Counter-rotating rotor configurations are considered more efficient than their single rotor counterparts. Consequently, the coaxially aligned rotors have appeared in the fixed-wing aircraft sector and are appearing in the quickly developing unmanned aerial vehicle sector, where they are expected to play a significant role, especially for long haul and heavy load configurations. As their noise levels have proven to be rather significant, the localization and reduction of the noise of such counter-rotating blade sets is a relevant topic of interest. One of the dominant contributors to counter-rotating rotor noise is interaction tones. Interaction tones appear at combinations of the harmonics of the blade passing frequencies of the two rotors and are significant throughout the spectra. In this paper, an automated method is presented that analyzes an entire series of beamforming noise source maps using principal component analysis-based methods in order to identify the dominant noise generation mechanisms in frequency bins that are associated with interaction tones. The processing technique is presented herein through the investigation of counter-rotating open rotor datasets developed for a fixed-wing aircraft configuration. With the proposed method, an objective mean has been provided for separating apart contributions from various noise sources, which can be automated, making the processing and investigation of large sets of measurement data rather quick and easy. The method has been developed such that the results of the analysis are easy to comprehend even without specialized prior knowledge in the area of counter-rotating rotor noise.