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SUMMARY:EESS talk on "Wear-and-tear of water quality sensors – Challenge
 s and opportunities"
DTSTART:20181023T121500
DTEND:20181023T131500
DTSTAMP:20260917T054019Z
UID:89b39e0dcbfa15dd23d25013a6d7cd78bbb4b3b2899bdd5b3e449e04
CATEGORIES:Conferences - Seminars
DESCRIPTION:Dr Kris Villez\, Group Leader\, Department of Process Engineer
 ing\, EAWAG\, CH Kris Villez leads the Spike research group at Eawag (Swis
 s Federal Institute for Aquatic Science and Technology). This group specia
 lizes in the development and experimental validation of methods for monito
 ring and automation of water treatment processes. He started his activitie
 s at Eawag in 2012 and received tenure in 2017. A unique feature of his re
 search group is the coverage of both black-box and white-box modelling met
 hods in pursuit of solutions to monitoring and automation challenges in na
 tural and engineered systems. Kris Villez is a fellow of the International
  Water Association (2016-2020) and actively contributes the mission of the
  Swiss Water Association (VSA).\nAbstract:\nThe abundant occurrence of fau
 lts and failures in sensors for environmental process monitoring is freque
 ntly cited as a major challenge for process monitoring and control of envi
 ronmental systems. Despite the wide recognition of this challenge\, little
  is known about the cause-and-effect relationships between sensor wear-and
 -tear (e.g.\, salt deposition\, fouling) and the appearance of fault sympt
 oms (e.g. signal drift). To alleviate this situation\, a specialized exper
 iment has been conducted by exposing 8 pH sensors to the same medium over 
 a period of two years. This experiment reveals that commonly held assumpti
 ons regarding the onset of sensor faults do not hold in practice. Indeed\,
  the recorded observations indicate that (1) sensor faults\, like signal d
 rift\, appear simultaneously rather than independently and that (2) none o
 f the commercial sensors produce signals that are free of drift at any tim
 e. Despite these challenging observations\, it appears possible to predict
  the expected drift in the near future\, which suggests that a reliable ap
 proach to predictive maintenance of sensor networks is feasible.
LOCATION:GR A3 32 https://plan.epfl.ch/?room==GR%20A3%2032
STATUS:CONFIRMED
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