数据驱动的工业故障诊断方法的研究进展
Liang Lei1, Weibin Li1, Shiwei Zhang2
1School of Artificial Intelligence, Xidian University, Xi'an 710071, China.
Sensors (Basel, Switzerland)
|May 14, 2025
概括
本综述探讨了使用大数据的工业故障诊断方法,重点是深度学习和大型模型. 未来的研究应该专注于数据质量,人工智能解释性和边缘计算,以加强设备维护.
科学领域:
- 工业工程和大数据分析
- 机器学习用于预测性维护
背景情况:
- 工业5.0强调智能设备维护和状态监控.
- 工业大数据对于理解和诊断设备故障至关重要.
研究的目的:
- 系统地审查主流的工业故障诊断方法.
- 分析数据驱动技术的演变和应用,特别是深度学习和大模型.
- 确定工业故障诊断的未来研究方向.
主要方法:
- 关于工业大数据来源,数据集和平台的综合文献综述.
- 在故障诊断中分析多源异质数据.
- 深入研究数据驱动的故障诊断,深度学习和大型模型应用.
主要成果:
- 深度学习算法在现代工业故障诊断中发挥着关键作用.
- 大型模型显示出增强诊断智能和概括的巨大潜力.
- 该审查涵盖数据源,数据集,平台和故障诊断方法的演变路径.
结论:
- 数据质量,深度学习模型的可解释性和基于边缘的大型模型对于未来的进步至关重要.
- 需要继续进行研究,以克服目前的局限性,并提高工业故障诊断系统的稳定性.
相关概念视频
01:10Documentation of Nursing Diagnosis
The nurse documents nursing diagnoses and enters them into the patient record. The identified patient's nursing diagnosis is either written out with a plan of care or entered into the electronic health record.
In some settings, data-driven computerized decision support systems are in place, allowing for more accurate nursing diagnoses. The database within one of these systems includes diagnostic labels defining characteristics, activities, and indicators for nursing. A nurse enters assessment...
In some settings, data-driven computerized decision support systems are in place, allowing for more accurate nursing diagnoses. The database within one of these systems includes diagnostic labels defining characteristics, activities, and indicators for nursing. A nurse enters assessment...
01:25Distribution Reliability and Automation
Distribution reliability in electrical power systems is critical for ensuring an uninterrupted power supply to consumers at minimal cost. According to IEEE Standard Terms, reliability is the probability that a device will function without failure over a specified time period or amount of usage. For electric power distribution, this translates to maintaining continuous power supply and addressing customer concerns over power outages. Several indices, as defined by IEEE Standard 1366-2012, are...