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Digital Twin-based framework for real-time fault diagnosis and prognosis of industrial robots using unsupervised learning and real experimental data
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| Published in: | International Journal of Data Science and Analytics |
|---|---|
| Format: | Online Article RSS Article |
| Published: |
2026
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| Subjects: | |
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| _version_ | 1867301678978433027 |
|---|---|
| collection | WordPress RSS FRELIP Feed Integration |
| container_title | International Journal of Data Science and Analytics |
| description | |
| discipline_display | Big data and data science |
| discipline_facet | Big data and data science |
| format | Online Article RSS Article |
| genre | Journal Article |
| id | rss_article:82881 |
| institution | FRELIP |
| journal_source_facet | International Journal of Data Science and Analytics |
| publishDate | 2026 |
| publishDateSort | 2026 |
| record_format | rss_article |
| spellingShingle | Digital Twin-based framework for real-time fault diagnosis and prognosis of industrial robots using unsupervised learning and real experimental data Big data and data science General Big data and data science |
| sub_discipline_display | General |
| sub_discipline_facet | General |
| subject_display | Big data and data science General Big data and data science Big data and data science General Big data and data science |
| subject_facet | Big data and data science General Big data and data science |
| title | Digital Twin-based framework for real-time fault diagnosis and prognosis of industrial robots using unsupervised learning and real experimental data |
| title_auth | Digital Twin-based framework for real-time fault diagnosis and prognosis of industrial robots using unsupervised learning and real experimental data |
| title_full | Digital Twin-based framework for real-time fault diagnosis and prognosis of industrial robots using unsupervised learning and real experimental data |
| title_fullStr | Digital Twin-based framework for real-time fault diagnosis and prognosis of industrial robots using unsupervised learning and real experimental data |
| title_full_unstemmed | Digital Twin-based framework for real-time fault diagnosis and prognosis of industrial robots using unsupervised learning and real experimental data |
| title_short | Digital Twin-based framework for real-time fault diagnosis and prognosis of industrial robots using unsupervised learning and real experimental data |
| title_sort | digital twin-based framework for real-time fault diagnosis and prognosis of industrial robots using unsupervised learning and real experimental data |
| topic | Big data and data science General Big data and data science |
| url | https://link.springer.com/article/10.1007/s41060-026-01164-z |