Metadata-Version: 2.1
Name: phm-feature
Version: 0.1.1
Summary: time-freq feature from signal for phm purpose
Home-page: UNKNOWN
Author: QinHaiNing
Author-email: 2364839934@qq.com
License: UNKNOWN
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
        
        
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Description-Content-Type: text/markdown
