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An investigation about the application of Acoustic Emission (AE) techniques to analyze the dynamic response of different cracked shafts rendered in bump tests is presented in this work. The experimental apparatus devised for this work complies of six shafts with different transverse crack sizes and a high-frequency data acquisition system. The AE signals generated in the bump tests performed on the different cracked shafts are captured by a wideband AE transducer. Those signals are treated by using statistical moments, wavelet transforms, and frequency- and time-domain procedures. A transverse crack of predetermined depth is etched into each shaft. The experimental results show that the values of kurtosis and skewness estimated for the AE signals can be used to identify the crack size.

Acoustic Emission (AE) is well known as a very efficient non-destructive technique for analysis, monitoring, and diagnosis of mechanical component failures. Elastic waves associated with defects or cracks on components subjected to steady-state or varying loads can propagate through the medium and be captured by AE sensors. The great sensitivity to crack detection may be considered as one of the main advantages of AE analysis. Only in the recent years, some AE analyses have been developed for rotating machinery failure diagnosis and bearing failure detection [

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Most of the recent works on the application of AE techniques in rotating systems is concerned with rotors supported by rolling bearings. Reference [

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Practically, the vast technical literature on the application of AE techniques in rotor dynamics is directed to analysis and detection of bearing failure. This paper deals with an experimental investigation about the AE analysis of cracked shafts. Six shafts with different transverse crack sizes are specially manufactured using commercial steel AISI 1020 for this work. The AE signals are captured during bump tests performed on all shafts [

A brief review of the statistical moments is presented to enlarge the understanding about their importance on the AE signal analysis.

Reference [

Skewness is a measure of the probability distribution asymmetry in relation to the average. Statistical distributions with data concentrated at one side from the mean value have large values of skewness. Negatively skewed distributions are not common in most engineering problems.

Skewness, S, can be expressed by Equation (1), in which _{3} are the second and third statistical moments, respectively.

The second statistical moment

The third statistical moment

Substituting Equation (2) and Equation (3) into Equation (1), the following expression is obtained for the skewness.

Reference [

Kurtosis is a measure of dispersion that characterizes the shape of the probability distribution. Kurtosis is associated with the fourth statistical moment of a probability distribution. Reference [

The skewness and kurtosis of the AE signal samples measured in the bump tests performed in this work are estimated to give some insights into the characteristics of the signal distribution.

The description of the experimental procedures employed in this work is presented into three items: 1) Shaft assembly; 2) AE data acquisition; and 3) AE signal analysis.

Six shafts made of commercial steel AISI 1020 are used in the bump tests [

A transverse crack is etched on the shaft by machining. Section A-A in

The shaft bump tests are performed at free-free boundary conditions [

Shaft | 1 | 2 | 3 | 4 | 5 | 6 |
---|---|---|---|---|---|---|

Ratio μ | 0.0 | 0.2 | 0.4 | 0.6 | 0.8 | 1.0 |

Each shaft undergoes five bump tests, which provide 30 AE signal samples for analysis. The bump is provided by a steel bar, which also is hanged from the ceiling using a 0.8 mm diameter nylon rope, as it is depicted in

The data acquistion system (DAQ) consists of an AE transducer PAC S9208, a NI deck PXI1042, a processor NI PXI 8106, a DAQ NI PXI6115 and a DAQ NI TB2708. The NI Sound and Vibation kit is used to capture the AE signals at sampling frequency of 0.4 MHz and acquisition time of 0.4 s. The signal amplitude is captured in volts. The AE data collected during the bump tests are stored in a computer for posterior analysis. The software MatLab© is employed to develop tools for analysis of the AE signal files.

The 30 AE signal samples are analyzed in the time-domain using the software MatLab©. The experimental data treatment is performed by using seven different approaches. In the first approach, the experimental data are treated by a Wavelet technique. Wavelet transform daubechies 4 [

It is noteworthy to say that assembly of the impacting metallic bar (

picts the AE curves rendered from the five bump tests performed on shaft 5 (µ = 0.8). The AE signal patterns are basically the same in all five bump tests.

The curves of AE amplitude distribution versus frequency for the 30 bump tests are shown in

Using the data from the distributions shown on

The mean value and the standard deviation from

Shaft | Average | Standard deviation σ |
---|---|---|

1 | 0.003626660 | 0.032385900 |

2 | 0.000432356 | 0.042992375 |

3 | 0.003069483 | 0.094906700 |

4 | 0.003982017 | 0.101927033 |

5 | 0.001094927 | 0.119982500 |

6 | −0.000899138 | 0.127265333 |

Finally,

The decreasing values of kurtosis as the crack depth increases, shown in

A very important finding in this work is the possibility of performing bump tests on rotating shafts in order to identify the crack initiation and to monitor the crack growth. The AE signal can be used to identify the presence of a crack and may even estimate the crack size. Further research is necessary to apply the same data treatment techniques on the AE signals on vibration tests performed on real operating conditions.

Shaft | Kurtosis | Skewness |
---|---|---|

1 | 8.347917255135211 | 2.571204037268968 |

2 | 5.947854644597201 | 2.083357350231635 |

3 | 2.225201824844565 | 0.880486883586829 |

4 | 2.056556545486382 | 0.778702767243726 |

5 | 1.763562767740631 | 0.550249606556120 |

The AE data rendered from the several bump tests performed on cracked shafts of different crack depths are treated by wavelet transform and statistical moments to analyze the influence of the crack size on the AE signal amplitude and frequency. The preliminary results obtained in this work indicate that a decrease on the AE amplitude peaks occurs as the crack depth increases. The values of kurtosis associated with the AE data apparently are very sensitive to the detection of geometric discontinuities in the shafts tested. At first glance, the statistical treatment of AE signals obtained in bump tests could be used to identify the crack initiation and monitor the crack growth in rotating shafts.

Pimentel-Junior, G.L.S., Oliveira, F.B. and Faria, M.T.C. (2016) On the Bump Tests of Cracked Shafts Using Acoustic Emission Techniques. Engineering, 8, 572-581. http://dx.doi.org/10.4236/eng.2016.89053