Abstract
A problem of local damage detection for condition monitoring based on vibration data can be approached from many different angles. One of the most common ways is selective filtration of the vibration signal. There are many techniques allowing to construct digital filter for particular input data (e.g. spectral selectors). In previous articles authors proposed a technique called Progressive Genetic Algorithm (PGA) to optimally design digital filter for a given data set using no prior assumptions. It uses kurtosis as fitness function and local linear fit of fitness function progression vector as a global termination criterion (GTC), but local termination criterion (LTC) was defined as simple stall limit of fitness value. In this paper authors propose a new quantile-based way to terminate PGA locally for faster convergence. Initial testing phase shows that for comparable quality of obtained result, individual epochs terminate significantly faster without sacrificing the progress of local convergence. It results in more efficient optimization and faster global convergence which reduces the overall execution time of the program for about the order of magnitude.
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Bartelmus W, Zimroz R (2009) A new feature for monitoring the condition of gearboxes in non-stationary operating conditions. Mech Syst Signal Process 23(5):1528–1534
Obuchowski J, Wyłomańska A, Zimroz R (2014) Selection of informative frequency band in local damage detection in rotating machinery. Mech Syst Signal Process 48(1):138–152
Obuchowski J, Wylomańska A, Zimroz R (2014) Recent developments in vibration based diagnostics of gear and bearings used in belt conveyors. Appl Mech Mater 683:171–176
Wyłomańska A, Zimroz R, Janczura J, Obuchowski J (2016) Impulsive noise cancellation method for copper ore crusher vibration signals enhancement. IEEE Trans Ind Electron 63(9):5612–5621
Żak G, Wyłomańska A, Zimroz R (2016) Data-driven vibration signal filtering procedure based on the \(\alpha \)-stable distribution. J Vibroeng 18(2):826–837
Makowski R, Zimroz R (2014) New techniques of local damage detection in machinery based on stochastic modelling using adaptive Schur filter. Appl Acoust 77:130–137
Makowski R, Zimroz R (2013) A procedure for weighted summation of the derivatives of reflection coefficients in adaptive Schur filter with application to fault detection in rolling element bearings. Mech Syst Signal Process 38(1):65–77
Wodecki J, Kruczek P, Wyłomańska A, Bartkowiak A, Zimroz R (2017) Novel method of informative frequency band selection for vibration signal using nonnegative matrix factorization of short-time fourier transform. In: 2017 IEEE 11th international symposium on diagnostics for electrical machines, power electronics and drives (SDEMPED). IEEE, pp 129–133
Wyłomańska A, Żak G, Kruczek P, Zimroz R (2017) Application of tempered stable distribution for selection of optimal frequency band in gearbox local damage detection. Appl Acoust 128:14–22
Wodecki J, Michalak A, Zimroz R (2018) Optimal filter design with progressive genetic algorithm for local damage detection in rolling bearings. Mech Syst Signal Process 102:102–116
Nilsson M, Dahl M, Claesson I (2003) Digital filter design of IIR filters using real valued genetic algorithm. In: WSEAS
Lee A, Ahmadi M, Jullien GA, Miller WC, Lashkari RS (1999) Digital filter design using genetic algorithm. In: 1998 IEEE symposium on advances in digital filtering and signal processing, symposium proceedings (Cat. No. 98EX185), pp 34–38
Sabbir U, Antoniou A (2006) Design of digital filters using genetic algorithms. In: 6th IEEE international symposium on signal processing and information technology, August 2006
Langford E (2006) Quartiles in elementary statistics. J Stat Educ 14(3):1–27
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Wodecki, J., Michalak, A., Wyłomańska, A., Zimroz, R. (2019). Local Termination Criterion for Impulsive Component Detection Using Progressive Genetic Algorithm. In: Fernandez Del Rincon, A., Viadero Rueda, F., Chaari, F., Zimroz, R., Haddar, M. (eds) Advances in Condition Monitoring of Machinery in Non-Stationary Operations. CMMNO 2018. Applied Condition Monitoring, vol 15. Springer, Cham. https://doi.org/10.1007/978-3-030-11220-2_39
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DOI: https://doi.org/10.1007/978-3-030-11220-2_39
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