42 results about "Status assessment" patented technology

This invention relates to a multi-dimensional dynamic assessment method and system for waterway operation status, belonging to the field of waterway transportation operation monitoring technology. This invention fuses processed data at the data layer, feature layer, and decision layer to form a deep coupling of multi-modal data; constructs a multi-dimensional waterway operation status assessment index system; utilizes this index system for real-time dynamic assessment of multi-dimensional waterway operation status; trains a deep learning model using historical multi-modal time-series data; and uses the deep learning model for time-series prediction and graded early warning of waterway operation status. Based on the assessment and early warning results, it outputs executable decision-making schemes. This invention constructs an integrated assessment system encompassing navigation environment, vessel flow, waterway siltation, structural health, hydrometeorology, and navigation safety dimensions, achieving a comprehensive depiction of waterway operation status. It employs a three-level fusion strategy to break down data silos from multiple sources, improving the accuracy and reliability of status assessment.

This invention provides a method for improving water conditions based on current status assessment and multi-objective synergy, relating to the field of water environment management technology. The invention comprehensively evaluates the current status of water areas to form an evaluation result table, identifies advantageous and disadvantageous indicators, determines the conflict relationships and optimization potential of engineering measures, constructs a mathematical response function between control indicators and engineering measures, establishes a multi-objective optimization model, and uses the NSGA-III algorithm to obtain the Pareto optimal solution set. Combined with multivariate criteria, it outputs optimized engineering combinations and expected results applicable to different management scenarios. This invention can transform static evaluation into dynamic decision support, improving the scientific rigor and accuracy of water management decisions.

This invention relates to the field of waste heat recovery technology in textile machinery, and more particularly to a multi-sensor fusion monitoring method and system for waste heat recovery systems in stenters. The method acquires data from multiple sensors and performs spatiotemporal alignment and fusion calculations to obtain a comprehensive system status assessment result. Based on this result, anomaly identification and multi-objective optimization are performed to generate a control execution scheme. After the scheme is executed, response data is collected to analyze control effect deviations, and relevant parameters are adaptively adjusted accordingly. This invention achieves precise monitoring and intelligent control of the waste heat recovery system status, improving system operational stability and energy efficiency.

This invention discloses a method and system for assessing the remaining lifespan of vehicles based on multi-dimensional dynamic fusion, belonging to the field of intelligent connected vehicle health assessment technology. The assessment method includes: collecting multi-source data, calculating five-dimensional lifespan sub-factors, dynamically configuring weights based on vehicle type, life cycle, and usage scenario, and weighted fusion to output a comprehensive remaining lifespan index for the vehicle. The assessment system includes a data acquisition and processing layer, a multi-dimensional factor fusion and assessment layer, and an application interface layer. The multi-dimensional factor fusion and assessment layer includes a multi-dimensional health factor extraction module, a dynamic factor weight adjustment and fusion module, and a status assessment and remaining lifespan prediction module. This invention is based on a lifespan factor quantification system encompassing five dimensions: time, health, usage, environment, and value. It adaptively adjusts weights according to vehicle type, life cycle, and usage scenario to achieve a comprehensive and accurate assessment of the vehicle's remaining lifespan, improving the prediction accuracy of the vehicle's remaining lifespan.

This application provides a method and system for intelligent assessment of safety early warning for power distribution equipment, relating to the field of equipment safety early warning. It addresses the technical problem in existing technologies where the lack of systematic analysis of inter-equipment relationships in power distribution equipment safety assessments leads to weak forward-looking capabilities. The method includes: creating a digital twin for each power distribution device and constructing a dynamic causal graph based on the digital twin; each digital twin performing a status assessment based on operational status data and generating a status score; when the status score exceeds a first threshold, performing risk propagation deduction based on the dynamic causal graph and outputting a risk propagation path; and triggering a tiered early warning based on the risk propagation path. This application is used in the safety assessment and early warning process for power distribution equipment.

This invention discloses a health status prediction system and method for electric shovel equipment based on edge-cloud collaboration and digital twins, belonging to the field of electric shovel equipment status prediction technology. The system includes an electric shovel equipment health status management system based on edge-cloud collaboration and an electric shovel digital twin model. It collects multi-dimensional status data of the electric shovel through multiple sensors, and achieves layered transmission and edge-cloud collaborative processing via NB-IoT, edge devices, and 5G base stations. A high-fidelity electric shovel digital twin model is constructed to achieve synchronous mapping between the physical entity and the virtual model. The method utilizes grey relational analysis to calculate the correlation between real-time status data and offline fault samples, accurately assessing the equipment's health status, and outputs predictive maintenance processes through edge-cloud collaboration, synchronously updating the cloud database. This invention achieves closed-loop management of electric shovel equipment from data acquisition, twin modeling, fault diagnosis to predictive maintenance, significantly improving the accuracy of status assessment and the efficiency of operation and maintenance collaboration.

Embodiments of the present disclosure provide a health status assessment method for a bearing. The method includes receiving multi-modal data with respect to the bearing and prompt information related to the content of the health assessment of the bearing. The method includes performing feature extraction on the multi-modal data using a first group of agents to generate a set of features regarding the multi-modal data. The method includes performing a health assessment of the bearing based on the set of features regarding the multi-modal data and the prompt information using a second group of agents to generate a plurality of health assessment results regarding the bearing. The method includes processing the plurality of health assessments using a third group of agents to generate a health assessment report regarding the bearing.

This invention discloses a virtual power plant trading method based on a transportation-energy integration scenario, belonging to the field of virtual power plant trading technology. It includes the following steps: (1) transportation-energy data fusion collection and preprocessing; (2) hierarchical resource aggregation and status assessment; (3) dynamic trading demand prediction and matching; (4) blockchain trusted execution and feedback optimization; and (5) collaborative management of the entire battery lifecycle. This invention enables efficient collaborative trading of transportation and energy resources, significantly improving resource collaboration efficiency. Simultaneously, the trading response speed meets the grid's needs, and a trusted and secure trading system is constructed, maximizing battery value utilization and yielding significant economic and environmental benefits.

This invention relates to a method for assessing the aging condition of transformers based on the analysis of sludge / trace main metal content in the bottom heavy oil. The method includes the following steps: collecting bottom heavy oil samples from transformers with different aging degrees; detecting the proportion of sludge in the bottom heavy oil samples to obtain the correlation between the proportion of sludge in the bottom heavy oil and the aging degree of the transformer; collecting bottom heavy oil samples from transformers whose aging degree is to be assessed; detecting the proportion of sludge in the bottom heavy oil samples; comparing the obtained detection results with the correlation between the proportion of sludge in the bottom heavy oil and the aging degree of the transformer to obtain the aging degree of the transformer to be assessed. The equipment and method involved in this invention are simple and facilitate efficient assessment of the aging condition of transformers.

This application relates to the field of AI data monitoring technology, and provides a health management status assessment method and AI server based on AI intelligent monitoring data. The method performs successive heartbeat waveform structure segmentation on the time series of photoplethysmography (PPG) signals to obtain a heartbeat waveform unit sequence, and performs successive respiratory waveform structure segmentation on the time series of chest impedance respiratory signals to obtain a respiratory waveform unit sequence. Based on the heartbeat waveform units, the method constructs the evolution trajectory of heartbeat waveform morphology features, and based on the respiratory waveform units, the method constructs the evolution trajectory of respiratory waveform morphology features. The method performs synchronous correlation and alignment processing on the time axis of the heartbeat and respiratory waveform morphology feature evolution trajectories to generate a joint state feature evolution path representing the coupling relationship of the cardiopulmonary system, and inputs it into a pre-trained health status assessment network for dynamic pattern encoding and mapping processing, and outputs a comprehensive assessment result of the cardiopulmonary function coupled health status.

This invention discloses a method and system for analyzing the status of aggregated equipment in a virtual power plant based on the Internet of Things (IoT). The method includes: prioritizing potential maintenance needs, integrating inter-equipment correlation data from synergy effect analysis, performing secondary calibration to assess the impact of multi-equipment collaborative operation, and determining the final scheme for predicting maintenance needs; generating a dynamic adjustment strategy based on the final scheme for predicting maintenance needs, combined with real-time feedback data from operational environment adaptation, to guide continuous monitoring of equipment status and obtain optimized operation scheduling instructions; and iteratively optimizing the health status assessment model using an automated update mechanism based on the optimized operation scheduling instructions and real-time changes in equipment operation data to determine the latest configuration of model parameters.

This invention discloses a method and system for load status assessment and early warning of a factory construction machine based on digital twins, belonging to the field of intelligent construction technology. The method includes the following steps: constructing a digital twin model of the factory construction machine; collecting multi-source sensor data of the physical entity and driving the twin to update synchronously; performing adaptive fusion of the data based on confidence level to generate a comprehensive load status vector; calculating a comprehensive load status assessment index based on the vector; generating real-time thresholds through a dynamic early warning threshold model to achieve graded early warning; predicting the remaining service life of key components by combining historical data; and finally displaying the early warning and prediction results through a visual interface. This invention achieves real-time comprehensive assessment of load status, adaptive early warning, and service life prediction, significantly improving the safety and intelligent operation and maintenance level of the factory construction machine.

This invention relates to a large language model-based automatic battery health status assessment system and method. The system includes: a program knowledge base for storing State of Health (SOH) estimation algorithms; a data processing module for acquiring battery data, preprocessing it, and extracting features highly sensitive to SOH changes to form a feature set; a large language model module for receiving dynamic prompts, retrieving corresponding code segments from the program knowledge base based on the prompts, and generating a new SOH estimation algorithm using the large language model or modifying a parent SOH estimation algorithm in the program knowledge base; an evaluation sandbox for receiving the feature set and calling the new or modified parent SOH estimation algorithm for SOH estimation and evaluation; and an evolutionary controller module for controlling the evolutionary cycle of the SOH estimation algorithm and generating dynamic prompts. Compared with existing technologies, this invention has advantages such as automatic algorithm iteration.

This invention relates to the field of status assessment technology for winding and packaging equipment, and particularly to a method, device, electronic device, and storage medium for intelligent decision-making regarding the status of winding and splicing equipment. The method includes the following steps: real-time data collection from multiple winding and splicing machines in a winding and packaging workshop; preprocessing of the collected real-time data based on specific data processing rules; constructing a scoring calculation model for the winding and splicing equipment, inputting the preprocessed production data into the model, and outputting a score for each machine; determining the lowest-scoring machine based on its score, analyzing the reasons for its low score, and generating a diagnostic analysis report and visualization charts corresponding to the score; and identifying and adjusting the weaknesses in the lowest-scoring machine based on the diagnostic analysis report and visualization charts. This addresses the problem that existing evaluation methods for winding and splicing equipment, due to the reliance on a single evaluation indicator, cannot accurately assess the overall status of the equipment and fail to identify potential problems by not conducting deeper analysis of the equipment's indicator data.

This invention relates to the field of anatomical specimen preservation technology, and more particularly to a method for the long-term preservation of anatomical visceral specimens. The method includes: collecting environmental parameters, visual images, and attribute data of the specimens; generating a monitoring data set after standardization processing; constructing and updating an individual characteristic profile of the specimen based on this data set; performing a fusion analysis on the data set by combining pre-set weights corresponding to organ type and preservation method to generate a comprehensive status assessment result; inputting the data set and assessment result into a pre-constructed hybrid prediction model to output a future status prediction report with confidence scores; inputting the assessment result and prediction report into a pre-constructed hierarchical decision engine to generate personalized preservation and maintenance instructions; and finally, based on these instructions, performing adaptive regulation or triggering early warnings for the specimen preservation environment. This invention achieves individualized and precise assessment and proactive maintenance of specimen status, improving the stability and intelligence level of long-term preservation.

The invention relates to the technical field of digital data processing, and particularly discloses an urban and rural digital fusion co-rich support system based on circulation network reconstruction, which comprises a digital twin mapping module, a network toughness evaluation module, a dynamic reconstruction decision module and a collaborative execution engine. Real-time mapping and state evaluation are performed by constructing a circulation network digital twinborn body, a network reconstruction scheme is generated based on multi-objective optimization, cross-system resource cooperative execution and closed-loop feedback are driven, self-adaptive and flexible intelligent reconstruction of an urban and rural circulation network along with environment change is realized, and the network reconstruction efficiency is improved. And the overall network toughness, the circulation efficiency and the balance of the co-richness target are improved.

This invention relates to the field of construction status assessment technology, specifically a method and system for fusion of compaction data and analysis of compaction quality. This invention accurately captures the soil impact response at the moment of maximum excitation energy by monitoring the rotation phase of the vibrating wheel. It utilizes a time-adaptive weighted information entropy calculation method to deeply analyze the micro-fluctuation patterns of the acceleration sequence, quantitatively assessing the orderliness and stability of soil particle arrangement. This allows for the precise elimination of unstable areas in a falsely solidified or loose state. Simultaneously, it combines historical rebound data with second-order difference operations to construct a compaction growth acceleration sequence, keenly capturing polarity reversals or abrupt changes in soil strength growth trends. It provides real-time warnings of the risk of shear failure induced by excessive compaction, achieving a leap from a single strength index to a multi-dimensional coupled analysis of structural stability and evolution trends. This ensures accurate identification of the true and false compaction quality under various geological conditions, effectively avoiding potential structural hazards and improving the level of refined management in dam filling operations.

This invention belongs to the field of intelligent status assessment technology for generator sets, and discloses a method and system for intelligent status assessment of natural gas generator sets. The method includes: acquiring multi-physics field operation data; reconstructing the phase space of the multi-physics field operation data based on different time scales to obtain a set of physically perceived state point clouds; performing complex filtering on the point clouds at each time scale, and conducting multi-scale topological evolution analysis of the filtered complex sequences; inputting the topological feature vectors into a topological random forest model for training, and performing joint inference to output the posterior distribution of fault modes; calculating a generator set health index, and combining the generator set health index with a dynamic early warning threshold to achieve the assessment of the operating status of the natural gas generator set. This invention can deeply explore the dynamic evolution laws of different physical processes such as combustion, mechanical, thermal, and degradation, and effectively capture early weak faults and multi-field coupling anomalies that are difficult to identify using traditional methods.

The invention discloses an unmanned aerial vehicle operation state multi-threshold evaluation method and system based on uncertainty quantization, and relates to the field of aircraft state evaluation. The problems that in an existing method, the evaluation capability of a key parameter prediction model reflecting the operation state of the unmanned aerial vehicle is insufficient, and evaluation result information given by a single-threshold abnormal state evaluation method is limited are solved. The method comprises the following steps: inserting a Dropout network layer in a prediction regression model, and obtaining a Monte Carlo Dropout prediction model; obtaining an uncertainty estimation result according to a prediction model of Monte Carlo Dropout; calculating an operation state evaluation quantitative score according to the uncertainty estimation result and the unmanned aerial vehicle operation state deviation degree; determining a multi-stage operation state evaluation threshold according to the operation state evaluation quantitative score; and evaluating the operation state of the unmanned aerial vehicle according to the multi-stage operation state evaluation threshold. The method is applied to the unmanned aerial vehicle flight field.

This invention provides an organizational situation assessment system, an organizational situation assessment device, an organizational situation assessment method, and a program to implement these, which enable easy and effortless assessment of an organization's opinions and circumstances. [Solution] An organizational situation assessment system 1 for compiling individual opinions within an organization to create an organizational opinion and understand the organization's situation, comprising: an individual storage means 20 that extracts the words and actions and / or information of each individual from a specific recording means 100 and stores them in advance for each individual; a question means 30 that, when a predetermined question is created, asks the individual storage means 20 the question; an individual opinion extraction means 40 that, when a question is asked from the question means 30, extracts the wording that will be the answer to the question from the individual storage means 20 to create an individual opinion; and an aggregation means 50 that combines the individual opinions created by the individual opinion extraction means 40 to create an organizational opinion.

This invention discloses a method and device for monitoring the status of queen bees. The method includes: acquiring real-time data using an RFID tag attached to the queen bee and sensors attached to the beehive; extracting individual queen bee movement characteristics, bee colony behavior characteristics, and environmental auxiliary characteristics; aligning and stitching these characteristics to generate a real-time multidimensional feature vector; inputting the queen bee spatial trajectory time-series data, bee colony inflow and outflow time-series data, beehive internal environmental information, and the real-time multidimensional feature vector into a pre-trained queen bee status assessment model, and outputting the queen bee status assessment result; and issuing a dynamic early warning based on the queen bee status assessment result, real-time data, and real-time multidimensional feature vector. This invention provides a continuous, objective, and multi-dimensional information-integrated queen bee status monitoring solution, improving accuracy and efficiency, avoiding interference with the bee colony, and achieving dynamic early warning of the queen bee status in multi-comb beehives.

This makes it possible to assess health status based on the proportion of beneficial Bifidobacteria in the gut microbiota. [Solution] A health status evaluation system for evaluating the health status of a user, comprising: an inspection management unit that acquires and records the results of tests related to the user's intestinal microbiota; an questionnaire management unit that presents a questionnaire related to the user's health status to the user, acquires and records the responses; and an analysis processing unit that evaluates the user's health status based on the occupancy rate of bifidobacteria in the intestinal microbiota in the test results and the responses to the questionnaire.

This invention discloses a method and system for optimizing ship cabin environments based on crew status. The method includes: real-time collection of crew activity data, physiological data, and environmental data through a multi-source sensor network; construction of an environmental status assessment index system based on an improved AHP-entropy weight method and calculation of weights; obtaining status levels using a grey-fuzzy comprehensive evaluation method; optimization based on deep reinforcement learning using a multi-agent simulation model to generate cabin equipment layout and environmental control schemes; and visualization of environmental status distribution and provision of decision support through a digital twin platform. This invention can improve the accuracy and real-time performance of environmental status assessment, optimize space utilization efficiency, enhance the scientific and dynamic nature of cabin environment management, and effectively solve problems such as incomplete data, inaccurate evaluation, and delayed optimization in existing technologies.

A controller for an ultrasonic handpiece having a load in the form of at least one piezo-driven crystal includes a processor and a computer-readable memory having a computer-readable instruction set recorded thereon. Execution of the instruction set during real-time operation of the handpiece causes the processor to execute an associated method during which the processor calculates a load capacitance of the load and a dissipation factor of the load capacitance. The processor also records the load capacitance and the dissipation factor in memory as a recorded capacitance history over time. The processor then performs a control action of the handpiece using the recorded capacitance history and possibly one or more additional recorded electrical parameters (such as estimated resistance, estimated inductance, and / or measured temperature) or a correlation of measured temperature to resonant frequency over time.

This invention discloses a multi-dimensional health status assessment method for equipment based on bulldozer distance measurement, which uses monitoring parameters (also known as monitoring data) that characterize the equipment's performance status as input. The method includes: first, preprocessing the full-lifecycle data and real-time data to improve data usability; then, performing a weighted average of degradation-sensitive parameters with the same direction of inversion, determining a standard health set using the health status sample sets of the full-lifecycle data and real-time data, and determining a standard fault set using the fault status sample set of historical data; then, calculating the bulldozer distance through a time-series sliding window to obtain a performance degradation sample set; and finally, linearly generating the equipment health status set.

This invention relates to the field of metal processing technology and provides a centrifugal casting process for gaming chairs, comprising the following steps: Step S1, Process status assessment: collecting centrifugal rotation speed, casting temperature, filling time, and mold heating temperature to construct a process status assessment model and output a process stability index; Step S2, Material-equipment status assessment: collecting melt density equivalent, mold vibration amplitude, and mold center eccentricity relative to the main rotation axis to construct a material-equipment status assessment model and output a material consistency index; This invention, through the systematic integration of process status assessment, material-equipment status assessment, online molding quality assessment, and parameter closed-loop control, constructs a multi-source information fusion and intelligent decision-making framework covering the entire centrifugal casting process. This framework effectively solves the systemic defects in existing technologies, such as the difficulty in decoupling nonlinear coupling of process parameters, delayed quality feedback, and lack of scientific basis for control.

This invention discloses a method and system for assessing the health status of packaging machinery based on multi-source data fusion, belonging to the field of multi-source data fusion technology. It includes locating the root cause of faults based on the feature vectors obtained from the decomposition of the principal eigenvalues, thus identifying the main assessment dimensions leading to a decline in the overall health index. This invention achieves precise location of the root cause of faults by analyzing the assessment dimensions mapped to the component with the largest absolute value in the feature vector corresponding to the principal eigenvalue. This process, based on multivariate statistical principles, effectively isolates the coupling correlation between data from different dimensions, avoiding the misjudgments and omissions caused by the reliance on the experience of maintenance personnel in traditional technologies. When the overall health index of the equipment declines, it can quickly pinpoint whether the problem originates from electrical, mechanical, process, or environmental dimensions, significantly shortening fault diagnosis time, improving maintenance response efficiency, and providing a clear direction for targeted equipment repair.

This invention discloses a method for detecting homologous recombination defects (HRDs) based on whole-genome sequencing, belonging to the field of gene detection technology. It includes the following steps: analyzing and comparing the sequencing data of the test sample aligned to a reference genome, performing data sorting and deduplication, and then assessing the HRD status. The HRD status assessment includes: importing the deduplicated data file into HRD status scoring software, setting the configure file to diploid parameters, and scoring the HRD status. This method has the technical advantages of low experimental complexity and low sample requirements, and maintains the same level of accuracy as similar products while requiring low sequencing volume (average sequencing depth ≤ 2×), significantly reducing detection costs by approximately one order of magnitude.

A specimen condition assessing device includes a processor that executes a program for performing image processing on an image of a target specimen container and a memory for storing a result of the image processing. The processor performs processing of inputting the image, processing of detecting a boundary position from the image, processing of determining a type of upper and lower regions of each boundary position and determining a boundary position of each inclusion, and processing of assessing whether or not the target specimen container is testable on the basis of the boundary position of each inclusion.

The invention discloses a display equipment use state supervision system and method based on big data analysis, and relates to the technical field of equipment state supervision. Comprising the following steps of collecting multiple items of data information at the awakening moment of display equipment, generating a conversion state index according to line supply information and network fluctuation information in the multiple items of data information, comparing the generated conversion state index with a set state evaluation threshold value, evaluating the state of a production environment, and outputting the evaluation result. According to the method, the influence condition of display equipment awakening on the production environment state is determined, then equipment feedback information generated by the display equipment after the production environment state is determined is collected, an equipment evaluation index is generated according to operation duration information and imaging quality information in the equipment feedback information, and different control signals are generated through comparison; and early warning supervision is carried out on the display equipment according to the generated control signal, so that the problem that the fault of the display equipment cannot be processed in time subsequently is solved, and the overall use efficiency of the display equipment is improved.