PROGNOST®-NT Early Failure Detection

The early detection of developing failures is a prime concern for machinery operators. The PROGNOST®-NT Early Failure Detection module keeps operators informed about actual machinery condition.

The general correlation regarding the relationship between component operating hours and the likelihood of failures does not always hold true. Industry surveys reveal, that several different failure “patterns” occur in complex machinery; but the majority of these do not depend on the operating time of components. Machinery parts will fail – sooner or later. But the idea that newly installed components or regular overhauls will avoid failures is not always viable.

Based on this important knowledge, early failure detection is vitally important for all process critical machinery. The early detection of developing failures allow proactive intervention before serious breakdowns can occur and reduce unplanned machinery shutdowns. The PROGNOST®-NT Early Failure Detection module provides maximum reliability in damage detection.

Varying operating conditions or load steps often result in dynamic changes of machine behavior. While other systems typically apply only one set of warning thresholds across all operating conditions, PROGNOST® recognizes these load step changes and applies different sets of thresholds for each distinct condition.

Trend plot of crosshead vibration RMS values over a period of 12 months. The green flags indicate machine starts and stops.This vibration plot informs the operator about developing failures in the motion works section of the compressor.

This unique product feature delivers extremely effective early failure detection capabilities.

Your advantages

Avoidance of costly damages through identification of mechanical defects at an early stage
Information instead of data: clear text messages with local and functional clarity
Definitive damage identification based on comparison an empically derived damage pattern database
Determination of an overall machine condition value
Adaptable threshold monitoring depending on the machine´s operating condition e. g. for partial load steps