下一代事物的人工智能预测性维护预测性维护
Taimia Bitam1, Aya Yahiaoui1, Djallel Eddine Boubiche1
1LEREESI Laboratory, HNS-RE2SD, Batna 05000, Algeria.
Sensors (Basel, Switzerland)
|December 31, 2025
概括
工业5.0通过以人为中心的方法增强了工业生态系统. 支持AIoT的预测性维护 (PdM) 对先进的故障检测和系统弹性至关重要.
科学领域:
- 工业工程 工业工程 工业工程
- 计算机科学 计算机科学
- 人工智能的人工智能
背景情况:
- 工业5.0优先考虑以人为中心,可持续和有弹性的工业系统.
- 传统的维护方法与复杂的,数据驱动的环境作斗争.
- 预测性维护 (PdM) 对工业5.0的适应性运营至关重要.
研究的目的:
- 在工业5.0的背景下,系统地审查支持AIoT的PdM.
- 为人工智能模型,IIoT基础设施和AIoT架构提供统一的分类法.
- 分析人工智能驱动的技术和特定行业的应用.
主要方法:
- 对启用AIoT的PdM进行系统的文献综述.
- 为人工智能模型,IIoT和AIoT架构开发统一的分类学.
- 对人工智能技术,行业实施和新兴范式的分析.
主要成果:
- AIoT可实现实时感应,学习和决策,用于PdM.
- 关键的人工智能技术包括故障检测,剩余使用寿命 (RUL) 估计和规范性行动.
- 像Edge-Cloud,联合学习和数字双胞胎这样的新兴范式增强了自主维护.
结论:
- 基于AIoT的PdM是工业5.0目标的基础.
- 未来的研究应该专注于可解释性,数据质量,网络安全和人类-人工智能合作.
- 本次审查为开发可扩展和可靠的AIoT-PdM系统提供了一个框架.
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