Mathematical Problems in Engineering

Modeling for Prognostics and Health Management: Methods and Applications


Status
Published

Lead Editor

1Xi'an Institute of High-Tech, Xi'an, China

2Ecole Centrale Paris LGI-Supelec, Paris, France

3University of Southern California, Los Angeles, USA


Modeling for Prognostics and Health Management: Methods and Applications

Description

Prognostics and health management (PHM) can make full use of condition monitoring (CM) data from a functioning system to assess the reliability of the system in its actual life cycle conditions, to determine the advent of failure, and to mitigate system risk through managerial activities. PHM is a systematic approach that is used to evaluate the reliability of a system in its actual life-cycle conditions, to predict failure progression, and to mitigate operating risks via management actions. There are two parts in PHM, namely, “prognostics” and “health management.” Prognostics is often characterized by estimating the remaining useful life (RUL) of a system using available CM information. Once such prognosis is available, appropriate health management actions such as repair, replacement, and logistic support can be performed to achieve the required system’s operational objectives. A requirement of a PHM enabled system is the ability to estimate the RUL, which can provide the decision-maker with enough lead-time to perform the necessary maintenance actions prior to failure. This prognostic ability is a fundamental prerequisite for health management. So far, estimating the RUL, conditional on the CM data, has been considered as one of the most central components in PHM and attached great importance in practice.

With advances in information and sensing technologies, degradation signals of the system can be obtained relatively easily through CM techniques. However, it is quite common in practice that the degradation occurs in a stochastic way for a number of engineering systems such as bearings, gyroscopes, and battery systems. As a result, the RUL is also a random variable, resulting in the difficulty to estimate the RUL with certainty. The past decade has witnessed an increasingly growing research interest on various aspects of stochastic degradation-modelling from the observed signals for prognostics. This is partly caused by its importance in a variety of fields like maintenance, inventory control, public health surveillance and management, and more.

The main focus of this special issue will be on the new theories and methodologies and their applications in degradation modeling and prognostics and health management for complex engineering systems, especially in industry applications. The special issue enables researchers worldwide to report their most recent developments and ideas in the field, with a special emphasis on technical advances and new trends within the last five years. The selection criterion is the quality of the paper and the process will follow a standard procedure of a peer review process.

Potential topics include, but are not limited to:

  • Degradation modeling
  • Data-driven
  • Condition-based maintenance
  • Fault diagnostics and prognostics
  • Lifetime estimation
  • Predictive maintenance
  • Prognostics and health management
  • Reliability theory and application
  • Remaining useful life prediction
  • Replacement
  • Spare parts ordering with prognostic information

Articles

  • Special Issue
  • - Volume 2015
  • - Article ID 613896
  • - Editorial

Modeling for Prognostics and Health Management: Methods and Applications

Xiao-Sheng Si | Chang-Hua Hu | ... | Gang Li
  • Special Issue
  • - Volume 2015
  • - Article ID 802505
  • - Research Article

Research on FCM and NHL Based High Order Mining Driven by Big Data

Zhen Peng | Jie Peng | ... | Zhenguo Chen
  • Special Issue
  • - Volume 2015
  • - Article ID 348729
  • - Research Article

Fault Prediction Algorithm for Multiple Mode Process Based on Reconstruction Technique

Jie Ma | Jianan Xu
  • Special Issue
  • - Volume 2015
  • - Article ID 908742
  • - Research Article

Generalized Accelerated Failure Time Frailty Model for Systems Subject to Imperfect Preventive Maintenance

Huilin Yin | Xiaohan Yang | Rui Peng
  • Special Issue
  • - Volume 2015
  • - Article ID 753175
  • - Research Article

A Well-Designed Parameter Estimation Method for Lifetime Prediction of Deteriorating Systems with Both Smooth Degradation and Abrupt Damage

Chuanqiang Yu | Cheng Jiang
  • Special Issue
  • - Volume 2015
  • - Article ID 908027
  • - Research Article

Circuit Tolerance Design Using Belief Rule Base

Xiao-Bin Xu | Zheng Liu | ... | Cheng-Lin Wen
  • Special Issue
  • - Volume 2015
  • - Article ID 356916
  • - Research Article

Remaining Useful Lifetime Prognosis of Controlled Systems: A Case of Stochastically Deteriorating Actuator

Danh Ngoc Nguyen | Laurence Dieulle | Antoine Grall
  • Special Issue
  • - Volume 2015
  • - Article ID 207469
  • - Research Article

A Belief Rule-Based Safety Evaluation Approach for Complex Systems

Jun Zhang | Jiang Jiang | ... | Kewei Yang
  • Special Issue
  • - Volume 2015
  • - Article ID 432651
  • - Research Article

Fault Diagnosis in Condition of Sample Type Incompleteness Using Support Vector Data Description

Hui Yi | Zehui Mao | ... | Hui Luo
  • Special Issue
  • - Volume 2015
  • - Article ID 563954
  • - Research Article

A Diagnosis Method for Rotation Machinery Faults Based on Dimensionless Indexes Combined with -Nearest Neighbor Algorithm

Jianbin Xiong | Qinghua Zhang | ... | Qi Wang
Mathematical Problems in Engineering
 Journal metrics
Acceptance rate27%
Submission to final decision64 days
Acceptance to publication34 days
CiteScore1.800
Impact Factor1.009
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