Sensor defect detection in multisensor information fusion
In industrial processes a vast variety of different sensors is increasingly used to measure and control processes, machines, and logistics. One way to handle the resulting large amount of data created by hundreds or even thousands of different sensors in an application is to employ information fusio...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
Copernicus Publications
2016-10-01
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| Series: | Journal of Sensors and Sensor Systems |
| Online Access: | http://www.j-sens-sens-syst.net/5/337/2016/jsss-5-337-2016.pdf |
| Summary: | In industrial processes a vast variety of different sensors is increasingly
used to measure and control processes, machines, and logistics. One way to
handle the resulting large amount of data created by hundreds or even
thousands of different sensors in an application is to employ information
fusion systems. Information fusion systems, e.g. for condition monitoring,
combine different sources of information, like sensors, to generate the state
of a complex system. The result of such an information fusion process is
regarded as a health indicator of a complex system. Therefore, information
fusion approaches are applied to, e.g., automatically inform one about a
reduction in production quality, or detect possibly dangerous situations.
Considering the importance of sensors in the previously described information
fusion systems and in industrial processes in general, a defective sensor has
several negative consequences. It may lead to machine failure, e.g. when
wear and tear of a machine is not detected sufficiently in advance. In this
contribution we present a method to detect faulty sensors by computing the
consistency between sensor values. The proposed sensor defect detection
algorithm exemplarily utilises the structure of a multilayered group-based
sensor fusion algorithm. Defect detection results of the proposed method for
different test cases and the method's capability to detect a number of
typical sensor defects are shown. |
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| ISSN: | 2194-8771 2194-878X |