RT info:eu-repo/semantics/article
T1 Application of composite spectrum in agricultural machines
A1 Feijóo García, Fernando
A1 Gómez Gil, Francisco Javier
A1 Gómez Gil, Jaime
K1 Monitoring
K1 Supervision
K1 Vibration
K1 Maquinas agrícolas
K1 Composite spectrum
K1 Coherent
K1 Predictive maintenance
K1 3102.04 Maquinas y Aperos
K1 2201.11 Vibraciones
AB Composite spectrum (CS) is a data-fusion technique that reduces the number of spectra to be analyzed, simplifying the analysis process for machine monitoring and fault detection. In this work, vibration signals from five components of a combine harvester (thresher, chopper, straw walkers, sieve box, and engine) are obtained by placing four accelerometers along the combine-harvester chassis in non-optimal locations. Four individual spectra (one from each accelerometer) and three CS (non-coherent, coherent and poly-coherent spectra) from 18 cases are analyzed. The different cases result from the combination of three working conditions of the components—deactivated (off), balanced (healthy), and unbalanced (faulty)—and two speeds—idle and maximum revolutions per minute (RPM). The results showed that (i) the peaks can be identified in the four individual spectra that correspond to the rotational speeds of the five components in the analysis; (ii) the three formulations of the CS retain the relevant information from the individual spectra, thereby reducing the number of spectra required for monitoring and detecting rotating unbalances within a combine harvester; and, (iii) data noise reduction is observed in coherent and poly-coherent CS with respect to the non-coherent CS and the individual spectra. This study demonstrates that the rotating unbalances of various components within agricultural machines, can be detected with a reduced number of accelerometers located in non-optimal positions, and that it is feasible to simplify the monitoring with CS. Overall, the coherent CS may be the best composite spectra formulation in order to monitor and detect rotating unbalances in agricultural machines.
PB MDPI
SN 1424-8220
YR 2020
FD 2020
LK https://uvadoc.uva.es/handle/10324/59025
UL https://uvadoc.uva.es/handle/10324/59025
LA eng
NO Sensors, 2020, Vol. 20, Nº. 19, 5519
NO Producción Científica
DS UVaDOC
RD 14-oct-2024