A new signal denoising method based on double dictionary learning and moving ruler strategy
Yunfei Ma, Xisheng Jia · Measurement Science and Technology · 2020
Abstract The denoising of vibration signals is useful with regards to various applications such as equipment monitoring. This study proposes a double dictionary learning method with a moving ruler strategy. The moving ruler strategy is used to construct a multi-layer and multi-position dictionary to reduce the gap between adjacent columns. However, the drawbacks of this strategy are high dictionary redundancy and reduced computation efficiency. Considering this issue, a double dictionary model is proposed combining the fixed dictionaries with learning dictionaries. The sparse coding and dictionary updating are improved correspondingly. Simulations demonstrate that the proposed method can outperform the existing denoising approaches. Moreover, an application of gearbox is presented to further validate the proposed method.