Precursory waves and eigenfrequencies identified from acoustic emission data based on Singular Spectrum Analysis and laboratory rock-burst experiments
Important task for acoustic emission (AE) monitoring involves detecting frequency shift phenomenon and intense periodic components. In the present research, we investigate time dynamics embedded in AE signal acquired in the laboratory rock burst experiment on limestone sample. By applying the Singul...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
Gong, Yuxin [verfasserIn] |
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| Format: |
E-Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
2017transfer abstract |
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| Schlagwörter: |
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| Umfang: |
15 |
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| Übergeordnetes Werk: |
Enthalten in: Synthesis, structural and luminescence properties of Ti co-doped ZnO/Zn2SiO4:Mn2+composite phosphor - Ramakrishna, P.V. ELSEVIER, 2014transfer abstract, RMMS, Oxford |
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| Übergeordnetes Werk: |
volume:91 ; year:2017 ; pages:155-169 ; extent:15 |
| Links: |
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| DOI / URN: |
10.1016/j.ijrmms.2016.11.020 |
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| 245 | 1 | 0 | |a Precursory waves and eigenfrequencies identified from acoustic emission data based on Singular Spectrum Analysis and laboratory rock-burst experiments |
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| 520 | |a Important task for acoustic emission (AE) monitoring involves detecting frequency shift phenomenon and intense periodic components. In the present research, we investigate time dynamics embedded in AE signal acquired in the laboratory rock burst experiment on limestone sample. By applying the Singular Spectrum Analysis (SSA)-based algorithm developed in this research, we reconstruct the decomposed components and then select the main component with a decision-making process based on the criterion that it should be significant both in the eigenvector space and spectral domain, termed eigenfrequency. The frequency shift phenomenon is represented by the eigenfrequencies of the first main component consistently. Precursory waves of the first main component represents time dynamics of the rock burst process by elastic wave over the low-level loading phase, high-frequency wave with self-oscillating envelopes at unloading, low-frequency quasi-shock waves during the rheological delay phase and low-frequency shock wave at complete rock burst failure. | ||
| 520 | |a Important task for acoustic emission (AE) monitoring involves detecting frequency shift phenomenon and intense periodic components. In the present research, we investigate time dynamics embedded in AE signal acquired in the laboratory rock burst experiment on limestone sample. By applying the Singular Spectrum Analysis (SSA)-based algorithm developed in this research, we reconstruct the decomposed components and then select the main component with a decision-making process based on the criterion that it should be significant both in the eigenvector space and spectral domain, termed eigenfrequency. The frequency shift phenomenon is represented by the eigenfrequencies of the first main component consistently. Precursory waves of the first main component represents time dynamics of the rock burst process by elastic wave over the low-level loading phase, high-frequency wave with self-oscillating envelopes at unloading, low-frequency quasi-shock waves during the rheological delay phase and low-frequency shock wave at complete rock burst failure. | ||
| 650 | 7 | |a Singular spectrum analysis |2 Elsevier | |
| 650 | 7 | |a Frequency shift |2 Elsevier | |
| 650 | 7 | |a Acoustic emission |2 Elsevier | |
| 650 | 7 | |a Eigenfrequency |2 Elsevier | |
| 650 | 7 | |a Rock burst precursor |2 Elsevier | |
| 700 | 1 | |a Song, Zhanjie |4 oth | |
| 700 | 1 | |a He, Manchao |4 oth | |
| 700 | 1 | |a Gong, Weili |4 oth | |
| 700 | 1 | |a Ren, Fuqiang |4 oth | |
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10.1016/j.ijrmms.2016.11.020 doi GBV00000000000049A.pica (DE-627)ELV040253880 (ELSEVIER)S1365-1609(16)30452-X DE-627 ger DE-627 rakwb eng 690 550 690 DE-600 550 DE-600 670 VZ 333.7 610 VZ 43.12 bkl 43.13 bkl 44.13 bkl Gong, Yuxin verfasserin aut Precursory waves and eigenfrequencies identified from acoustic emission data based on Singular Spectrum Analysis and laboratory rock-burst experiments 2017transfer abstract 15 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier Important task for acoustic emission (AE) monitoring involves detecting frequency shift phenomenon and intense periodic components. In the present research, we investigate time dynamics embedded in AE signal acquired in the laboratory rock burst experiment on limestone sample. By applying the Singular Spectrum Analysis (SSA)-based algorithm developed in this research, we reconstruct the decomposed components and then select the main component with a decision-making process based on the criterion that it should be significant both in the eigenvector space and spectral domain, termed eigenfrequency. The frequency shift phenomenon is represented by the eigenfrequencies of the first main component consistently. Precursory waves of the first main component represents time dynamics of the rock burst process by elastic wave over the low-level loading phase, high-frequency wave with self-oscillating envelopes at unloading, low-frequency quasi-shock waves during the rheological delay phase and low-frequency shock wave at complete rock burst failure. Important task for acoustic emission (AE) monitoring involves detecting frequency shift phenomenon and intense periodic components. In the present research, we investigate time dynamics embedded in AE signal acquired in the laboratory rock burst experiment on limestone sample. By applying the Singular Spectrum Analysis (SSA)-based algorithm developed in this research, we reconstruct the decomposed components and then select the main component with a decision-making process based on the criterion that it should be significant both in the eigenvector space and spectral domain, termed eigenfrequency. The frequency shift phenomenon is represented by the eigenfrequencies of the first main component consistently. Precursory waves of the first main component represents time dynamics of the rock burst process by elastic wave over the low-level loading phase, high-frequency wave with self-oscillating envelopes at unloading, low-frequency quasi-shock waves during the rheological delay phase and low-frequency shock wave at complete rock burst failure. Singular spectrum analysis Elsevier Frequency shift Elsevier Acoustic emission Elsevier Eigenfrequency Elsevier Rock burst precursor Elsevier Song, Zhanjie oth He, Manchao oth Gong, Weili oth Ren, Fuqiang oth Enthalten in Pergamon Ramakrishna, P.V. ELSEVIER Synthesis, structural and luminescence properties of Ti co-doped ZnO/Zn2SiO4:Mn2+composite phosphor 2014transfer abstract RMMS Oxford (DE-627)ELV017417449 volume:91 year:2017 pages:155-169 extent:15 https://doi.org/10.1016/j.ijrmms.2016.11.020 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U SSG-OLC-PHA SSG-OPC-GGO GBV_ILN_20 GBV_ILN_24 GBV_ILN_70 GBV_ILN_105 GBV_ILN_120 43.12 Umweltchemie VZ 43.13 Umwelttoxikologie VZ 44.13 Medizinische Ökologie VZ AR 91 2017 155-169 15 045F 690 |
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10.1016/j.ijrmms.2016.11.020 doi GBV00000000000049A.pica (DE-627)ELV040253880 (ELSEVIER)S1365-1609(16)30452-X DE-627 ger DE-627 rakwb eng 690 550 690 DE-600 550 DE-600 670 VZ 333.7 610 VZ 43.12 bkl 43.13 bkl 44.13 bkl Gong, Yuxin verfasserin aut Precursory waves and eigenfrequencies identified from acoustic emission data based on Singular Spectrum Analysis and laboratory rock-burst experiments 2017transfer abstract 15 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier Important task for acoustic emission (AE) monitoring involves detecting frequency shift phenomenon and intense periodic components. In the present research, we investigate time dynamics embedded in AE signal acquired in the laboratory rock burst experiment on limestone sample. By applying the Singular Spectrum Analysis (SSA)-based algorithm developed in this research, we reconstruct the decomposed components and then select the main component with a decision-making process based on the criterion that it should be significant both in the eigenvector space and spectral domain, termed eigenfrequency. The frequency shift phenomenon is represented by the eigenfrequencies of the first main component consistently. Precursory waves of the first main component represents time dynamics of the rock burst process by elastic wave over the low-level loading phase, high-frequency wave with self-oscillating envelopes at unloading, low-frequency quasi-shock waves during the rheological delay phase and low-frequency shock wave at complete rock burst failure. Important task for acoustic emission (AE) monitoring involves detecting frequency shift phenomenon and intense periodic components. In the present research, we investigate time dynamics embedded in AE signal acquired in the laboratory rock burst experiment on limestone sample. By applying the Singular Spectrum Analysis (SSA)-based algorithm developed in this research, we reconstruct the decomposed components and then select the main component with a decision-making process based on the criterion that it should be significant both in the eigenvector space and spectral domain, termed eigenfrequency. The frequency shift phenomenon is represented by the eigenfrequencies of the first main component consistently. Precursory waves of the first main component represents time dynamics of the rock burst process by elastic wave over the low-level loading phase, high-frequency wave with self-oscillating envelopes at unloading, low-frequency quasi-shock waves during the rheological delay phase and low-frequency shock wave at complete rock burst failure. Singular spectrum analysis Elsevier Frequency shift Elsevier Acoustic emission Elsevier Eigenfrequency Elsevier Rock burst precursor Elsevier Song, Zhanjie oth He, Manchao oth Gong, Weili oth Ren, Fuqiang oth Enthalten in Pergamon Ramakrishna, P.V. ELSEVIER Synthesis, structural and luminescence properties of Ti co-doped ZnO/Zn2SiO4:Mn2+composite phosphor 2014transfer abstract RMMS Oxford (DE-627)ELV017417449 volume:91 year:2017 pages:155-169 extent:15 https://doi.org/10.1016/j.ijrmms.2016.11.020 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U SSG-OLC-PHA SSG-OPC-GGO GBV_ILN_20 GBV_ILN_24 GBV_ILN_70 GBV_ILN_105 GBV_ILN_120 43.12 Umweltchemie VZ 43.13 Umwelttoxikologie VZ 44.13 Medizinische Ökologie VZ AR 91 2017 155-169 15 045F 690 |
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10.1016/j.ijrmms.2016.11.020 doi GBV00000000000049A.pica (DE-627)ELV040253880 (ELSEVIER)S1365-1609(16)30452-X DE-627 ger DE-627 rakwb eng 690 550 690 DE-600 550 DE-600 670 VZ 333.7 610 VZ 43.12 bkl 43.13 bkl 44.13 bkl Gong, Yuxin verfasserin aut Precursory waves and eigenfrequencies identified from acoustic emission data based on Singular Spectrum Analysis and laboratory rock-burst experiments 2017transfer abstract 15 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier Important task for acoustic emission (AE) monitoring involves detecting frequency shift phenomenon and intense periodic components. In the present research, we investigate time dynamics embedded in AE signal acquired in the laboratory rock burst experiment on limestone sample. By applying the Singular Spectrum Analysis (SSA)-based algorithm developed in this research, we reconstruct the decomposed components and then select the main component with a decision-making process based on the criterion that it should be significant both in the eigenvector space and spectral domain, termed eigenfrequency. The frequency shift phenomenon is represented by the eigenfrequencies of the first main component consistently. Precursory waves of the first main component represents time dynamics of the rock burst process by elastic wave over the low-level loading phase, high-frequency wave with self-oscillating envelopes at unloading, low-frequency quasi-shock waves during the rheological delay phase and low-frequency shock wave at complete rock burst failure. Important task for acoustic emission (AE) monitoring involves detecting frequency shift phenomenon and intense periodic components. In the present research, we investigate time dynamics embedded in AE signal acquired in the laboratory rock burst experiment on limestone sample. By applying the Singular Spectrum Analysis (SSA)-based algorithm developed in this research, we reconstruct the decomposed components and then select the main component with a decision-making process based on the criterion that it should be significant both in the eigenvector space and spectral domain, termed eigenfrequency. The frequency shift phenomenon is represented by the eigenfrequencies of the first main component consistently. Precursory waves of the first main component represents time dynamics of the rock burst process by elastic wave over the low-level loading phase, high-frequency wave with self-oscillating envelopes at unloading, low-frequency quasi-shock waves during the rheological delay phase and low-frequency shock wave at complete rock burst failure. Singular spectrum analysis Elsevier Frequency shift Elsevier Acoustic emission Elsevier Eigenfrequency Elsevier Rock burst precursor Elsevier Song, Zhanjie oth He, Manchao oth Gong, Weili oth Ren, Fuqiang oth Enthalten in Pergamon Ramakrishna, P.V. ELSEVIER Synthesis, structural and luminescence properties of Ti co-doped ZnO/Zn2SiO4:Mn2+composite phosphor 2014transfer abstract RMMS Oxford (DE-627)ELV017417449 volume:91 year:2017 pages:155-169 extent:15 https://doi.org/10.1016/j.ijrmms.2016.11.020 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U SSG-OLC-PHA SSG-OPC-GGO GBV_ILN_20 GBV_ILN_24 GBV_ILN_70 GBV_ILN_105 GBV_ILN_120 43.12 Umweltchemie VZ 43.13 Umwelttoxikologie VZ 44.13 Medizinische Ökologie VZ AR 91 2017 155-169 15 045F 690 |
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10.1016/j.ijrmms.2016.11.020 doi GBV00000000000049A.pica (DE-627)ELV040253880 (ELSEVIER)S1365-1609(16)30452-X DE-627 ger DE-627 rakwb eng 690 550 690 DE-600 550 DE-600 670 VZ 333.7 610 VZ 43.12 bkl 43.13 bkl 44.13 bkl Gong, Yuxin verfasserin aut Precursory waves and eigenfrequencies identified from acoustic emission data based on Singular Spectrum Analysis and laboratory rock-burst experiments 2017transfer abstract 15 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier Important task for acoustic emission (AE) monitoring involves detecting frequency shift phenomenon and intense periodic components. In the present research, we investigate time dynamics embedded in AE signal acquired in the laboratory rock burst experiment on limestone sample. By applying the Singular Spectrum Analysis (SSA)-based algorithm developed in this research, we reconstruct the decomposed components and then select the main component with a decision-making process based on the criterion that it should be significant both in the eigenvector space and spectral domain, termed eigenfrequency. The frequency shift phenomenon is represented by the eigenfrequencies of the first main component consistently. Precursory waves of the first main component represents time dynamics of the rock burst process by elastic wave over the low-level loading phase, high-frequency wave with self-oscillating envelopes at unloading, low-frequency quasi-shock waves during the rheological delay phase and low-frequency shock wave at complete rock burst failure. Important task for acoustic emission (AE) monitoring involves detecting frequency shift phenomenon and intense periodic components. In the present research, we investigate time dynamics embedded in AE signal acquired in the laboratory rock burst experiment on limestone sample. By applying the Singular Spectrum Analysis (SSA)-based algorithm developed in this research, we reconstruct the decomposed components and then select the main component with a decision-making process based on the criterion that it should be significant both in the eigenvector space and spectral domain, termed eigenfrequency. The frequency shift phenomenon is represented by the eigenfrequencies of the first main component consistently. Precursory waves of the first main component represents time dynamics of the rock burst process by elastic wave over the low-level loading phase, high-frequency wave with self-oscillating envelopes at unloading, low-frequency quasi-shock waves during the rheological delay phase and low-frequency shock wave at complete rock burst failure. Singular spectrum analysis Elsevier Frequency shift Elsevier Acoustic emission Elsevier Eigenfrequency Elsevier Rock burst precursor Elsevier Song, Zhanjie oth He, Manchao oth Gong, Weili oth Ren, Fuqiang oth Enthalten in Pergamon Ramakrishna, P.V. ELSEVIER Synthesis, structural and luminescence properties of Ti co-doped ZnO/Zn2SiO4:Mn2+composite phosphor 2014transfer abstract RMMS Oxford (DE-627)ELV017417449 volume:91 year:2017 pages:155-169 extent:15 https://doi.org/10.1016/j.ijrmms.2016.11.020 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U SSG-OLC-PHA SSG-OPC-GGO GBV_ILN_20 GBV_ILN_24 GBV_ILN_70 GBV_ILN_105 GBV_ILN_120 43.12 Umweltchemie VZ 43.13 Umwelttoxikologie VZ 44.13 Medizinische Ökologie VZ AR 91 2017 155-169 15 045F 690 |
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10.1016/j.ijrmms.2016.11.020 doi GBV00000000000049A.pica (DE-627)ELV040253880 (ELSEVIER)S1365-1609(16)30452-X DE-627 ger DE-627 rakwb eng 690 550 690 DE-600 550 DE-600 670 VZ 333.7 610 VZ 43.12 bkl 43.13 bkl 44.13 bkl Gong, Yuxin verfasserin aut Precursory waves and eigenfrequencies identified from acoustic emission data based on Singular Spectrum Analysis and laboratory rock-burst experiments 2017transfer abstract 15 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier Important task for acoustic emission (AE) monitoring involves detecting frequency shift phenomenon and intense periodic components. In the present research, we investigate time dynamics embedded in AE signal acquired in the laboratory rock burst experiment on limestone sample. By applying the Singular Spectrum Analysis (SSA)-based algorithm developed in this research, we reconstruct the decomposed components and then select the main component with a decision-making process based on the criterion that it should be significant both in the eigenvector space and spectral domain, termed eigenfrequency. The frequency shift phenomenon is represented by the eigenfrequencies of the first main component consistently. Precursory waves of the first main component represents time dynamics of the rock burst process by elastic wave over the low-level loading phase, high-frequency wave with self-oscillating envelopes at unloading, low-frequency quasi-shock waves during the rheological delay phase and low-frequency shock wave at complete rock burst failure. Important task for acoustic emission (AE) monitoring involves detecting frequency shift phenomenon and intense periodic components. In the present research, we investigate time dynamics embedded in AE signal acquired in the laboratory rock burst experiment on limestone sample. By applying the Singular Spectrum Analysis (SSA)-based algorithm developed in this research, we reconstruct the decomposed components and then select the main component with a decision-making process based on the criterion that it should be significant both in the eigenvector space and spectral domain, termed eigenfrequency. The frequency shift phenomenon is represented by the eigenfrequencies of the first main component consistently. Precursory waves of the first main component represents time dynamics of the rock burst process by elastic wave over the low-level loading phase, high-frequency wave with self-oscillating envelopes at unloading, low-frequency quasi-shock waves during the rheological delay phase and low-frequency shock wave at complete rock burst failure. Singular spectrum analysis Elsevier Frequency shift Elsevier Acoustic emission Elsevier Eigenfrequency Elsevier Rock burst precursor Elsevier Song, Zhanjie oth He, Manchao oth Gong, Weili oth Ren, Fuqiang oth Enthalten in Pergamon Ramakrishna, P.V. ELSEVIER Synthesis, structural and luminescence properties of Ti co-doped ZnO/Zn2SiO4:Mn2+composite phosphor 2014transfer abstract RMMS Oxford (DE-627)ELV017417449 volume:91 year:2017 pages:155-169 extent:15 https://doi.org/10.1016/j.ijrmms.2016.11.020 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U SSG-OLC-PHA SSG-OPC-GGO GBV_ILN_20 GBV_ILN_24 GBV_ILN_70 GBV_ILN_105 GBV_ILN_120 43.12 Umweltchemie VZ 43.13 Umwelttoxikologie VZ 44.13 Medizinische Ökologie VZ AR 91 2017 155-169 15 045F 690 |
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Enthalten in Synthesis, structural and luminescence properties of Ti co-doped ZnO/Zn2SiO4:Mn2+composite phosphor Oxford volume:91 year:2017 pages:155-169 extent:15 |
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Synthesis, structural and luminescence properties of Ti co-doped ZnO/Zn2SiO4:Mn2+composite phosphor |
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Precursory waves and eigenfrequencies identified from acoustic emission data based on Singular Spectrum Analysis and laboratory rock-burst experiments |
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Important task for acoustic emission (AE) monitoring involves detecting frequency shift phenomenon and intense periodic components. In the present research, we investigate time dynamics embedded in AE signal acquired in the laboratory rock burst experiment on limestone sample. By applying the Singular Spectrum Analysis (SSA)-based algorithm developed in this research, we reconstruct the decomposed components and then select the main component with a decision-making process based on the criterion that it should be significant both in the eigenvector space and spectral domain, termed eigenfrequency. The frequency shift phenomenon is represented by the eigenfrequencies of the first main component consistently. Precursory waves of the first main component represents time dynamics of the rock burst process by elastic wave over the low-level loading phase, high-frequency wave with self-oscillating envelopes at unloading, low-frequency quasi-shock waves during the rheological delay phase and low-frequency shock wave at complete rock burst failure. |
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Important task for acoustic emission (AE) monitoring involves detecting frequency shift phenomenon and intense periodic components. In the present research, we investigate time dynamics embedded in AE signal acquired in the laboratory rock burst experiment on limestone sample. By applying the Singular Spectrum Analysis (SSA)-based algorithm developed in this research, we reconstruct the decomposed components and then select the main component with a decision-making process based on the criterion that it should be significant both in the eigenvector space and spectral domain, termed eigenfrequency. The frequency shift phenomenon is represented by the eigenfrequencies of the first main component consistently. Precursory waves of the first main component represents time dynamics of the rock burst process by elastic wave over the low-level loading phase, high-frequency wave with self-oscillating envelopes at unloading, low-frequency quasi-shock waves during the rheological delay phase and low-frequency shock wave at complete rock burst failure. |
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Important task for acoustic emission (AE) monitoring involves detecting frequency shift phenomenon and intense periodic components. In the present research, we investigate time dynamics embedded in AE signal acquired in the laboratory rock burst experiment on limestone sample. By applying the Singular Spectrum Analysis (SSA)-based algorithm developed in this research, we reconstruct the decomposed components and then select the main component with a decision-making process based on the criterion that it should be significant both in the eigenvector space and spectral domain, termed eigenfrequency. The frequency shift phenomenon is represented by the eigenfrequencies of the first main component consistently. Precursory waves of the first main component represents time dynamics of the rock burst process by elastic wave over the low-level loading phase, high-frequency wave with self-oscillating envelopes at unloading, low-frequency quasi-shock waves during the rheological delay phase and low-frequency shock wave at complete rock burst failure. |
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Precursory waves and eigenfrequencies identified from acoustic emission data based on Singular Spectrum Analysis and laboratory rock-burst experiments |
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