This function can evaluate transient phenomena that were difficult to capture by FFT analysis, and display clearly time change of the frequency component while maintaining its frequency resolution . The OS-0527 is equipped with STFT (Short Time Fourier Transform) and Wavelet transform.

The Short-time Fourier TransformFourier analysis is able to be performed with any points (frame length and interval) set by the user. In other words, the user can set any cutting out time length, so this method is effective for observing spectrum changes over an extremely short time.

The wavelet transform is an analysis method that enables simultaneous analysis of temporal fluctuation and spatial transition of complicated waveforms such as a sudden or unstationary sound or vibration. The analysis time length is changed depending on the frequency in this method. It brings a good balance between time and frequency, so this method is effective for capturing the analysis result as a whole.

Item | STFT | Wavelet Transform |
---|---|---|

Time resolution | constant | High frequency ：finer Low frequency：coarse |

Frequency resolution | constant | High frequency ：coarse Low frequency：finer |

Advantages | Stable results can be obtained by extending the FFT. | The time resolution and the frequency resolution are good balance. |

Disadvantages | If the time resolution and frequency resolution are increased, the calculation time and the data amount will increase. | Only approximate frequency is obtained. |

By using the short-time Fourier transform, the frequency resolution and the time resolution are improved. Thus, transient vibration waveforms can be analyzed, and detailed analysis that cannot be performed with normal FFT analysis due to coarse time resolution is available.

Model | Product | Qty |
---|---|---|

OS-5100 | Platform | 1 |

OS-0522 | FFT Analysis function | 1 |

OS-0527 | Time Frequency Analysis function | 1 |

*Sound recording equipment (High performance Sound Level Meter, FFT analyzer, etc.) is required. |

It is an example of analyzing the impact sound of a golf club as an example of the frequency changing in a short time. Since the time length of the target signal is short, the change in the spectrum becomes unclear with respect to the time change in the FFT analysis (left figure). While, by using STFT, even if the frame length is the same, the frame interval and window length can be set at any points and the time change of the frequency component that changes in a short time is clearly displayed while maintaining the frequency resolution. (right figure).

Model | Product | Qty |
---|---|---|

OS-5100 | Platform | 1 |

OS-0522 | FFT Analysis function | 1 |

OS-0527 | Time Frequency Analysis function | 1 |

*Sound recording equipment (High performance Sound Level Meter, FFT analyzer, etc.) is required. |

This is an example of analyzing transient noise generated from a machine tool. The time length of abnormal sounds is very short and their frequency components are seen over a wide range. In the FFT analysis, the frame length cannot take long enough to obtain the resolution of low frequency components. While, by using the wavelet transform, it is possible to comprehensively capture time and frequency information. In this example, the components (low frequency components) in the red circles that are not seen in the FFT analysis can be seen in the right figure. In this way, the wavelet transform raises the time resolution for high frequency components with sufficiently high frequency resolution, and raises the frequency resolution for low frequency components with gradual time change. This is an analysis method using a constant ratio filter bank similar to 1/N octave band analysis that is often used for acoustic analysis.

Model | Product | Qty |
---|---|---|

OS-5100 | Platform | 1 |

OS-0522 | FFT Analysis function | 1 |

OS-0527 | Time Frequency Analysis function | 1 |

*Sound recording equipment (High performance Sound Level Meter, FFT analyzer, etc.) is required. |