基于分层滤波算法的无人机控制系统故障检测技术

针对传统无人机控制系统故障检测技术检测误差率高,检测速率低的问题,引入分层滤波算法研究了一种新的无人机控制系统故障检测技术,构建地面坐标系得到模型数据,同时收集无人机系统的内部转向角因素,录入转向角数据,采用算法整合处理主系统数据,利用滤波手段控制数据录入量,综合提取特征参数,选取不同于正常状态的特征参数,利用噪声估计器诊断故障,分析残差与“零”之间的关系,从而实现无人机控制系统的故障检测。实验结果表明,相较于传统技术,基于分层滤波算法的无人机控制系统故障检测技术误差率降低了0.56%,检测速率提升了27.39%。

Fault Detection Technology for UAV Control System Based on Hierarchical Filtering Algorithm

Aiming at the problem of high error rate and low detection rate of traditional UAV control system fault detection technology, a new hierarchical control algorithm is introduced to study a new UAV control system fault detection technology. The established ground coordinate system obtains model data. At the same time, the internal steering angle factor of the UAV system is collected, the steering angle data is entered, the main system data is processed by algorithm, the data input is controlled by filtering means, the characteristic parameters are extracted comprehensively, the characteristic parameters different from the normal state are selected, and the noise estimation is utilized. The device diagnoses the fault and analyzes the relationship between the residual and the "zero" to realize the fault detection of the drone control system. The experimental results show that compared with the traditional technology, the error detection technology of the UAV control system based on the layered filtering algorithm reduces the error rate by 0.56% and the detection rate by 27.39%.