38results about How to "Achieve accurate quantification" patented technology

The invention provides a mass spectrum quantitative imaging method based on a digital standard substance, and belongs to the technical field of analytical chemistry and digital models, and the method comprises the following steps: taking gelatin as a matrix material developed by the standard substance, obtaining an element grouping mode and the concentration of each element under each linear gradient, and adopting a freezing slicing method or a micro-droplet printing method to obtain a standard substance; a gelatin element physical standard substance is obtained; based on the concentration of each element, establishing a sensitivity difference response library according to an element grouping mode, performing uncertainty evaluation, constructing a digital model, and integrating man-machine interaction preset software to form a digital quantitative imaging platform of the laser ablation inductively coupled plasma mass spectrometer; acquiring a gelatin element physical standard substance of a sample to be detected, and performing mass spectrum quantitative biological imaging analysis to obtain an imaging result; the invention solves the problems that the existing mass spectrum quantitative imaging method is difficult to realize multi-target accurate quantification in one-time analysis and is difficult to prepare a standard substance meeting multi-target analysis.

The invention relates to the field of hoisting, in particular to a multi-device collaborative hoisting safety scheduling system based on the Internet of Things. Surface point cloud data and wind direction data of a hoisted object are acquired through a data acquisition module; the cutting construction module constructs a three-dimensional model based on the point cloud data and constructs a fluid control group in combination with a hoisting movement velocity vector and a current wind direction, and the fluid analysis module constructs a plurality of morphological observation surfaces to cut local parts to form contours and extracts fluid interference characteristics to obtain interference characteristic values so as to analyze interference tendency; and the scheduling control module analyzes the hoisting path section in a strong interference tendency section by section to identify a risk local path section and controls the hoisting equipment to adopt a deceleration scheduling strategy. According to the method, quantitative evaluation and adaptive adjustment of the dynamic influence of the outdoor complex wind environment on the hoisted object in the hoisting operation are realized, and the safety and scheduling accuracy of multi-equipment cooperative hoisting are improved.

The application discloses a user charging and changing behavior multi-dimensional feature space-time quantification method considering cross-domain factors, relies on user travel law, charging and changing service level, power grid price level, traffic network data, and meteorological factors of the place, and objectively quantifies the charging behavior of the user. In the method, not only the influence of the user charging behavior on the surrounding road traffic is proposed, the blank in the field is made up, but also the influence of the charging behavior on the area is fully considered, the traditional single evaluation dimension is transcended, the basic ability construction of vehicle-road-network coordination optimization can be better supported, the scientificity and precision of charging and changing infrastructure planning are improved, the user behavior modeling theory is enriched, and cross-domain technology integration is promoted.

The application is particularly applied to a security risk dynamic evaluation and early warning system for information integrated monitoring, relates to the technical field of information security and industrial internet monitoring, and comprises a disaster energy capture and transient conversion module, a threshold triggering module, a terminal signal generation and emission module and a gradient heat insulation and anti-destroying protection module.In the application, the plug-in protocol adaptation and space-time synchronization alignment technology can access monitoring data and business system data of multiple types and multiple protocols without distinction, break the information barrier between different systems, provide a comprehensive, accurate and space-time unified data basis for risk evaluation, avoid risk omissions caused by one-sided data, and at the same time, build a hierarchical dynamic risk evaluation system, realize accurate quantification of risks and evolution trend prediction through adaptive weight adjustment and risk dynamic deduction.

This invention relates to the field of power system fault quantification technology, and discloses a method, system, equipment, and medium for quantifying distribution network line faults under typhoon weather. It calculates the wind-induced fault rate of distribution network lines by constructing a wind field correction model that incorporates micro-topography correction factors and wind direction-line angle correction factors. With the goal of minimizing power outage losses in the distribution network, a coupled influence model of transmission network faults on the distribution network line fault rate is constructed and solved to obtain the optimal load shedding amount for each load node in the distribution network and its corresponding operational constraint boundary. Under this boundary, the random process of load shedding allocation and load transfer of faulty lines within the distribution network is simulated using a double Monte Carlo sampling method, and the probability of line cascading faults caused by transmission-distribution coupling is calculated based on the simulation results. The combined time-varying fault rate and type of distribution network lines are determined by integrating the two fault rates, achieving accurate quantification of distribution network line faults under the influence of transmission-distribution coupling.

The application provides a design method of an adaptive milling cutter with adjustable curvature, and relates to the technical field of cutter design and manufacturing. The application defines a cutter radius and a fillet radius, constructs a transition curve from a peripheral edge part to an end edge bottom part through a Bezier curve, establishes a cutter rectangular coordinate system, determines a Bezier curve parameter equation based on control point coordinates, calculates a curvature and a change rate, and then finds a control parameter combination that makes a target function value maximum by discretizing the control point coordinates, calculating the target function value and optimizing and solving, so as to realize accurate regulation and control of the cutter curvature, optimize a blade edge geometric shape, and improve the adaptability and cutting performance of the cutter under complex machining conditions.

This invention provides a three-trailer collaborative aircraft transfer method and system based on multi-sensor fusion. This invention relates to the field of aircraft ground support technology, specifically to a three-trailer collaborative aircraft transfer method based on multi-sensor fusion, applicable to short-haul aircraft ground transport to hangars. Through multi-sensor data fusion and multi-trailer collaborative control, it improves transfer accuracy, safety, and efficiency. The method specifically includes the following steps: system setup and sensor calibration; trailer attitude initialization and collaborative parameter configuration; real-time acquisition and preprocessing of multi-sensor data; multi-sensor data fusion and state estimation; dynamic path planning based on fused data; attitude error quantification and calibration based on complex statistics; multi-trailer collaborative driving control and traction distribution; real-time environmental monitoring and risk warning; precise docking at the hangar entrance and attitude fine-tuning; and parking and system review and optimization.

The application discloses an intelligent health monitoring system based on electroencephalogram signals, and relates to the technical field of intelligent medical treatment, comprising the following steps: constructing a user personalized neural baseline model through small sample calibration and meta-learning; carrying out daily monitoring based on the model, and dynamically updating the model by using an online Bayesian algorithm to track long-term physiological drift of the individual; when significant neural baseline drift is detected, automatically matching and triggering intervention measures; constructing an anti-fact causal inference model to quantify the net effect of the intervention measures on the neural baseline; generating a personalized health insight report based on the net effect; and driving the iterative evolution of the neural baseline model through reinforcement learning by using closed-loop data containing drift, intervention measures and net effect, so that the application realizes intelligent health management with long-term self-adaptation, accurate quantitative intervention effect and self-evolution ability.

This invention relates to the field of bid document management technology, and in particular to an automatic bid document review method and system based on natural language processing. The method includes: identifying target sections; determining historical performance and financial information; judging whether false performance exists; analyzing the complete sentences containing target keywords; calculating material scores; determining price deviation; and determining the review result. This invention achieves multi-dimensional and comprehensive review of bid documents by intelligently analyzing multiple sections such as qualifications, risks, materials, and pricing. This effectively improves the comprehensiveness and depth of the review. Utilizing natural language processing technology, it can accurately identify and extract key information from bid documents, overcoming the subjectivity and limitations of traditional manual review. Quantitative assessment based on risk level significantly improves the accuracy and relevance of risk identification. By comprehensively weighing material scores and price deviation, it significantly improves review efficiency.

The application discloses a ginseng supply chain optimization management method and system, relates to the technical field of supply chain optimization management, and brings significant benefits to the ginseng supply chain through the construction of a data-driven closed-loop optimization system, realizes accurate quantification and dynamic optimization of the value of ginseng, and directly improves economic benefits: based on a quality value dynamic mapping model, high-value sources and high-end markets can be accurately matched to realize high quality and high price; through double-layer collaborative optimization decision-making, resources are globally deployed under the quality constraint, warehouse loss and ineffective logistics are greatly reduced, and the overall net income of the supply chain is improved; at the same time, the whole-chain data fusion and state prediction realize the change from 'experience management' to 'accurate prediction', and the ability to respond to market fluctuations is enhanced; the final execution feedback mechanism ensures that the model continuously optimizes itself, forms a virtuous cycle of getting smarter and smarter, and comprehensively improves the resilience, transparency and core competitiveness of the supply chain.

The application discloses a method for efficiently preparing abalone tetraploid, which comprises the following steps: synchronously fertilizing the ovum of abalone triploid and the sperm of normal diploid to obtain inter-fertility hybridization fertilized eggs; starting timing and synchronously measuring water temperature after fertilization, and recording the first polar body discharge time of the fertilized egg as B and the second polar body discharge time as C; based on the A, B and C, calculating the processing time point (C-B) / 4 and the processing duration (6B-A) / 2, and performing the first polar body discharge inhibition processing under the same fertilization environment. After the processing, the fertilized eggs are resuspended in fresh sand filtered seawater, and are conventionally incubated and cultivated. The application introduces the fertilization water temperature and the embryonic development biology node as quantitative indexes, eliminates the applicable limitations of a single experience threshold in different environments, and can stably and efficiently obtain abalone tetraploid fry, thereby providing a reliable tetraploid parent source for large-scale production of abalone full triploid.

The invention relates to the technical field of chemical detection, in particular to an atmospheric particulate oxidation potential detection method and system.The detection method comprises the steps that reaction liquid obtained by mixed incubation of a probe molecule solution and an atmospheric particulate solution is injected into a photoelectrochemical micro-fluidic chip of a three-electrode system; and substituting the obtained photocurrent response value into a pre-established standard curve to obtain an equivalent value of the oxidizing component in the reaction liquid, thereby realizing the detection of the oxidation potential of the atmospheric particulates. A photoelectrochemical micro-fluidic chip is formed by combining a photoelectrochemical sensor and a micro-fluidic system, and an efficient analysis system is constructed. According to the present invention, the specific reaction between the oxidizing component in the atmospheric particulate matter and the probe molecule is adopted to cause the consumption of the probe molecule or the generation of the reactant so as to cause the quantitative change of the photocurrent signal, such that the atmospheric particulate matter oxidation potential is indirectly represented by detecting the consumption of the probe molecule; the interference of a complex matrix on direct detection is effectively avoided.

The invention discloses a method and system for dynamically returning, supplementing and restoring electric quantity data and a medium, and relates to the technical field of electrical measurement, and the method comprises the steps: building the direct connection between an electric power medium station and a first data source end and a second data source end; introducing a bidirectional asymmetric return and compensation protocol, deploying a return and compensation decision maker in a power grid middle station, performing data interaction with the first data source end and the second data source end, executing a return and compensation decision under a double-end decision, and determining electric quantity return and compensation restoration data; and according to the electric quantity returning, supplementing and restoring data, executing returning, supplementing and restoring management of power grid electric power measurement. According to the invention, the technical problems of bidirectional metering deviation and poor accuracy and adaptability of back-and-compensation processing caused by the fact that the existing electric quantity back-and-compensation method cannot effectively deal with electric energy quality fluctuation and metering information loss are solved; the technical effects of accurate quantification and responsibility division of two types of metering deviations and improvement of the accuracy and adaptability of return and supplement processing are achieved.

The application relates to the technical field of industrial control system security, and discloses an industrial control system abnormal intrusion detection method and system based on behavior analysis. The method first collects multi-source data of equipment operation, network interaction and operation behavior, and carries out cleaning and standardization pretreatment. Then, in a set time window, the peak deviation degree and the change rate abnormality degree of equipment parameters are calculated, the frequency and the message size deviation degree of network communication flow are calculated, the frequency and the sequence logic abnormality degree of operation behavior are calculated, and the three behavior abnormality indexes of equipment, network and operation are formed by weighted fusion. Finally, whether abnormal intrusion exists is determined by directly comparing the indexes with the early warning threshold or calculating the cosine similarity of the characteristic vector and the standard vector formed by the indexes. The application realizes accurate quantification and fusion perception of multi-level and multi-dimensional abnormal behaviors of the industrial control system, and effectively improves the detection capability of complex attacks.

The application discloses a kind of based on user balance flow distribution with maximum toughness as target damaged road network recovery order optimization method, to solve the problem of low efficiency, decision lacks scientific basis after disaster traffic network recovery.The method comprises the following implementation steps: first, construct damaged road network toughness evaluation framework, in combination with traffic network topological structure and flow demand, define toughness index as the reciprocal of recovery time and total travel time product;Second, establish damaged road network toughness optimization scene parameter, abstract road network into connected graph and define recovery scheme set;Then, construct the mixed integer linear programming model with maximum toughness as target, convert nonlinear problem into linear problem by cutting line approximation, and set flow balance, travel demand and other constraint conditions;Finally, the model is globally optimized and solved using high-performance solver, to generate the best recovery scheme.The method of the application can scientifically quantify road network toughness and optimize recovery order, avoid the blindness of experience decision, quickly improve the traffic efficiency of post-disaster traffic system, provide efficient and scientific decision support for post-disaster traffic recovery, and have important practical application value.

The application provides a kind of active penetration depth testing device and method of penetration crystalline waterproof material, belongs to penetration testing technical field, the active penetration depth testing device of penetration crystalline waterproof material, comprising: installation cabinet, driving part, water injection equipment, gas pressurizing device, placing piece and sealing cover, the raw material control sample and experimental test sample are placed in corresponding placing groove in the application respectively, the sealing cover is precisely attached with placing piece using driving part, and independent sealing environment of each station is constructed with sealing groove and sealing strip, then water or gas is injected into groove by water injection equipment or gas pressurizing device to implement pressurized penetration, so that the accurate quantification and nondestructive testing of waterproof material penetration depth are realized without destructive cutting sample, which fundamentally avoids irreversible damage to sample caused by traditional testing means.

The invention discloses an indoor intelligent exhibition appliance digital twinborn management system based on big data driving, and the system comprises a behavior obtaining module which is used for deploying a multi-source heterogeneous sensing device to collect the moving track and interactive behavior original data of an exhibition viewer, and obtaining the behavior event log data of each exhibition appliance through data cleaning fusion and spatial correlation analysis; the behavior analysis module is used for converting the behavior event log data into analog load time sequence data by utilizing an exhibition appliance digital prototype based on the behavior event log data, training a physical information neural network according to the analog load time sequence data, and reasoning an exhibition appliance hidden physical state vector; and the preventive maintenance module is used for performing feature discretization and mutual information filtering on the hidden physical state vector of the exhibition appliance, constructing an optimized decision tree model fusing information gain and coefficient double splitting criteria to obtain a preventive maintenance work order, and realizing closed-loop digital twinborn management of the indoor exhibition appliance.

The invention relates to a preparation method and application of a nervonic acid polyclonal antibody. When the prepared nervonic acid polyclonal antibody is used for detecting nervonic acid of an animal body, an instrument analysis method which is high in equipment dependence and complex in operation is abandoned, a rapid detection system based on competitive ELISA is constructed, and accurate quantification of nervonic acid in a sample is achieved by optimizing antibody coating concentration, enzyme-labeled antigen dilution proportion, reaction time and closing conditions. A reaction system is systematically optimized, so that the detection limit is reduced to 3.113 mu g / mL, and the within-batch precision is CV% lt; 6%, inter-batch CV% lt; the cross reaction rate with six common fatty acids is 0%, the detection performance is remarkably improved, and the clinical diagnosis and scientific research requirements are met.

The invention relates to the technical field of agricultural intelligent monitoring, and discloses a method for detecting a multi-layer composite high-strength anti-aging agricultural mulching film, and the method comprises the steps: carrying out the high-frequency noise suppression and edge preservation smoothing of a mulching film image, and obtaining a smooth image; generating a degraded area mask based on the color distribution characteristics and morphological processing; calculating a roughness degree score in combination with the standard texture value; fusing the roughness and color data to perform clustering mapping to obtain a comprehensive aging map; calculating an intensity reduction proportion according to the aging map, and calculating a recovery risk and a pollution level in combination with edge fragmentation characteristics to obtain a final aging quantification index; and inputting the index into a neural network model for deviation calibration to obtain a target aging detection result. According to the invention, accurate quantification of the aging degree of the mulching film and scientific evaluation of the pollution risk in a complex environment are realized.

This application relates to the technical field of bioassay, specifically disclosing a combined detection kit for pepsinogen I and pepsinogen II and its application. The disclosed combined detection kit for pepsinogen I and pepsinogen II includes: a sample pad, a conjugate pad, a coating membrane, and an absorbent pad; the coating membrane is an NC membrane coated with antibody; the conjugate pad is prepared by pretreating and drying a fiber membrane, followed by spraying time-resolved fluorescent microspheres labeled with antibody; the pretreating solution is a solution of pH 8.0-8.4 + 8-12mM BS + 0.8-1.2% BSA + 0.8-1.2% PEG4000 + 0.02-0.03% surfactant + 4-6% sucrose. Using the detection kit and method provided in this application for the combined detection of pepsinogen I / pepsinogen II exhibits high sensitivity, accuracy, and repeatability.

The application provides a method for brake thermal overload protection in the autonomous driving-out stage of a UAV, a control device and a medium, and relates to the technical field of UAV control. The method comprises: constructing a brake energy inheritance mechanism, taking the cumulative brake energy of landing deceleration sliding as the initial value for calculation in the autonomous driving-out stage; after starting the autonomous driving-out program, collecting brake pipeline pressure and wheel speed in real time, and dynamically calculating the cumulative total brake energy in the autonomous driving-out stage through an integral algorithm; based on the ratio of the cumulative energy to the thermal overload design threshold, executing a hierarchical response strategy, including early warning, autonomous braking and switching to emergency traction. Through the whole-cycle management of "energy inheritance + real-time integration + hierarchical response", the application solves the thermal overload risk caused by the energy superposition in the landing and driving-out stages, overcomes the limitations of traditional temperature monitoring lag and pressure limiting method, and effectively prolongs the service life of the brake disc and guarantees the operation safety.

This invention provides an economical operation system and control method for CAES (Compressed Air Storage) units after load shedding, belonging to the field of compressed air energy storage. The method first executes a load shedding process after the unit is disconnected from the grid, causing the speed to drop back to a preset value. Then, by acquiring energy consumption data for three strategies—continuous operation of the single-stage expander, intermittent control, and restart after shutdown—and combining the intersection of energy consumption curves, an energy consumption threshold is determined. Finally, based on the comparison between the unit's real-time energy consumption and the energy consumption threshold, the optimal operating strategy is dynamically selected. This method solves the problem of high air consumption during traditional continuous operation and avoids the drawback of long downtime and reconnection time, minimizing total energy consumption during the disconnection and reconnection period. Furthermore, the intermediate-stage expander in the system is equipped with an independent intake regulating valve and intake pipe, enabling control of the single-stage expander. The solution of this invention solves the problems of low operating efficiency and wasted air resources in existing technologies, improving the system's economy.

This invention discloses a method and system for elastic resource orchestration in a distributed intelligent parallel simulation engine. The method includes the following steps: dynamically marking time periods based on the predicted load state parameters of each simulation process in each subsequent simulation period, obtained from the dynamic load prediction of simulation data generated by each simulation process within each simulation period in the distributed simulation simulation system; dynamically setting and optimizing scheduling instructions based on the dynamic time period marking results and simulation event rules, and executing the dynamically set scheduling instructions after sorting them based on the topological constraint characteristics of the distributed simulation simulation system; and dynamically handling faults based on the container status parameters of each simulation container during the simulation process, and based on the container status assessment results and fault types. Through dynamic load prediction and intelligent scheduling, the periodic peak resource demand in distributed simulation is effectively smoothed, significantly improving overall resource utilization.

This invention relates to the field of network communication technology, specifically a 5G-A network slice dynamic adjustment and resource allocation system for the low-altitude economy. The system includes a mobility management feature integration module, a network slice service level protocol evaluation module, a mobility management demand prediction benchmark construction module, a multi-dimensional trend prediction module, a joint optimization decision generation module, and a strategy verification and execution module. The system acquires a mobility management feature dataset of the wireless network; evaluates the network slice service level protocol to obtain network slice status evaluation results; constructs a mobility management demand prediction benchmark; performs multi-dimensional trend analysis on the network slice status evaluation results to obtain prediction results; performs joint optimization decision-making on standard network slice configuration strategies to obtain network slice adjustment strategies; and executes the verified slice adjustment strategies to achieve dynamic adjustment and resource allocation of network slices. This invention improves the efficiency of dynamic adjustment and resource allocation of network slices.

The invention discloses a specific primer, a probe and a kit for rapidly identifying bulbus fritillariae cirrhosae and application of the specific primer, the probe and the kit, and aims to carry out rapid true and false identification (qualitative) and content determination (quantitative) on the bulbus fritillariae cirrhosae. The core technology is to design primers and probes capable of specifically recognizing all six bulbus fritillariae cirrhosae primordial (including bulbus fritillariae cirrhosae, unibract fritillary bulb and the like) chloroplast conserved genes specified in the 2025 edition Chinese Pharmacopoeia; meanwhile, the 16s rRNA gene is used as an internal reference, and a fluorescent quantitative PCR detection system is constructed. The method is high in specificity, common counterfeit products can be effectively distinguished, and the detection sensitivity reaches 0.005 ng / mu L. The technology provides a reliable tool for quality control of bulbus fritillariae cirrhosae medicinal materials and related preparations, and is suitable for various scenes such as market supervision, enterprise quality control, inspection and detection and the like.

The application relates to an adverse reaction attribution analysis method and system based on multi-modal constraint decoding. The method fuses disease course semantics and physiological space-time characteristics by constructing a three-dimensional splicing vector containing text, numerical value and time offset characteristics. A logic bias parameter is used to constrain the output layer of a large language model, converting uncontrolled text generation into quantitative causal calculation based on probability expectation, thereby avoiding model hallucinations. Combined with hybrid simulation verification of population pharmacokinetics and historical case retrieval, the attribution result conforms to the pharmacological mechanism, and accurate quantification and safety warning of adverse reaction risk are realized.

The application provides a kind of water power plant operating post multidimensional performance evaluation method and device, the present application includes: obtaining the multidimensional work behavior data of operating post personnel in the preset period, covering safety events, two votes execution, routine work, attendance and innovation achievement record;Based on the data, calculate the safety dimension score, the subject quantitative module score, and calculate the attitude constraint module score combined with the double evaluation system balance mechanism;Determine the reference weight template according to the post type, dynamically correct the target weight distribution scheme by combining attendance, workload and rotation adaptation factor;The basic score is obtained by weighting and fusing the subject quantification and attitude constraint score with the target weight, and the final performance evaluation result is calculated by combining the safety influence coefficient.The present application realizes multidimensional, fine and dynamic performance evaluation, ensures fair and just evaluation, and accurately reflects the work performance and post adaptation degree of personnel.

The application discloses a tunnel lining health state analysis method and system based on field monitoring data, and the method comprises the following steps: obtaining net displacement and net acoustic emission data through temperature deformation correction and thermal noise elimination; constructing a damage evolution constitutive model with a damage variable as an internal variable, performing finite element inversion on the net displacement and net acoustic emission data as boundary conditions and energy constraints, and solving a damage field distribution; identifying a continuous region with a damage variable exceeding a threshold value as an active damage area, extracting geometric center coordinates and an area of the active damage area; fitting a migration trajectory and an area expansion curve of a damage core along a time axis; extrapolating the trajectory and the curve to predict a future damage position and range, and dividing three stages of stable expansion, accelerated expansion and instability damage precursor according to a change rate of a slope of the expansion curve, and correspondingly generating a graded warning. The application realizes accurate quantification and space-time evolution prediction of internal damage of a tunnel lining, and significantly improves an intelligent level of health state evaluation.

This invention belongs to the field of medical testing equipment technology, specifically an intelligent anti-loosening chest breathing effort testing device with a magnetic quick-change probe. The proposed solution includes: a magnetic suction mechanism, one end of which is fitted with a sleeve tube. This mechanism enables quick magnetic attachment and disassembly of the probe to the device body, and forms an intelligent anti-loosening seal through the magnetic attraction and elastic structure, preventing the probe from falling off and leakage of the patient's exhaled air during testing; and a testing mechanism, with both ends fixedly mounted on the other ends of the two magnetic suction mechanisms. This invention utilizes a Tesla valve structure composed of a right side plate, a left side plate, and a mounting plate to create an asymmetric resistance airflow channel. During inhalation, the airflow passes through quickly; during exhalation, the airflow is guided by a triangular diverter and flows along the surfaces of the right and left side plates, creating a counter-impact. This counter-impact significantly increases exhalation resistance, ensuring the required airflow power for testing while greatly reducing the respiratory burden on the tester.

This invention belongs to the field of intelligent medical signal processing technology, and discloses a method and system for intelligent cleaning and dynamic analysis of multi-channel signals from a liquid phase chip. The method first acquires the raw digital signals collected by multiple optical channels of a liquid phase chip detection system; after time-domain and amplitude dual-dimensional feature extraction, based on a pre-constructed multi-type noise feature library, noise components are removed using a convolutional neural network to obtain a clean signal; then, each detection channel is defined as a network node, and the crosstalk coupling coefficient between channels is used as the edge weight. Based on the channel crosstalk correlation matrix, a graph convolution algorithm is used to complete decoupling operations and numerical compensation to obtain independent real signals; finally, multi-dimensional features such as channel signals, blank controls, acquisition parameters, and environmental correction coefficients are fused, and a signal distribution model is constructed through density clustering to independently calculate real-time judgment thresholds for each channel and complete validity determination. This invention solves the technical problems of poor denoising adaptability, insufficient crosstalk correction accuracy, and fixed and rigid judgment thresholds in existing liquid phase chip signal processing.