By combining vibration measurement and telecommunication techniques, we detect changes on gears and roller bearings 100 times earlier than traditional methods.
Acoustic sound signals as well as vibration signals from accelerometer are compatible with the VibSim method.
Traditional methods discover symptoms that rise above normal background noise.
VibSim method discover symptoms that are much smaller than normal background noise. We recognize specific patterns that represent possible damage to the machinery.
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VibSim calculates remaining lifetime by using our patented pattern recognition algorithm in combination with machine learning.
While traditional methods require manual effort to perform analyses, the VibSim method is fully automatic.
Traditional frequency-based methods, requires manual effort to perform the analyses. VibSims pattern recognition in time domain is feasible for robotization and no manual effort is required. Digitalized data acquisition makes the analyses complete automatic. Operator gets warning with remaining lifetime and precise diagnose.
In addition to vibration signals from accelerometers, VibSim pattern recognition techniques perform well on audio recordings. Hence, our method makes condition monitoring possible where accelerometers can’t be mounted, e.g., in drones, helicopters, subway doors, and cargo train wagons by use of microphones.
