Data mining for fault diagnostics in cyberphysical systems
| Title | Data mining for fault diagnostics in cyberphysical systems |
|---|---|
| Summary | Data mining for fault diagnostics in cyberphysical systems |
| Keywords | Machine learning, research preparatory, supervised learning, text data mining. |
| TimeFrame | The project should be done during the spring of 2014 and finished in late May. Ideally, the student(s) should start before the end of 2013. |
| References | [[References::[1] Sankavaram, Kodali, Martinez Ayala, Pattipati, Singh, Bandyopadhyay, "Event-driven Data Mining Techniques for Automotive Fault Diagnosis", 21st International Workshop on Principles of Diagnosis, (2010), http://www.phmsociety.org/node/451
[2] Saxena, Wu, Vachtsevanos, "A Hybrid Reasoning Architecture for Fleet Vehicle Maintenance", IEEE Instrumentation & Measurement Magazine, pp 29-36, (2006) [3] Kargupta, Gilligan, Puttagunta, Sarkar, Klein, Lenzi, Johnson, "MineFleet ®: The Vehicle Data Stream Mining System for Ubiquitous Environments", in (May and Saitta, Eds) Ubiquitous Knowledge Discovery, Lecture Notes in Artificial Intelligence 6202, Springer-Verlag, pp. 235–254, (2010)]] |
| Prerequisites | Learning systems, multivariate analysis, programming skills |
| Author | |
| Supervisor | Thorsteinn Rögnvaldsson, Stefan Byttner |
| Level | Master |
| Status | Open |
The problem is learning to link specific characteristics/features with observed historical faults in mobile cyberphysical systems (city buses). The available data bases are: (1) a large database with on-board data on a fleet of city buses over the period Aug 2011 – Dec 2013; (2) the service records for the same buses over the same period.
The project is suitable for 2 students. The students must have experience with matlab, be skilled in mathematics, be interested in text data mining and be able to work in an organized way.
Deliverables:
(a) A definition of the problem
(b) A state-of-the-art description of diagnostics methods, specifically data-mining based
(c) A set of suitable diagnostic cases from the data bases
(d) A list of suitable methods to use
(e) Results of testing with the set of suitable methods on the set of suitable cases
(f) A report
The work is well suited for writing a short scientific paper in the end and submit it to a conference. The project is suitable for 2 students with high work capacity and the ambition to show abilities for scientific or high-level development work.
Work packages: (a) Defining the problem (b) State-of-the-art definition (c) Extracting cases from the data bases (d) Defining the set of methods to test (e) Running the tests (f) Analysis, conclusions and writing the report
