Rockwell Automation Technologies Incorporated

Benfeng Tang

David Bradly Berman

Linglai Li

Phillip R Bush

John Patrick Caspers

Steven T Haensgen

Zhen Wei

Steven A Lombardi

Sean Charles Schmelzer

Chao Chen

David Dale Brandt

Michael Lee Gasperi

Alex Laurence Nicoll

Tao Song

David W Siegler

Kun Wei

Alvaro Sanchez

Chirag L Malkan

Yanbin Zhang

Xiaolong Zhang

Jeffrey Scott Martin

Mark E Delker

Fredrick M Discenzo

Xuyuan Xiao

Xuyyan Xiao

Liz V Bahl Prosak

Xiaofeng Shi

Vaithianathan Jothi

Bingchao Tang

Junfeng Liao

A method for determining contact thickness change in a contactor includes sensing a first displacement distance moved by an armature of the contactor from a reference location to a first transition point during a switch-off operation of the contactor at a first contactor life reference time when movable contacts and fixed contacts of the contactor define a first contact thickness. The method further includes sensing a second displacement distance moved by the armature from the reference location to a second transition point during a switch-off operation at a second contactor life reference time that is after the first contactor life reference time when the movable and fixed contacts define a second contact thickness that is less than the first contact thickness. The first displacement distance and the second displacement distance are used to determine a contact thickness change between the first contact thickness and the second contact thickness. A contactor adapted to implement the method is also disclosed.

Method and device for determining contact thickness change of a contactor

Various embodiments of the present technology generally relate to power topology discovery in industrial environments. More specifically, some embodiments relate to automatic power topology discovery for factories based on device data that is already recorded for other purposes. Systems and methods described herein may be used to generate an accurate electrical network topology by collecting power data from power devices that may provide real-time or recorded measurements, detecting power change events, and matching power change signatures over power events for the devices in order to calculate the likelihoods of possible topology assumptions. Power change event data is used to recursively update topology probabilities using the Bayesian formula until a system topology can be produced with satisfactory confidence.

Systems and methods for automatic power topology discovery

For device configuration and monitoring, a processor receives configuration settings from an electronic device via the electronic device interface. The processor converts the configuration settings to hardware settings for a target device. The processor communicates the hardware settings to the target device via a target device interface.

Adapter for device configuration and monitoring

For function block framework generation, a method generates a function block framework for a hardware device. The function block framework includes function block framework source code and a function block framework description. The hardware device includes a logic engine and automation hardware. The function block framework presents a standard interface to a function block core executed by the logic engine. The method instantiates the function block framework and the function block core as an executable image for the hardware device. The method further configures the logic engine to execute the executable image using the function block framework description. The method executes the executable image with the logic engine.

Function block framework generation

A system includes a plurality of power monitors that, in operation, monitor parameters of power in an automation system at points between loads and/or power sources. Each of the power monitors includes sensing circuitry to sense the power parameters, peer-to-peer communications circuitry to communicate with other power monitors via peer-to-peer communication, network communications circuitry to communicate with automation devices via a network, and functional circuits to perform analysis of monitored power parameters in a cooperative manner based upon the power parameters monitored by the respective power monitor and power parameters monitored by other power monitors communicated via peer-to-peer communication.

Systems and methods for monitoring power

An apparatus includes an upstream/downstream probability module that determines, for each measurement point in an electrical power system, an upstream/downstream probability. The apparatus includes a zone module that identifies a plurality of zones within the power system and an upstream/downstream module that identifies, for each measurement point and for each zone, if a power quality event in a zone is upstream or downstream of a measurement point. The apparatus includes a zone probability module that determines a zone probability for each zone by multiplying the upstream probability or the downstream probability for each measurement point. The zone probability is a probability that the event happened in a zone. The zone probability module uses the upstream probability of a measurement point when the zone is upstream of the measurement point and uses the downstream probability when the zone is downstream of the measurement point.

Power quality event localization by multiple indexes

Systems and methods self-organize a multifunctional power and energy control and management system by integrating multiple backplane based modules through module descriptions, the module descriptions including control logic and parameters associated with the modules. Dynamic data table structures may be configured based on information provides with the module descriptions and provide for improved data accessing, storing, and updating.

Data table structure for self-organized management of communication with functional modules coupled via backplane assembly based on received module description including control logic

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Shanghai, China

Benfeng Tang