It used to be a relatively common practice for plants to wait for equipment to fail, and then repair it. A range of predictive technologies can be implemented to detect developing machinery faults at an early stage, before they become problematic. These predictive technologies can include performance parameter sensors, specialized monitoring devices, and analytical and data management software to capture, trend, diagnose and report timely information on the operating conditions of machinery assets.
The key to choosing appropriate predictive technologies is to understand how a particular machine fails?, what symptoms would be visible and detectable before it fails?, and how fast that machine would deteriorate?.
Measuring Effects of Vibration
Many machinery problems manifest as vibration, which is widely considered the best operating parameter to assess a machine’s condition. Vibration can detect machine fault conditions, such as:
• Unbalance.
• Misalignment.
• Oil film bearing instabilities.
• Rolling bearing degradation.
• Mechanical looseness.
• Structural resonance.
• Soft foot.
• Rotor bow.
• Cracked rotors.
Vibration measurements are also quick and fairly non-intrusive since the operating equipment is undisturbed. Collected vibration measurements can be analyzed on the spot or downloaded to a specialized software application on a computer work station or network for analyzing, long-term trending and reporting abnormalities.
Detecting Defects in Bearings
The vibration measured at a machine’s bearings can open a window into equipment health because most machine problems have distinct vibration symptoms. A bearing can degrade due to:
• Improper lubrication.
• Contaminated lubrication.
• Heavier loading than anticipated, often caused by other machinery problems such as imbalance, misalignment or a bent shaft.
• Improper handling or installation.
• Surface fatigue.
• Misapplication.
If these symptoms are detected and properly analyzed, and the progression of the damage is monitored accordingly, these signals provide maintenance personnel adequate time to correct the cause of the bearing problem.
Analyzing Condition of Lubricant
Lubricant inspection and analysis serve as a particularly practical method to help detect problems with machinery assets, especially since many characteristics can be examined visually.
• Water contamination can be observed with clarity in a standing sample.
• Ferrous materials (filings, metal dust, etc.) can be detected using a magnet drawn up the side of a glass jar containing lubricant diluted with a solvent.
• Flow and discoloration can be noted in a bull’s-eye sight glass.
• Non-ferrous particles can be evaluated by residue on filter paper.
• Viscosity can be monitored using simple in-plant tools.
Before embarking on any predictive maintenance program, a clearly defined maintenance strategy should be in place. Decisions to apply related technologies should be prioritized according to the risks associated with equipment failure, the possible financial consequences, the impact on the safety of personnel, production processes and the environment.
The Electronic Diagnose PenBy Dave Staples, Copyright of Chem, Advantage Business Media, June 2008.
“Towards Hospital Intelligence Practices“
