Industrial PLC Network Modeling and Parameter Identification Using Sensitivity Analysis and Mean Field Variational Inference

Author:

Wonnacott Raelynn1ORCID,Ching David S.1ORCID,Chilleri John1ORCID,Safta Cosmin1ORCID,Rashkin Lee1ORCID,Reichardt Thomas A.1ORCID

Affiliation:

1. Sandia National Laboratories, 7011 East Avenue, Livermore, CA 94550, USA

Abstract

A multiple input multiple output (MIMO) power line communication (PLC) model for industrial facilities was developed that uses the physics of a bottom-up model but can be calibrated like top-down models. The PLC model considers 4-conductor cables (three-phase conductors and a ground conductor) and has several load types, including motor loads. The model is calibrated to data using mean field variational inference with a sensitivity analysis to reduce the parameter space. The results show that the inference method can accurately identify many of the model parameters, and the model is accurate even when the network is modified.

Funder

Defense Nuclear Nonproliferation Research and Development

Publisher

MDPI AG

Subject

Electrical and Electronic Engineering,Biochemistry,Instrumentation,Atomic and Molecular Physics, and Optics,Analytical Chemistry

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