5804results about "Material resistance" patented technology

The invention relates to the technical field of water pollution detection, in particular to a water quality pollution multi-dimensional analysis system which comprises the following steps: synchronously measuring an ultraviolet-visible absorption spectrum of a water sample to be detected and scattered light intensity in an orthogonal direction, and deducting spectrum baseline interference caused by suspended particulate matters in the water sample through a correction algorithm; the interferents in the water sample are selectively converted and degraded by applying a programmed potential to the inflowing water sample to be detected; the reverse pulse is periodically applied, so that the online regeneration function of the electrode is realized; analyzing the spectral data by adopting a multivariate correction algorithm, and calculating the concentration of the target pollutant; the calculation residual error of the multivariate correction algorithm is analyzed, new interference and system performance drift of current measurement are diagnosed, and a corresponding system state code is generated; and responding to the system state code, automatically starting and carrying out state checking and multi-point calibration on the instrument, and using a calibration result to update the analysis model. Through multi-dimensional perception and closed-loop operation, accuracy and reliability of water quality monitoring are guaranteed.

The invention, which belongs to the technical field of intelligent breeding equipment, discloses an underwater bionic robotic fish school cooperative breeding environment dynamic monitoring and regulation system comprising a bionic robotic fish body core module, a group cooperative control core module and an intelligent regulation core module. The bionic robotic fish module simulates a real fish swimming mode and carries various water quality sensors to autonomously cruise, so that interference to cultured fishes is reduced; the group cooperation module utilizes a cluster intelligent algorithm and an underwater acoustic communication technology to realize coordinated movement of multiple robotic fishes and full coverage of a monitoring area; the intelligent adjusting module is based on an abnormal detection algorithm, and integrates a miniature oxygenation device, a pH adjusting device and the like to achieve precise regulation and control of the local environment. By the adoption of the system, dynamic sensing and active regulation and control of the culture environment are achieved, a bionic monitoring regulation and control solution is provided for modern aquaculture through intelligent cooperation of the robot fish school and the management system, and the system has the important value of improving the culture efficiency and improving the growth environment.

The invention relates to the technical field of hydrological detection, and discloses a water quality detection equipment calibration system based on artificial intelligence assistance, which comprises a data preprocessing module, a drift identification module, a model comparison module, a self-adaptive calibration module and a feedback updating module. According to the water quality detection equipment calibration system based on artificial intelligence assistance provided by the invention, the aspects of data processing precision, drifting identification capability, calibration response efficiency and model adaptability are remarkably improved. Through cooperative work of multiple modules, the system can realize full-process intelligent operation from original data acquisition to calibration execution to model self-updating, the human intervention frequency is reduced, and the stability and accuracy of long-term operation of equipment are improved.

The invention discloses a soil salinity inversion method, system and device based on multi-mode remote sensing data fusion and a storage medium, and is applied to the technical field of soil quality monitoring, and the method comprises the steps: obtaining radar and optical remote sensing data of a to-be-inverted region of soil salinity, and carrying out the conductivity measurement, and taking the obtained data as an inversion index of the soil salinity; obtaining multi-modal remote sensing features based on radar and optical remote sensing data fusion, optimizing a remote sensing feature combination by combining the radar and optical remote sensing data and based on a random forest algorithm and utilizing a recursive feature elimination method, and performing model performance evaluation on the remote sensing feature combination by adopting cross validation to obtain an optimal remote sensing feature combination; and based on the optimal remote sensing feature combination, constructing and training a soil conductivity prediction model based on a random forest algorithm, and inputting to-be-measured data to the conductivity prediction model after hyper-parameter adjustment to complete soil salinity inversion. According to the method, more accurate inversion of the soil salinity under the interaction influence of a complex environment and human factors is realized.

The invention relates to the technical field of circuit boards, and discloses a circuit board interlayer connection detection method, device and equipment, and the method comprises the steps: carrying out the electrical characteristic parameter measurement of a multilayer flexible circuit board, and obtaining the characteristic parameter data of the circuit board; designing and arranging a multi-test-point detection structure on the multi-layer flexible circuit board, and performing signal excitation to obtain test point position information; applying a differential excitation signal, and collecting a differential response waveform between the test points to obtain a time domain reflection signal feature; impedance spectrum conversion and parameter extraction are carried out on the time domain reflection signal features, and an interlayer connection impedance distribution diagram is obtained; and establishing an interlayer connection defect characteristic model aiming at nickel-based alloy wire fracture, interface cracking and liquid metal fiber felt delamination in various bending states by utilizing the interlayer connection impedance distribution diagram, so that accurate classification of defect types and severity is realized, and interlayer connection faults and surface welding quality problems can be distinguished; and the misjudgment rate is greatly reduced.

The invention relates to a lake water quality real-time monitoring method and system based on a sensor array. The method comprises the steps that the sensor array is arranged in a target lake, and data acquisition frequency parameters are set; acquiring working parameters of the sensor array in real time, analyzing the working parameters, determining health states of the sensors, and performing adaptive adjustment on the sensors based on the health states of the sensors; collecting water quality monitoring data in real time based on the adjusted sensor array, performing preprocessing and quality control verification on the water quality monitoring data, and constructing a monitoring data set with qualified quality control; and comparing each water quality index in the monitoring data set with qualified quality control with a preset environmental standard limit value, marking a limit value exceeding event, and performing early warning, thereby completing real-time monitoring of the water quality of the target lake. According to the invention, intelligent real-time monitoring, abnormity identification, data quality control and early warning response of lake water quality are realized, and comprehensive technical support is provided for water environment management.

The invention provides a flexible palladium film hydrogen sensor and a preparation method thereof, the flexible palladium film hydrogen sensor is sequentially provided with a flexible substrate, a hydrogen sensitive sensing layer and a contact connection layer from bottom to top, and the contact connection layer is connected with a resistance measurement unit; and the hydrogen-sensitive sensing layer is a palladium or palladium alloy film with a conical micro-nano structure. The palladium or palladium alloy thin film with the conical micro-nano structure provides a hydrogen sensor conical surface micro-nano structure with a high specific surface area for the flexible palladium thin film hydrogen sensor, and the process that hydrogen is adsorbed, dissolved and diffused into the palladium or palladium alloy thin film is accelerated, so that the response speed of the sensor is increased; according to the hydrogen sensor, the flexible substrate is adopted, so that the hydrogen sensor can be conveniently arranged in various narrow spaces, and the applicability of the hydrogen sensor in various scenes is improved.

The invention discloses a self-adaptive calibration system and method for a combustible gas sensor. The self-adaptive calibration system and method are suitable for a catalytic combustion type combustible gas sensor. The system comprises a basic calibration unit, a real-time monitoring unit, a drift detection and compensation unit and an output adjustment unit. The basic calibration unit is used for carrying out basic calibration on the sensor and determining an initial sensitivity coefficient, zero offset and response time of the sensor; the real-time monitoring unit is used for monitoring real-time parameters of the sensor under different environmental conditions; the drift detection and compensation unit is used for establishing a sensor performance parameter drift model and calculating a calibration compensation coefficient; the output adjusting unit is used for adjusting the voltage output value of the sensor in real time according to the calibration compensation coefficient; the method can adapt to environment change for real-time calibration, effectively compensates sensor drift, improves measurement precision and reliability, prolongs the service life of the sensor, reduces maintenance cost, and improves system safety.

The invention discloses an egg quality detection system and method based on multi-sensor fusion, and relates to the technical field of multi-dimensional data process.The method comprises the steps that texture features are extracted from visible light images, and feature wavelengths are extracted from spectrums; pressure distribution and shell deformation in the pressing process are synchronously collected; recording a pressure-time curve and a deformation-time curve, extracting characteristic parameters, and constructing a three-dimensional dynamic model; performing wavelet transformation on the response curve of each sensor, extracting time-frequency domain characteristics, and generating a smell fingerprint spectrum; scanning the surface of the egg to excite resonance response, recording a sound pressure signal, and converting the sound pressure signal into frequency domain data through fast Fourier transform; and presetting a business rule, and generating a final decision by combining the model output with a rule matching result. The pressure feature extraction module, the smell feature extraction module and the crack degree quantification module are arranged to realize data depth association, and the quality inspection credibility is improved through an interpretable decision model.

The invention discloses a partition detection method for board card quality, and relates to the technical field of detection. The method comprises the following steps: dividing a board card into functional blocks according to a functional structure, and collecting thermal field distribution characteristic data of each block; constructing a standard thermal template, calculating the thermal imaging matching degree of the functional blocks by using an Euclidean distance algorithm, and marking the thermal imaging matching degree exceeding a preset threshold value as an abnormal thermal response region; collecting resistance and resistance gradient change data of an abnormal thermal response area, judging the area as a defect cluster area if conditions are met, and calculating a resistance abnormal amplitude; integrating defect cluster region data to form a composite characteristic spectrum, inputting a defect sample matching model, and outputting a defect classification result and a confidence score; calculating a regional quality score by combining fuzzy logic reasoning and a neural network algorithm and integrating a thermal imaging matching degree, a resistance abnormal amplitude and a confidence score; and fusing the defect classification result and the regional quality score to generate a quality grade label. And based on the quality grade labels, board card quality partition detection is completed.

The invention discloses a linearity closed-loop optimization method for a semiconductor gas sensor with adjustable voltage dynamic compensation, which relates to the technical field of gas detection and comprises the following steps: controlling the semiconductor gas sensor to start in a clean air environment, outputting an initial test voltage sequence through a voltage regulator, the method comprises the steps of collecting sensor reference resistance under different voltages, screening out initial working voltage with the minimum resistance fluctuation quantity, synchronously collecting initial environment temperature and humidity, and calibrating the sensor reference resistance based on preset temperature and resistance coefficients and humidity and resistance coefficients to obtain initial reference resistance. By dynamically adjusting the working voltage and combining real-time compensation on the environment temperature and humidity, the interference of environment factor fluctuation on the resistance characteristic of the sensitive material can be continuously counteracted, so that the linear relation between the output signal of the sensor and the target gas concentration is kept stable, the dynamic optimization of the linearity in a complex environment is realized, and the sensitivity of the sensor is improved. And more reliable basic data is provided for gas concentration detection in an industrial scene.

The invention relates to the technical field of material physical property detection, and discloses an injectable hydrogel wound dressing water absorbability detection method, which comprises: constructing a main measurement and reference dual channel, and synchronously monitoring a mixed conductivity signal and an interference signal generated only by gel self ion leakage; according to the method, the interference is deducted through real-time differential operation, a pure target signal is obtained, and then the water absorption volume of the hydrogel is calculated through inversion based on the law of conservation of mass, a measured object is transferred to an external solution from a gel body, and the interference of a sample is stripped through an endogenous dynamic correction mechanism, so that the accuracy of the water absorption volume of the hydrogel is improved. The determinacy of a measurement result is derived from a physical law instead of model hypothesis, so that double restrictions caused by irregular sample forms and complexity of a chemical environment are avoided, and reliable quantification of the water absorption performance of the in-situ dynamic forming hydrogel is realized.

The invention provides a titanium plate performance analysis method and system, and relates to the technical field of metal material detection.The method comprises the steps that an optical scanner is adopted to establish a three-dimensional structure on the surface of a titanium plate, and test areas are divided; synchronously acquiring stress, hardness and conductivity data of a test point by using a multi-probe collaborative detection device; constructing a dual-branch feature extraction network, wherein the dual-branch feature extraction network comprises a surface topography feature branch and a physical feature branch; performing statistical integration on the features in the test area, calculating distribution features and determining a weight coefficient; and generating a performance analysis result through feature fusion and a multi-task output layer, and finally determining the performance grade of the titanium plate. According to the method, deep fusion of morphology information and physical characteristics is realized, and the accuracy and reliability of titanium plate performance evaluation are improved.

The invention relates to the field of ulcerative colitis, and discloses a multi-parameter monitoring system for evaluating the intestinal barrier function of ulcerative colitis, which is used for realizing the goal of automatically adjusting a treatment scheme according to a monitoring result by constructing a closed-loop feedback treatment system. According to the invention, by designing the nanoprobe of which the surface is modified with a specific binding element and combining with a swallowing capsule endoscopy, real-time imaging and molecular level dynamic tracking of the intestinal barrier are realized, genetically engineered bacteria are constructed to quantify intestinal permeability abnormality and local inflammation level, and an intestinal barrier function damage score and a disease progress prediction result are output; individual monitoring is achieved through transfer learning, ultrasonic elastography, optical coherence tomography, wearable equipment for measuring intestinal electric field impedance spectroscopy and other technologies are adopted, an intestinal wall mechanics-electrophysiology composite parameter set is obtained, and the evaluation accuracy is improved.

The invention discloses a gas sensing material based on Ag / Pd-LaFeO3 and application of the gas sensing material in detection of hydrogen sulfide gas in municipal sewage, and relates to the technical field of gas sensing materials. The chemical formula of the gas sensing material based on Ag / Pd-LaFeO3 is X wt% of Ag-Y wt% of Pd-LaFeO3, wherein 0 lt; x < = 5, 0lt; y < = 5. According to the invention, on the basis of LaFeO3, the humidity interference resistance of the gas sensing material based on Ag / Pd-LaFeO3 can be improved through double noble metal surface modification of Ag and Pd. In addition, through double noble metal doping of Ag and Pd, the response sensitivity and selectivity of the prepared gas-sensitive material to H2S gas can be improved, and the working temperature of the gas-sensitive material is reduced. Specifically, at the working temperature of 110 DEG C, the response value of the prepared double noble metal modified LaFeO3 to 1ppm H2S gas is 46.16.

The invention provides an aluminum enameled flat wire online defect detection and self-adaptive deviation correction method and system, and relates to the technical field of enameled wire defect detection.The aluminum enameled flat wire online defect detection and self-adaptive deviation correction method comprises the steps that an aluminum enameled flat wire is immersed in fluid with set viscosity, and a reference fluid resistance signal and a reference electromagnetic signal are collected; fluid resistance signals and electromagnetic induction signals are detected in real time; positioning defect positions of surface defects of the enameled wire; identifying types and distribution of internal defects of the aluminum enameled flat wire; distinguishing defect types through a machine learning algorithm; outputting a corresponding correction scheme through the pre-trained neural network model; and outputting the deviation correction control signal to the correction module for deviation correction operation. Through synchronous acquisition and analysis of fluid resistance signals and electromagnetic induction signals, synchronous detection of surface defects and internal defects is realized, and the limitation of a traditional single detection means is solved; by forming a high-precision three-stage classification system, an interpretability report is generated, and the classification accuracy of the composite defects is remarkably improved.

A spoke winding type high-sensitivity humidity sensor, the humidity sensor comprising a humidity-sensitive winding material and a spoke winding skeleton disc; a plurality of "T" shaped winding skeletons are uniformly distributed in a radial manner on the circumference of the spoke winding skeleton disc, and the humidity-sensitive winding material is wound on the plurality of "T" shaped winding skeletons; the space between every two adjacent "T" shaped winding skeletons simultaneously constitutes a winding limiting groove and an air flow channel, and after the humidity-sensitive winding material is wound, there is still space, i.e. the air flow channel, for air circulation, which is used to shorten the humidity absorption response time and the humidity desorption response time of the humidity-sensitive winding material.

The invention discloses a method for predicting the damage of a prestressed concrete cylinder pipe in a complex environment, and relates to the technical field of pipeline structure health monitoring, and the method comprises the steps: collecting multi-physical field data through deploying multiple types of sensors, transmitting the data to a central monitoring system in a wireless manner, carrying out the standardized preprocessing, and obtaining a multi-source fusion data set; a salt migration driving index dsa, a stress disturbance induction index yry and an electrochemical activity potential index che are constructed, a comprehensive corrosion risk index SCR is obtained, and corrosion behavior evaluation is carried out. And when the corrosion behavior is evaluated as a disturbance sign, a corrosion change prediction index CAR is further calculated according to time sequence evolution forming a corrosion risk index SCR, grading evaluation and transition identification of the corrosion state are realized, an evaluation result is stored in a database, and a corrosion risk evolution trend is presented through a visual chart. The method supports early warning and emergency response decision making, and has high adaptability and engineering practicability without adding hardware.

The invention discloses a DNAPLs pollutant diffusion migration path depicting method and system, and relates to the technical field of pollution monitoring, and the method comprises the steps: obtaining the soil conductivity of a target region through an improved TDR probe, obtaining the time sequence characteristics and spatial characteristics of a soil conductivity data set, obtaining the fusion spatial-temporal characteristics, calculating the spatial-temporal similarity of historical migration paths, and obtaining the DNAPLs pollutant diffusion migration path depicting result. Screening prior knowledge; constructing a space-time prediction model by using a graph neural network and priori knowledge, extracting deep space-time features from a space adjacent graph and a time-dependent heterogeneous graph corresponding to the target region, and obtaining a conductivity prediction value of a future time step; the diffusion direction of the pollutants is deduced by combining the relation between the resistivity and the DNAPLs concentration, migration frontal surface diagrams at different time points are drawn, and dynamic path visualization is achieved. According to the method, the improved TDR (time domain reflectometry) technology and the deep learning model are combined, so that high-precision monitoring and prediction of the dynamic migration process of the pollutants are realized.

The invention discloses a system for saline-alkali land farmland soil water and salt detection and drought and flood disaster early warning. According to the method, spectral information is extracted through a remote sensing image or an unmanned aerial vehicle image, and a salinity spectral index and a moisture spectral index are constructed. Meanwhile, the water content and the salt content of the soil at different depths are collected. Key spectrum variables are screened through an RXGBoost model, a salinity-moisture coupling relationship is synchronously calculated through a single model, and an independent calibration link is reduced for a calibration process. According to the method, a comprehensive and modular technical method and a solution are applied for the first time, maximum application of limited information is realized, and the technical requirements of efficient utilization, monitoring and management of irrigation water are met; and difficult points and key points coexist. Through deep coupling of theoretical innovation and system design, the system is realized in the field of saline-alkali soil irrigation: single data monitoring is transited to a multidisciplinary collaborative ecological hydrological theoretical system, a recessive water-salt interaction process is converted into modelable and controllable dominant decision parameters, and a systematic solution is provided for efficient utilization of saline-alkali soil agricultural resources.

The invention discloses a target impedance simulation circuit, an element parameter determination method and an impedance simulation jig. The target impedance analog circuit comprises a plurality of RC modules, wherein each RC module comprises a resistor unit and a capacitor unit which are connected in series; part or all of the RC modules are connected in parallel to simulate impedance data of a to-be-measured target. According to the technical scheme provided by the invention, the RC module is adopted to simulate the impedance value, so that the impedance behavior characteristics of the specified object under different frequencies can be accurately simulated, and the device can be flexibly and repeatedly used.

The invention provides a constructional engineering concrete compressive strength detection method and system.The method comprises the steps that multi-modal information of a to-be-detected concrete member for constructional engineering is collected, and the multi-modal information comprises rebound data, ultrasonic data, resistivity data and temperature data; constructing a hybrid prediction model; and outputting compressive strength data according to the mixed prediction model, and visually displaying the compressive strength data. According to the method and the system for detecting the compressive strength of the constructional engineering concrete, disclosed by the invention, multi-modal information such as ultrasonic, rebound, resistivity and temperature of the to-be-detected concrete member is input into the mixed prediction model for compressive strength prediction, and the model can be used for more accurately processing nonlinear and high-dimensional characteristics in data; a transfer learning mechanism is introduced, so that the model adapts to changes of different regions and materials under limited training data, and the generalization ability and accuracy of prediction are improved. And the compressive strength data is visually displayed, so that the analysis efficiency of engineers is improved.

The invention discloses a method and system for detecting abnormal welding spots in the spot welding process. The method comprises the steps that a time sequence data sequence collected in real time in the welding process is obtained; calculating a first-order difference sequence of the time sequence data sequence; screening a target data segment representing a stable trend based on the first-order difference sequence; performing linear fitting on the first K data points of the target data segment to obtain a first trend direction; performing linear fitting on the last K data points of the target data segment to obtain a second trend direction; calculating the variable quantity of the first trend direction and the second trend direction; and when the variable quantity exceeds a preset threshold value, it is judged that welding is abnormal, and an alarm is triggered. The stable trend section is screened through the differential sequence, noise interference is effectively eliminated, and it is ensured that the quality criterion is based on reliable data. And whether the welding spot is abnormal or not is quickly and accurately judged, so that real-time and non-destructive spot welding quality on-line monitoring is realized.

The invention belongs to the field of atmospheric environment particulate matter monitoring, and particularly relates to an atmospheric environment salt mist concentration real-time monitoring device and method. The monitoring device comprises a computer control module, a container and a buoy, a conductivity electrode, a temperature sensor, a displacement sensor, an air inlet pipe and an air outlet pipe are integrated on the top of the container, and the air outlet pipe is connected with a reciprocating cylinder with a piston and a limit switch. The monitoring method comprises the following steps: calibrating the initial volume V < initial > of liquid and the volume V < initial > of a reciprocating cylinder; circularly collecting the conductivity k0 and k1, the temperature T0 and T1 and the displacement D and Dtotal of the buoy before and after ventilation; correcting the salt mass increment delta M through the dynamic volume, and finally outputting the salt mist concentration C; according to the invention, the defects of inaccurate ventilation volume metering, solution density change and interference of moisture in high-humidity air on concentration monitoring in the prior art are overcome, full-automatic continuous monitoring of the salt mist concentration is realized, the measurement error is effectively reduced, the measurement precision and the monitoring capability are remarkably improved, and the method has relatively good environmental adaptability.

The invention provides a portable water quality detection system based on multi-sensor fusion, self-calibration and image recognition, and relates to the technical field of water quality detection.Water quality parameters are collected through multi-sensor fusion, data are processed in combination with the deep learning self-calibration and image recognition technology, and a comprehensive water quality analysis result is generated; the system integrated communication module uploads data to a cloud end in real time, low-power-consumption power management is achieved, portable deployment of field and emergency scenes is supported, the detection accuracy, intelligence and real-time monitoring capacity are remarkably improved, and efficient water quality safety supervision is achieved.

The invention belongs to the technical field of preparation of sensor materials, and particularly relates to a room-temperature formaldehyde sensor material based on a catalytic principle as well as preparation and application of the room-temperature formaldehyde sensor material. The polyphenol is adsorbed on the surface of the semiconductor metal oxide through chelation, then noble metal ions are introduced, and the polyphenol on the surface of the semiconductor metal oxide can capture the noble metal ions and reduce and stabilize the noble metal ions on the surface of the semiconductor metal oxide; the noble metal nanoparticles are anchored on the surfaces of the semiconductor metal oxide nanoparticles, the original morphology of the semiconductor metal oxide is maintained, and the noble metal nanoparticles are loaded on the surfaces of the semiconductor metal oxide nanoparticles. The nano composite material not only has the intrinsic electrical and thermodynamic properties of semiconductor metal oxide, but also combines the catalytic characteristics of noble metal nanoparticles, so that the lower detection limit of formaldehyde is reduced to 3ppb, and the sensitivity of the sensor is remarkably improved. The preparation method of the room-temperature formaldehyde sensing material is simple and suitable for large-scale production, the raw materials are simple and easy to obtain, the cost is low, and the materials are environment-friendly.

The invention relates to the technical field of environment monitoring, in particular to an intelligent digital rural environment monitoring system and method based on big data, and the system comprises a layered water potential collection module, a gradient reverse correction module, a path inversion modeling module and a multi-dimensional diffusion modeling module, and the layered water potential collection module calculates and generates rural soil environment monitoring data; the rural soil environment monitoring data comprises layered soil water potential distribution, soil water content gradient and a soil conductivity characteristic value, and the soil water potential abnormal flow data comprises a vertical water potential difference value, an abnormal water flow direction vector and a water flow intensity grade; the moisture permeation path distribution diagram comprises a permeation path distribution structure, a soil water potential accumulation interval and a water flow propagation direction identifier, and the diffusion boundary space model comprises a pollutant diffusion boundary range, a moisture transverse migration region and multi-dimensional diffusion rate distribution. According to the scheme, the abnormal distribution range, the duration time and the development trend are quantitatively described, and the research and judgment accuracy of the abnormal penetration and diffusion process is improved.

The invention discloses a dynamic monitoring method, system and device for soil carbon loss and a storage medium, and relates to the technical field of environment monitoring, and the method comprises the steps: obtaining soil parameters through a multi-mode sensing array and a runoff monitoring device which are arranged in a target soil area, the soil parameters comprise a soil gaseous parameter, conductivity, a soil solid parameter and a liquid carbon parameter; calculating a carbon loss amount generated by soil respiration according to the soil gas state parameter, and taking the carbon loss amount as a respiration carbon flux; according to the conductivity, the soil solid parameters and a preset soil organic carbon content relation model, calculating the carbon loss amount of soil erosion migration as erosion carbon flux; calculating the carbon loss amount of soil leaching loss according to the liquid carbon parameters, and taking the carbon loss amount as leaching carbon flux; and performing weighted summation on the respiration carbon flux, the erosion carbon flux and the leaching carbon flux to obtain the total carbon loss of the soil in the target area. A more comprehensive carbon income and expenditure evaluation method is provided by establishing a soil total carbon loss calculation framework covering'gas-solid-liquid 'three phases.

The invention relates to a soil detection system and a detection method. Soil detection equipment comprises a sampling module, a positioning module for generating original point sampling coordinates, a sample treatment module for chemical, electrochemical and biological treatment means, a detection module, a detection database, a detection control module, a generating and sending module and a sending and receiving module. The detection method comprises the steps of sampling and processing, binding coordinates, comparing abnormal data through preliminary detection, generating a pollution map, carrying out secondary detection on abnormal data, calculating a spatial uncertainty index, dynamically generating a near-origin secondary sampling coordinate, circularly sampling and detecting until the index reaches the standard or the density upper limit, and finally generating the pollution map and a prediction model. And the detection database is updated and optimized through machine learning.

The invention belongs to the technical field of water quality monitoring, and discloses a reclaimed water reuse landscape water quality change monitoring method and system, and the method comprises the steps: obtaining original measurement data of a target index in a water body and a plurality of environment background parameters representing a water body environment background; analyzing and calculating a dynamic influence relationship between the original measurement data of the target index and each environment background parameter to obtain a state parameter representing a measurement deviation state of the target measurement device; determining a correction value corresponding to the current environment background and the measurement deviation state of the target measurement device by using a pre-established knowledge base according to the plurality of environment background parameters and the state parameters; correcting the original measurement data of the target index by using the correction value to obtain the corrected measurement data of the target index for evaluating the long-term influence of the reclaimed water on the aquatic ecological environment; an evaluation result is sent to a remote monitoring center; therefore, accurate measurement data can be provided, and reliable long-term influence evaluation is realized.