17 Others Andersen and Rasmussen, 1999
have referred to it as ‗information about technical health‘. It has been reported that major improvements have occurred in the
technology, practice and use of equipment condition monitoring over the past sixty years Mitchell, 1999. An example is the development from the mechanical
instruments that were used 20 years ago to capture a simple low frequency dynamic waveform to today‘s high-performance digital instrumentation. Methods of equipment
condition monitoring can be classified according to the monitored parameters that were influenced by the potential failure Moubray, 1997. To support his argument, Moubray
divides condition-monitoring techniques into six categories:
1. Dynamic effects, such as vibration and noise levels. 2. Particles released into the environment.
3. Chemicals released into the environment. 4. Physical effects, such as cracks, fractures, wear and deformation.
5. Temperature rise in the equipment. 6. Electrical effects, such as resistance, conductivity, dielectric strength, etc.
However, irrespective of the condition monitoring techniques used, the key elements of condition monitoring are the same: the condition data that becomes available needs to
be converted into a meaningful form and appropriate actions must be taken accordingly. As examples in this discussion, a few condition monitoring techniques that are popular
in industry have been selected from the survey conducted by Higgs et al. 2004. For other references to such methods, see Moubray, 1997 and Williams et al., 1995.
2.5 Condition-monitoring techniques
2.5.1 Vibration Monitoring
The vibration-monitoring technique is perhaps the most popular and widely used of all monitoring techniques Higgs et al., 2004. It can be used to detect several system
conditions, such as fatigue, imbalance, misalignment, loosened assemblies and turbulence, which can occur in rotational or reciprocating parts such as bearings,
gearboxes, shafts, pumps, motors, engines and turbines. The operating processes of these components will release energy in the form of vibration, whose amplitude will
remain in a steady state unless there is a change in the operating dynamic of the system.
18 The changes at this stage may signal a warning of the impending failures that may occur.
Reeves 1998 explains that vibration monitoring consists of identifying two quantities: the magnitude of the vibrations and their frequency. The former is used to establish the
severity of the vibration, while the latter indicates the origin of the defect. It should also be noted that the severity of the vibration in any particular case would depend on these
factors:
1. Type of machine 2. Flexibility of the mountingfoundation
3. Position or direction of measurement 4. Operating conditions during measurement
A summary of techniques used in vibration monitoring is given by Reeves 1998.
2.5.2 Oil Analysis
Condition monitoring through oil analysis provides a means of analysing oil at regular
intervals to determine if it still meets the lubrication requirements of the equipment. The particles contained in a lubricating fluid carry detailed and important information about
the condition of the machine components. There are many methods, which can be utilised to perform an analysis to obtain such information. A comparison between
different methods, which were available, is given by Roylance 2005. The features of the analysis can be deduced from particle shape, size, composition, size distribution and
concentration, which can be classified into three categories namely quantitative, qualitative and material properties, see Khan and Starr 2006 for details of the
classifications.
A change in the rate of particles collected indicates a change in the condition of the machine. When this condition reaches an unacceptable state, the machine must be
replaced to maintain satisfactory system operations. The two most commonly used
methods in oil analysis are spectrometric and ferrographic analysis. Spectrometric analysis is the method commonly used to detect small wear particles. It is also used to
identify the possible introduction of contaminants. The results are typically reported in parts per million PPM. According to Edwards et al. 1998, it is important to note that
19 this method monitors only the smaller particles present in the oil 10 microns. This
disadvantage of spectrometric analysis is due to the fact that large and medium particles 10 microns are likely to exit the oil flow via some filtration. This leaves the small
particles which passed through the filter to remain suspended within the engine and their oil measurements to provide an indication of machine condition Edwards et al.,
1998.
Ferrographic analysis produces similar results to spectrometric analysis, but with two main exceptions. First, ferrographic analysis separates wear particles by using a
magnetic field, rather than burning a sample as in spectrographic analysis. Secondly, wear particles that are larger than 10 microns can be separated and analysed, which
provides a better representation of the wear particles in used oil analysis. The only criticism of this technique is that the analysis of the wear particles is very skill-
dependent, subjective and time-consuming as well Whitlock, 1997 and Roylance, 2005.
2.5.3 Temperature Monitoring
