An automatic data augment method for remaining useful life prediction of aeroengines Article Swipe

PDF

YOU? · · 2025 · Open Access · · DOI: https://doi.org/10.21203/rs.3.rs-7162348/v1

The prediction of remaining service life in complex aviation engine systems is of great significance for airlines to develop maintenance plans for engines and reduce maintenance cost.However, the complex operating conditions of the engine and insufficient fault mode data limit the prediction accuracy. One direction to solve such problems is data augmentation, which aims to generate synthetic data from real datasets to expand training samples and improve the model's generalization ability.Admittedly, There are already many mature data augmentation methods, but the optimal data augmentation strategy for RUL prediction tasks varies in different situations. Confirming which data augmentation strategy is most suitable for the current remaining useful life prediction problem requires human experience or extensive parameter experiments.This work proposes an automatic data augmentation method(AdaRUL),Build an automatic search space and use reinforcement learning algorithms to search for the optimal strategy in the automatic search space to expand the sample dataset. The experiments conducted on the C-MAPSS public dataset provided by NASA demonstrate that AdaRUL has successfully generated high fidelity multivariate monitoring data. In addition, these generated data effectively support RUL prediction tasks and significantly improve the predictive ability of underlying deep learning models.

Related Topics

M1918 Browning Automatic Rifle

Automatic Identification System

Semi-Automatic Rifle

Automatic Certificate Management Environment

Computer Data Storage

Tokenization (Data Security)

Data Entry Clerk

Healthcare Effectiveness Data And Information Set

Concepts

No concepts available.

Metadata

Type: preprint
Language: en
Landing Page: https://doi.org/10.21203/rs.3.rs-7162348/v1
PDF: https://www.researchsquare.com/article/rs-7162348/latest.pdf
OA Status: gold
References: 19
OpenAlex ID: https://openalex.org/W4414410273

All OpenAlex metadata

Raw OpenAlex JSON

OpenAlex ID: https://openalex.org/W4414410273

Canonical identifier for this work in OpenAlex
DOI: https://doi.org/10.21203/rs.3.rs-7162348/v1

Digital Object Identifier
Title: An automatic data augment method for remaining useful life prediction of aeroengines

Work title
Type: preprint

OpenAlex work type
Language: en

Primary language
Publication year: 2025

Year of publication
Publication date: 2025-09-22

Full publication date if available
Authors: Z. Jane Wang, Hanqing Zhou

List of authors in order
Landing page: https://doi.org/10.21203/rs.3.rs-7162348/v1

Publisher landing page
PDF URL: https://www.researchsquare.com/article/rs-7162348/latest.pdf

Direct link to full text PDF
Open access: Yes

Whether a free full text is available
OA status: gold

Open access status per OpenAlex
OA URL: https://www.researchsquare.com/article/rs-7162348/latest.pdf

Direct OA link when available
Cited by: 0

Total citation count in OpenAlex
References (count): 19

Number of works referenced by this work

Full payload

id	https://openalex.org/W4414410273
doi	https://doi.org/10.21203/rs.3.rs-7162348/v1
ids.doi	https://doi.org/10.21203/rs.3.rs-7162348/v1
ids.openalex	https://openalex.org/W4414410273
fwci	0.0
type	preprint
title	An automatic data augment method for remaining useful life prediction of aeroengines
biblio.issue
biblio.volume
biblio.last_page
biblio.first_page
topics[0].id	https://openalex.org/T11512
topics[0].field.id	https://openalex.org/fields/17
topics[0].field.display_name	Computer Science
topics[0].score	0.8845000267028809
topics[0].domain.id	https://openalex.org/domains/3
topics[0].domain.display_name	Physical Sciences
topics[0].subfield.id	https://openalex.org/subfields/1702
topics[0].subfield.display_name	Artificial Intelligence
topics[0].display_name	Anomaly Detection Techniques and Applications
topics[1].id	https://openalex.org/T12597
topics[1].field.id	https://openalex.org/fields/22
topics[1].field.display_name	Engineering
topics[1].score	0.8485999703407288
topics[1].domain.id	https://openalex.org/domains/3
topics[1].domain.display_name	Physical Sciences
topics[1].subfield.id	https://openalex.org/subfields/2213
topics[1].subfield.display_name	Safety, Risk, Reliability and Quality
topics[1].display_name	Fire Detection and Safety Systems
topics[2].id	https://openalex.org/T10534
topics[2].field.id	https://openalex.org/fields/22
topics[2].field.display_name	Engineering
topics[2].score	0.8424999713897705
topics[2].domain.id	https://openalex.org/domains/3
topics[2].domain.display_name	Physical Sciences
topics[2].subfield.id	https://openalex.org/subfields/2205
topics[2].subfield.display_name	Civil and Structural Engineering
topics[2].display_name	Structural Health Monitoring Techniques
is_xpac	False
apc_list
apc_paid
language	en
locations[0].id	doi:10.21203/rs.3.rs-7162348/v1
locations[0].is_oa	True
locations[0].source
locations[0].license	cc-by
locations[0].pdf_url	https://www.researchsquare.com/article/rs-7162348/latest.pdf
locations[0].version	acceptedVersion
locations[0].raw_type	posted-content
locations[0].license_id	https://openalex.org/licenses/cc-by
locations[0].is_accepted	True
locations[0].is_published	False
locations[0].raw_source_name
locations[0].landing_page_url	https://doi.org/10.21203/rs.3.rs-7162348/v1
indexed_in	crossref
authorships[0].author.id	https://openalex.org/A5051587486
authorships[0].author.orcid	https://orcid.org/0000-0002-3791-0249
authorships[0].author.display_name	Z. Jane Wang
authorships[0].affiliations[0].raw_affiliation_string	China Aero-Polytechnology Establishment
authorships[0].author_position	first
authorships[0].raw_author_name	Zequan Wang
authorships[0].is_corresponding	False
authorships[0].raw_affiliation_strings	China Aero-Polytechnology Establishment
authorships[1].author.id	https://openalex.org/A5091316221
authorships[1].author.orcid	https://orcid.org/0009-0004-2077-6030
authorships[1].author.display_name	Hanqing Zhou
authorships[1].affiliations[0].raw_affiliation_string	China Aero-Polytechnology Establishment
authorships[1].author_position	last
authorships[1].raw_author_name	Hanqing Zhou
authorships[1].is_corresponding	False
authorships[1].raw_affiliation_strings	China Aero-Polytechnology Establishment
has_content.pdf	True
has_content.grobid_xml	False
is_paratext	False
open_access.is_oa	True
open_access.oa_url	https://www.researchsquare.com/article/rs-7162348/latest.pdf
open_access.oa_status	gold
open_access.any_repository_has_fulltext	False
created_date	2025-10-10T00:00:00
display_name	An automatic data augment method for remaining useful life prediction of aeroengines
has_fulltext	False
is_retracted	False
updated_date	2025-11-06T03:46:38.306776
primary_topic.id	https://openalex.org/T11512
primary_topic.field.id	https://openalex.org/fields/17
primary_topic.field.display_name	Computer Science
primary_topic.score	0.8845000267028809
primary_topic.domain.id	https://openalex.org/domains/3
primary_topic.domain.display_name	Physical Sciences
primary_topic.subfield.id	https://openalex.org/subfields/1702
primary_topic.subfield.display_name	Artificial Intelligence
primary_topic.display_name	Anomaly Detection Techniques and Applications
cited_by_count	0
locations_count	1
best_oa_location.id	doi:10.21203/rs.3.rs-7162348/v1
best_oa_location.is_oa	True
best_oa_location.source
best_oa_location.license	cc-by
best_oa_location.pdf_url	https://www.researchsquare.com/article/rs-7162348/latest.pdf
best_oa_location.version	acceptedVersion
best_oa_location.raw_type	posted-content
best_oa_location.license_id	https://openalex.org/licenses/cc-by
best_oa_location.is_accepted	True
best_oa_location.is_published	False
best_oa_location.raw_source_name
best_oa_location.landing_page_url	https://doi.org/10.21203/rs.3.rs-7162348/v1
primary_location.id	doi:10.21203/rs.3.rs-7162348/v1
primary_location.is_oa	True
primary_location.source
primary_location.license	cc-by
primary_location.pdf_url	https://www.researchsquare.com/article/rs-7162348/latest.pdf
primary_location.version	acceptedVersion
primary_location.raw_type	posted-content
primary_location.license_id	https://openalex.org/licenses/cc-by
primary_location.is_accepted	True
primary_location.is_published	False
primary_location.raw_source_name
primary_location.landing_page_url	https://doi.org/10.21203/rs.3.rs-7162348/v1
publication_date	2025-09-22
publication_year	2025
referenced_works	https://openalex.org/W3042756942, https://openalex.org/W2883525675, https://openalex.org/W2617137613, https://openalex.org/W3024761859, https://openalex.org/W4308000713, https://openalex.org/W3201901361, https://openalex.org/W4317436033, https://openalex.org/W4298007512, https://openalex.org/W3207579445, https://openalex.org/W3096831136, https://openalex.org/W2114492997, https://openalex.org/W2961638199, https://openalex.org/W2795398772, https://openalex.org/W3046438071, https://openalex.org/W4290929874, https://openalex.org/W3042925324, https://openalex.org/W2481916066, https://openalex.org/W3173407600, https://openalex.org/W4385245566
referenced_works_count	19
abstract_inverted_index.In	171
abstract_inverted_index.an	119, 124
abstract_inverted_index.by	158
abstract_inverted_index.in	7, 91, 139
abstract_inverted_index.is	12, 50, 99
abstract_inverted_index.of	3, 13, 32, 187
abstract_inverted_index.on	152
abstract_inverted_index.or	113
abstract_inverted_index.to	18, 46, 55, 62, 133, 144
abstract_inverted_index.One	44
abstract_inverted_index.RUL	87, 178
abstract_inverted_index.The	1, 149
abstract_inverted_index.and	24, 35, 66, 128, 181
abstract_inverted_index.are	73
abstract_inverted_index.but	80
abstract_inverted_index.for	16, 22, 86, 102, 135
abstract_inverted_index.has	163
abstract_inverted_index.the	28, 33, 41, 68, 81, 103, 136, 140, 146, 153, 184
abstract_inverted_index.use	129
abstract_inverted_index.NASA	159
abstract_inverted_index.aims	54
abstract_inverted_index.data	39, 51, 58, 77, 83, 96, 121, 175
abstract_inverted_index.deep	189
abstract_inverted_index.from	59
abstract_inverted_index.high	166
abstract_inverted_index.life	6, 107
abstract_inverted_index.many	75
abstract_inverted_index.mode	38
abstract_inverted_index.most	100
abstract_inverted_index.real	60
abstract_inverted_index.such	48
abstract_inverted_index.that	161
abstract_inverted_index.work	117
abstract_inverted_index.There	72
abstract_inverted_index.data.	170
abstract_inverted_index.fault	37
abstract_inverted_index.great	14
abstract_inverted_index.human	111
abstract_inverted_index.limit	40
abstract_inverted_index.plans	21
abstract_inverted_index.solve	47
abstract_inverted_index.space	127, 143
abstract_inverted_index.tasks	89, 180
abstract_inverted_index.these	173
abstract_inverted_index.which	53, 95
abstract_inverted_index.AdaRUL	162
abstract_inverted_index.engine	10, 34
abstract_inverted_index.expand	63, 145
abstract_inverted_index.mature	76
abstract_inverted_index.public	155
abstract_inverted_index.reduce	25
abstract_inverted_index.sample	147
abstract_inverted_index.search	126, 134, 142
abstract_inverted_index.useful	106
abstract_inverted_index.varies	90
abstract_inverted_index.C-MAPSS	154
abstract_inverted_index.ability	186
abstract_inverted_index.already	74
abstract_inverted_index.complex	8, 29
abstract_inverted_index.current	104
abstract_inverted_index.dataset	156
abstract_inverted_index.develop	19
abstract_inverted_index.engines	23
abstract_inverted_index.improve	67, 183
abstract_inverted_index.model's	69
abstract_inverted_index.models.	191
abstract_inverted_index.optimal	82, 137
abstract_inverted_index.problem	109
abstract_inverted_index.samples	65
abstract_inverted_index.service	5
abstract_inverted_index.support	177
abstract_inverted_index.systems	11
abstract_inverted_index.airlines	17
abstract_inverted_index.aviation	9
abstract_inverted_index.dataset.	148
abstract_inverted_index.datasets	61
abstract_inverted_index.fidelity	167
abstract_inverted_index.generate	56
abstract_inverted_index.learning	131, 190
abstract_inverted_index.methods,	79
abstract_inverted_index.problems	49
abstract_inverted_index.proposes	118
abstract_inverted_index.provided	157
abstract_inverted_index.requires	110
abstract_inverted_index.strategy	85, 98, 138
abstract_inverted_index.suitable	101
abstract_inverted_index.training	64
abstract_inverted_index.accuracy.	43
abstract_inverted_index.addition,	172
abstract_inverted_index.automatic	120, 125, 141
abstract_inverted_index.conducted	151
abstract_inverted_index.different	92
abstract_inverted_index.direction	45
abstract_inverted_index.extensive	114
abstract_inverted_index.generated	165, 174
abstract_inverted_index.operating	30
abstract_inverted_index.parameter	115
abstract_inverted_index.remaining	4, 105
abstract_inverted_index.synthetic	57
abstract_inverted_index.Confirming	94
abstract_inverted_index.algorithms	132
abstract_inverted_index.conditions	31
abstract_inverted_index.experience	112
abstract_inverted_index.monitoring	169
abstract_inverted_index.prediction	2, 42, 88, 108, 179
abstract_inverted_index.predictive	185
abstract_inverted_index.underlying	188
abstract_inverted_index.demonstrate	160
abstract_inverted_index.effectively	176
abstract_inverted_index.experiments	150
abstract_inverted_index.maintenance	20, 26
abstract_inverted_index.situations.	93
abstract_inverted_index.augmentation	78, 84, 97, 122
abstract_inverted_index.insufficient	36
abstract_inverted_index.multivariate	168
abstract_inverted_index.significance	15
abstract_inverted_index.successfully	164
abstract_inverted_index.augmentation,	52
abstract_inverted_index.cost.However,	27
abstract_inverted_index.reinforcement	130
abstract_inverted_index.significantly	182
abstract_inverted_index.generalization	70
abstract_inverted_index.experiments.This	116
abstract_inverted_index.ability.Admittedly,	71
abstract_inverted_index.method(AdaRUL),Build	123
abstract_inverted_index.<title>Abstract</title>	0
cited_by_percentile_year
countries_distinct_count	0
institutions_distinct_count	2
citation_normalized_percentile.value	0.19820957
citation_normalized_percentile.is_in_top_1_percent	False
citation_normalized_percentile.is_in_top_10_percent	True