An AI-assistant health state evaluation method of sensing devices

IF 4.2 2区 工程技术 Q2 ENGINEERING, MANUFACTURING Advances in Manufacturing Pub Date : 2024-07-22 DOI:10.1007/s40436-024-00517-w
Le-Feng Shi, Guan-Hong Chen, Gan-Wen Chen
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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.

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传感设备的人工智能辅助健康状态评估方法
传感设备的健康状态对智能能源、智能制造等众多智能应用场景有着长远的影响。本文提出了一种基于人工智能(AI)技术的传感设备健康状态评估集合方法,该方法首先考虑设备的运行特性,然后设计场景识别方法提取典型场景,最后提出具体的健康状态评估。该方法能有效推断故障设备的因果关系,为健康状态评估提供了可解释的依据,提高了健康状态评估的准确性。该方法有望为智能时代传感设备的高效精细管理提供支持。
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来源期刊
Advances in Manufacturing
Advances in Manufacturing Materials Science-Polymers and Plastics
CiteScore
9.10
自引率
3.80%
发文量
274
期刊介绍: As an innovative, fundamental and scientific journal, Advances in Manufacturing aims to describe the latest regional and global research results and forefront developments in advanced manufacturing field. As such, it serves as an international platform for academic exchange between experts, scholars and researchers in this field. All articles in Advances in Manufacturing are peer reviewed. Respected scholars from the fields of advanced manufacturing fields will be invited to write some comments. We also encourage and give priority to research papers that have made major breakthroughs or innovations in the fundamental theory. The targeted fields include: manufacturing automation, mechatronics and robotics, precision manufacturing and control, micro-nano-manufacturing, green manufacturing, design in manufacturing, metallic and nonmetallic materials in manufacturing, metallurgical process, etc. The forms of articles include (but not limited to): academic articles, research reports, and general reviews.
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