Paraconsistent annotated logic applied to industry assets condition monitoring and failure prevention based on vibration signatures
DOI:
https://doi.org/10.33448/rsd-v11i1.25104Keywords:
Paraconsistent annotated logic; Maintenance; Preventive; Corrective; Assets; Artificial intelligence; Industry 4.0.Abstract
In this study, we introduced an expert system (ESvbrPAL2v), responsible for monitoring assets based on vibration signature analysis through a set of algorithms based on the Paraconsistent Annotated Logic – PAL. Being a non-classical logic, the main feature of the PAL is to support contradictory inputs in its foundation. It is therefore suitable for building algorithmic models capable of performing out appropriate treatment for complex signals, such as those coming from vibration. The ESvbrPAL2v was built on an ATMega2560 microcontroller, where vibration signals were captured from the mechanical structures of the machines by sensors and, after receiving special treatment through the Discrete Fourier Transform (DFT), then properly modeled to paraconsistent logic signals and vibration patterns. Using the PAL fundamentals, vibration signature patterns were built for possible and known vibration issues stored in ESvbrPAL2v and continuously compared through configurations composed by a network of paraconsistent algorithms that detects anomalies and generate signals that will report on the current risk status of the machine in real time. The tests to confirm the efficiency of ESvbrPAL2v were performed in analyses initially carried out on small prototypes and, after the initial adjustments, tests were carried out on bearings of a group of medium-power motor generators built specifically for this study. The results are shown at the end of this study and have a high index of signature identification and risk of failure detection. These results justifies the method used and future applications considering that ESvbrPAL2v is still in its first version.
References
Abe, J. M., Akama, S., Nakamatsu, K., Da Silva Filho, J.I. (2018). Some Aspects on Complementarity and Heterodoxy in Non-Classical Logics. Procedia Computer Science, 126, pp. 1253–1260. https://doi.org/10.1016/j.procs.2018.08.068
Chen, J., Pan J., Li Z.,Zi, Y, Chen, X. (2016). Generator bearing fault diagnosis for wind turbine via empirical wavelet transform using measured vibration signals. Renewable Energy VL.89. DOI: 10.1016/j.renene.2015.12.010
Coelho M. S., Da Silva Filho J. I., Cortes H. M., De Carvalho Jr A., Blos M. F., Mario M. C., Rocco A. (2019). Hybrid PI controller constructed with paraconsistent annotated logic. Control Engineering Practice. 84, pp. 112–124. https://doi.org/10.1016/j.conengprac.2018.11.007.
Côrtes, H.M., Santos, P.E., da Silva Filho, J.I. (2022) Monitoring electrical systems data-network equipment by means of Fuzzy and Paraconsistent Annotated Logic. Expert Systems with Applications. 187, https://doi.org/10.1016/j.eswa.2021.115865
Da Costa N. C.A., Abe J. M. (2000). Paraconsistência em informática e inteligência artificial, Ciência • Estud. av. 14 (39) • https://doi.org/10.1590/S0103-40142000000200012
Da Silva Filho, J.I.; Abe, J.M.; Marreiro, A.d.L.; Martinez, A.A.G.; Torres, C.R.; Rocco, A.; Côrtes, H.M.; Mario, M.C.; Pacheco, M.T.T.; Garcia, D.V.; Blos, M.F. (2021) Paraconsistent annotated logic algorithms applied in management and control of communication network routes Sensors, 21(12), 4219 https://doi.org/10.3390/s21124219
Da Silva Filho, J. I., Lambert-Torres, G., Abe, J. M. (2010). Uncertainty Treatment Using Paraconsistent Logic - Introducing Paraconsistent Artificial Neural Networks. IOS Press, 328, 211, Frontiers in Artificial Intelligence and Applications, Amsterdam, Netherlands,
Da Silva Filho, J. I. et al. (2015). Paraconsistent Logic Algorithms Applied to Seasonal Comparative Analysis with Biomass Data Extracted by the Fouling Process. Paraconsistent Intelligent Based Systems - New Trends in the Applications of Paraconsistency - Intelligent Systems Reference Library -Springer International Publishing AG Switzerland, pp 131-152, DOI 10.1007/978-3-319-19722-7
Da Silva Filho, J. I., Nunes, C. V., Garcia, D. V., Mario, M.C., Giordano, F., Abe, J. M., Pacheco, M. T. T. & Silveira Jr., L. (2016)., Paraconsistent analysis network applied in the treatment of Raman spectroscopy data to support medical diagnosis of skin cancer. Medical and Biological Engineering and Computing, 54(10), pp. 1453–1467
Da Silva Filho, J.I., Misseno Da Cruz, C. (2016). A Method with Paraconsistent Partial Differential Equation used in Explicit Solution of one-dimensional Heat Conduction. IEEE Latin America Transactions, 14(4), pp. 1842–1848, 7483524.
De Carvalho, A., Justo, J.F., Angelico, B.A., De Oliveira, A.M., Da Silva Filho, J.I. (2021) Rotary Inverted Pendulum Identification for Control by Paraconsistent Neural Network. IEEE Access, 9, pp. 74155–74167, 9430548. doi: 10.1109/ACCESS.2021.3080176.
Garcia, D. V., Da Silva Filho, J. I., Silveira Jr., L., Pacheco, M. T. T., Abe, J. M., Carvalho Jr., A., Blos, M. F., Pasqualucci, C. A. G. & Mario, M.C. (2019). Analysis of Raman spectroscopy data with algorithms based on paraconsistent logic for characterization of skin cancer lesions. Vibrational Spectroscopy, 103, https://doi.org/10.1016/j.vibspec.2019.102929.
Giantomassi A., Ferracuti F., Iarlori S., Ippoliti G. and Longhi S., (2015). Electric Motor Fault Detection and Diagnosis by Kernel Density Estimation and Kullback–Leibler Divergence Based on Stator Current Measurements, in IEEE Transactions on Industrial Electronics, vol. 62, no. 3, pp. 1770-1780, doi: 10.1109/TIE.2014.2370936.
Hemmati, F., Orfali W. and Gadala, M. S. (2016). Roller bearing acoustic signature extraction by wavelet packet transform, applications in fault detection and size estimation. Applied Acoustics. pp. 101 – 118. doi.org/10.1016/j.apacoust.2015.11.003
Ince T., Kiranyaz S., Eren L., Askar M. and Gabbouj M., (2016). Real-Time Motor Fault Detection by 1-D Convolutional Neural Networks, in IEEE Transactions on Industrial Electronics, vol. 63, no. 11, pp. 7067-7075, doi: 10.1109/TIE.2016.2582729.
Janssens O., Slavkovikj V., Vervisch B. , Stockman K. , Loccufier M., Verstockt S., Van de Walle R. and Van Hoecke S. (2016). Convolutional neural network based fault detection for rotating machinery. Journal of Sound and Vibration. 377. P.331-345.
Kwon D., Hodkiewicz M. R., Fan J., T. Shibutani and M. G. Pecht, (2016). IoT-Based Prognostics and Systems Health Management for Industrial Applications. In IEEE Access, vol. 4, pp. 3659-3670doi: 10.1109/ACCESS.2016.2587754.
Lei, X., Wu, Y. (2020). Research on mechanical vibration monitoring based on wireless sensor network and sparse Bayes. J Wireless Com Network 2020, 225 https://doi.org/10.1186/s13638-020-01836-9
Mario, M. C., Garcia, D. V., Da Silva Filho, J. I., Silveira Júnior, L., Barbuy, H. S. (2021). Characterization and classification of numerical data patterns using Annotated Paraconsistent Logic and the effect of contradiction. Research, Society and Development, [S. l.], v. 10, n. 13, p. e283101320830, DOI: 10.33448/rsd-v10i13.20830. Disponível em: https://rsdjournal.org/index.php/rsd/article/view/20830.
Mario, M.C., Da Silva Filho, J.I., Blos, M.F., Amaral Moino, C.A., Pereira Matos, M.C. (2018). Paraconsistent Logic applied in the metallography of welds classification through morphological characteristics and entropy of digital images. Journal of Physics: Conference Series, 1074(1), 012168
Ricciotti, A. C. D, Da Silva Filho J. I., De Oliveira R. A. B., Ricciotti, V. B. S. D., Côrtes H. M. and Nicolini A. M. (2019). A new strategy of modulation based on Space Vector Modulation and Annotated Paraconsistent Logic for a three-phase converter, 2019 IEEE 15th Brazilian Power Electronics Conference and 5th IEEE Southern Power Electronics Conference (COBEP/SPEC), pp. 1-6, doi: 10.1109/COBEP/SPEC44138.2019.9065882.
Song L., Wang H. and Chen P. (2018). Vibration-Based Intelligent Fault Diagnosis for Roller Bearings in Low-Speed Rotating Machinery, in IEEE Transactions on Instrumentation and Measurement, vol. 67, no. 8, pp. 1887-1899, doi: 10.1109/TIM.2018.2806984.
Weijtjens, W., Verbelen, T., Capello, E., & Devriendt, C. (2017). Vibration based structural health monitoring of the substructures of five offshore wind turbines. In Procedia Engineering: X International Conference on Structural Dynamics, EURODYN 2017 (Vol. 199, pp. 2294-2299). (Procedia Engineering). https://doi.org/10.1016/j.proeng.2017.09.187
Zhang, M., Feng, K., & Jiang, Z. (2017). Research on variational mode decomposition in rolling bearings fault diagnosis of the multistage centrifugal pump. Mechanical Systems and Signal Processing, 93(1), 460-493. https://doi.org/10.1016/j.ymssp.2017.02.013
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2022 Márcio Pereira Corrêa; Ayslan Cuzzuol Machado; João Inácio da Silva Filho; Dorotéa Vilanova Garcia; Mauricio Conceição Mario; Carlos Teofilo Salinas Sedano
This work is licensed under a Creative Commons Attribution 4.0 International License.
Authors who publish with this journal agree to the following terms:
1) Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution License that allows others to share the work with an acknowledgement of the work's authorship and initial publication in this journal.
2) Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgement of its initial publication in this journal.
3) Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work.
