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Predictive Maintenance







Anticipated Value

The value of a predictive maintenance program can be estimated for bearing-related failures by means of calculation worksheet.  This calculation can help to make an informed decision about the merit of installing a predictive maintenance system in your specific context.


The critical part of an Online Condition Monitoring System is automated fault identification. This requires systematic data processing leading to reliable fault determination and trending.
TS-2 uses tachometers and gear ratios to accurately and continuously determine all shaft rotational speeds.  This is equally effective on high and low speed machines during steady speed or variable speed operation.  The shaft speed is used to separate the vibration into synchronous and non-synchronous components.

Tensor Systems Predictive Maintenance

The World’s Most Sophisticated Predictive Maintenance Monitor
Finding faults in the early stages allows for planned repairs, eliminating unplanned shutdowns and expensive catastrophes


TS-2 software trends overall vibration, synchronous vibration, non-synchronous vibration, spectra, cepstrum, kurtosis, etc. for a complete analysis.  When a trend starts increasing in amplitude, the rate of increase is used to determine the length of time before an alarm level is reached. This is indicative of time to failure.

TS-2 database is designed to store each trend for maximum value for the analyst. Each recently collected sample is retained, but older data is purged to less frequent intervals.  The value of the data is thus maximized, while maintaining a reasonable database size.


Why TS-2?
In comparison with other monitoring systems, there are important benefits in the TS-2 monitoring system.





Automated fault detection:

Life Remaining:




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