基于人工智能的计算机电路系统故障检测与诊断技术研究

Research on Fault Detection and Diagnosis Technology for Computer Circuit Systems Based on Artificial Intelligence

文章旨在探讨基于人工智能的故障检测与诊断技术在计算机电路系统中的应用。通过综述当前电路系统故障检测与诊断技术的发展现状,分析其局限性与挑战,引出基于人工智能的解决方案。研究当前机器学习和深度学习在故障检测中的关键技术,如数据预处理、特征提取以及模型训练。借助机器学习算法高效识别电路系统中的潜在故障模式,并实现准确的故障诊断。此外,强调基于人工智能的故障检测与诊断技术在提高电路系统可靠性和维护效率方面的巨大潜力,为未来智能化维护系统的发展提供了重要启示。

This paper aims to explore the application of artificial intelligence-based fault detection and diagnosis technology in computer circuit systems.By reviewing the current development status of fault detection and diagnosis technology in circuit systems,analyzing its limitations and challenges,the solution based on artificial intelligence is introduced.The paper studies the key technologies of machine learning and deep learning in fault detection,such as data preprocessing,feature extraction,and model training.By efficiently identifying potential fault patterns in circuit systems and achieving accurate fault diagnosis through machine learning algorithms.In addition,it emphasizes the enormous potential of artificial intelligence based fault detection and diagnosis technology in improving the reliability and maintenance efficiency of circuit systems,providing important insights for the development of future intelligent maintenance systems.