# Machine Fault Diagnosis Techniques

**Type:** Topics  
**Canonical URL:** https://scholariq.org/topics/machine-fault-diagnosis-techniques-2/

## Facts

| Field | Value |
| --- | --- |
| Citations | 1,126,279 |
| Description | This cluster of papers focuses on machine fault diagnosis and prognostics using methods such as Empirical Mode Decomposition, wavelet transform, and deep learning. It covers topics like condition monitoring, vibration analysis, and remaining useful life estimation for rotating machinery. The research explores the application of machine learning techniques, neural networks, and signal processing in fault detection and health management of various mechanical systems. |
| Domain | Physical Sciences |
| Field | Engineering |
| OpenAlex ID | https://openalex.org/T10220 |
| Works | 69,398 |

## Topic researchers

Showing 12 of 20.

- [M. Wąs](https://scholariq.org/researchers/m-was/)
- [B. L. Swinkels](https://scholariq.org/researchers/b-l-swinkels/)
- [Zidong Wang](https://scholariq.org/researchers/zidong-wang/)
- [Stéphane Mallat](https://scholariq.org/researchers/stephane-mallat/)
- [Zhihui Du](https://scholariq.org/researchers/zhihui-du/)
- [Ponnuthurai Nagaratnam Suganthan](https://scholariq.org/researchers/ponnuthurai-nagaratnam-suganthan/)
- [Bhim Singh](https://scholariq.org/researchers/bhim-singh/)
- [Ingrid Daubechies](https://scholariq.org/researchers/ingrid-daubechies/)
- [Michael Pecht](https://scholariq.org/researchers/michael-pecht/)
- [Norden E. Huang](https://scholariq.org/researchers/norden-e-huang/)
- [Huijun Gao](https://scholariq.org/researchers/huijun-gao/)
- [Richard G. Baraniuk](https://scholariq.org/researchers/richard-g-baraniuk/)

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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.