Related Experiment Video
Updated: Feb 3, 2026

A Simple Approach to Manipulate Dissolved Oxygen for Animal Behavior Observations
Published on: June 28, 2016
Fault signatures and bias progression in dissolved oxygen sensors
Oscar Samuelsson1, Anders Björk2, Jesús Zambrano3
1IVL Swedish Environmental Research Institute, Stockholm, Sweden E-mail: oscar.samuelsson@ivl.se; Uppsala University, Uppsala, Sweden.
Abstract:
Biofilm fouling is known to impact the data quality of sensors, but little is known about the exact effects. We studied the effects of artificial and real biofilm fouling on dissolved oxygen (DO) sensors in full-scale water resource recovery facilities, and how this can automatically be detected. Biofilm fouling resulted in different drift direction and bias magnitudes for optical (OPT) and electrochemical (MEC) DO sensors. The OPT-sensor was more affected by biofilm fouling compared to the MEC-sensor, especially during summer conditions. A bias of 1 mg/L was detected by analysing the impulse response (IR) of the automatic air cleaning system in the DO sensor. The IR is an effect of a temporal increase in DO concentration during the automatic air cleaning. The IRs received distinct pattern changes that were matched with faults including: biofilm fouling, disturbances in the air supply to the cleaning system, and damaged sensor membrane, which can be used for fault diagnosis. The results highlight the importance of a condition-based sensor maintenance schedule in contrast to fixed cleaning intervals. Further, the results stress the importance of understanding and detecting bias due to biofilm fouling, in order to maintain a robust and resource-efficient process control.
More Related Videos
Related Concept Videos
Confirmation Biases
Fault Types
For line-to-line faults occurring between phases B and C, the...
Hindsight Biases
Bias
In statistics, a sampling bias is created when a sample is collected from a population, and some members of the population are not as likely to be chosen as others (remember, each member...
Correspondence Bias
Self-Serving Bias

