摘 要
随着现代工业自动化水平的不断提高，机械电子系统在各个领域得到广泛应用，而智能传感与检测技术作为其关键组成部分，对系统的性能优化和智能化发展具有重要意义。本研究旨在探索适用于复杂工况下机械电子系统的智能传感与检测技术，以提高系统的感知能力和故障诊断精度。通过融合多源异构传感器数据，构建基于深度学习算法的智能检测模型，实现了对设备运行状态的实时监测与预测性维护。研究采用理论分析、仿真实验与实际工况测试相结合的方法，针对传统检测手段存在的局限性，提出了一种自适应阈值调整机制，有效解决了信号干扰问题，提高了检测灵敏度。实验结果表明，该技术方案能够准确识别微弱故障特征，在不同工况条件下均表现出良好的稳定性和鲁棒性。与现有方法相比，本研究提出的智能传感与检测技术不仅提升了检测效率，还为机械电子系统的全生命周期管理提供了可靠的技术支持，为实现智能制造奠定了坚实基础。
关键词：智能传感与检测技术 多源异构传感器数据融合 深度学习算法
Abstract
With the continuous improvement of modern industrial automation, mechatronic systems have been widely applied across various fields. As a critical component, intelligent sensing and detection technologies play a significant role in optimizing system performance and promoting intelligent development. This study aims to explore intelligent sensing and detection technologies suitable for mechatronic systems under complex operating conditions to enhance the system's perception capabilities and fault diagnosis accuracy. By integrating multi-source heterogeneous sensor data, a deep learning-based intelligent detection model was constructed, enabling real-time monitoring and predictive maintenance of equipment operation status. The research combined theoretical analysis, simulation experiments, and actual operating condition tests to address the limitations of traditional detection methods. A self-adaptive threshold adjustment mechanism was proposed, effectively solving signal interference issues and improving detection sensitivity. Experimental results demonstrated that this technical solution can accurately identify weak fault characteristics and exhibits excellent stability and robustness under different operating conditions. Compared with existing methods, the intelligent sensing and detection technology proposed in this study not only improves detection efficiency but also provides reliable technical support for the entire lifecycle management of mechatronic systems, laying a solid foundation for achieving smart manufacturing.
Keyword:Intelligent Sensing And Detection Technology Multi-source Heterogeneous Sensor Data Fusion Deep Learning Algorithm
目 录
1绪论 1
1.1研究背景与意义 1
1.2国内外研究现状 1
1.3本文研究方法 2
2智能传感技术原理 2
2.1传感器工作机理 2
2.2数据采集与处理 3
2.3信号传输与抗干扰 3
3检测技术在机械电子系统中的应用 4
3.1故障诊断与预测 4
3.2状态监测与评估 5
3.3性能优化与改进 5
4智能传感与检测的融合创新 6
4.1多传感器数据融合 6
4.2智能化检测算法 6
4.3系统集成与实现 7
结论 8
参考文献 9
致谢 10
