DOE Patents title logo U.S. Department of Energy
Office of Scientific and Technical Information

Title: Full-field imaging learning machine (FILM)

Abstract

A method of determining dynamic properties of a structure (linear or nonlinear) includes receiving spatio-temporal inputs, generating mode shapes and modal components corresponding to the spatio-temporal inputs using a trained deep complexity coding artificial neural network, and subsequently generating the dynamic properties by analyzing each modal component using a trained learning machine. A computing system for non-contact determination of dynamic properties of a structure includes a camera, a processor, and a memory including computer-executable instructions. When the instructions are executed, the system is caused to receive spatio-temporal image data, decompose the spatio-temporal image data into constituent manifold components using an autoencoder, and analyze the constituent manifold components using a trained learning machine to determine the dynamic properties.

Inventors:
Issue Date:
Research Org.:
Argonne National Laboratory (ANL), Argonne, IL (United States)
Sponsoring Org.:
USDOE
OSTI Identifier:
1840476
Patent Number(s):
11127127
Application Number:
16/429,857
Assignee:
UChicago Argonne, LLC (Chicago, IL)
Patent Classifications (CPCs):
G - PHYSICS G06 - COMPUTING G06N - COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
G - PHYSICS G06 - COMPUTING G06T - IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
DOE Contract Number:  
AC02-06CH11357
Resource Type:
Patent
Resource Relation:
Patent File Date: 06/03/2019
Country of Publication:
United States
Language:
English

Citation Formats

Yang, Yongchao. Full-field imaging learning machine (FILM). United States: N. p., 2021. Web.
Yang, Yongchao. Full-field imaging learning machine (FILM). United States.
Yang, Yongchao. Tue . "Full-field imaging learning machine (FILM)". United States. https://www.osti.gov/servlets/purl/1840476.
@article{osti_1840476,
title = {Full-field imaging learning machine (FILM)},
author = {Yang, Yongchao},
abstractNote = {A method of determining dynamic properties of a structure (linear or nonlinear) includes receiving spatio-temporal inputs, generating mode shapes and modal components corresponding to the spatio-temporal inputs using a trained deep complexity coding artificial neural network, and subsequently generating the dynamic properties by analyzing each modal component using a trained learning machine. A computing system for non-contact determination of dynamic properties of a structure includes a camera, a processor, and a memory including computer-executable instructions. When the instructions are executed, the system is caused to receive spatio-temporal image data, decompose the spatio-temporal image data into constituent manifold components using an autoencoder, and analyze the constituent manifold components using a trained learning machine to determine the dynamic properties.},
doi = {},
journal = {},
number = ,
volume = ,
place = {United States},
year = {2021},
month = {9}
}

Works referenced in this record:

A vision-based approach for the direct measurement of displacements in vibrating systems
journal, September 2003


Spatio-Temporal Features for Video Analysis
patent-application, June 2019


System and method for utilizing aggregated weather data for road surface condition and road friction estimates
patent, November 2020


Internet-Based System and a Method for Automated Analysis of Tactile Imaging Data and Detection of Lesions
patent-application, June 2008


System and Method for Automated Extraction of High Resolution Structural Dynamics from Video
patent-application, March 2018


Structure Defect Detention Using Machine Learning Algorithms
patent-application, June 2020


3D digital image correlation methods for full-field vibration measurement
journal, April 2011


Systems and Methods for a Computer Understanding Multi Modal Data Streams
patent-application, August 2016


Artificial neural networks for vibration based inverse parametric identifications: A review
journal, March 2017


Finite element model updating from full-field vibration measurement using digital image correlation
journal, April 2011


Electric Grid Analytics Learning Machine
patent-application, October 2020


Riesz Pyramids For Fast Phase-Based Video Magnification
patent-application, July 2015


Multi-Scale Mesh Modeling Software Products and Controllers
patent-application, November 2016