TY  - JOUR
A1  - Schwaneberg, Oliver
A1  - Köckemann, Uwe
A1  - Steiner, Holger
A1  - Sporrer, Sebastian
A1  - Kolb, Andreas
A1  - Jung, Norbert
T1  - Material classification through distance aware multispectral data fusion
T2  - Measurement science and technology
N2  - Safety applications require fast, precise and highly reliable sensors at low costs. This paper presents signal processing methods for an active multispectral optical point sensor instrumentation for which a first technical implementation exists. Due to the very demanding requirements for safeguarding equipment, these processing methods are targeted to run on a small embedded system with a guaranteed reaction time T < 2 ms and a sufficiently low failure rate according to applicable safety standards, e.g., ISO-13849. The proposed data processing concept includes a novel technique for distance-aided fusion of multispectral data in order to compensate for displacement-related alteration of the measured signal. The distance measuring is based on triangulation with precise results even for low-resolution detectors, thus strengthening the practical applicability. Furthermore, standard components, such as support vector machines (SVMs), are used for reliable material classification. All methods have been evaluated for variants of the underlying sensor principle. Therefore, the results of the evaluation are independent of any specific hardware.
KW  - estimation
KW  - detection
KW  - opto-electronic  protective device
KW  - displacement measurement
KW  - optical sensor
KW  - optical triangulation
KW  - signal  processing algorithm
Y1  - 2013
UR  - https://pub.h-brs.de/frontdoor/index/index/docId/1019
SN  - 0957-0233
VL  - 24
IS  - 4
SP  - 045001
ER  -