication redundancy while guaranteeing the prediction accuracy and reliability, is suitable for a large-scale deployment scene, and is especially suitable for a temperature and humidity sensing network analysis task in an edge environment.

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 relates to a dried beancurd stick drying method, device, equipment and medium applied to a dried beancurd stick drying oven, and the method comprises the following steps: obtaining real-time temperature and humidity data of a plurality of monitoring areas in the oven at the initial drying stage of dried beancurd sticks, and generating a first hot air circulation parameter adjustment instruction; and controlling the baking oven to execute a first hot air circulation mode, collecting real-time temperature fluctuation and humidity gradient data and generating an evaluation index. And if the evaluation index does not reach the threshold value, multi-stage parameter readjustment operation is triggered to generate a second hot air circulation parameter adjustment instruction. Controlling the baking box to switch to a second hot air circulation mode, monitoring the surface morphology change data of the dried beancurd sticks, and generating a drying termination instruction to end the drying process according to the matching degree with the standard curve, thereby improving the drying quality and efficiency of the dried beancurd sticks.

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 a method and system for gradient drying of butyronitrile gloves after impregnation in the field of intelligent manufacturing, and the method comprises the steps: obtaining surface and internal moisture content data of an adhesive film through a sensor array, generating a real-time moisture distribution matrix, and determining a moisture gradient change trend; if the moisture gradient change trend exceeds a preset threshold value, calculating a local moisture evaporation rate according to the distribution matrix to obtain a dynamic temperature and humidity regulation and control parameter; obtaining an adhesive film surface image through a high-resolution imaging system, detecting micro-crack and white point defect areas, and determining defect distribution characteristics; adjusting power distribution of the composite heating system according to the lowest energy consumption operation parameters, and generating an efficient drying operation mode; updating data of the dynamic regulation and control parameters and the defect distribution characteristics are obtained through a feedback control algorithm, and final drying process parameters are determined; and generating a production control instruction from the final drying process parameters, and outputting the production control instruction to a drying equipment controller to finish uniform diffusion of moisture of the adhesive film and elimination of surface defects.

The invention provides a water vapor infrared spectrum humidity correction method based on big data analysis, and relates to the technical field of near infrared spectrum humidity measurement. Through introduction of synchronous acquisition of three-dimensional porosity distribution and surface humidity gradient of a porous material and combination of distributed feature engineering and dimension reduction processing, the humidity of the surface of the porous material is corrected; a big data regression and classification model for jointly outputting a spectral humidity correction coefficient and a micro-crack classification result is constructed, and organic fusion of six technical elements including micro-pore structure parameter acquisition, surface humidity gradient acquisition, big data feature extraction, distributed regression modeling, correction formula construction and micro-crack detection is realized; the robustness of the corrected spectral characteristics and the accuracy of crack detection are remarkably improved, and the technical requirements of online defect diagnosis of porous ceramics in a high-humidity environment are met.

The invention discloses a mushroom residue fermentation batching control method based on AI dynamic proportioning and a batching device, and relates to the technical field of biological fermentation. Comprising the following steps: S1, multi-modal data acquisition: acquiring cellulose / lignin spatial distribution, decay characteristics and humidity gradient through a near-infrared spectrometer, a metal oxide semiconductor gas sensor array and a microwave resonance moisture sensor; s2, parameter determination: determining optimal parameters according to a target threshold value, the three-dimensional characteristics of the original mushroom residue stockpile and a time sequence result; and S3, adjusting and controlling: according to the optimal solution, adjusting the fermentation temperature, the auxiliary material addition and the aeration rate in real time. According to the method, the spatial features and the time series data are combined, digital twin modeling of the fermentation process is achieved, meanwhile, the optimal parameters are determined through the constructed decomposition degree-conversion rate-energy consumption three-dimensional target space in combination with the K-means clustering algorithm and B spline curvature optimization, and the fermentation parameter adjustment response time is shortened.

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 relates to the technical field of water consumption regulation and control, in particular to a laying hen house intelligent drinking water scheduling and water-saving control method integrated with multi-source sensing, which comprises the following steps of: acquiring a chicken flock space-time distribution map in real time through a positioning sensing network, and constructing a partition grid in combination with drinking water line pressure pulsation data, dividing the chicken house into a plurality of regulation and control units with independent hydraulic characteristics based on the partition grids; based on the triggering frequency sequence of the chicken beak touch sensor in each regulation and control unit, generating a water drinking behavior pattern matrix, and meanwhile, combining environment temperature and humidity gradient data to establish a water demand compensation function of each subarea; and according to the water drinking behavior mode matrix and the water demand compensation function, driving the micro-channel water-saving valve corresponding to each subarea to execute a differential water supply mode, and synchronously adjusting the on-off time sequence of the aeration device of the subarea. According to the invention, the real-time dynamic regulation of the flow is realized, the physiological water demand and the system water-saving target are effectively balanced, and the intelligence and robustness of the drinking water control strategy are obviously 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 relates to the technical field of intelligent control, and discloses an intelligent insole and a control method. The method comprises the steps that temperature data, humidity data and contact resistance data of a half sole area and an arch area in the intelligent insole are collected, and a foot environment parameter matrix is formed; performing micropore activity calculation and distribution analysis on the foot environment parameter matrix to obtain current distribution output parameters; calculating a humidity gradient ratio of a half sole area to an arch area according to the current distribution output parameters, and implementing a coordinated direct current control strategy to obtain a real-time current control parameter matrix; and inputting the real-time current control parameter matrix into an adaptive fuzzy control model for gradient descent optimization processing to obtain an optimal current intensity parameter and an optimal pulse frequency parameter. The foot environment is regulated and controlled according to needs, and meanwhile the stability of the humidity of the contact surface is guaranteed.

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 invention discloses a kelp drying moisture dynamic balance regulation and control method and system based on multi-source sensing. The method comprises the steps that data are collected in real time through a multi-source sensor in drying equipment; identifying a drying stage in real time based on the obtained temperature and humidity time sequence data, and dynamically adjusting process parameters according to data difference; performing space-time calibration compensation on the kelp surface temperature distribution data and the kelp surface image data; constructing a moisture distribution prediction model, and obtaining kelp moisture distribution gradient data; a local area with the moisture content higher than the global average value is recognized as a high-moisture area, and targeted intensified drying is conducted on the high-moisture area by controlling a subarea heating unit; and water distribution gradient data are obtained, and if the whole-region water gradient difference is smaller than a threshold value and the global average water content is smaller than the threshold value, drying is completed. The kelp drying device has the advantages that the drying process is monitored in real time and dynamically adjusted through the sensor, kelp moisture distribution is accurately controlled, the drying efficiency and quality are improved, and uniform drying of kelp is ensured.

The invention belongs to the field of hydrogel production, and relates to a complete set of hydrogel particle production equipment and a production method, the complete set of hydrogel particle production equipment comprises: a data acquisition module for acquiring oxygen concentration data and humidity data; the oxygen analysis module is used for determining whether the single freezing and thawing cycle is qualified or not based on the single-cycle oxygen concentration difference of the oxygen concentration data; the data processing module is used for determining whether the structure of the hydrogel is stable or not based on the concentration difference change characterization parameters after the three times of freezing and thawing cycles, and determining and adjusting the freezing duration or the drying duration according to the difference value; the humidity analysis module is used for determining whether the humidity uniformity is qualified or not based on the humidity gradient value of the humidity data, and determining an environment box with unqualified humidity according to the humidity change rate of the humidity data; the data adjusting module is used for determining and adjusting the temperature based on the ratio of the humidity change rate to the preset humidity change rate or determining and adjusting the fan rate based on the relative difference between the humidity change rate and the preset humidity change rate, and the stability of the hydrogel structure is improved.

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 present invention discloses a sizing and laminating device and a usage method for preparing a medical nursing pad, which relates to the technical field of laminated products. The sizing and laminating device includes: an equipment frame, a top conveying mechanism, a core layer conveying mechanism, and a bottom conveying mechanism that are sequentially installed inside the equipment frame from top to bottom, and a first laminating mechanism installed inside the equipment frame near one end; two sizing mechanisms are arranged between the first laminating mechanism and the core layer conveying mechanism; by increasing the humidity of the core layer base material, the formed liquid bridge network and humidity gradient not only enhance the bonding force between fibers, reduce fiber brittleness, but also optimize the penetration of glue in the deep layer of fibers, improve the interfacial bonding force, enhance the bonding strength of the nursing pad after sizing, and at the same time eliminate the electrostatic adsorption effect, enable SAP particles to be evenly embedded in the fiber network, avoid agglomeration and voids. The whole process has a high degree of automation and significantly improves production efficiency.

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.