【作者】 张新；

【导师】 费业泰；

【作者基本信息】 合肥工业大学 ， 精密仪器及机械， 2008， 博士

【摘要】 多维加速度传感器在工程技术中的应用越来越广泛,因此对三维加速度传感器的研究成为一个重要课题。目前推出的三维加速度传感器大多采用压阻式、压电式和电容式工作原理,利用MENS技术加工制造,结构上大多采用一体化弹性体结构。对于一体化多维加速度传感器还存在许多问题值得探讨。本课题来源于安徽省教育厅自然科学基金项目“应变式三维加速度传感器的设计”。在对目前现有三维加速度传感器结构和工作原理进行深入分析的基础上,设计出一种新型应变式全剪切一体化结构三维加速度传感器。传感器应用应变式测量原理,其弹性体采用整体结构,单一惯性质量块,三维加速度信息均利用剪切应变测量;弹性体制造采用一般机加工技术,大大降低了工艺要求和制造成本,是一种新型的三维加速度传感器;是一体化三维加速度传感器设计方法的一种创新,为三维加速度传感器增添一新的类型。同时对多维加速度传感器解耦方法进行了分析研究。论文的主要工作内容和创新点如下:对弹性体结构进行了优化设计。弹性体是传感器的核心元件,其结构参数直接影响传感器静、动态特性。采用正交试验设计和极差分析方法全面分析弹性体主要结构参数对传感器静、动态特性影响。运用有限元方法对传感器模型进行了静特性分析。通过静态分析,确定了弹性体在不同方向载荷作用下应变分布规律,证明了传感器具有良好线性。在此基础上确定了不同方向载荷作用下的电桥方案,并从理论上分析了如何实现解耦输出。对传感器进行了模态、谐响应和瞬态响应等动态特性分析。模态分析得到传感器的六阶固有频率和振型,谐响应分析和瞬态分析得到传感器的幅频特性及动态维间耦合情况。设计了三维加速度传感器静动态标定方法。采用重力加速度方法对传感器进行静态标定,通过标定分别得到传感器三个方向的灵敏度、非线性度和回程误差三个主要静态特性指标。设计制造了精密振动实验台和计算机自动化标定系统对三维加速度传感器的频响特性进行动态标定,得到传感器三个方向的频响特性曲线,确定传感器的动态应用范围。提出了基于BP神经网络的多维传感器非线性解耦方法。维间耦合是制约传感器测量精度的主要因素,为了克服传统线性解耦方法的局限性,研究了基于BP神经网络的加速度传感器的非线性静态解耦方法,应用该方法对应变式三维加速度传感器进行了解耦分析,并与最小二乘法的线性解耦方法进行了比较,结果表明BP神经网络比最小二乘法有更高的标定精度。更多还原

【Abstract】 Three-axis acceleration sensor is applied more and more increasingly in engineering. So the research about three-axis acceleration sensor is useful. At present, three-axis acceleration sensor based on piezoresistive, piezoelectric and capacitive is made by MENS and monolithic yielding part structure is used. There are many existed issues on multi-dimensional monolithic acceleration sensor. On the background of Anhui province nature science fund program, "Development of strain gauge three-axis acceleration sensor", a new type of three-axis full shearing acceleration sensor had been developed based on analysis to present three-axis acceleration sensor in its structure and working principles. The strain gauge full shearing measurement, monolithic yielding part structure and single mass are adopted in this sensor. It is made by mechanical manufacturing with less cost. It is a new type three-axis acceleration sensor and is an innovation at sensor design. Main research work and creative points of the paper are shown as follows:Yielding part is key component of sensor, static and dynamic characteristics are influenced by its main structure parameters. The influence of the main structure parameters on static and dynamic performance was studied by orthogonal experiment design and extreme analysis method, yielding part was optimized.Structure design of sensor and method of machining were introduced. Static performance of three-axis acceleration sensor was analyzed by finite element , which assured strain distribution regulation of yielding part loaded in different direction , and proved that sensor has good line characteristic. Based on this, bridge scheme and deployment of strain gauge were assured, how to realize decoupling output was analysis in theory.Modal analysis , harmonic response analysis and transient analysis of sensor were finished in this paper. Through modal analysis former six natural frequencies and mode shapes were obtained, through harmonic response analysis and transient analysis amplitude frequency characteristic of sensor was obtained, and dimension coupling was known.Static calibration of sensor was done by gravity acceleration method. Sensitivity, nonlinearity and hysterisis error , that static characteristics of three direction of sensor were abstained by static calibration. New type horizontal vibration table and computer automatic calibration system were designed, which realized dynamic calibration of frequency response characteristic of sensor, frequency response curves of three directions and frequency application range of sensor were assured .The coupling problem is an important factor limiting measuring accuracy of acceleration sensor, in order to overcome the limitation of traditional linear decoupling, a nonlinear static decoupling method was studied based on BP neural network, by which decoupling analysis of three-axis strain gauge acceleration sensor was finished. Compared with least square method, the result indicates that the method greatly improved the decoupling accuracy.更多还原