摘要
针对传统的残差χ2检测法未充分考虑缓变故障渐进变化的特点,而导致对缓变故障检测失效的问题,提出了一种改进的新息序列故障检测方法。该算法在传统新息序列检测法的基础上,通过模糊隶属函数构造检验统计量函数,并利用加权平均算法将落在有故障和无故障概率密度曲线交迭区域的检验统计量纳入故障信息检验中,以增加判断缓变故障的信息,从而更早地检测到缓变故障,而又不会增加虚警。仿真实验结果表明,将该方法应用到联邦滤波组合导航系统中,能够有效提高农业机械组合导航系统对缓变故障的容错能力。
With the development of agricultural machinery automatic navigation technology,the precision and stability of agricultural machinery positioning are becoming more and more demanding,MIMU has a broad application prospect in the fields of intelligent agricultural equipment because of its small size,low cost and high reliability.However,due to its own working principle,structure,manufacturing level and error in the installation of the device,MIMU signal output accuracy is poor,resulting in fast dispersion of navigation information over time.It has become an important way to improve the overall performance and accuracy of MIMU-based agricultural mechanical navigation system by using combined navigation technology.However,the increase in system sensors means that the complexity and failure rate of the entire combined navigation system are also increasing.Since the traditional residualχ2 test method hasn't fully considered the characteristic of the progressive change of the soft fault,which may cause the failure detection of the soft fault,an improved fault detection method of interest sequence was created.Based on the traditional innovation sequence fault detection method,the statistical magnitude with the fuzzy membership function was detected.By using the weighted average algorithm,it can take the detection statistics sitting in the overlapping area of the fault probability density curve and the fault-free probability density curve into the fault detection and increase information for soft fault estimation,so the soft fault could be detected early without increasing the false alarm.The simulation test result showed that the application of this method in the federated filter integrated navigation system could effectively increase the fault-tolerant ability of the integrated navigation system to soft fault.
作者
傅军
韩洪祥
戴海发
FU Jun;HAN Hongxiang;DAI Haifa(Department of Navigation, Naval University of Engineering, Wuhan 430033, China)
出处
《农业机械学报》
EI
CAS
CSCD
北大核心
2020年第3期28-33,50,共7页
Transactions of the Chinese Society for Agricultural Machinery
基金
国家自然科学基金项目(41876222)。
关键词
农业机械
组合导航
故障检测
新息序列
联邦滤波
agricultural machinery
combined navigation system
fault detection
interest sequence
federated filter
