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A A Fig. 14 plasma actuator off (left) and on (right). Start CCoolllelecct tWininddoowwoof fDDaatata PePrfeorrfmormFFFTFoTnoWn iWndinodwow SStotorereFFFTTDDaatata CCalacluclualtaeteSStatnadnadradrd DDeveivaitaiotinonfofroer aecahch FrFerqeuqeunecnycy AAcctutuaatotorrOOffff CompareSTDvalueto ActuatorOn Compare STD value to c ct A fA Angle of Attack (deg) A t n n g g l l e eo o f At f f Actuator On tt t a a c ck k( ( d de e g g) ) PATEL ET AL. 523 u ua a t t o or rO Of f Plots showing frequency versus angle of attack (and time) from the NACA 0015 airfoil pitch-up experiment with the unsteady leading-edge No thtrhersehsohlodldvavlauleuefofroer aecahch frefrqeuqeunecnycy Increment Counter for each SSTDTDvavlauleuelalragregretrhtahnan thtrhersehsohlodld Is Counter Larger than Threshold? Yes the APSC experiments. Pitching tests were conducted with the plasma actuator held off and on to capture the pressure fluctuations and the resulting lift and forces. Figure 12 shows an example of the characteristic rise in the amplitude of a single frequency bin (from a total of 64 bins that were examined) as the 0015 was pitched up from 0 to 24 deg at 0:1 deg =s. A detailed time- and frequency-domain analysis was conducted using the PASC method for all frequency bins captured during pitch-up and pitch-down experiments with the actuator held off and on. Frequency bins that featured promising trends in predicting the stall onset behavior (abrupt shifts in the amplitude levels) were identified for further analysis. The results from the PSD analysis are shown in Figs. 13 and 14. Figure 13 shows a spectral power distribution plot of the 0015 pitch-up case with the actuator off, and Fig. 14 shows a two-dimensional view of the spectral plot for the 0015 pitch-up case with the actuator off (left panel) and on (right panel). A characteristic rise in the amplitude levels is observed for the frequency bins near 60 Hz at 12 deg (indicated by a circle in Fig. 13, right) before stall which occurs at 14 deg in this case. These amplitude levels are higher in the actuator off case (Fig. 14, left) compared to the actuator on case (Fig. 14, right), which indicate that the actuator is highly effective in reattaching the flow (or reducing the bubble size) and reducing the large-scale flow structures in the flowfield. Based on this explanation of the PASC method, a control system illustrated by the flowchart shown in Fig. 15 was implemented. First, the system selects a window of data, filters out low-frequency phenomena, and performs a FFT on the windowed data. Then it stores each transformed window as a row in a first-in–first-out (FIFO) stack. Each column in that FIFO stack represents the component of the signal at that time within a narrow frequency range. The STDEV of the preselected columns or “bins” is then calculated and compared to a predetermined “threshold”; if more than a predetermined fraction of the bins exceeds their respective thresholds, then the actuator state is set to on, or else the actuator state is set to off. Certain frequencies that exhibit a characteristic rise in the amplitude are selected and analyzed to identify specific threshold values to change the sensitivity/robustness of the controller. It is found that if more threshold values are used to trigger the actuators in feedback control, the system becomes insensitive to faulty precursors (see Fig. 16). Examples of this are shown in Fig. 16 where the controller activity (triggering the actuator off and on) is compared for different frequency-bin and threshold settings during pitch-up and pitch-down experiments. This clearly shows that when the controller used only two frequency bins to monitor the flow, it was highly sensitive to the flow instabilities and turned the actuator on upon detecting the slightest instability (relatively speaking) in the amplitude (power) at those frequencies. As more and more frequency bins were added to the “stall detection” analysis portion of the PASC code, the controller became more robust and less sensitive to the flow instabilities, and it turned the actuator off and on only when “true” onset to stall was detected. This was verified experimentally as shown in Fig. 16 by comparison of the control off/on state in the top, Fig. 15 Flowchart for the pressure amplitude sense-and-control (PASC) feedback control method. analysis of discrete frequency bins of the pressure signal for feedback control, as opposed to looking at an aggregate of all frequencies, as was done in the STDEV technique [8]. The PASC method allows us to examine how the power (amplitude) of the pressure time series is distributed with frequency. A characteristic rise in the amplitude levels of pressure frequencies is measured before stall, which is used as a precursor to the onset of stall phenomena. An increase in the amplitude (power) of the pressure signal is indicative of increased flow turbulence in the vicinity of the pressure sensor which is caused by high adverse pressure gradient and a separating flowfield. Identifying these precursors of flow separation at the wing leading edge enables the control system to activate the plasma actuator to control the flow separation and delay of stall. To demonstrate the performance of the smart plasma slat using the PASC approach, experiments were conducted on a slowly pitching 0015 (0:118 deg =s) using a single pressure sensor at x=c 0:05 on the suction side. The experimental setup was exactly the same for Magnitude (ct) Magnitude (ct) Frequency (Hz) Frequency (Hz)PDF Image | Autonomous Sensing and Control of Wing Stall Using a Smart Plasma Slat
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