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time-freq feature from signal for phm purpose

Project description

phm-feature

介绍

  • phm中的特征抽取任务
  • 抽取振动信号中的各类时、频域业务特征值

软件架构

软件架构说明

.. code-block:: shell

.
├── build
│   ├── bdist.linux-x86_64
│   └── lib
│       └── phm_feature
│           └── __init__.py
├── dist
│   ├── phm_feature-0.0.2-py3-none-any.whl
│   └── phm_feature-0.0.2.tar.gz
├── LICENSE
├── phm_feature
│   ├── __init__.py
├── phm_feature.egg-info
│   ├── dependency_links.txt
│   ├── PKG-INFO
│   ├── SOURCES.txt
│   └── top_level.txt
├── README.md
├── setup.py
└── test.py

安装教程

  • 使用pip进行安装

.. code-block:: python

pip install phm-feature

使用说明

获得振动信号的特征值


.. code-block:: python

    import phm_feature
    from phm_feature import *
    enable_parallel(processnum=None) 开启多线程模式
    disable_parallel() 开启单线程模式
    feature_t(data) 获取时间域特征
    feature_f 获取频率域特征
    fft(data, 50) 快速离散傅里叶变换
    power(data, 50) 功率谱
    ifft(data, 50) 快速离散逆傅里叶变换
    cepstrum(data, 50) 倒谱
    envelope(data) 包络谱
    window(data, 'hamming') 加窗-汉明窗
    divide(data, 50, 25) 分帧

参与贡献
--------------------------------------------------------------------------------------------

2022-07-04 v0.0.1
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

pypi上传初版本

pypi上传phm-feature初版本


2022-07-04 v0.0.2
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

新增多线程模式


phm-feature
=========================================================================

介绍
-------------------------------------------------------------------------

使用torch torchaudio 构建PHM特征抽取功能层

功能层介绍
-----------------------------------------------------------------------------

torchphm.layers 将phm固定使用的数据操作,固化为如下层:

.. code-block:: python

    1. STFT 离散傅立叶变换
    2. Spectrogram 谱图
    3. MelFilterbank mel譜过滤
    4. AmplitudeToDb 幅度取分贝
    5. TimeStretch 变速不变调
    6. ComplexNorm 复数输出取模'范数'
    7. ApplyFilterbank 过滤器应用

应用场景
------------------------------------------------------------------------------------

.. note::

    组合上述功能层,实现不同场景

.. code-block:: shell

    1. STFT
        分帧==>加窗==>短时离散傅立叶变换

    2. "变速不变调" Time scale modification
        详细见 https://zhuanlan.zhihu.com/p/337193578
        用于声谱图压缩、扩张处理,供后续分析

    3. 梅尔mel谱转换
       对于语谱图进行mel谱转换

    4. HPSS
        中值滤波,过滤出频率的谐波分量与冲击分量
        为什么中值滤波,可以过滤出"数据轮廓"及发现"谐波分量和冲击分量",参见
        https://blog.csdn.net/qq_38131594/article/details/80758567


软件结构说明
-----------------------------------------------------------------------------------

.. code-block:: shell

    .
    ├── dist
    │   ├── torchphm-1.1.7.tar.gz
    │   └── torchphm-1.1.8.tar.gz
    ├── draw
    │   ├── draw_functional.py
    │   ├── draw_layers.py
    │   ├── draw_torchphm_layers.ipynb
    │   ├── torchphm -> ../torchphm
    │   └── Untitled.ipynb
    ├── examples_torchphm.ipynb
    ├── README.md
    ├── setup.cfg
    ├── setup.py
    ├── tests
    │   ├── test_functional.py
    │   └── test_layers.py
    ├── torchphm
    │   ├── beta_hpss.py
    │   ├── functional.py
    │   ├── __init__.py
    │   ├── layers.py
    └── torchphm.egg-info

======================== =========== 
dist                     pypi上传包
======================== =========== 
draw                     画图
examples_torchphm.ipynb  应用例程
tests                    测试文件
torchphm                 实现源码
======================== =========== 

安装教程
--------------------------------------------------------------------------------------

.. code-block:: python 

    pip install phm-feature



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