专利快速检索-快速检索全球专利，免费商用专利数据库-IPRDB

1. 发明申请

US20200160208A1 MODEL SHARING AMONG EDGE DEVICES 审中-公开
公开(公告)号：US20200160208A1
公开(公告)日：2020-05-21
申请号：US16191993
申请日：2018-11-15
申请人： General Electric Company
发明人： Huan TAN , Colin PARRIS , Xiao BIAN , Shaopeng LIU , Kiersten RALSTON , Guiju SONG , Dayu HUANG
IPC分类号： G06N20/00 , G06K9/32 , G05B17/02
摘要： The example embodiments are directed to a system and method for sharing machine learning model parameters among edge devices in a clustered group of edge devices sensing data about an industrial asset. In one example, the method may include one or more of storing unique parameters of a machine learning (ML) model associated with an industrial asset which are unique with respect to unique parameters of other edge systems in the group of edge systems, receiving common parameter information from the group of edge systems which is shared among the group of edge systems, generating updated parameter values for an ML model based on a combination of the unique parameters and the received common parameter information, and executing the updated ML model based on incoming data from the industrial asset to generate predictive information about the industrial asset.

2. 发明申请

US20200160227A1 MODEL UPDATE BASED ON CHANGE IN EDGE DATA 审中-公开
公开(公告)号：US20200160227A1
公开(公告)日：2020-05-21
申请号：US16191879
申请日：2018-11-15
申请人： General Electric Company
发明人： Shaopeng LIU , Colin PARRIS , Xiao BIAN , Huan TAN , Kiersten RALSTON , Guiju SONG , Dayu HUANG
IPC分类号： G06N99/00
摘要： The example embodiments are directed to a system for triggering a model update for an edge device in an IIoT network. In one example, the method may include one or more of receiving data of an operation performed by an industrial asset, the received data comprising input for a machine learning (ML) model associated with the industrial asset, determining that the received data comprises a change in data pattern with respect to a training data set which was used to previously train the ML model, storing the received data comprising the change in data pattern in a new data set, and in response to the new data set reaching a minimum threshold size, at least one of updating the ML model based on the new data set and transmitting a request to update the ML model based on the new data set.

3. 发明申请

US20200167652A1 IMPLEMENTATION OF INCREMENTAL AI MODEL FOR EDGE SYSTEM 审中-公开
公开(公告)号：US20200167652A1
公开(公告)日：2020-05-28
申请号：US16199877
申请日：2018-11-26
申请人： General Electric Company
发明人： Dayu HUANG , Colin PARRIS , Xiao BIAN , Huan TAN , Kiersten RALSTON , Shaopeng LIU , Guiju SONG
IPC分类号： G06N3/08 , G06N5/04 , G06N20/20 , G06N3/04
摘要： The example embodiments are directed to a system and method for cold start deployment of an ML model for an edge system associated with an industrial asset. In one example, the method may include one or more of storing an incremental ML model comprising a plurality increments which sequentially increase a complexity of a predictive function of the incremental ML model, receiving performance information from an edge system that processes incoming data of an industrial asset using a current increment of the incremental ML model, dynamically determining to modify the current increment of the incremental ML model used by the edge system with a next increment of the incremental ML model having increased complexity based on the received performance information, and transmitting the next increment of the incremental ML model to the edge system.

4. 发明申请

US20200223069A1 UTILIZING OPTICAL DATA TO DYNAMICALLY CONTROL OPERATION OF A SNAKE-ARM ROBOT 审中-公开
公开(公告)号：US20200223069A1
公开(公告)日：2020-07-16
申请号：US16245017
申请日：2019-01-10
申请人： General Electric Company
发明人： Huan TAN , Xiao BIAN , Todd DANKO
IPC分类号： B25J13/00 , B25J17/02 , B25J9/16 , B25J5/00
摘要： Methods and systems for controlling a snake-arm robot. In an embodiment, a server computer receives real-time image data associated with at least one of an operating environment and a location of a workpiece from an optical sensor mounted on a robot head of a snake-arm robot, and receives, input data describing a desired pose of the robot head from a user device. The server computer then computes a desired velocity of the robot head using an image Jacobian, translates the desired velocity of the robot head into incremental displacement data and rotation data within a control cycle, computes a position of each of a plurality of links comprising a snake-arm of the snake-arm robot to follow motion of the robot head, computes a current position of each of the plurality of links utilizing a forward dynamics model, and computes force and torque data required to move at least one of a plurality of joints connecting the links to move the snake-arm robot to the desired pose. The method also includes generating movement instructions based on the force and torque data, and transmitting the movement instructions to at least one of a drive motor associated with an introduction device and a plurality of controllers associated with servo-motors operably connected to joints connecting the links of the snake arm causing the robot head to move to the desired pose.

5. 发明申请

US20200160207A1 AUTOMATED MODEL UPDATE BASED ON MODEL DETERIORATION 审中-公开
公开(公告)号：US20200160207A1
公开(公告)日：2020-05-21
申请号：US16191826
申请日：2018-11-15
申请人： General Electric Company
发明人： Guiju SONG , Colin PARRIS , Xiao BIAN , Huan TAN , Kiersten RALSTON , Shaopeng LIU , Dayu HUANG
IPC分类号： G06N20/00 , H04L29/08 , G06F11/34
摘要： The example embodiments are directed to a system and methods for determining to update a machine learning model based on model degradation. In one example, the method may include one or more of receiving data acquired at an edge of an Internet of things (IoT) network from an industrial asset, executing a machine learning model with the received data as input to generate a predictive output associated with the industrial asset, determining that a performance of the machine learning model on the edge has degraded based on the generated predictive output of the machine learning model, and transmitting information about the degraded performance of the machine learning model to a central server within the IoT network.

6. 发明申请

US20200167202A1 COLD START DEPLOYMENT FOR EDGE AI SYSTEM 审中-公开
公开(公告)号：US20200167202A1
公开(公告)日：2020-05-28
申请号：US16199713
申请日：2018-11-26
申请人： General Electric Company
发明人： Dayu HUANG , Colin PARRIS , Xiao BIAN , Huan TAN , Kiersten RALSTON , Shaopeng LIU , Guiju SONG
IPC分类号： G06F9/50 , H04L12/24 , G06N20/10 , G05B13/02 , G05B19/418
摘要： The example embodiments are directed to a system and method for cold start deployment of an ML model for an edge system associated with an industrial asset. In one example, the method may include one or more of storing machine learning (ML) models and local edge information where the ML models are already deployed, receiving, via a network, meta information of an edge system associated with an industrial asset in response to a cold start of the edge system, dynamically determining an optimum ML model for the cold start of the edge system from among the already deployed ML models based on the received meta information and the local edge information, and transmitting the determined optimum ML model to the edge system.

7. 发明申请

US20200159195A1 SELECTIVE DATA FEEDBACK FOR INDUSTRIAL EDGE SYSTEM 审中-公开
公开(公告)号：US20200159195A1
公开(公告)日：2020-05-21
申请号：US16192968
申请日：2018-11-16
申请人： General Electric Company
发明人： Xiao BIAN , Colin PARRIS , Dayu HUANG , Huan TAN , Kiersten RALSTON , Shaopeng LIU , Guiju SONG
IPC分类号： G05B19/418 , G06N99/00
摘要： The example embodiments are directed to a system and method for optimizing data the is transmitted from an edge device to a central server such as the cloud platform. In one example, the method may include one or more of receiving incoming data which is associated with an industrial asset positioned at an edge of an Internet of Things (IoT) network, transforming the incoming data into a pattern of data points within a feature space based on a machine learning model configured to detect patterns within the data, selecting a subset of data points from the pattern based on a distance between data points in the pattern of data points with respect to a previous pattern of data points in a previous dataset associated with the industrial asset, and transmitting the selected subset of data points to a central platform via the IoT network.

你已经成功收藏专利！

检索式保存成功!

IPRDB

热门服务

关于我们

友情链接

联系方式