基于AD系列陀螺仪和加速度计信号处理及其应用研究

发布时间：2018-04-08 22:14

本文选题：陀螺仪　切入点：加速度计　出处：《闽南师范大学》2014年硕士论文

【摘要】：随着科学技术日新月异的发展，MEMS惯性传感器在倾角测量系统中具有一定的应用价值。惯性系统的精度主要取决于陀螺仪和加速度计的精度，之前许多关于惯性系统精度的研究都是通过改善硬件结构或加工工艺技术提高精度，虽然在某种程度上提高了惯性传感器的精度，但也造成了技术困难和成本昂贵的局面。因此有必要寻求一种软件方法替代惯性传感器信号处理系统，以降低工艺要求和成本。利用软件优化算法提高信号的精度是惯性传感器一个重要研究方向。本论文主要以微机械AD系列加速度计ADXL203和陀螺仪ADXRS622为研究对象，从理论分析、电路设计、算法仿真、试验验证等方面展开工作，探讨微惯性器件的工作特性和信号处理方法。论文研究的重点从两个方面出发，即MEMS惯性传感器的信号调理电路设计和软件消噪算法试验。实验结果表明小波变换阈值消噪算法优于卡尔曼滤波算法，，在实际应用获得良好的效果。论文主要工作有：首先，根据MEMS惯性传感器的工作原理和结构特点分析ADXL系列加速度计和ADXRS系列陀螺仪的工作性能，完成MEMS惯性传感器与数据采集之间的信号调理电路、DSP处理器与A/D转换接口以及电源模块等具体设计与物理实现，并通过实验验证设计方案的可行性。其次，建立陀螺仪信号的检测装置，选用TMS320F28335作为测量系统的处理器，编写相关程序，研究卡尔曼滤波算法和小波变换阈值消噪算法在AD系列MEMS惯性传感器信号的应用，且做了相关试验。借助CCS4.2软件开发平台，在F28335DSP开发板上实时实现陀螺仪信号的卡尔曼滤波处理，有一定的消噪效果。MEMS陀螺仪信号的小波阈值消噪建立在陀螺仪漂移分析基础上，借助MATLAB仿真平台，选出最佳小波函数、分解层数和匹配阈值，编写小波变换阈值消噪相关MATLAB程序。多次试验结果表明sym4小波函数6层分解和启发式硬阈值的消噪效果最佳。最后，将所设计的AD系列MEMS惯性传感器测量系统应用于两轮自平衡小车中，通过比较两种软件消噪算法优缺点，选择小波变换阈值算法作实时消噪，实验结果表明算法的实时性能满足两轮自平衡小车平衡控制的需要，小车的车体平衡效果良好。
[Abstract]:With the rapid development of science and technology, MEMS inertial sensors have certain application value in inclination measurement system.The precision of inertial system mainly depends on the precision of gyroscope and accelerometer.Although the precision of inertial sensor is improved to some extent, it also causes technical difficulties and high cost.Therefore, it is necessary to find a software method to replace the inertial sensor signal processing system in order to reduce the process requirements and costs.It is an important research direction of inertial sensor to improve the signal precision by software optimization algorithm.In this paper, the micromechanical AD series accelerometer ADXL203 and gyroscope ADXRS622 are taken as the research objects. The work is carried out from the aspects of theoretical analysis, circuit design, algorithm simulation and experimental verification, and the working characteristics and signal processing methods of micro-inertial devices are discussed.This paper focuses on two aspects: the design of signal conditioning circuit of MEMS inertial sensor and the experiment of software de-noising algorithm.The experimental results show that the wavelet transform threshold denoising algorithm is better than the Kalman filter algorithm and has good effect in practical application.The main work of the thesis is as follows:First of all, according to the working principle and structural characteristics of MEMS inertial sensors, the performance of ADXL series accelerometers and ADXRS series gyroscopes is analyzed.The signal conditioning circuit between MEMS inertial sensor and data acquisition is completed. The interface between DSP processor and A / D converter and the power module are designed and realized. The feasibility of the design is verified by experiments.Secondly, the gyroscope signal detection device is established, the TMS320F28335 is selected as the processor of the measurement system, and the related program is written. The application of Kalman filter algorithm and wavelet transform threshold de-noising algorithm in AD series MEMS inertial sensor signal is studied.The related experiments were also done.With the help of CCS4.2 software development platform, the Kalman filter processing of gyroscope signal is realized in real time on F28335DSP development board. The wavelet threshold de-noising of MEMS gyroscope signal is established on the basis of gyroscope drift analysis, and the simulation platform of MATLAB is used.The optimal wavelet function, the number of decomposition layers and the matching threshold are selected, and the wavelet transform threshold denoising related MATLAB program is written.The experimental results show that the sym4 wavelet function with 6 layers decomposition and heuristic hard threshold denoising is the best.Finally, the AD series MEMS inertial sensor measurement system is applied to the two-wheel self-balancing vehicle. By comparing the advantages and disadvantages of the two software de-noising algorithms, the wavelet transform threshold algorithm is selected for real-time de-noising.Experimental results show that the real-time algorithm can meet the needs of two-wheel self-balancing vehicle balance control, and the car body balance effect is good.
【学位授予单位】：闽南师范大学
【学位级别】：硕士
【学位授予年份】：2014
【分类号】：TP212;TN911.7

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