Rockwell Automation Technologies Incorporated

Hanyu Shi

Bijan Sayyarrodsari

Kadir Liano

Jakob Methfessel

Dongzuo Tian

Bijan Sayyarodsari

A non-transitory computer-readable medium comprising computer-executable instructions that, when executed, cause a processor to perform operations including receiving a first dataset from a first automation component, the first dataset corresponds to raw data acquired by a first sensor; receiving a second dataset from a second automation component, the second dataset corresponds to raw data acquired by a second sensor; receiving data indicating an expected operation related to operations of an industrial automation system including the first and second automation components; determining a signature based on the first and second datasets and the data indicating the expected operation, wherein the signature indicates an unexpected operation as compared to the expected operation; performing a root cause analysis using the signature to determine a relationship indicating a first set of changes of the first dataset corresponding to a second set of changes in the data indicating the expected operation.

Device control using processed sensor data corresponding to unexpected operations

A method may include receiving data representative of one or more commands generated by a model-less controller to control operations of devices within a system and output parameters associated with the devices of the system. The method may also include determining whether the data is indicative of a change in operational characteristics of the system and generating a model representative of the operational characteristics of the system as a function of the data based on a Bayesian optimization algorithm in response to the data being indicative of the change. The method may also involve transmitting an excitation input to the devices in response to the data not being indicative of the change, receiving updated output parameters associated with the devices of the system after the excitation input is transmitted, and generating the model based on the updated output parameters and the excitation input.

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Austin, TX, United States of America

Hanyu Shi