389results about How to "Improve analytical accuracy" patented technology

The invention relates to the field of inductive control of illuminating lamps, in particular to an inductive control system of an inductive LED illuminating lamp. The method comprises the following steps: the lighting scene module is used for identifying all LED lighting lamps in an area; calculating node positions of all the LED lighting lamps in the area one by one, and identifying use scenes in the area to construct a plurality of LED lighting scene sub-areas; the ambient light feature module is used for acquiring ambient light parameters of a scene sub-region; performing light spatial distribution tracking on the ambient light parameters of the scene sub-regions, and performing ambient light state feature mining to generate ambient light comprehensive state features; and the multi-area lighting cooperation module is used for carrying out dynamic light source output parameter adjustment and multi-area lighting cooperation smoothing on the plurality of LED lighting scene sub-areas based on the environment light comprehensive state characteristics so as to generate multi-area lighting cooperation control parameters. According to the invention, rapid and accurate induction control of the LED illuminating lamp is realized.

The invention relates to the field of circuit board quality detection, in particular to an aluminum circuit board surface treatment quality detection system and method. The method comprises the following steps: acquiring a real-time thermal imaging view of the aluminum circuit board; performing multi-point sampling calculation on the real-time thermal imaging view of the aluminum circuit board, and performing temperature distribution analysis so as to generate temperature distribution data of the aluminum circuit board; performing temperature rise distribution trend reconstruction based on the temperature distribution data of the aluminum circuit board, and performing abnormal region positioning so as to obtain a coating abnormal region; carrying out multidirectional ultrasonic pulse detection on the coating abnormal area, and collecting a multi-array sound wave signal; carrying out low-pass filtering processing on the multi-array sound wave signals, then carrying out three-dimensional projection remodeling, and constructing a three-dimensional sound wave projection drawing; and acoustic wave penetrating circuit board attenuation inversion is carried out on the three-dimensional acoustic wave projection drawing, and then surface defect analysis is carried out, so that an aluminum circuit board surface defect area is obtained. The method for accurately and efficiently detecting the surface defects of the aluminum circuit board is realized.

The invention discloses an underground cable pipeline abnormity monitoring method and system, and the method comprises the following steps: S1, building a three-dimensional grid based on the regional soil distribution condition, and obtaining a collection point data set based on the three-dimensional grid and underground cable pipeline data; s2, acquiring acquisition distribution corresponding to each to-be-arranged sensor type based on the to-be-arranged sensor type and the acquisition point data set; s3, acquiring underground cable pipeline time sequence data acquired by each sensor based on acquisition distribution, and performing clustering analysis on the underground cable pipeline time sequence data to acquire abnormal data points; and S4, obtaining an abnormal position according to the abnormal data points and the collection distribution, and outputting abnormal information of the underground cable pipeline according to the abnormal position. The method has the beneficial effects that the physical position of the cable pipeline is considered, meanwhile, the soil environment characteristics are considered, the accuracy of sensor arrangement in the pipeline is improved, the abnormal data point analysis efficiency is improved, and the underground cable pipeline abnormity can be conveniently and timely checked.

The invention discloses a cloud computer end-to-end fault root cause analysis method and system, and relates to the technical field of operation and maintenance data analysis, and the method comprises the steps: deploying data collectors on a virtual resource pool, a multi-stage cloud management platform and a cloud computer terminal, and monitoring and collecting various operation and maintenance data in real time; a unified operation and maintenance management center is introduced to complete the following work: providing management and configuration services of the data collector; receiving and summarizing operation and maintenance data; various AI models are accessed, operation and maintenance data from different sources are distributed based on the types of the AI models, the AI models perform deep analysis and diagnosis on the operation and maintenance data, and potential fault modes or abnormal behaviors are identified; customizing an alarm strategy, an alarm processing flow and an alarm notification mode; and introducing an AIOps service to generate an alarm and fault analysis report according to the analysis and diagnosis results of the AI model. According to the method, the service quality of the end-to-end full link of the cloud computer is monitored in real time, so that faults can be quickly positioned, early warning can be performed in advance, and the operation and maintenance cost and the fault risk are reduced.

The invention discloses a lightweight space-time traffic flow prediction method based on GAT and Mama, and relates to the technical field of intelligent traffic systems. According to the method, the feature expression ability of the model is improved through multi-dimensional feature learning (time, date and space-time) of an embedded layer, rich features of input data can be deeply captured, and the learning ability of the model is enhanced; a graph attention module is used to adaptively pay attention to the relative importance between nodes, so that the graph structure relationship in the data can be more effectively captured and utilized, and the analysis accuracy of the model on the spatial data is improved; the GAT-Mama module optimizes the time sequence analysis and spatial data processing capability, and the model can more accurately capture the dynamic dependency relationship between time points and between spatial positions through a multi-layer graph attention mechanism and residual connection; the GAT-Mama layer structure supports flexible adjustment, a user can adjust the depth of the model according to specific task requirements so as to adapt to spatio-temporal data prediction tasks with different complexities, and good adaptability is achieved.

The invention discloses an automatic auditing and analyzing method for cultivated land soil data. The method comprises the following steps: S1, acquiring original soil data through multi-spectral imaging of an Internet of Things sensor and an unmanned aerial vehicle to form a data set; s2, using an extended Kalman filter to reduce noise and remove abnormal values, and using time sequence interpolation to complement missing data; s3, analyzing and auditing the preprocessed data based on the time sequence, and identifying an abnormal mode; s4, analyzing and fusing auditing data by using a causal reasoning graph neural network; s5, performing multi-dimensional analysis and prediction on the fused data by applying a big data analysis technology; s6, realizing real-time data visualization and interactive display through a visualization method driven by quantum computing; s7, using a natural language generation technology to generate a report for the soil data set and the analysis result; and S8, implementing encryption and access control in the data processing and transmission process. The invention provides a comprehensive soil data processing solution, and the data auditing efficiency, accuracy and safety are effectively improved.

The invention relates to a replay playback display control method based on event tracing, which is suitable for event analysis and playback control in a simulation deduction process, and comprises the following steps: inputting a key event; event data analysis; key events are dynamically displayed; deducing situation backtracking; performing playback control; subscribing and pushing key events; tracing an evaluation result; and deducing data association analysis. According to the method, the playback experience of the user is improved, the user can subscribe specific key events, the system pushes event results in real time in the deduction process, multi-path analysis is carried out through different conditions, the evaluation results are visually displayed and traced, and the user is helped to comprehensively analyze the influence of the key events on deduction.

The invention discloses a fault root cause analysis method based on multi-source equipment data fusion. According to the method, multi-source heterogeneous data such as equipment operation data, maintenance records and environment data are collected and efficiently fused, a fault mode is automatically recognized from fused data, and time sequence evolution characteristics related to faults are mined. And based on the established knowledge base of the fault modes and reasons, and in combination with interactive Bayesian network reasoning and manual feedback, the root cause of the fault is deduced. According to the method, innovative technologies such as active learning and transfer learning are introduced, and the intelligent level, accuracy and efficiency of fault diagnosis are improved. And a visual interface visually presents an analysis process, supports man-machine interaction correction, and enhances interpretability. The method is suitable for the fields of industrial equipment, transportation tools, medical equipment and the like, and the system stability and usability are improved.

The invention relates to the technical field of ring piece rolling, and discloses a large special-shaped ring piece rolling forming process analysis method which comprises the following steps: (1) forge piece and blank design: designing different types of blanks; (2) material characteristic modeling: establishing a material model meeting rolling conditions; (3) finite element model establishment: establishing a geometric model of a rolling process by utilizing finite element analysis software; (4) rolling process scheme design: designing a plurality of rolling process schemes; (5) process simulation and defect prediction: analyzing strain, stress, temperature field and metal flow conditions in the simulated rolling process, and analyzing defect generation conditions; and (6) real-time monitoring and feedback control: monitoring changes of stress, strain and temperature in real time, and automatically adjusting process parameters. And through dynamic material characteristic modeling, a self-adaptive grid division technology and multi-physical field coupling analysis, the analysis accuracy of the rolling process is improved, so that defect prediction is more accurate, and the quality of finished products is improved.

The invention discloses a hotspot mining system and method based on Internet finance and economics information and a medium, and relates to the field of Internet finance and economics hotspot mining systems, and the system comprises an information collection module which collects finance and economics information in a multi-source manner, determines a collection period according to source characteristics, and carries out the screening and storage; the text preprocessing module is used for cleaning and analyzing texts, standardizing terms and carrying out classification labeling; the hotspot evaluation index calculation module is used for calculating indexes such as classification weighting, TF-IDF and the like; the hotspot mining and analyzing module is used for setting threshold mining hotspots, analyzing emotion and the like; and the visual display module is used for visually displaying the hot spots and supporting interaction and pushing. According to the invention, financial information is integrated, and hotspots are mined accurately. The information acquisition efficiency is improved, and decision-making investment and research are assisted. Information spreading is promoted, and financial field development is promoted.

The invention discloses a spectral analysis device and a control method thereof, and relates to the technical field of spectral analysis. The spectral analysis device comprises a spectral analysis chamber, a measuring gas chamber and a sample loading device. A light source and a detector are arranged in the spectrum analysis chamber; the measuring gas chamber is adjacent to the spectral analysis chamber and is used for providing required adjustable atmosphere conditions for a sample to be detected, and an optical window for an optical signal to pass through is arranged between the measuring gas chamber and the spectral analysis chamber; a to-be-tested sample is placed on the sample loading device. The measuring gas chamber is additionally arranged at the position adjacent to the spectral analysis chamber, and can provide required adjustable atmosphere conditions for the sample to be detected, so that the stability of environmental conditions in the analysis process is ensured. When XRF or LIBS spectral analysis is carried out, absorption of the atmosphere to spectral signals in a light path can be effectively reduced. The arrangement of the measuring air chamber can separate the sample to be measured from the optical window, so that attenuation and distortion of spectral signals caused by attachment of external dust are effectively avoided, and the acquired spectral data are ensured to be more accurate.

The invention relates to the technical field of marine monitoring, and discloses an intelligent marine organism monitoring method and system, the method is applied to a marine resource management platform, the marine resource management platform is constructed based on a digital twinborn technology, and the method comprises the following steps: determining a biological monitoring demand corresponding to a target area; collecting sensing data of the target area about marine organisms; according to the sensing data, determining a marine organism recognition result corresponding to the target area; according to biological monitoring requirements, analyzing the marine organism recognition result to obtain a marine organism analysis result corresponding to the target area; the marine organism analysis result is used for representing the growth and / or activity and / or distribution condition of the marine organisms in the target area. Therefore, the monitoring comprehensiveness and the monitoring accuracy of marine organisms can be improved, so that the management comprehensiveness and the management accuracy of the marine ranch are improved.

The invention discloses a signal processing method and device based on a micro-grid and electronic equipment. The method relates to the field of power system stability analysis, and comprises the following steps: constructing a target micro-grid model based on a plurality of components included in a micro-grid; based on the target micro-grid model, performing bifurcation operation on a plurality of balance points in the micro-grid to obtain a bifurcation result; based on the bifurcation result, obtaining a state space result of the target microgrid model; and determining a signal stability result of the micro-grid based on the bifurcation result and the state space result. According to the method, the technical problems that the method for analyzing the signal stability of the micro-grid in the related technology is a linearized method, is lack of relation with the dynamic process of the system, can only be used for evaluating the stability of the small signal, and cannot provide a system oscillation and instability mechanism which is more concerned by operation and maintenance personnel are solved.

The invention is suitable for the field of pressure storage power station construction monitoring, and particularly relates to a BIM-based pressure storage power station underground chamber construction monitoring method and system, and the method comprises the steps: obtaining monitoring data used for representing the surrounding rock state of an underground chamber in a construction model; extracting feature distribution of the monitoring data in a time dimension by using a long-short term memory neural network; extracting feature distribution of the monitoring data in a spatial dimension based on a graph attention network; fusing the feature distribution of the monitoring data in the time dimension and the space dimension by adopting a cross attention fusion network structure, and constructing fusion features of the monitoring data; and taking the fusion features as input of a pre-constructed prediction model, and outputting a surrounding rock state prediction result. According to the invention, the BIM model and the monitoring data are combined, so that the construction state of the underground chamber can be comprehensively understood; and on the basis of feature extraction of monitoring data, monitoring and early warning of the surrounding rock state are realized, and the technical problem of poor accuracy of a monitoring result of a traditional monitoring method is solved.

The invention relates to the field of vehicle network communication, in particular to an automobile attack chain analysis method and device, electronic equipment and a storage medium. According to the method, the security event and the corresponding event data are firstly obtained to provide a basis for subsequent analysis; then, safety key elements in the event data are extracted, a knowledge graph is constructed with the safety key elements and the automobile software and hardware assets, the safety key elements and the automobile software and hardware assets serve as different entity nodes respectively, the association between the different elements is determined in this way, and the problem that the association of attack behaviors is neglected is solved. Then, analyzing the knowledge graph to obtain target malicious nodes to construct an initial attack graph, and analyzing event data to obtain an attack link to update a node relationship of the initial attack graph to obtain a target attack graph, so that a unified description framework is provided for complex attacks; the whole attack process and the relation between the nodes can be clearly known, and the inconsistency of understanding and reaction caused by lack of a unified description framework is avoided.

The invention discloses an environmental microbial community state evaluation method based on unsupervised clustering, and the specific implementation mode is as follows: obtaining metagenome sequencing data in an environmental sample, and carrying out microbial species annotation and abundance calculation; based on abundance data, sample microbial species richness and Shannon diversity indexes are calculated, microbial functional gene annotation and abundance calculation are carried out, standardization processing, principal component analysis, Euclidean distance calculation, Ward clustering and contour coefficient evaluation are carried out on the data, and dimensionality reduction and clustering are carried out on the multi-dimensional features. Therefore, comprehensive indexes with obvious differences are provided. According to the comprehensive indexes obtained through the method, original data can be reserved, the complexity of the data can be greatly reduced, the analysis process is simplified, and an intuitive and operable means is provided for overall state evaluation of the environmental microbial community, so that the analysis efficiency and accuracy are improved, and the method is suitable for popularization and application. And determining the overall influence of the environmental change on the microbial community state.

The invention discloses an intensity modulated radiotherapy plan quality assurance method and system based on virtual prediction, and the method comprises the steps: extracting complexity parameters from a radiotherapy plan RTplan of a patient, extracting three-dimensional dose distribution characteristics from RTdense, calculating the preprocessing data of a flux diagram through combining with TPS, and designing and training an end-to-end convolutional neural network model. The model comprehensively analyzes plan complexity, dosiomics features, and flux image features to predict virtual measurement flux and Gamma pass rate. Through multi-dimensional data fusion, the prediction accuracy and the QA efficiency are remarkably improved, the quality of the radiotherapy plan can be automatically evaluated in advance, the radiotherapy process is assisted to be accelerated, and the treatment precision is improved.

The invention discloses a characteristic value calculation method based on electrocardio data, belongs to the field of medical data analysis, and provides an electrocardio data analysis and processing method. Comprising the following steps: decomposing different frequency components of an electrocardiosignal by using wavelet transform, and analyzing on different time scales. Wavelet transformation is relatively suitable for detecting QRS wave groups, and due to the fact that the wavelet transformation can highlight transient characteristics of signals on different frequency bands, complex electrocardiosignal processing is more efficient. In addition, wavelet transform is not only suitable for wave crest detection, but also can help to remove signal noise and improve signal definition. The deep learning technology is used for automatically extracting the features from the electrocardiosignals, a feature extractor does not need to be manually designed, related medical professional knowledge and the artificial intelligence technology are combined, wave crests in the electrocardiosignals can be more accurately detected, and meanwhile anomaly detection can be carried out, such as early signs of heart diseases such as sinus arrhythmia and the like.

The invention discloses a machine vision-assisted intelligent road inspection method and system. The method comprises the following steps: acquiring road condition video image data and vehicle position data; performing road condition detection operation and road condition grading operation according to the road condition video image data to obtain road condition grade data; according to the road condition video image data, performing road sign detection operation and lane grading detection operation to obtain lane grading data; according to the vehicle position data, performing road environment detection operation and traffic dispersion grading operation to obtain dispersion grading data; according to the vehicle position data, carrying out clustering operation to obtain vehicle clustering data; performing confidentiality identification operation according to the vehicle clustering data to obtain position detection data; and according to the road condition level data, the lane level data, the dredging level data and the position detection data, performing inspection level judgment operation to obtain inspection level data. The method can improve the road analysis accuracy.

The invention discloses a network information intelligent analysis method and system based on a large model, and the method comprises the steps: firstly carrying out the preprocessing of network information, constructing a prompt word template through a multi-step thinking method, and processing the network information; calling the large model to obtain a network information analysis result presented by JSON format data; performing format judgment on the analysis result by using a feedback optimization method, and if the format requirement is not met, repeatedly calling the large model, and updating the network information analysis result; and performing JSON format matching on the analysis result of which the output format of the large model still does not meet the requirement to obtain an analysis result meeting the JSON template. According to the method, emotion analysis can be more accurately carried out on the network information, and the efficiency and accuracy of analysis work are remarkably improved.

The invention discloses a case data analysis system based on a large model, and the system comprises a data collection module, a preprocessing module, a large model training and optimization module, an analysis module, a visualization and interaction module, a security and privacy protection module, a data preprocessing module with an innovative algorithm, a large model training module with an adaptive learning rate formula, and a disease risk prediction module with an evaluation formula. System functions and performance indexes are clear, equipment and medium requirements are clear, the steps of the method are complete, and high efficiency, accuracy and safety of case data analysis are guaranteed; the case data processing efficiency and accuracy are improved, and powerful support is provided for medical decision making. A large model is accurately analyzed, visual and convenient to check, and a security module guarantees data privacy. The medical quality can be improved, the treatment scheme can be optimized, and the method has important application value.

The invention belongs to the technical field of global space planting, and discloses a global space planting environment regulation and control method and system based on artificial intelligence. The method comprises the following steps: constructing a global space planting environment analysis model and a global space planting environment regulation and control model based on a cloud computing center; acquiring real-time planting environment monitoring data based on a planting environment monitoring device; processing the real-time planting environment monitoring data based on an edge computing gateway; based on the cloud computing center, carrying out global space planting environment analysis; carrying out global space planting environment regulation and control, and sending a real-time regulation and control scheme to a corresponding edge computing gateway; and based on the edge computing gateway, according to the real-time regulation and control scheme, generating a real-time regulation and control instruction, and sending the real-time regulation and control instruction to the planting environment monitoring device and the planting environment regulation and control device. According to the method, the problems of high analysis cost, low efficiency, poor accuracy, unstable regulation and control effect and resource waste in the prior art are solved.

The invention discloses a flight personnel operation state analysis method. The method comprises the steps that S1, an eye movement tracker is adopted to collect eye movement trajectory data of a pilot and generate eye movement time sequence data; meanwhile, an electromyographic sensor array is adopted to collect eye muscle electrical activity signals and convert the signals into electromyographic feature vectors; s2, generating multi-modal deep fused eye movement track spatial position coding data from the eye movement track; s3, fusing the eye movement time sequence data after importance weight distribution with the eye movement track space position coding data after hyperplasia to obtain fused data; s4, training the fusion data in an XGBoost model to obtain a situation awareness evaluation model; and S5, evaluating the operation state of the flight personnel according to the situation awareness evaluation model. Eye movement track data and eye muscle electrical activity signals are obtained through a high-precision data acquisition means, deep processing and fusion are carried out on the eye movement track data and the eye muscle electrical activity signals, and therefore the accuracy and reliability of flight personnel operation state evaluation are improved.

The invention relates to the technical field of image processing, in particular to a construction method and system of a water area breach live-action three-dimensional model. The method comprises the following steps: acquiring breach area control point position data; performing surveying and mapping reference confirmation on the breach area control point position data to generate breach area control point reference data; performing three-dimensional coordinate conversion through the breach area control point reference data so as to generate breach area plane coordinate data; unmanned aerial vehicle satellite signal receiving is carried out based on the breach area plane coordinate data, and a standard unmanned aerial vehicle satellite signal is obtained; and performing unmanned aerial vehicle aerial image acquisition based on the standard unmanned aerial vehicle satellite signal to obtain an aerial image of the breach area. Through accurate data acquisition, efficient unmanned aerial vehicle image acquisition and processing, dynamic image utilization and optimized point cloud model construction and texture mapping, the accuracy and timeliness of the three-dimensional model are improved.

The invention belongs to the technical field of parking lot management, and relates to a parking lot intelligent operation analysis method based on a Mama model, and the method comprises the steps: firstly collecting and processing multi-source data; performing feature extraction and preprocessing on the processed data to obtain multi-dimensional tensor data; then, constructing a Mama model, and outputting a predicted value of a future traffic flow, abnormal and normal behaviors and predicted values of future parking demands; the Mama model is trained and optimized, a solution and a report are finally generated, manual intervention is reduced, efficiency is improved, data are automatically processed and analyzed, dependence on manual operation is reduced, analysis efficiency and accuracy are improved, human errors are reduced, real-time operation reports and insights are provided, and the requirement for modern management is met.

The invention discloses a method for accurately determining the content of trimethylamine, diethylamine and triethylamine in animal-derived traditional Chinese medicinal materials, which comprises the following steps: mixing alkali liquor and n-tetracosane in a headspace bottle, heating to completely dissolve the n-tetracosane, and standing until the n-tetracosane layer is solidified to seal the alkali liquor below the n-tetracosane layer; animal-derived traditional Chinese medicinal materials are crushed, sieved and dispersed in a trichloroacetic acid aqueous solution, centrifugation is performed after homogenization, supernate is collected, volume metering is performed, and a sample extracting solution is obtained; adding the sample extracting solution above the n-tetracosane layer in the headspace bottle, sealing by a gland, placing on an automatic sampler, sucking gas at the upper part of the headspace bottle, analyzing by a gas chromatograph-triple quadrupole mass spectrometer, and obtaining the contents of trimethylamine, diethylamine and triethylamine in the animal-derived traditional Chinese medicinal materials by an external standard method. The method is accurate and reliable in quantitative result, high in sensitivity and high in analysis efficiency, derivation is assisted by the phase change material n-tetracosane, the phenomenon that the quantitative accuracy is poor due to the volatile and escape characteristics of trimethylamine, diethylamine and triethylamine is effectively improved, the false positive phenomenon can be effectively eliminated through headspace sampling and a multi-reaction monitoring mode, and the method is suitable for large-scale popularization and application. The peak appearance of trimethylamine, diethylamine and triethylamine is completed within 6.5 minutes.

The invention belongs to the technical field of analysis and detection, and relates to an analysis method and an analysis system of ethylene glycol by-product mixed alcohol, the analysis method comprises the following steps: S1, preparing a corresponding reference solution and a standard mixed alcohol solution according to a to-be-analyzed component in the ethylene glycol by-product mixed alcohol; s2, for the reference substance solution and the standard mixed alcohol solution, constructing a standard curve model corresponding to each component through gas chromatography; s3, collecting by-products in ethylene glycol production in real time, and filtering; according to the method, peak areas corresponding to components to be analyzed in the mixed alcohol sample are obtained and then substituted into respective standard curve models respectively, and the content of the components to be analyzed in the mixed alcohol sample is obtained. According to the method, the standard curve model is constructed, and the mixed alcohol is pretreated, so that the content of multiple components in the mixed alcohol is analyzed and detected, the analysis time is shortened, the analysis cost is reduced, and the analysis accuracy and sensitivity are improved.

The invention relates to a rope tensile tension control method and system based on a tensiometer, and the method comprises the steps: carrying out the continuous pressurization of a to-be-detected rope, obtaining the tensile transient tension and the tensile critical tension of the to-be-detected rope through the tensiometer, obtaining the tensile change of the to-be-detected rope in the continuous pressurization process, and obtaining the tension value of the to-be-detected rope. Analyzing the stretching change relation between the pressurization load and the stretching tension of the to-be-detected rope by combining the corresponding stretching transient tension and the stretching critical tension, analyzing the dynamic deformation degree of the to-be-detected rope according to the stretching change relation, and determining the static deformation degree of the to-be-detected rope according to the static deformation degree under the constant pressure. And constructing a rope tension control model for analyzing the tensile tension of the to-be-detected rope, obtaining the actual hanging load of the to-be-detected rope, inputting the actual hanging load into the rope tension control model to analyze the actual deformation of the current hanging load, and adjusting and controlling the tensile tension of the to-be-detected rope according to the analysis result. The device has the effect of improving the test accuracy of the rope tensile tension.

The invention discloses a purity analysis method for crude vinyl chloride in a conversion process, which comprises the following steps: after sampling, carrying out qualitative and quantitative analysis on small molecule components in the crude vinyl chloride, then analyzing acetylene and high-boiling residues in the crude vinyl chloride, and calculating the purity of the crude vinyl chloride according to a deduction method. Compared with the prior art, the aluminum foil sampling bag is adopted for sampling, so that the problem of poor sample representativeness is solved; the content of the high-boiling residues in the crude vinyl chloride can be accurately analyzed by adopting gas chromatography, so that the accuracy and precision of analysis data are improved; according to the method, gas chromatography is adopted to completely replace a dichloroethane absorption method, so that the working intensity of workers is reduced, and the method has the effects of safety, environmental protection and low energy consumption.

The invention discloses an electric energy meter crimping process automatic detection and analysis method and system. In the prior art, when automatic detection and analysis are carried out in the electric energy meter crimping process, data processing in the crimping process is insufficient, and complex conditions in the electric energy meter crimping process cannot be comprehensively reflected due to data analysis from a single angle. The method comprises the following steps: detecting parameter data in a crimping process of the electric energy meter in real time, preprocessing the detected parameter data, and then performing intelligent enhancement processing to obtain detection data after the intelligent enhancement processing; and performing real-time analysis on the detection data after the intelligent enhancement processing to obtain an analysis result including pressure step-by-step analysis, position deviation detection and contact quality evaluation, determining an abnormal crimping condition of the electric energy meter based on the analysis result, and performing automatic alarm. According to the invention, possible abnormal pressure points, position deviation and contact quality problems can be identified, and the quality and consistency of the crimping process can be ensured from multiple angles.