SS 17
随着复杂装备、新能源系统及工业基础设施的规模化发展，系统运行不确定性、多源失效耦合、寿命衰减演化等问题日益突出，传统可靠性分析方法已难以满足高精度评估需求。高级统计学作为可靠性研究的核心基础，能够有效量化随机扰动、不确定性传播与动态退化规律，为装备健康评估、寿命预测、风险管控提供理论支撑。本专题聚焦贝叶斯统计、随机过程、不确定性量化、多维数据分析等前沿统计理论，围绕航空、核电、新能源、智能制造等多领域的可靠性实际场景，探究统计模型优化、算法改进与工程落地路径。旨在汇聚国内外学者交流最新研究成果，推动高级统计方法与可靠性工程深度融合，为复杂工程系统的安全运行与韧性提升提供新思路、新方法。
With the large-scale development of complex equipment, new energy systems and industrial infrastructure, challenges such as operational uncertainty, coupled multi-source failures and dynamic life degradation have become increasingly prominent. Traditional reliability analysis methods are insufficient to meet the requirements of high-precision performance evaluation. As an essential foundation of reliability research, advanced statistics can effectively quantify random interference, uncertainty propagation and degradation mechanisms, supporting equipment health assessment, remaining life prediction and systematic risk management. This special session focuses on cutting-edge statistical theories, including Bayesian statistics, stochastic processes, uncertainty quantification and multi-dimensional data analysis. It combines practical reliability scenarios in aerospace, nuclear power, renewable energy and intelligent manufacturing, exploring the optimization of statistical models, algorithm innovation and engineering application strategies. It aims to gather global researchers to share latest advances, promote the in-depth integration of advanced statistical tools and reliability engineering, and provide innovative theoretical and technical references for the safe operation and resilience enhancement of modern complex engineering systems.
主题：Topics:
电力负载预测 Power load prediction
锂离子电池寿命预测 PHM of Lithium-ion battery
风力发电预测 Wind power prediction
电动装置PHMPHM of Electric device
光伏功率预测 Photovoltaic power prediction
电网可靠性分析 Grid reliability analysis
功率管寿命预测与可靠性分析 Life Prediction and Reliability Analysis of IGBT
集成电路寿命预测与可靠性分析 Life Prediction and Reliability Analysis of Integrated module
