Articles
Signal processing application for vibration generated by blasting in tunnels
- Details
- Category: Content №5 2021
- Last Updated on 29 October 2021
- Published on 30 November -0001
- Hits: 5022
Authors:
S.Feltane, orcid.org/0000-0003-3521-575X, Laboratory of Natural Resources and Development Badji Mokhtar University, Annaba, Algeria, e-mail: This email address is being protected from spambots. You need JavaScript enabled to view it.
S.Yahyaoui, orcid.org/0000-0002-9278-7562, National Polytechnic School, Alger, Algeria
A.Hafsaoui, orcid.org/0000-0002-1720-9527, Laboratory of Natural Resources and Development Badji Mokhtar University, Annaba, Algeria, e-mail: This email address is being protected from spambots. You need JavaScript enabled to view it.
A.Boussaid, orcid.org/0000-0002-6859-9983, University of brothers Mentouri, Constantine 1, Algeria
Naukovyi Visnyk Natsionalnoho Hirnychoho Universytetu. 2021, (5): 054 - 060
https://doi.org/10.33271/nvngu/2021-5/054
Abstract:
Purpose. To study the vibrations waves generated by blasting in a tunnel using the signal processing tools.
Methodology. Field tests are carried out to measure vibration wave during blasting operations at different locations in the tunnel and its immediate environment. Results of the measurements are processed by the autocorrelation method, which consists of filtering based on signal shape recognition. A comparison is accomplished between the peak particle velocities (PPV) measured and those obtained after filtering.
Findings. The results obtained after filtering gave a significant reduction in PPV of the measured vibration amplitudes in comparison to those obtained after treatment for the three components: longitudinal, transversal and vertical ones. Good knowledge of vibration source is important for amplitude attenuation regarding the observed difference between the recorded seismogram during explosion of a single unit charge and other standard explosions.
Originality. The work introduces signal processing methods for filtering vibration signals related to blasting, which is insufficiently studied.
Practical value. This study shows that the treatment of blasting vibrations by a filtering method should reduce the peak velocity of the particles by separating the signals and eliminating the interference in the initial signal.
Keywords: blasting, vibration amplitude, signal processing, autocorrelation methods, filtered signal, signal degradation
References.
1. Ragam, P., & Nimaje, D. (2018). Assessment of Blast-induced Ground Vibration using Different Predictor Approaches A Comparison. Chemical Engineering Transactions, 66, 487-492. https://doi.org/10.3303/CET1866082.
2. Aloui, M., Bleuzen, Y., Essefi, E., & Abbes, C. (2016). Ground vibrations and air blast effects induced by blasting in open pit mines: Case of Metlaoui Mining Basin, South western Tunisia. Journal of Geology and Geophysics,5(3).
3. Ray, S., & Dauji, S. (2019). Ground vibration attenuation relationship for underground blast: a case study. Journal of The Institution of Engineers (India): Series A, 100(4). https://doi.org/10.1007/s40030-019-00382-y.
4. Mansouri, H., & Farsangi Ebrahimi, M.A. (2015). Blast vibration modeling using linear superposition method. Journal of Mining and Environment, 6(2).
5. Chen, S.H., Wu, J., & Zhang, Z.H. (2015). Influence of millisecond time, charge length and detonation velocity on blasting vibration. Journal of Central South University, 22(12). https://doi.org/10.1007/s11771-015-3030-8.
6. Dhion, P., Chani, P., & Syarif, N. (2019), Linier Superposition Analysis on Managing Blasting Ground Vibration in Coal Mining. Indonesian Mining Professionals Journal. https://doi.org/10.36986/impj.v1i1.8.
7. Kumar, S., Mishra, A.K., Choudhary, B.S., Sinha, R.K., Deepak,D., & Agrawal, H. (2020). Prediction of ground vibration induced due to single hole blast using explicit dynamics. Mining, Metallurgy and Exploration, 37, 733-741.
8. Trivedi, R., Singh, T.N., Mudgal, K., & Gupta, N. (2014). Application of artificial neural network for blast performance evaluation.International Journal of Research in Engineering and Technology,3(5), 564-574.
9. Ragam, P., & Nimaje, D.S. (2018). Evaluation and prediction of blast-induced peak particle velocity using artificial neural network: Acase study.Noise & Vibration Worldwide, 49(3), 111-119.
10. Kumar, N., Mishra, B., & Bali, V. (2018). A Novel Approach for Blast-Induced Fly Rock Prediction Based on Particle Swarm Optimization and Artificial Neural Network. In Tiwari, B., Tiwari, V., Das,K., Mishra, D., & Bansal, J. (Eds.). Proceedings of International Conference on Recent Advancement on Computer and Communication. Lecture Notes in Networks and Systems, 34. Springer. https://doi.org/10.1007/978-981-10-8198-9_3.
11. Farahani, G. (2017). Autocorrelation-based noise subtraction method with smoothing, overestimation, energy, and cepstral mean and variance normalization for noisy speech recognition. EURASIP Journal on Audio, Speech, and Music Processing, 2017(1), 1-16. https://doi.org/10.1186/s13636-017-0110-8.
12. Tryputen, M., Kuznetsov, V., Kuznetsova, A., Maksim, K., & Tryputen, M. (2020, September). Developing Stochastic Model of a Workshop Power Grid. In2020 IEEE Problems of Automated Electrodrive. Theory and Practice (PAEP),(pp. 1-6). IEEE. https://doi.org/10.1109/PAEP49887.2200.9240898.
Newer news items:
- Ecological and economic management of innovation activity of enterprises - 29/10/2021 02:08
- Improvement of methodology of justification of safe routes for transportation of dangerous substances and cargo - 29/10/2021 02:08
- Choosing injectable solution for auger technology of underground space protection against pollution - 29/10/2021 02:08
- Validation of the operation efficiency criteria for geothermal probes in flooded mine workings - 29/10/2021 02:08
- Influence of diesel vehicles on the biosphere - 29/10/2021 02:08
- Current state and forecast of sulfur dioxide and dust emissions at thermal power plants of Ukraine - 29/10/2021 02:08
- Mathematical modeling of wave processes in two-winding transformers taking into account the main magnetic flux - 29/10/2021 02:08
- Simulation of industrial solar photovoltaic station with transformerless converter system - 29/10/2021 02:08
- Determination of vertical dynamics for a standard Ukrainian boxcar with Y25 bogies - 29/10/2021 02:08
- Elastic, inelastic and time constant measurement for M102 (AL–C–O) dispersions-reinforced aluminum alloys - 29/10/2021 02:08
Older news items:
- Increasing the sensitivity of measurement of a moisture content in crude oil - 29/10/2021 02:08
- Formation mechanisms of maximal loads on cutters and cutting heads of coal mining machines - 29/10/2021 02:08
- Determination of adhesion stages of the Fe-Ni ore at the Ferronikeli plant in Drenas - 29/10/2021 02:08
- Calculation of the overburden ratio by the method of financial and mathematical averaged costs - 29/10/2021 02:08
- Surface modelling by geoid determination for flood control of Ewekoro limestone deposit (Nigeria) - 29/10/2021 02:08
- Mineralization of rare metals in the lakes of East Kazakhstan - 29/10/2021 02:08
- Tectonic factors of impurity elements accumulation at the Shubarkol coal deposit (Kazakhstan) - 29/10/2021 02:08
- Feature space of the Atasu type deposits (Сentral Kazakhstan) - 29/10/2021 02:08