Sensor defect detection in multisensor information fusion

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.