### Analyze Statistics

Random Import generates a random test profile from recorded data. Most significantly, it can be used to analyze statistics from a time-history recording. The behavior of the original environment can be used to help determine the cause of product failure, validate a test method or standard, or compare a current test to real-world measurements.

Upload an acceleration time history file and view the following statistics:

- Length (# of samples)
- Peak Acceleration (positive and negative)
- Peak – Peak Acceleration
- Acceleration (RMS)
- Acceleration Squared Variance
- Crest Factor
- Kurtosis
- Velocity
- Displacement
- Sample Rate
- Channel Count
- # Of Samples
- Duration (time)
- Channel Layout by Column

Random Import Lesson

### When Should I Select a Random Test?

Real-world vibration displays random characteristics and is not repetitive or predictable like a sine wave. A random vibration test can be generated to represent one or multiple environments where the device under test will be used. A random test can also be accelerated to represent a longer field life than can be run in a lab.

A random vibration test excites all the frequencies of the device under test and is a more realistic representation of the end-use environment than a sine test. Additionally, a device under test may have multiple resonances. A sine test only excites one resonance at a time. By exciting all potential resonances at the same time, a random vibration test reveals the interaction between multiple resonances. The random test often reflects a greater damage potential than a sine test.

Vibration test engineers should use a random vibration test to:

- Test a product against vibrations that will occur in the field environment
- Determine how a product will respond to the excitement of multiple resonances at the same time
- Test a product to failure

#### Webinar: Fundamentals of Random Testing

### Generate a PSD

The Random Import option in VibrationVIEW can be used to create a random power spectral density (PSD) based on averaging or a peak hold import, or a fatigue damage spectrum (FDS) based on a recorded time-history file(s) and a user-defined m value. The resulting random test is reflective of the original environment.

### What is the Power Spectral Density (PSD)?

Random vibration is often analyzed with the power spectral density (PSD). The PSD represents the distribution of a signal over a defined frequency spectrum. It reveals resonances and harmonics that may not be visible in a time-history graph.

Normally distributed time-domain data is transformed into frequency-domain data (i.e., a PSD) using the fast Fourier transform. An understanding of the PSD will help engineers to determine the correct parameters to use when generating a PSD from a waveform. To learn more about generating a PSD, please enroll in our Random Testing course on VRU.

### What is Fatigue Damage Spectrum?

The fatigue damage spectrum is random vibration spectrum based on Miner’s rule of damage. Miner’s rule states that fatigue damage will accumulate over time until it reaches a level that causes a crack or other deformation of a product.

The Fatigue Damage Spectrum software is a test development tool that replicates the operational environment of a product. It is used to create an accelerated random test using real-world data. The resulting test is the damage equivalent to a product’s lifespan.

For test purposes, the FDS can then be converted into a power spectral density (PSD) using Henderson-Piersol’s potential damage spectrum. The result is a single PSD profile for multiple time-history files. The FDS-generated PSD is a cumulative spectrum that represents the relative damage experienced by the product for all the combined and weighted environments.

Fatigue Damage Spectrum

### When Should I Use FDS?

With the FDS software, engineers can create a random test profile that is the damage equivalent to weighted time history files that portray the product’s end-use environment. They can also use FDS to compare multiple failure runs of a product, compare specifications to real-world data, and determine if current testing is valid or if a product is being under/over-tested.

**IF YOU’RE ASKING THESE QUESTIONS, YOU NEED FDS:**

- What is the best random test to simulate my product’s environment?
- How long should I be running my random test?
- Can I accelerate my testing?