245 results about "Soil texture" patented technology

The invention relates to a shield tunneling machine tunneling error compensation control method and system, and relates to the field of tunneling operation, and the method comprises the steps: carrying out the time domain alignment and cutting region mapping alignment of a predicted soil feature distribution sequence and a predicted tool wear distribution sequence, and carrying out the integration to obtain a predicted operation state data sequence; and performing iterative optimization analysis on tunneling control parameters of the shield tunneling machine on the basis of the predicted operation state data sequence by taking the minimum overall tunneling operation error of the cutterhead as an expected target until a preset optimization scale is met, outputting an optimal tunneling parameter sequence, and controlling the shield tunneling machine to execute tunnel construction in a future time zone. According to the method, the technical problems of insufficient tunneling precision and low operation efficiency caused by the fact that a traditional method lacks a dynamic adjustment mechanism and cannot adjust tunneling control parameters in a targeted manner according to soil texture changes and cutter wear conditions can be solved; by effectively reducing the tunneling operation error, the accuracy and the operation efficiency of the shield tunneling machine in the tunneling process are remarkably improved.

The invention relates to the technical field of agriculture, and discloses an intelligent fertilization technical measure and method for improving the fertilizer utilization rate, and the intelligent fertilization technical measure comprises a soil sensor module which is used for monitoring various parameters of soil in real time, including but not limited to soil nutrient content, soil humidity, soil acidity and alkalinity, soil temperature and soil texture; the soil sensor module can collect monitored parameter data with high precision and high frequency, and transmit the data to the central control unit through the wireless communication module; the fertilizer storage and conveying module is internally provided with a plurality of independent fertilizer storage bins, and each storage bin can store different types of fertilizers. According to the present invention, the type, the use amount and the application time of the fertilizer can be precisely controlled according to the growth requirements of different crops and the soil state through the precise fertilization mode so as to ensure the efficient absorption of the fertilizer by the crops, such that the fertilizer utilization rate is significantly improved, and compared with the traditional fertilization mode, the fertilizer waste can be reduced, and the agricultural production cost can be reduced.

The invention provides an automatic navigation and positioning method for agricultural equipment, and the method comprises the steps: obtaining the root system residue distribution data of a previous crop and the soil hardening difference, building a correlation model of the crop root system residue distribution and the soil hardening difference, and determining a target tillage depth plan for the sowing of a next crop according to the correlation model; the operation track and depth parameters meeting the soil texture improvement requirements are applied to an automatic navigation and positioning system of agricultural equipment, and the operation process of the agricultural equipment is automatically controlled and dynamically adjusted; and based on the adjusted operation track and depth parameters, analyzing the long-term influence of an automatic navigation and positioning system of agricultural equipment on soil texture improvement in different growing seasons by tracking soil quality indexes, crop yields and root system distribution.

The invention relates to an urban rainfall flood process forecasting method based on data assimilation and multi-mode coupling, and the method comprises the following steps: (1) collecting historical meteorological data, hydrological data, topographic data, soil texture data, vegetation data and urban infrastructure data in a region; performing quality control and format standardization on all the data, and inputting the data to a GIS technology-based visual analysis and decision-making platform; (2) establishing a parameter transfer rule among the WRF, the SHUD and the two-dimensional hydrodynamic model; (3) operating WRF, obtaining regional high-resolution rainfall forecast data, performing EnKF dynamic updating, and inputting the data to the platform; (4) driving the SHUD to obtain regional surface runoff and groundwater prediction data, performing EnKF dynamic updating and inputting the data to the platform; (5) driving the two-dimensional hydrodynamic model to obtain a flood propagation path and spatio-temporal release data of a submerged area, and inputting the data to the platform; and (6) forming risk level assessment by using an automatic threshold identification technology, and inputting the risk level assessment to the platform. The method is high in practicability and can realize accurate forecasting.

The invention relates to the technical field of auxiliary devices of detection equipment, in particular to a robot and method for detecting the stability of the wall of a pile hole and poisonous gas in the hole, and the robot can be automatically clamped according to the size of the pile hole and automatically ascends and descends for detection after being clamped. The method for detecting the soil texture of the poison gas in the deep pit comprises the following steps: according to the types of harmful gases possibly existing, oxygen, methane, hydrogen sulfide, carbon monoxide and the like, detecting the soil texture of the poison gas in the deep pit, and detecting the soil texture of the poison gas in the deep pit. A multi-parameter gas detector capable of detecting the gases is selected, so that all operators are properly trained to know how to correctly use the detector and deal with emergency situations; and determining that the sensor works normally and is not damaged or blocked, and placing the gas detector at different heights of the pile hole, generally performing detection once from the bottom to the top at a certain distance so as to obtain comprehensive data.

The invention relates to the technical field of intelligent agriculture, and particularly discloses an orchard intelligent water and fertilizer integration-based edge end fruit tree fertilizer demand prediction method, which comprises the following steps of: constructing each fruit tree as a graph node, and fusing canopy spatial characteristics extracted by unmanned aerial vehicle multispectral remote sensing and nutrient time sequence characteristics monitored by a soil sensor; space influence weights among nodes are calculated according to the terrain, the soil texture and the space distance, and a fruit tree individual relation graph is established; then, through a space-time diagram convolutional network, aggregating space neighborhood features and capturing time dynamic changes, and outputting target state features subjected to multi-scale enhancement; when the canopy conflicts with the soil characteristic indication, combined diagnosis is carried out based on a neighborhood consistency index and an adjacent node state, systematic nutrient stress and local non-nutrient factors are distinguished, and final fertilizer demand prediction is generated after the conflict is eliminated; a digital fertilization prescription map is generated through spatial interpolation, soil characteristics and slope correction, and the water and fertilizer integrated equipment is driven to execute precise operation.

The invention discloses an intelligent inrush current irrigation method based on meteorological data and Internet of Things monitoring. The method comprises the following steps: A1, weather data acquisition and judgment; a2, soil humidity monitoring and demand judgment; a3, calculating irrigation duration; a4, carrying out inrush irrigation period division and dynamic control; the total irrigation duration is decomposed into an inrush current period, and period parameters are dynamically optimized; a5, executing intelligent irrigation; internet weather data and soil humidity monitoring are integrated, intelligent irrigation decision making is achieved, and irrigation accuracy and timeliness are improved. By combining the soil texture, the meteorological data and the real-time soil humidity, the irrigation duration and the irrigation period number are dynamically calculated, the problems of parameter distortion and soil type neglecting in a traditional method are solved, the irrigation effect is ensured, and the irrigation uniformity is improved.

The invention provides a near-infrared spectrum rapid detection method and system for effective components of a herbicide, which are applied to the technical field of agricultural detection.The near-infrared spectrum rapid detection method comprises the steps of obtaining near-infrared spectrum data of a to-be-detected soil area and moisture content and compactness numerical values reflecting soil texture differences, and calculating the effective components of the herbicide on the basis of a preset interval to which the moisture content numerical value belongs; according to the method, the corresponding preset scattering correction parameter is selected, the actual scattering correction parameter is obtained through compactness numerical calculation, fine adjustment of the scattering correction parameter is achieved, and the quality and reliability of spectral data are improved through spectral correction; and the corrected spectrum is analyzed, so that the real condition of the herbicide in the soil can be reflected more accurately. Therefore, the interference of complex soil texture in the field on near infrared spectrum herbicide detection is effectively overcome, and the beneficial effect of rapidly and accurately detecting the effective components of the herbicide under the complex soil condition is achieved.

The invention discloses a land complex environment-oriented path planning system based on three-dimensional voxel grids, which is characterized by comprising a land complex environment maneuverability evaluation and prediction module, a three-dimensional voxel grid establishment and optimization module and a three-dimensional voxel grid-based path planning module. The technical scheme disclosed by the invention mainly starts from three parts: firstly, the problem of interaction between a carrier and terramechanics is solved through regional maneuverability evaluation and prediction, and traffic capacity evaluation of the carrier in regional maneuverability is obtained after factors such as terrain, landform, soil, soil texture and vehicle power are considered; then three-dimensional voxel data of land path planning is formed through three-dimensional voxel lattice representation of the multi-dimensional environment elements; and finally, realizing a path planning task in a complex environment based on the three-dimensional voxel lattice.

The invention discloses a method for estimating total nitrogen of soil of different plough layers based on a field in-situ spectrum, and relates to the technical field of crop growth monitoring. Collecting soil samples of different plough layers in a field, and obtaining in-situ spectral data of soil; performing indoor analysis on the collected soil sample, and determining the total nitrogen content, the soil texture type and the porosity; classifying the soil samples according to the soil texture types, and respectively establishing correlation models between the total nitrogen contents of the soil with different textures and the in-situ spectral data; introducing a northern eagle optimization algorithm to improve a random forest and a generalized regression neural network to improve the prediction capability of the correlation model on the total nitrogen content of the deep soil; and constructing a comprehensive monitoring model by combining a surface spectrum inversion result and a soil vertical variation equation, so as to realize indirect high-precision estimation of the total nitrogen content of the soil in different plough layers. And a theoretical basis is provided for future soil total nitrogen deep monitoring model research, and a technical support and a theoretical decision are provided for rapid acquisition of deep soil nutrients in precision agriculture.

The invention discloses a mobile multi-scene fluid soil rapid production factory and method, and relates to the technical field of constructional engineering, the mobile multi-scene fluid soil rapid production factory comprises a fluid soil integrated production mechanism, a multi-stage blanking station, a transfer robot, an earthwork robot and a stirring hopper which are mutually matched for use; wherein the earthwork robot is used for rolling waste muck raw materials to adjust the compactness, and collecting and transferring the waste muck raw materials; the multi-stage discharging station is used for storing curing agent production raw materials and accurately regulating and controlling the curing agent feeding ratio according to soil texture; the carrying robot is used for transporting the stirring hopper to the position below the multi-stage discharging station, and curing agent production raw materials are put into the carrying robot through the multi-stage discharging station. And the flow-state soil integrated production mechanism is used for transferring and stirring a stirring hopper filled with raw materials and a curing agent, and stirring the raw materials and the curing agent in a site prefabricated stirring pit outside the equipment. According to the invention, the fluid soil can be rapidly prepared on the construction site, the production time and cost of the fluid soil are greatly saved, and the efficiency and the quality of the fluid soil are improved.

The invention relates to the technical field of agricultural machinery, in particular to a crop layered fertilization intelligent precision plowing and sowing machine which comprises a rack, a walking driving part is arranged on the rack, a sowing machine is arranged on one side of the rack, a bearing frame is fixedly connected to the side, away from the sowing machine, of the rack, and a plurality of rotary tillage assemblies are transversely arranged on the bearing frame at equal intervals; a plurality of fertilization assemblies capable of vertically sliding are arranged at the bottom of the side, close to the rack, of the bearing frame, transmission assemblies are arranged between the soil retaining assemblies and the fertilization assemblies, and the transmission assemblies are used for reducing the impact force of the soil particles raised by the rotary tillage assemblies to the soil retaining assemblies and reducing the impact force of the soil particles raised by the rotary tillage assemblies to the fertilization assemblies. Transmission is converted into driving force for the height of the fertilizing assembly. The soil texture is fed back through the impact force of soil particles raised by rotary tillage and soil disturbance, so that the layered fertilization depth is adjusted in a linkage manner, and the defects of poor adaptability between the fixed layered fertilization depth and different soil properties and soil nutrient loss in traditional tillage and sowing are overcome.

The invention belongs to the technical field of intelligent soil monitoring, and particularly relates to a multi-sensor networking soil parameter high-precision detection device and method.The device adopts sensing, transmission and data processing, a four-layer architecture is applied, a sensing layer collects soil texture, temperature and salinity parameters, an environment interference factor matrix is constructed, and a data processing layer is constructed; outputting non-interference data through a layered interference calibration model; the transmission layer completes data transmission through wired and wireless dual modes; the data processing layer extracts spatial-temporal characteristics after preprocessing, and obtains a soil parameter fusion value through dynamic weight fusion; and the application layer matches the fusion value with a preset template to realize scene generation and visual rendering. According to the invention, the problems that the precision of the existing multi-sensor networking system is easily influenced by the outside and the intelligent level is insufficient can be solved.

The invention discloses a roadbed disease repairing method considering grouting pressure, grouting materials, soil texture types and disease types. The roadbed disease repairing method comprises the steps that it is judged that the roadbed soil texture type is clay sand or low-liquid-limit clay; judging whether the disease repair type is pure void repair or loose repair; and the grouting material and the grouting pressure are selected according to the influence rule of the grouting material and the grouting pressure on different disease repair effects of different roadbed soil properties. According to the method, the repairing effect is improved, meanwhile, the cost is reduced, and the defects caused by purely pursuing the optimal performance of a grouting material and the maximum grouting pressure in the prior art are overcome.

The utility model discloses an efficient drainage ditch excavation device based on an adjustable shaping excavator bucket, and relates to the technical field of municipal engineering and hydraulic engineering construction. Different design requirements are met by hydraulically adjusting the size of the bucket, the bucket body is formed at a time, manual finishing and template use are reduced, the construction cost is reduced by more than 20%, the excavation precision is controlled by combining GPS positioning and real-time measurement, the groove longitudinal slope and elevation precision is ensured, and the construction efficiency is improved. One-time forming of the drainage ditch and synchronous outward transportation of spoil are achieved, and site accumulation is avoided. According to the scheme, the construction efficiency and quality are remarkably improved, and the method is suitable for municipal drainage engineering under soil texture and strong weathered rock geological conditions.

The invention discloses a method for safely irrigating saline water with different mineralization degrees and reducing salt in a plough layer, and relates to the technical field of agricultural irrigation, and the method is characterized by comprising the following steps: monitoring the mineralization degree of irrigation water and soil moisture and salt dynamic states under various irrigation mode conditions; through a soil column simulation test, a saline water mineralization degree threshold value suitable for irrigation of saline-alkali cultivated lands with different soil properties and salt contents is found; performing a plot test in the field, and establishing an irrigation water-soil water-underground water salt migration model under various irrigation modes; hYDRUS-1D software is adopted for dynamic simulation and prediction of soil hydrothermal salt coupling migration under different saline water irrigation conditions. The method can be suitable for different soil texture types, crop types and underground water conditions, the salt content of the saline-alkali cultivated land can be effectively reduced, on the premise that crop growth is guaranteed, salt water resources are utilized to the maximum extent, irrigation cost is reduced, sustainable utilization of the saline-alkali cultivated land is achieved, and the method has important practical application value.

The invention relates to the technical field of artificial intelligence, and provides a soil texture recognition model construction method, a soil texture recognition model construction device, a computer readable storage medium and electronic equipment, and the soil texture recognition model construction method comprises the steps: screening key soil texture features from a plurality of ocean soil texture features; the feature importance score of the key soil feature is higher than a preset score threshold; collecting training data associated with the key soil characteristics, and training a plurality of initial machine learning models by using the training data; and according to a preset performance evaluation index, screening out a final target machine learning model for ocean soil texture identification from the plurality of initial machine learning models. According to the invention, through an automatic modeling mechanism combining feature optimization and multi-model performance screening, the classification precision and engineering applicability of the ocean soil texture identification model are improved.

A root tuber type traditional Chinese medicinal material harvester comprises a harvesting assembly, a rack, a separating assembly and a material collecting assembly, the harvesting assembly comprises a scraper knife part, and the movement track and the inclination angle of the scraper knife part can be adjusted; the rack comprises an upper rack and a lower rack, and a containing cavity is formed between the upper rack and the lower rack and used for containing the separation assembly; the separation assembly comprises a first separation mechanism and a second separation mechanism which are obliquely arranged from back to top and are staggered; the first separation mechanism comprises a screen mechanism, a crushing wheel assembly and a hydraulic cylinder, the distance between the crushing wheel assembly and the screen mechanism can be adjusted, and the hydraulic cylinder can lift the first separation mechanism. The whole structure and arrangement of the digging shovel, the separation assembly and the rack are optimized, so that the shovel blade part can be suitable for traditional Chinese medicine crops with different soil textures and categories; a multi-stage separation mechanism is arranged by optimizing the space of the rack, so that the separation effect is improved; the separating mechanism is obliquely arranged, the volume of the material collecting assembly is increased, the hopper can swing and dump, manual replacement is not needed, and the working efficiency is improved.

The invention relates to the technical field of geological exploration, and discloses a geological exploration steel pipe sampling mechanism which comprises a sampling barrel body and a supporting frame far away from the sampling barrel body, a steel pipe supporting column is integrally installed on the upper side of the sampling barrel body, a movable hole is formed in the supporting frame, and the steel pipe supporting column is slidably inserted into the movable hole in a penetrating mode. The steel pipe supporting column is in sliding fit with the supporting frame, a connecting column is installed on the inner wall of the sampling barrel body, an expansion mechanism is installed on the bottom side of the connecting column, a sampling plate is installed at the movable end of the expansion mechanism, and the expansion mechanism comprises a telescopic rod used for dragging the sampling plate and a track groove used for controlling the telescopic rod to move. The flexibility and adaptability of operation are improved; the sampling barrel body is pushed in the mode that the motor drives the gear and the threads are matched, so that the sampling process is high in automation degree and even in force application, damage to the soil texture structure in a traditional mode can be effectively avoided, it is guaranteed that the obtained sample is closer to the real geological condition, and the accuracy of the geological exploration result is improved.

The invention discloses a regional soil monitoring method, which comprises the following steps: dividing a planting region and a growth cycle, acquiring remote sensing image data of the planting region, and acquiring real-time soil moisture content data; correcting the soil moisture content data by adopting multiple vegetation indexes, identifying soil texture by adopting a convolutional neural network random detection model, and obtaining soil data features; dividing soil moisture content values of different depths according to the soil data characteristics, and obtaining parameter factors influencing the soil moisture content; according to the parameter factors, a soil texture identification model is adopted to identify soil sample features, a soil monitoring and positioning model is established, real-time soil monitoring is performed on different scenes, a more comprehensive data view angle is provided, real-time monitoring of soil conditions is realized, soil texture feature data can be acquired and processed in real time, and the real-time monitoring of the soil conditions is realized. And dynamic monitoring requirements under different scenes are supported, challenges under complex environmental conditions are dealt with, and continuity and reliability of soil monitoring tasks are ensured.

The invention discloses an agricultural drought monitoring method for a humid and semi-humid area. The method comprises the following steps: acquiring a day-by-day soil moisture content historical time sequence of a drought generation year of a research site; according to the day-by-day soil moisture content historical time sequence of the research site, estimating the field moisture capacity and the wilting moisture content of various soil textures, and calculating the soil effective moisture content of the various soil textures; according to the crop irrigation water amount and the actual monitoring value of the soil water content in the key growth period of the dry crops, obtaining the soil water content when the dry crops are subjected to water stress; calculating agricultural drought monitoring indexes of the dry crops in the humid and semi-humid areas according to the soil water content when the dry crops are subjected to water stress and the soil effective water content of the corresponding soil texture, and determining agricultural drought severity grade division according to the STAD value for representing the agricultural drought grade of the research area so as to realize drought monitoring. According to the method, the problem that other indexes fail in drought monitoring of a wet or semi-wet area can be solved, and the method has relatively high universality.

The invention provides a site pollution abatement agent injection method and system, and belongs to the technical field of pollution remediation. The method comprises the following steps: determining an in-situ injection agent; constructing a three-dimensional site model; based on the optimal injection parameters of different soil texture types, injection points are distributed in the three-dimensional site model, and an injection point vector point location map is obtained; according to the three-dimensional pollution space distribution model, the three-dimensional stratum model, the optimal injection parameters of different soil texture types, the injection point vector point location map and the medicament injection associated equation, generating a medicament injection scheme based on three-dimensional site model driving; the medicament injection scheme is guided into an injection equipment control system, and medicament injection is executed; and when the site pollutant remediation result does not reach the preset standard, updating the three-dimensional site model based on the current site, and repeating the steps until the site pollutant remediation result reaches the preset standard. The consistent distribution of the medicament injection space and the pollution space is ensured, the intelligent and accurate control of medicament injection is improved, and the medicament consumption is reduced.

The invention provides a drought and flood sudden change prediction method fusing a soil moisture content and rainfall coupling model, and relates to the technical field of drought and flood sudden change. Comprising the steps that layered soil moisture content, high-frequency rainfall and auxiliary data are collected and preprocessed, and a soil moisture content-rainfall coupling coordination initial value is constructed and corrected; traversing drought and flood windows by using the standardized soil moisture content-rainfall coupling coordination index sequence, and determining an optimal window; carrying out nonlinear correction, judging a sudden turning event according to a corrected threshold value, and outputting a drought and flood sudden turning prediction result; and calculating a drought and flood sudden change duration prediction value Tint and a soil moisture content rainfall mutation index SPIef according to a drought and flood sudden change prediction result, a soil texture coefficient and the like, constructing a risk matrix, outputting an early warning level and a response suggestion in combination with the vulnerability of the disaster-bearing body, and outputting early warning information. According to the method, the optimal window is determined and optimized, drought and flood sudden turning is predicted, the scientificity and accuracy of prediction are guaranteed, and the practical application value is enhanced.

The invention relates to the technical field of geotechnical engineering investigation, and provides a soil layer identification method and system based on static sounding data, and the method comprises the steps: carrying out the framing of static sounding sequence data through a sliding window, and carrying out the layering according to the formation process of a soil layer, the method comprises the following steps: inputting each soil layer in an uplink soil layer into an uplink head for soil layer evolution information extraction, inputting each soil layer in a downlink soil layer into a downlink head for soil layer evolution information extraction, carrying out vector splicing on features extracted by the uplink head and the downlink head, and then carrying out classification, so that a soil development and evolution rule can be comprehensively captured; redundant information is abandoned, and the purpose of capturing stratum depth sequence correlation to assist in soil texture type prediction is achieved.

The invention provides a soil carbon reserve measuring and calculating method and system and a medium, and belongs to the technical field of organic carbon reserves, and the method comprises the following steps: obtaining surface layer reflectivity spectral data of each layer of soil after construction of a disturbance area; dividing a plurality of grids based on the spatial distribution characteristics of the reflectivity spectrum; according to the coordinates of the center position of each grid, the soil texture and land utilization type corresponding to each grid in the database are called, and according to the reflectivity spectral characteristics of each grid, the soil organic carbon content on each grid is inverted through a pre-trained organic carbon content estimation model; according to the center position coordinate of each grid, calling the corresponding soil bulk density on each grid in the database, and determining the soil organic carbon reserve on each grid based on the soil bulk density and the soil organic carbon content; wherein the database stores soil texture, volume weight and land utilization type data corresponding to different coordinates; and obtaining the soil organic carbon reserve of the disturbance area according to the soil organic carbon reserve of each grid. The method can efficiently calculate the soil carbon reserve in the field.

The invention belongs to the technical field of plant planting, and discloses a plant root zone water-retaining agent targeted application method and system based on an intelligent model, and the method comprises the steps: obtaining plant parameter data, planting pit structure data and soil texture data; determining a root zone radius and a root zone effective depth, calculating a root zone cross section area and a root zone volume, and obtaining the number of layers and the volume of each layer; obtaining a water supply event record and a water content time sequence, obtaining a root zone equivalent infiltration volume, and obtaining a root zone effective water retention volume; calculating the notch volume of the effective moisture supply of the root zone by combining the effective moisture retention volume of the root zone, and endowing the notch with a grade mark; pre-constructing a water-retaining agent application prediction model, and outputting a water-retaining agent target dosage and layered putting proportion set; correcting an output result of the water-retaining agent application prediction model; modeling analysis is carried out on the moisture retention and notch of the root zone through the model, the water-retaining agent dosage and the layering proportion are output, and the pertinence and stability of water-retaining agent application are improved.

The invention relates to the technical field of soil quality monitoring and analysis, and discloses a soil quality data monitoring and analysis system which comprises a data acquisition unit, a data integration unit, a data analysis unit and a result output unit.In the soil quality data monitoring and analysis system, a multi-sensor network is combined with spatio-temporal information to acquire various data and integrate the data into a multi-dimensional matrix, and a foundation is laid for analysis; soil texture classification and ventilation evaluation can determine texture types and reflect ventilation conditions, planting and seed selection can be reasonably planned, and crop growth environment suitability and yield can be improved; nutrient conditions can be accurately judged through nutrient balance analysis, reasonable fertilization and environmental protection are assisted, the salinization degree is judged through conductivity, salinized soil can be conveniently improved in time, and degradation is prevented; the detailed report is convenient for each person to know the soil quality, thereby scientifically deciding, optimizing the planting structure, improving the scheme and the management strategy, improving the agricultural production and resource utilization efficiency, reducing the production risk and promoting the agricultural sustainable development.

The invention discloses a device capable of flexibly adjusting turning and burying depth and returning amount, which comprises a main frame and further comprises the following modules: a straw treatment module arranged at the front part of the main frame and used for collecting field straws; the straw crushing module is arranged at the position of the middle of the main machine frame and used for crushing straw and conveying the crushed straw; and the straw turning and burying module is arranged at the rear part of the main frame. According to the device capable of flexibly adjusting the turning and burying depth and the field returning amount, through the depth adjusting module, the straw turning and burying depth can be accurately controlled according to the actual conditions of different soil textures, crop root system distribution and the like, and meanwhile the field returning amount is reasonably adjusted; straw can be fully turned and buried into soil, sufficient organic matter is provided for the soil, adverse effects on crop growth caused by too deep or too shallow turning and burying and too large or too small returning amount can be avoided, and the agricultural production quality is effectively improved.

The invention discloses a soil texture remote sensing mapping method based on time window screening. The method comprises the following steps: step 1, collecting and testing a soil sample; 2, screening a remote sensing image time window; step 3, acquiring and preprocessing an environment covariable; 4, constructing a multi-source data set; 5, constructing a soil texture prediction model; 6, multi-temporal remote sensing covariable combination optimization modeling is carried out; and step 7, soil texture mapping based on the optimal multi-temporal remote sensing combination. And fusing the multi-source environment covariable and the multi-temporal remote sensing data, and constructing a soil texture prediction model based on the optimal multi-temporal model combination by adopting an extreme gradient lifting algorithm. The problems of insufficient representativeness and weak generalization ability of single-time-phase remote sensing data are solved. On one hand, the generalization ability of the model is improved, and on the other hand, quantitative analysis of the key environmental factors is realized in combination with the SHAP technology, the interpretability of the model is enhanced, and meanwhile, the soil texture prediction precision is effectively improved.

The invention provides a dredger sensor health state diagnosis method and system, and belongs to the technical field of ship equipment health management.The dredger sensor health state diagnosis method comprises the following steps that N recent continuous sampling points are selected, a data mean value and a standard deviation in a sliding window are calculated, and a threshold confidence interval is defined; if the current sampling value continuously falls into the threshold confidence interval for M times; data such as mud pump power, mud density, pressure and flow velocity are collected in real time through the data collection unit, the mean value and the standard deviation are analyzed and calculated through the signal preprocessing unit, and then the fault type is judged in combination with the dynamic threshold value adaptation module, the soil texture classification strategy module and the redundancy check module. Alarm signals such as disconnection, water inflow and border crossing are triggered according to priorities through an alarm output unit, and the problems of mismatching of static thresholds, poor soil adaptability, high false alarm rate and the like in the prior art are solved by utilizing dynamic threshold adjustment, multi-dimensional data fusion and redundancy check mechanisms.