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A popular approach for conditional monitoring of mechanical machines is to embed vibration sensors into a machine and start "listening" to it. The data from the sensors must be stored somewhere. So, the more efficient we compress them, the longer history we can keep. When we deal with sensors we always have noise from them, and when a machine is stopped we have only noise which wastes our storage space. WaveletBuffer was developed to solve this problem by using the wavelet transformation and efficient compression of denoised data. However, a user must know many settings to use it efficiently. In this tutorial, you will learn how to find denoising parameters to get rid of white noise in your data.
For an educational purpose, I brought two samples from a vibration sensor which is maintained on a real machine. You can find them in the directory docs/tutorials. buffer_signal.bin contains a second of the signal when the machine is working. buffer_no_signal.bin has only noise because the machine is stopped. Both files are serialized buffer without any denoising, so they have equal sizes but different amount of the information!
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