2187 results about "Water content" patented technology

The invention relates to the technical field of model construction, and discloses a neural network-based frozen soil unfrozen water content detection model construction method and system. The method comprises the following steps: carrying out segmented sampling test on a clay sample in a temperature interval of 0 DEG C to-20 DEG C to obtain a multi-dimensional original data set, and carrying out standardization and principal component analysis on the data set to obtain a standardized feature vector; and performing three-stage classification marking on the feature vectors to obtain a training data matrix. A deep neural network is adopted to carry out five-fold cross validation training, and a prediction model of three hidden layers is constructed. And performing correction calculation on model output according to soil mineral composition and porosity parameters, and finally identifying an abnormal value through root-mean-square error analysis and a three-time standard deviation principle to obtain a standardized prediction result. According to the method, the mapping relation between the thermal parameters and the unfrozen water content is established, correction is carried out in combination with the soil body characteristic parameters, and the technical problem that the prediction precision of the unfrozen water content is not high in the prior art can be solved.

The invention belongs to the technical field of intelligent agriculture, and discloses a canopy-atmospheric environment information-based soil water content prediction method and system, and the method comprises the steps: setting a canopy and atmospheric environment monitoring unit in a field, and synchronously collecting the canopy temperature, wind speed, relative humidity, and six-dimensional environment parameters of atmospheric temperature, wind speed and relative humidity; the crown temperature difference is calculated after preprocessing; the method comprises the following steps: constructing a training set by utilizing measured data of soil relative water content, constructing a soil water content prediction model by adopting a random forest algorithm, screening and confirming an optimal prediction model through grid search and cross validation, and screening key features by combining an SHAP value; the water demand is automatically calculated according to a pre-established crop whole-growth-period drought stress threshold table and a dynamic irrigation decision formula, and meanwhile, the adaptation of a general model to a regional specific model is realized by constructing an environmental parameter-actually measured water content database and transfer learning, so that the soil water content state is accurately predicted, and the soil quality is improved. And a scientific basis is provided for precise irrigation.

The present disclosure relates to the technical field of landslide hazard model tests, and in particular to a landslide model test method and device for realizing multi-variable synchronous monitoring. In the test device, a soil slope simulation unit is configured to pile up a soil slope and simulate different inclinations of the slope. A rainfall simulation unit is configured to simulate rainfall of different intensities and induce a landslide. A runoff-seepage separation unit is configured to realize separation of runoff from seepage of the slope under the effect of rainfall. A monitoring module is configured to monitor runoff and seepage flow rates of the slope, changes in water content and pore water pressure within the slope, and a morphological change of the slope under the effect of rainfall, to obtain a mechanism of rainfall-induced landslide deformation and damage based on changes in the flow rate.

The invention discloses an intelligent irrigation control method and system based on meteorological information, and relates to the technical field of irrigation control, an area to be irrigated is divided into a plurality of sub-areas, and future rainfall (first rainfall) is predicted through a preset meteorological early warning model; acquiring water absorption data of each sub-region, calculating a water absorption coefficient, and determining absorbable rainfall (second rainfall) in combination with the first rainfall; and judging the water consumption of each sub-region according to the crop growth data and the historical data, and comparing the water consumption with the second rainfall. If the water consumption is greater than the second rainfall, the sub-region needs to be irrigated; according to the method, the soil water content of each sub-region can be finely judged, and whether rainfall meets the water demand or not is evaluated, so that whether irrigation is needed or not is judged, excessive irrigation and water resource waste are avoided, meanwhile, it is ensured that crops obtain enough water, water resource management is optimized, and the crop growth effect and agricultural production efficiency are improved.

The invention relates to the technical field of slope engineering, in particular to a settlement deformation prediction method and system for a reinforced soil slope building structure. The method comprises the following steps: acquiring a soil body infiltration line position parameter of a reinforced soil slope, an interface friction coefficient of a reinforced material and a soil body, a soil body grain grading curve and environment temperature and humidity duration information, and obtaining initial characteristic data of a slope system state; constructing a heat-force-water multi-field coupling monitoring network in the soil-reinforced material interface area according to the initial characteristic data of the slope system state, and obtaining the interface shear stress, the interface normal strain, the pore water pressure gradient and the temperature gradient of each monitoring point to obtain interface action characteristic data. According to the method, the environment disturbance probability density model based on the temperature fluctuation and the sudden change of the water content is constructed, the influence of a complex environment on the slope stability can be quantitatively described, and the robustness of the model is improved.

A slope safety and stability analysis method based on an integrated sensor and an intelligent algorithm comprises the following steps: acquiring initial values of geometric parameters (including height, gradient and width) of a slope and basic physical parameters (weight, internal friction angle and cohesive force) of a soil body through a method of combining in-situ static sounding and an indoor test; an improved integrated sensor slope state monitoring device is adopted to continuously obtain state parameters such as water content, matrix suction, internal three-way displacement, an inclination angle and soil pressure of a slope soil body, and multi-dimensional dynamic monitoring is achieved; basic physical parameters of a soil body are updated in real time based on data collected by a sensor, and the slope stability safety coefficient is predicted through a semi-supervised learning model; safety early warning is triggered in a grading mode according to prediction results, model prediction values and measured values are recorded and analyzed, and the system evaluates the long-term stability and applicability of the model; through multi-source data fusion and intelligent analysis, theoretical support and technical guarantee are provided for safety monitoring and early warning of the loess slope.

The invention relates to an agricultural biomass characteristic intelligent detection method, system and device based on multi-frequency conductance coupling and a medium, and the method comprises the following steps: applying an electric excitation signal to an agricultural biomass sample, and synchronously collecting multi-physics coupling response data; based on the multi-physics field coupling response data, constructing a multi-scale equivalent circuit model comprising a resonance unit, a constant phase unit and a diffusion impedance unit; synchronously optimizing a resonance unit parameter, a constant phase unit parameter and an impedance unit parameter of the multi-scale equivalent circuit model through a Bayesian joint inversion algorithm to obtain an optimal parameter combination; and according to the optimal parameter combination, calculating a preliminary detection result of biomass components containing cellulose crystallinity, lignin crosslinking degree and water content, combining the collected environment temperature and humidity sensing data to implement dynamic compensation, and outputting a final detection result. Therefore, the detection precision, the environment robustness and the operation reliability are synergistically improved in three aspects of hardware design, model construction and algorithm optimization.

The invention belongs to the technical field of oil and gas production and development, and discloses a sand production pressure difference and sand production quantity quantitative prediction method suitable for a high-temperature and high-pressure sandstone reservoir, which comprises the following steps: calculating static rock mechanical parameters of a target well; predicting initial crustal stress; establishing a porosity and permeability dynamic evolution model; establishing a three-dimensional finite element model; establishing a seepage stress coupling transient nonlinear finite element equation; applying well bottom pressure drop to simulate production, and determining sand production pressure difference; and establishing a sand production rate prediction model, and quantitatively predicting the sand production rate. According to the method, factors such as pore permeability stress, temperature change and water content influencing rock strength are comprehensively considered, a three-dimensional finite element model is established, a seepage stress coupling finite element equation and solving steps are established based on a reservoir elastic-plastic consolidation theory, critical plastic strain is introduced to quantitatively characterize the sand production risk, a sand production prediction model is established, and the rock strength is predicted. And finally, quantitative and accurate calculation and scientific pressure control of the critical sand production pressure difference and the sand production amount are realized.

The invention provides a seasonal frozen earth region roadbed stability evaluation method, a seasonal frozen earth region roadbed stability evaluation device and a medium, and relates to the technical field of seasonal frozen earth region roadbed stability evaluation. Meanwhile, performing a freeze-thaw cycle experiment in a laboratory, and fitting to obtain a heat conduction coefficient and a moisture diffusion coefficient of the soil sample; inputting field data and experimental parameters into the finite element model, simulating hydrothermal transfer and mechanical behaviors under different seepage and drainage grating arrangement conditions, and analyzing dynamic change rules of a temperature field, a water content field and frost heaving stress; then, a hydrothermal dynamic behavior and rib-soil interface behavior prediction model is trained based on an LSTM network architecture, and hydrothermal changes and mechanical properties of the roadbed under different conditions are predicted; and finally, based on an output result of the prediction model, calculating a roadbed stability index by combining a comprehensive stability evaluation model.

The invention relates to the technical field of smart city operation, and discloses a pressure regulation and loss reduction method based on steam simulation and condensate water analysis, comprising the following steps: step S1, collecting operation parameters of a steam pipe network system; s2, converting the preprocessed operation parameters into scale space parameters; s3, establishing a condensate water source term equation, a heat source term equation and a condensate water generation model to obtain pressure, temperature and condensate water content; s4, solving the optimal pressure adjustment amount and the condensate water adjustment amount by combining the pressure and condensate water coupling matrix, and optimizing the circulation degree; and S5, correcting model parameters in the condensate water source term equation, the heat source term equation and the condensate water generation model based on a comparison result. By coupling and simulating the condensate water source item, the heat source item and the generation model, dynamic distribution of condensate water can be accurately analyzed, and the problems that in the prior art, calculation efficiency and model precision are difficult to balance, and dynamic coupling is lacked are solved.

The invention discloses a shaft surrounding rock deformation prediction method and device based on fluid-solid coupling linkage simulation, and the method comprises the steps: 1, describing the influence of rainwater permeation on surrounding rock deformation through the change of water content, constructing and forming a permeation-surrounding rock deformation model, and constructing and forming a scouring-surrounding rock deformation model, building a vertical shaft excavation model under the action of rainwater; 2, performing multi-scale linkage simulation on the permeation-surrounding rock deformation model, the scouring-surrounding rock deformation model and the vertical shaft excavation model to obtain surrounding rock deformation data; 3, taking the surrounding rock deformation data as a training set to train a TCN-LSTM neural network model, and obtaining a shaft surrounding rock deformation prediction model under the rainwater effect; and 4, acquiring real-time surrounding rock deformation data, inputting the real-time surrounding rock deformation data into the shaft surrounding rock deformation prediction model, and outputting a prediction result. The shaft surrounding rock deformation prediction precision, efficiency and application flexibility can be improved, and meanwhile the implementation complexity and the calculation amount are reduced.

Methods, apparatus, and storage medium for providing real-time asphalt density and / or moisture content prediction with ground penetrating radar. A method includes using raw data from a ground penetrating radar sensing an asphalt concrete at a location; processing the raw data to obtain processed data; determining an asphalt density of the asphalt concrete at the location based on the processed data according to an asphalt density prediction model; determining a compaction status of the asphalt concrete at the location based on the asphalt density and a target compaction threshold; and outputting the compaction status of the asphalt concrete at the location to an operator for determining whether to continue or stop compacting the asphalt concrete at the location. In another method, moisture content for cold recycling and existing asphalt concrete pavement is predicted in real-time from using raw from data of ground penetrating radar mounted on a vehicle.

The invention discloses a method and a device for testing moisture migration characteristics of frozen soil under low-temperature nuclear magnetic triaxial seepage, and relates to the technical field of frozen soil testing. In order to solve the problems that in the prior art, compatibility control of freezing and seepage cannot be achieved, and whole-process evolution of frozen soil moisture migration characteristics is difficult to dynamically capture, the scheme comprises the following steps that the real confining pressure, axial pressure and seepage speed of the environment where a soil sample is located are simulated; collecting a nuclear magnetic resonance image and an overall and layered T2 spectrum of the soil sample before freezing under the action of seepage; gradually freezing the soil sample based on different temperature gradients, and collecting a nuclear magnetic resonance image and an overall and layered T2 spectrum of the soil sample under the seepage and freezing coupling action in real time; data are collected according to the whole soil sample freezing process, and the evolution law of water migration characteristics in the soil body freezing process is analyzed. According to the invention, the whole-process, visual and nondestructive detection is realized, and the whole-process evolution rule of water migration characteristics such as unfrozen water content and pore cracks in the frozen soil under the seepage and freezing coupling action can be accurately captured.

The present invention belongs to the field of resource utilization of building materials and solid waste, and relates to a red-mud-based cementing material based on efficient drying, component homogenization and activity improvement, and a preparation method therefor. The preparation method comprises: adding a filter aid to red mud to carry out sedimentation, then subjecting same to filter pressing until the water content is 14-16%, then drying the solid material, which has been subjected to filter pressing, until the water content is 4% or below, and finally grinding same to obtain the product. The filter aid comprises the following raw materials: 10-30 parts of polyaluminum chloride, 5-15 parts of polyaluminum sulfate, 1000-1200 parts of blast furnace slag or fly ash, 700-900 parts of steel slag, 400-600 parts of carbide slag or alkaline residues, and 300-400 parts of desulfurized gypsum or phosphogypsum or fluorgypsum. By means of the present invention, the dehydration efficiency of red mud can be improved, the red-mud-based cementing material can also be prepared in one step; the preparation process for the red-mud-based cementing material is simplified; and the prepared red-mud-based cementing material has the advantages of a high mechanical strength, high durability and erosion resistance.

The invention discloses a soil water content inversion method and system based on L-band dual-polarization data and a medium, and belongs to the field of remote sensing technology and environment monitoring. The system comprises an SAR data acquisition module, an optical data processing module, a vegetation scattering separation module, an inversion model construction module, a spatial distribution calculation module and a risk assessment module, wherein the SAR data acquisition module is used for regularly acquiring L-band dual-polarized SAR data of a target area; the optical data processing module assists in identifying and separating vegetation scattering components by calculating vegetation indexes; the vegetation scattering separation module is used for extracting pure soil back scattering signals; the inversion model building module is used for training and optimizing a soil water content inversion model based on the pure soil back scattering signals and field sampling data; the spatial distribution calculation module is used for calculating a spatial distribution diagram of the surface soil water content of the target area; and the risk assessment module is used for carrying out landslide risk grade division and early warning management.

The invention discloses a landslide early warning method and system, and the method comprises the steps: carrying out the field testing of a sampling point through a multi-parameter soil rapid detection device, obtaining the index data of the water content, density, particle size distribution and the like of the soil, uploading the data to a cloud server in real time through a wireless transmission module, and achieving the comprehensive evaluation of the soil indexes; according to the soil evolution prediction result, combined with a preset landslide risk threshold value, the landslide risk grade is dynamically evaluated, if the predicted landslide possibility exceeds the threshold value, an early warning signal is generated, and the early warning signal is pushed to related departments and personnel in real time through a wireless transmission module; according to different geological conditions and landslide types, a plurality of soil property-environment factor coupling analysis sub-models are pre-established, and according to the geological features of the current sampling point, the optimal sub-model is dynamically selected to perform landslide risk pre-judgment, so that the applicability and accuracy of early warning are improved.

The invention relates to the technical field of land degradation monitoring, in particular to a remote sensing comprehensive monitoring method for land degradation of a coal mining subsidence area. The method comprises the following steps: establishing a prediction model, obtaining a predicted soil erosion intensity sequence, a predicted primary productivity sequence, a predicted surface water content index sequence and a predicted arid remote sensing monitoring index sequence by utilizing the prediction model, and then respectively obtaining a first trend index, a second trend index, a third trend index and a fourth trend index at the current moment; obtaining a first index, a second index, a third index and a fourth index by using the soil erosion intensity, the primary productivity, the surface water content index, the arid remote sensing monitoring index, the first trend index, the second trend index, the third trend index and the fourth trend index at the current moment; and obtaining a land degradation degree index of the coal mining subsidence area based on the first index, the second index, the third index and the fourth index at the current moment. According to the method, the land degradation degree of the coal mining subsidence area can be accurately judged.

The invention discloses a water storage and drainage system capable of keeping slope stability. The water storage and drainage system comprises a water drainage pipe assembly and an automatic water supplementing assembly. The drainage pipe assembly comprises a plurality of transverse assembly type pipes, a plurality of oblique assembly type pipes and a plurality of plastic capillary pipes, the transverse assembly type pipes and the oblique assembly type pipes are perpendicularly communicated in a staggered mode, and the transverse assembly type pipes are communicated with the plastic capillary pipes at the corresponding positions. A sand cushion layer and a perlite layer are laid on the slope surface of the side slope; the automatic water supplementing assembly comprises a water pumping machine, a plurality of water supplementing pipes and a plurality of wireless temperature and humidity sensors. A water outlet of the water pumping machine is connected with the water supplementing pipes through a water conveying pipeline. The water pumping machine is provided with an intelligent automatic sensing system; the water storage and drainage system capable of keeping the stability of the side slope further comprises a plurality of assembly type concrete sash beams laid on the perlite layer, and the water supplementing pipe is connected with the rotating spray heads. A soil dressing layer used for planting cold-resistant water-retaining vegetation is laid in the planting area of the fabricated concrete sash beam. The water content of the side slope can be effectively adjusted and controlled, so that the stability of the side slope is improved.

The invention provides a power transmission and transformation project reinforced concrete corrosivity evaluation method and system, and relates to the technical field of civil engineering durability evaluation.The method comprises the steps that temperature data of a project location and the total volume, the water content and the pore volume of reinforced concrete are collected, and a freeze-thaw failure index formula is constructed; the product type is judged according to the measured sulfate concentration, different sulfate erosion index formulas are constructed in combination with related data, and the magnesium ion concentration is independently considered in the marine environment; constructing a chlorine salt erosion index formula according to the chloride ion concentration; extracting data from the research report to construct a carbonization erosion index formula; and giving a weight to each erosion type to establish a comprehensive corrosivity evaluation index formula, and judging the erosion degree according to a result. By means of the method, various erosion factors can be comprehensively considered, the erosion degree can be effectively judged according to the evaluation result, and a key basis and scientific guidance are provided for durability guarantee, protective measure making and maintenance decision making of the reinforced concrete structure of the power transmission and transformation project.

The utility model belongs to the technical field of geological disaster control, and discloses an anchoring device for geological disaster control. Comprising an anchoring pipe, a flowerpot, a rubber ring, a supporting rod and an inserting rod, vent holes are formed in the outer side of the flowerpot in an array mode, a mounting hole is formed in the bottom of the flowerpot, a filtering cover is mounted in the mounting hole, and the bottom of the filtering cover is attached to the anchoring pipe and the top of a mounting ring. The screw rod, the rotating ring, the transmission rod and the supporting rod are additionally arranged, the supporting rod is unfolded when the screw rod rotates, the anti-skid and anti-falling effects of the anchoring pipe are improved, the flowerpot and the anchoring pipe are fixed through the bolt, flowerpots of different sizes can be replaced according to plants of different thicknesses, the bolt is covered with the rubber ring, the bolt can be prevented from rusting, and the service life of the flowerpot is prolonged. The filter cover and the rotary drum are added, and when the water level of underground water rises, the underground water seeps through the filter screen of the rotary drum and the filter cover, so that the water content of slope soil is reduced, the shear strength of the soil body is improved, and the slope stability is further improved.

The invention discloses a self-healing concrete intelligent preparation method and system based on a dynamic optimization algorithm. The method comprises the following steps: S1, feeding: feeding materials to a premixing module by a raw material bin and a repairing agent carrier storage bin; s2, premixing: monitoring the water content of the aggregate fed into the raw material bin in real time by a premixing module, and dynamically adjusting the rotating speed of the premixing module through the water content; s3, gradient stirring: after premixing, feeding the materials into a gradient stirring module, and sequentially stirring; s31, firstly entering a low-speed paddle for stirring, monitoring the stirring resistance moment and the slurry viscosity distribution in real time, and dynamically adjusting the rotating speed of the paddle according to the torque-viscosity relationship; s32, performing ultrasonic homogenization on the materials subjected to low-speed stirring, monitoring the dispersity of each substance in low-speed stirring in real time through an identification camera, calculating the concentration gradient, monitoring the particle size distribution of a carrier at a discharge port of an ultrasonic homogenizer to obtain the particle size of a target aggregate, and dynamically adjusting the ultrasonic frequency according to the particle size of the target aggregate to obtain the target aggregate. And dynamically adjusting ultrasonic power and action time according to the concentration gradient.

The invention discloses an automatic deviation rectifying method for long-distance jacking of a pipe-jacking tunneling roadway, and relates to the technical field of automatic deviation rectifying of pipe tunneling, which comprises the following steps: collecting the compactness, water content and hardness data of a soil layer in a tunneling path in real time through a multi-point distributed sensing device, and calculating the deviation of the pipe-jacking tunneling roadway in combination with soil parameters and pipe-jacking equipment propulsion mechanical characteristics; and generating a geological condition profile map, constructing a resistance distribution model, predicting resistance change trends under different geological conditions, and establishing a correction early warning mechanism. According to the invention, through real-time stress monitoring, multi-point sensing and intelligent feedback control, the accuracy, efficiency and complex geology adaptability of pipe-jacking tunneling are improved. The equipment can quickly identify resistance abnormity, dynamically regulate and control propulsion in real time, reduce the influence of asymmetric force, and reduce personal error and construction loss. And in combination with a geological profile map, the equipment actively deals with soil layer changes through automatic deviation correction, the clamping stagnation problem is solved, safety and continuity are guaranteed, and risks and cost are reduced.

The invention discloses a coal moisture content and spatial distribution analysis method and system based on an image spectrum, and belongs to the technical field of coal moisture content analysis, and the method comprises the following steps: obtaining a visible light image and a hyperspectral image of to-be-detected coal; semantic segmentation is performed on the visible light image, and the visible light image is divided into a dry area and a water-containing area; the method comprises the following steps: extracting hyperspectral data of each pixel point in a hyperspectral image of a water-containing area, extracting spectral features of a plurality of wavebands by using a sliding window, and dynamically adjusting through an attention mechanism to extract spectral features related to moisture; constructing a sample sequence by taking the spectral feature and the spatial feature of each pixel point of the water-containing area as samples, inputting the sample sequence into a Transform model, and outputting a feature matrix; pooling the feature matrix, inputting the pooled feature matrix into a least square SVM model, and outputting the water content corresponding to each pixel point of the water-containing area; and performing graded developing treatment according to the water contents of different pixel points to obtain accurate coal water and spatial distribution conditions thereof.

The invention discloses an expansive soil free expansion rate and permeability coefficient field test device and method, relates to the technical field of expansive soil tests, and aims to solve the problems that in the prior art, expansive soil expansion potential judgment standards are not unified, and test data discreteness is large. Comprising a cutting ring assembly, a moisture content measuring assembly, a displacement measuring assembly and a water supply assembly. The cutting ring assembly is used for fixing a test soil body; the moisture content measuring assembly monitors the moisture content of the soil body in real time; the displacement measuring assembly records soil surface and deep displacement; the water supply assembly controls water injection. The test method comprises a test method and a numerical analysis method, the permeability coefficient and the free expansion rate of the soil body are calculated by injecting water and monitoring the moisture content and the displacement change of the test soil body, a moisture content curve is fitted by combining numerical analysis, the expansion coefficient and the saturated moisture content are solved, and the free expansion rate of the soil body is finally determined. The free expansion rate and the permeability coefficient of the expansive soil are rapidly and accurately measured on site, the expansion potential is judged, and a reliable basis is provided for engineering application.

The invention discloses a water conservation amount calculation simulation method based on an RCCC-WBM hydrological model, and the method comprises the steps: collecting hydro meteorological data in a research basin, calculating the average rainfall, air temperature and water surface evaporation amount of a lunar surface, and inputting the average rainfall, air temperature and water surface evaporation amount into the model; calculating and researching the average soil water content, the actual evapotranspiration, the surface runoff, the snow melting runoff and the underground runoff of the watershed for many years by adopting an RCCC-WBM model; according to the monthly-scale water source conservation amount calculation formula and the annual-scale water source conservation amount calculation formula, the monthly-scale water source conservation amount and the annual-scale water source conservation amount of the drainage basin are calculated respectively. The water conservation amount calculation formula provided by the invention can effectively avoid the negative value problem in water conservation evaluation, and the dynamic process of the basin water conservation amount can be calculated through the state variable and the intermediate output result of the RCCC-WBM model. The water conservation amount calculation method provided by the invention has less requirements on input data and parameters, and has a better simulation effect on a hydrological process.

The invention discloses a soil water content inversion method based on improved combination roughness, and relates to the field of remote sensing, and the method comprises the steps: synchronously obtaining a Sentinel-1 radar image and a Sentinel-2 optical image, and extracting different polarization backscattering coefficients, local incident angles and normalized water body indexes through preprocessing; the method comprises the following steps: generating a bare soil simulation backscattering coefficient data set, removing vegetation scattering contribution by using a water cloud model, obtaining a real bare soil backscattering coefficient, constructing a training set and a verification set containing actually measured soil water content, constructing a lookup table based on double models, and calculating the water content of the bare soil by minimizing a root-mean-square error between simulation and the real backscattering coefficient. Global search is carried out in a preset parameter space to determine an optimal earth surface root mean square height and a correlation length, a novel polynomial combination roughness is constructed, a physical correlation between the roughness and a backscattering coefficient is established, a dual-polarization empirical equation set is constructed, and simultaneous solution is carried out after parameters are optimized according to a criterion; according to the method, a more reasonable inversion result of the soil water content in a large range can be obtained.

The invention provides a method for automatically monitoring the humidity of a corrugated board on line, and belongs to the technical field of corrugated board production. Uniform thermal pulses are applied to the surface of the corrugated board through a thermal infrared imaging device in combination with a thermal pulse excitation system, and high-resolution thermal response images are collected in real time. The system calculates thermal diffusivity and thermal attenuation characteristics based on an unsteady state heat conduction equation, generates a temperature distribution matrix, extracts a humidity characteristic spectrum by using a heat and humidity two-parameter neural network model, and establishes a corresponding relation between temperature and water content. Carrying out region segmentation through the humidity characteristic spectrum, identifying a humidity abnormal region, calculating a deviation value, and triggering an alarm when the deviation value exceeds a preset threshold value. The technical problem that in the prior art, corrugated board humidity detection mainly depends on manual sampling and special instruments, and real-time online monitoring on a production line cannot be achieved is solved.

The invention relates to the technical field of rock sample oil-water saturation determination based on a nuclear magnetic technology, and provides a shale sample oil-water saturation intelligent determination method based on a two-dimensional nuclear magnetic technology, and the method comprises the following steps: collecting volumes, echo signals and signal-to-noise ratios of a preset number of rock samples; marking a target rock sample and a comparison rock sample, and determining a volume influence comprehensive interference degree and a noise amplification coefficient of a target echo signal; obtaining a denoised target echo signal according to the target echo signal, the volume of the rock sample corresponding to the target echo signal and the noise amplification coefficient of the echo signal; according to experiments of rock sample two-dimensional nuclear magnetic oil-water distribution, pore attributes and the like, a two-dimensional nuclear magnetic T1-T2 map is divided into an invalid pore area and an effective pore area of a rock sample corresponding to the two-dimensional nuclear magnetic T1-T2 map and an oil-water distribution area of the effective pore area, a fluid close to reservoir oil-water distribution is adopted to recover a two-dimensional nuclear magnetic spectrum of the rock sample, and the oil-water content corresponding to a nuclear magnetic signal is extracted; and obtaining a rock sample oil-water saturation determination result based on the nuclear magnetic technology.

The invention discloses a method for rapidly detecting the content of a residual flocculating agent in washing machine-made sand, which comprises the following steps of: screening out particles with the particle size of more than 4.75 mm from machine-made sand to be detected, respectively testing the critical water contents of degraded and untreated machine-made sand samples, and determining the mass concentration range of the flocculating agent on the basis of the difference value of the critical water contents of the two kinds of machine-made sand. Compared with tests through neat paste, mortar and concrete systems, deviation possibly caused by introduction of other materials is avoided, and the method is more convenient, faster and more accurate. A'critical water absorption 'test method is provided according to the stability of the stacking state of sand, a transparent circular truncated cone test mold with scales is designed, the filling height and the tamping method of each layer of sample are accurately stipulated, and the test normalization and the test result repeatability of different time, different places and different operators are improved.

The invention provides a multifunctional digging and tamping machine integrating digging, shoveling, tamping and humidifying. The multifunctional digging and tamping machine comprises a small arm, a large arm and a digging machine body. According to the multifunctional digging and tamping machine integrating digging, shoveling, tamping and humidifying, the high-strength steel bucket is modified and customized, the bottom plate of the bucket is arranged to be a tamping plate, and the attached vibrator is additionally arranged, so that the digging and tamping functions are achieved, the bucket can be rotated by 360 degrees through the top end rotating device to form a bucket, construction at any angle such as front shoveling, side shoveling and inclined shoveling is conducted, and the construction efficiency is improved. A water tank, a water pipe and a spray head are additionally arranged, the water content of backfill soil can be adjusted in time to achieve the optimal tamping effect, well chamber periphery backfill and tamping construction can be conducted, the power of an attached vibrator is large, a hydraulic telescopic rod is convenient to operate, the tamping effect is good, a square tamping plate can conduct all-directional tamping by being attached to the edges and the corners, construction operation is mechanized, time and labor are saved, and the construction efficiency is improved. Construction of four working procedures can be completed at the same time only by one person, a large amount of manpower is saved, the construction quality is improved, and cost reduction and efficiency improvement are achieved.