Evaluation of Effectiveness of Wavelet Based Denoising Schemes Using ANN and SVM for Bearing Condition Classification

<table>(a) Raw vibration signal from bearing with OR defect. (b) Denoised vibration signal from bearing with OR defect using <svg height="10.925" id="M74" style="vertical-align:-0.1638pt" version="1.1" viewbox="0 0 14.6625 10.925" width="14.6625" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink">
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q-97 56 -97 123q0 50 51 96q19 17 58 32.5t62 15.5q37 0 61 -18t24 -39z" id="x1D460"></path></g><g transform="matrix(.017,-0,0,-.017,6.437,10.65)"><path d="M447 623l8 -12l-283 -613l-74 -10l-7 11q174 283 297 551h-216q-48 0 -62.5 -12t-33.5 -63h-29q10 60 18 148h382z" id="x37"></path></g>
</svg>.</table>

Computational Intelligence and Neuroscience

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Figure 6

Figure 6: Evaluation of Effectiveness of Wavelet Based Denoising Schemes Using ANN and SVM for Bearing Condition Classification 