114 results about "Similarity analysis" patented technology

The invention discloses a seismic activity parameter determination method and system based on incomplete seismic data, and relates to the technical field of engineering seismology, and the method comprises the steps: collecting seismic data, and constructing a historical directory; simulating a seismic directory according to the seismic activity parameters and the activity model; similarity comparison is carried out on the simulated seismic catalog and the historical catalog; and determining a seismic activity parameter combination according to a similarity result between the directories. According to the method, the seismic activity parameters are determined based on the incomplete seismic data, and the sample size is increased by coupling various seismic data, so that the defect of a historical seismic directory can be overcome, and the length of available data can be prolonged; a Monte Carlo method is adopted to simulate a seismic directory so as to obtain a characteristic index sample matrix, and Euclidean distance is adopted to carry out mapping similarity analysis on a historical directory and a simulated directory so as to give a parameter optimization result; the earthquake information is utilized as much as possible, and excessive constraints are avoided.

The invention belongs to the technical field of data mining and analysis processing, and particularly discloses a real-time data stream processing method and system based on distributed computing, and the method comprises the steps: obtaining real-time and historical data streams of a server program window, employing a time sequence synchronization mode to rapidly position and start a window matching path and historical abnormal performance, and obtaining a real-time data stream of the server program window; the high real-time requirement is met; historical abnormal event statistics and real-time data flow similarity analysis are combined to dynamically construct a distributed tracking link, a depth-first search algorithm is used to predict a risk event, and an abnormal probability and a deviation degree are accurately quantified; different optimization strategies are configured according to different performance parameters, a multi-level defense mechanism is formed, and the self-adaptive capacity of the system is improved. According to the method, the interaction track and the performance parameter set are comprehensively analyzed, the abnormal performance link relation is marked, abnormal event correlation analysis is refined, the maintainability and expansibility of the system are enhanced, and the data processing efficiency is remarkably improved.

The invention discloses a similarity and distance calculation system and method based on an R language, and relates to the technical field of data processing, and the key point of the technical scheme is that the system comprises the following modules: a data reading module, a data standardization module, a similarity calculation module and an error checking module. Through automatic data inspection, standardized processing and efficient similarity calculation, the user can easily perform complex similarity analysis. The method has a wide prospect in the application of big data analysis, machine learning and the like, a more convenient and more accurate similarity calculation scheme can be provided for a user, and the data processing and analysis efficiency is greatly improved.

The invention provides a wrong question book intelligent learning system and method based on OCR and similarity analysis. The method comprises the following steps: S1, carrying out wrong question picture preprocessing and feature extraction; s2, multi-dimensional similarity calculation is associated with knowledge points; s3, knowledge point error rate statistics and error pattern analysis; and S4, generating and pushing personalized exercises. According to the method, intelligence and individuation of error question management are realized through multi-technology fusion, the bottleneck of current error question management is broken through, and the learning efficiency and the knowledge mastering depth are improved.

The invention belongs to the technical field of bid and bid behavior monitoring, and particularly discloses a bid and bid behavior monitoring management platform based on artificial intelligence, and the bid and bid behavior monitoring management platform adopts a chart normalization preprocessing technology, carries out the multi-dimensional similarity analysis of text content, chart features and image-text matching degree, and combines the order of images and texts with a recombination comparison mode. Omnibearing detection of the bidding document is realized, and the recognition rate of chart tampering and content recombination type bidding behaviors is effectively improved; based on a dynamic weight distribution mechanism of a project type, accurate risk assessment of different importance contents is realized through intelligent segmentation and differential weight setting of bidding document unit bodies; the multi-dimensional risk fusion analysis relation is constructed, the risk index is generated through comprehensive evaluation, and graded early warning is triggered, so that targeted monitoring on different structural weight markers is ensured, the detection breadth and depth are remarkably improved, and the problem of stiffness of a multi-modal analysis evaluation standard in the prior art is solved.

The invention discloses a topology anti-error risk management and control method and system, and relates to the technical field of risk management and control, and the method comprises the following steps: obtaining a power grid topology structure chart, and employing a graph algorithm to code power grid nodes in the topology structure chart, and obtaining a node feature vector; constructing a truth-supplementing parameter group based on the measurement missing node identification result and the node level, and performing random disturbance on the truth-supplementing parameter group based on a preset first constraint condition to obtain a plurality of truth-supplementing schemes; repairing the node feature vectors of the measurement missing nodes by adopting a truth-supplementing scheme to obtain a node repairing feature vector set, and performing similarity analysis on the node repairing feature vector set and a preset risk scene; and calculating an optimal similarity threshold value corresponding to the authentic scheme based on a similarity analysis result, constructing an optimal pairing group, and applying the optimal pairing group to actual anti-error risk identification, so that the problem that the accuracy of power grid risk management and control is reduced due to the lack of a dynamic adaptation mechanism between the repaired node features and an actual risk scene in the face of node measurement deficiency is solved.

The invention relates to an electric power project demand similarity analysis method based on a rearrangement model and retrieval enhancement generation, and belongs to the technical field of computer science, artificial intelligence and natural language processing. The method comprises the following steps: constructing a multi-modal knowledge base; after user query is received, self-adaptive query expansion is carried out through a large language model, preliminary recall is carried out by adopting a mixed search strategy, secondary accurate scoring and reordering are carried out on candidate lists by utilizing a rearrangement model of a cross encoder framework, and a final result is generated in combination with an interpretability analysis technology. And finally, driving the large language model to generate a multi-dimensional intelligent analysis report through chained thinking prompt. According to the method, the problem of analysis deviation caused by low retrieval quality in a traditional RAG method is solved, the transparency of the system is enhanced through interpretability analysis, and the finally generated multi-dimensional analysis report can provide unprecedented decision support for project management.

The invention discloses a solid waste classification method based on a spectrometer, and relates to the technical field of solid waste analysis, and the method comprises the following steps: S1, preliminary classification: obtaining a sample of unknown solid waste, and observing the characteristics of the sample to obtain characteristic information; s2, selecting a spectrograph: selecting the spectrograph according to the feature information; analyzing the sample by using a spectrograph to obtain a spectrogram; the spectrogram comprises a spectrum curve; s3, spectrogram preprocessing: carrying out normalization processing on the data of the spectrum curve; s4, similarity analysis: for the spectrum curves of the multiple samples, randomly selecting two samples for comparison to obtain a similarity value; if the similarity value is within a preset threshold range, the two samples to be compared belong to the same kind of solid waste. The method is low in operation cost and low in professional degree requirement on workers, and can realize rapid and efficient analysis and classification of solids.

The invention discloses a hyperspectral remote sensing mineralization alteration information extraction method, device and equipment and a medium, and is applied to the technical field of remote sensing geological survey, the hyperspectral remote sensing mineralization alteration information extraction method comprises the following steps: obtaining sample laboratory spectral data and sample hyperspectral satellite remote sensing data of a rock and soil sample; calculating the sample laboratory spectral data and the sample hyperspectral satellite remote sensing data by adopting a direct standardization algorithm, and determining a transfer matrix required for converting the sample hyperspectral satellite remote sensing data into the sample laboratory spectral data; based on the transfer matrix, converting hyperspectral satellite remote sensing data of a research area to obtain laboratory-like spectral data of the research area; and performing similarity analysis on the laboratory-like spectral data and the standard spectral data of the altered mineral, and determining mineralization alteration information in the laboratory-like spectral data.

The invention belongs to the technical field of data analysis, and provides an abnormal data analysis method and system in a financial fast report scene based on artificial intelligence, and the method comprises the steps: comparing obtained target financial data with a pre-configured threshold value through employing a three-dimensional threshold value model, judging whether there is abnormal data or not according to a comparison result, and carrying out the analysis of the abnormal data in a financial fast report scene. The threshold value of the three-dimensional threshold value model is configured by integrating an industry financial benchmark, historical financial data of the enterprise and financial data of the enterprise in the current year; if the abnormal data exists, retrieving data associated with the abnormal data by using the updated knowledge graph, and identifying a business event having correlation with the abnormal data according to the retrieved data; and performing similarity analysis, statistical significance analysis and anomaly classification analysis on the abnormal data and the business event, and performing weighted fusion to obtain a final analysis result. The accuracy of financial abnormal data analysis in the prior art is improved.

The invention provides a microbial community analysis method based on statistical analysis, and belongs to the technical field of microbial community analysis. The microflora analysis method comprises the following steps: collecting a plurality of water samples, and carrying out pretreatment; sequencing the microflora of the water sample by adopting high-throughput sequencing to obtain a microflora sequencing result; preprocessing the microbial community sequencing result by adopting OTU clustering analysis and species annotation to obtain a data preprocessing result; and analyzing the data preprocessing result by adopting a statistical method. According to the method disclosed by the invention, various microorganisms in the water sample are sequenced by adopting high-throughput sequencing, the sequencing process is rapid, the result is accurate, and the microflora sequencing result is analyzed by combining various statistical analysis means such as difference analysis, similarity analysis and diversity analysis; and the structural composition and characteristics of the microbial community can be analyzed more comprehensively and accurately.

The invention belongs to the technical field of hydrological forecasting, and particularly provides a method for forecasting future session flood based on peak rainstorm distribution characteristics, and the method comprises the steps: collecting and reorganizing data, and processing the data into a time sequence with equal time intervals; obtaining space-time distribution of the flood peak formation rainstorm amount of each session of the research basin; calculating the rainfall process of each sub-basin of the flood to be forecasted, and analyzing the spatial and temporal distribution characteristics of peak rainstorm; performing similarity analysis on the spatial and temporal distribution characteristics of the peak storm of the to-be-forecasted flood and the historical session flood to obtain a session flood which is highly similar to the spatial and temporal distribution characteristics of the peak storm of the to-be-forecasted flood and is close to the peak storm amount, and taking the session flood as a to-be-calibrated session flood; establishing a multi-objective function; optimizing the objective function to obtain an optimal parameter of the hydrological model; and performing hydrological forecasting on the to-be-forecasted flood. According to the method, the parameters of the hydrological model for forecasting the flood in the future session with high accuracy can be obtained, so that a high-accuracy flood forecasting result is obtained.

The invention discloses a medium surface microstructure detection device and method based on a spectrum technology, and relates to the technical field of structure detection, and the device comprises a partition division module which is used for dividing a target medium surface to obtain a medium partition sequence, and collecting a reflection spectrum of a surface microstructure to obtain a reflection spectrum sequence; the quality identification module is used for carrying out quality identification on the target medium to obtain a quality coefficient sequence and configuring abnormal residue identification precision; the exception identification module is used for calling exception residue identification resources and carrying out exception residue identification on the reflection spectrum sequence to obtain an exception residue parameter sequence; and the result processing module is used for performing processing to obtain abnormal residual distribution, performing similarity analysis on the abnormal residual distribution and historical abnormal residual distribution, obtaining identification confidence, combining the quality coefficient sequence and the abnormal residual parameter sequence, and performing calculation to obtain a medium quality parameter as a detection result. The technical problem that the medium surface detection effect is poor in the prior art is solved.

A device may process data associated with a first entity and a second entity, using one or more machine learning techniques, to identify a set of trends associated with a set of documents. The device may receive new documents associated with the first entity and the second entity. The device may generate, based on the set of trends, a first set of exceptions indicating that a new document is associated with a first type of error. The device may generate, using a similarity analysis technique, a second set of exceptions indicating that a new document is associated with a second type of error. The device may communicate with one or more systems to perform one or more actions associated with correction or prevention of processing errors relating to the new document based a claim relating to the first set of exceptions or the second set of exceptions.

The invention relates to a multi-dimensional feature-based case series-parallel analysis method and device, computer equipment and a storage medium. The method comprises the following steps: performing feature extraction processing on denoised sample data of each case sample to obtain a case feature set of the corresponding case sample; performing vector construction processing according to the case feature set of each case sample to obtain a multi-dimensional feature vector of the corresponding case sample, and performing calculation according to the multi-dimensional feature vector of each case sample to obtain a reference multi-dimensional feature vector; performing similarity analysis according to the multi-dimensional feature vector of each case sample and the reference multi-dimensional feature vector to obtain case similarity of each case sample; wherein the case similarity is the similarity between the multi-dimensional feature vector of the corresponding case sample and the reference multi-dimensional feature vector; in response to the existence of the target case similarity, recording a case identity identification number of a case sample corresponding to the target case similarity to a case string, and analyzing a statistical result; by adopting the method, the efficiency and the accuracy can be improved.

The invention relates to the technical field of ecological environment monitoring, in particular to an environment assessment method and device based on carbon footprint and regional ecological data. The method comprises the following steps: acquiring carbon footprint data and regional ecological data of a target region; performing dimension alignment on the carbon footprint data and the regional ecological data to obtain an associated data set associated with a preset grid of the target region; and based on the associated data set, through at least one of a time sequence similarity analysis strategy, a spatial distribution overlapping degree analysis strategy and a causal relationship influence analysis strategy, determining an environment assessment result of the target area. Compared with the prior art, a manual evaluation mode is replaced, and the analysis efficiency is improved. And on the other hand, the carbon footprint data and the regional ecological data are aligned according to the preset grids of the region, so that the problem of non-uniform comparison dimensions and indexes is solved. And meanwhile, three analysis strategies are provided for reflecting the internal relation of the two types of data, so that the data analysis precision is improved.

The invention discloses a role copyright infringement detection method and system based on visual and semantic features, and the method comprises the steps: S1, role target separation and feature extraction: inputting to-be-detected content, separating a role target in the content, and extracting role features which comprise at least one of a visual feature, a semantic feature and a time sequence feature; s2, role feature correspondence and matching: performing correspondence and matching on the extracted role features and existing role features in a copyright content library; and S3, role feature similarity analysis: when the similarity between the extracted role and the matched role exceeds a preset threshold value, judging that the role is a potential infringement role. According to the method, the visual and semantic features of the role are taken as the core, and a full-process detection framework from target separation to feature matching to similarity analysis is constructed, so that the problem of low efficiency caused by dependence on a manual comparison method in the prior art can be effectively solved; an automatic and intelligent solution is provided for role copyright infringement affirmation of large-scale digital content, and the detection efficiency and the judgment scientificity are remarkably improved.

The invention relates to the technical field of network security, and discloses a program-level code similarity analysis method and device based on semantic slicing, and the method comprises the steps: constructing a program-level target function call graph based on a target source code; matching the target function call graph with a standard function call graph to obtain a plurality of isomorphic sub-graphs; performing semantic slicing on each function node in the first sub-graph and the second sub-graph to obtain a first slicing result of the first sub-graph and a second slicing result of the second sub-graph; and evaluating the slice similarity between each function in the first slice result and each function in the second slice result, and determining the similarity of the target source code according to the slice similarity. According to the method, the user-defined function call graph for eliminating system function interference is constructed, an isomorphic sub-graph matching algorithm is combined, multi-dimensional features are comprehensively considered, the accuracy of similarity calculation is improved, effective support is provided for practical application scenes such as code reconstruction and security audit, and the guarantee of code quality and security is improved.

The invention discloses an inquiry teaching method and system based on a large language model, and the method comprises the steps: randomly extracting to-be-recombined data from a pre-constructed patient play background library, a patient disease question and answer library and a disease picture library, recombining each piece of data to be recombined to generate a virtual digital patient object for interacting with the user; in the interrogation teaching process, performing similarity analysis on the interrogation question output by the user and the patient disease question and answer library, and screening and determining a matching result corresponding to the interrogation question from the patient disease question and answer library; and obtaining reference inquiry reply data according to a matching result, and inputting the reference inquiry reply data into the constructed big language inquiry teaching model to obtain a reply result which is output by the big language inquiry teaching model and meets the inquiry teaching standard so as to realize virtual inquiry teaching. Doctor-patient flexible interaction can be carried out, and the independent diagnosis ability of doctors and students is improved.

The application provides a tunnel positioning method, device, equipment, medium and product, the method comprises the following steps: obtaining a plurality of network parameters reported by a user terminal when the user terminal is at a to-be-positioned point in a tunnel, predicted position data of the to-be-positioned point output by an inertial navigation system, and tunnel position data; based on the plurality of network parameters and the tunnel position data, a plurality of first MR fingerprint data are matched from an MR fingerprint library; similarity analysis is performed based on the plurality of first MR fingerprint data and the predicted position data, and MR fingerprint positioning data of the to-be-positioned point is obtained; and position data correction is performed based on the MR fingerprint positioning data and the predicted position data, and actual positioning data of the to-be-positioned point is obtained. The tunnel positioning method provided by the application can accurately calculate the positioning data of a user in a tunnel environment through an algorithm without the need to separately deploy a positioning device in the tunnel environment and without the need to be limited by hardware devices, so that the flexibility is improved while the accuracy is ensured.

The invention relates to a method for identifying microbial core species in a river ecosystem, and belongs to the field of microbial ecology. Through OTU relative abundance data, a presence-absence matrix is constructed, and an OTU occurrence rate and an average relative abundance are calculated. And evaluating the OTU ecological importance, and identifying a potential core OTU. And analyzing the consistency of the OTU occurrence frequency and the time scale in combination with the time point location, and generating a ranking index Index for ranking. And performing Bray-Curis similarity analysis to quantify the structural diversity of the OTU community, and identifying the OTU which has the greatest influence on the community similarity. And determining a core OTU threshold value based on an inflection point method and a growth rate method, verifying a core classification group combination mechanism by using a Sloan neutral model, and finally determining the representativeness of the core OTU by comparing the actual occurrence frequency with model prediction. According to the method, rich information is provided for explaining the diversity pattern of the microflora level.

The invention discloses a science and technology project document duplicate checking method and device based on multi-level abstract generation and a medium, belongs to the technical field of document duplicate checking, and solves the problem of how to improve the reliability and accuracy of science and technology project document duplicate checking. The method comprises the following steps: firstly, carrying out structured analysis on a project document to be subjected to duplicate checking, introducing a fine-tuned abstract generation model to obtain a multi-level abstract of a project to be subjected to duplicate checking, and extracting a feature vector of the multi-level abstract through a fine-tuned and trained text feature extraction model; secondly, performing similarity search in a vector database based on feature vectors corresponding to the dimensions of the main abstract, further calculating cosine similarities based on the dimensions of the subordinate abstract, and sequencing the weighted similarities to obtain a similarity rank; and finally, according to the structured analysis information and the similarity ranking result, LLM similarity analysis is performed by using a large language model, a document duplicate checking report is formed, the originality of the science and technology project is ensured, repeated subsidization is avoided, and the method has important practical application value for science and technology project management.

The invention discloses an object recognition method and device, equipment and a storage medium, and relates to the technical field of machine learning, and the method comprises the steps: carrying out the feature similarity analysis of a target object feature of a to-be-recognized object and a class index feature group corresponding to a target object class, and obtaining target feature similarity data; the category index feature group is a clustering center feature corresponding to the positive sample object feature; the positive sample object is a sample object which is screened based on a feature density clustering result of a plurality of original sample objects and belongs to a target object category; based on the target feature similarity data and a preset feature similarity threshold, determining object category indication information of the to-be-recognized object; the preset feature similarity threshold value is obtained by performing threshold value adaptive adjustment based on a preset identification index threshold value and the sample feature similarity data; the sample feature similar data represents the feature similarity condition between the positive sample object feature of the positive sample object and the category index feature group. By using the scheme of the invention, accurate identification of a new category can be rapidly realized.

The invention relates to the technical field of optical test analysis, in particular to an intelligent water quality monitoring method, system and device based on data analysis, and the method comprises the steps: carrying out the iterative decomposition of original spectral data to obtain a component signal tree, and analyzing the extreme point distribution characteristics of data points in any component signal in the component signal tree; calculating spectral noise factors of the component signals according to the number difference corresponding to the extreme points and the data points among the different component signals; combining the spectral noise factors of all the component signals and the amplitude difference and frequency information in the component signals, performing similarity analysis on the component signals and the original spectral data, obtaining an updated noise coefficient of the original spectral data, denoising the original spectral data, and obtaining a water quality monitoring result of the water body sample by using new spectral data. According to the invention, the denoising effect on the spectral signal is improved, and the accuracy of the water quality monitoring result is further improved.

The present invention belongs to the field of Internet of Things security technology, and discloses a firmware password library detection method and device based on similarity analysis. The method includes: constructing a public password library data set, obtaining the binary file of the public password library data set as the data set binary file, and unpacking the firmware to be detected to obtain the binary file of the firmware as the binary file to be analyzed; performing file similarity analysis on the binary file to be analyzed and the data set binary file to identify the public password library; in the files where the public password library is not identified, clustering according to the file similarity to identify the private password library. In the process of performing similarity analysis, the method of the present invention not only utilizes the features inside the function, but also uses the sequence order between functions as the basis for similarity recognition, so as to be able to accurately identify the password library in the Internet of Things firmware and restore the APIs of all functions in the library, which greatly facilitates the subsequent security analysis work.

The invention relates to a historical case similarity-based quality evaluation method, which belongs to the field of software development, and comprises the following steps of: screening out a prior index and a posterior index; collecting data of each stage in the research and development process of each software historical version as historical cases; the specific numerical value of each index is counted; obtaining quality problem source data of the historical cases; taking the historical cases with the labels as input samples, performing model training by adopting an SVM classification algorithm, and constructing a quality problem classification model; constructing a prior index vector matrix for each historical case and the newly-added case, and calculating the similarity between the newly-added case and each historical case; automatically classifying the newly added cases and setting labels; calculating a risk value of each similar case; and averaging the risk values of all the similar cases to obtain a risk coefficient value of the newly added case. According to the method, the influence of manual subjective deviation on index interpretation can be avoided, and an objective quality evaluation standard is established through quantitative similarity analysis.

The invention discloses an intelligent pressure emotion management method and system based on multi-dimensional behavior style feature evaluation, and relates to the field of pressure emotion management. Firstly, body and behavior information of a new user is collected and preprocessed, and a pressure data set is generated. And through similarity analysis with historical user data, a group most similar to the new user is found out. On the basis of the pressure release schemes of the similar groups, scheme vectors are constructed, users are divided into different similar groups according to the schemes, and proportion distribution of each group is recorded; thirdly, social attributes of the new users are analyzed, and the matching degree between the new users and all the groups is calculated; and finally, performing weighted summation on the matching degree and the group proportion distribution to obtain a conformity coefficient, and selecting the most suitable pressure release scheme of the new user according to the coefficient. According to the method, the user behavior style can be evaluated in multiple dimensions, a personalized pressure release scheme is recommended, and the management efficiency and the user satisfaction degree are improved.

The invention discloses a control method of a mixed water heat supply system. The control method comprises the steps that operation data of a plurality of mixed water pipe networks in the mixed water heat supply system within a preset time period are obtained; clustering the operation data of the plurality of water mixing pipe networks in a preset time period, and determining clustering operation data corresponding to the plurality of water mixing pipe networks; performing similarity analysis based on the clustering operation data corresponding to the plurality of water mixing pipe networks to obtain a similarity analysis result; based on the similarity analysis result and the energy consumption parameters of the multiple water mixing pipe networks, target water mixing pipe networks corresponding to the multiple water mixing pipe networks are determined, and according to the target operation parameters of the target water mixing pipe networks, the operation states of the water mixing pipe networks corresponding to the target water mixing pipe networks are controlled. The problem that in the prior art, when the mixed water heat supply system is controlled, a complex calculation process is needed, the mixed water heat supply system cannot be controlled in time, and then energy waste is easily caused is solved.

The application discloses a role copyright infringement detection method and system based on visual and semantic features, the method comprises the following steps: S1, role target separation and feature extraction: input the content to be detected, separate the role target therein, and extract the role features, the role features comprising at least one of visual features, semantic features and time sequence features; S2, role feature correspondence and matching: the extracted role features are matched with the existing role features in the copyright content library; S3, role feature similarity analysis: when the similarity between the extracted role and the matched role exceeds a preset threshold, the role is determined as a potential infringing role. The application takes the visual and semantic features of the role as the core, constructs a whole-process detection framework from target separation to feature matching and then to similarity analysis, can effectively solve the low-efficiency problem of the prior art which depends on the manual comparison method, provides an automatic and intelligent solution for the role copyright infringement identification of large-scale digital content, and significantly improves the detection efficiency and the scientificity of the identification.

The present invention discloses a device and method for detecting the microstructure of a medium surface based on spectral technology, which relates to the field of structural detection technology. The device includes: a partitioning module for partitioning the surface of a target medium to obtain a medium partition sequence, collecting the reflectance spectrum of the surface microstructure to obtain a reflectance spectrum sequence; a quality identification module for performing quality identification of the target medium to obtain a quality coefficient sequence, and configuring the abnormal residue identification accuracy; an abnormal identification module for calling abnormal residue identification resources, performing abnormal residue identification on the reflectance spectrum sequence to obtain an abnormal residue parameter sequence; and a result processing module for processing the obtained abnormal residue distribution, performing similarity analysis with historical abnormal residue distributions, obtaining identification confidence, and combining the quality coefficient sequence and the abnormal residue parameter sequence to calculate and obtain the medium quality parameter as the detection result. The present invention solves the technical problem of poor medium surface monitoring and detection effect in the prior art.