Frequency as a key parameter in discriminating the failure types of thermal barrier coatings: Cluster analysis of acoustic emission signals

A key parameter in discriminating the failure types of thermal barrier coatings (TBCs) was found out by using the k-means cluster analysis of acoustic emission (AE) signals. It is shown that there are five classes of mechanisms, including surface vertical cracks, opening interface cracks, sliding in...

Full description

Bibliographic Details
Main Authors: Yang, L., Kang, H., Zhou, Y., Zhu, W., Cai, C., Lu, Chunsheng
Format: Journal Article
Published: Elsevier S.A 2015
Subjects:
Online Access:http://hdl.handle.net/20.500.11937/27294
_version_ 1848752223518982144
author Yang, L.
Kang, H.
Zhou, Y.
Zhu, W.
Cai, C.
Lu, Chunsheng
author_facet Yang, L.
Kang, H.
Zhou, Y.
Zhu, W.
Cai, C.
Lu, Chunsheng
author_sort Yang, L.
building Curtin Institutional Repository
collection Online Access
description A key parameter in discriminating the failure types of thermal barrier coatings (TBCs) was found out by using the k-means cluster analysis of acoustic emission (AE) signals. It is shown that there are five classes of mechanisms, including surface vertical cracks, opening interface cracks, sliding interface cracks, substrate deformation and macroscopic cleavage or spallation. Except for the last one, the other four classes can be clearly distinguished from their peak frequency distributions in the ranges of 170–250, 400–500, 260–350 and 40–150 kHz, respectively. However, AE signals overlap with each other in other parameter spaces, e.g., amplitude, energy, rise time, and duration time. The results indicate that the frequency can be applied to identify the AE source mechanisms in TBCs.
first_indexed 2025-11-14T08:05:12Z
format Journal Article
id curtin-20.500.11937-27294
institution Curtin University Malaysia
institution_category Local University
last_indexed 2025-11-14T08:05:12Z
publishDate 2015
publisher Elsevier S.A
recordtype eprints
repository_type Digital Repository
spelling curtin-20.500.11937-272942017-09-13T15:32:26Z Frequency as a key parameter in discriminating the failure types of thermal barrier coatings: Cluster analysis of acoustic emission signals Yang, L. Kang, H. Zhou, Y. Zhu, W. Cai, C. Lu, Chunsheng Acoustic emission k-Means clustering Thermal barrier coatings Key parameter A key parameter in discriminating the failure types of thermal barrier coatings (TBCs) was found out by using the k-means cluster analysis of acoustic emission (AE) signals. It is shown that there are five classes of mechanisms, including surface vertical cracks, opening interface cracks, sliding interface cracks, substrate deformation and macroscopic cleavage or spallation. Except for the last one, the other four classes can be clearly distinguished from their peak frequency distributions in the ranges of 170–250, 400–500, 260–350 and 40–150 kHz, respectively. However, AE signals overlap with each other in other parameter spaces, e.g., amplitude, energy, rise time, and duration time. The results indicate that the frequency can be applied to identify the AE source mechanisms in TBCs. 2015 Journal Article http://hdl.handle.net/20.500.11937/27294 10.1016/j.surfcoat.2015.01.014 Elsevier S.A restricted
spellingShingle Acoustic emission
k-Means clustering
Thermal barrier coatings
Key parameter
Yang, L.
Kang, H.
Zhou, Y.
Zhu, W.
Cai, C.
Lu, Chunsheng
Frequency as a key parameter in discriminating the failure types of thermal barrier coatings: Cluster analysis of acoustic emission signals
title Frequency as a key parameter in discriminating the failure types of thermal barrier coatings: Cluster analysis of acoustic emission signals
title_full Frequency as a key parameter in discriminating the failure types of thermal barrier coatings: Cluster analysis of acoustic emission signals
title_fullStr Frequency as a key parameter in discriminating the failure types of thermal barrier coatings: Cluster analysis of acoustic emission signals
title_full_unstemmed Frequency as a key parameter in discriminating the failure types of thermal barrier coatings: Cluster analysis of acoustic emission signals
title_short Frequency as a key parameter in discriminating the failure types of thermal barrier coatings: Cluster analysis of acoustic emission signals
title_sort frequency as a key parameter in discriminating the failure types of thermal barrier coatings: cluster analysis of acoustic emission signals
topic Acoustic emission
k-Means clustering
Thermal barrier coatings
Key parameter
url http://hdl.handle.net/20.500.11937/27294