{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,16]],"date-time":"2026-03-16T18:59:38Z","timestamp":1773687578771,"version":"3.50.1"},"reference-count":33,"publisher":"MDPI AG","issue":"3","license":[{"start":{"date-parts":[[2022,1,31]],"date-time":"2022-01-31T00:00:00Z","timestamp":1643587200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>In this work, different types of artificial neural networks are investigated for the estimation of the time of arrival (ToA) in acoustic emission (AE) signals. In particular, convolutional neural network (CNN) models and a novel capsule neural network are proposed in place of standard statistical strategies which cannot handle, with enough robustness, very noisy scenarios and, thus, cannot be sufficiently reliable when the signal statistics are perturbed by local drifts or outliers. This concept was validated with two experiments: the pure ToA identification capability was firstly assessed on synthetic signals for which a ground truth is available, showing a 10\u00d7 gain in accuracy when compared to the classical Akaike information criterion (AIC). Then, the same models were tested via experimental data acquired in the framework of a localization problem to identify targets with known coordinates on a square aluminum plate, demonstrating an overreaching precision under significant noise levels.<\/jats:p>","DOI":"10.3390\/s22031091","type":"journal-article","created":{"date-parts":[[2022,1,31]],"date-time":"2022-01-31T08:20:29Z","timestamp":1643617229000},"page":"1091","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":36,"title":["Deep Learning Approaches for Robust Time of Arrival Estimation in Acoustic Emission Monitoring"],"prefix":"10.3390","volume":"22","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-2429-1469","authenticated-orcid":false,"given":"Federica","family":"Zonzini","sequence":"first","affiliation":[{"name":"Advanced Research Center on Electronic Systems \u201cErcole De Castro\u201d (ARCES), University of Bologna, 40136 Bologna, Italy"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2085-6469","authenticated-orcid":false,"given":"Denis","family":"Bogomolov","sequence":"additional","affiliation":[{"name":"Advanced Research Center on Electronic Systems \u201cErcole De Castro\u201d (ARCES), University of Bologna, 40136 Bologna, Italy"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6022-9489","authenticated-orcid":false,"given":"Tanush","family":"Dhamija","sequence":"additional","affiliation":[{"name":"Department of Electrical, Electronic and Information Engineering (DEI), University of Bologna, 40136 Bologna, Italy"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3281-137X","authenticated-orcid":false,"given":"Nicola","family":"Testoni","sequence":"additional","affiliation":[{"name":"Advanced Research Center on Electronic Systems \u201cErcole De Castro\u201d (ARCES), University of Bologna, 40136 Bologna, Italy"}]},{"given":"Luca","family":"De Marchi","sequence":"additional","affiliation":[{"name":"Department of Electrical, Electronic and Information Engineering (DEI), University of Bologna, 40136 Bologna, Italy"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7697-6729","authenticated-orcid":false,"given":"Alessandro","family":"Marzani","sequence":"additional","affiliation":[{"name":"Department of Civil, Chemical, Environmental and Materials Engineering (DICAM), University of Bologna, 40136 Bologna, Italy"}]}],"member":"1968","published-online":{"date-parts":[[2022,1,31]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"1075","DOI":"10.12989\/sem.2015.54.6.1075","article-title":"A review of the application of acoustic emission technique in engineering","volume":"54","author":"Gholizadeh","year":"2015","journal-title":"Struct. Eng. Mech."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"401","DOI":"10.1016\/0013-7944(94)00274-L","article-title":"Study of fatigue crack characteristics by acoustic emission","volume":"51","author":"Berkovits","year":"1995","journal-title":"Eng. Fract. Mech."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"569","DOI":"10.1016\/j.ymssp.2013.01.020","article-title":"Damage localization using transmissibility functions: A critical review","volume":"38","author":"Deraemaeker","year":"2013","journal-title":"Mech. Syst. Signal Process."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"967","DOI":"10.1121\/1.1381027","article-title":"Acoustic echo detection and arrival-time estimation using spectral tail energy","volume":"110","author":"Ainsleigh","year":"2001","journal-title":"J. Acoust. Soc. Am."},{"key":"ref_5","first-page":"1","article-title":"AE testing fundamentals, equipment, applications","volume":"7","author":"Vallen","year":"2002","journal-title":"J. Nondestruct. Test."},{"key":"ref_6","unstructured":"Wirtz, S.F., and S\u00f6ffker, D. (2018, January 10\u201313). Improved signal processing of acoustic emission for structural health monitoring using a data-driven approach. Proceedings of the 9th European Workshop on Structural Health Monitoring, Manchester, UK."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1243\/09544089JPME111","article-title":"Challenges and obstacles in the application of acoustic emission to process machinery","volume":"222","author":"Sikorska","year":"2008","journal-title":"Proc. Inst. Mech. Eng. Part E J. Process Mech. Eng."},{"key":"ref_8","unstructured":"Ramesh, S. (2012). The Applied Welding Engineering. Processes, Codes, and Standards, Elsevier."},{"key":"ref_9","doi-asserted-by":"crossref","unstructured":"Karbhari, V.M. (2013). Non-Destructive Evaluation (NDE) of Polymer Matrix Composites, Elsevier.","DOI":"10.1533\/9780857093554"},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"192","DOI":"10.1080\/09349847.2021.1959692","article-title":"Guided Wave Studies for Enhanced Acoustic Emission Inspection","volume":"32","author":"Rose","year":"2021","journal-title":"Res. Nondestruct. Eval."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"1318","DOI":"10.1177\/1045389X18798948","article-title":"Theoretical and numerical analysis of acoustic emission guided waves released during crack propagation","volume":"30","author":"Faisal","year":"2019","journal-title":"J. Intell. Mater. Syst. Struct."},{"key":"ref_12","doi-asserted-by":"crossref","unstructured":"Lowe, M.J.S. (2001). Wave Propagation|Guided Waves in Structures, Elsevier. Encyclopedia of Vibration.","DOI":"10.1006\/rwvb.2001.0173"},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"2507","DOI":"10.1109\/TIM.2018.2866358","article-title":"An indoor ultrasonic system for autonomous 3-D positioning","volume":"68","author":"Carotenuto","year":"2018","journal-title":"IEEE Trans. Instrum. Meas."},{"key":"ref_14","doi-asserted-by":"crossref","unstructured":"Adri\u00e1n-Mart\u00ednez, S., Bou-Cabo, M., Felis, I., Llorens, C.D., Mart\u00ednez-Mora, J.A., Salda\u00f1a, M., and Ardid, M. (2014). Acoustic signal detection through the cross-correlation method in experiments with different signal to noise ratio and reverberation conditions. International Conference on Ad-Hoc Networks and Wireless, Springer.","DOI":"10.1007\/978-3-662-46338-3_7"},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"51","DOI":"10.1016\/j.sigpro.2013.05.008","article-title":"Frequency warped cross-wavelet multiresolution analysis of guided waves for impact localization","volume":"96","author":"Perelli","year":"2014","journal-title":"Signal Process."},{"key":"ref_16","doi-asserted-by":"crossref","unstructured":"St-Onge, A. (2011). Akaike information criterion applied to detecting first arrival times on microseismic data. SEG Technical Program Expanded Abstracts 2011, Society of Exploration Geophysicists.","DOI":"10.1190\/1.3627522"},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"382","DOI":"10.1177\/1475921716672206","article-title":"Improved acoustic emission source location during fatigue and impact events in metallic and composite structures","volume":"16","author":"Pearson","year":"2017","journal-title":"Struct. Health Monit."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"57","DOI":"10.1016\/j.cageo.2016.12.005","article-title":"Identifying P phase arrival of weak events: The Akaike Information Criterion picking application based on the Empirical Mode Decomposition","volume":"100","author":"Li","year":"2017","journal-title":"Comput. Geosci."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"8260","DOI":"10.1002\/2017GL074634","article-title":"Aftershocks driven by afterslip and fluid pressure sweeping through a fault-fracture mesh","volume":"44","author":"Ross","year":"2017","journal-title":"Geophys. Res. Lett."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"1750","DOI":"10.1093\/gji\/ggaa186","article-title":"Automatic microseismic event picking via unsupervised machine learning","volume":"222","author":"Chen","year":"2020","journal-title":"Geophys. J. Int."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"5120","DOI":"10.1029\/2017JB015251","article-title":"P wave arrival picking and first-motion polarity determination with deep learning","volume":"123","author":"Ross","year":"2018","journal-title":"J. Geophys. Res. Solid Earth"},{"key":"ref_22","first-page":"261","article-title":"PhaseNet: A deep-neural-network-based seismic arrival-time picking method","volume":"216","author":"Zhu","year":"2019","journal-title":"Geophys. J. Int."},{"key":"ref_23","first-page":"335","article-title":"Artificial neural networks as emerging tools for earthquake detection","volume":"23","author":"Rojas","year":"2019","journal-title":"Comput. Sist."},{"key":"ref_24","doi-asserted-by":"crossref","unstructured":"Tabian, I., Fu, H., and Sharif Khodaei, Z. (2019). A convolutional neural network for impact detection and characterization of complex composite structures. Sensors, 19.","DOI":"10.3390\/s19224933"},{"key":"ref_25","doi-asserted-by":"crossref","unstructured":"Zhang, Z. (2018, January 4\u20136). Improved adam optimizer for deep neural networks. Proceedings of the 2018 IEEE\/ACM 26th International Symposium on Quality of Service (IWQoS), Banff, AB, Canada.","DOI":"10.1109\/IWQoS.2018.8624183"},{"key":"ref_26","unstructured":"Lin, J., Rao, Y., Lu, J., and Zhou, J. (2017, January 4\u20139). Runtime neural pruning. Proceedings of the 31st International Conference on Neural Information Processing Systems, Long Beach, CA, USA."},{"key":"ref_27","doi-asserted-by":"crossref","unstructured":"Saad, O.M., and Chen, Y. (2021). CapsPhase: Capsule Neural Network for Seismic Phase Classification and Picking. IEEE Trans. Geosci. Remote Sens.","DOI":"10.1109\/TGRS.2021.3089929"},{"key":"ref_28","unstructured":"Sabour, S., Frosst, N., and Hinton, G.E. (2017). Dynamic routing between capsules. arXiv."},{"key":"ref_29","doi-asserted-by":"crossref","unstructured":"Mandal, B., Dubey, S., Ghosh, S., Sarkhel, R., and Das, N. (2018, January 7\u20139). Handwritten indic character recognition using capsule networks. Proceedings of the 2018 IEEE Applied Signal Processing Conference (ASPCON), Kolkata, India.","DOI":"10.1109\/ASPCON.2018.8748550"},{"key":"ref_30","first-page":"109","article-title":"Intelligent AE signal filtering methods","volume":"28","author":"Barat","year":"2010","journal-title":"J. Acoust. Emiss."},{"key":"ref_31","doi-asserted-by":"crossref","unstructured":"Testoni, N., De Marchi, L., and Marzani, A. (2016, January 5\u20138). A stamp size, 40 mA, 5 grams sensor node for impact detection and location. Proceedings of the European Workshop on SHM, Bilbao, Spain.","DOI":"10.1117\/12.2084817"},{"key":"ref_32","unstructured":"Bogomolov, D., Testoni, N., Zonzini, F., Malatesta, M., de Marchi, L., and Marzani, A. (July, January 30). Acoustic emission structural monitoring through low-cost sensor nodes. Proceedings of the 10th International Conference on Structural Health Monitoring of Intelligent Infrastructure, Porto, Portugal."},{"key":"ref_33","unstructured":"Jiang, Y., and Xu, F. (2012, January 12\u201315). Research on source location from acoustic emission tomography. Proceedings of the 30th European Conference on Acoustic Emission Testing & 7th International Conference on Acoustic Emission, Granada, Spain."}],"container-title":["Sensors"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1424-8220\/22\/3\/1091\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T22:11:47Z","timestamp":1760134307000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1424-8220\/22\/3\/1091"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,1,31]]},"references-count":33,"journal-issue":{"issue":"3","published-online":{"date-parts":[[2022,2]]}},"alternative-id":["s22031091"],"URL":"https:\/\/doi.org\/10.3390\/s22031091","relation":{},"ISSN":["1424-8220"],"issn-type":[{"value":"1424-8220","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022,1,31]]}}}