A new method for determining the crack classification criterion in acoustic emission parameter analysis

Significance 

Engineering materials exhibit various properties, including brittleness. At the microscopic scale, brittle materials are highly susceptible to failure initiated by crack initiation, propagation, and coalescence. Thus, it is imperative to analyze the cracks to ensure high structural integrity. Currently, the acoustic emission technique has been widely used to study the formation and growth of cracks in brittle materials and predict the safety and performance of engineering structures. Acoustic emission can be classified into a waveform-based approach and parameter-based approach/parameter analysis. However, parameter analysis is commonly used owing to its convenience and less time-consuming. Besides, it uses two key parameters: RA value and average frequency, used as a criterion for classifying crack modes. Unfortunately, parameter analysis in crack classification is mostly based on the empirical relation between the parameters, which may not provide the desired accuracy. Moreover, the optimal transition line between shear and tensile cracks have not been clarified.

Recent research revealed that improving crack classification based on parametric analysis requires effective methods for determining the optimal ratio of the RA value and average frequency. To this note, Dr. Zheng-Hu Zhang from the Dalian University of Technology, in collaboration with Professor Jian-Hui Deng from Sichuan University developed a new method for determining the crack transition line for crack classification in acoustic emission parameter analysis. The novel approach was based on the statistical analysis of the dominant frequency characteristics of acoustic emission signals. The aim was to combine the advantages of waveform and parametric analysis to improve the accuracy and efficiency of acoustic emission crack analysis. Their work is currently published in the International Journal of Rock Mechanics and Mining Sciences.

In their approach, four types of rocks: marble, diorite, fine-grained granite, and coarse-grained granite, were utilized as specimens. First, the four specimens were subjected to unconfined compression tests, and their acoustic emissions were monitored. Next, the optimal transition line in the acoustic emission parameter analysis was determined via statistical analysis of dominant frequency characteristics of AE waveforms. Lastly, the feasibility of the proposed method was verified by comparing the crack modes acquired by the proposed method with those obtained by the polarity method.

The authors determined the predicted ratios of both tensile and shear cracks for a series of different transition lines. Also, the proportions of waveforms distributed in the low and high dominant frequency bands were determined. Specifically, the optimal transition line was reported to correspond to the least square difference between the measurements and predicted data. From the laboratory tests, the optimal line in the parameter analysis of brittle rocks subjected to compression was observed to lie in the range 1:100 to 1:500. Different rock types exhibited different optimal transition lines, which could be attributed to the difference in the microstructure and mineral composition.

In summary, the study proposed a new method, based on a statistical analysis of dominant frequency characteristics, for determining the crack classification criterion in acoustic emission parameter analysis. Combining the merits of waveform and parameter analysis, the proposed method significantly improved the accuracy and efficiency of acoustic emission classification of cracks as well as structural monitoring and damage analysis. In a statement to Advances in Engineering, the authors said their study would improve crack classification, thus enhancing the performance and longevity of engineering structures.

A new method for determining the crack classification criterion in acoustic emission parameter analysis - Advances in Engineering
Fig. 1. Characteristic of dominant frequency versus the normalized applied stress in white marble during direct tensile tests.13
A new method for determining the crack classification criterion in acoustic emission parameter analysis - Advances in Engineering
Fig. 2. Characteristic parameters of a simplified AE hit.
A new method for determining the crack classification criterion in acoustic emission parameter analysis - Advances in Engineering
Fig. 3. Crack classification in AE parameter analysis.22
A new method for determining the crack classification criterion in acoustic emission parameter analysis - Advances in Engineering
Fig. 4. Flowchart of the proposed method for determining the optimal transition line between shear and tensile cracks in AE parameter analysis.
A new method for determining the crack classification criterion in acoustic emission parameter analysis - Advances in Engineering
Fig. 5. Typical rock specimens for different rock types: (a) marble; (b) fine-grained granite; (c) diorite; and (d) coarse-grained granite.
A new method for determining the crack classification criterion in acoustic emission parameter analysis - Advances in Engineering
Fig. 6. Schematic diagram of acoustic emission monitoring.
A new method for determining the crack classification criterion in acoustic emission parameter analysis - Advances in Engineering
Fig. 7. AE sensor and its sensitivity calibration curve: (a) picture of AE sensor; and (b) sensitivity calibration curve of AE sensor.
A new method for determining the crack classification criterion in acoustic emission parameter analysis - Advances in Engineering
Fig. 8. Representative AE waveform in time domain and its corresponding spectrum in frequency domain: (a) AE waveform and (b) amplitude spectrum.
A new method for determining the crack classification criterion in acoustic emission parameter analysis - Advances in Engineering
Fig. 9. Typical temporal change of A-FRQ and RA values in different rock types: (a) marble; (b) fine-grained granite; (c) diorite; and (d) coarse-grained granite.
A new method for determining the crack classification criterion in acoustic emission parameter analysis - Advances in Engineering
Fig. 10. Typical relationship between the A-FRQ and RA values in different rock types: (a) marble; (b) fine-grained granite; (c) diorite; and (d) coarse-grained granite.
A new method for determining the crack classification criterion in acoustic emission parameter analysis - Advances in Engineering
Fig. 11. Distribution of AE signals in the dominant frequency bands for different rock types: (a) marble; (b) fine-grained granite; (c) diorite; and (d) coarse-grained granite. Note that the dominant frequency band obeys the following rules: the interval of each of the first 45 bands is 10 kHz, where the No. 1 band ranges from 0 to 10 kHz and the No. 45 band ranges from 440 to 450 kHz, and dominant frequencies that are beyond 450 kHz were grouped into the No. 46 band.
A new method for determining the crack classification criterion in acoustic emission parameter analysis - Advances in Engineering
Fig. 12. Comparison between predicted and measured ratios of shear and tensile cracks for all rock specimens. Noted that the Av. represents the average value.
A new method for determining the crack classification criterion in acoustic emission parameter analysis - Advances in Engineering
Fig. 13. Proportions of tensile and shear cracks in marble specimens for different number values (n) for the moving average.
A new method for determining the crack classification criterion in acoustic emission parameter analysis - Advances in Engineering
Fig. 14. Typical spatial distribution of tensile and shear cracks in different rock types: (a) marble; (b) fine-grained granite; (c) diorite; (d) coarse-grained granite. Note that black lines represent the boundaries of rock specimens and green lines refer to macroscopic cracks distributed in rock specimens.
A new method for determining the crack classification criterion in acoustic emission parameter analysis - Advances in Engineering
Fig. 15. Proportions of different crack modes in marble specimens acquired from the polarity method (PM) and the parameter analysis (PA) by using the determined optimal transition line.

About the author

Dr. Zhenghu Zhang is currently a Research Fellow at the State Key Laboratory of Coastal and offshore Engineering, School of Civil Engineering of Dalian University of Technology, China. He received the bachelor’s degree in water resources and hydropower engineering from Sichuan University, China, in 2012, and the Ph.D. degree in civil engineering from Sichuan University, China, in 2018. He joined Dalian University of Technology in 2018. His current research focuses on rock mechanics, nondestructive testing technique, and stability analysis, monitoring and early warning of rock engineering. He is a fellow of CSRME and ISRM.

Personal Email: [email protected]

About the author

Prof. Jianhui Deng is currently the distinguished Professor of College of Water Resource and Hydropower of Sichuan University. He is Deputy Director of State Key Laboratory of Hydraulics and Mountain River Engineering. His background is in mining engineering, geotechnical mechanics, hydraulic structure engineering, as well as engineering geology. His research interests are mainly focused on deformation and stability analysis of slope and landslide, numerical analysis method, in-situ monitoring and feedback analysis.

He serves as Executive Member of CSRME. He is also invited as the editorial board member of academic journals, e.g., <Chinese Journal of Rock Mechanics and Engineering>,<Rock and Soil Mechanics>.

Personal Email: [email protected]

Reference

Zhang, Z., & Deng, J. (2020). A new method for determining the crack classification criterion in acoustic emission parameter analysisInternational Journal of Rock Mechanics and Mining Sciences, 130, 104323.

Go To International Journal of Rock Mechanics and Mining Sciences

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