# Fault detection and diagnosis for rotating machinery: A model based on convolutional LSTM, Fast Fourier and continuous wavelet transforms

**Type:** Papers  
**Canonical URL:** https://scholariq.org/papers/fault-detection-and-diagnosis-for-rotating-machinery-a-model-based-on/

## Facts

| Field | Value |
| --- | --- |
| Author Names | Masoud Jalayer,Carlotta Orsenigo,Carlo Vercellis |
| Citations | 375 |
| DOI | 10.1016/j.compind.2020.103378 |
| Fields | Chemistry,Engineering |
| Open Access | false |
| OA Status | closed |
| OpenAlex ID | https://openalex.org/W3116250684 |
| Type | article |
| Year | 2020 |

## Paper authors

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

## Paper journal

- [Computers in Industry](https://scholariq.org/journals/computers-in-industry/)

## 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/)
- [Fault Detection and Control Systems](https://scholariq.org/topics/fault-detection-and-control-systems/)
- [Spectroscopy and Chemometric Analyses](https://scholariq.org/topics/spectroscopy-and-chemometric-analyses/)

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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.