TY - GEN
T1 - Flow-Loop Testing of Online Oil-in-Water UV-Fluorescence-Based Measurement
AU - Jespersen, Stefan
AU - Hansen, Dennis Severin
AU - Yang, Zhenyu
AU - Ivar Andersen, Simon
PY - 2022
Y1 - 2022
N2 - The online monitoring of Oil-in-Water (OiW) concentration in dynamic flow-loops using UV-Fluorescence-based sensors is investigated. Though the OiW sensors can be carefully calibrated in the static condition, many dynamic flow conditions can still impact their real-time measurement. In order to examine the considered OiW sensor's capability in handling dynamic flows, an extensive experimental study has been committed, which considers the following aspects, such as (i) different flow-loop configurations, e.g., standalone-loops and cyclone-in-loop; (ii) different online sampling mechanisms, e.g., (direct) in-line measurement and (indirect) side-stream measurement; (iii) different flow-rates of total stream or side-stream under different configurations and sampling mechanisms; (iv) impacts of air bubbles and pressure-pumps. The experimental results show that the considered OiW sensor can provide quite reasonable dynamic measurements in general. However this sensor's measurement can be very sensitive to different flow regimes, impurities (incl. air) in the measured stream as well as upstream (nearby) operating conditions. These observations could inspire automation researchers and industrial operators to create some innovative sensor fusion method(s), to combine this OiW measurement with other available measurements in the produced water treatment processes for better control of the de-oiling hydrocyclone system.
AB - The online monitoring of Oil-in-Water (OiW) concentration in dynamic flow-loops using UV-Fluorescence-based sensors is investigated. Though the OiW sensors can be carefully calibrated in the static condition, many dynamic flow conditions can still impact their real-time measurement. In order to examine the considered OiW sensor's capability in handling dynamic flows, an extensive experimental study has been committed, which considers the following aspects, such as (i) different flow-loop configurations, e.g., standalone-loops and cyclone-in-loop; (ii) different online sampling mechanisms, e.g., (direct) in-line measurement and (indirect) side-stream measurement; (iii) different flow-rates of total stream or side-stream under different configurations and sampling mechanisms; (iv) impacts of air bubbles and pressure-pumps. The experimental results show that the considered OiW sensor can provide quite reasonable dynamic measurements in general. However this sensor's measurement can be very sensitive to different flow regimes, impurities (incl. air) in the measured stream as well as upstream (nearby) operating conditions. These observations could inspire automation researchers and industrial operators to create some innovative sensor fusion method(s), to combine this OiW measurement with other available measurements in the produced water treatment processes for better control of the de-oiling hydrocyclone system.
KW - Oil-in-Water (OiW)
KW - flow-loop
KW - hydrocarbon pollution
KW - online
KW - process control
UR - http://www.scopus.com/inward/record.url?scp=85130562985&partnerID=8YFLogxK
U2 - 10.1109/SCC53769.2021.9768363
DO - 10.1109/SCC53769.2021.9768363
M3 - Article in proceeding
SP - 313
EP - 319
BT - Proceedings of IEEE 2nd International Conference on Signal, Control and Communication (SCC 2021)
PB - IEEE (Institute of Electrical and Electronics Engineers)
ER -