PAM3: Machine Learning in the Railway Industry ( Predix Transform 2016)
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The document discusses the application of machine learning and computer vision in the railway industry, specifically through GE Transportation's Predix platform, which aids in track inspection by utilizing high-definition cameras on locomotives. It highlights the benefits of automating the historically manual and time-consuming inspections and improving defect coverage and accuracy using data analytics. The Predix platform offers a unified environment for data acquisition and analysis, focusing on enhancing operational efficiency in railway maintenance.
PAM3: Machine Learning in the Railway Industry ( Predix Transform 2016)
- 1. PAM3: Machine Learning in the Railway Industry Dattaraj J Rao – Senior Architect – GE Transportation (@DattarajR) Scott Nelson – Product Manager – GE Transportation
- 2. 2PREDIX TRANSFORM Agenda LocoVISION – Eyes for the Train1 Business problem and Value story Computer Vision models The PREDIX Advantage DEMO 2 3 4 5
- 3. 3PREDIX TRANSFORM LocoVISION – Eyes for the Train • High-definition cameras on Locomotive • Monitor Track geometry, Assets • Computer Vision
- 4. 4PREDIX TRANSFORM Business problem and Value story • Track Inspection: Manual, Time consuming • Too late to find defects - Coverage • In-accurate PTC Asset database Image Sources: ntsb.gov, Wikipedia.org PTC = Positive Train Control
- 5. 5PREDIX TRANSFORM Picture Here Geometry-based approach • Extract geometry from images • Isolate features of interest • Define “rules” for anomalies Computer Vision models Machine Learning method • Image as pixel data array • Positive and Negative images • Self-learning from data
- 6. 6PREDIX TRANSFORM The PREDIX Advantage • Common Platform – Data Acquisition to Action • BLOB store for Video + metadata (GPS) • On-demand + Batch Analytics in Cloud DATA ACQUISITION PREDIX 2.0 PRESENTATION § COMPUTER VISION MODELS § MACHINE LEARNING MODELS BLOB STORE ACTION PREDIX MACHINE
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