An AI-assistant health state evaluation method of sensing devices

doi:10.1007/s40436-024-00517-w

Abstract

Abstract: The health states of sensing devices have a long-reaching influence on many smart application scenarios, such as smart energy and intelligent manufacturing. This paper proposes an ensemble methodology of the health-state evaluation of sensing devices, based on artificial intelligence (AI) technologies, which firstly takes into the operational characteristics, then designs a method of scenario identification to extract the typical scenarios, and subsequently puts forth a specific health-state evaluation. This method could infer the causalities of faulty devices effectively, which provides the interpretable basis for the health-state evaluation and enhances the evaluation accuracy of the health states. The suggested method has the promising potential to support the efficiently fine management of sensing devices in smart age.

The full text can be downloaded at https://link.springer.com/article/10.1007/s40436-024-00517-w

Key words: Sensing devices, Scenario identification, Health state evaluation, Artificial intelligence (AI)

Le-Feng Shi, Guan-Hong Chen, Gan-Wen Chen. An AI-assistant health state evaluation method of sensing devices[J]. Advances in Manufacturing, 2025, 13(3): 539-551.

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