국내 최대 기계 및 로봇 연구정보

기술보고서

기술보고서 게시판 내용
타이틀	Metrics for Offline Evaluation of Prognostic Performance
저자	Saxena, Abhinav;; Celaya, Jose;; Saha, Bhaskar;; Saha, Sankalita;; Goebel, Kai
Keyword	ACCURACY;; ALGORITHMS;; CONVERGENCE;; FAULT DETECTION;; MATHEMATICAL MODELS;; PERFORMANCE TESTS;; PROBABILITY THEORY;; RELIABILITY ANALYSIS;; STATISTICAL ANALYSIS;; SYSTEMS HEALTH MONITORING
URL	http://hdl.handle.net/2060/20100039169
보고서번호	ARC-E-DAA-TN1136
발행년도	2010
출처	NTRS (NASA Technical Report Server)
ABSTRACT	Prognostic performance evaluation has gained significant attention in the past few years. Currently, prognostics concepts lack standard definitions and suffer from ambiguous and inconsistent interpretations. This lack of standards is in part due to the varied end-user requirements for different applications, time scales, available information, domain dynamics, etc. to name a few. The research community has used a variety of metrics largely based on convenience and their respective requirements. Very little attention has been focused on establishing a standardized approach to compare different efforts. This paper presents several new evaluation metrics tailored for prognostics that were recently introduced and were shown to effectively evaluate various algorithms as compared to other conventional metrics. Specifically, this paper presents a detailed discussion on how these metrics should be interpreted and used. These metrics have the capability of incorporating probabilistic uncertainty estimates from prognostic algorithms. In addition to quantitative assessment they also offer a comprehensive visual perspective that can be used in designing the prognostic system. Several methods are suggested to customize these metrics for different applications. Guidelines are provided to help choose one method over another based on distribution characteristics. Various issues faced by prognostics and its performance evaluation are discussed followed by a formal notational framework to help standardize subsequent developments.