A new method for particle velocity measurement based on fast algorithm for cross-correlation and filter interpolation

Cross-correlation method is a well-known technique in online continuous velocity measurement of particulate solids in pneumatic pipelines, but the low sampling rate and noise will cause inaccuracy in the delay estimates, and the computation of the cross correlation function is expensive which is not suited for real-time implementation. This paper presents a method based on fast algorithm for cross-correlation and filter interpolation to obtain the velocity in real-time and improve the accuracy of the velocity measurement. The real-time DSP-based cross-correlation velocity measurement system is designed and experiments are carried out to evaluate the performance of the proposed method, and the experimental results show that the sampling rate is increased, and system relative error is within ±4% over a velocity range of 2.8-4.0m/s for a moving particle. This method can lower the requirements for data acquisition hardware and improve the estimation accuracy by increasing the sampling rate and eliminate the noise at the same time. It is well suited for real-time implementation in DSP-based velocity measurement system because of the little computation of the cross-correlation function.