230 results about "Soil type" patented technology

The invention discloses a drainage basin water quality pollution source flux identification method based on an SWAT model, computer equipment and a storage medium, and the method comprises the steps: obtaining topographic data, land utilization data, soil type data and meteorological data, and enabling the topographic data, the land utilization data, the soil type data and the meteorological data to form a drainage basin spatial database; based on the preprocessed digital elevation model, determining a water flow direction and setting a reasonable water collection area threshold value, and dividing sub-basins to construct a basin calculation unit network topology structure; obtaining pollution source data, and constructing an SWAT-CUP model according to the pollution source data; performing system calibration and verification on the watershed hydrological process by adopting an SUFI-2 algorithm in the SWAT-CUP model; carrying out system calibration and verification on the total nitrogen load of the drainage basin by adopting an SWAT-CUP model; and based on the calibrated SWAT hydrological model, the input condition of the pollution source is changed. The method can cover the whole watershed and quantify the contribution rate of different pollution sources; cost is high, operation is simple, and long-term change can be dynamically simulated.

The invention relates to the technical field of ecological restoration scene modeling, in particular to an ecological restoration scene modeling method and system platform applied to territorial space planning, and the method comprises the following steps: based on a successful ecological restoration technical scheme case and a to-be-restored land parcel unit. According to the method, normalization processing is carried out on multi-dimensional attributes between successful ecological restoration technical scheme cases and to-be-restored land parcel units, a source-target land parcel feature fingerprint set is constructed, and specific attributes such as annual average temperature, precipitation, soil types, pH values, altitudes, native vegetation types and labor cost are combined; modeling is realized on data source selection granularity and expression dimension. Furthermore, an importance coefficient is set according to the influence degree of each dimension in a historical repair success case, feature difference weight calculation is guided, and a technical migration adaptation degree score is obtained by combining normalized difference calculation, so that a quantifiable source-place adaptation capability evaluation index is established, and the limitation that judgment depends on experience in the prior art is broken through.

The invention relates to the related technical field of climate monitoring, in particular to a freezing circle climate change monitoring method and system suitable for an Asian alpine region, and the method comprises the steps: configuring a monitoring network, receiving a frozen soil multi-source monitoring data set, constructing a frozen soil and climate coupling response model, embedding a region climate assessment engine, and generating a frozen soil degradation risk grade distribution map. And judging whether risk reminding is triggered or not according to the dynamic frozen soil degradation threshold value, and if the risk reminding is triggered, marking an abnormal region in the frozen soil degradation risk level distribution diagram. The technical problems that Asian alpine region freezing circle climate change monitoring abnormity reminding mostly depends on static data, the dynamic evolution process of frozen soil cannot be accurately captured, and the frozen soil degradation risk identification precision is limited are solved, a frozen soil and climate coupling response model constructed based on multi-source data is achieved, and the frozen soil degradation risk identification accuracy is improved in combination with a dynamic degradation threshold value set according to the frozen soil type. And risk reminding is triggered in time and an abnormal region is marked, so that the frozen soil degradation risk identification precision is improved.

The invention belongs to the technical field of pile foundation construction, and particularly relates to an inversion method of a pile foundation construction and geological exploration technology, which comprises the following steps of: 1, collecting geological exploration data; the method comprises the following steps: acquiring property data of an underground soil layer through drilling and in-situ testing operation, including the thickness, compactness and soil type of the soil layer; and calculating the numerical values of the thickness, the compactness and the soil type of the soil layer through a static sounding test method. According to the inversion method of the pile foundation construction and geological exploration technology, accurate geological exploration data can be provided, specific characteristics of an underground soil layer are calculated through the inversion method, and accurate parameters are provided for pile foundation design. Meanwhile, the interaction between the pile foundation and the soil layer is simulated through a finite element method, deformation and stress distribution in the construction process are predicted, and a scientific basis is provided for engineering design. In addition, settlement and pile sinking resistance of the pile foundation need to be monitored in real time, so that a construction scheme is adjusted in time, and construction safety and quality are ensured.

The invention relates to the technical field of soil moisture content monitoring, and discloses a method and a system for accurately monitoring soil moisture content through remote sensing inversion of an unmanned aerial vehicle. Acquiring original spectral data of different soil types and environmental conditions through a spectral sensor to obtain an initial multispectral image data set; dividing soil types by using a support vector machine classification method according to pixel reflection characteristics to form a soil type grouping set; calculating a multispectral band reflectivity variance for each group, and screening candidate bands to construct a set; processing the candidate wave band set through a random forest regression model, adjusting the weight in combination with an environment variable, and performing iterative screening to form an optimized wave band combination sequence; extracting spectral features of the optimized wave band, and carrying out weighted fusion on the soil variation region to output a processed image; and calculating the soil moisture content by using a linear inversion model based on the pixel reflectivity of the processed image, and outputting a distribution diagram when the deviation reaches the standard. The method is suitable for different soil and environments, the wave band is accurately selected, the precision is improved, and high-quality data is provided for agricultural and environmental governance.

The invention relates to the field of remote sensing image processing, in particular to a farmland soil type classification-oriented remote sensing image data acquisition method, which comprises the following steps of: regularly acquiring remote sensing image data of a target area according to a preset period; obtaining a distance measure between any two pixel points in each remote sensing image, and segmenting each remote sensing image to obtain a ground feature region; analyzing the trend and the amplitude of each pixel point on the spectral curve, and determining the red edge expression degree of each pixel point; determining the vegetation growth performance degree of each pixel point; determining the farmland soil segmentation quality of each remote sensing image; and screening a to-be-classified image from all remote sensing images of the target area, screening a farmland soil area to construct a bare soil mask image, and performing farmland soil classification on a ground feature area in the to-be-classified image in combination with a neural network. According to the method, the farmland soil area in the remote sensing image is accurately divided, and the accuracy of farmland soil type classification is improved.

The invention relates to the technical field of water resource management, in particular to a flow hydrograph simulation method based on coupling of a Xinanjiang model and a depression, and the method comprises the steps: obtaining the geographic space data and meteorological data of a target drainage basin; the geospatial data at least comprises a digital elevation model, land utilization data and soil type data; and carrying out sub-drainage-basin division on the target drainage basin based on the digital elevation model, identifying depressions in the digital elevation model by adopting an improved priority flood algorithm, and constructing a spatial topological relation of the depressions. According to the method, the hydrological characteristics of the depression are fused into the Xinanjiang model, the regulation and storage function of the depression group on the drainage basin runoff is quantified, the hydrological simulation precision of the depression dominant drainage basin is remarkably improved, and by improving the depression recognition algorithm, pre-construction of the slope confluence time matrix based on the cells and rapid judgment of the depression merging mechanism, the stability of the depression confluence time matrix is improved. The calculation speed of the distributed hydrological model is greatly improved, and the efficiency requirement of the real-time hydrological model can be met.

The invention relates to a soil erosion amount dynamic monitoring method and system based on multi-source remote sensing data fusion. The method comprises the following steps: acquiring multi-source remote sensing data and auxiliary data, and performing geometric fine correction and atmospheric correction on an image based on high-resolution digital elevation data to obtain a data set with consistent space; performing inversion based on the data set to obtain a corrected terrain factor and a water and soil conservation measure factor; generating a time sequence rainfall erosivity factor and a time sequence vegetation coverage factor in combination with the multi-temporal satellite rainfall data; and calculating a preliminary soil erosion modulus in combination with the soil type map, and correcting by using multi-stage high-resolution digital elevation data to obtain a dynamic monitoring result of the soil erosion amount. By adopting the method, the problem of multi-source data fusion matching can be solved, and the factor inversion precision is improved, so that the accuracy of a dynamic monitoring result of the soil erosion amount is improved.

Disclosed in the present invention is an intelligent energy efficiency management system for an LNG dual-fuel powered trailing suction hopper dredger, comprising: an online intelligent LNG energy efficiency monitoring module, configured to collect energy efficiency key factor parameters of a main energy consumption device of the LNG dual-fuel powered trailing suction hopper dredger to form a unified LNG powered trailing suction hopper dredger energy efficiency data dictionary; an intelligent energy efficiency analysis and evaluation module, configured to construct, on the basis of the LNG powered trailing suction hopper dredger energy efficiency data dictionary, an operating condition identification model, an energy efficiency indicator calculation model, a carbon emission calculation model, an energy efficiency level model and a periodic energy efficiency analysis model to form an energy efficiency analysis and evaluation system; and a dredging operation energy efficiency auxiliary decision-making module, configured to construct an energy consumption prediction model for ten-thousand cubic meters of soil on the basis of soil type, design dredging depth, construction parameters and historical fuel consumption data, and recommending a dredging construction operation parameter combination by means of an optimization algorithm. Also disclosed is an intelligent energy efficiency management method for an LNG dual-fuel powered trailing suction hopper dredger. The present invention increases the energy efficiency.

The invention relates to the technical field of soil component detection, in particular to a soil component detection method and system based on spectral analysis, and the system comprises an intelligent mobile platform and a multifunctional integrated spectrum acquisition module. In the advancing process, soil is continuously scanned through the spectrum collection module, spectrum information is obtained in real time, data are processed through the spectrum feature extraction unit, the soil component type and distribution proportion are obtained, and a soil component distribution diagram and quantitative data are generated. According to the method, the detection efficiency can be remarkably improved, the problem of data missing of a traditional fixed-point sampling mode is avoided, meanwhile, the adaptability to complex terrains and diversified soil types is enhanced, and high precision and wide applicability of a detection result are ensured.

The invention discloses a DEM adaptive multi-algorithm fusion lifting method for a high-precision distributed hydrological model, and relates to the field of hydrological model basic data construction. The method comprises the following steps: acquiring original DEM data, land utilization data and soil type data; performing standardization processing on the original DEM data to obtain a unified grid DEM; calculating a basic terrain field based on the unified grid DEM; generating at least one enhanced topographic parameter (such as an enhanced gradient grid or topographic index) through a predetermined optimization pipeline based on the base topographic field; finally, hydrological response units are divided in combination with the at least one enhanced topographic parameter, the land utilization data, and the soil type data. Through the optimization assembly line, the problem that traditional filtering is insufficient in geomorphic feature reservation is solved, and the physical rationality of hydrological response unit division is improved.

The invention provides a mountain freeze-thaw desertification early warning method and related equipment. The method comprises the following steps: acquiring thermal neutron intensity and epithermal neutron intensity of a target area; based on a target intensity ratio and a pre-obtained empirical fitting parameter set, target parameters are determined, and the target intensity ratio is the ratio of the thermal neutron intensity to the epithermal neutron intensity of the target area; determining a target moisture content according to the target parameter and the thermal neutron intensity or epithermal neutron intensity of the target area; and when the target moisture content is lower than a preset critical soil moisture threshold value, carrying out mountain freeze-thaw desertification early warning. Soil moisture is inverted through a cosmic ray neutron detection technology, environmental interference factors such as a non-soil water hydrogen source are corrected, local soil moisture of different vegetation types and soil types is accurately captured, freeze-thaw desertification is judged in combination with a critical soil moisture threshold, and early warning is given.

The invention relates to the technical field of soil spectral analysis, in particular to a hyperspectral soil classification method, which comprises the following steps: acquiring hyperspectral images of various types of soil to be detected, and extracting a spectral feature group and a texture feature group from the hyperspectral images; obtaining topographic data, and extracting a topographic feature group from the topographic data; calculating separability indexes of the three feature groups among different soil classes; weighting the three feature groups based on a separability index to obtain an input feature vector; simplifying the input feature vector by adopting a recursive feature deletion method to obtain an optimal feature vector; and inputting the optimal feature vector into a middle layered random forest model for soil type detection to obtain a predicted soil type. According to the method, hyperspectral spectral features, spectral indexes, texture features and topographic features are integrated, a high-dimensional multi-source feature optimization mechanism based on factor weighting and recursive feature screening is introduced, and classification precision and model robustness are improved while feature dimensions are remarkably compressed.

The invention relates to the technical field of intelligent detection, in particular to a road settlement and damage intelligent detection method and system, and the method comprises the following steps: obtaining geological attribute data of a settlement area, calling settlement deformation quantity data, and calculating a correlation strength value according to an underground water level, a soil type, a stratum thickness and a settlement deformation quantity in geological attributes. According to the method, through combined calculation of the geological attribute data and the settlement deformation quantity, the high-correlation area is dynamically recognized, the partition boundary is accurately adjusted, the matching degree of data distribution and actual change is effectively optimized, and damage evaluation is more targeted through analysis of the fracture depth and width proportion value; risk extension trend analysis is combined with geological parameter change and settlement trend, a potential influence direction is defined, a basis is provided for pre-judging risk extension, partition identification, crack assessment and trend data are integrated, multi-dimensional risk assessment is realized, the comprehensiveness and accuracy of a detection result are improved, and the real-time performance and adaptability of road condition monitoring are remarkably enhanced.

The invention discloses a buried gas pipeline multi-leakage parameter identification and concentration distribution rapid prediction method, and belongs to the technical field of buried gas pipeline safety detection. The method comprises the following steps: firstly, based on a porous medium flow control equation and a component transport equation, establishing a leakage diffusion physical model by utilizing computational fluid mechanics and generating a multi-working-condition sample data set; training a neural network model by using the sample data, and constructing a rapid concentration prediction agent model; in combination with measured data of a monitoring area, an ensemble Kalman filtering algorithm is adopted, the agent model serves as a forward prediction operator, and collaborative inversion of parameters such as the soil type, the leakage direction and the flow is achieved through iterative updating; and finally, outputting complete underground gas concentration distribution in the monitoring area based on the leakage parameters obtained through identification. According to the method, rapid identification of multiple leakage parameters and accurate prediction of concentration distribution are realized under the condition of limited measuring points, and the method has remarkable disaster early warning and engineering application values.

The invention relates to the technical field of digital soil mapping and soil information extraction, and discloses a soil type texture map deduction method, device and equipment of surface soil and a medium. The soil type texture map deduction method comprises the steps of obtaining mechanical composition of field sampling points, obtaining environment covariants of a target area, and obtaining the environment covariants of the target area; modeling the environment covariables of the target area into a plurality of spatial point elements, and modeling the soil type map into a plurality of spatial surface elements; establishing a machine learning model, and predicting the mechanical composition corresponding to the environment covariable array of all spatial point elements; assigning a corresponding soil texture to each space surface element based on a mechanical composition mean value of all space point elements in each space surface element surface; and drawing a continuously distributed soil type texture map according to the soil type textures corresponding to all the spatial surface elements. The soil type texture map inference method, device and equipment and the medium are used for assisting soil type naming in a soil classification system, the prediction precision is high, the prediction efficiency is high, and the cost is low.

The invention discloses an osmotic pressure analysis method and device fusing model optimization and physical inversion and a medium, and the method comprises the steps: calculating correlation coefficients of a specified reservoir water level and osmotic pressure under different time lags based on cross-correlation function analysis, and recognizing a differential nonlinear feature corresponding to the maximum correlation coefficient; aiming at the differentiated nonlinear characteristics of different dam types, constructing a plurality of corresponding diagnosis prediction models in parallel, and establishing a model selection decision rule to select an optimal diagnosis model; according to delay parameters obtained through cross-correlation analysis, a permeability coefficient is reversely deduced through a pore medium heat transfer diffusion theoretical formula; according to the regression slope and the theoretical value attenuation factor of the optimal model, a permeability coefficient is reversely deduced in combination with a correction diffusion equation, credibility evaluation and weighted fusion are performed on the permeability coefficient, and a comprehensive permeability coefficient is calculated; and diagnosing the soil type and the permeability characteristic grade. According to the method, the propagation delay characteristic of reservoir water level change in the pore medium can be accurately quantified, and the inversion precision of the permeability coefficient and the engineering applicability are improved.

The invention relates to the technical field of data processing, and provides a comprehensive intelligent evaluation method and system for a soil conditioning effect, and the method comprises the steps: obtaining the soil cadmium content, the crop cadmium content and the soil acidity and alkalinity of a plurality of soil samples of a plurality of soil types after multiple times of conditioning, and the conditioner cost of each time of conditioning; dividing the soil sample to obtain a plurality of pollution categories; according to the soil cadmium content change and change difference of the same soil sample after adjacent conditioning, the soil passivation degree of each soil sample under the soil cadmium content after each conditioning is obtained; the conditioning response degree of each soil sample under the soil cadmium content is obtained; the remediation contribution degree of each pollution category under the soil cadmium content is obtained; and obtaining the grey correlation degree of each evaluation index and other evaluation indexes in each pollution category, so as to construct a conditioning evaluation model. The invention aims to solve the problem of inaccurate evaluation caused by the fact that the influence of soil quality and pollution degree is not considered in the evaluation process of the soil conditioning effect.

The invention provides a protection method, device and equipment for power grid facilities under natural disasters and a medium. The method comprises the following steps: firstly, acquiring an initial data set, wherein the initial data set comprises a rainfall data set, a normalized vegetation index, land utilization data, road network data, soil type data, river network density data, elevation data, slope data, rock data and a surface deformation rate; and then, based on the initial data set, simulating a position point of a landslide barrier dam generated in a river after landslide is generated by rainfall, and geometric parameters of the landslide barrier dam. A first evolution law of outburst flood generated by the landslide barrier dam after outburst is then simulated based on the location points and the geometric parameters. And finally, based on the first evolution rule of the outburst flood, determining emergency protection measures of power grid facilities at the downstream of the landslide barrier dam. The protection accuracy of power grid facilities under natural disasters in the prior art is improved.

The invention relates to the technical field of roadbed detection, and discloses a roadbed compaction quality detection method based on ultrasonic wave collaboration, and the roadbed compaction quality detection method comprises the following steps: collecting full-wave band ultrasonic echo signals, and obtaining current environment data; calculating a longitudinal wave speed, a transverse wave speed and a wave speed ratio, and extracting an attenuation coefficient and a frequency dispersion characteristic of the ultrasonic echo signal to obtain an acoustic characteristic set; inputting the acoustic feature set and the environmental data into an environmental compensation model, outputting a standard acoustic parameter set subjected to temperature, humidity and water content correction, analyzing the standard acoustic parameter set through a soil texture classification algorithm, and judging the current soil texture type; and combining the standard acoustic parameter set and the current soil texture type into a multi-dimensional feature vector, inputting the multi-dimensional feature vector into a compactness calculation model, and calculating to obtain a roadbed compactness value of the current measuring point. According to the method, high-precision compaction degree numerical calculation is realized, and intelligent and visual whole-process support is provided for roadbed construction quality.

The invention provides a multi-disaster-type linkage-oriented grain and cotton crop meteorological risk grading early warning method and system, and relates to the technical field of risk grading early warning. The first information comprises soil salinity change data, frost meteorological data, drought meteorological data, wind disaster meteorological data and crop monitoring data in a preset time period; performing disaster type space-time relation analysis on the first information to generate a multi-disaster type linkage space-time model; performing fusion processing on the multi-disaster linkage spatial-temporal model through spectral clustering and a preset gradient boosting tree to obtain a disaster influence prediction model; carrying out adaptive filtering and grading judgment processing on the disaster influence prediction model to obtain a disaster influence grade; and generating an adversarial network based on the disaster influence levels and historical early warning coping strategies, and determining coping strategies corresponding to all disaster influence levels of each crop. According to the invention, targeted disaster grading can be carried out according to soil types and crop planting characteristics in different areas.

The invention relates to the field of technical analysis and to determining for construction purposes the optimum moisture content and maximum density of natural and man-made soils under static compaction. The essence of the invention consists in compacting a first soil specimen after first determining the initial moisture content thereof and, if necessary, adjusting same by adding water in accordance with recommended values for the given type of soil. A compaction mold cylinder and a lower liner are then placed on 18-20 mm high support stands on a level surface, a weighed amount of the soil under examination is placed in the compaction mold cylinder, the cylinder is positioned on a base plate of a compactor, a top plate of the compactor is brought into contact with the upper end of the cylinder and the compactor is set to a 20 mPA loading mode which is maintained for 5-10 minutes. Loading is ceased, the compaction mold is removed from the compactor, the compacted specimen is extruded and the volume thereof is calculated, the specimen is broken up, a representative sample is taken and weighed on electronic scales with an accuracy of up to 0.01 before being dried and reweighed. On the basis of the data obtained, the damp soil density and the dry soil density are calculated according to given formulae, and the data obtained are entered into a table and noted on a graph. A second soil specimen is compacted, the moisture content of which is increased by 1%, the specimen is placed in the compaction mold, placed under a 20 mPA load in the compactor and held for 5-10 minutes, after which loading is ceased, the compaction mold is removed from the compactor, the compacted specimen is extruded, the volume thereof is calculated, the specimen is broken up, a representative sample is taken and weighed on electronic scales with an accuracy of up to 0.01 before being dried and reweighed, the moisture content of the soil and the dry soil density are calculated and the d

The present application relates to the technical field of ecological restoration scene modeling, in particular to an ecological restoration scene modeling method and system platform applied to land space planning, comprising the following steps: based on successful ecological restoration technical scheme cases and land units to be restored.The present application realizes modeling in data source selection granularity and expression dimension by normalizing the multi-dimensional attributes between successful ecological restoration technical scheme cases and land units to be restored, constructing source-target land feature fingerprint sets, and combining annual mean temperature, precipitation, soil type, pH value, altitude, native vegetation type and labor cost and other specific attributes.Further, by setting importance coefficients according to the influence degree of each dimension in historical restoration success cases, the present application guides feature difference weight calculation, and obtains technical migration adaptation score by combining normalized difference value calculation, thereby establishing a quantifiable source land adaptation capability evaluation index, and breaking the original limitations of relying on experience judgment.

The utility model discloses a garden municipal soil loosening device, and belongs to the technical field of garden municipal soil loosening devices, the garden municipal soil loosening device comprises a rack, four groups of rollers are mounted on two sides of the rack, two groups of driving motors are mounted in the middle of the upper part of the rack, a rotating rod is mounted at the bottom of the rack, and mounting frames are rotatably connected to two ends of the rotating rod; a plurality of groups of soil loosening blades are mounted outside the rotating rod, mounting plates are mounted above the mounting frames, a plurality of groups of mounting screw holes are formed in the middles of the two sides of the rack at the two ends of the mounting plates, the distances between the plurality of groups of mounting screw holes are the same, and the positions of the plurality of groups of mounting screw holes correspond to each other; the penetrating mounting plate is in threaded connection with the mounting screw hole; according to the soil loosening device, the device can be better adjusted according to the current land condition, flexible adaptation to different soil types and soil loosening depths is achieved, the soil loosening effect and operation efficiency are improved, and the practicability of the device is effectively improved.

The invention discloses a seed cultivation process optimization method based on a discrete element theory, and belongs to the technical field of seed cultivation. The method comprises the following steps: establishing a mechanical interaction model between soil particles and seeds according to an acquired physical characteristic parameter set by utilizing a discrete element method; acquiring a target physical characteristic parameter set, inputting the target physical characteristic parameter set into a mechanical interaction model, and performing discrete element analogue simulation output under a dynamic simulation condition to obtain a change curve of contact force along with seed growth displacement; and judging whether the contact force in the change curve meets a preset threshold value in each stage of seed growth, if not, continuously self-optimizing the target physical characteristic parameter set, and ending optimization until the judgment result is yes. According to the method, a seed optimization design scheme can be generated, improvement strategies for different soil types can be formulated, and a reliable basis is provided for agricultural machinery design optimization and seeding efficiency improvement.

The invention relates to the field of geological survey, and discloses a light dynamic sounding device suitable for regional shallow landslide survey, the light dynamic sounding device comprises a hollow sounding probe, a hollow extension probe rod, a self-weight hammer, a stress rod and a visual soil sampling rod core, the bottom end of the sounding probe is provided with a conical tip, the self-weight hammer is slidably arranged on the stress rod in a penetrating manner, and the soil sampling rod core is arranged on the extension probe rod. The bottom end of the stress rod is detachably connected with the top end of the extension probe rod, a limiting piece used for limiting the self-weight hammer is arranged at the joint of the stress rod and the extension probe rod, the bottom end of the extension probe rod is detachably connected with the top end of the sounding probe, and the top end of the sounding probe can be detachably connected with the bottom end of the stress rod. Through holes for inserting the soil sampling rod core are formed in the hollow parts of the extension probe rod and the sounding probe, a positioning piece for positioning the soil sampling rod core is arranged at the bottom end of the through hole of the sounding probe, and a reaction film which changes color when encountering water is arranged on the inner wall of the soil sampling rod core. The method can solve the problems that a traditional DCP technology cannot accurately distinguish soil types and cannot sense the water content state of a soil layer in situ.

The invention provides an electric power construction supervision project-based project quantity metering method, which comprises the following steps of: acquiring geographic coordinate data of an extra-high voltage tower footing position, and extracting topographic and geomorphic diversity characteristics and soil type difference information from the geographic coordinate data through satellite remote sensing image processing, carrying out overlay analysis through a geographic information system to obtain an extra-high voltage tower footing resistance geographic rule distribution diagram; high-voltage electric field interference intensity data generated by an extra-high voltage transmission line around the tower footing is collected, the influence degree of high-voltage electric field interference on tower footing grounding resistance fluctuation is analyzed in combination with the extra-high voltage tower footing resistance geographical rule distribution diagram, and the adjusted tower footing resistance change rate and fluctuation frequency are obtained; and obtaining a tower footing position analysis result from the differentiated reinforcement cage binding amount metering strategy, and optimizing the distribution proportion of the reinforcement cage binding amount in combination with the resistance geographical rule subset to obtain a binding amount meter with optimized resource allocation.

The invention discloses construction and system implementation of a water and fertilizer integrated accurate control model. The system determines the appropriate single-time irrigation amount (irrigation quota) according to the root system distribution and the soil type of the planting object; reasonably distributing the demands for different nutrients in different growth periods of the plant to each growth period of the plant according to a nutrient demand curve, and determining the fertilizer dosage in each growth period; and considering irrigation amounts and fertilization amounts in different growth periods, determining a fertilization concentration suitable for single operation, calculating a series of suitable nutrient solution preparation concentrations, and recommending the concentrations to a user for selection. Model construction is presented in a software mode, peripheral electrical equipment is controlled directly or remotely through a controller, and the function of precise irrigation and fertilization is achieved. Through the construction and implementation of the system, the use convenience of the intelligent water and fertilizer integrated system can be greatly enhanced, a set of simple and easy-to-use production tool is provided for planting farmers and agricultural technical service personnel, and agricultural precise irrigation and precise fertilization decision making are assisted.

The application provides an engineering quantity measurement method based on power construction supervision engineering, comprising: acquiring geographic coordinate data of an extra-high voltage tower base position, extracting terrain and landform diversity features and soil type difference information from the geographic coordinate data through satellite remote sensing image processing, and obtaining an extra-high voltage tower base resistance geographic regularity distribution map through geographic information system superposition analysis; collecting high-voltage electric field interference intensity data generated by an extra-high voltage transmission line around the tower base, combining the extra-high voltage tower base resistance geographic regularity distribution map, analyzing the influence degree of high-voltage electric field interference on tower base grounding resistance fluctuation, and obtaining an adjusted tower base resistance change rate and fluctuation frequency; obtaining tower base position analysis results from a differentiated steel reinforcement cage binding quantity measurement strategy, combining a resistance geographic regularity subset to optimize the distribution proportion of the steel reinforcement cage binding quantity, and obtaining a resource configuration optimized binding quantity measurement table.

The utility model discloses a multifunctional soil test sample cutting device relates to soil test technical field. The utility model discloses a frame is provided with adjusting mechanism and positioning mechanism on the frame, the adjusting mechanism includes two slide rods no. 1 slidingly penetrating the top of frame. The utility model discloses be provided with adjusting mechanism, manually hold the handle and drive slide rod no. 1 and arc plate no. 1 to move upwards or downwards, so that multiple soil cutters can move vertically upwards or downwards, and then multiple soil cutters sample cutting to soil sample, and before sample cutting, individually twist knob no. 1 and drive threaded rod no. 1 to rotate, under the cooperation of multiple slide rods no. 2, make soil cutter can be close to or away from sample, and then the sample cutting thickness of sample is adjusted, greatly improve the precision and operation flexibility of this soil test sample cutting device, and multiple different shapes of soil cutters make the equipment can adapt to various soil types and test demand.