Ying Zhang, Di Peng, Gong Meng, Qian Zhao, Tiantian Li
{"title":"Simulation of Fault Diagnosis Model for Managing Aeronautical Multivariate Heterogeneous Inputs","authors":"Ying Zhang, Di Peng, Gong Meng, Qian Zhao, Tiantian Li","doi":"10.1109/prmvia58252.2023.00043","DOIUrl":null,"url":null,"abstract":"This paper studies the fault diagnosis model of aeronautical multivariate heterogeneous input data. Because of the gyroscope’s powerful nonlinear mapping capabilities, it is a natural fit for modeling failure detection, this article combined with a variety of aviation gyro input data with fault monitoring methods, a model simulation method for multivariate heterogeneous input data in different states is proposed, which are one-dimensional and multi-dimensional data fault diagnosis in the standby state of the aircraft, and multi-sensor fault detection in the flight state or stationary state, which can effectively meet the needs of managing the fault diagnosis of multi-heterogeneous input of aviation.","PeriodicalId":221346,"journal":{"name":"2023 International Conference on Pattern Recognition, Machine Vision and Intelligent Algorithms (PRMVIA)","volume":"18 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2023 International Conference on Pattern Recognition, Machine Vision and Intelligent Algorithms (PRMVIA)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/prmvia58252.2023.00043","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
This paper studies the fault diagnosis model of aeronautical multivariate heterogeneous input data. Because of the gyroscope’s powerful nonlinear mapping capabilities, it is a natural fit for modeling failure detection, this article combined with a variety of aviation gyro input data with fault monitoring methods, a model simulation method for multivariate heterogeneous input data in different states is proposed, which are one-dimensional and multi-dimensional data fault diagnosis in the standby state of the aircraft, and multi-sensor fault detection in the flight state or stationary state, which can effectively meet the needs of managing the fault diagnosis of multi-heterogeneous input of aviation.