SIA OpenIR  > 水下机器人研究室
全海深ARV控制器设计与推进器故障诊断研究
其他题名Research on Controller Design and Thruster Fault Diagnosis of Full Ocean Depth ARV
徐高朋1,2
导师李硕
分类号TP242
关键词全海深ARV 控制器设计 推进器故障诊断 小波包变换 神经网络
索取号TP242/X74/2018
页数68页
学位专业控制工程
学位名称硕士
2018-05-17
学位授予单位中国科学院沈阳自动化研究所
学位授予地点沈阳
作者部门水下机器人研究室
摘要控制器是全海深自主/遥控水下机器人(Autonomous Remotely-operated Vehicle, ARV)的关键部件之一,深渊科考对全海深ARV控制器在功能、功耗、耐压能力和空间布局等方面有着特殊要求。深渊科考作业环境复杂,对作业过程中出现的异常状况进行正确诊断,有助于提高载体作业安全。为满足以上需求,本文对全海深ARV控制器设计和推进器故障诊断方法进行了研究,论文主要工作包括以下几个方面:(1)根据全海深ARV控制器对功能、功耗、耐压等方面的具体需求,进行基于I.MX6Q的控制器硬件设计,先后完成电源模块设计、串口扩展转换、CAN总线隔离设计、AD资源扩展和IO驱动模块设计等工作。(2)根据控制器硬件资源构建用于交叉编译的开发环境,在控制器硬件设计基础上,进行Linux内核裁剪、FTP服务和Telnet服务的移植,完成与控制器硬件资源对应的串口、CAN总线、AD模块、IO和SPI驱动的移植与开发。(3)搭建实验测试平台,对全海深ARV控制器进行功能测试和耐压实验。在应用层编写相应的测试程序对全海深ARV控制器进行功能测试,通过测试对本论文控制器硬件设计、linux系统移植和驱动移植开发方案进行可行性验证。模拟深海高压环境对设计的控制器进行在线压力实验,通过实验对控制器耐压工作性能进行测试。(4)针对现有推进器故障诊断算法过于依赖水下机器人数学模型或运动状态的异常变化等问题,提出一种基于小波包变换和遗传算法优化神经网络的推进器故障诊断方法。搭建实验平台模拟推进器常见故障,获取不同工作状态下推进器实验数据,利用数据对本论文算法性能进行验证。
其他摘要The controller is one of the key components of the full ocean depth ARV (Autonomous Remotely-operated Vehicle). The trenches scientific exploration has special requirements for the full ocean depth ARV controller in terms of function, power consumption, pressure capability and space layout.The trenches science exploration operating environment is complex, and fault diagnosis of abnormal conditions during the operation process will helps to improve the safety and work performance of underwater vechile. In order to meet the above requirements, this paper focuses on the design of the deep sea ARV controller and fault diagnosis method of the thruster. The main work of the thesis includes the following aspects: (1) Based on the specific requirements of the full-sea-depth ARV controller for functions, power consumption, and withstand pressure capability, I.MX6Q-based controller hardware design is implemented. The power conversion module design, serial port expansion and type conversion, CAN bus isolation design, AD resource expansion, and IO driver module design were performed. (2) Construct a development environment for cross-compilation based on the hardware resources of the controller. Based on the hardware of the controller, perform the Linux kernel cutting and the transplantation of FTP and Telnet service. Completion of transplantation and development of serial ports, CAN buses, AD modules, IO, and SPI drivers corresponding to controller hardware resources. (3) Build an experimental test platform to perform functional tests and withstand pressure capability tests on the full ocean depth ARV controller.Write corresponding test programs at the application layer to perform functional tests on the full-sea depth ARV controller.According to the test results, verification the feasibility of the hardware design , linux migration and driver development scheme Simulate the deep-sea high pressure environment to carry on the withstanding pressure experiment to the controller of the design, test the working performance of the controller through the experiment. (4) Aiming at the problems that the existing thruster fault diagnosis algorithm is too dependent on the mathematical model of underwater vechile or the abnormal change of motion state, a thruster fault diagnosis method based on wavelet packet transform and genetic algorithm optimization neural network is proposed. Set up an experimental platform to simulate the common failure mode of the thruster, collect the experimental data of the thruster under different working conditions, and use the data to verify the performance of the proposed algorithm.
语种中文
产权排序1
文献类型学位论文
条目标识符http://ir.sia.cn/handle/173321/21804
专题水下机器人研究室
作者单位1.中国科学院沈阳自动化研究所
2.中国科学院大学
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GB/T 7714
徐高朋. 全海深ARV控制器设计与推进器故障诊断研究[D]. 沈阳. 中国科学院沈阳自动化研究所,2018.
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