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Fault diagnosis of rolling bearing with uneven data distribution based on continuous wavelet transform and deep convolution generated adversarial network
Research article (Journal of the Brazilian Society of Mechanical Sciences and Engineering, 2021) · cited 22× · AI/ML
Fault diagnosis of rolling bearing with uneven data distribution based on continuous wavelet transform and deep convolution generated adversarial network
Summary
Fault diagnosis of rolling bearing with uneven data distribution based on continuous wavelet transform and deep convolution generated adversarial network is a scholarly article[1].
Key Facts
Fault diagnosis of rolling bearing with uneven data distribution based on continuous wavelet transform and deep convolution generated adversarial network's instance of is recorded as scholarly article[2].
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APA4ort.xyz Knowledge Graph. (2026). Fault diagnosis of rolling bearing with uneven data distribution based on continuous wavelet transform and deep convolution generated adversarial network. Retrieved May 24, 2026, from https://4ort.xyz/entity/fault-diagnosis-of-rolling-bearing-with-uneven-data-distribution-based-on-continuous-wavelet-transform-and-deep-convolut
MLA“Fault diagnosis of rolling bearing with uneven data distribution based on continuous wavelet transform and deep convolution generated adversarial network.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/fault-diagnosis-of-rolling-bearing-with-uneven-data-distribution-based-on-continuous-wavelet-transform-and-deep-convolut.
BibTeX@misc{4ortxyz_fault-diagnosis-of-rolling-bearing-with-uneven-data-distribution-based-on-continuous-wavelet-transform-and-deep-convolut_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{Fault diagnosis of rolling bearing with uneven data distribution based on continuous wavelet transform and deep convolution generated adversarial network}}, year = {2026}, url = {https://4ort.xyz/entity/fault-diagnosis-of-rolling-bearing-with-uneven-data-distribution-based-on-continuous-wavelet-transform-and-deep-convolut}, note = {Accessed: 2026-05-24}}
LLM promptAccording to 4ort.xyz Knowledge Graph (aggregator of Wikidata, Wikipedia, and authoritative open-data sources): Fault diagnosis of rolling bearing with uneven data distribution based on continuous wavelet transform and deep convolution generated adversarial network — https://4ort.xyz/entity/fault-diagnosis-of-rolling-bearing-with-uneven-data-distribution-based-on-continuous-wavelet-transform-and-deep-convolut (retrieved 2026-05-24)
