A review of intelligent methods of health assessment technology

被引:1
|
作者
Liu, Diyi [1 ]
Peng, Linyuan [1 ]
Zhao, Zhiyao [1 ]
机构
[1] Beijing Technol & Business Univ, Sch Artificial Intelligence, 11-33 FuCheng Rd, Beijing 100048, Peoples R China
来源
INTELLIGENCE & ROBOTICS | 2023年 / 3卷 / 03期
基金
北京市自然科学基金; 中国国家自然科学基金;
关键词
Prognostics and health management; health assessment; intelligent methods; industrial systems; USEFUL LIFE PREDICTION; PROCESS FAULT-DETECTION; LITHIUM-ION BATTERIES; PARTICLE FILTER; RELIABILITY PREDICTION; RESIDUAL GENERATION; QUANTITATIVE MODEL; DIAGNOSIS; PROGNOSTICS; PERFORMANCE;
D O I
10.20517/ir.2023.16
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
The core technology of prognostics and health management, a key technology that detects system anomalies, is health assessment, which analyzes and diagnoses the current system working status and quantitatively assesses the health of the system. This paper reviews the development of health assessment technology in recent years from three aspects: health definition, health assessment indicators, and health assessment approaches. In terms of health definition, this paper summarizes three common definition methods. Health assessment indicators are reviewed from four levels: process variables, data features, residuals, and fusion indicators. Finally, health assessment approaches are divided into model-based, data-driven, and fusion approaches. Concerning the data- driven approach, rapidly developing health assessment research based on an intelligent approach is discussed. The paper also compares various approaches and identifies the current challenges and development prospects of this technology.
引用
收藏
页码:355 / 373
页数:19
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