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Description
Occupational noise exposure is a leading cause of work-related hearing loss worldwide, with impulsive noise being particularly hazardous due to its sudden high-amplitude pressure peaks, which can cause irreversible cochlear damage even after brief exposure. While its harmful effects are well documented, the scientific community still lacks robust tools to characterize the wide morphological diversity of industrial impulsive signals. Most existing characterization frameworks were developed for military-type signals, which generally exhibit a single dominant pressure peak and an abrupt rise time on the order of microseconds, whereas industrial impulsive sources present fundamentally different temporal structures, with more progressive pressure build-up over several milliseconds and multiple successive sub-peaks of significant amplitude. This gap calls for the development of controlled laboratory tools capable of reproducing realistic industrial impulsive signals.This study addresses this need through a four-step approach. First, a representative acoustic database was assembled from field recordings collected in multiple industrial environments and complemented by laboratory measurements. Second, eight temporal and energetic indicators were selected and adapted to capture the specific characteristics of industrial impulsive signals. Third, unsupervised clustering was applied to the indicator dataset to identify distinct categories of industrial impulsive signals. Fourth, the clusters were used to define acoustic target signatures for the controlled reproduction of industrial impulsive noise in laboratory conditions.Results demonstrate that the proposed clustering approach provides a robust characterization of the acoustic variability across industrial impulsive sources, and that the selected indicators define reliable target signatures for their controlled reproduction in laboratory conditions.