jBEAM contains several features that are used in various applications.
jBEAM contains several components that are specifically developed for GPS data:
Different video technologies can be used.
Due to the fact that some (only common in the automotive sector) video codes are not supported anymore on 64-bit computer systems, automatic converter can be offered particularly in the MaDaM context. An example is the Indeo format, which is used in Crash.
jBEAM contains a very fast algorithm to calculate the Fast Fourier Transformation. In addition, this algorithm has been developed further so that jBEAM has now a 2n independent algorithm. Thus, it is possible to use metrological usable FFT-based filter. The time signal is transformed in the frequency domain, folded with the filter characteristic and afterwards transformed back in the time period. These filters have extreme rates of changes. Therefore practically any filter characteristic can be realized. The corresponding components allow even the user to enter graphically the filter characteristic.
In addition to the conversion of mechanical strains in stresses, a rosette calculation is also available, which supports 45° as well as 60° rosettes. Furthermore the following special calculations are available: hole drill 2D, hole drill 3D and ring kernel.
Complete analysis of engine test data is provided. Automatic identification of revolution / manifold pressure test points from continuous time signals is included. Either on mathematical level or for graphical presentation correct characteristic matrices are calculated and visualized. Characteristic maps of differences between two tests are supported. jBEAM provides high interactivity, defined by manually changeable cursors, cuts through the characteristic maps can be calculated and compared. Certainly not only combustion engines but also electric motors with the two operation areas of running as a motor or as a generator are supported. Iso-power lines can be easily added in the graphical representation.
MATLAB (MATrix LABoratory of Mathworks Inc.) is a software tool to solve mathematical problems, which includes comprehensive libraries for numerical calculations. With the MATLAB Builder JA, complete MATLAB algorithms can be exported as JAR file and be run with the free of charge MATLAB Compiler Runtime (MCR).
The JAR files are used by the jBEAM component "MATLAB Wrapper" to run MATLAB algorithms with different datasets and to visualize the results. The MATLAB Wrapper investigates the JAR file and finds automatically all contained MATLAB algorithms. By means of the dialogue of the MATLAB Wrapper, the user can interactively define jBEAM channels and values as input parameter of the exported MATLAB algorithms. The results of the MATLAB algorithms are automatically converted to jBEAM data items and are available for further processing.
A set of 1D and 2D counting algorithms are available in jBEAM such as Statistical Frequency with equidistant or not equidistant class widths in one or two directions
For lifetime predictions the Rainflow algorithm is available with two different ways for handling the residua. From the 2D rainflow matrix derived 1D counting methods are available as Rangepair, Level Crossing, Span, or Average counting.
Dwell time, Min-Max Frequency, or Reversal Points calculation are some of the other offered counting algorithms.
All calculations necessary to calculate the passive safety of cars are available: CFC filtering with different methods (incl. two way Butterworth), all the HIC, 3 millisecond values, time at level, HCD, and different criteria calculations. All calculations can be used individually or as a complete NCAP analysis, observing the input channel codes for necessary additional filtering.
The forces of a crash wall can be visualized like a movie synchronized with high speed crash videos and all the time based signals.
Safety and behavior of railway vehicles can be calculated according to UIC 518 of the International Union of Railways and EN 14363. To support a complete analysis also a Test Section Generator helps to identify the time based measurements and to classify for the defined curve segments. An automated time shift for the signals depending on the position of the sensors in rail direction and the actual speed leads to correct results.