Feasibility of dictionary-based sparse coding for data compression in machine condition-based monitoring

On-time machine maintenance and upkeep are critical to ensure on-time production. In recent years, Condition-Based Monitoring (CBM) has been regarded as one of the most state-of- the-art machine maintenance techniques that can significantly lower unscheduled maintenance cost and provide greater efficiency. This however means that more data needs to be streamed and stored for CBM to work properly, which might prove costly in the long run in terms of data storage. This paper therefore focuses on the feasibility of using Sparse Coding as a method for signal compression for CBM purposes. Specifically, the feasibility of the method will be measured for vibration signals coming from the spindle component of machines.