Failure mode classification for grid-connected photovoltaic converters

Failure Mode Classification for Tumor Endoprostheses

The Journal of Bone and Joint Surgery (American) ◽

10.2106/jbjs.j.00834 ◽

2011 ◽

Vol 93 (5) ◽

pp. 418-429 ◽

Cited By ~ 259

Author(s):

Eric R. Henderson ◽

John S. Groundland ◽

Elisa Pala ◽

Jeremy A. Dennis ◽

Rebecca Wooten ◽

...

Keyword(s):

Failure Mode ◽

Failure Mode Classification

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Failure mode classification for control valves for supporting data-driven fault detection

2017 IEEE International Conference on Industrial Engineering and Engineering Management (IEEM) ◽

10.1109/ieem.2017.8290311 ◽

2017 ◽

Cited By ~ 3

Author(s):

Emanuel Trunzer ◽

Iris Weis ◽

Jens Folmer ◽

Carolin Schrufer ◽

Birgit Vogel-Heuser ◽

...

Keyword(s):

Fault Detection ◽

Failure Mode ◽

Data Driven ◽

Control Valves ◽

Failure Mode Classification

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Incorporating software failure in risk analysis – Part 1: Software functional failure mode classification

Reliability Engineering & System Safety ◽

10.1016/j.ress.2020.106803 ◽

2020 ◽

Vol 197 ◽

pp. 106803 ◽

Cited By ~ 1

Author(s):

Christoph A. Thieme ◽

Ali Mosleh ◽

Ingrid B. Utne ◽

Jeevith Hegde

Keyword(s):

Risk Analysis ◽

Failure Mode ◽

Functional Failure ◽

Software Failure ◽

Failure Mode Classification

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The Research on the Failure Mode Classification Based on Reconstructed Phase Space and GMM

Earth and Space 2010 ◽

10.1061/41096(366)238 ◽

2010 ◽

Author(s):

Han Xiao ◽

Yourong Li ◽

Lv Yong

Keyword(s):

Phase Space ◽

Failure Mode ◽

Reconstructed Phase Space ◽

Failure Mode Classification

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Failure mode classification and bearing capacity prediction for reinforced concrete columns based on ensemble machine learning algorithm

Advanced Engineering Informatics ◽

10.1016/j.aei.2020.101126 ◽

2020 ◽

Vol 45 ◽

pp. 101126 ◽

Cited By ~ 2

Author(s):

De-Cheng Feng ◽

Zhen-Tao Liu ◽

Xiao-Dan Wang ◽

Zhong-Ming Jiang ◽

Shi-Xue Liang

Keyword(s):

Machine Learning ◽

Reinforced Concrete ◽

Bearing Capacity ◽

Failure Mode ◽

Learning Algorithm ◽

Concrete Columns ◽

Machine Learning Algorithm ◽

Ensemble Machine Learning ◽

Failure Mode Classification ◽

Capacity Prediction

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Improved risk analysis through failure mode classification according to occurrence time

2012 IEEE International Conference on Condition Monitoring and Diagnosis ◽

10.1109/cmd.2012.6416287 ◽

2012 ◽

Cited By ~ 1

Author(s):

Ravish P. Y. Mehairjan ◽

Qikai Zhuang ◽

Dhiradj Djairam ◽

Johan J. Smit

Keyword(s):

Risk Analysis ◽

Failure Mode ◽

Occurrence Time ◽

Failure Mode Classification

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Failure mode classification and control for surrounding rock of large-scale cavern group

Rock Mechanics: Achievements and Ambitions ◽

10.1201/b11438-104 ◽

2011 ◽

pp. 527-533

Author(s):

T Xiang ◽

X Feng ◽

Q Jiang ◽

J Chen

Keyword(s):

Failure Mode ◽

Large Scale ◽

Surrounding Rock ◽

And Control ◽

Failure Mode Classification

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Failure Mode Classification of RC Columns by the Analysis of the Main Bar Strain Distribution Based on the Truss and Arch Model

Concrete Research and Technology ◽

10.3151/crt1990.10.2_13 ◽

1999 ◽

Vol 10 (2) ◽

pp. 13-28

Author(s):

Alcantara Primo Allan ◽

Hiroshi Imai

Keyword(s):

Failure Mode ◽

Strain Distribution ◽

Arch Model ◽

Rc Columns ◽

Failure Mode Classification

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Rapid Failure Mode Classification and Quantification in Batteries: A Deep Learning Modeling Framework

Energy Storage Materials ◽

10.1016/j.ensm.2021.07.016 ◽

2021 ◽

Author(s):

Sangwook Kim ◽

Zonggen Yi ◽

Bor-Rong Chen ◽

Tanvir R. Tanim ◽

Eric J. Dufek

Keyword(s):

Deep Learning ◽

Failure Mode ◽

Modeling Framework ◽

Failure Mode Classification

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A Four-Step Safety Integrity Level Analysis of Numerous Subsea Control System Components

ASCE-ASME J Risk and Uncert in Engrg Sys Part B Mech Engrg ◽

10.1115/1.4051043 ◽

2021 ◽

Author(s):

Jafar Mahmoudi

Keyword(s):

Control System ◽

Failure Mode ◽

Failure Modes ◽

Failure Rates ◽

Safety Integrity Level ◽

Closed Position ◽

Failure Mode Classification ◽

Time In Service ◽

Level Analysis ◽

Classification Table

Abstract In this paper, a four-step Safety Integrity Level (SIL) analysis is developed to analyze numerous components of the subsea control system based on the OREDA database. For this purpose, initially, a failure mode classification table is provided aiming to identify the number of dangerous as well as the prevalent failure modes. Then, several parameters such as the total time in service of the components are calculated. Also, failure rates are evaluated and the software checking is provided as the final step of the proposed framework. The results show that the number of dangerous failure modes is a noticeable value and the leakage in closed position is the failure mode occurring more than the other ones. Moreover, the quantification of parameters indicates that the process isolation valve of the subsea X-mass tree has the largest values in all the considered parameters. Besides, hydraulic coupling of the choke module and HC leak sensor are the two components with the highest value of failure rates.

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