基于非线性变刚度智能结构的可调低频振动传感器设计

低频/超低频振动传感器是实现地震灾害预警、地质勘探、航空航天装备健康监测、核爆监控、生物医学及科学探索等领域应用的核心器件，为重点工程项目的顺利进行提供重要决策信息。由于这些重大工程和装备的自振频率低(0.01~20Hz频段)、振幅大、微加速度且极易受到环境噪声的影响，使得有效信号极易被噪声湮没而难以准确测量。因而，迫切需要具有良好的超低频特性（甚至零频特性）的高性能低频振动传感器来实现“超深”和“超清晰”的振动环境监测。. 如何提升传感器的低频特性、增大带宽和增强抗干扰能力一直是低频振动测量领域的难点。然而，现有技术难以解决低频传感器多设计约束之间的相互制约关系。例如，线性软弹簧结构虽然可以保证低频特性，但该类结构通常尺寸较大，抗冲击能力弱，且抗干扰能力差。另外，虽然增加结构刚度可以提升传感器的抗冲击破坏能力，但同时也降低了探测灵敏度，二者存在矛盾式制约关系。因此，迫切需要探索敏感弹性元件多功能化（低频传感、抗环境噪声与冲击干扰）的设计方法，在微小尺寸空间内通过调节刚度来消除环境振动噪声影响是亟待解决的关键问题。. 本项目以研制可用传感器设计的可调变刚度敏感元件为目标，提出引入刚度可调的压电驱动多层级智能结构作为关键敏感单元，借助拓扑优化技术协同设计敏感弹性元件的宏-微观结构构型，使其具备分段变刚度特性、低频滤波及刚度自调节等特异功能，以实现传感器低频性能的突破。考虑测量环境与自身功能需求形成的多约束制约关系，建立基于非线性变刚度智能结构的可调低频振动传感器设计方法，建立具有分段变刚度和机械低频滤波特征的弹性敏感结构构型创新设计方法，实验验证和完善设计理论。综合调研国内外研究进展，尚未见到相关敏感结构的报道。本项目的研究成果将为低频、大带宽、高抗干扰能力的智能可调低频振动传感器设计提供重要的技术支撑和保障。

Low/ultra-low frequency vibration sensor is a key sensing element for earthquake warning, healthy status monitoring of large structures and equipment, and frontier scientific explorations (gravitational wave). So far, it remains a hot topic to explore the ways to improve its low frequency sensitivity, widen the bandwidth, and increase its anti-jamming performances. In this project, the tunable stiffness smart structure with multi-level imbedded micro-structures is introduced as the key sensing element for low frequency vibration sensor, and the multi-functions including the wide bandwidth, mechanical wave filtering, and anti-jamming capabilities to shock and environment noise are achieved by integrated design of the variable stiffness structure, smart material arrangement, micro-imbedded structure and circuit and the corresponding strategies. Hence, consider the relationship of the multi-constraints induced by measuring environments and self-function requirements, the project aims to establish the systematic design model for the adjustable low-frequency sensor incorporating the tunable nonlinear smart structures, to establish the integrated method for macro-micro structures for obtaining the elastic wave filtering based on the topology optimization. The design methodology and theory will be improved through experiments, thus providing guidance for new adjustable low-frequency vibration sensors.