Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-07-10T10:16:14.867402Z
Paper Citation Record · LEDGER
Empirical Calibration and Conditional-Reliability Diagnostics for Bearing RUL Prediction under Operating-Regime Shift
As of 5 August 2026, this Paper Citation Record lists 52 of 52 outbound references and 0 inbound Pith citation observations for arXiv:2607.08273.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
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Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links
A source-named dated measurement, never combined with another source.
Source: cited_works
Reference resolution
52 of 52 outbound references displayed
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Outbound references
Observation 346c0bf5-d09c-495f-97a0-1d0920968746 · outbound
This paper cites Run-to-failure data set of ball bearings subjected to time-varying load and speed conditions.
Empirical Calibration and Conditional-Reliability Diagnostics for Bearing RUL Prediction under Operating-Regime Shift Run-to-failure data set of ball bearings subjected to time-varying load and speed conditions
Reference 1
- Resolution
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Observation e2be57f7-563b-4b86-bb01-ce48f7e65a5a · outbound
This paper cites Angelopoulos and Stephen Bates.
Empirical Calibration and Conditional-Reliability Diagnostics for Bearing RUL Prediction under Operating-Regime Shift Angelopoulos and Stephen Bates
Reference 2
- Resolution
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Observation 132a832c-7983-4a25-a7a7-904aaccc1dfd · outbound
This paper cites An Empirical Evaluation of Generic Convolutional and Recurrent Networks for Sequence Modeling.
Empirical Calibration and Conditional-Reliability Diagnostics for Bearing RUL Prediction under Operating-Regime Shift An Empirical Evaluation of Generic Convolutional and Recurrent Networks for Sequence Modeling
Reference 3
- Resolution
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Observation f9c38edb-a9e4-4e9b-bfca-c7f2e91a863e · outbound
This paper cites Cluster Computing 6(3), 215–226 (Jul 2003), https://doi.org/10.1023/A: 1023588520138.
Empirical Calibration and Conditional-Reliability Diagnostics for Bearing RUL Prediction under Operating-Regime Shift Cluster Computing 6(3), 215–226 (Jul 2003), https://doi.org/10.1023/A: 1023588520138
Reference 5
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Observation c82df30d-6dba-471c-a8c7-2f3529f658e8 · outbound
This paper cites Digital twin-driven graph domain adaptation neural network for remaining useful life prediction of rolling bearing.Re- liability Engineering & System Safety, 245:109991, 2024.
Empirical Calibration and Conditional-Reliability Diagnostics for Bearing RUL Prediction under Operating-Regime Shift Digital twin-driven graph domain adaptation neural network for remaining useful life prediction of rolling bearing.Re- liability Engineering & System Safety, 245:109991, 2024
Reference 6
- Resolution
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation 192973b9-8799-43bd-ae46-879b8f62aaa4 · outbound
This paper cites Remain- ing useful lifetime prediction via deep domain adaptation.Reliability Engineering & System Safety, 195:106682, 2020.
Empirical Calibration and Conditional-Reliability Diagnostics for Bearing RUL Prediction under Operating-Regime Shift Remain- ing useful lifetime prediction via deep domain adaptation.Reliability Engineering & System Safety, 195:106682, 2020
Reference 7
- Resolution
- verified exact
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation 4a16bd57-33a1-45b7-b420-3d8a557cbeea · outbound
This paper cites Remain- ing useful life prediction based on physics-informed data augmentation.Reliability Engineering & System Safety, 252:110451, 2024.
Empirical Calibration and Conditional-Reliability Diagnostics for Bearing RUL Prediction under Operating-Regime Shift Remain- ing useful life prediction based on physics-informed data augmentation.Reliability Engineering & System Safety, 252:110451, 2024
Reference 8
- Resolution
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation ee2e5559-8ce0-467a-a886-1c3dfd5268b5 · outbound
This paper cites Remaining useful life estimation using deep metric transfer learning for kernel regression.Reliability Engineering & System Safety, 212:107583, 2021.
Empirical Calibration and Conditional-Reliability Diagnostics for Bearing RUL Prediction under Operating-Regime Shift Remaining useful life estimation using deep metric transfer learning for kernel regression.Reliability Engineering & System Safety, 212:107583, 2021
Reference 9
- Resolution
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation 93e6b379-8920-497b-b935-077582696b54 · outbound
This paper cites doi: 10.1016/j.engappai.2020.103678.
Empirical Calibration and Conditional-Reliability Diagnostics for Bearing RUL Prediction under Operating-Regime Shift doi: 10.1016/j.engappai.2020.103678
Reference 10
- Resolution
- verified exact
- arxiv_id, observed 2026-07-10T10:17:00.892903Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation b8b41e45-5d6b-4afe-9ce5-863f7a4f5640 · outbound
This paper cites month = oct, year =.
Empirical Calibration and Conditional-Reliability Diagnostics for Bearing RUL Prediction under Operating-Regime Shift month = oct, year =
Reference 11
- Resolution
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Source-reported events for the cited work
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Observation 99245eef-5429-4481-b650-43efbfc8c18a · outbound
This paper cites IEEE Access8, 199523–199538 (2020) https://doi.org/10.1109/ACCESS.
Empirical Calibration and Conditional-Reliability Diagnostics for Bearing RUL Prediction under Operating-Regime Shift IEEE Access8, 199523–199538 (2020) https://doi.org/10.1109/ACCESS
Reference 12
- Resolution
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Observation 8e111ae4-de91-443f-adca-ba313d8bc9e3 · outbound
This paper cites an unresolved cited work.
Empirical Calibration and Conditional-Reliability Diagnostics for Bearing RUL Prediction under Operating-Regime Shift Unresolved cited work
Reference 13
- Resolution
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Source-reported events for the cited work
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Observation daa6a77c-9258-43ee-9a22-b04f25925004 · outbound
This paper cites A recurrent neural network based health indicator for remaining useful life prediction of bearings.Neurocomputing, 240:98–109,.
Empirical Calibration and Conditional-Reliability Diagnostics for Bearing RUL Prediction under Operating-Regime Shift A recurrent neural network based health indicator for remaining useful life prediction of bearings.Neurocomputing, 240:98–109,
Reference 14
- Resolution
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Source-reported events for the cited work
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Observation 528abe17-70ed-4bd9-b1c3-da7d1881a83d · outbound
This paper cites Neurocomputing 240, 98–109.
Empirical Calibration and Conditional-Reliability Diagnostics for Bearing RUL Prediction under Operating-Regime Shift Neurocomputing 240, 98–109
Reference 15
- Resolution
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Source-reported events for the cited work
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Observation dfcfe598-f3e2-479b-b075-a56ed5dccecd · outbound
This paper cites an unresolved cited work.
Empirical Calibration and Conditional-Reliability Diagnostics for Bearing RUL Prediction under Operating-Regime Shift Unresolved cited work
Reference 16
- Resolution
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Source-reported events for the cited work
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Observation ab8f3413-7a68-4dbe-8509-b1cf4928a16c · outbound
This paper cites an unresolved cited work.
Empirical Calibration and Conditional-Reliability Diagnostics for Bearing RUL Prediction under Operating-Regime Shift Unresolved cited work
Reference 17
- Resolution
- verified exact
- doi, observed 2026-07-10T10:17:00.937095Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation df06d328-03ab-4796-99c1-14ff466d06e6 · outbound
This paper cites an unresolved cited work.
Empirical Calibration and Conditional-Reliability Diagnostics for Bearing RUL Prediction under Operating-Regime Shift Unresolved cited work
Reference 18
- Resolution
- verified exact
- arxiv_id, observed 2026-07-10T10:17:00.961379Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation 822e9863-ae0b-46ee-a5ff-6f564f5b5a6f · outbound
This paper cites Prognostics and health man- agement: A review from the perspectives of design, development and decision.Reliability Engineering & System Safety, 217:108063, 2022.
Empirical Calibration and Conditional-Reliability Diagnostics for Bearing RUL Prediction under Operating-Regime Shift Prognostics and health man- agement: A review from the perspectives of design, development and decision.Reliability Engineering & System Safety, 217:108063, 2022
Reference 19
- Resolution
- verified exact
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation 83be1331-d038-45ff-af6c-57bec40cd381 · outbound
This paper cites A review on machinery diagnostics and prognostics implement- ing condition-based maintenance.
Empirical Calibration and Conditional-Reliability Diagnostics for Bearing RUL Prediction under Operating-Regime Shift A review on machinery diagnostics and prognostics implement- ing condition-based maintenance
Reference 20
- Resolution
- verified exact
- doi, observed 2026-07-10T10:17:00.863895Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation a2dea05d-8c4e-44b4-8ae8-efa6fcb1518b · outbound
This paper cites Conformal prediction intervals for remaining useful lifetime estimation.International Journal of Prognostics and Health Management, 14(2), 2023.
Empirical Calibration and Conditional-Reliability Diagnostics for Bearing RUL Prediction under Operating-Regime Shift Conformal prediction intervals for remaining useful lifetime estimation.International Journal of Prognostics and Health Management, 14(2), 2023
Reference 21
- Resolution
- verified exact
- doi, observed 2026-07-10T10:17:00.890859Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation 0a1c2da0-2054-462c-ac4f-4e0c90f7fd31 · outbound
This paper cites Remaining useful lifetime estimation of bearings operating under time-varying conditions.PHM Society European Conference, 8(1):9, 2024.
Empirical Calibration and Conditional-Reliability Diagnostics for Bearing RUL Prediction under Operating-Regime Shift Remaining useful lifetime estimation of bearings operating under time-varying conditions.PHM Society European Conference, 8(1):9, 2024
Reference 22
- Resolution
- verified exact
- doi, observed 2026-07-10T10:17:00.916875Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation f4b83558-73eb-4720-a80d-0a4b6f4a6c6c · outbound
This paper cites Physics-informed machine learning.
Empirical Calibration and Conditional-Reliability Diagnostics for Bearing RUL Prediction under Operating-Regime Shift Physics-informed machine learning
Reference 23
- Resolution
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Source-reported events for the cited work
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Observation edb89b72-0d7a-4586-a15b-4c3315121b4b · outbound
This paper cites URL https://doi.org/10.1080/ 01621459.2017.1307116.
Empirical Calibration and Conditional-Reliability Diagnostics for Bearing RUL Prediction under Operating-Regime Shift URL https://doi.org/10.1080/ 01621459.2017.1307116
Reference 24
- Resolution
- metadata mismatch
- arxiv_id, observed 2026-07-10T10:17:00.917385Z
Source-reported events for the cited work
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Observation 8b9786ae-8b3b-42c0-ac98-525b6a2ec336 · outbound
This paper cites and Li, N.
Reference 25
- Resolution
- metadata mismatch
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Source-reported events for the cited work
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Observation aafd2fa9-c2f2-4fa8-ae58-e15a91007b3a · outbound
This paper cites A review on physics-informed data- driven remaining useful life prediction: Challenges and opportunities.Mechanical Systems and Signal Processing, 209:111120, 2024.
Empirical Calibration and Conditional-Reliability Diagnostics for Bearing RUL Prediction under Operating-Regime Shift A review on physics-informed data- driven remaining useful life prediction: Challenges and opportunities.Mechanical Systems and Signal Processing, 209:111120, 2024
Reference 26
- Resolution
- verified exact
- arxiv_id, observed 2026-07-10T10:17:00.962972Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation 3358037e-c1cb-4812-9f9c-0a97843278a8 · outbound
This paper cites Managing engineering systems with large state and action spaces through deep reinforcement learning.
Empirical Calibration and Conditional-Reliability Diagnostics for Bearing RUL Prediction under Operating-Regime Shift Managing engineering systems with large state and action spaces through deep reinforcement learning
Reference 27
- Resolution
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation bf1f2050-dd19-45a9-b071-d0885189e1db · outbound
This paper cites Hierarchical attention graph convolutional network to fuse multi-sensor signals for remaining useful life prediction.
Empirical Calibration and Conditional-Reliability Diagnostics for Bearing RUL Prediction under Operating-Regime Shift Hierarchical attention graph convolutional network to fuse multi-sensor signals for remaining useful life prediction
Reference 28
- Resolution
- verified exact
- arxiv_id, observed 2026-07-10T10:17:00.954338Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation bf3faa37-0fa0-48ec-aa50-54bcdca8c435 · outbound
This paper cites The emerging graph neural networks for intelligent fault diagnostics and prognostics: A guideline and a benchmark study.Mechanical Systems and Signal Processing, 168:108653, 2022.
Empirical Calibration and Conditional-Reliability Diagnostics for Bearing RUL Prediction under Operating-Regime Shift The emerging graph neural networks for intelligent fault diagnostics and prognostics: A guideline and a benchmark study.Mechanical Systems and Signal Processing, 168:108653, 2022
Reference 29
- Resolution
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation 7924a872-fcee-4339-8034-8f7ad999a8db · outbound
This paper cites A reliable bearing remaining useful life prediction method based on multi-hierarchy dynamic evaluation and uncertainty amelioration.
Empirical Calibration and Conditional-Reliability Diagnostics for Bearing RUL Prediction under Operating-Regime Shift A reliable bearing remaining useful life prediction method based on multi-hierarchy dynamic evaluation and uncertainty amelioration
Reference 30
- Resolution
- verified exact
- arxiv_id, observed 2026-07-10T10:17:00.931926Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation 594715b5-e6ac-42c8-8f46-9fc04e662c69 · outbound
This paper cites Remaining useful life estimation in prognostics using deep convolution neural networks.Reliability Engineering & System Safety, 172:1–11, 2018.
Empirical Calibration and Conditional-Reliability Diagnostics for Bearing RUL Prediction under Operating-Regime Shift Remaining useful life estimation in prognostics using deep convolution neural networks.Reliability Engineering & System Safety, 172:1–11, 2018
Reference 31
- Resolution
- verified exact
- doi, observed 2026-07-10T10:17:00.941961Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation 73c21b5d-f2da-4d1f-8e7f-fedbd950d343 · outbound
This paper cites Deep learning-based remaining useful life estimation of bearings using multi-scale feature extraction.Reliability Engineering & System Safety, 182: 208–218, 2019.
Empirical Calibration and Conditional-Reliability Diagnostics for Bearing RUL Prediction under Operating-Regime Shift Deep learning-based remaining useful life estimation of bearings using multi-scale feature extraction.Reliability Engineering & System Safety, 182: 208–218, 2019
Reference 32
- Resolution
- verified exact
- doi, observed 2026-07-10T10:17:00.914932Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation 560a287c-04bf-4b5d-b1c6-0c87db99479b · outbound
This paper cites Remaining useful life with self- attention assisted physics-informed neural network.Advanced Engineering Informatics, 58: 102195, 2023.
Empirical Calibration and Conditional-Reliability Diagnostics for Bearing RUL Prediction under Operating-Regime Shift Remaining useful life with self- attention assisted physics-informed neural network.Advanced Engineering Informatics, 58: 102195, 2023
Reference 33
- Resolution
- verified exact
- arxiv_id, observed 2026-07-10T10:17:00.951507Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation 1337cd85-9407-4e79-9fec-63c690f9002f · outbound
This paper cites Digital twin-driven remaining useful life prediction for rolling element bearing.Machines, 11(7):678, 2023.
Empirical Calibration and Conditional-Reliability Diagnostics for Bearing RUL Prediction under Operating-Regime Shift Digital twin-driven remaining useful life prediction for rolling element bearing.Machines, 11(7):678, 2023
Reference 34
- Resolution
- verified exact
- doi, observed 2026-07-10T10:17:00.981293Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation 5cac9d87-11e5-427f-aef2-ea8ccfe7ca8c · outbound
This paper cites IMS Bearings dataset.
Empirical Calibration and Conditional-Reliability Diagnostics for Bearing RUL Prediction under Operating-Regime Shift IMS Bearings dataset
Reference 35
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-07-10T10:17:01.702170Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation 997fcd30-0acd-4390-baf8-c6aba870a0d3 · outbound
This paper cites Accessed 30 April 2026.
Empirical Calibration and Conditional-Reliability Diagnostics for Bearing RUL Prediction under Operating-Regime Shift Accessed 30 April 2026
Reference 36
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-07-10T10:17:01.697375Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation e1a24186-96e8-4c30-b2b0-5699a4309dad · outbound
This paper cites PRONOSTIA: An experimental plat- form for bearings accelerated degradation tests.
Empirical Calibration and Conditional-Reliability Diagnostics for Bearing RUL Prediction under Operating-Regime Shift PRONOSTIA: An experimental plat- form for bearings accelerated degradation tests
Reference 37
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-07-10T10:17:01.690097Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation 12187887-c148-486a-9a68-5d433c22dd7f · outbound
This paper cites Scikit-learn: Machine learning in python.Journal of Machine Learning Research, 12:2825–2830, 2011.
Empirical Calibration and Conditional-Reliability Diagnostics for Bearing RUL Prediction under Operating-Regime Shift Scikit-learn: Machine learning in python.Journal of Machine Learning Research, 12:2825–2830, 2011
Reference 38
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-07-10T10:17:01.699857Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation 09cd154e-35ad-4cf1-a962-26943f75bb80 · outbound
This paper cites Raissi, P.
Reference 39
- Resolution
- verified exact
- doi, observed 2026-07-10T10:17:00.972323Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation 72ddb4e0-d776-405d-8eca-a8e943332b99 · outbound
This paper cites Prediction of bearing remaining useful life with deep convolution neural network.IEEE Access, 6:13041–13049, 2018.
Empirical Calibration and Conditional-Reliability Diagnostics for Bearing RUL Prediction under Operating-Regime Shift Prediction of bearing remaining useful life with deep convolution neural network.IEEE Access, 6:13041–13049, 2018
Reference 40
- Resolution
- malformed identifier
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation 4978f2aa-8e1d-41b5-b1f9-3a5a05fc0e23 · outbound
This paper cites Conformalized quantile regression.
Empirical Calibration and Conditional-Reliability Diagnostics for Bearing RUL Prediction under Operating-Regime Shift Conformalized quantile regression
Reference 41
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-07-10T10:17:01.693201Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation 5284c8aa-c669-4bcf-8e34-e1e6efdd8237 · outbound
This paper cites Significance, interpretation, and quantification of uncertainty in prog- nostics and remaining useful life prediction.Mechanical Systems and Signal Processing, 52–53: 228–247, 2015.
Empirical Calibration and Conditional-Reliability Diagnostics for Bearing RUL Prediction under Operating-Regime Shift Significance, interpretation, and quantification of uncertainty in prog- nostics and remaining useful life prediction.Mechanical Systems and Signal Processing, 52–53: 228–247, 2015
Reference 42
- Resolution
- verified exact
- doi, observed 2026-07-10T10:17:00.948619Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation 5735aed7-b9e1-4f4f-bf7d-edca567d6f1e · outbound
This paper cites Remaining use- ful life estimation—A review on the statistical data-driven ap- proaches.
Empirical Calibration and Conditional-Reliability Diagnostics for Bearing RUL Prediction under Operating-Regime Shift Remaining use- ful life estimation—A review on the statistical data-driven ap- proaches
Reference 43
- Resolution
- verified exact
- doi, observed 2026-07-10T10:17:00.979117Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation 2a9c1216-3c68-45f7-86ff-7fcaed446c5e · outbound
This paper cites Sikorska, Melinda Hodkiewicz, and Lin Ma.
Empirical Calibration and Conditional-Reliability Diagnostics for Bearing RUL Prediction under Operating-Regime Shift Sikorska, Melinda Hodkiewicz, and Lin Ma
Reference 44
- Resolution
- verified exact
- doi, observed 2026-07-10T10:17:00.969283Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation 0ef6aa4b-b8ba-48dc-9504-831afa4c262b · outbound
This paper cites an unresolved cited work.
Empirical Calibration and Conditional-Reliability Diagnostics for Bearing RUL Prediction under Operating-Regime Shift Unresolved cited work
Reference 45
- Resolution
- verified exact
- doi, observed 2026-07-10T10:17:00.956029Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation 9446e8a8-9a6d-44ce-a523-51a1e8e7a8f0 · outbound
This paper cites Deep separable convolutional network for remaining useful life prediction of machinery.Mechanical Systems and Signal Processing, 134: 106330, 2019.
Empirical Calibration and Conditional-Reliability Diagnostics for Bearing RUL Prediction under Operating-Regime Shift Deep separable convolutional network for remaining useful life prediction of machinery.Mechanical Systems and Signal Processing, 134: 106330, 2019
Reference 46
- Resolution
- verified exact
- arxiv_id, observed 2026-07-10T10:17:00.923370Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation 9d9ba692-c2d2-4169-8820-005c7c256121 · outbound
This paper cites A hybrid prognostics approach for estimating remaining useful life of rolling element bearings.
Empirical Calibration and Conditional-Reliability Diagnostics for Bearing RUL Prediction under Operating-Regime Shift A hybrid prognostics approach for estimating remaining useful life of rolling element bearings
Reference 47
- Resolution
- verified exact
- arxiv_id, observed 2026-07-10T10:17:00.951160Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation 5efd6f59-7153-40f4-b2c0-86fc0b502818 · outbound
This paper cites an unresolved cited work.
Empirical Calibration and Conditional-Reliability Diagnostics for Bearing RUL Prediction under Operating-Regime Shift Unresolved cited work
Reference 48
- Resolution
- verified exact
- arxiv_id, observed 2026-07-10T10:17:00.946661Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation 68da5163-fb6f-4262-9f28-be73fb5926df · outbound
This paper cites Remaining useful life prediction with uncertainty quantification based on multi-distribution fusion structure.
Empirical Calibration and Conditional-Reliability Diagnostics for Bearing RUL Prediction under Operating-Regime Shift Remaining useful life prediction with uncertainty quantification based on multi-distribution fusion structure
Reference 49
- Resolution
- verified exact
- arxiv_id, observed 2026-07-10T10:17:00.942054Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation 4100d563-1571-46a5-83aa-b74735789ceb · outbound
This paper cites an unresolved cited work.
Empirical Calibration and Conditional-Reliability Diagnostics for Bearing RUL Prediction under Operating-Regime Shift Unresolved cited work
Reference 50
- Resolution
- verified exact
- doi, observed 2026-07-10T10:17:00.943908Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation 92701e5e-95ee-44d1-bbd0-a99990229433 · outbound
This paper cites an unresolved cited work.
Empirical Calibration and Conditional-Reliability Diagnostics for Bearing RUL Prediction under Operating-Regime Shift Unresolved cited work
Reference 51
- Resolution
- verified exact
- arxiv_id, observed 2026-07-10T10:17:00.976357Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation baf82601-ea64-490a-b213-79476e26ae7b · outbound
This paper cites Mechanical Systems and Signal Processing , author =.
Empirical Calibration and Conditional-Reliability Diagnostics for Bearing RUL Prediction under Operating-Regime Shift Mechanical Systems and Signal Processing , author =
Reference 52
- Resolution
- verified exact
- doi, observed 2026-07-10T10:17:00.971433Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation 6f1bd02a-57c3-459f-b773-81993e817247 · outbound
This paper cites Prognostics and health management (PHM): Where are we and where do we (need to) go in theory and practice.Reliability Engineering & System Safety, 218:108119, 2022.
Empirical Calibration and Conditional-Reliability Diagnostics for Bearing RUL Prediction under Operating-Regime Shift Prognostics and health management (PHM): Where are we and where do we (need to) go in theory and practice.Reliability Engineering & System Safety, 218:108119, 2022
Reference 53
- Resolution
- verified exact
- arxiv_id, observed 2026-07-10T10:17:00.926950Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Pith citing papers
No inbound Pith citation observations are available.