Segmented Kalman Filter Based Antistrong Transient Impact Method for Vortex Flowmeter

Vortex flowmeter is installed in piping to measure the fluid flow rate. The piping is easily disturbed by strong transient impact in the application fields, such as other components impacting on the pipeline, manual knocking on the pipe, and opening and closing of valves. The strong transient impact will be picked up by the vortex flow sensor, which makes the vortex flowmeter output wrong measurement results. The current commonly used digital signal processing method can do nothing about it. To solve this problem, an experimental setup is built in our laboratory to study the impact interference, and a large number of vortex flow sensor output signals are collected. The characteristics of transient impacts outputted by the vortex sensor are analyzed so as to describe this type of signal quantitatively. The pattern of transient impact is that the signal amplitudes increase suddenly and then attenuate gradually. A segmented Kalman filter based digital signal processing method is proposed according to this pattern. The data segment containing strong transient impact is found first; the transient impact power is reduced by filtering the data segment second; and through spectral analysis of the filtered signal, the maximum peak of the spectrum is extracted as the vortex flow signal finally. The algorithm is implemented in real time by a low-power microcontroller. Both gas and water flow experiments have been conducted to verify the validity and reliability of the antistrong transient impact algorithm.