Equipment

Acoustic emission monitoring: An opportunity not a threat

Issue 11 and Volume 19.

Acoustic emission (AE) technology should be welcomed as the next generation in vibration monitoring, argues Martin Lucas, the managing director of Kittiwake Developments Ltd, UK.

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.

Martin Lucas of Kittiwake puts the case for AE technology

Acoustic emission (AE) technology was spawned in the aviation industry, where vibration analysis couldn’t be easily applied, short of a suicidal maintenance technician hanging off the wings. AE is based on frequencies much higher than those monitored in the repetitive synchronous movement of vibration. These frequencies result from shock, impact, friction and cracking, for example, and can make it possible to detect impending failure, as well as to monitor progress thereafter.

Simplifying the science

With well-defined ISO standards, traditional vibration techniques including vibration monitoring and vibration analysis have provided a trusted approach to condition monitoring for 30 years. Yet they remain a complex science and require sophisticated knowledge and understanding. AE 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 in an easily understandable form.

Let’s be clear, vibration analysis (VA) as a technique will have a place for many for years to come for many end-users. But there is no escaping from the fact that a costly and unsustainable level of knowledge is often required to achieve a good diagnosis.

For VA, the defect repetition frequencies depend critically 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, so orientation of the sensor is as important as location. A detailed interpretation also requires being aware of factors such as internal machine geometries, shaft speeds and meshing frequencies, and analysing the data before making a diagnosis. So, in objective summary, VA is valuable, but too often overly complicated.

Providing an earlier warning

With AE, signal processing is undertaken automatically at the sensor level, while with VA, the signal is processed downstream manually or semi-automatically. In fact, the areas where vibration and AE both apply can be illustrated as overlapping circles. But AE provides an earlier warning, detecting wear and small defects. 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. But it must be acknowledged that the totality of information from AE will be more limited than that from vibration.

Problems that can be detected with both VA and AE monitoring
Problems that AE technology alone can detect
Problems that VA alone can detect

The signal processing required by AE is, in itself, 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. But recent developments have enabled this processing at the sensor level. The sensor output can now provide pre-characterised numbers that tell you about the condition of the machine. AE technology has been effectively deskilled, enabling much wider application use.

Suitable for continuously running machinery, as well as machinery operating intermittently, slowly or for short durations, AE 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.

Shorter measurement periods

As awareness of the unique capabilities of AE increases, so do its applications – many of which have proven difficult for other forms of condition monitoring. For example, the analysis of signals, whether from AE sensors or accelerometers, requires a machine to run at constant speed for long enough for statistically meaningful signal characterisation to be made.

But that is where the similarity ends. AE can be effective after about 10 seconds of measurements. For example, the algorithm used to derive the widely used acoustic emission parameters of Distress® & dB Level in the MHC range of products from Kittiwake Holroyd requires a 10 second period of running at an approximately constant speed. By way of contrast, Fast Fourier Transform (FFT) based vibration analysis typically needs 60–120 seconds of measurement time and tight tolerances on machine speed for an effective signal interpretation.

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 CM measurements. But such disruption is not always possible and never convenient. Furthermore, it is not compatible with the current trend towards CM automation, which requires continuous online monitoring with permanently installed sensors inputting CM data or status into SCADA systems or PLCs. Kittiwake Holroyd’s AE product range includes portable instruments, permanently installed remote sensors for areas of difficult access, as well as stand-alone programmable smart sensors for continuous surveillance.

Why resist?

So why are many CM practitioners so resistant to the benefits that AE brings? We know many senior people have invested a lifetime in vibration and are, perhaps, understandably wary of losing power and status. After all, if you ‘dumb down’ vibration, surely this reduces the perceived value they bring? Actually, it doesn’t. Just because AE is disruptive as a technology, it in no way invalidates traditional vibration techniques.

For vibration techniques to be effective you need equipment that’s far from cheap coupled with clever people. Every result must be analysed to understand what’s good and what’s bad. For those that cannot afford in-house vibration experts, there are many vibration specialists who offer a contract monitoring service, again requiring not insignificant investment. While the criticality of certain applications coupled with the scale of some companies might justify this cost, others could still benefit from the efficiencies realised 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. AE techniques indeed are only deemed disruptive because they are now mature with a proven track record.

Keeping machinery running

Ultimately, maintenance personnel are responsible for keeping machinery running. If they are empowered to monitor condition themselves – so that they 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. It is the efficient and effective approach to CM.

We must start to take a broader, longer-term view, nurturing the technology of a new era. Surely it makes sense to embrace CM techniques that provide for the greatest protection or longest period of warning. If we can achieve similar results in a simpler, more cost-effective way, then – to borrow an Americanism – “go figure!” By ‘deskilling’ technology, all maintenance professionals can make informed decisions quickly and with confidence. Of course there is room for sentiment in business, but not at the expense of progress.

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