Pregled bibliografske jedinice broj: 1114099
A Bayesian conjugate model for the estimation of friction intensity
A Bayesian conjugate model for the estimation of friction intensity // Transactions of FAMENA, 45 (2021), 1; 63-77 doi:10.21278/TOF.451026321 (međunarodna recenzija, članak, znanstveni)
CROSBI ID: 1114099 Za ispravke kontaktirajte CROSBI podršku putem web obrasca
Naslov
A Bayesian conjugate model for the estimation of friction intensity
(A Bayesian conjugate model for the estimation of
friction intensity)
Autori
Perišić, Stipe ; Barle, Jani ; Đukić, Predrag ; Wolf, Hinko
Izvornik
Transactions of FAMENA (1333-1124) 45
(2021), 1;
63-77
Vrsta, podvrsta i kategorija rada
Radovi u časopisima, članak, znanstveni
Ključne riječi
Bayesian inference ; Conjugate priors ; Coulomb dry friction ; experimental friction estimation
Sažetak
This paper addresses the Coulomb dry friction force as a technical indicator for fast and efficient condition-based maintenance. To estimate the value of friction force, the Bayesian analysis is used. Instead of the complex Markov Chain Monte Carlo numerical method, a closed-form analytical solution is applied. Thus, a simple and efficient procedure for friction estimation is described. Such a solution in the Bayesian context is known as the conjugate prior. The procedure presented here is verified numerically and experimentally by directly comparing the estimated value with the measured one. Two families of conjugate priors, the gamma-exponential and the normal- gamma, are compared. It is shown that the latter is suitable for friction estimation. An additional parameter, the precision parameter, was proposed as a criterion for the acceptance of estimation.
Izvorni jezik
Engleski
Znanstvena područja
Strojarstvo
POVEZANOST RADA
Ustanove:
Fakultet strojarstva i brodogradnje, Zagreb,
Sveučilište u Splitu Sveučilišni odjel za stručne studije
Citiraj ovu publikaciju:
Časopis indeksira:
- Web of Science Core Collection (WoSCC)
- Science Citation Index Expanded (SCI-EXP)
- SCI-EXP, SSCI i/ili A&HCI
- Scopus