Challenges and obstacles in the application of acoustic emission to process machinery

Abstract

Managing asset integrity is crucial for the cost-effective asset management of processing plants. Consequently, new techniques for detection and classification of incipient faults are continuously being sought by industry and developed by research and development professionals, both corporate and academic. Although acoustic emission (AE) testing for faults in static equipment has been used since the 1970s, its use as a monitoring technology for various machinery conditions has been poorly adopted by industry, despite a significant volume of work having been published over the past twenty years describing success in detecting numerous rotating and reciprocating machinery faults. Anecdotal evidence from industry suggests that many 'tried and failed'. The authors believe that this is because applying AE monitoring to industrial plant is fraught with poorly documented challenges, obstacles, and limitations that must be well understood and overcome before any reported results can be replicated. Thus, to enable potential users to approach AE monitoring with more realistic expectations, the current paper discusses several such problems and suggests some available techniques for their management. After an initial introduction on the basics of AE specifically applied to machinery monitoring, issues are divided into generic problems and application-specific challenges.

The application of spectral kurtosis on Acoustic Emission and vibrations from a defective bearing

“…This was attributed to the variation in test rig assembly, such as adjustments and sensor attachments; therefore it offered a good opportunity to asses methods for diagnosis. Such challenges with AE sensor attachment and noise interference have been discussed recently [13]. The overall trends of Acoustic Emission and vibration levels for both tests are presented in Fig.…”

The combined use of vibration, acoustic emission and oil debris on-line monitoring towards a more effective condition monitoring of rotating machinery

“…It was observed that the AE RMS varied with time as the gearbox reached a stabilized temperature and the variation in AE activity RMS could be as much as 33% [16,17]. In [18] challenges and obstacles in the application of acoustic emission to process machinery are discussed whilst in Hamzah and Mba [19] investigate the influence of operating conditions in recorded acoustic emission in helical gears as well. Recently, independent component analysis (ICA) has been applied to extract meaningful information from a collection of data regarding rotating machinery health monitoring yielding promising results [20].…”

How can Acoustic Emission Signals be Used in Condition Monitoring and Diagnosis of Diesel Engine Condition?

“…It further poses problems in AE signal analysis when multiple sensors are needed in health monitoring of multi cylinder diesel engine [4]. Consequently, the accuracy of results obtained for direct comparison of AE signals from different (un-calibrated) sensors is always questionable since each AE sensor has the inherently unique nonlinear frequency response during the manufacturing process [5]. The second part of this paper will present a simple processing technique where the nonlinear responses of AE sensors are normalized in the frequency domain based on the sensor calibration chart provided by the manufacturer [6].…”