# Fault Detection and Diagnosis with Imbalanced and Noisy Data: A Hybrid Framework for Rotating Machinery

**Type:** Papers  
**Canonical URL:** https://scholariq.org/papers/fault-detection-and-diagnosis-with-imbalanced-and-noisy-data-a-hybrid-framework/

## Facts

| Field | Value |
| --- | --- |
| Author Names | Masoud Jalayer,Amin Kaboli,Carlotta Orsenigo,Carlo Vercellis |
| Citations | 42 |
| DOI | 10.3390/machines10040237 |
| Fields | Computer Science,Engineering |
| Open Access | true |
| OA Status | gold |
| OA URL | https://www.mdpi.com/2075-1702/10/4/237/pdf?version=1648451856 |
| OpenAlex ID | https://openalex.org/W4220949726 |
| Type | article |
| Year | 2022 |

## Paper authors

- [Masoud Jalayer](https://scholariq.org/researchers/masoud-jalayer/)

## Paper primary topic

- [Machine Fault Diagnosis Techniques](https://scholariq.org/topics/machine-fault-diagnosis-techniques/)

## Paper topics

- [Machine Fault Diagnosis Techniques](https://scholariq.org/topics/machine-fault-diagnosis-techniques/)
- [Machine Learning and ELM](https://scholariq.org/topics/machine-learning-and-elm/)
- [Fault Detection and Control Systems](https://scholariq.org/topics/fault-detection-and-control-systems/)

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Source: ScholarIQ — public research metadata, principally OpenAlex. See https://scholariq.org/sources/ for provenance and https://scholariq.org/methodology/ for what these figures mean.