Omkar2118/datasets huggingface dataset:
M²ConceptBase

M²ConceptBase is a concept-centric multimodal knowledge base designed to bridge the gap between visual and linguistic semantics. It features 951K images and 152K concepts, with each concept linked to an average of 6.27 images and a detailed textual description.

Introducing paper: M^2ConceptBase: A Fine-Grained Aligned Concept-Centric Multimodal Knowledge Base
Centrifugal Pump Fault Detection

## Dataset Overview

The dataset used for training and testing consists of vibration signals for six pump conditions:

| Fault Type        | Training Samples | Testing Samples | Flow Range (L/min) |
|------------------|-----------------|----------------|------------------|
| Healthy          | 1460             | 360            | 170 - 220        |
| Low Flow Rate    | 1120             | 280            | 80 - 120         |
| Cavitation       | 1440             | 360            | 120 - 170        |
| Major Defect     | 1440             | 360            | 150 - 200        |
| Minor Defect     | 1040             | 360            | 130 - 160        |
| Crack            | 1280             | 320            | 150 - 200        |

Introducing paper: An Intelligent Approach to Detecting Novel Fault Classes for Centrifugal Pumps Based on Deep CNNs and Unsupervised Methods