EE - Kalman Filtering applied to Rotating Machinery

The goal of this research is to investigate signal processing techniques for "Once per Revolution" monitoring of rotating machinery.  The approach to be investigated relies on estimation of the revolutions-per-minute (RPM), and the application of signal processing to enhance markers/signatures to facilitate tracking.  Techniques such as Kalman Filtering will likely be utilized to achieve a solution.  The research will involve Matlab-based modeling and simulation and subsequent analysis of filtering techniques.

Name of research group, project, or lab
RF Communications and Sensing Lab ( Prof. Pratt's Research Group)
Why join this research group or lab?

The RF Communications and Sensing Lab is involved in a number of applied research activities, some of which have spawned spin-offs for commercialization.  A future area will potentially revolve around monitoring of rotating machinery.  The proposed project deals with an important capability to facilitate the monitoring of machinery with high fidelity.

Logistics Information:
Project categories
Electrical Engineering
Student ranks applicable
Junior
Senior
Student qualifications

Ability to use Matlab and related toolboxes.

Familiarity with Systems and/or Digital Signal Processing will help significantly.

Hours per week
1 credit / 3-6 hours
2 credits / 6-12 hours
Compensation
Research for Credit
Number of openings
1
Techniques learned

Modeling and simulation of dynamic systems

Kalman filtering and applications to tracking.

Project start
Spring Semester
Contact Information:
Mentors
tpratt@nd.edu
Research Professor
rls@nd.edu
Name of project director or principal investigator
Prof. Tom Pratt
Email address of project director or principal investigator
tpratt@nd.edu
1 sp. | 0 appl.
Hours per week
1 credit / 3-6 hours (+1)
1 credit / 3-6 hours2 credits / 6-12 hours
Project categories
Electrical Engineering