{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,5,31]],"date-time":"2025-05-31T10:30:56Z","timestamp":1748687456764,"version":"3.40.3"},"publisher-location":"Cham","reference-count":28,"publisher":"Springer International Publishing","isbn-type":[{"type":"print","value":"9783030336943"},{"type":"electronic","value":"9783030336950"}],"license":[{"start":{"date-parts":[[2019,11,2]],"date-time":"2019-11-02T00:00:00Z","timestamp":1572652800000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2020]]},"DOI":"10.1007\/978-3-030-33695-0_12","type":"book-chapter","created":{"date-parts":[[2019,11,1]],"date-time":"2019-11-01T16:04:57Z","timestamp":1572624297000},"page":"154-172","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":21,"title":["Approach for Creating Reference Signals for Detecting Defects in Diagnosing of Composite Materials"],"prefix":"10.1007","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-0704-4116","authenticated-orcid":false,"given":"Artur","family":"Zaporozhets","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4330-7518","authenticated-orcid":false,"given":"Volodymyr","family":"Eremenko","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8010-8844","authenticated-orcid":false,"given":"Volodymyr","family":"Isaenko","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5053-1999","authenticated-orcid":false,"given":"Kateryna","family":"Babikova","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2019,11,2]]},"reference":[{"issue":"11","key":"12_CR1","doi-asserted-by":"publisher","first-page":"3821","DOI":"10.1007\/BF01133328","volume":"22","author":"M Lee","year":"1987","unstructured":"Lee, M., Thomas, C.E., Wildes, D.G.: Prospects for in-process diagnosis of metal cutting by monitoring vibration signals. J. Mater. Sci. 22(11), 3821\u20133830 (1987). \nhttps:\/\/doi.org\/10.1007\/BF01133328","journal-title":"J. Mater. Sci."},{"issue":"2, Part 2","key":"12_CR2","doi-asserted-by":"publisher","first-page":"7252","DOI":"10.1016\/j.eswa.2008.09.033","volume":"36","author":"A Widolo","year":"2009","unstructured":"Widolo, A., Kim, E.Y., Son, J.-D., Yang, B.-S., Tan, A.C.C., Gu, D.-S., Choi, B.-K., Mathew, J.: Fault diagnosis of low speed bearing based on relevance vector machine and support vector machine. Expert Syst. Appl. 36(2, Part 2), 7252\u20137261 (2009). \nhttps:\/\/doi.org\/10.1016\/j.eswa.2008.09.033","journal-title":"Expert Syst. Appl."},{"issue":"2","key":"12_CR3","doi-asserted-by":"publisher","first-page":"199","DOI":"10.1016\/S0888-3270(03)00075-X","volume":"18","author":"ZK Peng","year":"2004","unstructured":"Peng, Z.K., Chu, F.L.: Application of the wavelet transform in machine condition monitoring and fault diagnostics: a review with bibliography. Mech. Syst. Signal Process. 18(2), 199\u2013221 (2004). \nhttps:\/\/doi.org\/10.1016\/S0888-3270(03)00075-X","journal-title":"Mech. Syst. Signal Process."},{"issue":"Part A","key":"12_CR4","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1016\/j.sigpro.2013.04.015","volume":"96","author":"R Yan","year":"2014","unstructured":"Yan, R., Gao, R.X., Chen, X.: Wavelets for fault diagnosis of rotary machines: a review with applications. Sig. Process. 96(Part A), 1\u201315 (2014). \nhttps:\/\/doi.org\/10.1016\/j.sigpro.2013.04.015","journal-title":"Sig. Process."},{"key":"12_CR5","doi-asserted-by":"publisher","first-page":"171","DOI":"10.1016\/j.measurement.2016.04.007","volume":"89","author":"W Sun","year":"2016","unstructured":"Sun, W., Shao, S., Zhao, R., Yan, R., Zhang, X., Chen, X.: A sparse auto-encoder-based deep neural network approach for induction motor faults classification. Measurement 89, 171\u2013178 (2016). \nhttps:\/\/doi.org\/10.1016\/j.measurement.2016.04.007","journal-title":"Measurement"},{"doi-asserted-by":"publisher","unstructured":"Zaporozhets, A., Eremenko, V., Serhiienko, R., Ivanov, S.: Methods and hardware for diagnosing thermal power equipment based on smart grid technology. In: Advances in Intelligent Systems and Computing III, vol. 871, pp. 476\u2013492 (2019). \nhttps:\/\/doi.org\/10.1007\/978-3-030-01069-0_34","key":"12_CR6","DOI":"10.1007\/978-3-030-01069-0_34"},{"doi-asserted-by":"publisher","unstructured":"Zaporozhets, A.A., Eremenko, V.S., Serhiienko, R.V., Ivanov, S.A.: Development of an intelligent system for diagnosing the technical condition of the heat power equipment. In: 2018 IEEE 13th International Scientific and Technical Conference on Computer Sciences and Information Technologies (CSIT), Lviv, Ukraine, 11\u201314 September 2018. \nhttps:\/\/doi.org\/10.1109\/stc-csit.2018.8526742","key":"12_CR7","DOI":"10.1109\/stc-csit.2018.8526742"},{"issue":"2","key":"12_CR8","doi-asserted-by":"publisher","first-page":"121","DOI":"10.11113\/jt.v69.3121","volume":"69","author":"YH Ali","year":"2014","unstructured":"Ali, Y.H., Rahman, R.A., Hamzah, R.I.R.: Acoustic emission signal analysis and artificial intelligence techniques in machine condition monitoring and fault diagnosis: a review. Jurnal Teknologi 69(2), 121\u2013126 (2014)","journal-title":"Jurnal Teknologi"},{"key":"12_CR9","doi-asserted-by":"publisher","first-page":"646","DOI":"10.1016\/j.compstruct.2017.11.067","volume":"185","author":"S Sikdar","year":"2018","unstructured":"Sikdar, S., Kudela, P., Radzienski, M., Kundu, A., Ostachowicz, W.: Online detection of barely visible low-speed impact damage in 3D-core sandwich composite structure. Compos. Struct. 185, 646\u2013655 (2018). \nhttps:\/\/doi.org\/10.1016\/j.compstruct.2017.11.067","journal-title":"Compos. Struct."},{"issue":"8","key":"12_CR10","doi-asserted-by":"publisher","first-page":"54","DOI":"10.15587\/1729-4061.2016.85408","volume":"6","author":"V Babak","year":"2016","unstructured":"Babak, V., Mokiychuk, V., Zaporozhets, A., Redko, O.: Improving the efficiency of fuel combustion with regard to the uncertainty of measuring oxygen concentration. Eastern-Eur. J. Enterp. Technol. 6(8), 54\u201359 (2016). \nhttps:\/\/doi.org\/10.15587\/1729-4061.2016.85408","journal-title":"Eastern-Eur. J. Enterp. Technol."},{"issue":"2","key":"12_CR11","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1142\/S1793536909000047","volume":"01","author":"Z Wu","year":"2009","unstructured":"Wu, Z., Huang, N.E.: Ensemble empirical mode decomposition: a noise-assisted data analysis method. Adv. Adapt. Data Anal. 01(2), 1\u201341 (2009). \nhttps:\/\/doi.org\/10.1142\/S1793536909000047","journal-title":"Adv. Adapt. Data Anal."},{"issue":"1","key":"12_CR12","doi-asserted-by":"publisher","first-page":"338","DOI":"10.1214\/17-EJS1223","volume":"11","author":"Y Song","year":"2017","unstructured":"Song, Y., Fellouris, G.: Asymptotically optimal, sequential, multiple testing procedures with prior information on the number of signals. Electron. J. Stat. 11(1), 338\u2013363 (2017). \nhttps:\/\/doi.org\/10.1214\/17-EJS1223","journal-title":"Electron. J. Stat."},{"issue":"10","key":"12_CR13","doi-asserted-by":"publisher","first-page":"2594","DOI":"10.1109\/TCSI.2015.2468996","volume":"62","author":"W-L Hsue","year":"2015","unstructured":"Hsue, W.-L., Chang, W.-C.: Real discrete fractional Fourier, Hartley, generalized Fourier and generalized Hartley transforms with many parameters. IEEE Trans. Circuits Syst. I Regul. Pap. 62(10), 2594\u20132605 (2015). \nhttps:\/\/doi.org\/10.1109\/TCSI.2015.2468996","journal-title":"IEEE Trans. Circuits Syst. I Regul. Pap."},{"doi-asserted-by":"publisher","unstructured":"Hsue, W.-L., Chang, W.-C.: Multiple-parameter real discrete fractional Fourier and Hartley transforms. In: 2014 19th International Conference on Digital Processing, Hong Kong, China, 20\u201323 August 2014. \nhttps:\/\/doi.org\/10.1109\/icdsp.2014.6900753","key":"12_CR14","DOI":"10.1109\/icdsp.2014.6900753"},{"doi-asserted-by":"publisher","unstructured":"Zaporozhets, A.: Analysis of control system of fuel combustion in boilers with oxygen sensor. Periodica Polytech. Mech. Eng. (2019). \nhttps:\/\/doi.org\/10.3311\/ppme.12572","key":"12_CR15","DOI":"10.3311\/ppme.12572"},{"key":"12_CR16","doi-asserted-by":"publisher","first-page":"245","DOI":"10.1016\/j.compstruc.2017.03.006","volume":"207","author":"VK Dertimanis","year":"2018","unstructured":"Dertimanis, V.K., Spiridonakos, M.D., Chatzi, E.N.: Data-driven uncertainty quantification of structural systems via B-spline expansion. Comput. Struct. 207, 245\u2013257 (2018). \nhttps:\/\/doi.org\/10.1016\/j.compstruc.2017.03.006","journal-title":"Comput. Struct."},{"key":"12_CR17","doi-asserted-by":"publisher","first-page":"10021","DOI":"10.1038\/ncomms10021","volume":"6","author":"RW Andrews","year":"2015","unstructured":"Andrews, R.W., Reed, A.P., Cicak, K., Teufel, J.D., Lehnert, K.W.: Quantum-enabled temporal and spectral mode conversion of microwave signals. Nat. Commun. 6, 10021 (2015). \nhttps:\/\/doi.org\/10.1038\/ncomms10021","journal-title":"Nat. Commun."},{"issue":"5","key":"12_CR18","doi-asserted-by":"publisher","first-page":"1761","DOI":"10.1007\/s00158-018-2160-7","volume":"59","author":"Y Jung","year":"2019","unstructured":"Jung, Y., Cho, H., Lee, I.: MPP-based approximated DRM (ADRM) using simplified bivariate approximation with linear regression. Struct. Multi. Optim. 59(5), 1761\u20131773 (2019). \nhttps:\/\/doi.org\/10.1007\/s00158-018-2160-7","journal-title":"Struct. Multi. Optim."},{"issue":"8","key":"12_CR19","doi-asserted-by":"publisher","first-page":"4391","DOI":"10.1109\/TGRS.2018.2818159","volume":"56","author":"Y Qu","year":"2018","unstructured":"Qu, Y., Wang, W., Guo, R., Ayhan, B., Kwan, C., Vance, S., Qi, H.: Hyperspectral anomaly detection through spectral unmixing and dictionary-based low-rank decomposition. IEEE Trans. Geosci. Remote Sens. 56(8), 4391\u20134405 (2018). \nhttps:\/\/doi.org\/10.1109\/TGRS.2018.2818159","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"doi-asserted-by":"publisher","unstructured":"Zaporozhets, A.O., Redko, O.O., Babak, V.P., Eremenko, V.S., Mokiychuk, V.M.: Method of indirect measurement of oxygen concentration in the air. Naukovyi Visnyk Natsionalnoho Hirnychoho Universytetu (5), 105\u2013114 (2018). \nhttps:\/\/doi.org\/10.29202\/nvngu\/2018-5\/14","key":"12_CR20","DOI":"10.29202\/nvngu\/2018-5\/14"},{"unstructured":"Babak, S., Babak, V., Zaporozhets, A., Sverdlova, A.: Method of statistical spline functions for solving problems of data approximation and prediction of objects state. In: CEUR Workshop Proceedings, vol. 2353, pp. 810\u2013821 (2019). \nhttp:\/\/ceur-ws.org\/Vol-2353\/paper64.pdf","key":"12_CR21"},{"doi-asserted-by":"publisher","unstructured":"Ali, A., Khan, K., Haq, F., Shah, S.I.A.: A computational modeling based on trigonometric cubic B-spline functions for the approximate solution of a second order partial integro-differential equation. In: New Knowledge in Information Systems and Technologies. Advances in Intelligent Systems and Computing, WorldCIST 2019, vol. 930, pp. 844\u2013854 (2019). \nhttps:\/\/doi.org\/10.1007\/978-3-030-16181-1_79","key":"12_CR22","DOI":"10.1007\/978-3-030-16181-1_79"},{"unstructured":"Eremenko, V., Zaporozhets, A., Isaenko, V., Babikova, K.: Application of wavelet transform for determining diagnostic signs. In: CEUR Workshop Proceedings, vol. 2387, pp. 202\u2013214 (2019). \nhttp:\/\/ceur-ws.org\/Vol-2387\/20190202.pdf","key":"12_CR23"},{"key":"12_CR24","doi-asserted-by":"publisher","first-page":"82","DOI":"10.1016\/j.cam.2017.09.049","volume":"331","author":"X Han","year":"2018","unstructured":"Han, X., Guo, X.: Cubic Hermite interpolation with minimal derivative oscillation. J. Comput. Appl. Math. 331, 82\u201387 (2018). \nhttps:\/\/doi.org\/10.1016\/j.cam.2017.09.049","journal-title":"J. Comput. Appl. Math."},{"key":"12_CR25","doi-asserted-by":"publisher","first-page":"173","DOI":"10.1007\/s13201-018-0807-6","volume":"8","author":"SG Meshram","year":"2018","unstructured":"Meshram, S.G., Powar, P.L., Meshram, C.: Comparison of cubic, quadratic, and quintic splines for soil erosion modeling. Appl. Water Sci. 8, 173 (2018). \nhttps:\/\/doi.org\/10.1007\/s13201-018-0807-6","journal-title":"Appl. Water Sci."},{"unstructured":"Zaporozhets, A.: Development of software for fuel combustion control system based on frequency regulator. In: CEUR Workshop Proceedings, vol. 2387, pp. 223\u2013230 (2019). \nhttp:\/\/ceur-ws.org\/Vol-2387\/20190223.pdf","key":"12_CR26"},{"key":"12_CR27","doi-asserted-by":"publisher","first-page":"113","DOI":"10.1016\/j.sigpro.2016.08.007","volume":"131","author":"M Brajovic","year":"2017","unstructured":"Brajovic, M., Orovic, I., Dakovic, M., Stankovic, S.: On the parameterization of Hermite transform with application to the compression of QRS complexes. Sig. Process. 131, 113\u2013119 (2017). \nhttps:\/\/doi.org\/10.1016\/j.sigpro.2016.08.007","journal-title":"Sig. Process."},{"unstructured":"Zaporozhets, A.O., Eremenko, V.S., Isaenko, V.M., Babikova, K.O.: Methods for creating reference signals for the diagnosis of composite materials. In: Proceedings of International Scientific Conference Computer Sciences and Information Technologies (CSIT-2019), vol. 1, pp. 84\u201387 (2019)","key":"12_CR28"}],"container-title":["Advances in Intelligent Systems and Computing","Advances in Intelligent Systems and Computing IV"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-030-33695-0_12","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2020,9,19]],"date-time":"2020-09-19T10:08:13Z","timestamp":1600510093000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/978-3-030-33695-0_12"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019,11,2]]},"ISBN":["9783030336943","9783030336950"],"references-count":28,"URL":"https:\/\/doi.org\/10.1007\/978-3-030-33695-0_12","relation":{},"ISSN":["2194-5357","2194-5365"],"issn-type":[{"type":"print","value":"2194-5357"},{"type":"electronic","value":"2194-5365"}],"subject":[],"published":{"date-parts":[[2019,11,2]]},"assertion":[{"value":"2 November 2019","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"CSIT","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Conference on Computer Science and Information Technologies","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Lviv","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Ukraine","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2019","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"11 September 2019","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"13 September 2019","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"csit2019","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}