Abstract
Acoustic Emission (AE) is an effective nondestructive method for investigating the behavior of materials under stress. In recent decades, AE applications in structural health monitoring have been extended to other areas such as rotating machineries and cutting tools. This research investigates the application of acoustic emission data for unbalance analysis and detection in rotary systems. The AE parameter of interest in this study is a discrete variable that covers the significance of count, duration and amplitude of AE signals. A statistical model based on Zero-Inflated Poisson (ZIP) regression is proposed to handle over-dispersion and excess zeros of the counting data. The ZIP model indicates that faulty bearings can generate more transient wave in the AE waveform. Control charts can easily detect the faulty bearing using the parameters of the ZIP model. Categorical data analysis based on generalized linear models (GLM) is also presented. The results demonstrate the significance of the couple unbalance.
Highlights
Acoustic emission (AE) is defined as transient elastic waves generated due to localized physical changes in a solid material under mechanical or thermal stresses (Tan et al, 2007)
Acoustic Emission (AE) count rate was introduced as a reliable parameter for monitoring tool wear during turning, AE signals highly depend on process parameters (Li 2002, Sharma et al 2007)
This paper investigates the usefulness of AE data for unbalance analysis in rotary systems
Summary
Acoustic emission (AE) is defined as transient elastic waves generated due to localized physical changes in a solid material under mechanical or thermal stresses (Tan et al, 2007). The fundamental features of the AE hit include amplitude, duration, count, and rise time These parameters can be used to provide additional signal features such as root mean square (RMS), AE cumulative event count, counts to peak, rise time slope, crest factor and Kurtosis We provide more details of the application of AE count for fault detection. The unit of PAC-energy is micro-volt-seconds per count and the range is 0 to 65535 in each AE hit. This parameter is a discrete random variable that covers the significance of count, duration and peak amplitude.
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