In this paper, a novel slot–groove hybrid casing treatment is designed and optimized to improve the stall margin of a low-speed axial compressor. A combination of the axial slot and circumferential groove casing treatments is utilized to increase the stall margin without incurring efficiency loss. The slot meridional profile is described with 2 B-spline curves. Circumferential grooves are parametrically described with groove height and width. An in-house optimization design platform is constructed based on the nondominated sorting genetic algorithm II and Kriging surrogate model. The optimization objectives are the stall margin and the peak efficiency of the compressor at the design rotating speed. To avoid the large number of unsteady simulations that are required to predict the stall margin, a stall margin improvement indicator is proposed based on the axial momentum budget analysis at the rotor tip region. The performance of the optimal slot–groove hybrid casing treatment design is tested and simulated. The experimental data show that the optimal slot–groove hybrid casing treatment improves the stall margin by 8.42% without generating efficiency loss. The flow details are captured by unsteady simulations and analyzed in depth. The application of the optimal casing treatment enhances the blade tip axial momentum and the interface between tip leakage flow and incoming main flow is pushed downstream. Consequently, the stability of the compressor is improved.

To study the influence of rotating inlet distortion on a single-stage axial compressor, both experiment and full-annulus unsteady simulation methods are carried out to reveal the stall mechanism under different inflows. First, the experimental results show that compared with static distortion, rotating distortion reduces the compressor stall margin more seriously. The wavelet analysis of dynamic pressure data shows that although the addition of inlet distortions has changed the stalling process, the compressor still stalls through spike-type. The full-annulus unsteady simulations indicate that the low-velocity zone first appears at the hub under uniform inflow condition. When the compressor is subjected to rotating distortion, the low-velocity zone first appears at the tip region. Time-averaged solutions of unsteady simulations are further studied to reveal the underlying mechanisms. Compared with the flow field under uniform inflow, the addition of rotating distortion can produce co-swirl, but it also causes the change of axial velocity distribution along the radial direction. Under the combined effect of both, the blade loading of rotor tip increases significantly, altering the position where the low-velocity zone first appears.

As a reliable stall warning strategy, the fast wavelet method was introduced to successfully predict the aerodynamic instability of a multistage axial flow compressor. One single sensor installed at each stage is proved to be sufficient to predict the stability status in a three-stage axial flow compressor. The whole prediction strategy includes the dynamic pressure signal capture, disturbance extraction using decomposition and reconstruction via fast wavelet transform, and stall warning index calculation based on statistical probability distribution. On this premise, the first occurrence of the stall in this three-stage axial flow compressor is predicted to be within the first stage, which is consistent with the stall route captured by the eight transducers around the casing wall. Thereafter, the stall warning index is used to monitor the stability status during the continuous throttling process. Furthermore, the validation using tip air injection and inlet radial distortion indicated that the stall warning index decreases as the compressor's stability improves. Conversely, the deterioration of stability causes the increase of the stall warning index. Thus, experimental results demonstrate that the stall warning method based on fast wavelet analysis can predict the aerodynamic instability in actual application.