26 results about "Operational performance" patented technology

This invention belongs to the field of elevator technology, specifically relating to a method, equipment, and medium for elevator fault injection based on multiphysics operating mechanisms. It establishes digital models of the main elevator platform system and the isolation door system and defines interfaces. The method includes configuring a data acquisition and control module; initializing the multiphysics parameter set; determining the fault injection point; sending a fault excitation signal to drive co-simulation; collecting state response data; evaluating the fault impact; and generating a report. This method, based on multiphysics coupling mechanisms, achieves accurate simulation of the fault evolution process, quantifies the impact of faults on elevator performance, and accurately locates fault propagation paths. Accurate modeling based on multiphysics mechanisms covers fault injection in core components, and co-simulation realistically reflects fault evolution. It quantitatively assesses the impact of faults on operational performance, clarifies propagation paths, and provides data support for elevator fault diagnosis, preventative maintenance, and control system optimization, thereby improving operational safety and reliability.

A method includes generating a trading performance model for a trading activity involving a set of decisions by a set of expert traders. The trading performance model includes a set of input data sets, a set of data processing workflows operating on the input data sets, and a set of trading decision outputs resulting from interaction of the expert traders with a user interface representing the trading performance model. The method includes generating a brain state model representing a sequential set of brain states of the set of expert traders that characterize brain states measured during the interactions of the expert traders with the user interface representing the trading performance model, assessing the quality of the trading decisions, determining a preferred pattern of trader brain state sequences, and modifying a subsequent trading activity.

An AI-driven blockchain protocol provides systems / methods for managing tokenized assets via autonomous operational Risk-Aware Agents (RAAs). Distinct from prior art automating simple events, the protocol actively coordinates, incentivizes, and manages the RAAs' on-chain lifecycle and operational / financial performance metrics using an Agent Coordination Contract / Module. Verifiable on-chain incentives link RAA operational performance, tracked by said metrics, to risk / return outcomes, thereby underwriting operational execution. An AI engine analyzes aggregated data including RAA metrics, recommending adjustments to RAA incentives and / or metric targets managed by the protocol. RAAs execute operations driven by these incentives, using a protocol-native stablecoin for reward / penalty settlement. A continuous feedback loop enables optimization. This verifiable autonomous operational management provides a foundation for stablecoin-based leverage against the assets, addressing illiquidity. The system comprises interconnected contracts, processor, engine, and RAAs under protocol governance.

This invention discloses a method for fault prediction and resource pre-allocation optimization in disaster recovery systems, relating to the field of disaster recovery systems. The method includes: real-time collection of operational performance data, historical fault sequences, and related business pressure indicators of primary and backup nodes in the disaster recovery system; simultaneously, collection of operation response logs and operation completion quality data from relevant operations and maintenance teams during historical disaster recovery switchover processes. By introducing an advanced prediction and flexible pre-allocation mechanism at the nascent stage of performance degradation, this invention can initiate precise resource preparation earlier than traditional fault thresholds, effectively extending the system intervention window and alleviating the pressure of insufficient switchover preparation time. Through a resource pre-collateralization mechanism, it dynamically allocates idle resources, significantly improving the overall resource pool utilization efficiency while ensuring the reliability of high-priority services, thus resolving the contradiction between resource idleness and temporary shortages.

Methods and systems for driving and evaluating operational performance for an organization, and an accompanying auditing system for creating audits, presenting the audits to auditor users, capturing data via a user interface, compiling results from captured data, and presenting the results, is disclosed.

This invention provides an elevator operation monitoring device and an elevator maintenance support method that can more reliably ensure the appropriate timing of maintenance and inspection work for elevators. [Solution] The operation information acquired by the operation monitoring device 61 from the elevator 2 includes cumulative values ​​accumulated during normal operation for one or more monitoring items related to the operation of the car 21 as operational performance values. When the operational performance value for at least one of the monitoring items exceeds a set threshold, the operation monitoring device 61 identifies the elevator 2 in which the operational performance value exceeds the set threshold as an elevator recommended for maintenance. When the operation monitoring device 61 identifies the elevator 2 as an elevator recommended for maintenance, it produces maintenance support information regarding the implementation of maintenance and inspection work for the elevator recommended for maintenance. The notification unit 62 notifies the maintenance support information in the control room 5 of the building 3 where the elevator 2 is installed.

This invention provides a control method for a thermal storage enclosure structure and the thermal storage enclosure structure itself. The control method first obtains initial control weight curves for multiple control objectives of the thermal storage enclosure structure. Then, according to a preset adjustment step size, the initial control weight curves are gradually corrected based on the operational performance of the thermal storage enclosure structure, resulting in corrected weight curves for the multiple control objectives. Next, based on the real-time operating state parameters of the thermal storage enclosure structure and a predictive model, the operational optimization function of the thermal storage enclosure structure is solved to obtain the control quantity of the thermal storage enclosure structure. Finally, the thermal storage enclosure structure is controlled to execute control actions corresponding to the control quantity. This control method for the thermal storage enclosure structure, through multi-objective weight adaptive correction and model predictive optimization, can closely meet the actual user needs, accurately and stably maintain indoor comfort, minimize room temperature fluctuations, provide more timely responses, and consistently remain within the comfortable range.

This invention discloses a method and system for generating and optimizing warehouse layouts in an automated warehousing system. The method includes: discretizing the warehouse space into a two-dimensional mesh diagram and defining a type for each mesh cell; generating an initial layout based on preset parameters, and storing it in an elite solution library based on a multi-dimensional feature space using the MAP-Elites algorithm after initial repair; selecting layouts from the elite solution library for mutation operations to generate candidate layouts under MAP-Elites driving; using a MILP model to perform constraint repair on the candidate layouts with the goal of minimizing the amount of modification; importing the repaired layouts into the MAPF simulation environment for performance evaluation, and updating the elite solution library based on the evaluation results. This invention constructs a complete closed loop for automated layout generation and optimization, capable of outputting multiple layout schemes with high throughput performance while meeting actual engineering constraints, significantly improving the design efficiency, operational performance, and scenario adaptability of the warehousing system.

A system, method, and computer program product for implementing deep learning software model modification is provided. The method includes monitoring operational performance of a software model. An expected confidence level associated with the operational performance is first determined and it is determined that an inference associated with the expected confidence level is below a selected range of inferences associated with assigning new feature data as candidate video data. A candidate sequence comprising video data associated with the candidate video data is received and a similarity between frames of the candidate sequence is determined. A frame comprising a highest similarity with respect to segments of candidate video data is selected and it is detected that the frame is not associated with additional frames stored within a full cache structure. The software model is retrained such that the operational performance is modified.

A method, system, device, and medium for monitoring power transmission and distribution equipment are disclosed. The method includes: acquiring operational data, historical fault data, real-time environmental data, electrical topology data of the power transmission and distribution network, and environmental prediction data of the area where the power transmission and distribution network is located for each equipment node in the power transmission and distribution network; constructing a set of operational performance indicators for the equipment nodes based on the operational data and real-time environmental data; calculating the fault probability of each equipment node based on the set of operational performance indicators and historical fault data; determining the fault impact level of each equipment node based on the electrical topology data; calculating a comprehensive risk index for each equipment node, and identifying equipment nodes in the power transmission and distribution network whose comprehensive risk index is greater than a preset risk threshold as target equipment nodes; and performing spatiotemporal extrapolation of the risk evolution process of the target equipment nodes based on environmental prediction data to generate a risk evolution extrapolation diagram. This application can improve the monitoring reliability of power transmission and distribution equipment.

The invention relates to a system and method for predicting manufacturing process risk. The present disclosure provides systems, methods, and computer program products for predicting and detecting anomalies in subsystems of a system. An example method may include (a) determining a first plurality of tags indicating operational performance of a subsystem. The tag may be obtained from (i) a plurality of sensors in the subsystem and (ii) a plurality of sensors in the system that are not located in the subsystem. The method may also include (b) processing the measurements of the first plurality of tags using an auto-encoder trained according to historical values of the first plurality of tags to generate estimates of the first plurality of tags; (c) determining whether a difference between the measured value and the estimated value satisfies a threshold; and (d) if the difference satisfies a threshold, transmitting an alert indicating that the subsystem is expected to experience an anomaly.

This invention relates to the field of hydraulic engineering technology and provides a long-term perception method for the operational performance of dams based on deformation-stress mapping analysis. The method includes: acquiring target environmental data of the dam in real-time monitoring; inputting the target environmental data into a deep learning model to obtain the three-dimensional stress field of the dam output by the deep learning model; the deep learning model serves as a student model, trained through knowledge transfer from a teacher model based on target environmental data samples and their corresponding three-dimensional stress field labels; the teacher model includes a first mapping model, a second mapping model, a third mapping model, and a fourth mapping model. This invention trains the deep learning model (serving as a student model) using a teacher model comprising four mapping models, enabling the deep learning model to not only accurately characterize the relationship between deformation and stress but also capture the nonlinear correlation between target environmental data, deformation, and the three-dimensional stress field, achieving online and accurate long-term perception of dam stress.

Disclosed in the embodiments of the present disclosure are a communication method and apparatus. The method may comprise: a first device sending a first command, wherein the first command is used for instructing a second device to enter a target state and / or indicating a first duration, which first duration may be a duration in the target state, and both the first device and the second device are devices in an Internet of Things (IoT) scenario. By means of implementing the embodiments of the present disclosure, the problem of how to instruct an IoT device to enter a specific power state in an IoT scenario can be solved, such that the power consumption of the device can be significantly reduced, the service life of the device can be prolonged, the availability of the device can be maintained, and the operational performance of the device can be improved.

The present disclosure provides system, methods, and computer program products for predicting and detecting anomalies in a subsystem of a system. An example method may comprise (a) determining a first plurality of tags that are indicative of an operational performance of the subsystem. The tags can be obtained from (i) a plurality of sensors in the subsystem and (ii) a plurality of sensors in the system that are not in the subsystem. The method may further comprise (b) processing measured values of the first plurality of tags using an autoencoder trained on historical values of the first plurality of tags to generate estimated values of the first plurality of tags; (c) determining whether a difference between the measured values and estimated values meets a threshold; and (d) transmitting an alert that indicates that the subsystem is predicted to experience an anomaly if the difference meets the threshold.

A method and system generate a building operational performance analysis output. A synthetic data set is generated and includes a set of 3D building conceptual mass geometries. The generating includes identifying geometry types, dividing the geometry types into categories, and algorithmically generating the mass geometries using a separate workflow for each category using generative design. Analytical models associated with each of the mass geometries are generated. Simulation results are generated for each of the analytical models. A surrogate model is trained based on a set of features extracted from the simulation results using machine learning (ML). The ML iteratively determines the set of features based on a measured accuracy of the surrogate model. Geometry input is received and processed through the surrogate model to generate the building operational performance analysis output which is then used to inform a designer of an approximate Energy Use Intensity of the geometry input.

This application provides a joint planning method for power systems, including establishing a shared energy storage joint planning model based on the power system's topology, and using a two-level optimization method to solve the shared energy storage joint planning model to obtain the energy storage system's operation plan. The optimization objective is to optimize the overall economic performance of the power system at the upper level, and the operational performance of the energy storage system in a typical scenario is used as the lower level optimization objective. The shared energy storage joint planning model uses a fuzzy chance-constrained programming method to describe the source-side model of wind turbine output, the load-side model describing the impact of price incentives on user demand load response, and the storage-side model considering the lifespan of the energy storage power station. This application considers the randomness and uncertainty of the power system's source-side and load-side operation, thereby achieving power system dispatch balance, improving energy utilization efficiency, and reducing overall system cost.

This invention relates to the field of hearing aids, specifically to a method and system for testing the operational performance of hearing aids. The system includes a processing module, a receiver module, a timed switching module, and a comparison module. The processing module comprises a processor module, a button module, a power supply module, a playback module, and a transmission module. By setting a timed self-test, the system collects sound from the inside of the device normally used for auxiliary receiver switching during the self-test. Then, the auxiliary receiver module collects the sound played by the playback module and compares it briefly with normal sounds in a normal sound database. If the playback is confirmed to be problem-free, it proves that neither the playback module nor the receiver module has a performance degradation issue. If the short comparison confirms a playback problem, a long-term comparison is performed, comparing the sound data played by the playback module with the sound data collected by the receiver module to determine whether either the playback module or the receiver module has a problem, or which module is malfunctioning.

The invention is suitable for the technical field of nuclear power human factor engineering, and provides an operation performance evaluation method, computer equipment and a computer program product, and the method comprises the steps: obtaining multi-dimensional data of a target operator in a process of achieving a task target in a target scene; generating an experimental sample set, and training the basic model based on the experimental sample set to obtain a target evaluation model; and inputting the multi-dimensional data into the target evaluation model to obtain a personnel performance score, wherein the personnel performance score represents the operation performance of the target operator for realizing the task target in the target scene. According to the method and the device, the operation performance of the task target under the target scene realized by the target operator in the digital main control room can be efficiently and accurately evaluated in real time.

This invention discloses an enterprise multi-business interconnection system for data processing, relating to the field of enterprise business process optimization technology. It includes a value stream definition module, a process analysis module, a requirement backpropagation module, a business interconnection module, a value stream processing module, and a value verification module. Based on enterprise business objectives, this invention determines the end-to-end business value stream and decomposes processes to identify business nodes, states, and collaborative relationships. Then, based on optimization objectives, it deduces the minimum necessary data interconnection scope. Subsequently, it implements data interaction between heterogeneous businesses according to this scope and integrates and processes multi-source data to construct a business interaction view, generating operational performance indicators. Finally, the value verification module quantifies and displays the optimization effect. This invention achieves value-driven interconnection and optimization, effectively improving the targeting and measurability of cross-system business operations.

This application discloses a method for predicting and analyzing the operational performance of metering equipment based on locally weighted partial least squares (LSS). The method includes: acquiring and preprocessing the historical operational dataset of the metering equipment to be predicted, dividing the dataset into training and testing sets; using the K-Means clustering algorithm to cluster the training set into several sub-training sets and calculating the centroid of each sub-training set; evaluating the prediction accuracy and performance of the model; acquiring operational data, combining the operational data with each sub-training set, using the locally weighted partial least squares modeling algorithm to build a sub-model for each sub-training set, and obtaining the predicted acquisition success rate value corresponding to the operational data under each sub-model; and calculating the final predicted acquisition success rate value corresponding to the operational data point by weighting the sub-model prediction values ​​based on the distance from the operational data point to the centroid of each sub-training set. This invention has high prediction accuracy and can be effectively applied to the prediction and analysis of the operational performance of metering equipment under climatic factors.

This invention relates to the field of automated dispensing equipment management technology, specifically to an automated dispensing management system and method based on artificial intelligence. Upon detecting a new fault report, the invention triggers an assessment of the dispensing control platform within the corresponding work evaluation period. It determines whether this is due to performance degradation. The analysis involves analyzing the continuous operational distribution of the dispensing robot within the evaluation period and the frequency distribution of challenging task change nodes. Ultimately, this allows for the evaluation of the dispensing control platform's operational performance index within the evaluation period. This invention effectively monitors and addresses aging or damage caused by prolonged operation of the dispensing control platform, promptly identifying and resolving performance degradation issues.

The invention discloses a high new energy proportion power grid intelligent regulation and control application method and system, and relates to the technical field of power grid intelligent regulation and control application, and the method comprises the steps: employing a new energy output ultra-short-term prediction method to carry out the evaluation of the new energy power generation capability, and obtaining the dynamic reserve capacity configuration; performing optimization scheduling on the dynamic reserve capacity by adopting a multi-time scale robust optimization scheduling method to obtain day-ahead and intra-day optimization scheduling plans; executing the day-ahead and intra-day optimization scheduling plans by adopting a data-physical fusion control method to obtain a control effect; performing verification and parameter adjustment on the control effect by adopting a virtual inertia dynamic distribution method, ensuring that the frequency deviation meets the requirement, and obtaining a verification result; a performance index verification method is adopted to analyze a verification result, and an operation performance evaluation report is generated; through accurate prediction of the prediction module, the system risk caused by uncertainty of new energy power generation is reduced, the stability and reliability of the power system are optimized, and the wind and light abandoning rate is reduced.

A thermal system includes a refrigerant loop operable between a cooling mode and a heat pump mode, a compressor, and a heat exchanger. A thermal control system includes a controller programmed to monitor one or more conditions of the refrigerant loop related to an operational performance of the heat exchanger; estimate, via a pre-calibrated model of the thermal system, an expected operational performance of the heat exchanger when ice is not present and during the monitored one or more conditions; determine an instantaneous operational performance of the heat exchanger based on the monitored one or more conditions; compare the instantaneous operational performance to the expected operational performance to determine a performance degradation of the heat exchanger; and initiate a deicing operation of the heat exchanger when the performance degradation exceeds a predetermined threshold.

This invention discloses a method, medium, and device for automatically linking and constructing relationships between enterprises and industrial chains. Based on relationship construction trigger events, it dynamically orchestrates and generates a hybrid reasoning execution graph for operational performance analysis from the enterprise performance management meta-strategy library. It schedules each performance management meta-strategy unit in parallel to execute enterprise performance relationship judgment tasks, outputting a local performance relationship judgment set with a performance judgment logic summary and performance management calibration factors. Through fusion and conflict resolution based on the performance judgment evidence weights, it generates a dynamic relationship sub-network of industrial chain performance and a performance relationship judgment interpretation library. It then performs time-series causal judgment analysis on the core relationship edges of the dynamic relationship sub-network of industrial chain performance, generating a set of performance causal quantitative edges and injecting them into the dynamic relationship sub-network of industrial chain performance to form an enterprise performance enhancement causal relationship sub-network. Finally, it generates an interpretable judgment report, realizing the dynamic on-demand construction and causal quantitative analysis of industrial chain relationships.

Techniques are described for automatically converting a standard operating procedure (SOP) into a simulatable non-ambiguous single state machine (SSM) architecture in which a given input (transition condition) necessarily and unambiguously moves the system from a first state to a predictable second state. By converting a written SOP into a simulatable non-ambiguous SSM architecture, the techniques described herein reduce the possibility of errors and improve the safety, efficiency, and operational performance of the system. The described techniques also allow the architecture, and indeed the entire system, to be simulated.

The objective is to provide an evaluation system, evaluation program, and evaluation method for selecting the optimal equipment using predicted air conditioning loads. [Solution] An evaluation system having a control unit for evaluating an air conditioning system, wherein the control unit acquires first operational performance information acquired during a first period of a predetermined period, spatial environment information indicating the environment of the space to be air-conditioned by the air conditioning system, and second operational performance information estimated based on estimation information for a second period of the predetermined period in which the first operational performance information has not been acquired, and derives evaluation information for the air conditioning system based on equipment configuration information relating to the equipment included in the air conditioning system and operational performance information for the predetermined period including the first operational performance information and the second operational performance information.