# ICGL-GNN

**Repository Path**: yunfeixie/ICGL-GNN

## Basic Information

- **Project Name**: ICGL-GNN
- **Description**: 第一份科研工作，使用基于信息论的因果图神经网络提升工业故障分类的准确率和可解释性
- **Primary Language**: Unknown
- **License**: Not specified
- **Default Branch**: master
- **Homepage**: None
- **GVP Project**: No

## Statistics

- **Stars**: 2
- **Forks**: 0
- **Created**: 2024-12-04
- **Last Updated**: 2025-08-20

## Categories & Tags

**Categories**: Uncategorized

**Tags**: None

## README

# Information-based Gradient Enhanced Causal Learning Graph Neural Network for Fault Diagnosis of Complex Industrial Processes

## 实验环境

请按照此要求设置环境。通常，您可能需要运行以下命令：

```shell
conda create -n IGCL_GNN python=3.9
conda activate IGCL_GNN
conda install pytorch cudatoolkit=11.6 -c pytorch
conda install opencv scikit-learn networkx pandas tqdm matplotlib seaborn
pip install torch==1.12.1
pip install torch-scatter==2.1.0 -f https://pytorch-geometric.com/whl/torch-1.12.1+cu116.html
pip install torch-sparse==0.6.16 -f https://pytorch-geometric.com/whl/torch-1.12.1+cu116.html
pip install torch-cluster==1.6.0 -f https://pytorch-geometric.com/whl/torch-1.12.1+cu116.html
pip install torch-spline-conv==1.2.1 -f https://pytorch-geometric.com/whl/torch-1.12.1+cu116.html
pip install torch-geometric==2.4.0
```

## 数据集下载

**三相流动设施数据：** 克兰菲尔德大学的三相流动设施（TFF）设计用于控制加压系统，并测量水流量、油流量和空气流量。该设施中共有24个传感器，用于测量系统不同关键位置的压力、流速、密度和温度。

**下载地址：**

[A Benchmark Case for Statistical Process Monitoring - Cranfield Multiphase Flow Facility - File Exchange - MATLAB Central (mathworks.com)](https://www.mathworks.com/matlabcentral/fileexchange/50938-a-benchmark-case-for-statistical-process-monitoring-cranfield-multiphase-flow-facility)

## 运行方式

对模型进行训练和测试，执行以下指令：

```shell
python main_real.py --model CausalGAT --dataset TFF --layers 3 --epochs 100 --folds 10 --lr 0.001 --n 0.5 --e 0.5 --train_model mgda 
```