Quantitative Method of Health State Assessment Inside the Safe Region

2020 ◽  
Author(s):  
Yuhua Yin ◽  
Zhiliang Liu ◽  
Zhe Cheng
Keyword(s):  
Quantitative Method ◽  
State Assessment ◽  
Health State ◽  
Safe Region

New health-state assessment model based on belief rule base with interpretability

2021 ◽  
Vol 64 (7) ◽  
Author(s):  
Zhijie Zhou ◽  
You Cao ◽  
Guanyu Hu ◽  
Youmin Zhang ◽  
Shuaiwen Tang ◽  
...  
Keyword(s):  
State Assessment ◽  
Assessment Model ◽  
Rule Base ◽  
Health State ◽  
Model Based ◽  
Belief Rule Base

Health State Assessment and Lifetime Prediction Based on Unsupervised State Estimation

2019 ◽  
Author(s):  
Rosmawati Jihin ◽  
Dirk Söffker
Keyword(s):  
State Estimation ◽  
Clustering Algorithm ◽  
State Machine ◽  
State Assessment ◽  
Remaining Useful Life ◽  
Lifetime Prediction ◽  
Hydraulic Pressure ◽  
Health State ◽  
Estimation Process ◽  
Lifetime Model

Abstract Assessment of system health and prediction of remaining useful life can be performed effectively through the evaluation of degradation levels configured by multiple states. Commonly, degradation progression is modeled according to the specific configuration using existing algorithms with assuming numbers and state conditions. However, due to the complexity, especially in the case of a system with multiple hidden states, the proper configuration is hard to assign and to identify. The need for unsupervised state estimation process to assist degradation modeling preventing under or over assumption becomes obvious. Among the existing approaches is the application of clustering methods to classify data and to estimate the number of degradation states might exist. However, integration into the lifetime prediction framework is still infancy and often not considered. Therefore, in this work, a previously developed state machine lifetime model is extended to allow flexibility in configuring state topology based on K-means clustering algorithm and cluster validity index for the optimal number of states identification. Combining unsupervised state estimation process with a new state machine lifetime model has transformed it into a semi-supervised prognostic approach. For validation, hydraulic pressure data from tribology experiment are deployed for training and test the algorithm. Based on the evaluation, this approach demonstrates the ability to improve health state assessment and lifetime prediction in a more flexible way to address the variability in the system.

Failure Modes Mechanisms Effects Analysis for Refrigeration Device

2013 ◽  
Vol 288 ◽  
pp. 69-74 ◽  
Author(s):  
Ren Xiao Xu ◽  
Yang Liu
Keyword(s):  
Life Cycle ◽  
Failure Modes ◽  
Life Cycle Management ◽  
State Assessment ◽  
Remaining Useful Life ◽  
Automatic Identification ◽  
Health State ◽  
Useful Life ◽  
Using Data ◽  
Fusion Approach

FMMEA (failure mode, mechanisms, and effects analysis) is an effective tool for the life-cycle management of products and devices. We conducted an FMMEA for a refrigeration device at the request of a corporation. This paper demonstrates the process of our analysis of the compressor by employing Ganesan’s methodology. The results are listed in a table, including the physics of failures, risk priorities and parameters for monitoring. This paper also provides health-state assessment approaches based on FMMEA results and values of relevant parameters using fusion approach. Such assessment can be used for remaining useful life (RUL) estimation. Additionally, the paper illustrates our approach of computer-program-based automatic identification of failure using data of parameters retrieved from sensors.

scholarly journals PCN133 EPICLIN-LUNG STUDY: NON-SMALL-CELL LUNG CANCER (NSCLC) PATIENT QUALITY OF LIFE AND HEALTH-STATE ASSESSMENT

2010 ◽  
Vol 13 (7) ◽  
pp. A277
Author(s):  
M Thomas ◽  
G Cruciani ◽  
A Vergnenegre ◽  
E Guallar ◽  
E Medina ◽  
...  
Keyword(s):  
Quality Of Life ◽  
Lung Cancer ◽  
Small Cell Lung Cancer ◽  
Cell Lung Cancer ◽  
Nsclc Patient ◽  
State Assessment ◽  
Small Cell ◽  
Health State ◽  
Small Cell Lung

Remaining useful life prediction of rolling element bearings based on health state assessment

2015 ◽  
Vol 230 (2) ◽  
pp. 314-330 ◽  
Author(s):  
Zhiliang Liu ◽  
Ming J Zuo ◽  
Yong Qin
Keyword(s):  
Regression Model ◽  
Hybrid Approach ◽  
State Assessment ◽  
Remaining Useful Life ◽  
Support Vector ◽  
Health State ◽  
Rolling Element Bearings ◽  
Local Regression ◽  
Rolling Element ◽  
Useful Life

Instead of looking for an overall regression model for remaining useful life (RUL) prediction, this paper proposes a RUL prediction framework based on multiple health state assessment that divides the entire bearing life into several health states where a local regression model can be built individually. A hybrid approach consisting of both unsupervised learning and supervised learning is proposed to automatically estimate the real-time health state of a bearing in cases with no prior knowledge available. Support vector machine is the main technology adopted to implement health state assessment and RUL prediction. Experimental results on accelerated degradation tests of rolling element bearings demonstrate the effectiveness of the proposed framework.

Aeronautical relay health state assessment model based on belief rule base with attribute reliability

2020 ◽  
Vol 197 ◽  
pp. 105869 ◽  
Author(s):  
Zhijie Zhou ◽  
Zhichao Feng ◽  
Changhua Hu ◽  
Guanyu Hu ◽  
Wei He ◽  
...  
Keyword(s):  
State Assessment ◽  
Assessment Model ◽  
Rule Base ◽  
Health State ◽  
Model Based ◽  
Belief Rule Base
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