Application and practice of Artificial Intelligence in industrial equipment fault diagnosis
人工智能在工业设备故障诊断中的应用与实践

摘要

随着工业智能化水平的不断提高，人工智能在工业设备故障诊断中展现了巨大的潜力。利用人工智能技术，如机器学习、深度学习和数据挖掘，能够对设备运行状态进行实时监控，并精准识别潜在故障。通过对历史数据的分析与处理，AI系统能够自动判断设备健康状况并提供预警，从而大大提高了故障诊断的效率和准确性。本研究探讨了人工智能在工业设备故障诊断中的应用，分析了其技术优势和实施中的挑战，并提出了未来的发展方向。

Abstract

With the continuous improvement of industrial intelligence, artificial intelligence has demonstrated great potential in fault diagnosis of industrial equipment. Using artificial intelligence technologies such as machine learning, deep learning, and data mining, it is possible to conduct real-time monitoring of equipment operation status and accurately identify potential faults. Through the analysis and processing of historical data, AI systems can automatically judge the health status of equipment and provide early warnings, which significantly improves the efficiency and accuracy of fault diagnosis. This study explores the application of artificial intelligence in industrial equipment fault diagnosis, analyzes its technical advantages and challenges in implementation, and proposes future development directions.