Transformer-Based Bearing Fault Detection using Temporal Decomposition Attention Mechanism | Paper Citation Record

Observation 70853041-403d-44a7-a7b2-64380dd186a9 · outbound

This paper cites an unresolved cited work.

Transformer-Based Bearing Fault Detection using Temporal Decomposition Attention Mechanism Unresolved cited work

Reference 1

Resolution: unresolved; raw_fallback, observed 2026-08-11T15:11:54.603830Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation ee289fec-907c-4a01-9136-552c99e7b9d4 · outbound

This paper cites The CWRU dataset is a prominent benchmark for assessing fault detection techniques.

Transformer-Based Bearing Fault Detection using Temporal Decomposition Attention Mechanism The CWRU dataset is a prominent benchmark for assessing fault detection techniques

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T15:11:54.579342Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 37343c9e-5909-4f6f-a9a5-2210a039b94e · outbound

This paper cites It begins with an explanation of the HEMA for feature extraction, followed by a detailed description of the TDA mechanism.

Transformer-Based Bearing Fault Detection using Temporal Decomposition Attention Mechanism It begins with an explanation of the HEMA for feature extraction, followed by a detailed description of the TDA mechanism

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T15:11:54.500232Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 95812362-3944-4c7d-b033-c55d536f050e · outbound

This paper cites Each subsection offers a detailed evaluation of the models' efficiency, dependability, and capability to handle the challenges of bearing fault detection.

Transformer-Based Bearing Fault Detection using Temporal Decomposition Attention Mechanism Each subsection offers a detailed evaluation of the models' efficiency, dependability, and capability to handle the challenges of bearing fault detection

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T15:11:54.474046Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 1f77e05a-1ad2-4741-8ce3-eda899db57dc · outbound

This paper cites an unresolved cited work.

Transformer-Based Bearing Fault Detection using Temporal Decomposition Attention Mechanism Unresolved cited work

Reference 5

Resolution: unresolved; raw_fallback, observed 2026-08-11T15:11:54.443753Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation ce8e9ed2-1046-4f9c-8b95-bfae536ab9f7 · outbound

This paper cites Fault diagnosis of hydro -turbine via the incorporation of bayesian algorithm optimized CNN-LSTM neural network,.

Transformer-Based Bearing Fault Detection using Temporal Decomposition Attention Mechanism Fault diagnosis of hydro -turbine via the incorporation of bayesian algorithm optimized CNN-LSTM neural network,

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T15:11:54.275640Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 62921e0c-09f5-45af-b922-9e8349495308 · outbound

This paper cites Towards better benchmarking using the CWRU bearing fault dataset,.

Transformer-Based Bearing Fault Detection using Temporal Decomposition Attention Mechanism Towards better benchmarking using the CWRU bearing fault dataset,

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T15:11:54.420182Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 5286bb38-d10d-4a34-8565-bf8f520b39f5 · outbound

This paper cites Bearing fault detection and diagnosis using case western reserve university dataset with deep learning approaches: A review,.

Transformer-Based Bearing Fault Detection using Temporal Decomposition Attention Mechanism Bearing fault detection and diagnosis using case western reserve university dataset with deep learning approaches: A review,

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T15:11:54.399191Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation b7658fb2-abd1-43ed-ab89-ed82c997b3a0 · outbound

This paper cites Extracting features from time series,.

Transformer-Based Bearing Fault Detection using Temporal Decomposition Attention Mechanism Extracting features from time series,

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T15:11:54.369497Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation b9ba0471-aaca-4766-a302-e02325d4ed14 · outbound

This paper cites Time domain synchronous moving average and its application to gear fault detection,.

Transformer-Based Bearing Fault Detection using Temporal Decomposition Attention Mechanism Time domain synchronous moving average and its application to gear fault detection,

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T15:11:54.346666Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 3ad13927-bc7f-4f7f-a69d-c9c58aebff9d · outbound

This paper cites End -to-end CNN+ LSTM deep learning approach for bearing fault diagnosis,.

Transformer-Based Bearing Fault Detection using Temporal Decomposition Attention Mechanism End -to-end CNN+ LSTM deep learning approach for bearing fault diagnosis,

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T15:11:54.309797Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation fdeb2f3a-9f9b-4641-9ddc-ebc8bbc7deb1 · outbound

This paper cites A study on the evaluation of tokenizer performance in natural language processing,.

Transformer-Based Bearing Fault Detection using Temporal Decomposition Attention Mechanism A study on the evaluation of tokenizer performance in natural language processing,

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T15:11:54.087219Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation f671e1dc-665d-4368-924b-d4debeb8cc21 · outbound

This paper cites Fault diagnosis using variational autoencoder GAN and focal loss CNN under unbalanced data,.

Transformer-Based Bearing Fault Detection using Temporal Decomposition Attention Mechanism Fault diagnosis using variational autoencoder GAN and focal loss CNN under unbalanced data,

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T15:11:54.254254Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 06dc4dce-de3c-4176-97ee-652b2413a6a3 · outbound

This paper cites Battery fault diagnosis and failure prognosis for electric vehicles using spatio-temporal transformer networks,.

Transformer-Based Bearing Fault Detection using Temporal Decomposition Attention Mechanism Battery fault diagnosis and failure prognosis for electric vehicles using spatio-temporal transformer networks,

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T15:11:54.211978Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 0e053468-882a-417f-a7f3-f543216180be · outbound

This paper cites Twins transformer: Cross-attention based two- branch transformer network for rotating bearing fault diagnosis,.

Transformer-Based Bearing Fault Detection using Temporal Decomposition Attention Mechanism Twins transformer: Cross-attention based two- branch transformer network for rotating bearing fault diagnosis,

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T15:11:54.186133Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 1b73757d-eef1-4f80-98a1-cc437da0e19d · outbound

This paper cites Compound fault diagnosis for industrial robots based on dual-transformer networks,.

Transformer-Based Bearing Fault Detection using Temporal Decomposition Attention Mechanism Compound fault diagnosis for industrial robots based on dual-transformer networks,

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T15:11:54.143560Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 83c746a9-28f4-4f41-8f0f-af9bc893a9b2 · outbound

This paper cites Deep learning attention mechanism in medical image analysis: Basics and beyonds,.

Transformer-Based Bearing Fault Detection using Temporal Decomposition Attention Mechanism Deep learning attention mechanism in medical image analysis: Basics and beyonds,

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T15:11:54.119784Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation abb89079-e2c6-43aa-9635-9104359c45a7 · outbound

This paper cites an unresolved cited work.

Transformer-Based Bearing Fault Detection using Temporal Decomposition Attention Mechanism Unresolved cited work

Reference 18

Resolution: unresolved; raw_fallback, observed 2026-08-11T15:11:54.553060Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation d3dcd310-be38-4ae3-9a1c-d118a32c8f90 · outbound

This paper cites Vision Transformer Based Tokenization for Enhanced Breast Cancer Histopathological Images Classification,.

Transformer-Based Bearing Fault Detection using Temporal Decomposition Attention Mechanism Vision Transformer Based Tokenization for Enhanced Breast Cancer Histopathological Images Classification,

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T15:11:54.052329Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 89568873-a8fe-45bc-a0d5-4b08fb59e2ba · outbound

This paper cites STARNet: Sensor Trustworthiness and Anomaly Recognition via Approximated Likelihood Regret for Robust Edge Autonomy.

Transformer-Based Bearing Fault Detection using Temporal Decomposition Attention Mechanism STARNet: Sensor Trustworthiness and Anomaly Recognition via Approximated Likelihood Regret for Robust Edge Autonomy

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-11T15:11:53.070814Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3d8c886f-80ed-41f6-a2dc-ea42ad958746 · outbound

This paper cites Deep prediction on financial market sequence for enhancing economic policies,.

Transformer-Based Bearing Fault Detection using Temporal Decomposition Attention Mechanism Deep prediction on financial market sequence for enhancing economic policies,

Reference 21

Resolution: verified exact; doi, observed 2026-08-11T15:11:53.315670Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation f53e67f8-98ea-4bb5-a639-f3975c8ed295 · outbound

This paper cites Exploring Cross -model Neuronal Correlations in the Context of Predicting Model Performance and Generalizability,.

Transformer-Based Bearing Fault Detection using Temporal Decomposition Attention Mechanism Exploring Cross -model Neuronal Correlations in the Context of Predicting Model Performance and Generalizability,

Reference 22

Resolution: verified exact; raw_fallback, observed 2026-08-11T15:11:53.614114Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 95086ceb-1b0f-4d5f-88d1-8cc8a09e6465 · outbound

This paper cites Application of recurrent neural network to mechanical fault diagnosis: a review,.

Transformer-Based Bearing Fault Detection using Temporal Decomposition Attention Mechanism Application of recurrent neural network to mechanical fault diagnosis: a review,

Reference 23

Resolution: verified exact; doi, observed 2026-08-11T15:11:53.290058Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 38532aa0-cb0c-4ba5-8e35-196adbe3f991 · outbound

This paper cites Fault diagnosis of rotating machinery based on recurrent neural networks,.

Transformer-Based Bearing Fault Detection using Temporal Decomposition Attention Mechanism Fault diagnosis of rotating machinery based on recurrent neural networks,

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T15:11:54.028280Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 88bd1bc0-1947-4dfd-9fa6-d8f14ca4bb67 · outbound

This paper cites A novel fault diagnosis method based on CNN and LSTM and its application in fault diagnosis for complex systems,.

Transformer-Based Bearing Fault Detection using Temporal Decomposition Attention Mechanism A novel fault diagnosis method based on CNN and LSTM and its application in fault diagnosis for complex systems,

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T15:11:54.006783Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 8f779465-1df1-43d8-8275-ead18098f3d1 · outbound

This paper cites A power transformer fault prediction method through temporal convolutional network on dissolved gas chromatography data,.

Transformer-Based Bearing Fault Detection using Temporal Decomposition Attention Mechanism A power transformer fault prediction method through temporal convolutional network on dissolved gas chromatography data,

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T15:11:53.971984Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation e36258a6-9bb4-4f98-ae67-701328bb2cb5 · outbound

This paper cites An innovative transformer neural network for fault detection and classification for photovoltaic modules,.

Transformer-Based Bearing Fault Detection using Temporal Decomposition Attention Mechanism An innovative transformer neural network for fault detection and classification for photovoltaic modules,

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T15:11:53.941420Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 953a80ef-7939-428f-aa6d-ef6830788d1a · outbound

This paper cites Variational attention-based interpretable transformer network for rotary machine fault diagnosis,.

Transformer-Based Bearing Fault Detection using Temporal Decomposition Attention Mechanism Variational attention-based interpretable transformer network for rotary machine fault diagnosis,

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T15:11:53.915705Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation f058a33f-d30e-493b-9bb0-19ea480955b9 · outbound

This paper cites CNN -based transformer model for fault detection in power system networks,.

Transformer-Based Bearing Fault Detection using Temporal Decomposition Attention Mechanism CNN -based transformer model for fault detection in power system networks,

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T15:11:53.892323Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 003f58b6-866a-4b81-a021-3201aa8b7e9f · outbound

This paper cites A planetary gearbox fault diagnosis method based on time-series imaging feature fusion and a transformer model,.

Transformer-Based Bearing Fault Detection using Temporal Decomposition Attention Mechanism A planetary gearbox fault diagnosis method based on time-series imaging feature fusion and a transformer model,

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T15:11:53.860783Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation a6c23fa3-d130-4db7-b052-4f67199ad907 · outbound

This paper cites Bearing fault detection and diagnosis using case western reserve university dataset with deep learning approaches: A review,.

Transformer-Based Bearing Fault Detection using Temporal Decomposition Attention Mechanism Bearing fault detection and diagnosis using case western reserve university dataset with deep learning approaches: A review,

Reference 31

Resolution: unresolved; no resolver link, observed 2026-08-11T15:11:53.169829Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 373e42b4-14b5-4c4b-900b-a898cf7679ae · outbound

This paper cites Machine learning based bearing fault diagnosis using the case western reserve university data: A review,.

Transformer-Based Bearing Fault Detection using Temporal Decomposition Attention Mechanism Machine learning based bearing fault diagnosis using the case western reserve university data: A review,

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T15:11:53.820179Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation a4cd0fe8-9dbb-42c8-a0b9-01cefe5080ee · outbound

This paper cites Enhanced Fault Detection in Bearings Using Machine Learning and Raw Accelerometer Data: A Case Study Using the Case Western Reserve University Dataset,.

Transformer-Based Bearing Fault Detection using Temporal Decomposition Attention Mechanism Enhanced Fault Detection in Bearings Using Machine Learning and Raw Accelerometer Data: A Case Study Using the Case Western Reserve University Dataset,

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T15:11:53.792594Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 39c6c3dc-5562-4469-bdf6-a5d1539b015e · outbound

This paper cites Hull, Active Investing.

Transformer-Based Bearing Fault Detection using Temporal Decomposition Attention Mechanism Hull, Active Investing

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T15:11:53.769847Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 51a749a6-add0-4b99-9ddc-01a61d6a5673 · outbound

This paper cites Moving convolutional neural networks to embedded systems: the alexnet and VGG -16 case,.

Transformer-Based Bearing Fault Detection using Temporal Decomposition Attention Mechanism Moving convolutional neural networks to embedded systems: the alexnet and VGG -16 case,

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T15:11:53.736141Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 8febe963-49e1-49e9-8ed7-d2638ba30ec3 · outbound

This paper cites A feature transferring fault diagnosis based on WPDR, FSWT and GoogLeNet,.

Transformer-Based Bearing Fault Detection using Temporal Decomposition Attention Mechanism A feature transferring fault diagnosis based on WPDR, FSWT and GoogLeNet,

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T15:11:53.709223Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation e8867093-bc2d-424a-a19e-a77f71fefca1 · outbound

This paper cites A transfer convolutional neural network for fault diagnosis based on ResNet-50,.

Transformer-Based Bearing Fault Detection using Temporal Decomposition Attention Mechanism A transfer convolutional neural network for fault diagnosis based on ResNet-50,

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T15:11:53.673080Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 21fdbe3c-f52d-40cd-84f6-910445b1dfc6 · outbound

This paper cites Motor fault diagnosis algorithm based on wavelet and attention mechanism,.

Transformer-Based Bearing Fault Detection using Temporal Decomposition Attention Mechanism Motor fault diagnosis algorithm based on wavelet and attention mechanism,

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T15:11:53.646251Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Coverage vector

Reference resolution

Outbound references

Pith citing papers