Cody LaFlamme

ORCID: 0000-0003-2758-7262
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About
Contact & Profiles
Research Areas
  • Electrical Fault Detection and Protection
  • Integrated Circuits and Semiconductor Failure Analysis
  • Electrostatic Discharge in Electronics
  • Structural Health Monitoring Techniques
  • Concrete Corrosion and Durability
  • Silicon and Solar Cell Technologies
  • Lightning and Electromagnetic Phenomena

University of Florida
2020-2022

University of Utah
2021

This article utilizes variational autoencoder (VAE) and spread spectrum time domain reflectometry (SSTDR) to detect, isolate, characterize anomalous data (or faults) in a photovoltaic (PV) array. The goal is learn the distribution of non-faulty input signals, inspect reconstruction error test flag anomalies, then locate or using predicted baseline rather than fixed that might be too rigid. use VAE handles imbalanced better other methods used for classification PV faults because its...

10.1109/jsen.2022.3140922 article EN publisher-specific-oa IEEE Sensors Journal 2022-01-06

This article explains the use of supervised and unsupervised dictionary learning approaches on spread spectrum time domain (SSTDR) data to detect locate disconnections in a PV array consisting five panels. The aim is decompose an SSTDR reflection signature into different components where each component has physical interpretation, such as noise, environmental effects, faults. In approach, decomposed are inspected localize maximum difference between actual predicted location fault 0.44 m...

10.1109/jsen.2020.3029707 article EN publisher-specific-oa IEEE Sensors Journal 2020-10-08

In this article, we explore the possibility of using spread spectrum time domain reflectometry (SSTDR) for detecting disconnections in a large-scale photovoltaic (PV) array. We discuss importance, role, and trade-offs SSTDR resolution, frequency, attenuation disconnects system. Our results show that if proper system parameters are chosen, can be detected 1-kV consisting twenty-six 60-cell PV panels located within 1.52 m first 22 modules.

10.1109/jphotov.2021.3081437 article EN IEEE Journal of Photovoltaics 2021-06-03

Spread spectrum time domain reflectometry (SSTDR) is a non-intrusive method for electrical fault detection and localization that enables continuous monitoring of live systems. Electrical faults create changes in impedance subsequent the SSTDR reflection response. These response can be detected only if are outside window uncertainty measurement. In this paper, we establish determining associated minimum-detectable change measurements. We demonstrate photovoltaic (PV) systems, although methods...

10.1109/jsen.2021.3059412 article EN publisher-specific-oa IEEE Sensors Journal 2021-02-13

Current spread spectrum time-domain reflectometry (SSTDR) fault detection methods in photovoltaics compare measurements with a fault-free baselin.Yet, environmental factors, such as illuminance, temperature, and humidity, affect these signals can negatively our ability to detect locate faults. This article explains quantifies the effects of factors on SSTDR measurements. We demonstrate that humidity each significantly reflections from photovoltaic panels, which require use up 240 baselines...

10.1109/jphotov.2021.3127465 article EN IEEE Journal of Photovoltaics 2021-11-30

Unexpected results have been seen in multiple papers involving spread spectrum time domain reflectometry (SSTDR) measurements on twin lead cables with one line containing a fault. A small portion of the signal is able to transmit past fault, reflect off end cable, return back through and be recorded by SSTDR. This paper explains physics why this can happen, effect nearby ground planes. The transmission fault involves electric magnetic fields coupling conductive objects. allows for amount...

10.1109/jsen.2021.3075363 article EN publisher-specific-oa IEEE Sensors Journal 2021-04-23
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