97 results about "Chemical index" patented technology

The invention discloses a method and a system for analyzing a pollution source of a rainwater pipe network. The method comprises the following steps of: 1, obtaining a first key fluorescence characteristic parameter combination according to basic physicochemical indexes by adopting a fluorescence characteristic parameter prediction model; 2, three-dimensional fluorescence characteristic parameters of the pollution source are obtained, and a pollution source three-dimensional fluorescence characteristic data set is obtained; screening by adopting a multivariate statistical method to obtain a second key fluorescence characteristic parameter combination; 3, determining a fluorescence characteristic parameter combination according to the first key fluorescence characteristic parameter combination and the second key fluorescence characteristic parameter combination; 4, inputting the fluorescence characteristic parameter combination into the Bayesian mixture model to obtain the contribution rate of the pollution source to the receptor water quality, and completing the analysis of the pollution source of the rainwater pipe network; according to the method, the DOM fluorescent fingerprint information is predicted by adopting basic data; and based on the three-dimensional fluorescence characteristic parameters and in combination with a Bayesian mixture model, precise quantitative analysis of the pipe network pollution source is realized.

The invention discloses a river nitrogen pollutant source analysis method based on drainage basin nitrogen turnover and isotope, and particularly relates to the technical field of water treatment.The river nitrogen pollutant source analysis method comprises the following steps that a drainage basin to be researched is selected, river water and soil samples in the drainage basin are systematically collected, and physical and chemical indexes and isotope indexes # imgabs0 # of the collected samples are tested. Nitrate marked by nitrogen isotope delta 15N / delta 18O and # imgabs1 # are used as key indication marks to perform high-precision identification on nitrogen sources in a river and an environmental system, the contribution proportion of different nitrogen sources to the nitrate concentration in a water body is quantified through a stable isotope analysis model, and the concentration of the nitrate in the water body is calculated. And in combination with data, the rates of denitrification and anaerobic ammonia oxidation in environmental samples, sediments and soil are directly measured through combined application of an isotopic tracer technology and a membrane inlet mass spectrometer technology.

The invention discloses a water environment safety early warning method and system based on the Internet of Things, and relates to the technical field of water environment monitoring and safety alarming, and the main scheme is as follows: firstly, collecting water quality physical and chemical parameters and water quantity parameters of a current detection period, then respectively calculating each subentry index, and calculating the water quality index; comprising temperature, turbidity, conductivity index and the like obtained by physical parameters, dissolved oxygen, pH value, lead content index and the like obtained by chemical parameters, and water quantity index, so as to obtain water quality physical index, chemical index and water environment safety index, and then judge whether to trigger safety real-time alarm or not; and acquiring data of a previous cycle to calculate a historical water environment safety index and an index growth rate, and comparing with corresponding threshold values to judge whether to give a delayed alarm. According to the method, multi-parameter and multi-cycle data are integrated, a comprehensive and accurate judgment basis is provided for water environment safety monitoring, the monitoring accuracy and reliability are effectively improved, and the water environment safety is guaranteed.

The invention relates to the technical field of grease detection, in particular to a grease detection data analysis system and method based on multi-source data. The method comprises the following steps: acquiring grease multi-source detection data, and performing near infrared spectrum detection feature extraction according to the grease multi-source detection data so as to obtain infrared spectrum detection data; performing signal enhancement processing on the infrared spectrum detection data to generate enhanced infrared spectrum data; carrying out physicochemical index feature extraction based on the grease multi-source detection data so as to obtain physicochemical index data; performing detection anomaly analysis according to the physicochemical index data and the enhanced infrared spectrum data so as to obtain grease anomaly detection data; and performing type division on the grease anomaly detection data so as to obtain grease chemical component anomaly data and grease microorganism anomaly data. Based on the grease detection technology, the abnormal recognition rate and the quality evaluation accuracy of grease detection are improved.

The invention discloses a soil physical and chemical parameter spectrum inversion method based on an SVM and a BP neural network. The method comprises the steps that near infrared spectrum data of soil samples with different water contents are collected and preprocessed; training and verifying a pre-constructed dry and wet soil sample classification model based on an SVM (Support Vector Machine) by utilizing the near infrared spectrum data of the preprocessed soil samples with different water contents, and dividing the soil samples into dry soil and wet soil by utilizing the trained dry and wet soil sample classification model; and respectively training and verifying a pre-constructed soil physical and chemical parameter prediction model based on a BP neural network by using the near infrared spectrum data after the pretreatment of the dry soil and wet soil samples and the measured values of the physical and chemical parameters of the soil samples to obtain soil physical and chemical parameter prediction models corresponding to the dry soil and wet soil samples respectively. The model not only can improve the accuracy and efficiency of soil physical and chemical index analysis, but also can provide a scientific basis for agricultural production and environmental protection.

The invention provides an earth surface geochemical identification method and system for geothermal resource fracture, and the method comprises the steps: preferably selecting a plurality of geothermal fracture chemical identification indexes according to the conduction characteristics of heat in a stratum and the response attributes of elements to heat, carrying out the collection operation, obtaining a sample, processing the sample according to the sample measurement demands, and carrying out the detection of the geothermal resource fracture. Determining data of different chemical identification indexes of the sample by adopting a matched instrument; according to the types of the chemical identification indexes and the corresponding numerical value distribution condition, the type of geothermal fracture and the heat transmission direction are identified, wherein the thermal control fracture and the heat conduction fracture are included; and further calculating a temperature evaluation score of geothermal fracture based on a chemical identification index to realize grade division. By adopting the scheme, the limitation of the geothermal fracture identification technology in the prior art is overcome, the control heat fracture, the heat conduction fracture, the heat transmission channel and the heat transmission direction are identified by adopting the earth surface geochemical indexes, and the identification efficiency and accuracy are higher.

The invention provides a method and system for determining a water quality risk value of industrial sewage, and the method comprises the steps: obtaining water quality monitoring data of different monitoring points, obtaining a physical index parameter, a chemical index parameter and a biological index parameter, and constructing a water quality parameter of a target water area; the method comprises the following steps: training historical physical index parameters, historical chemical index parameters and historical biological index parameters of historical water quality monitoring data to obtain a water quality monitoring deduction model, and deducing water quality parameters of a target water area through the water quality monitoring deduction model to obtain an initial water quality risk value; the corresponding actual index parameters are obtained by updating the water quality monitoring data of different monitoring points in real time, the parameters of the water quality monitoring deduction model are optimized, and the optimized water quality risk value is obtained through deduction again. The industrial sewage is subjected to multi-index analysis, the water quality risk trend is predicted, and the water quality monitoring accuracy of the industrial sewage is improved.

The invention belongs to the technical field of physical and chemical index prediction of jerusalem artichoke, and particularly relates to a method for rapidly predicting main physical and chemical indexes in jerusalem artichoke based on a near infrared spectrum technology. The method mainly comprises the steps of pretreatment of a jerusalem artichoke sample, acquisition of physicochemical indexes and spectral data, pretreatment of the spectral data, screening of characteristic wave bands, establishment of a quantitative prediction model, evaluation and verification of model performance and the like. According to the invention, a partial least squares regression (PLSR) model of inulin, protein, total polyphenol and ash content in jerusalem artichoke is established, and an external verification result of the model shows that detection results obtained by a near infrared spectrum and a standard chemical method have no significant difference. Compared with a traditional chemical detection method, the near-infrared technology improves the analysis efficiency and reduces the detection cost on the basis of meeting basic detection requirements, and has an application prospect in rapid prediction of the physical and chemical indexes of the jerusalem artichoke in actual production.

The invention provides a biochar soil carbon sequestration stability prediction method and device and a storage medium, and relates to the technical field of biochar soil carbon sequestration stability prediction.The method comprises the steps that a test soil physical and chemical index data set A and a control soil physical and chemical index data set B are obtained; establishing a nonlinear regression model M1 by using A and B; constructing a training sample set; training a preset initial machine learning model by using the training sample set to obtain a target prediction model M2; obtaining the accuracy eta2 of the prediction result of the M2; if eta2 is greater than QR, predicting the soil carbon sequestration stability of the to-be-predicted soil by using M2; determining a first weight alpha 1 corresponding to the M1 and a second weight alpha 2 corresponding to the M2 according to the eta 1 and the eta 2; determining the soil carbon sequestration stability of the to-be-predicted soil; according to the method, the accuracy of predicting the carbon sequestration stability of the biochar soil is improved.

The invention discloses a preparation technology of collection paper literature deacidification test paper, and belongs to the technical field of papermaking engineering. The method comprises the following steps: firstly, determining physicochemical indexes of the deacidification test paper according to ontology characteristics of precious ancient books and recent modern paper literatures, then taking saponified rosin size as an internal sizing agent, taking talcum powder as a filler, taking cationic polyacrylamide (CPAM) as a retention aid, and finally, carrying out papermaking and drying to obtain the deacidification test paper. The performance of the product prepared by the process is basically consistent with that of recent modern literature paper, the product has the capability of replacing a paper literature body to carry out lossy testing, and a more reliable, more comprehensive and more economical basis can be provided for constructing a deacidification effect evaluation system.

The embodiment of the invention provides a catalyst activity analysis method and system based on material surface physical and chemical indexes, and relates to the technical field of water treatment. According to the method, a sample data set can be obtained firstly, after the sample data set is divided into a training set and a test set, the training set is used for training a plurality of alternative models, and then a prediction model is selected from the alternative models. And inputting data of a catalyst to be detected into the prediction model to obtain a predicted degradation rate output by the prediction model. Wherein the sample data set comprises surface physical property parameters such as pore depth gray difference of the catalyst and surface chemical property parameters such as functional group peak height ratio. According to the method, alternative model training can be carried out through Bayesian optimization, a prediction model is selected by combining evaluation indexes obtained by calculation of a test set, and a machine learning process can be enhanced by utilizing multi-mode fusion data in an environment of small sample machine learning data volume, so that the prediction precision and generalization ability of catalyst activity analysis are improved.

The invention relates to the technical field of early warning and monitoring, in particular to a deep groundwater supplementation data analysis and early warning system which comprises a signal processing module, an oxygen consumption analysis module, a nitrogen transmetabolism module, a risk identification module and a coupling optimization module. According to the method, the metabolism trend is analyzed by synchronously collecting underground multi-depth chemical indexes and removing noise, establishing a unified time sequence data set, extracting dissolved oxygen, nitrate and ammonia nitrogen concentration change characteristics, calculating the oxygen dissipation rate and constructing the time-depth distribution relation, and combining nitrogen conversion rate regression. A risk section is identified according to the directions of oxygen dissipation increase and metabolism decrease, the micro-potential gradient and coupling index change are further analyzed in combination with an electrochemical change rule, dynamic identification and risk early warning of the deep groundwater refilling process are achieved, and monitoring is changed from static data comparison to multi-dimensional dynamic analysis. The accuracy and the timeliness of abnormal recognition are improved, and the complement safety and the continuity and the reliability of data results are guaranteed.

The invention discloses a method for rapidly detecting the aging year of pericarpium citri reticulatae, which comprises the following steps: constructing a function model of the aging year of pericarpium citri reticulatae and physical and chemical index parameters of pericarpium citri reticulatae, and then inputting corresponding physical and chemical index parameter values of pericarpium citri reticulatae of a pericarpium citri reticulatae sample to be detected into the function model to obtain the aging year of the sample to be detected. According to the method, the advantages of optical and chemical analysis technologies are combined, through simple determination of physical and chemical indexes, the operation is simple, the aging years of the dried orange peel can be detected in a short time, and the detection efficiency is improved. Through double verification of quantitative analysis and statistical analysis, personal errors are reduced, and the accuracy and objectivity of detection are improved. The method can also be popularized to aging year detection of other traditional Chinese medicinal materials or agricultural products, and has a wide application prospect.

The invention discloses a coal slime flotation dosing data processing method and system. The method comprises the steps that a continuous image sequence of surface foam of a flotation cell is collected, and X fluorescence detection signals are collected; converting the continuous image sequence from an RGB color space to an HSL color space; the change rate of the single foam surface area along with time is calculated to track the foam fusion behavior, and an overall foam merging rate index is obtained; calculating the foam viscosity according to the integral foam merging rate index and the diameter distribution of the foam; calculating the foam ash content and the foam water loading rate according to the fluorescence intensity and the total fluorescence signal in the X fluorescence detection signal; constructing a multi-modal feature vector; according to the multi-modal feature vector, feature extraction is carried out through a neural network, and a foam quality comprehensive score and a foam change trend are obtained; aiming at inaccurate extraction of coal slime flotation froth features in the prior art, the stability and the product quality of the flotation process are improved through combination of visible light image features and X fluorescence chemical indexes and the like.

The invention belongs to the technical field of heating cigarette processing, and particularly relates to a method for improving the thickness stability of thick paste method tobacco sheets. By adding part of adhesive in the plant fiber pulping process, adding real-time viscosity detection, feedback and microwave heating fine adjustment mechanisms while heating in a water bath, and combining methods of controlling the liquid level of slurry in a headbox, keeping a metal belt to run at a constant speed, controlling a drying program and the like, the thickness stability of slices among batches and in the batches is improved, and the quality of the slices is improved. The stability of physicochemical indexes such as slice quantification, tensile strength and moisture is improved, fluctuation of the product thickness is reduced, repeated adjustment is avoided, the method is simple and convenient, the slurry ratio cannot be changed, and the production efficiency is improved.

An intelligent discrimination method and apparatus for a mine water inrush source, a device, and a storage medium. The method comprises: acquiring a water chemical index of a water source sample to be discriminated (S1), wherein the water chemical index comprises a plurality of inorganic indexes and a plurality of organic indexes; and inputting the water chemical index into a preset water source discrimination model to obtain a water source type of said water source sample (S2). In addition to inorganic indexes for discrimination, organic indexes are added, so that the problem of being difficult to accurately discriminate, by means of inorganic water chemical indexes, water samples with similar component is solved, thereby improving the accuracy of water source type discrimination.

The invention relates to the technical field of tobacco leaf processing, in particular to a flue-cured tobacco real-time grading method and device based on near-infrared online detection data. Firstly, chemical indexes, obtained based on the near-infrared online detection data, of flue-cured tobacco leaves are associated with quality grades obtained in an appearance grading mode; the method comprises the following steps of: screening key chemical indexes through an information gain and a Fisher criterion, and then selecting an iterative algorithm (Informational gain and Fisher crisis restitution) to screen out the key chemical indexes through the information gain and the Fisher criterion; secondly, designing a tobacco leaf quality chemical index grading table aiming at a specific producing area on the basis of the screened key chemical indexes in combination with rich and historical tobacco leaf chemical index statistical data; finally, real-time grading of the flue-cured tobaccos is achieved on the basis of the combination of near-infrared online detection data and a designed chemical index grading table, and the grading efficiency and accuracy are improved. The problems that when tobacco leaves are graded in real time in the prior art, the grading quality is uneven and the grading efficiency is low in the flue-cured tobacco grading process due to the fact that chemical indexes referred to in the tobacco leaf grading process are different are solved.

The invention relates to the technical field of nuclear power plant engineering, and discloses a WANO chemical index calculation method and system for a pressurized water reactor nuclear power plant, and the method comprises the steps: obtaining the chemical parameters and operation state of a nuclear power plant; determining WANO chemical index calculation logic, and calculating WANO chemical indexes according to the chemical parameters; and triggering an abnormal alarm according to the WANO chemical index. The method is suitable for different reactor types and working conditions, has wide applicability, solves the problem of false alarm or missing alarm in a fixed limit value mode, provides accurate operation guidance for operators, reduces the operation risk, improves the operation and maintenance efficiency, fills the blank of insufficient combination of dynamic adjustment and working conditions in the prior art, and improves the operation and maintenance efficiency. And the method has remarkable innovativeness and practical engineering value.

The application provides a heavy metal contaminated paddy field agricultural product quality safety evaluation method and application, and belongs to the field of agricultural product quality safety evaluation. The evaluation method comprises the following steps: (1) taking field soil physical and chemical indexes and heavy metal data as a bottom base for model training and verification, screening factors for evaluating agricultural product quality safety, and clarifying the causal relationship between each factor and agricultural product quality safety; (2) constructing an agricultural product quality safety evaluation model for evaluating agricultural product quality safety. The two-stage cascade model combining nonlinearity and linearity and the multi-dimensional driving mechanism analysis based on SHAP provide a reliable bottom algorithm support and theoretical research basis for quantitatively evaluating the occurrence state and transformation and cross-medium transfer rule of Cd / As composite pollution in the Xiangjiang River Basin.

The invention relates to the field of surface water quality safety evaluation, in particular to a CRITIC method-based physical and chemical index water environment quality evaluation method, which comprises the following steps of: determining a quality evaluation index based on a water body type; according to the selected quality evaluation index, calculating the condition of the quality evaluation index and then assigning a score; an original index data matrix is constructed to store assigned scores of the quality evaluation indexes, and nondimensionalization is carried out on data values in the original index data matrix; calculating the standard deviation of data values in the original index data matrix, and calculating the conflict of the evaluation indexes; calculating the information amount of the quality evaluation index, and calculating the weight of the quality evaluation index; and calculating a comprehensive index, and rating the water environment quality according to the comprehensive index. The method has the effects of improving the accuracy of a calculation result and improving the accuracy of a water environment quality evaluation result in the water environment quality evaluation process.

The invention discloses a method for detecting water quality for water conservancy projects, comprising the following steps: S1, fixed-point sampling; S11, selecting sampling points: selecting representative sampling points according to the flow direction and purpose of the water body and the distribution of possible pollution sources; S12, sampling selection: using sampling equipment to sample the water source at the sampling point to ensure the representativeness of the sample and avoid pollution, and the sampling position includes the collection of surface water and bottom water; S2, transportation and preservation: ensuring that the collected water samples maintain their original state before analysis, and adopting anti-pollution, anti-light and constant temperature preservation measures; S3, experimental analysis: performing physical index analysis, chemical index analysis and biological index analysis on the collected water samples according to the needs of the experiment; S4, data coordination and analysis; when the invention is capable of detecting the transparency of the water sample, the transparency of the water quality is comprehensively evaluated by two factors, namely the color of the water body and the concentration of suspended matter, so as to ensure the comprehensiveness and accuracy of the water quality detection.

The invention relates to the technical field of lubricating oil heating, in particular to a low-temperature heating device and method for lubricating oil on-line monitoring equipment, and the low-temperature heating device comprises a gear box, an oil groove, PTC ceramic heating sheets, and monitoring sensors for physical and chemical indexes such as oil temperature and kinematic viscosity, a heating module is arranged at the side part of the bottom of the oil groove, and the PTC ceramic heating sheets are respectively arranged on multiple surfaces of the oil groove; a physical and chemical index sensor for monitoring oil temperature is arranged in the oil tank, the physical and chemical index monitoring sensor for monitoring oil temperature, kinematic viscosity and the like is electrically connected with external control equipment through a control module, and lubricating oil can be monitored in real time through the physical and chemical index monitoring sensor for monitoring oil temperature, kinematic viscosity and the like. The lubricating oil temperature monitoring device can monitor lubricating oil on line, so that the temperature of the lubricating oil is monitored, a worker can monitor the oil temperature at any time, and normal use of equipment is prevented from being affected.

The present application provides a kind of liquor pit mud quality evaluation method based on image recognition, it is related to the technical field of brewing liquor, first by obtaining pit mud surface image, and combining physical and chemical indexes and expert experience are marked with quality grade, the pit mud image obtained is preprocessed, obtain the pit mud image after preprocessing, construct high-quality training data set, by training data set the image after preprocessing is input into improved YOLO11 model and is trained and tested, obtain pit mud quality evaluation model, obtain the pit mud image of pit mud to be evaluated, after preprocessing, pit mud quality class and confidence of pit mud to be evaluated are obtained using pit mud quality evaluation model, the existing problem of low efficiency of liquor pit mud quality evaluation detection is solved, the present application is applicable to pit mud quality evaluation.

The application discloses a water environment water quality detection method and device, and relates to the technical field of water quality detection. In view of the problems that water sample extraction in existing drinking water source detection easily leads to physical index distortion, and underwater full detection easily causes chemical waste liquid pollution, the scheme completes physical index detection in an underwater in-situ through-flow path, and chemical index detection is carried out in a closed space on water; the same adjustable action unit is used to switch working parameters, so that physical detection excitation, water sample directional transportation and pipeline self-cleaning are realized at different times, and detection waste liquid is fully collected in a closed manner without external discharge. The application guarantees that physical detection data is close to the real state of raw water, completely avoids chemical pollution risk, has a simple structure, and is suitable for high-standard water quality monitoring scenes.

An intelligent discrimination method and apparatus for a mine water inrush source, a device, and a storage medium. The method comprises: acquiring a water chemical index of a water source sample to be discriminated (S1), wherein the water chemical index comprises a plurality of inorganic indexes and a plurality of organic indexes; and inputting the water chemical index into a preset water source discrimination model to obtain a water source type of said water source sample (S2). In addition to inorganic indexes for discrimination, organic indexes are added, so that the problem of being difficult to accurately discriminate, by means of inorganic water chemical indexes, water samples with similar component is solved, thereby improving the accuracy of water source type discrimination.

The application discloses a river water ecological comprehensive evaluation method fusing benthos and water physical and chemical parameters, relates to the technical field of river water ecological environment evaluation, and comprises the following steps: constructing a comprehensive evaluation index system based on water physical and chemical parameters and benthic community parameters of a river to be evaluated; calculating water physical and chemical index weights and benthic index weights based on the comprehensive evaluation index system; inputting the comprehensive evaluation index system, the water physical and chemical index weights and the benthic index weights into a pre-constructed biological-physical coupling evaluation model to output a river water ecological comprehensive health index EHI; determining the ecological comprehensive health grade of the river to be evaluated from a pre-constructed ecological grade determination table based on the river water ecological comprehensive health index EHI; and generating and outputting an evaluation result. The application can fuse two types of monitoring data of water physical and chemical parameters and benthos to complete river water ecological comprehensive evaluation, output an evaluation result, and support fine management of a watershed water environment.

The invention belongs to the technical field of oil and gas exploration lithology recognition, and discloses a method and device for recognizing underground evaporation rock lithology based on element chemical characteristics, and the method comprises the steps: carrying out the petrology and mineralogy analysis of an evaporation rock sample, and determining the lithology of a main evaporation rock; performing chemical analysis on the lithology of the main evaporative rock, and establishing element chemical indexes of the lithology of the main evaporative rock; establishing an element ternary chart of the lithology of the main evaporative rock based on the element chemical indexes; and matching the petroleum drilling and logging element content value with the element chemical index and the ternary chart, and judging the lithology of the drilling evaporation rock. By means of the method, the lithology of the evaporation rock under the petroleum well can be corrected more directly and more accurately, and favorable technical support is provided for arrangement and implementation of oil and gas engineering exploration.

The invention discloses a method for evaluating cigarette product quality difference based on a multi-dimensional space chemical fingerprint spectrum, and relates to the field of cigarette quality evaluation.The method comprises the following steps that near-infrared diffuse reflection spectrum data of a sample is collected, and a near-infrared discrimination classification model is established after optimization treatment; establishing a near-infrared correction model by taking a control sample; introducing the collected sample into the near-infrared correction model of the control sample for calculation, and predicting and analyzing the chemical component contents of the comparison sample and the control sample; the method comprises the following steps: classifying samples according to different batches, applying a principal component analysis method, drawing a spectrum classification effect picture, calculating the distribution condition of each category of samples, drawing a principal component score picture, collecting sample gas chromatography fingerprint data by adopting HS-GC-MS combination, and establishing a gas chromatography discrimination classification model after optimization treatment; the method comprises the following steps: determining conventional chemical indexes, polyphenol content, ash content, pH value and volatile components of selected cigarette samples, and performing variance analysis, correlation analysis and discriminant analysis.

The invention discloses a sediment heavy metal pollution analysis and evaluation method, and belongs to the technical field of environmental statistical modeling. The method comprises the following steps: acquiring physicochemical property indexes of sediments, and calculating the effective adsorption capacity of each component by utilizing a preset saturation response relationship; inputting the physicochemical indexes into a Bayesian network constructed through hierarchical mechanism constraint, and deducing the adsorption affinity latent variable of the heavy metal; constructing a competition mapping function containing a vacancy constant term based on a competition Langmuir mechanism, and calculating a capacity occupancy rate under a multi-metal competition condition; and finally, calculating a heavy metal content predicted value according to the effective adsorption capacity and the occupancy rate. According to the method, a physical capacity upper limit and a multi-metal competition occupation mechanism are introduced into the Bayesian network, so that the problems of prediction distortion and lack of a competition mechanism of a traditional model under high load are solved, and accurate evaluation conforming to physical and chemical laws is realized.

The invention discloses a mushroom multi-mode intelligent sorting and RFID traceability system and method, an ESP32 chip and Raspberry Pi 4B are used as main control chips, the Raspberry Pi 4B carries a YOLOv8 model, and the Raspberry Pi 4B is externally connected with a USB camera module to realize deep learning machine vision identification of mushrooms so as to obtain appearance characteristics, classification varieties and quality grades of the mushrooms. The humidity sensor, the gas sensor, the weight sensor and the RFID module are integrated on the ESP32 chip, the ESP32 chip transmits information of various sensors to the Raspberry Pi 4B, the Raspberry Pi 4B classifies shiitake mushrooms by fusing the information of various sensors and shiitake mushroom image identification information on the basis of timestamps, and classification results are written into the RFID module to be made into RFID tags. By the adoption of the system and method, the problem that an existing shiitake mushroom sorting system cannot comprehensively evaluate physical and chemical indexes and recessive quality of shiitake mushrooms is solved.