Dao Zhong, Jing Feng, Quan Sun, Zhengqiang Pan, N. Yang
{"title":"Maintenance request prediction for airplanes based on multivariate damage model","authors":"Dao Zhong, Jing Feng, Quan Sun, Zhengqiang Pan, N. Yang","doi":"10.1109/ICRMS.2016.8050059","DOIUrl":null,"url":null,"abstract":"Field data is often used as the basis for the prediction of an airplanes maintenance request. In the traditional methods, maintenance request predictions are mainly obtained immediately using data. However, uncertainty analysis during the failure detection is ignored, which makes maintenance request inaccurate. To overcome the above problems, a novel approach is proposed in this paper: a multivariate damage model is established to obtain the degree of airplane damage, which is used as an indicator for maintenance request predictions. On the basis of the degree of damage, uncertainty analysis can be effectively described using a stochastic process and the Markov process. The transition probability and transition time corresponding to the potential detection rate and date of maintenance, which are used to determine the distribution of maintenance requests. Experiments are implemented based on field data of a certain type of airplane. Results confirm that the proposed method performs well in the predictions of maintenance requests.","PeriodicalId":347031,"journal":{"name":"2016 11th International Conference on Reliability, Maintainability and Safety (ICRMS)","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 11th International Conference on Reliability, Maintainability and Safety (ICRMS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICRMS.2016.8050059","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
Field data is often used as the basis for the prediction of an airplanes maintenance request. In the traditional methods, maintenance request predictions are mainly obtained immediately using data. However, uncertainty analysis during the failure detection is ignored, which makes maintenance request inaccurate. To overcome the above problems, a novel approach is proposed in this paper: a multivariate damage model is established to obtain the degree of airplane damage, which is used as an indicator for maintenance request predictions. On the basis of the degree of damage, uncertainty analysis can be effectively described using a stochastic process and the Markov process. The transition probability and transition time corresponding to the potential detection rate and date of maintenance, which are used to determine the distribution of maintenance requests. Experiments are implemented based on field data of a certain type of airplane. Results confirm that the proposed method performs well in the predictions of maintenance requests.