The vibration analysis and condition monitoring technology is based on comparison of measurements obtained with benchmarks suggested by manufacturers or standards. In this case, the references provided by current rules are static and independent of parameters such as age, operational or environmental conditions in which the machine is analyzed. It creates false alarms and many unnecessary interventions. New communication technologies allow the integration of e-maintenance systems, production and real-time data or the result of vibration routes. The integration of all these data allows data mining and extraction of parameters to be incorporated into decision making typical of CBM, such as repairs, downtime, overhauls, etc. Absolute vibration data and spectral analysis of rotating machinery require the study of several signals by machine, which become hundreds of values and spectra to analyze where there, is a large number of machines. It is therefore necessary to find proper benchmark points to compare with vibration parameters. These parameters and benchmark points have to be adapted to the real status of the plant and vibratory conditions have to be automated to be easily understood by persons not connected with the detailed analysis of spectra. The trend of the measured data and its comparison with benchmarks should assess the success of the implementation of CBM and other decisions about implementation and changes in maintenance programs. This article proposes the use of two new indicators that result from data mining as a reference dynamic, not static as proposed by the standard, manufacturer or the expertise of maintenance technicians. These values show the real condition of the machine in terms of vibration. The application of these references to the decision making process of the maintenance manager and its inclusion in maintenance scorecard avoids unnecessary repairs caused by false alarms and thus prolongs the life of the equipment, resulting in the improvement of parameters such as the MTBF, in a e-maintenance system.
[1]
Heinz P. Bloch,et al.
Machinery failure analysis and troubleshooting
,
1983
.
[2]
Clarence W. de Silva,et al.
Vibration: Fundamentals and Practice
,
1999
.
[3]
Igor J. Karassik,et al.
Pump Handbook, Third Edition/Igor J. Karassik, Joseph P. Messina, Paul Cooper, Charles C. Heald
,
2001
.
[4]
Yong-Jin Joo,et al.
Implementation of on-line performance monitoring system at Seoincheon and Sinincheon combined cycle power plant
,
2005
.
[5]
Jesús Royo,et al.
Overall Factory Vibration Level: The need for global indicators in CBM
,
2010
.
[6]
Prakash Vinod,et al.
Standardization of Absolute Vibration Level and Damage Factors for Machinery Health Monitoring
,
2002
.
[7]
Uday Kumar,et al.
An integrated approach to design and development of e-maintenance system
,
2004
.
[8]
H. P. Bloch,et al.
Practical machinery management for process plants. Volume 2: Machinery failure analysis and troubleshooting
,
1983
.
[9]
Paresh Girdhar.
Practical Machinery Vibration Analysis and Predictive Maintenance
,
2004
.