Rotating Component Noise Troubleshooting via Acoustic Frequency Analysis

The patent replaces the mechanical troubleshooting method (removing components physically) with an acoustic analysis system. The system uses audio sensors to capture sounds from rotating components, processes these signals through Fourier transforms to generate frequency spectra, and automatically identifies defective components by comparing detected frequencies with expected rotational speeds. This substitution eliminates the need for physical component removal while maintaining identification accuracy.

The patent introduces an intermediary acoustic signal analysis system between the rotating components and the troubleshooting process. Instead of directly manipulating components, the system captures acoustic emissions as intermediaries, processes them through spectral analysis, and uses the resulting frequency data to identify defects. This intermediary approach enables non-contact, non-intrusive detection.

The patent creates a digital copy of the acoustic signal through audio recording and processes this copy through computational algorithms. Instead of requiring expensive physical diagnostic equipment, the system uses software-based spectral analysis (Fourier transforms) to extract diagnostic information from the recorded audio signals. This copying approach enables sophisticated analysis using inexpensive hardware.

The patent transforms the acoustic signal from the time domain to the frequency domain through Fourier transforms. This parameter change enables the system to identify defects by analyzing frequency characteristics rather than requiring complex expensive equipment. The transformation converts audible sounds into frequency spectra that can be automatically interpreted by comparing against expected rotational speed parameters.