Fast Cyclostationary Beamforming Algorithm Based on Snapshot Matrix for Localization of Cyclostationary Sound Sources
Mingjie Yu, Liang Yu, Chenyu Zhang, Ran Wang, Youhong Xiao · 2024
The acoustic imaging techniques are used in areas such as diagnosing faults in rotating machinery due to the advantages of non-contact measurements. Most existing acoustic imaging techniques do not consider the cyclostationarity of faulty sound sources. As a result, cyclostationary sound sources cannot be accurately identified in their localization results. The cyclostationary conventional beamforming (CSCBF) method has been proposed to obtain the cyclic spectral density (CSD) at the source plane by constructing the cyclic cross-spectral matrix (CCSM) between the signals from different microphones, and its problem is the runtime limitation in the construction of the CCSM. The fast algorithm for CSCBF based on the snapshot matrix (SNM-CSCBF) is proposed to optimize the construction of the CCSM by the snapshot matrixes of acoustic signals at different frequencies. The localization accuracy and robustness of the fast algorithm is demonstrated by comparing the runtime of the algorithms as well as the error of the sound source localization (SLE) in simulations. The speaker source localization experiments and faulty bearing localization experiments are used to examine the SNM-CSCBF fast algorithm, which enables accurate and fast localization of cyclostationary sound sources.