14results about How to "Systematize" patented technology

The invention discloses a power grid monitoring alarm event handling method and system based on a large model, and relates to the technical field of power systems, and the method comprises the steps: obtaining a historical sample of a power grid monitoring alarm event, and carrying out the preprocessing; constructing a balance training sample set based on a first large language model and resampling combined sample enhancement method; based on the pre-training language model, utilizing the balance training sample set to carry out fine tuning training, and constructing a power grid monitoring alarm event diagnosis model; on the basis of a second large language model, a power grid monitoring alarm event disposal model is constructed, and the disposal model is used for retrieving reference information from a historical disposal knowledge base in combination with an event type diagnosis result output by the diagnosis model and generating an auxiliary disposal suggestion for an input alarm event text; and integrating the diagnosis model and the disposal model to form a power grid monitoring alarm event disposal framework. According to the invention, intelligent diagnosis and auxiliary disposal of the power grid monitoring alarm are realized, and the diagnosis accuracy and the disposal efficiency are improved.

The invention relates to the technical field of data processing, and particularly provides a manufacturing industry energy-saving and efficiency-increasing scheme generation method, system and equipment and a storage medium, and the method comprises the steps: collecting the operation state data, energy consumption data and real-time working condition data of industrial equipment in real time through an equipment monitoring module; preprocessing the collected data, establishing an energy efficiency reference, calculating a key energy efficiency index based on the energy efficiency reference to judge the energy efficiency state of the equipment, and executing multi-dimensional root cause analysis when the energy efficiency state is abnormal; according to the energy efficiency state and a root cause analysis result, matching and filtering applicable technical schemes from a technical unit library, and performing quantitative evaluation and comprehensive sorting on the technical schemes to generate a preferential transformation scheme list; and an energy efficiency analysis result is fed back to the equipment monitoring module for state early warning, and a customized proposal is generated based on the transformation scheme. According to the invention, the systematization and automation of industrial energy-saving management are realized by constructing a full-link closed loop generated by data perception, intelligent diagnosis and decision.

The application discloses a kind of comprehensive quality control methods of pasture data set, first carry out pasture data collection work, cover three major core dimensions of pasture development period, pasture growth height and pasture yield, lay foundation for subsequent data processing and quality control;After completing original data collection, carry out pasture original data cleaning, eliminate redundancy, incomplete, messy invalid information, comb and integrate to form complete standardized pasture basic data set;Specific implementation content includes: merging data format, standardizing pasture name and Latin name, standardizing development period name, data supplement and unit characteristic value uniformity;Then rely on multilevel checking rules, implement pasture data all-around quality detection and control, carry out station metadata inspection, repeated value inspection, format inspection, observation time inspection, value range inspection, limit value inspection and internal consistency inspection in turn, through multidimensional layer-by-layer checking, effectively improve the accuracy, reliability and standardization of overall data set.

The application provides a surface layout optimization method for chip assembly, relates to the technical field of layout optimization, acquires chip key index information, performs circuit board region division analysis according to the chip key index information, performs region division control according to region division analysis data, performs chip placement according to circuit board region division data, performs thermal-electric state analysis and determination according to chip placement data, and obtains basic state determination information; performs pad area analysis according to the basic state determination information, obtains pad area analysis data, acquires preset influence factor information, adjusts and analyzes the pad area analysis data according to the preset influence factor information, obtains pad adjustment analysis data, and adjusts the pad area according to the pad adjustment analysis data. The application solves the problems of strong subjectivity, poor adaptability and many performance hidden troubles of traditional design, and meets the assembly layout requirements of high precision and high stability of power chips.

The invention discloses a regional environment anomaly monitoring method based on remote sensing inversion and deep learning, and relates to the technical field of environment monitoring application, and the method is characterized in that multi-source remote sensing data is integrated, three types of core environment data of atmosphere, water and soil are inverted after preprocessing, monitoring units are divided in a unified manner, and a global data matrix is constructed; three types of environment association feedback nodes are defined, an exception list is generated by calculating an environment exception potential index, and the traditional data scattering limitation is broken through. According to the method, high-priority monitoring units are screened, a'pollution source-pollution factor-sensitive node 'full-chain monitoring association link is constructed based on three rules, risk indexes are quantified to mark abnormities, resources are concentrated, and the monitoring accuracy is improved. Meanwhile, unprocessed units are marked as dynamic adjustment units, correction indexes are calculated in combination with multiple factors, the monitoring range is dynamically optimized, a closed-loop system is formed, static monitoring defects are avoided, and monitoring timeliness and perspectiveness are improved.

The application relates to the technical field of saline-alkali soil irrigation, and discloses a saline-alkali soil irrigation system and method based on electric water folding and an electrode array layout, wherein the saline-alkali soil irrigation system comprises electrodes arranged in an array, a power supply assembly and a control assembly arranged at the edge of the saline-alkali soil, and a sensor assembly uniformly arranged in the saline-alkali soil; the power supply assembly is electrically connected with the control assembly; the control assembly is electrically connected with the electrodes and the sensor assembly; the sensor assembly comprises a moisture sensor and a salt content sensor; the electrodes are divided into three groups; the embedding depth of the electrodes in the third group is 1.6-2 times that of the electrodes in the second group; the embedding depth of the electrodes in the second group is 1.6-2 times that of the electrodes in the first group; and the electrodes comprise negative electrodes and positive electrodes. Through the technical scheme, the problem that the irrigation amount cannot be accurately controlled due to the fact that the moisture parameters and the salt content parameters in the soil cannot be obtained in a timely manner in the existing saline-alkali soil is solved.

The present application relates to the technical field of mine safety production and geological disaster monitoring, in particular to a kind of open pit slope floatstone dangerous intelligent sensing method and related equipment, method is, obtain target slope image, and reconstruct depth map.Prepreg floatstone region segmentation is carried out to slope image using pre-trained PSPNet image segmentation model, and floatstone segmentation map is generated.Pixel-level fusion is carried out to segmentation map and depth map, and three-dimensional point cloud data of floatstone is extracted.Convex hull algorithm is used to carry out three-dimensional grid reconstruction to point cloud, and the geometric characteristic parameter of floatstone is calculated, based on fuzzy comprehensive evaluation theory, in combination with above-mentioned geometric characteristic parameter, the danger level of floatstone is comprehensively evaluated, and scientific basis is provided for mine safety management.The method realizes the full-process automation from image acquisition to danger level evaluation, improves the evaluation efficiency and accuracy.

The application discloses a kind of bag cultivation inoculator sterilization method, including sequentially closed loop interface's before sterilization positioning verification preparation, collaborative steam sterilization negative feedback control, gradient pressure reduction pollution prevention time interlocking, strain pipeline preflushing and residual, terminal double sterilization, standardization reset and automatic inoculation trigger six steps, between each step through cross-post operation authority separation, state verification interlocking and negative feedback control mechanism Form one-way irreversible whole-process anti-bacterial closed loop system;Wherein, the state verification of previous step does not pass, inoculator control system is automatically locked and prohibited to enter next step.The application has the advantages of whole-process anti-bacterial, high degree of automation, safe and reliable operation, stable sterilization effect and traceability.

This invention relates to the field of mine ecological restoration technology, and discloses a method and system for mine ecological restoration. The restoration method includes selecting an area with residual heat from underground coal fires on a mine slope where residual coal has spontaneously combusted as a restoration zone; reinforcing and stabilizing the slope of the restoration zone; laying a sludge substrate with a moisture content of 60%-80% on the stabilized slope surface, and using the residual heat from the underground coal fires for in-situ biological drying until the volume reduction reaches a preset threshold of 40%-60%; subsequently, covering the dried sludge substrate with a soil substrate layer and a soil microbial substrate layer to construct a composite growth matrix; and finally, maintaining vegetation on the slope. This invention cleverly combines the residual heat from abandoned mines with urban sludge treatment, achieving the harmlessness, reduction, and resource utilization of sludge, while simultaneously solving the problems of excessively high soil temperatures and difficulty in plant survival in mining areas, achieving the goal of ecological restoration through waste treatment and synergistic efficiency.

This invention discloses a morphology-based method and system for classifying pores in tight reservoir porous media, comprising: acquiring microstructural images of rock tight reservoir samples using field emission scanning electron microscopy; labeling the SEM images with two types of samples, pores and matrix / background, as training sets, and training a segmentation model for rock samples; segmenting the sample SEM images using the trained segmentation model to generate binary images that identify the background and pores; automatically measuring pore morphology parameters based on the binary images to obtain pore roundness and aspect ratio; classifying pore shapes according to preset quantitative classification thresholds for pore roundness and aspect ratio, and outputting statistical classification results; this invention achieves a systematic and objective characterization of pore cross-sectional shape, transforming the traditional subjective judgment-dependent pore morphology description into a quantifiable and comparable structural index, solving the problem that traditional pore morphology classification relies on subjective judgment and lacks unified quantitative standards.

This invention discloses a method for assessing building-embedded carbon emissions based on multimodal remote sensing and graph neural networks. The method includes: constructing a building structure type classification system for building-wide lifecycle carbon emissions; identifying building structure types and calculating lifecycle carbon emissions based on a building project inventory to generate a sample dataset; extracting and fusing building features based on multimodal remote sensing data to generate a unified building feature vector; jointly training a multi-task graph neural network using the sample dataset and the building feature vector to obtain a model capable of simultaneously predicting building structure type and lifecycle carbon emissions; and mapping and spatial analysis of building-wide lifecycle carbon emissions based on the model's prediction results. This invention achieves high-precision joint prediction of building structure identification and lifecycle carbon emissions, overcoming the limitations of traditional methods in data completeness and spatial accuracy, and enabling intelligent monitoring of urban carbon emissions.

The invention relates to the technical field of data acquisition, and discloses a domestic acquisition device component matching optimization method and system based on a genetic algorithm, and the method comprises the steps: obtaining a domestic acquisition device core component library, and arranging performance parameters; constructing a comprehensive performance evaluation model, and establishing association between the component parameters and the overall performance of the device; initializing a component combination population to generate an initial candidate set; performing fitness evaluation on the population individuals based on the evaluation model; executing genetic operation iteration to generate a new population; the evaluation and operation are repeated until a termination condition is met, and an optimized population is obtained; and screening an optimal or suboptimal combination to obtain a recommended matching scheme. According to the method, the technical problems of poor component matching, high acquisition delay, insufficient data processing throughput and large signal synchronization error caused by relying on engineer experience type selection and lacking multi-dimensional comprehensive optimization are solved.

The application provides an interview question divergent generation method, comprising the following steps: S1, obtaining current question data and candidate's current answer data in the interview interaction process, and simultaneously loading interview investigation target data, post image, candidate background auxiliary reference data; S2, performing dimension analysis and path coverage analysis on the current question data and the current answer data, identifying the opened investigation direction of the current question, the covered investigation direction of the current answer, and marking the to-be-investigated direction which is not expanded; the application realizes systematization and multi-level divergent generation of the interview question by obtaining the interview interaction data, performing path coverage analysis, constructing a dynamic update investigation space expansion diagram, generating and evaluating candidate questions, outputting optimal questions and correlation update, has systematization and multi-level divergent capacity, and significantly improves the coverage, pertinence, logic, dynamic adaptability and traceability of the interview evaluation.

The application relates to a wheel hub motor heat dissipation monitoring method, system, device and medium thereof, comprising the following steps: acquiring temperature sensors arranged on three components of a stator winding, a bearing end cover and a shell surface of a wheel hub motor; continuously collecting temperature data according to a preset sampling period to obtain temperature time sequence data corresponding to each component; taking a temperature value at a historical sampling time point with a preset time length from a current sampling time point as a moving average value, performing weighted moving average calculation on temperature values corresponding to temperature time sequence data within the preset time length to obtain a weighted moving temperature value; determining a heat dissipation monitoring state grade of the wheel hub motor according to the weighted moving temperature value corresponding to each component at the current sampling time point and real-time operation parameters of the wheel hub motor; and controlling a corresponding heat dissipation fan of the wheel hub motor to perform air supply heat dissipation according to the heat dissipation monitoring state grade.