Foto del docente

Federica Zonzini

Junior assistant professor (fixed-term)

Department of Electrical, Electronic, and Information Engineering "Guglielmo Marconi"

Academic discipline: IINF-01/A Electronics

Research

Keywords: SHM Vibration Analysis Signal Processing Spectral Analysis Compressed Sensing GW-based Communication Systems Edge/Extreme Edge Computing Smart Sensor Nodes Smart Sensor Nodes Acoustic Emission-based monitoring Artificial Intelligence Tiny Machine Learning

Data Compression

Analysis, application and development of Signal processing techniques for data compression applied to vibration-based structural assessment

  • Compressed sensing
  • Adapted CS: Model Assisted Rakeness-based Compressed Sensing
  • Wavelet Packet Transform
  • Autoregressive models

System Identification

Analysis, application and development of strategies for the reconstruction of structural properties for structures in dynamic regime

  • Time-domain analysis
  • Frequency-domain analysis: parametric and non-parametric methods
  • Operational Modal Analysis
  • Modal features reconstruction

Graph Signal Processing

Adoption of graph-based signal representation for mode shapes retrieval in multiple, non-simultaneous measurements in vibration-based monitoring

  • Mode shape pairing

Edge Computing/Tiny Machine Learning

Implementation of machine learning models, CS techniques and autoregressive models at the extreme edge for sensor-near data inference

  • Tiny Machine Learning
  • Parametric system identification @edge
  • Compressed Sensing @edge
  • Neural Architecture Search
  • Compression-Accuracy Co-optimization

Guided Wave-based Data Communication

Application of standard communication schemes to acoustic data communication exploiting the mechanical wave as a form of communication content and the mechanical channel as a form of communication medium

  • CDMA modulation scheme
  • FDM and OFDM modulation scheme
  • Time Reversal, Pulse Position Modulation
  • Frequency Steerable Acoustic Transducers

Acoustic Emission-based Monitoring

Application of artificial intelligence model to the estimation of acoustic features for the damage detection and localization of cracking phenomena

  • Time of Arrival localization with ML/DL architectures

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