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Journal of Sensors and Sensor Systems An open-access peer-reviewed journal
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Volume 5, issue 2
J. Sens. Sens. Syst., 5, 337–353, 2016
https://doi.org/10.5194/jsss-5-337-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.

Special issue: Sensor/IRS2 2015

J. Sens. Sens. Syst., 5, 337–353, 2016
https://doi.org/10.5194/jsss-5-337-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.

Regular research article 18 Oct 2016

Regular research article | 18 Oct 2016

Sensor defect detection in multisensor information fusion

Jan-Friedrich Ehlenbröker, Uwe Mönks, and Volker Lohweg Jan-Friedrich Ehlenbröker et al.
  • inIT – Institute Industrial IT, Langenbruch 6, 32657 Lemgo, Germany

Abstract. 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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This paper presents a novel method for the detection of sensor defects. Here, the consistency between measurements of sensor groups are utilized for this method. The sensor groups are pre-determined by the structure of an existing sensor fusion algorithm, which is in turn used to determine the health of a monitored system (e.g. a machine). Defect detection results of the presented method for different test cases and the method's capability to detect a number of typical sensor defects are shown.
This paper presents a novel method for the detection of sensor defects. Here, the consistency...
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