46results about How to "Solve the hysteresis" patented technology

This application provides a method and apparatus for controlling corrosion in generator set pipelines. The method includes: performing feature normalization processing on the original dataset to obtain a target dataset; constructing an iron ion concentration prediction model based on the iron ion concentration in the target dataset and the unit operating parameters; calculating the predicted iron ion concentration using the iron ion concentration prediction model and real-time unit operating parameters; calculating the real-time corrosion rate using a corrosion rate physical model and the predicted iron ion concentration; obtaining the monitoring result based on the relationship between the real-time corrosion rate and a corrosion rate threshold; and adjusting the unit operating parameters in reverse when the real-time corrosion rate exceeds the corrosion rate threshold until the real-time corrosion rate falls back to within the corrosion rate threshold. By predicting the predicted iron ion concentration under real-time unit operating parameters and combining it with the corrosion rate physical model for online monitoring and control of the corrosion rate, this method solves the problems of significant lag and insufficient accuracy in existing boiler steam-water system corrosion monitoring and control methods.

The invention provides a human body lower limb joint angle calculation method and device, and the method comprises the steps: collecting a surface electromyogram signal of a subject at a previous moment in a walking state through a surface electromyogram sensor, and calculating a lower limb joint angle estimation value at the previous moment; acquiring a lower limb joint angle measurement value of the subject at the current moment in a walking state by using an IMU; establishing a state equation by using the lower limb joint angle estimated value, establishing an observation equation by using the lower limb joint angle measured value, and constructing a fusion model based on extended Kalman filtering; and on the basis of the lower limb joint angle estimated value at the previous moment and the lower limb joint angle measured value at the current moment, an optimal estimated value of the lower limb joint angle at the current moment is obtained by utilizing a fusion model based on extended Kalman filtering. According to the method, the measurement result of the IMU and the estimation result of the surface electromyogram signal are fused, the stable and advanced joint angle is obtained, and the hysteresis problem of the IMU lower limb joint angle measurement value is solved.

The invention discloses an MICP intensity prediction method and system based on machine learning and multi-feature fusion, and relates to the field of solidified data analysis. An accurate quality prediction mapping model and an abnormal compensation parameter mapping model are constructed based on historical data; the system has the capabilities of predicting curing quality from process parameters and intelligently recommending an optimal disposal scheme from an abnormal state; by setting a dual-threshold quality control mechanism and a real-time abnormity monitoring and early warning system, various abnormal conditions in the curing process can be actively identified and timely responded, and complete closed-loop processing from parameter deviation detection to automatic compensation measure execution to hardware standby switching can be realized. The stability of the solidification process and the consistency of the engineering quality are effectively guaranteed, the requirement for manual intervention and the misjudgment risk are greatly reduced, powerful technical support is provided for standardization, normalization and industrialization development of the sand solidification technology, and the engineering efficiency and economic benefits are remarkably improved.

This invention relates to the technical field of circuit breaker analysis, specifically to an intelligent monitoring system for circuit breaker characteristics based on opening and closing identification. The system includes: a current analysis module for analyzing changes in current data of the circuit breaker at various monitoring times to obtain multiple opening and closing current characteristic indices; a temperature analysis module for analyzing changes in contact temperature data of the circuit breaker at various monitoring times to obtain multiple opening and closing temperature characteristic indices; an identification module for identifying at least one first index and at least one second index; a consistency analysis module for analyzing the consistency between the data sequences corresponding to the first index and the data sequences corresponding to the second index to obtain multiple time-related indices; and an opening / closing determination module for determining the monitoring time indicated by the current data corresponding to the largest time-related index as the opening / closing time of the circuit breaker. This invention enables accurate acquisition of the opening and closing time of the circuit breaker.

The utility model discloses an in-situ CT (Computed Tomography) analysis device for real-time observation of a soldering tin melting process. The in-situ CT analysis device comprises a heating box, an X-ray receiving device arranged above the heating box and an X-ray emitting device arranged below the heating box, the heating box comprises a mounting box body; a first mounting groove is formed in the top of the mounting box body, and a product clamping mechanism is further mounted in the first mounting groove; and the product clamping mechanism comprises two clamping rods. Based on the X-ray detection principle, the internal structure change in the soldering tin melting process can be observed in real time, the hysteresis and destructive problems of a traditional method are solved, the annular infrared heating pipe is adopted, it can be ensured that a soldering tin sample is evenly heated, temperature change in the real welding environment is simulated, meanwhile, shielding of ray imaging is avoided, and the welding quality is improved. And the resolution and the precision of CT scanning are improved.

The invention relates to the technical field of information security, discloses a data privacy protection protocol analysis method, device and system based on a dynamic rule, and aims to solve the problems that an existing privacy protection strategy statically solidifies, rule dynamic perception is insufficient, and protocol compliance evaluation is limited. The method, the device and the system are characterized in that formalized modeling is performed on a protocol, a privacy protection rule is dynamically acquired and converted, and a model is checked based on the rule; and if not, automatically correcting the model, and converting the model into instruction deployment. According to the scheme, dynamic, continuous and intelligent management of the protocol is realized, and privacy security guarantee and compliance agility are remarkably improved.

The application discloses a kind of quality intelligent evaluation methods and systems for multi-source medical data, it is related to big data processing technical field.The quality intelligent evaluation methods and systems for multi-source medical data, including S1, acquisition multi-source medical data is preprocessed, store and construct medical database;S2, drive the spatiotemporal semantic alignment and joint representation learning of cross-modal data, construct medical data optimization model and output spatiotemporal alignment value;S3, fusion spatiotemporal correlation and multidimensional quality index, data quality evaluation and abnormal analysis are carried out;S4, according to data credible result executes the traceability path generation and explainability report output operation;S5, through user feedback data and model evolution state analysis optimization effect.It solves the problem that multi-source medical data exists in spatiotemporal alignment, quality evaluation and abnormal detection, spatiotemporal mismatch, data inconsistency and low quality repair efficiency.

The invention discloses a laser soliton explosion pre-judgment and active suppression method and system based on real-time monitoring, and provides a three-level control architecture for solving the problem that a device is damaged due to sudden soliton explosion of a mode-locked fiber laser in a stable operation stage. Comprising the following steps: capturing an optical power signal in real time by using a high-speed photoelectric detector, converting the optical power signal into an electric signal, inputting the electric signal into a laser power control system, and judging whether threshold power is exceeded and performing abnormal power gradient analysis by a calculation module based on a control algorithm; and the attenuation coefficient obtained by the calculation module outputs a driving voltage through a digital-to-analog converter to drive an acousto-optic modulator (AOM), so that incident light is attenuated according to a target value through the AOM, and the regulation and control of the intra-cavity power are further achieved. The problems that a traditional method is slow in response and extensive in control are solved, and reliable protection is provided for the ultrafast laser.

The invention provides a vehicle data auditing method and device, equipment and a storage medium. The method comprises the following steps: analyzing a data security regulation text through a natural language processing technology, and extracting a data security entity and a constraint relationship thereof to construct a dynamic knowledge graph; determining a corresponding structured fact according to the vehicle multi-source data; mapping the structured facts to corresponding nodes of the knowledge graph to establish semantic associations; and performing reasoning verification based on the associated knowledge graph, judging whether the data processing activity meets compliance requirements or not, and generating an audit report. It can be understood that according to the scheme, intelligent and automatic auditing of the whole life cycle of the vehicle data is achieved, the method can dynamically adapt to regulation changes, and the auditing efficiency and accuracy are remarkably improved.

This invention relates to the field of cloud service technology and provides an intelligent cloud service management method and system, comprising the following steps: collecting hardware performance counter data on each physical node, predicting the memory bandwidth contention intensity and last-level cache contention intensity of each application in the near future, and determining the interference fingerprint based on the number of instruction cycles per second; calculating the interference potential coefficient between each pair of applications, calculating the global co-location interference entropy of nodes, and classifying nodes into different levels based on the interference entropy; when a node is at a low or medium interference level, identifying aggressive applications, and dynamically adjusting the last-level cache quota, memory bandwidth limit, and CPU scheduling priority of aggressive applications; when a node is at a high interference level, determining candidate migration plans: selecting target nodes through a distributed node negotiation mechanism and executing application migration. This invention achieves the optimal balance between performance assurance and system overhead through a two-level strategy of local resource elastic adjustment and proactive migration.

This application discloses an adaptive configuration method, apparatus, device, and storage medium for JP cabinets, belonging to the field of JP cabinet load configuration technology. This application obtains a main node graph characterizing the real-time operating status of a distribution transformer area and a secondary node graph characterizing the future operating trend and adjustability of the distribution transformer area; it performs cross-graph feature fusion on the main node graph and the secondary node graph, and outputs adaptive configuration instructions for the nodes where each JP cabinet in the distribution transformer area is located based on the cross-graph feature fusion result; it sends the adaptive configuration instructions to the corresponding JP cabinets for execution and collects the operating status data after execution; based on the operating status data, it synchronously updates the main node graph and the secondary node graph, and continuously optimizes the configuration parameters of each JP cabinet based on the updated main node graph and secondary node graph, thereby achieving the effect of accurately allocating the load of the JP cabinets.

This invention discloses a multi-unit collaborative vacuum maintenance system and its control method, including a pressure monitoring module, a precursor feature identification module, a surge prediction module, a pumping speed matching module, and a collaborative control module. The pressure monitoring module is constructed based on multiple pressure sensors to collect physical pressure signals in real time and calculate the dynamic change characteristics of the pressure based on these signals. The precursor feature identification module sequentially performs time alignment and buffering on the dynamic change feature data, and extracts three key features from a fixed-duration sliding data window: the overall intensity of pressure fluctuations, the energy proportion of the surge-sensitive frequency band, and the number of times the threshold abrupt change occurs. This invention achieves early identification of surge phenomena by calculating the instantaneous rate of change, fluctuation frequency, and a feature set combining the three key features, effectively overcoming the lag problem of traditional simple threshold judgment, while also coordinating load distribution among multiple units.

The present application relates to the field of financial technology and securities investment, and particularly relates to a quick stock selection and wave band transaction strategy optimization system. The system comprises a fund flow monitoring module, a pattern recognition and screening module, a hot spot matching and policy correlation module, and a theory integration and combination construction module. The four modules work together to construct a four-dimensional integrated screening framework of fund, pattern, hot spot and theory. The present application has the following advantages: the present application realizes a wave band operation mode of "fast in and fast out, steady arbitrage", sets the stock selection period to 9:15-9:50, effectively overcomes the lag problem of traditional stock selection, and the loose time window is more suitable for the actual trading scenario, which can help investors quickly grasp investment opportunities in the key period of opening. Through systematic, multi-dimensional screening and combination management, the probability of capturing stocks with a rising limit and strong targets is significantly improved, and the investment success rate is improved. The four-in-one screening framework of fund, pattern, hot spot and theory can comprehensively consider the investment value of individual stocks.

This invention discloses a dynamic interval elastic scaling method and system based on long-term series prediction. The method includes: collecting load time-series data of applications deployed in a container cloud platform and storing it in a time-series database; using a combined time-series prediction model based on the Transformer architecture and a Bi-LSTM time-series prediction model to perform long-term time-series prediction on the load time-series data; dynamically determining the scaling interval based on the predicted load; generating and executing a scaling strategy for application replicas in the container cloud platform, scaling up and allocating sufficient resources in advance before the actual increase in application load, thus ensuring the service quality of applications in the container cloud platform. This invention can effectively reduce the number of scaling operations, avoid window jitter caused by frequent scaling up and down, and ensure the stability of the container cloud cluster; effectively meet the resource requirements of applications and avoid application service quality instability caused by rapid scaling down.

The present application relates to natural product separation and extraction technical field, specifically disclose a kind of method for separating and extracting astaxanthin with haematococcus pluvialis as raw material, comprising the following steps: (1) haematococcus pluvialis pretreatment preparation haematococcus pluvialis dry powder;(2) using ultrasonic-assisted natural deep eutectic solvent separates and extracts astaxanthin from haematococcus pluvialis dry powder and obtains crude extract;(3) using macroporous resin dynamic adsorption crude extract and purifying and collecting astaxanthin eluate;(4) astaxanthin eluate is concentrated by rotary evaporation under reduced pressure, freeze-dried, and astaxanthin crystal powder is obtained.The method provided by the present application effectively improves the extraction rate of astaxanthin by the ternary synergy of natural deep eutectic solvent, the trans-phase antioxidant synergy of tocopherol and ascorbyl palmitate, and the mild process of ultrasonic-assisted extraction and resin gradient elution, maintains the purity of astaxanthin and the proportion of all-trans astaxanthin, and prolongs the antioxidant retention time of astaxanthin.

The invention relates to a shaded pole rotor production quality feedback method and system, and relates to the field of motor quality inspection, and the method comprises the steps: determining the material component proportion data of a to-be-processed material block in response to a quality detection signal; when the material component data of the to-be-machined material block falls into the standard component proportion data range, mold machining operation is executed; rotor size information is obtained after the mold machining operation process; acquiring the rotation frequency of the rotor in real time; acquiring actual measurement data of the motor; determining eddy current data and forming a qualified eddy current data reference range; determining eddy current data to be verified when the rotor rotation frequency does not fall into the qualified rotor rotation frequency range; determining an eddy current data deviation value based on the eddy current data to be verified and the qualified eddy current data reference range; and outputting an abnormal signal when the eddy current data deviation value exceeds the maximum eddy current data deviation range. According to the invention, the production quality of the shaded pole rotor is greatly improved, and the production cost and the defective rate are reduced.

The invention provides an ultrasonic probe maintenance service automatic response processing method and system, and belongs to the technical field of semantic analysis, and the method comprises the steps: firstly carrying out data acquisition operation, constructing an initial maintenance knowledge graph through the data acquisition operation, carrying out the dynamic enhancement of the initial maintenance knowledge graph, and obtaining a maintenance enhanced knowledge graph; then obtaining client context data, and obtaining semantic analysis data based on the client context data and the maintenance enhanced knowledge graph; executing a query strategy based on the semantic analysis data, obtaining final result data, and obtaining response material data based on the final result data; and finally, response service is carried out based on the response material data, and a prospective and integrated automatic response processing method is provided, so that maintenance response service can be better carried out on clients.

This invention discloses a three-dimensional visualization organoid culture device, belonging to the field of organoid culture technology. It includes a control center, which is communicatively connected to a virtual three-dimensional scaffold module, a laser visualization monitoring module, a biolayer interference sensing module, and an automated culture medium control module. This invention abandons the traditional matrix gel solid scaffold and employs focused acoustic vortex technology to construct a dynamically adjustable virtual acoustic trap array. It utilizes acoustic radiation force to achieve cell capture and spatial arrangement, avoiding the interference of uncertainties in the composition and biocompatibility differences of solid scaffolds on organoid growth. Simultaneously, the acoustic trap array can adaptively reconstruct its topology according to the cell aggregation stage and metabolic state, solving the problem that traditional scaffold structures cannot adapt to dynamic cell growth, improving the morphological uniformity and physiological relevance of organoids, and providing a high-quality culture medium for organoid research and clinical applications.

The invention discloses a ship common rail oil injector health assessment method and system, and relates to the field of ship equipment health monitoring, and the method comprises the steps: obtaining a normal pressure signal of a common rail pipe of an oil injector in normal work; preprocessing the normal pressure signal, extracting normal time domain features, and normalizing the normal time domain features; constructing and training a self-organizing mapping neural network by using the normalized normal time domain features to obtain an optimal matching unit and obtain a reference distance threshold value; wherein the optimal matching unit is a node with the minimum Euclidean distance from the input normal time domain feature in an output layer of the self-organizing mapping neural network; s2, processing the real-time pressure signals collected in real time according to the step S2, obtaining real-time time domain features, calculating the Euclidean distance between the real-time time domain features and the optimal matching unit, and comparing the Euclidean distance with a reference distance threshold value; and when the reference distance threshold value is larger, it is judged that the oil injector is in a healthy state. The method has the effect of high real-time performance.

The application discloses a health monitoring method and system for a fluid circulating system, and the method comprises the following steps: collecting multi-source data of the fluid circulating system; outputting a health baseline data set in a historical period; pre-training a physical information neural network (PINN) that fuses fluid motion physical laws to generate a PINN-based prediction model; inputting circulating pump flow and rotating speed under real-time working conditions into the PINN-based prediction model to output a predicted pressure difference; calculating the difference between the measured pressure difference and the predicted pressure difference at each time point to obtain a residual sequence; extracting residual fluctuation characteristics by using a first-level moving average deviation (MAD) method, combining a second-level exponentially weighted moving average (EWMA) method to construct health characteristics, and outputting a health characteristic sequence to be tested; and realizing fault early warning of the fluid circulating system through a preset control limit. The method provided by the application is a health monitoring method that does not need to rely on a large number of fault samples, and meets the operation monitoring demand of long service life and high reliability of the fluid circulating pump.

The invention provides a microwave reaction cavity heating uniformity analysis method and system, and relates to the technical field of microwave heating. Real-time microwave excitation and cavity wall temperature array signals are synchronously collected, and excitation weights are analyzed by using a pre-built model and a regularization inversion algorithm; on-line and dynamic analysis of the heating state of the microwave reaction cavity in operation is achieved, the hysteresis problem of traditional detection depending on shutdown is solved, random noise can be effectively stripped from an actually measured temperature field through screening of dominant modes, construction of energy space distribution and weighted fusion, and the detection accuracy is improved. The method comprises the following steps: firstly, extracting a characteristic temperature field dominated by the inherent electromagnetic characteristics of a cavity, enhancing the physical mechanism property and anti-interference capability of analysis, then introducing compensation calculation based on the dielectric temperature change characteristics of the material, correcting heat distribution distortion caused by the change of the attributes of the material, and calculating the heat distribution distortion; and the obtained reference temperature field can more truly reflect the heating uniformity capability of the cavity.

The invention belongs to the field of medical treatment, and particularly relates to a multi-mode pain assessment method and a pain monitoring system for an ICU patient. The method comprises the following steps: constructing a pain recognition model for generating a pain state of a patient according to multi-modal data; the pain recognition model comprises a feature extraction module, a feature fusion module, a personalized module and a pain evaluation module; basic information, face videos and physiological monitoring data of ICU patients meeting requirements are obtained to form multi-modal data, and label information is added according to CPOT pain assessment results; setting a loss function according to task types to obtain a large number of sample data sets; the training set, the test set and the verification set are divided into a training set, a test set and a verification set for training, testing and verifying the pain recognition module; the validated model is retained and used for pain assessment of the ICU patient. According to the invention, the defects of hysteresis and insufficient reliability of a patient pain assessment scheme adopted in the existing ICU are overcome.

This invention relates to a sulfur dioxide detection device and method applicable to blast furnace gas before and after fine desulfurization. The detection device includes a pre-desulfurization gas control component, a post-desulfurization gas control component, a blast furnace gas combustion device, and SO2 and O2 detection devices. The detection method includes steps such as preheating the combustion device, igniting and burning the pre-desulfurization blast furnace gas and air, detecting the pre-desulfurization gas combustion gas, switching to combustion of post-desulfurization gas, detecting the post-desulfurization gas combustion gas, and performing result analysis and comparison. By specifically configuring the device and setting each step, continuous switching combustion is achieved to separately measure the sulfur dioxide content of the combustion gas, thereby enabling real-time monitoring of the desulfurization results of the fine desulfurization device and real-time prediction of different combustion conditions at the user end, greatly improving the monitoring effect of the fine desulfurization device.

The invention relates to the field of particulate matter detection, and discloses a particulate matter online diluting, sampling and measuring system and method.The particulate matter online diluting, sampling and measuring system comprises a particulate matter pre-separation module used for conducting particle size grading on sampled flue gas; the multi-stage dilution module is connected with the particulate matter pre-separation module and is used for carrying out at least two-stage dilution on the graded flue gas; the ionization and online measurement module is connected with the multi-stage dilution module and is used for charging particulate matters in the diluted flue gas and measuring the concentration of the particulate matters in real time; the particulate matter filtering module is connected with the ionization and on-line measurement module and is used for capturing particulate matters flowing through the ionization and on-line measurement module; the gas source and distribution module is used for generating and distributing multiple paths of clean gas flows and respectively providing the clean gas flows to the multi-stage dilution module and the ionization and online measurement module; the online real-time accurate measurement of the particulate matter concentration is realized, and the hysteresis problem of traditional offline sampling is thoroughly solved.

This invention relates to the field of environmental protection and resource recycling technology, and discloses a method for reducing the volume of oily emulsified wastewater. The method includes: real-time acquisition of multimodal sensor data such as turbidity, conductivity, oil-water interface height, pH, and temperature; and fusing and calculating a dynamic characteristic state vector composed of coalescence efficiency, phase separation rate, and interface stability. This invention, through the fusion of multimodal sensor data and deep feature extraction, transforms the monitoring of the demulsification process from macroscopic, qualitative subjective observation to microscopic, quantitative dynamic state characterization, achieving precise, objective, and real-time understanding of the process state. This fundamentally solves the problems of subjectivity and lag in manual judgment; it can predict the evolution trend of the system state over a future period, thereby transforming the control strategy from passive responsive regulation to proactive predictive intervention.

The utility model provides a valve with a signal feedback function, which belongs to the technical field of valves and comprises a valve main body, a switch handle is rotatably arranged at the top of the valve main body, a valve body limit bump is arranged at one end of the switch handle, and an opening limit block and a closing limit block are arranged at the top of the valve main body corresponding to the valve body limit bump. A switch feedback assembly is arranged on one side of the valve body limiting protruding block. The switch feedback assembly comprises a valve opening signal feedback device and a valve closing signal feedback device, an installation block is arranged on one side of the valve body limiting protruding block, first installation grooves are formed in the two sides of the installation block, and the valve opening signal feedback device is installed in the position, corresponding to the opening limiting block, of one set of first installation grooves. The valve opening signal feedback device and the valve closing signal feedback device are used for detecting the opening or closing state of the valve, the problem that a traditional valve depends on manual inspection is solved, and the management efficiency is improved.

The utility model discloses a high-pressure infusion pump for a high performance liquid chromatography system, which comprises a driving module and a pump module, the driving module comprises a stepping motor and a driving shell, a transmission cavity is arranged in the driving shell, the output end of the stepping motor is connected with an eccentric shaft, the eccentric shaft is provided with a photometric sheet, the driving shell is provided with a photoelectric sensor, and the photoelectric sensor is connected with the transmission cavity. The pump module comprises a pump body and a pump head, a linear bearing is arranged in the pump body in a penetrating mode, a push rod is correspondingly inserted in the linear bearing, one end of the push rod is correspondingly in transmission connection with the eccentric shaft, and the other end of the push rod is connected with a plunger seat. A butt joint groove is formed in the side, close to the pump module, of the driving shell, and the groove wall of the butt joint groove is gradually reduced from an opening of the butt joint groove to the groove bottom end of the butt joint groove in the axial direction of the butt joint groove so that a step structure can be formed. The method has the effect of remarkably improving the output stability of the mobile phase.

The application relates to the technical field of partial discharge processing, and discloses a partial discharge processing method and system based on electric field analysis, which comprises the following steps: synchronously collecting the electric field intensity and the charge density of multiple points on the surface of a device; identifying abnormal charge areas and calculating the electric field unevenness index according to the above information; inputting the above information into a finite element analysis model, simulating the electric field distortion process, and locating potential discharge induction points; combining historical operation data to predict the charge accumulation trend of each potential point, and constructing an optimization function aiming at minimizing the global electric field distortion and charge accumulation risk according to the charge accumulation trend; and taking the function as a convergence target, and automatically solving the optimal electric field compensation parameter through iterative calculation. The partial discharge processing method and system based on electric field analysis can predictively identify and offset the core causes of discharge, and actively and accurately inhibit the partial discharge of a device.

This invention relates to a method and system for predictive and proactive control of cigarette machine production quality based on operating condition parameters, belonging to the fields of tobacco machinery manufacturing, industrial automation control, and artificial intelligence. It includes: real-time acquisition of multi-dimensional operating condition parameters during cigarette machine operation; data preprocessing; acquisition of multi-dimensional time-series feature input sequences; construction of a time-series prediction model based on a long short-term memory network and incorporating an attention mechanism; training the time-series prediction model using the time-series feature input sequences; inputting the real-time operating condition feature sequences into the trained model to obtain key quality indicators; establishing a multi-index quality evaluation system using the analytic hierarchy process (AHP); comprehensively evaluating key quality indicators and other key quality indicators to obtain quantitative scores; and initiating graded quality early warning signals based on the degree to which the quantitative scores deviate from target values, using the early warning signals to drive parameter adjustments in the cigarette machine control system, thereby achieving proactive correction of quality deviations.

The invention discloses a supplier production line quality control method and system based on an MES system, and the method comprises the steps: obtaining the production data of a supplier MES end based on a pre-constructed standardized interface; before the materials arrive at the purchasing party MES end, quality analysis is conducted on the materials according to the production data, the materials are screened according to the quality analysis result, and screened materials are obtained; when the sieved material enters the MES end of the purchaser, inputting production data into a quality prediction model for potential quality risk prediction, and outputting a prediction risk grade; after the sieved materials reach the MES end of the purchaser, sampling inspection is conducted on the sieved materials according to the predicted risk grade and the production data, and a sampling inspection result is obtained; and when the screened material has an online quality problem, root cause analysis is carried out according to production data and a sampling inspection result, and a quality problem root cause is obtained. The quality risk can be blocked in advance, the data tracing process is simple and transparent, and the method can be widely applied to the technical field of quality control.