微小型水下机器人冗余惯性导航系统优化设计及故障检测方法

Inertial navigation plays an important role in the field of autonomous underwater vehicle. However, comparing with conventional inertial sensors, the measurement accuracy of MEMS inertial sensors is so poor. but it is very small, micropower consumption and cheap.Therefore, the technique of fault-tolerance with redundant sensors can be adopted to improve its measurement accuracy and reliability, and to improve the performance of Micro inertial measurement system with navigation, positioning and control information. According to the characteristics of AUV, we put the emphasis on the issues of redundant configuration, on-line fault diagnosis. 1) The technique of redundant configuration is brought into the MEMS gyroscope measurement unit. In the view of measurement accuracy and reliability, a new configuration with nine MEMS gyroscopes is proposed. Then its accuracy, reliability, and performance of reconstruction after failure are analyzed theoretically.2)For the on-line fault diagnosis method of redundant gyroscopes, the performance of widely used method, optimal parity test (OPT), is analyzed by both theoretical and experimental aspects. Taking the limitation of the OPT into consideration, the support vector machine (SVM) is brought forward to the diagnosis method. Firstly, the effect of the SVM kernel function and parameters are studied in depth. Secondly, a simple and efficient parameter optimization algorithm is addressed. At last, a comparison test between OPT and SVM shows that the SVM method has higher recognition rate of failure, lower missing rate and false alarm rate. 3)A new method of AFSA aided by RS is used in redundant system refactoring. Our research will be very useful for the further application in AUV inertial navigation.

为提高微小型AUV惯性导航的精度和可靠性,开展MEMS冗余惯性系统优化设计及故障检测方法研究.1)根据AUV应用特性,设计了一种新颖的斜交冗余配置方案,尝试用试验的手段,建立一套适用于MEMS冗余惯性系统的性能评估方法,为冗余方案优化选择提供理论依据.2)将支持向量机(SVM)引入冗余系统在线故障检测中,提高故障诊断率和降低虚警率,突破传统方法只能对固定数量陀螺发生特定类型故障诊断的局限性.3)对故障后的系统重构采用粗糙集理论(RS)和人工鱼群算法(AFSA)结合的方法,在AFSA寻优搜索中,用RS来选择合理的特征集,减小输入特征量的维数,从而降低工作模式的规模和复杂程度,克服AFSA寻优后期收敛速度慢,易陷入局部最优的缺点,实现重构工作无缝衔接,降低故障对导航实时性的影响.课题研究对MEMS惯性导航技术在AUV上的实际应用具有重要的价值,对其它陀螺类型的冗余惯性系统中也有一定的借鉴意义.

近些年来，水下机器人无论在民用还是在军用领域都得到了人们的广泛关注。微小型水下机器人能够代替人类广泛的应用于执行各种复杂的战略战术任务，具有体积小、成本低、能耗低、隐蔽性好、机动灵活、搭载方便等特点，已成为当前研究的热点。随着国家对微小型水下机器人技术的日益重视，对导航系统的性能要求也提高，包括精度、可靠性、成本、功耗以及尺寸等指标。因此，开展高精度、低成本、微功耗、高可靠性的惯性导航技术研究具有重要的意义。随着高精度的MEMS惯性器件的出现，目前，MEMS陀螺与MEMS加速度计的精度已经达到军事上的应用要求，因此，MEMS惯性导航系统在军事领域的应用需求越来越强，发展前景日益广阔，我国对MEMS惯性导航系统的研究工作已经提上日程，已成为当今惯性技术发展的一个重要方向。. 根据微型水下机器人对导航系统的要求，在原有冗余陀螺测量系统研究的基础上，提出了一种新型三个 MEMS-IMU斜交冗余配置方案，设计了一套微小型、微功耗、低成本的冗余MEMS惯性导航系统，利用余度技术对MEMS-IMU的测量精度和可靠性进行改进，并对采集到的传感器的数据进行故障检测，显著地提高了导航系统的测量精度与可靠性。另外，对冗余的惯性导航系统的研究也有利于拓展MEMS在其他领域的应用，例如武器装备等领域。