Computationally lean algorithm of novel optimal FIR adaptive filter for vortex signal extraction

• The filter algorithm for vortex signal extraction.
• The comparative results for existing system and newly developed system.
• Error analysis of newly developed system and existing system.
• Low Power implementation of the newly developed algorithm.

In a vortex flowmeter vortices are generated by a bluff body, inserted in the path of flow, which has a piezoelectric sensor embedded in it. This piezosensor develops a signal having a fundamental frequency that is proportional to flow. The flow measurement relies completely on extraction of true vortex signal and estimation of the correct frequency. A novel adaptive FIR filter has been designed and implemented using low power computational resource (8.25 mW), which gives better results than an existing contemporary system when tested on an industrial flow rig. Further more a comparative study of autocorrelation, EMD Scales filter and proposed algorithm is carried on the good and bad vortex signals. From this comparative study it is seen that proposed algorithm is effective for bad vortex signals and low flowrates where vortex signals are weak.