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Vibration signals can be successfully captured and analyzed for quality control at the end of the production line. Various signal processing techniques and their applications are presented in this paper. These applications demonstrate the importance of selecting proper signal processing tools in order to extract the most reliable information from the signals. The presented applications regards tooth fault detection in helical gears and the detection of assembly faults in diesel engines by means of cold test technology.

This work seeks to study the potential effectiveness of Fourier-Bessel (FB) series expansion for gear fault diagnostics. FB series expansion is a method for cross-terms suppression in Wigner-Ville distribution (WVD). In particular, FB series expansion is used as a signal decomposition technique in order to subdivide the signal into its components before WVD evaluation. The pros and cons of this method are highlighted by the analysis of experimental results. In particular two case studies are taken into account: a fatigue crack at the tooth root and spalls of different sizes. The presented results highlight the conditions in which FB decomposition technique is effective in WVD cross-term suppression, the limitations, as well as the advantages in terms of fault identification.