Flow velocity effectiveness identification and correction method for frequency domain space-time image velocity measurement

Abstract

The invention discloses a flow velocity validity identification and correction method for frequency domain space-time image velocity measurement, and the method comprises the following steps: 1, detecting a target signal peak value and a corresponding direction in an amplitude spectrum, searching a valley value and a direction from the peak value to a nearest boundary of the amplitude spectrum, taking an amplitude symmetric point of a valley value point relative to a signal peak value point, and calculating a peak value of the peak value; the main direction of the frequency spectrum is relocated after the peak symmetry is judged; 2, taking the valley value as background mean noise, calculating confidence, and calculating a starting point distance of a velocity measurement line and a flow velocity value on the velocity measurement line; 3, acquiring a confidence threshold according to an adaptive confidence mechanism to set a validity flag bit of a corresponding flow rate, and performing interpolation correction on an error vector according to the validity flag bit; and 4, calculating the effective data rate according to the effective flag bit. The effectiveness of the flow velocity measurement value can be effectively identified, random noise and gross errors caused by environmental disturbance under the field monitoring condition are eliminated, and the effective data rate is improved.

Description

technical field [0001] The invention relates to the image-based flow measurement technology, in particular to a method for identifying and correcting the effectiveness of flow velocity oriented to frequency-domain spatio-temporal image velocity measurement. Background technique [0002] Spatio-temporal image velocimetry (STIV) is a velocity measurement method applied in straight river conditions, setting the velocity line as the analysis area, and estimating the one-dimensional time-average velocity according to the main direction of the texture of the synthetic space-time image. It utilizes the continuity of the movement of water flow tracers in the three-dimensional space-time domain, adopts the speed measuring line parallel to the downstream direction as the analysis area, and detects the texture direction related to the movement of tracers in the space-time images composed of image space and sequence time , so as to calculate the velocity value on the velocity line. Due...

AI Technical Summary

Problems solved by technology

However, in practical applications, due to natural environmental interference such as glare, rain, and occlusion, it is easy to cause excessive background noise, and the signal-to-noise ratio of the amplitude spectrum of the spatio-temporal image is low, which may cause errors in the main direction of the spectrum detected on the amplitude spectrum. Then the wrong flow velocity value is calculated, which is not conducive to the subsequent flow field reconstruction

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