ecstayalive / SparrowLinks
This is a project for mechanical fault detection. The reason why it is called cute little bird may be because the eyesight of birds is particularly good, and they can detect small bugs. Besides, they are cute too. In the current version, we have tested some planetary gearbox vibration data in the lab, and there are 8 error types in total. And us…
☆11Updated last year
Alternatives and similar repositories for Sparrow
Users that are interested in Sparrow are comparing it to the libraries listed below
Sorting:
- Vibration Analysis for Fault Detection using STFT, FFT in Python☆22Updated 2 years ago
- 帮同学做的轴承故障检测的代码☆18Updated 2 years ago
- Lab-scale Vibration Analysis Dataset and Its Machine Learning Methods☆25Updated 3 weeks ago
- The relevant codes and more comparison results of "Physics-informed machine learning for tool wear monitoring".☆16Updated 3 years ago
- This work presents a multi-feature fusion neural network (MSFN) comprised of two inception layer-type multiple channel networks (MCN) for…☆19Updated 4 years ago
- Capsule network for fault diagnosis (胶囊网络用于故障诊断)☆31Updated 2 years ago
- Interpretable Physics-informed Domain Adaptation Paradigm for Cross-machine Transfer Fault Diagnosis (故障诊断)☆33Updated last year
- 轴承有3种故障:外圈故障,内圈故障,滚珠故障,外加正常的工作状态。如表1所示,结合轴承的3种直径(直径1,直径2,直径3),轴承的工作状态有10类☆32Updated 6 years ago
- 一种用于复杂工况机械故障检测的GNN方法☆46Updated last year
- ☆39Updated 3 years ago
- Python code for TCTL method☆12Updated last year
- 基于LabVIEW,可由故障齿轮箱振动信号生成时域图、频谱图、倒频谱图和包络谱图☆16Updated 5 years ago
- 基于机器学习的机械故障诊断☆18Updated last year
- Real time tool wear monitoring method based on a TCN model for PHM-2010 Dataset.☆11Updated 2 years ago
- A fault diagnosis method for rotating machinery based on CNN with mixed information☆29Updated last year
- 论文“时变转速下基于改进图注意力网络的轴承半监督故障诊断”源码☆28Updated 3 years ago
- 采用一种包含加权水平可见图(WHVG)的图卷积网络(GCN),对采样的轴承震动时间序列数据分析,进行滚动轴承故障诊断。其中,对HVG中两节点的边,以节点距离的倒数作为权重进行加权,以削弱噪声节点对其他距离较远节点的影响。☆41Updated 2 years ago
- Code for our paper "Domain adaptive transfer learning for fault diagnosis." 2019 Prognostics and System Health Management Conference (PHM…☆22Updated 3 years ago
- Innovative bearing fault diagnosis using SST algorithm for time-frequency images. Accurately transform signals into efficient time-freque…☆21Updated last year
- MSTDA☆11Updated 8 months ago
- 基于小波时频图与 Swin Transformer 的轴承故障诊断方法☆42Updated last year
- Deep learning models (RNN & LSTM & WaveNet) for predicting the remaining useful life of rolling element bearings using time series health…☆14Updated 3 months ago
- The code of our work “Mixed attention network for source-free domain adaptation in bearing fault diagnosis”.☆7Updated last year
- 1 提出了一种新的相似度损失(SimL),用于增大类间差异同时减小类内差异;2 SimL+CE优化CNN;3 基于电信号诊断轴承故障☆13Updated last year
- Tool wear monitoring plays an important role in improving product quality and machining efficiency of high-speed milling. As a typical da…☆8Updated 3 years ago
- Hongchun-Qu / Research-and-Application-of-Bearing-Fault-Diagnosis-Based-on-Deep-Encoder-Classification-Model☆13Updated 3 years ago
- xLSTM: Extended Long Short-Term Memory for Intelligent Fault Diagnosis of Rolling Bearings☆30Updated last year
- PyTorch Implementation of "Understanding and Learning Discriminant Features based on Multiattention 1DCNN for Wheelset Bearing Fault Diag…☆27Updated last year
- Thin-walled parts 2023 dataset released from Shandong University☆12Updated last year
- FWA-DBN-ELM fault diagnosis 故障诊断 烟花算法优化DBN-ELM的故障诊断☆29Updated 2 years ago