Volterra System Analysis for an Electrochemical Sensor

Current biological methods for quantifying bacterial and fungal populations are time and labour intensive, whilst remaining expensive to automate. A potential solution to this problem is an electrochemical sensor, which applies a stochastic voltage across a liquid medium and measures the resultant current flow. This data can then be used to model the liquid’s electrochemical interactions and monitor it for bacterial growth and spoilage. Linear dynamic impedance models have previously been explored for this. However, the ability to capture the nonlinear effects observed at higher voltages can provide greater insights into the liquid’s properties. This is extremely difficult with neural networks which offer accurate predictive capabilities without much insight into the system. A different strategy is to model the liquid using a Volterra series representation. This work will document the integration of Volterra system identification capabilities within the sensor and its performance when modelling different liquid media as well as modifications made to the sensor for the applications tested.

Name thesis:degree_name

Master

Department dc:contributor.department

Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science

Grantor dc:publisher

Massachusetts Institute of Technology

Year dc:date.issued

2024

Author dc:creator

• Iqbal, Billal

Advisor dc:contributor.advisor

• Hunter, Ian W.

Statement dc:rights

• Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0)
• Copyright retained by author(s)

Licence dc:rights.uri

• https://creativecommons.org/licenses/by-nc-nd/4.0/

Handle dc:identifier.uri

https://hdl.handle.net/1721.1/156552

OAI identifier oai:identifier

oai:dspace.mit.edu:1721.1/156552