Fuzzy comprehensive assessment of running condition for a large-scale centrifugal compressor set
暂无分享,去创建一个
Xin Li | Zhongliang Zhou | Yanji Sun | Yanqiu Pan | Z. Zhou | Yan-Fang Sun | Yanqiu Pan | Xin Li
[1] Carsten Schröder,et al. Reasonable Sample Sizes for Convergence to Normality , 2014 .
[2] Feng Qian,et al. Total plant performance evaluation based on big data: Visualization analysis of TE process , 2018 .
[3] Zhang Zai-li. Analysis of the wind power forecasting performance based on high-order Markov chain models , 2012 .
[4] Sun Guang-qiang. Application of Markov Theory in Mid-Long Term Load Forecasting , 2011 .
[5] T. Saaty,et al. The Analytic Hierarchy Process , 1985 .
[6] Junfei Qiao,et al. Data-driven intelligent monitoring system for key variables in wastewater treatment process , 2018, Chinese Journal of Chemical Engineering.
[7] V. V. Alekseev,et al. Data measurement system of compressor units defect diagnosis by vibration value , 2017, 2017 XX IEEE International Conference on Soft Computing and Measurements (SCM).
[8] Liu Zhixiang. Method for On-line Operating Conditions Assessment for a Grid-connected Wind Turbine Generator System , 2010 .
[9] Zaiwu Gong,et al. Risk prediction of low temperature in Nanjing city based on grey weighted Markov model , 2014, Natural Hazards.
[10] Lin Wang,et al. A Review of Regional Ecological Security Evaluation , 2012 .
[11] Fouad Slaoui-Hasnaoui,et al. Wind Turbine Condition Monitoring: State-of-the-Art Review, New Trends, and Future Challenges , 2014 .
[12] A. Testa,et al. Very short-term probabilistic wind power forecasting based on Markov chain models , 2010, 2010 IEEE 11th International Conference on Probabilistic Methods Applied to Power Systems.
[13] Zhe Chen,et al. An improved fuzzy synthetic condition assessment of a wind turbine generator system , 2013 .
[14] A. Shamshad,et al. First and second order Markov chain models for synthetic generation of wind speed time series , 2005 .
[15] Jin Fang Zhu. Fault Tree Analysis of Centrifugal Compressor , 2011 .
[16] Zhenyu Wang,et al. Fuzzy synthetic condition assessment of wind turbine based on combination weighting and cloud model , 2017, J. Intell. Fuzzy Syst..
[17] Wei Zhang,et al. A New Deep Learning Model for Fault Diagnosis with Good Anti-Noise and Domain Adaptation Ability on Raw Vibration Signals , 2017, Sensors.
[18] John N. Mordeson,et al. Fuzzy Mathematics - An Introduction for Engineers and Scientists , 2001, Studies in Fuzziness and Soft Computing.
[19] Catherine M. Burns. Towards proactive monitoring in the petrochemical industry , 2006 .
[20] Iqbal Gondal,et al. Vibration Spectrum Imaging: A Novel Bearing Fault Classification Approach , 2015, IEEE Transactions on Industrial Electronics.
[21] Seref Sagiroglu,et al. Data mining and wind power prediction: A literature review , 2012 .
[22] Jay Lee,et al. Wind turbine performance assessment using multi-regime modeling approach , 2012 .
[23] Ludmila A. Uvarova,et al. Mathematical modeling : problems, methods, applications , 2001 .
[24] Geoff Coyle. Practical Strategy: Structured tools and techniques , 2004 .
[25] Dong,et al. Real-time Health Condition Evaluation on Wind Turbines Based on Operational Condition Recognition , 2013 .
[26] Xiao Lei,et al. A generalized model for wind turbine anomaly identification based on SCADA data , 2016 .
[27] Simon J. Watson,et al. Using SCADA data for wind turbine condition monitoring – a review , 2017 .
[28] Peter Matthews,et al. Classification and Detection of Wind Turbine Pitch Faults Through SCADA Data Analysis , 2020, International Journal of Prognostics and Health Management.
[29] Keping Li,et al. Identifying multi-variable relationships based on the maximal information coefficient , 2017, Intell. Data Anal..
[30] Michael Mitzenmacher,et al. Detecting Novel Associations in Large Data Sets , 2011, Science.