Читать книгу Engineering Acoustics - Malcolm J. Crocker - Страница 16

Stationary signals can be divided into deterministic and random signals. Stationary deterministic signals can be described by a mathematical function. They are made of a combination of sinusoidal signals (pure tones) with different amplitudes and frequencies. The spectrum of a stationary deterministic signal is characterized by content (power) at discrete frequencies (a line spectrum). The measured displacement signal of a simple mass‐spring system and the noise and vibration signals from machinery rotating at constant speeds are both examples of stationary deterministic signals.

Stationary random signals cannot be described by explicit mathematical functions but instead they must be described by their statistical properties (mean value, variance, standard deviation, crest factor, kurtosis, amplitude probability, etc.). In contrast to stationary deterministic signals, they have a continuous distribution of spectral content. If the random signal has constant statistical values which do not change with time, we refer to the random signal as stationary. The sound produced by rain or a waterfall, the noise produced by turbulent air coming out of a ventilation system, the noise produced by a passing vehicle, and the airborne noise of a circular saw during idle are examples of random signals. A random signal which has a flat (constant) spectral content over a wide frequency range is called white noise.