Signal Processing with WaveImage

This module allows you to view and compare any type of data in a variety of different views. With the included Preprocessing you can cut, filter or resample your data and track the changes live. WaveImage is designed to process large amounts of data. It is the ideal starting point for checking and preparing your measurement data for structural dynamic analysis.

You can visualize your source data, transform time data into the frequency domain for FRF analysis, display it as a spectrogram or scalogram, calculate the correlation and autocorrelation, view the Complex Mode Indicator Function (CMIF) curves, and much more.

In each view, you have many options for normalizing, scaling, and comparing your measurements and you can also display the properties contained in the file format and a statistical analysis of the measured data.

With WaveImage Preprocessing your measurement data can be edited, compressed, improved or converted in various ways.  The module supports signals of all sensor types, including displacement, velocity, acceleration, rotational speed, transistor-transistor logic and force. You can use the integrated conversion features for example to adjust the ranges of time data or calculate their frequency response.


Time domain:

  • Cutting the time interval to save memory
  • Reduction of the sampling rate to save memory and gain computing time
  • Detrend to subtract the mean value or a best-fit line (in the sense of least squares of error)
  • Filter (low-pass, high-pass, band-pass, band-stop) to reduce the signal to the relevant frequency range
  • Wavelet denoising to remove noise from the data
  • Editing of data information such as hardware type, units or names
  • Kinetic transformation into displacement, velocity or acceleration
  • FRF calculation (H1, H2 or Hn)
  • TTL to RPM conversion
  • Interpolation of RPM signals
  • Extraction of RPM signals using RPM track (only in combination with Order Analysis)

Frequency domain:

  • Frequency cut to reduce signal bandwidth
  • PCA Noise Removal as wavelet noise reduction that uses principal component analysis (PCA) to filter the significant features in the data
  • Overlapping can be used in the calculation of the Complex Mode Indicator Function (CMIF) to remove noise or simulate additional inputs (reference nodes).
  • Denoising smoothes the CMIF curves for noisy data.
  • Simulation of Inputs simulates additional reference nodes (inputs) and thus produces additional CMIF curves.
  • Exchange of excitation and response channels (roving input to roving output transformation)


  • Original view of the data as they are stored in the file format (e.g. time and frequency data)
  • View the spectrum (Fast Fourier Transformation or Frequency Response Function Analysis) of time data to identify the resonant frequencies
    • Real and imaginary part
    • Magnitude and phase
    • Lower and upper envelope
    • Nyquist chart
  • Correlation and autocorrelation view
  • Bar view and histogram view
  • Orbit plot for diagnosing problems with rotating machinery (visual representation of the centerline of a rotating shaft).
  • (Cross) Power Spectral Density (PSD and CPSD) view for measuring signal power content versus frequency.
  • Multiple Coherence and Magnitude Squared Coherence to investigate the relation between two or more signals
  • View of the Complex Mode Indicator Function (CMIF) based on the Singular Value Decomposition (SVD) of the Frequency Response Function (FRF) to identify all modes detected during the modal test measurements
  • View as spectrogram and as power spectrogram representing visually the frequency (power) spectrum of a signal as a function of time
    • Comparison of several spectrograms as maximum, minimum, difference or average
    • View cuts at specific times or at specific frequency lines
  • View as scalogram representing visually the wavelets of a signal as a function of time
    • Comparison of several scalograms as maximum, minimum, difference or mean
    • Supported wavelets: Morse, Amor, Bump, Hanning
  • View as Impulse Response Function (IRF)
    • Retransform your FRF data with an inverse fft
  • Geometry view to visualize the assignment of the channels to the geometry


Display of several channels as sum, average, difference

  • Normalization of data
  • Drag average to zero
  • Scale amplitude to plus/minus one
  • Cutting signals to the same length
  • Display of mean value and standard deviation
  • Calculation of statistical moments such as skewness or kurtosis
  • Linear and logarithmic scaling
  • Play time data as sound
  • Save views as image or send them to Word or PowerPoint report

Input Format

  • Universal file format (*.uff, *.unv)
  • Polytec file format (*.svd and *pvd)
  • The SVS configuration file format (*.cfg)
  • The WAVE file format (*.wav)
  • Our own vibration file format (*.vib)