scholarly journals Corrigendum to “Frequency energy shift method for bearing fault prognosis using microphone sensor” [Mech. Syst. Signal Process. 147 (2021) 107068]

2022 ◽  
Vol 162 ◽  
pp. 108023
Author(s):  
Jaewoong Park ◽  
Seokgoo Kim ◽  
Joo-Ho Choi ◽  
Seung Hwan Lee
2021 ◽  
Vol 147 ◽  
pp. 107068 ◽  
Author(s):  
Jaewoong Park ◽  
Seokgoo Kim ◽  
Joo-Ho Choi ◽  
Seung Hwan Lee

Author(s):  
Robert F. Cook ◽  
Chris A. Michaels

Stress measurements in single-crystal and polycrystalline alumina are revisited using a recently developed optical fluorescence energy shift method. The method simultaneously utilizes the R1 and R2 Cr-related ruby line shifts in alumina to determine two components of the stress tensor in crystallographic coordinates, independent of the intended or assumed stress state. Measurements from a range of experimental conditions, including high-pressure, shock, quasi-static, and bulk polycrystals containing thermal expansion anisotropy effects, are analyzed. In many cases, the new analysis suggests stress states and stress magnitudes significantly different from those inferred previously, particularly for shock experiments. An implication is that atomistic models relating stress state to fluorescence shift require significant refinement for use in materials-based residual stress distribution analyses. Conversely, the earliest measurements of fluorescence in polycrystalline alumina are shown to be consistent with recent detailed measurements of stress equilibrium and dispersion.


Author(s):  
О. О. Грицай ◽  
А. К. Гримало ◽  
В. В. Колотий

2021 ◽  
Vol 19 ◽  
pp. 338-343
Author(s):  
A. Insuasty ◽  
◽  
C. Tutivén ◽  
Y. Vidal

This work proposes a fault prognosis methodology to predict the main bearing fault several months in advance and let turbine operators plan ahead. Reducing downtime is of paramount importance in wind energy industry to address its energy loss impact. The main advantages of the proposed methodology are the following ones. It is an unsupervised approach, thus it does not require faulty data to be trained; ii) it is based only on exogenous data and one representative temperature close to the subsystem to diagnose, thus avoiding data contamination; iii) it accomplishes the prognosis (various months in advance) of the main bearing fault; and iv) the validity and performance of the established methodology is demonstrated on a real underproduction wind turbine.


2012 ◽  
Vol 39 (5) ◽  
pp. 5200-5213 ◽  
Author(s):  
Hack-Eun Kim ◽  
Andy C.C. Tan ◽  
Joseph Mathew ◽  
Byeong-Keun Choi

Sensors ◽  
2021 ◽  
Vol 21 (6) ◽  
pp. 2228 ◽  
Author(s):  
Ángel Encalada-Dávila ◽  
Bryan Puruncajas ◽  
Christian Tutivén ◽  
Yolanda Vidal

As stated by the European Academy of Wind Energy (EAWE), the wind industry has identified main bearing failures as a critical issue in terms of increasing wind turbine reliability and availability. This is owing to major repairs with high replacement costs and long downtime periods associated with main bearing failures. Thus, the main bearing fault prognosis has become an economically relevant topic and is a technical challenge. In this work, a data-based methodology for fault prognosis is presented. The main contributions of this work are as follows: (i) Prognosis is achieved by using only supervisory control and data acquisition (SCADA) data, which is already available in all industrial-sized wind turbines; thus, no extra sensors that are designed for a specific purpose need to be installed. (ii) The proposed method only requires healthy data to be collected; thus, it can be applied to any wind farm even when no faulty data has been recorded. (iii) The proposed algorithm works under different and varying operating and environmental conditions. (iv) The validity and performance of the established methodology is demonstrated on a real underproduction wind farm consisting of 12 wind turbines. The obtained results show that advanced prognostic systems based solely on SCADA data can predict failures several months prior to their occurrence and allow wind turbine operators to plan their operations.


2005 ◽  
Vol 113 (08) ◽  
Author(s):  
KM Oltmanns ◽  
UH Melchert ◽  
HG Scholand-Engler ◽  
C Guenther ◽  
B Schultes ◽  
...  
Keyword(s):  

Sign in / Sign up

Export Citation Format

Share Document