22 results about "Benchmark database" patented technology

This invention discloses a method and system for real-time prediction of laser strike effects for rapid deployment. The system includes: defining standard reference environmental parameters, calibrating standard attenuation coefficients and standard power-to-target (PTO) values; constructing a benchmark database; collecting target environmental parameters and calculating the power attenuation ratio between the target environmental parameters and the standard reference environmental parameters; calculating the PTO power under the target environmental parameters based on the power attenuation ratio, and calculating the PTO power density based on the PTO power; finding the benchmark minimum effective power density of the target target material based on the benchmark database; and, if the PTO power is greater than or equal to the benchmark minimum effective power density, estimating the estimated penetration time of the target target material based on the PTO power, the power density at which the target material penetrates the target material under the standard reference environmental parameters, and the penetration time. This invention features extremely low computational complexity, fast response speed, and guarantees laser strike effects superior to empirical estimates.

This application discloses a visual laser composite monitoring method and system for disconnector switch contacts, relating to the field of power system monitoring technology. The method includes: establishing a corresponding reference database based on the target disconnector switch; acquiring real-time image information, real-time laser ranging information, and real-time control information of the target disconnector switch after completing the closing action, and analyzing these to determine if the switch is in place, obtaining closing determination information; and issuing a closing warning result based on the closing determination information. This application addresses the problem that existing disconnector switch position monitoring relies on external indicators and cannot intuitively and accurately determine the insertion depth of internal contacts. By combining visualization and laser ranging principles, it solves the difficulties of existing methods in determining whether the switch is in place and quantifying the insertion depth, aiming to fundamentally avoid power safety accidents caused by incomplete closing.

This application relates to the field of semantic analysis technology, specifically to a method and system for extracting audit anomaly semantics from unstructured data. The method includes: acquiring a benchmark graph and a benchmark database and their entity mentions; obtaining the strings of entity mentions based on their positions; acquiring an audit candidate set of strings from the benchmark database; determining a matching score based on the consistency of audit roles, and then filtering the candidate entity set; encoding the candidate entities, their audit role sets, entity mentions, and strings to obtain the probability distribution of entity mentions and candidate entities, and determining the audit role consistency score based on the probability distribution; classifying the association between entity mentions and candidate entities based on the overall magnitude of the audit role consistency score, and applying different audit rules to each category; and extracting audit anomaly semantics using the audit rules. This application improves the accuracy and efficiency of semantic extraction.

The present application relates to the field of expressway green channel violation monitoring, and particularly relates to a kind of fresh agricultural products transport truck intelligent rapid detection method based on multi-source data fusion. Including the following steps: step one, build goods packaging loading proportion benchmark database and empty car mass benchmark database;Step two, collect total weight of loaded vehicle, actual vehicle information and transport goods information, obtain goods packaging loading proportion;Step three, obtain difference absolute value according to actual goods loading quality and theoretical maximum goods loading quality;Step four, determine trust level according to the ratio of difference absolute value and theoretical load;The trust level includes mild suspicion and severe suspicion;For the vehicle determined as severe suspicion, it is suggested to carry out artificial strict inspection, and the vehicle determined as mild suspicion is normally inspected. The present application can automatically identify insufficient loading, mixed loading goods and other various violations, significantly improve the accuracy and efficiency of green channel vehicle detection.

This invention relates to the field of battery state monitoring technology, and more particularly to a method and system for monitoring the state of hybrid energy storage batteries based on data processing. The method includes the following steps: acquiring impedance measurement data of the hybrid energy storage battery pack at a preset frequency sequence; performing temperature correction processing on the impedance measurement data to obtain corrected impedance data under standard temperature conditions; establishing a health state impedance benchmark value for each energy storage unit based on the corrected impedance data, thus obtaining an impedance benchmark database; calculating the impedance difference value sequence between adjacent frequency points for each energy storage unit using the corrected impedance data; dividing the impedance difference value sequence by the characteristic impedance value of the corresponding energy storage unit in the impedance benchmark database and performing normalization processing to obtain a differential impedance characteristic vector. This invention establishes an accurate temperature compensation mechanism, eliminating the influence of ambient temperature changes on impedance measurement results, and ensuring the consistency and comparability of monitoring results under different operating conditions.

The application discloses a vehicle mass and wheel load distribution estimation method and device based on steady-state signal decoupling, comprising: obtaining test calibration data of a plurality of suspension type test vehicles, establishing a partial load reference database and a partial load solving rule library covering a plurality of suspension types according to the test calibration data; matching corresponding target partial load reference data and target partial load solving rules in the partial load reference database and the partial load solving rule library according to a target suspension type of a target vehicle; obtaining a standard sensor signal of the target vehicle in a steady-state straight running state, determining a partial load estimation result and an estimation accuracy identifier of the target vehicle according to the standard sensor signal, the target partial load reference data and the target partial load solving rules; and outputting the partial load estimation result and the estimation accuracy identifier to a vehicle-mounted control system of the target vehicle. The application improves the reliability of vehicle mass and wheel load distribution estimation and can be applied to the technical field of vehicle control.

This disclosure provides a method and electronic device for diagnosing bearing faults. The diagnostic method includes: acquiring historical vibration signals of the bearing in three channel directions to form a benchmark database; extracting several key influence features associated with bearing faults from each historical vibration signal in the benchmark database, and determining a reference interval corresponding to each key influence feature; acquiring actual vibration signals of the target bearing in the three channel directions; extracting several target features corresponding to the key influence features from the actual vibration signals; calculating the comprehensive deviation of the actual vibration signals based on the target features and the reference intervals; and determining the bearing fault feature vector and target fault characteristics in response to the comprehensive deviation exceeding a preset threshold. This disclosure ensures the accuracy of bearing diagnosis while meeting the real-time monitoring needs of unlabeled, multi-condition industrial applications, and can dynamically adapt to changes in operating conditions without supervision, thereby significantly improving the accuracy of bearing fault identification.

This invention discloses a one-click management method and system for the entire process of steel structure materials based on Tekla and VBA, belonging to the field of steel structure information technology. The method establishes a maintainable material baseline database in Excel; exports a parts list containing "usage location, drawing number, manufacturer, net weight, and gross weight" via a Tekla plugin; utilizes six sequentially executed VBA programs to automatically translate material codes, match and deduct planned quantities from delivered quantities, summarize by system / manufacturer dimensions, provide material shortage / overconsumption warnings, calculate area from budget orders, and statistically analyze delivery rates; a single refresh forms a closed-loop management system of "design quantity - planned quantity - delivered quantity - cost quantity," eliminating duplicate purchases, reducing steel waste, and achieving automation, refinement, cost reduction, and efficiency improvement in steel structure material management.

This invention discloses a method and system for analyzing changes in the storage quality of potatoes, relating to the field of food storage technology. The method includes: assigning unique identifiers to potato samples to be analyzed and constructing an inherent anchor point benchmark database; generating anchor point homogeneous time-series datasets with storage duration as the time-series axis for potato samples with uniform identifiers at preset fixed time intervals; executing a spatiotemporal anchoring homogeneous matching algorithm to extract the specific degradation time-series difference and degradation spatial diffusion gradient time-series sequence of degradation points; solving to generate a full-cycle spatiotemporal coupled degradation surface of the potato's true degradation process from local to overall; and outputting an analysis report on the spatiotemporal evolution law of the storage quality of the corresponding potato samples. This invention can accurately reconstruct the entire process of quality degradation, identify key inflection points of degradation, provide accurate data support for real-time control of storage processes, and effectively reduce post-harvest storage losses of potatoes.

This invention discloses a method for generating tabular data based on local context retrieval and fine-tuning, comprising: obtaining raw tabular data samples for machine learning training from a public benchmark database, performing preprocessing and data partitioning to obtain feature columns and label columns, and constructing a training set; fine-tuning the local calibration parameters of a TabPFN model based on the training set to obtain a parameter-fine-tuned TabPFN model; obtaining pseudo-data samples based on the training set by manually setting the target number of samples and target category labels; and iteratively updating the pseudo-data samples and the parameter-fine-tuned TabPFN model using an iterative sampling method based on dynamic local context to finally obtain a tabular dataset. This invention, through local calibration parameter fine-tuning and dynamic local context iterative sampling, can generate high-quality, diverse tabular datasets, effectively improving the realism and usability of the generated data.

This invention relates to the field of gas radiation calculation technology, providing a method and system for calculating gas radiation during methanol-coal blending. The method involves obtaining the monochromatic radiation absorption coefficients of each radiating gas component under basic operating parameters during the blending process, then using Planck's law to calculate the total emissivity of the mixed gas under different basic operating parameters during blending, establishing a benchmark database of gas radiation characteristics in methanol-coal blending; fitting the parameters of the mixed gas emissivity calculation model using the benchmark database; and calculating the gas radiation characteristics under any methanol-coal blending condition using a mixed gas emissivity calculation model with defined parameters, based on actual combustion conditions. This improves the accuracy of gas radiation characteristic calculation during blending and provides reliable theoretical support for the optimized design, operating parameter control, and energy saving and carbon reduction of methanol-coal blending systems.

A method includes receiving two-dimensional images. The two-dimensional images are slices from three-dimensional electronic scans. The two-dimensional images are for a region of interest within a person's mouth. The method includes generating a benchmark database. The benchmark database includes views of different mouth areas, previous information from dentists relating to annotations on the views of the different mouth areas, bilateral mandible electronic images; and unilateral mandible electronic images. The method includes determining a mandibular canal area with the person's mouth.

The application discloses a kind of state identification and monitoring methods of beating-up mechanism of polyester cotton loom, to solve the problems such as poor adaptability of existing scheme, high false alarm and missed judgment rate, fuzzy fault positioning etc.The method comprises: deploying customized sensor array, synchronously collecting beating-up mechanism operation signal and polyester cotton process parameters, and constructing exclusive reference database containing hierarchical sub-reference model;Using hierarchical filtering and load feature mask technology, extract fault features and distinguish process fluctuations and mechanism failure;Based on the coupling motion law, a dynamically corrected fault location correlation matrix is constructed to accurately locate the faulty components and classify the fault level;Combined with process parameters and production batch, predict the maintenance cycle and dynamically update the reference database.The application adapts to the characteristics of polyester cotton blending process, can accurately identify early faults, reduce the false alarm and missed judgment rate, shorten the repair time, adapt to differentiated production needs, improve production stability and reduce operation and maintenance costs.

This invention relates to the field of product traceability technology, specifically to a full lifecycle traceability method and system for intelligent supply chains. It addresses the technical problem of poor model generalization ability in the traceability process due to data gaps and the reliance on high-quality labeled data and high computing power costs of existing artificial intelligence models. The method includes: constructing a standardized traceability benchmark database with a globally unique identifier as the primary key; analyzing the business correlation strength between each link and the target batch, as well as the business causal relationships between different links, to determine the imputation value of missing data and the reliability of the imputation value; automatically labeling the imputation value and determining the false noise index based on the reliability and the original labeled data; filtering the imputation value based on the false noise index; and merging the filtered imputation value, labeled data, and original data to construct a closed-loop traceability link for the entire lifecycle with a globally unique identifier as the main thread.

The application discloses a BSD camera-based speed-limiting area self-adaptive adjustment method and device and electronic equipment, and particularly relates to the active safety field of engineering vehicles, and comprises the following steps: acquiring a vehicle driving track and judging a driving state; demarcating an initial speed-limiting area and an initial braking area according to the driving track; collecting multi-source parameters such as a vehicle real-time load, a road surface type and a driving speed; dynamically adjusting area parameters based on the multi-source parameters and a five-dimensional benchmark database to determine a final area; identifying an obstacle position through a BSD camera; and executing hierarchical early warning and braking according to the position relationship between the obstacle and the final area. The device comprises a driving track acquisition unit, a driving state judgment unit and the like, and the electronic equipment executes the above method through a processor. The application realizes self-adaptive adjustment of the speed-limiting area working condition, improves the braking distance calculation precision and the safety protection reliability, and can accurately adapt to complex working conditions such as heavy load, slope and turning.

The application relates to the technical field of bolt monitoring, and discloses a bolt health state monitoring system and method based on historical data comparison, which comprises a parameter acquisition module, a parameter processing module, an index generation module and a state monitoring module. The parameter acquisition module is used for acquiring multi-dimensional historical sensing parameters and real-time sensing parameters of a bolt to be monitored in a service cycle. The parameter processing module is used for performing time sequence segmentation and modal decomposition processing on the historical sensing parameters, and constructing a health benchmark database representing normal behavior characteristics of the bolt to be monitored. The index generation module is used for performing measurement analysis on the real-time sensing parameters and the health benchmark database, and generating multi-scale deviation quantitative indexes. The state monitoring module is used for determining the classification level of the current health state of the bolt according to the mapping position of the multi-scale deviation quantitative indexes in the health degree evaluation space, and fusing historical data mining and dynamic trend analysis to avoid simple threshold judgment in the prior art and ensure the accuracy of bolt health state monitoring.

The present application provides a kind of steelmaking cost calculation method, device, equipment and storage medium, it is related to steelmaking technical field.The method comprises: obtaining iron consumption task quantity and the yield of at least one target steel grade;Match the iron consumption task quantity with the iron consumption task quantity gradient interval in the benchmark database, extract the steel material consumption standard value corresponding to the matched iron consumption task quantity gradient interval;Each target steel grade is matched with the steel grade in the benchmark database, to obtain the alloy material consumption standard value, slag consumption standard value and auxiliary material consumption standard value corresponding to each target steel grade;Steel material consumption standard value, alloy material consumption standard value, slag consumption standard value and auxiliary material consumption standard value are multiplied by the corresponding yield respectively and summed up, to obtain the steelmaking cost corresponding to the iron consumption task quantity and the yield of each target steel grade.The present application supports the yield structure of multiple steel grades, can flexibly handle the cost accounting under different iron consumption task quantity, improves the efficiency of steelmaking cost prediction and plan formulation.

The application discloses a multi-dimensional intelligent verification method for building material goods signing and receiving; a "cloud-edge-end" cooperation and "sensing-calculation-storage" integrated architecture is constructed, taking material unique identity coding as the core, a multi-source heterogeneous data cross verification and block chain credible evidence storage mechanism is established, and through six steps, full-process intelligent verification is realized: building an encryption benchmark database, dynamic code assignment of a delivery unit is chained, multi-level identity authentication is started for verification, four-dimensional data acquisition is performed, cloud edge cooperation comparison is performed, and four-party signature reports are chained and stored; the multi-dimensional intelligent verification method for building material goods signing and receiving reduces the quantity error rate to below 0.2%, the specification recognition accuracy rate reaches 99.5%, the bulk material verification efficiency is improved by more than 80%, the dispute rate is reduced by 95%, data islands are broken, the whole life cycle of the material is tracked, the supply chain is digitally upgraded, and the method has remarkable technical innovation and economic benefits.

This invention discloses a furnace condition analysis method, terminal, medium, and product, relating to the field of blast furnace production technology. By collecting process parameters from the blower side, identifying and extracting hot blast stove changeover disturbance data, constructing a steady-state operation benchmark database for the blower, and comprehensively diagnosing real-time parameters based on multiple decision rules of an expert system, the blast furnace operation status can be inverted from the air supply side, providing real-time and accurate decision-making basis for blast operation, effectively improving the response speed and operational accuracy of abnormal furnace conditions, and reducing surge risk and the probability of unplanned shutdowns.

This invention relates to the field of fracture risk warning technology, specifically to a system and method for osteoporotic fracture risk warning based on bone mineral density analysis. The invention first acquires data from a benchmark database and current user data, and extracts the most matching benchmark template from the benchmark database; further, it acquires static and dynamic risk indices; further, it obtains the dynamic risk weight of each grid cell based on the duration and metabolic equivalent of different activities, and analyzes the distribution of duration proportions; finally, it merges the dynamic and static risk indices to obtain a comprehensive fracture risk index and provides risk warning. This invention, by integrating user-personalized skeletal models, static / dynamic biomechanical analysis, and daily behavioral data to construct a comprehensive fracture risk index, achieves a shift from single bone mineral density assessment to comprehensive and personalized accurate warning, effectively improving the comprehensiveness and accuracy of osteoporotic fracture risk assessment.

The present application relates to the technical field of transformer winding fault detection, and particularly relates to a preventive maintenance method and device for transformer winding faults. The method comprises: obtaining current signals and vibration acceleration signals in different directions of a three-phase winding of a transformer; obtaining an excitation-response spectrum matrix based on the current signals and the vibration acceleration signals, and constructing a health state vibration mode base; projecting the excitation-response spectrum matrix onto the health state vibration mode base to obtain a vibration mode contribution coefficient vector; constructing a frequency-mode correlation graph structure according to the similar situation of different frequencies in the health state vibration mode base at the initial stage of equipment operation; giving characteristics to the nodes of the graph structure to obtain a winding structure state characteristic vector, and establishing a reference database of each temperature interval; matching the winding structure state characteristic vector and the vibration mode contribution coefficient vector in the current period with the reference database to determine the fault cause. The present application improves the timeliness of transformer winding fault early warning.