MTS in false positive reduction for multi-sensor fusion

Robert Woodley; Michael Gosnell; Elizabeth Cudney

doi:10.1117/12.2050527

22 May 2014 MTS in false positive reduction for multi-sensor fusion

Robert Woodley, Michael Gosnell, Elizabeth Cudney

Proceedings Volume 9121, Multisensor, Multisource Information Fusion: Architectures, Algorithms, and Applications 2014; 912102 (2014) https://doi.org/10.1117/12.2050527
Event: SPIE Sensing Technology + Applications, 2014, Baltimore, MD, United States

Abstract

The Mahalanobis Taguchi System (MTS) is a relatively new tool in the vehicle health maintenance domain, but has some distinct advantages in current multi-sensor implementations. The use of Mahalanobis Spaces (MS) allows the algorithm to identify characteristics of sensor signals to identify behaviors in machines. MTS is extremely powerful with the caveat that the correct variables are selected to form the MS. In this research work, 56 sensors monitor various aspects of the vehicles. Typically, using the MTS process, identification of useful variables is preceded by validation of the measurements scale. However, the MTS approach doesn’t directly include any mitigating steps should the measurement scale not be validated. Existing work has performed outlier removal in construction of the MS, which can lead to better validation. In our approach, we modify the outlier removal process with more liberal definitions of outliers to better identify variables’ impact prior to identification of useful variables. This subtle change substantially lowered the false positive rate due to the fact that additional variables were retained. Traditional MTS approaches identify useful variables only to the extent they provide usefulness in identifying the positive (abnormal) condition. The impact of removing false negatives is not included. Initial results show our approach can reduce false positive values while still maintaining complete fault identification for this vehicle data set.

Citation Download Citation

Robert Woodley, Michael Gosnell, and Elizabeth Cudney "MTS in false positive reduction for multi-sensor fusion", Proc. SPIE 9121, Multisensor, Multisource Information Fusion: Architectures, Algorithms, and Applications 2014, 912102 (22 May 2014); https://doi.org/10.1117/12.2050527

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available

Members: $17.00

Non-members: $21.00 ADD TO CART

PROCEEDINGS
12 PAGES

DOWNLOAD PAPER SAVE TO MY LIBRARY

GET CITATION

RIGHTS & PERMISSIONS

Get copyright permission Get copyright permission on Copyright Marketplace

KEYWORDS

Signal to noise ratio

Mahalanobis distance

Mendelevium

Sensors

Databases

Distance measurement

Failure analysis

Show All Keywords

Keywords/Phrases

Search In:

Publication Years