摘要
微纳传感器作为精密制造领域的重要工具，其在尺寸精度、材料特性检测及工艺优化中的作用日益凸显。本研究以微纳传感器在精密制造中的应用为切入点，旨在探讨其性能优化策略及其对制造工艺的提升效果。通过结合理论分析与实验验证，研究选取了典型微纳传感器（如压电式和光学式传感器）进行性能测试，并采用信号处理算法与结构设计改进相结合的方法，实现了传感器灵敏度与稳定性的双重提升。结果表明，经过优化的微纳传感器在亚微米级位移检测中误差降低至0.5%以下，同时在复杂环境下的长期稳定性显著增强。此外，该研究提出了一种基于机器学习的传感器校准模型，有效解决了多参数耦合问题，进一步提升了测量精度。研究结论表明，微纳传感器的性能优化不仅能够满足精密制造对高精度检测的需求，还为智能制造系统的实时监控与反馈控制提供了可靠的技术支持。本研究的创新点在于将先进算法与硬件设计相结合，提出了适用于复杂工况的传感器优化方案，为精密制造技术的发展提供了新的思路与方法。
关键词：微纳传感器；性能优化；精密制造；信号处理算法；机器学习校准模型
Abstract
Micro-nano sensors, as essential tools in the field of precision manufacturing, have increasingly demonstrated their significance in dimensional accuracy, material property testing, and process optimization. This study focuses on the application of micro-nano sensors in precision manufacturing, aiming to explore strategies for performance optimization and their enhancement effects on manufacturing processes. By integrating theoretical analysis with experimental validation, typical micro-nano sensors, such as piezoelectric and optical sensors, were selected for performance testing. A combined approach of signal processing algorithms and structural design improvements was employed, achieving dual enhancements in sensor sensitivity and stability. The results indicate that the optimized micro-nano sensors reduced errors in sub-micrometer displacement detection to below 0.5%, while significantly improving long-term stability in complex environments. Additionally, a machine-learning-based sensor calibration model was proposed, effectively addressing multi-parameter coupling issues and further enhancing measurement accuracy. The conclusions reveal that the performance optimization of micro-nano sensors not only meets the high-precision detection requirements of precision manufacturing but also provides reliable technical support for real-time monitoring and feedback control in intelligent manufacturing systems. The innovation of this study lies in the integration of advanced algorithms with hardware design, proposing an optimized solution suitable for complex working conditions, thereby offering new insights and methodologies for the development of precision manufacturing technology.
Keywords：Micro-Nano Sensor; Performance Optimization; Precision Manufacturing; Signal Processing Algorithm; Machine Learning Calibration Model
目 录
摘要 I
Abstract II
一、绪论 1
(一) 微纳传感器与精密制造的背景意义 1
(二) 国内外研究现状分析 1
(三) 本文研究方法与技术路线 2
二、微纳传感器在精密制造中的关键应用 2
(一) 精密测量中的微纳传感器功能 2
(二) 工艺监控中的性能优化策略 3
(三) 数据采集与反馈控制的应用场景 3
三、微纳传感器性能优化的技术路径 4
(一) 材料选择对性能的影响分析 4
(二) 制造工艺对精度的提升作用 4
(三) 信号处理算法的优化设计 5
四、微纳传感器在实际制造中的案例分析 6
(一) 典型应用场景的性能评估 6
(二) 性能优化的实际效果验证 6
(三) 应用中存在的问题与改进建议 7
结 论 8
参考文献 9
