Remaining useful life(RUL) prediction is one of the most crucial elements in prognostics and health management(PHM). Aiming at the imperfect prior information, this paper proposes an RUL prediction method based on a n...Remaining useful life(RUL) prediction is one of the most crucial elements in prognostics and health management(PHM). Aiming at the imperfect prior information, this paper proposes an RUL prediction method based on a nonlinear random coefficient regression(RCR) model with fusing failure time data.Firstly, some interesting natures of parameters estimation based on the nonlinear RCR model are given. Based on these natures,the failure time data can be fused as the prior information reasonably. Specifically, the fixed parameters are calculated by the field degradation data of the evaluated equipment and the prior information of random coefficient is estimated with fusing the failure time data of congeneric equipment. Then, the prior information of the random coefficient is updated online under the Bayesian framework, the probability density function(PDF) of the RUL with considering the limitation of the failure threshold is performed. Finally, two case studies are used for experimental verification. Compared with the traditional Bayesian method, the proposed method can effectively reduce the influence of imperfect prior information and improve the accuracy of RUL prediction.展开更多
受特殊的地质环境条件和人类工程活动的强烈影响,中国川西地区地质灾害频发,对当地居民生命财产和区域生态安全构成严重威胁。以四川省德昌县区域内滑坡灾害为研究对象,甄选了坡度、坡向、地势起伏度、距断层距离、斜坡结构、工程岩组...受特殊的地质环境条件和人类工程活动的强烈影响,中国川西地区地质灾害频发,对当地居民生命财产和区域生态安全构成严重威胁。以四川省德昌县区域内滑坡灾害为研究对象,甄选了坡度、坡向、地势起伏度、距断层距离、斜坡结构、工程岩组、与道路距离、与水系距离、植被覆盖率9个因子构建评价指标体系,利用地质灾害基础数据,结合ArcGIS平台和遥感数据,分析指标与滑坡灾害空间分布规律;并基于信息量−地理逻辑回归耦合模型评价滑坡灾害的易发性及叠加降雨因子的综合易发性。结果表明:德昌县滑坡灾害综合易发性分级面积比分别为高易发区(13.61%)、中易发区(52.83%)、低易发区(32.61%)、极低易发区(0.95%)。该评价模型精度检验中ROC曲线的AUC(Area Under Curve)值为0.912,其准确性和合理性较高,可作为德昌县区域滑坡灾害评价的有效方法,为区域滑坡灾害防治策略的制定提供科学依据。展开更多
基金supported by National Natural Science Foundation of China (61703410,61873175,62073336,61873273,61773386,61922089)。
文摘Remaining useful life(RUL) prediction is one of the most crucial elements in prognostics and health management(PHM). Aiming at the imperfect prior information, this paper proposes an RUL prediction method based on a nonlinear random coefficient regression(RCR) model with fusing failure time data.Firstly, some interesting natures of parameters estimation based on the nonlinear RCR model are given. Based on these natures,the failure time data can be fused as the prior information reasonably. Specifically, the fixed parameters are calculated by the field degradation data of the evaluated equipment and the prior information of random coefficient is estimated with fusing the failure time data of congeneric equipment. Then, the prior information of the random coefficient is updated online under the Bayesian framework, the probability density function(PDF) of the RUL with considering the limitation of the failure threshold is performed. Finally, two case studies are used for experimental verification. Compared with the traditional Bayesian method, the proposed method can effectively reduce the influence of imperfect prior information and improve the accuracy of RUL prediction.
文摘受特殊的地质环境条件和人类工程活动的强烈影响,中国川西地区地质灾害频发,对当地居民生命财产和区域生态安全构成严重威胁。以四川省德昌县区域内滑坡灾害为研究对象,甄选了坡度、坡向、地势起伏度、距断层距离、斜坡结构、工程岩组、与道路距离、与水系距离、植被覆盖率9个因子构建评价指标体系,利用地质灾害基础数据,结合ArcGIS平台和遥感数据,分析指标与滑坡灾害空间分布规律;并基于信息量−地理逻辑回归耦合模型评价滑坡灾害的易发性及叠加降雨因子的综合易发性。结果表明:德昌县滑坡灾害综合易发性分级面积比分别为高易发区(13.61%)、中易发区(52.83%)、低易发区(32.61%)、极低易发区(0.95%)。该评价模型精度检验中ROC曲线的AUC(Area Under Curve)值为0.912,其准确性和合理性较高,可作为德昌县区域滑坡灾害评价的有效方法,为区域滑坡灾害防治策略的制定提供科学依据。
