Experiments for PHM: Needs, developments and challenges

[1]  Donghua Zhou,et al.  Remaining useful life estimation - A review on the statistical data driven approaches , 2011, Eur. J. Oper. Res..

[2]  Linxia Liao,et al.  Review of Hybrid Prognostics Approaches for Remaining Useful Life Prediction of Engineered Systems, and an Application to Battery Life Prediction , 2014, IEEE Transactions on Reliability.

[3]  Guang Meng,et al.  A predictive maintenance scheduling framework utilizing residual life prediction information , 2013 .

[4]  Daming Lin,et al.  A review on machinery diagnostics and prognostics implementing condition-based maintenance , 2006 .

[5]  Brian P. Weaver,et al.  Accelerated Test Methods for Reliability Prediction , 2013 .

[6]  Zhigang Tian,et al.  A framework for predicting the remaining useful life of a single unit under time-varying operating conditions , 2013 .

[7]  Joseph Mathew,et al.  Rotating machinery prognostics. State of the art, challenges and opportunities , 2009 .

[8]  Bhaskar Saha,et al.  Prognostics Methods for Battery Health Monitoring Using a Bayesian Framework , 2009, IEEE Transactions on Instrumentation and Measurement.

[9]  Kwok-Leung Tsui,et al.  Condition monitoring and remaining useful life prediction using degradation signals: revisited , 2013 .

[10]  W. Wang,et al.  A data-model-fusion prognostic framework for dynamic system state forecasting , 2012, Eng. Appl. Artif. Intell..

[11]  You Ming-yi Review on condition-based equipment residual life prediction and preventive maintenance scheduling , 2011 .

[12]  Gang Niu,et al.  Development of an optimized condition-based maintenance system by data fusion and reliability-centered maintenance , 2010, Reliab. Eng. Syst. Saf..

[13]  Jay Lee,et al.  Prognostics and health management design for rotary machinery systems—Reviews, methodology and applications , 2014 .

[14]  Xiao Hong Wang,et al.  Research of Double Nozzle Flapper Valve Accelerated Degradation Test , 2014 .

[15]  Enrico Zio,et al.  A dynamic particle filter-support vector regression method for reliability prediction , 2013, Reliab. Eng. Syst. Saf..

[16]  Enrico Zio,et al.  A data-driven fuzzy approach for predicting the remaining useful life in dynamic failure scenarios of a nuclear system , 2010, Reliab. Eng. Syst. Saf..

[17]  Tongmin Jiang,et al.  Accelerated Degradation Test and Particle Filter Based Remaining Useful Life Prediction , 2013 .

[18]  He Zhengjia Review of Life Prediction for Mechanical Major Equipments , 2011 .

[19]  William Q. Meeker,et al.  A Review of Accelerated Test Models , 2006, 0708.0369.

[20]  Loon Ching Tang,et al.  A Bayesian optimal design for accelerated degradation tests , 2010, Qual. Reliab. Eng. Int..

[21]  Jiang Tongmin,et al.  Degradation assessment and life prediction of electro-hydraulic servo valve under erosion wear , 2014 .

[22]  Gang Niu,et al.  Machine condition prognosis based on sequential Monte Carlo method , 2010, Expert Syst. Appl..

[23]  Lin Ma,et al.  Prognostic modelling options for remaining useful life estimation by industry , 2011 .

[24]  Tongmin Jiang,et al.  A combined prediction method for the life of product based on PSO with immunity algorithms , 2014, 2014 Reliability and Maintainability Symposium.

[25]  Marvin Rausand,et al.  Remaining useful life, technical health, and life extension , 2011 .

[26]  Luis A. Escobar,et al.  Accelerated degradation tests: modeling and analysis , 1998 .

[27]  Narayanaswamy Balakrishnan,et al.  Optimal Step-Stress Accelerated Degradation Test Plan for Gamma Degradation Processes , 2009, IEEE Transactions on Reliability.

[28]  Kai Goebel,et al.  Comparison of prognostic algorithms for estimating remaining useful life of batteries , 2009 .