The mean and variance dominate statistical measurements in both the time and frequency domains. They are also reflected by so-called amplitude domain measurements. The most basic of these is called a histogram. To measure a histogram, break a signal’s potential amplitude range into a contiguous series of N amplitude categories (i.e. x is between a and b) and associate a counter with each category.

One statistical description measured during a random shake test is the Control Spectrum. Specifically, this variable is often the output of an accelerometer mounted to the shaker table. The sensor’s voltage output is scaled to engineering units of acceleration, typically gravitational units (g’s) sampled at a fixed interval, Δt. This time-sampled history is transformed to the frequency domain using the Fast Fourier Transform (FFT). In this process, a series of “snapshots” from the continuous time waveform are taken and dealt with sequentially.

Verifying the robustness of products (or their packaging) by subjecting them to shaker-induced vibration is an accepted method of “improving the breed”. While shock bumps and sine sweeps are intuitively obvious, random shakes with their jumps and hissing are anything but. Even the language of a random test is confusing at encounter. Let’s try to improve upon that first introduction to random signals!

This patent protects an important contribution to CI’s Vibration Control System (VCS) business, its unique means of controlling the kurtosis of a random vibration signal. A conventional (Gaussian) random signal has a peak-to-rms ratio (the crest factor) of about 3. In contrast, a high kurtosis random signal of the same RMS intensity, with identical spectrum shape, can have a significantly higher crest factor.