PSI - Issue 17

Andra Gabriela Stancu et al. / Procedia Structural Integrity 17 (2019) 238–245 A. G. Stancu et al./ Structural Integrity Procedia 00 (2019) 000 – 000

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5

The condition monitoring process assumes the comparison of each signature with the baseline, in which case the process M is similarly defined as Equation 2 and 3, as follows: = [ ( × +1:( +1)× 1 ) ( × +1:( +1)× 2 ) ⋮ ( × +1:( +1)× ) ] (6)

( , ) = 100% × √ 1 ∑ =1 [1 − ( +1:( +1)× ) ( 1 : )) ] 2

(7)

Deviations from the baseline can be plotted as a trend of systematic progression and are calculated using Equations (6) and (7). Assuming the system operates fault free, it is anticipated that M will remain a steady horizontal trend.

3. Case study and algorithm validation

The programme of work carried out involves monitoring of slow speed rotating machinery components (shaft and bearing), using AE. Over the last years, other research studies have focused on the use of AE for this particular application, such as [12], [13]. The development and validation of the algorithm was performed on a practical case study, involving an escalator bearing, which operates constantly at a low speed of 12RPM. The mechanism was regularly inspected using vibration analysis. In spite of the inspection programme in place, unexpected failures occur, without any symptoms detected in advance, hence the motivation for conducting this research. While vibration monitoring is the most regularly used technique in rotating machinery applications, at very low RPM it is difficult to diagnose damage or degradation. One reason is the background noise in the fault signals, being complicated and of the small amount of energy and preventing conventional vibration testing methods from being sensitive enough. Acoustic Emission is a high frequency elastic wave emitted due to structural damage. Fundamentally, the frequency range of acoustic emission signals is broader in comparison with vibration signals and can detect small-scale degradation, such as friction and material loss at very early stages. The use of acoustic emission enables inhibiting the noise interferences and therefore improve diagnostics accuracy. For this reason, this technique is applicable to slow speed rotating machinery and is able to detect small energy release rates. Furthermore, the broader frequency spectrum (1 - 100 MHz) in comparison with vibration signal facilitates various high-frequency or structural resonance related signal processing techniques. 3.1. Technique selection

Figure 1. Acoustic emission signals: representation of continuous and burst type emission.