CAJ | 학술논문

针对传统组合导航故障诊断算法对系统模型精度要求较高，对非线性组合导航系统处理能力有限的问题，提出了自适应神经网络的SINS/GPS/DVL组合导航系统故障诊断。算法首先对组合导航故障诊断进行数学建模和故障信息提取，然后再采用遗传算法对基于BP神经网络进行故障诊断过程中容易遇到的局部极小值问题和网络结构进行自适应优化处理，有效提高了BP神经网络在进行组合导航故障诊断时的执行速度和效率，同时，也增强了系统故障诊断的准确性和可靠性。仿真试验有效验证了算法的有效性。
침대전통조합도항고장진단산법대계통모형정도요구교고，대비선성조합도항계통처리능력유한적문제，제출료자괄응신경망락적SINS/GPS/DVL조합도항계통고장진단。산법수선대조합도항고장진단진행수학건모화고장신식제취，연후재채용유전산법대기우BP신경망락진행고장진단과정중용역우도적국부겁소치문제화망락결구진행자괄응우화처리，유효제고료BP신경망락재진행조합도항고장진단시적집행속도화효솔，동시，야증강료계통고장진단적준학성화가고성。방진시험유효험증료산법적유효성。
Since the traditional integrated navigation fault diagnosis algorithm has high requirement to the accuracy of sys?tem model,and the limited processing ability to the nonlinear integrated navigation system,the fault diagnosis of SINS/GPS/DVL integrated navigation system based on adaptive neural network is proposed. The mathematical model of the integrated navi?gation fault diagnosis is established and the fault information is extracted. The genetic algorithm is adopted to optimize the local minimum problem and network structure encountered in the process of fault diagnosis with BP neural network,which can im?prove the execution speed and efficiency of the algorithm,and enhance the fault diagnosis accuracy and system reliability. The validity of the algorithm is verified by simulation tests.