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History, experience and familiarity count for a lot where conditioning monitoring is concerned, but that doesn’t negate the need for change, innovation and the advancement of tried, tested and trusted techniques.
The late Steve Jobs commented: “Innovation is the ability to see change as an opportunity, not a threat.” Condition monitoring (CM) is transforming rapidly and so too must the mindset of CM practitioners and users.
It’s not good enough to simply disregard a disruptive technology in an effort to protect the “old guard.” When combating downtime, there’s no place for historical sentiment.
Steadily disrupting traditional vibration techniques is acoustic emission (AE). AE technology spawned from the aviation industry where vibration analysis simply couldn’t be easily applied, short of a suicidal maintenance technician hanging off the wings.
Acoustic emissiontechnique is based on frequencies much higher than are monitored in the repetitive, synchronous movement of vibration. These frequencies are the result of shock, impact, friction and cracking, for example. By this means, it is possible to detect impending failure before damage occurs, as well as monitoring its progress thereafter.
With well-defined ISO standards, traditional vibration techniques including vibration monitoring and vibration analysis have provided a trusted approach to condition monitoring for the past 30 years.
Yet, it remains a complex science and requires sophisticated knowledge and understanding from a seasoned expert. In contrast, acoustic emission technology extends and simplifies the science, placing the power of vibration techniques directly into the hands of every engineer. Signals can be processed at the AE sensor into an easily understandable form.
Of course, vibration analysis (VA) as a technique will have a place for many for years to come for many end users. However, there is no escaping the fact that there is often a requirement for a costly and unsustainable level of knowledge required to affect a good diagnosis.
For vibration analysis, the defect repetition frequencies are critically dependent upon the machine component design and geometry, as well as the precise running speed. Vibration can occur independently in the X, Y or Z axis, and so orientation of the sensor is as important as location.
For a detailed interpretation, it is also necessary to know internal machine geometries, shaft speeds, meshing frequencies, etc., and to analyze the data before making a diagnosis. So in summary, vibration analysis is valuable but too often overly complicated.
With acoustic emission (AE), signal processing is undertaken automatically at the sensor level.
With vibration analysis (VA), the signal is processed downstream manually or semi-automatically.
The areas in which vibration and acoustic emission both apply can be illustrated as overlapping circles. However, acoustic emission provides an earlier warning, detecting wear and small defects, whereas with vibration, damage must have occurred to detect a signal.
AE will pick up a lack of lubrication, friction and cracking, which vibration will not, although it must be acknowledged that the totality of information obtained from AE will be more limited than that derived from vibration.
The signal processing required by acoustic emission is not something that can be performed by just anyone; it’s a high-frequency signal, so the user must have the knowledge to interpret the squiggly lines on a stethoscope.
However, recent developments have enabled this processing at the sensor level. The sensor output can now provide pre-characterized numbers that tell you about the condition of the machine. Acoustic emission technology has been effectively de-skilled, enabling much wider application use.
Suitable for continuously running machinery as well as machinery operating intermittently, slowly or for short durations, acoustic emission allows the user to diagnose problems with machinery at an early stage, carry out maintenance procedures and then monitor the improvement. It provides real-time information with early sensitivity to faults and applicability to a wide range of rotational speeds.
As awareness of the unique capabilities of acoustic emission increases, so too does the number of applications that it is suited to, many of which have proven difficult for other forms of condition monitoring to address.
For example, the analysis of signals, whether from AE sensors or accelerometers, requires a sufficiently long period of machine running at constant speed so that a statistically meaningful signal characterization can be made. But that is where the similarity stops. AE can be effective after around 10 seconds of measurements.
For example, the algorithm used to derive the widely used acoustic emission parameters of Distress and dB Level in the MHC range of products from Kittiwake Holroyd requires a 10-second period of running at an approximately constant speed.
This compares favorably to Fast Fourier Transform (FFT) based vibration analysis, which typically needs 60 to 120 seconds of measurement time and tight tolerances on machine speed for an effective signal interpretation.
In cases where a hand-held instrument is used for periodic CM, it may be possible to interrupt normal machine operation and put it into a special continuously running mode for the duration of condition monitoring measurements. However, such disruption is not always possible and never convenient.
Furthermore, it is not compatible with the current trend toward condition monitoring automation, which requires continuous online monitoring with permanently installed sensors inputting condition monitoring data or status into supervisory control and data acquisition (SCADA) systems or programmable logic controllers (PLCs).
So why are many condition monitoring practitioners being so resistant to the benefits that AE brings to the table? It may be because many people have invested a lifetime in vibration and are understandably wary of losing power and status.
After all, if you “dumb down” vibration, surely this reduces the perceived value that they bring to the organization. Actually, it doesn’t. Just because AE is disruptive as a technology, it in no way invalidates traditional vibration techniques but simply extends the impact way beyond what has been able to be achieved to date.
For vibration techniques to be effective, you need equipment that’s far from cheap coupled with clever people to get the best from it. Every result must be analyzed to understand what’s good and what’s bad.
For those who cannot afford the luxury of in-house vibration experts, there are many vibration specialists who offer a contract monitoring service, which is not an insignificant investment. While for some, the criticality of certain applications coupled with the scale of some companies might justify this cost, others could still benefit from the efficiencies realized by similar CM techniques.
Furthermore, the “we don’t buy into one-month wonders/we’ve all been bitten by the latest whizz-bang technology” argument no longer rings true. Indeed, AE techniques are only deemed disruptive because they are now mature with a proven track record.
Ultimately, maintenance personnel are responsible for keeping machinery running. If they are empowered to monitor condition themselves, identify where action is needed and then check that the action taken has solved the problem, then AE has significant advantages of cost, speed, flexibility and ease of field application in comparison to traditional vibration analysis techniques. It is the efficient and effective approach to CM.
To nurture the technology of a new era, a broader, longer-term view is required. Surely it makes sense to embrace CM techniques that provide for the greatest protection or longest period of warning for potential damage and eventual failure.
By “de-skilling” technology, all maintenance professionals are empowered to make informed decisions quickly and with confidence, ultimately enabling them to positively and significantly impact a company’s bottom line. Of course, there is room for sentiment in business but not at the expense of progress.