Traditional beamforming methods do not effectively separate the mixed field of sound sources for different rotational speeds. The coexistence of these sources often manifests out-of-focus sources (for instance, stationary sources appearing with a rotational focus), thereby blurring the beamforming outcomes. Most existing algorithms for segregating rotational different speed sources employ a virtual rotating array utilizing ring arrays. However, due to the constant microphone spacing, the acoustic imaging of the ring array suffers from the interference of high-level side lobes. In this work, a hybrid deconvolution method based on modal composition beamforming is used to explore the ability of a multi-arm spiral array to separate different speed sources. Considering the even energy distribution from the out-of-focus source along the circular trajectory, the beamforming result of out-of-focus sources exhibits a weaker amplitude than the source amplitude. Therefore, out-of-focus sources can be considered noise. First, the point spread function is derived based on the modal transfer function. Then, a system of linear equations is constructed based on an incomplete cross-point spread function matrix. Finally, the source separation is solved through sparse-constrained deconvolution. Simulation and experimental results demonstrate that this method can accurately locate and separate different rotational speed sound sources.