-
公开(公告)号：US20200227142A1
公开(公告)日：2020-07-16
申请号：US16739239
申请日：2020-01-10
Applicant: General Electric Company
Inventor： Jason NICHOLS , Johan Michael REIMANN , Nurali VIRANI , Naresh Sundaram IYER
Abstract: According to some embodiments, a system, method and non-transitory computer-readable medium are provided comprising a Hypothesis Generation Engine (HGE) to receive one or more property target values for a material; a memory for storing program instructions; an HGE processor, coupled to the memory, and in communication with the HGE, and operative to execute program instructions to: receive the one or more property target values for the material; analyze the one or more property target values as compared to one or more known values in a knowledge base; generate, based on the analysis, an initial set of hypothetical structures, wherein each hypothetical structure includes at least one property target value; execute a likelihood model for each candidate material to generate a likelihood probability for each hypothetical structure, wherein the likelihood probability is a measure of the likelihood that the hypothetical structure will have the target property value; convert each hypothetical structure into a natural language representation; execute an abduction kernel on the natural language representation with the at least one likelihood probability, to output at least one proposed structure that satisfies a likelihood threshold for having the property target value; and receive the output of the executed abduction kernel at a testing module to determine whether the output satisfies the property target values. Numerous other aspects are provided.
-
公开(公告)号：US20170372224A1
公开(公告)日：2017-12-28
申请号：US15195347
申请日：2016-06-28
Applicant: General Electric Company
Inventor： Johan Michael REIMANN
CPC classification number: G06N20/00
Abstract: A method for imputing multivariate-time series data in a predictive model includes performing historical training of the predictive model by accessing data element information obtained from a real world physical asset, the data element information representing operational characteristics or measurements of the real world physical asset, examining configuration details of the real world physical asset, evaluating an expressiveness of the predictive model by comparing the predicative model to the configuration details, developing the model to express the configuration details, training the developed model by running scenarios based on the data element information, comparing error metrics between a model prediction and a corresponding one of the data element information, deploying the model if the error metrics are within predetermined parameters, and retraining the model if the error metrics are outside the predetermined parameters. A non-transitory computer readable medium and a system for implementing the method are also disclosed.
-
公开(公告)号：US20240419154A1
公开(公告)日：2024-12-19
申请号：US18336491
申请日：2023-06-16
Applicant: GENERAL ELECTRIC COMPANY
Inventor： Masoud ABBASZADEH , Johan Michael REIMANN , Hema K ACHANTA
IPC: G05B19/418
Abstract: In some embodiments, a system node data store may contain historical system node data associated with normal operation of an industrial asset, and a plurality of artificial intelligence model construction platforms may receive historical system node data. Each platform may then automatically construct a data-driven, dynamic artificial intelligence model associated with the industrial asset based on received system node data. The plurality of artificial intelligence models are interconnected and simultaneously trained to create a digital twin of the industrial asset. A synthetic disturbance platform may inject at least one synthetic disturbance into the plurality of artificial intelligence models to create, for each of a plurality of monitoring nodes, a series of synthetic disturbance monitoring node values over time that represent simulated abnormal operation of the industrial asset.
-
公开(公告)号：US20170175567A1
公开(公告)日：2017-06-22
申请号：US15380781
申请日：2016-12-15
Applicant: General Electric Company
Inventor： Atanu TALUKDAR , Venkatesh Kattigari MADYASTHA , Guruprasad SRINIVASAN , Kotesh Kummamuri RAO , Jose Leon VEGA , Jose MENDOZA , Hardev SINGH , Yan CHEN , Johan Michael REIMANN
Abstract: A controller includes a processor and memory. The memory stores instructions that, when executed, are configured to cause the processor to receive measurements pertaining to a measured operation parameter of at least a portion of a turbine system. The instructions are also configured to cause the processor to generate a customized model for the at least the portion of the turbine system. Moreover, the instructions are configured to cause the processor to estimate an estimated value using the received measurements. The estimated value pertains to a parameter of the turbine system. Furthermore, the instructions are configured to cause the processor to using the customized model, reduce or remove at least some environmental conditions from a corrected estimated value derived from the estimated value.
-
-
-
Search Results
4
records
(took 0.01 seconds)
