Wykaz publikacji wybranego autora

Paweł Pawlik, dr hab. inż., prof. AGH

profesor nadzwyczajny

Wydział Inżynierii Mechanicznej i Robotyki
WIMiR-kmw, Katedra Mechaniki i Wibroakustyki

  • 2018

    [dyscyplina 1] dziedzina nauk inżynieryjno-technicznych / inżynieria mechaniczna

[poprzednia klasyfikacja] obszar nauk technicznych / dziedzina nauk technicznych / mechanika

Identyfikatory Autora Informacje o Autorze w systemach zewnętrznych

ORCID: 0000-0002-2654-6138 orcid iD

ResearcherID: T-1947-2017

Scopus: 55596440400

PBN: 5e709406878c28a0473b50ce

OPI Nauka Polska

System Informacyjny AGH (SkOs)

1
  • Application of the interval arithmetic in the reverberation time uncertainty assessment
2
  • Automatic detection system of aircraft noise events during acoustic climate long-term monitoring near airport
3
  • CMAFI – copula-based multifeature autocorrelation fault identification of rolling bearing
4
  • Condition monitoring of distributed systems using two-stage Bayesian inference data fusion
5
  • Does stochastic and modulated wind turbine infrasound affect human mental performance compared to steady signals without modulation?
6
  • Experimental studies of the impact of amplitude modulation (AM) and tonality on the annoyance of wind turbine noise in the low frequency (LF) range
7
  • Experimental verification of windshields in the measurement of low frequency noise from wind turbines
8
  • Fault diagnosis using artificial neural networks trained only on signals from an undamaged machine
9
  • Identification of acoustic event of selected noise sources in a long-term environmental monitoring systems
10
11
  • Measurement system for harmonic source noise directivity definition, based on phase correlation in multimicrophone configuration
12
  • Modelling low-frequency noise of wind turbines
13
14
  • The acoustic method for diagnosing machines operating under variable conditions
15
  • The dependence of transformer sound power measurement accuracy on microphone configurations in the anechoic chamber
16
  • The uncertainty in modelling of environmental acoustic threats generated by railway transport
17
  • The use of deep learning methods in diagnosing rotating machines operating in variable conditions
18
  • Uncertainty analysis in the noise parameters estimation
19
  • Uncertainty analysis in the road traffic noise modelling
20
  • Uncertainty analysis in the road traffic noise modelling
21
  • Uncertainty in sound diffusion and scattering coefficients measurement