News06.12.2011 Calendar Update 2012 The calendar of events is now filled with events of 2012. By clicking one of... 07.11.2011 VISU - OneClick Cockpit To complete the media beside the new brochure (PROGNOST®-NT Enhancements... 19.09.2011 Open Position: Machinery Analyst PROGNOST Systems, the recognized leader in online condition monitoring and... |
Feature Fuzzy logic and neural networksThe past 10 years have seen continuous progress in the technological means available for monitoring the condition of reciprocating compressors. For years, machine protection relied almost exclusively on indirect state, or condition, variables such as vibration. Yet, more recent systems have been taking account of direct mechanical state variables such as piston rod position or thermodynamic variables like pressure volume (PV) curves. This is no longer being done exclusively for the purposes of machine protection, but in order to gain the most comprehensive information on the condition of a machine and its components.  Traditionally, the role of machine protection is to prevent damage to components that occurs between scheduled maintenance inspections from causing catastrophic damage to a machine. Maintenance personnel will shut down a machine and disassemble it in order to get a comprehensive idea of the state of its components. In such cases, machine protection parameters are usually only determined based on a single threshold value, so that the only available information is either the ‘OK’ or the ‘alarm’ status. The operator often lacks any information whatsoever on how the parameter used for machine protection purposes is trending. For example, he or she may not know whether the machine is operating at levels close to or well below an alarm threshold. Yet many machine operators are now unsatisfied with these kinds of basic safety mechanisms, where only a single variable (for example, frame vibration) is analysed. At the very least, machine protection parameters in the 21st century should be recorded in such a way that their evolution over time (trending) is discernable. In order to be able to derive added value from ongoing analysis, a measured variable’s curve has to be evaluated, and machines usually have to be equipped with a finer net of sensors to obtaininformation on the condition of as many components as feasible. |
Product
19.05.2011 PROGNOST®-NT Swift This mobile system is a complete PROGNOST®-NT system with all the features of a fully equipped, permanent PROGNOST®-NT installation. Portable and powerful, it can be installed quickly to meet short-term or temporary monitoring requirements, eg. after overhauls or initial start-ups. Industry19.05.2011 LDPE Learn how the PROGNOST® technology enables operators to deploy successfully a predictive maintenance strategy and operate safe and reliable compressors. |