2021
DOI: 10.3397/1/376921
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Research on a method for diagnosing clogging faults and longitudinal axial flow in the threshing cylinders of drum harvesters

Abstract: Here we present a high-precision method for predicting threshing drum clogging in drum harvesters, with strong applicability for longitudinal axial flow in crawlers. This method can be used to determine the alarm threshold. It entails placing a wireless vibration sensor at the outer end of the rotary shaft of the harvester to collect axial vibration signals from the drum to detect early fault characteristics. The method employs the Hilbert-Huang transform-analysis method to obtain time-frequency spectrum char… Show more

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Cited by 3 publications
(2 citation statements)
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“…In Equation (15), the torque at the left and right ends can be approximately equal to I, the torsional stiffness is K T , and the torsional damping is D r . The solution to this equation is shown in Equation (16).…”
Section: Modeling Of Threshing Drum Drive Systemmentioning
confidence: 99%
See 1 more Smart Citation
“…In Equation (15), the torque at the left and right ends can be approximately equal to I, the torsional stiffness is K T , and the torsional damping is D r . The solution to this equation is shown in Equation (16).…”
Section: Modeling Of Threshing Drum Drive Systemmentioning
confidence: 99%
“…Wang et al collected the vibration signal of the shaft end of the threshing drum by a wireless vibration sensor, and the Hilbert-Huang transform analysis method was used to analyze and process the signal to obtain the blockage process of the threshing drum. The time-spectral characteristics of the combined harvester predict its blocking trend, so as to adjust the combine harvester's travel speed to avoid blocking [16]. Kumar et al used vibration sensors to collect vibration signals of rotating machinery, and analyzed the spectrum of the obtained signals through signal processing technology to determine the severity of component vibration to propose failure prediction methods [17,18].…”
Section: Introductionmentioning
confidence: 99%