Investigation into the vibration characteristics of agricultural wheeled tractor-implement system with hydro-pneumatic suspension on the front axle

Zheng, Enlai; Zhong, Xinyu; Zhu, Rui; Xue, Jinlin; Cui, Song; Gao, Hongbo; Lin, Xiangze

doi:10.1016/j.biosystemseng.2019.05.004

Cited by 25 publications

(13 citation statements)

References 36 publications

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“…It can be seen that the frequency band range in the power spectral density is 0∼13 Hz, and the most active part of the vibration power value is 0∼3 Hz. It is close to the test frequency band of tractor vibration in references [21,24,[31][32][33], and the frequency band range does not change significantly with the change of rectangular pit size. is shows that, under the excitation of soft soil pavement, the vehicle vibration is mainly in the low-frequency range, and the SDOF vibration test system can reflect the overall vibration characteristics of the tractor.…”

Section: Vibration Test Analysissupporting

confidence: 81%

“…Moreover, in the frequency domain, the output signal is the product of the frequency response function of the system and the input signal [29], indicating that the frequency response function of the system is the most active in the excitation of frequency doubling 2 and frequency doubling 3. At the same time, the vibration generated by the ground excitation of the whole tractor is in the low frequency band (0∼3 Hz) [21,24,[31][32][33]. When the acceleration signal is integrated in the frequency domain, the signal in the 0∼1 Hz frequency band would be amplified, and the signal in the 1∼3 Hz frequency band would be reduced, which results that the soil soft road excitation corresponding to the highest peak of the vehicle vibration response is not the fundamental frequency.…”

Section: Correlation Analysis Of Vibration Acceleration Intensity and Effective Roughness Intensity Matlab Combination Equation (mentioning

confidence: 99%

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Perceiving Excitation Characteristics from Interactions between Field Road and Vehicle via Vibration Sensing

Cheng

Man

et al. 2021

Journal of Advanced Transportation

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When agricultural vehicles operate in the field, the soft road excitation makes it difficult to measure the vehicle vibration. A camera-accelerator system can solve this issue by utilizing computer vision information; however, the relationship between the field road surface and the vehicle vibration response remains an unsolved problem. This study aims to investigate the correlation of the soft road excitation of different long-wave surfaces with the vehicle vibration response. Vibration equation between the vehicle and soft road surface system was established to produce an effective roughness model of the field soft road surface. In order to simulate the vehicle vibration state under different long-wave road surfaces, the soil rectangular pits with 21 kinds of different spans and depths were applied to the road surfaces, and a tractor vibration test system was built for vibration test. The frequency spectrum analysis was performed for the vibration response and the roughness signals of the road surfaces. The results showed that coefficient (R2) of frequency correlation between the roughness excitation and the original unevenness at the excitation point at the rear end of the rectangular soil pit fell within 0.9641∼0.9969. The main frequency band of the vibration response fell within 0∼3 Hz, and the phenomenon of quadruple frequency existed. The correlation of roughness excitation with quadruple frequency fell within 0.992165∼1. The primary excitation points were located at the rear end of the rectangular soil pit. In addition, it also indicated that when the vehicle was driven without autonomous power, the vehicle vibration frequency mainly depended on the excitation frequency of the field road surface and the frequency at the maximum vehicle vibration intensity was 2 or 3 times of that at the maximum field soft road excitation. These findings may provide a reference for optimal design of vibration reduction and control for agricultural vehicles.

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Section: Vibration Test Analysissupporting

confidence: 81%

Section: Correlation Analysis Of Vibration Acceleration Intensity and Effective Roughness Intensity Matlab Combination Equation (mentioning

confidence: 99%

Perceiving Excitation Characteristics from Interactions between Field Road and Vehicle via Vibration Sensing

Cheng

Man

et al. 2021

Journal of Advanced Transportation

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“…Розрахункову схему руху задньоначепленого на орно-просапний трактор очисника за умови представлення його переміщення тільки у поздовжньо-вертикальній площині подано на рис. 1. результатів стосується автомобілів [14,15] або колісних тракторів [16,17], в яких параметри коліс і діючі на них сили неспівставні з аналогічними показниками опорно-копіювальних коліс очисника головок коренеплідних культур.…”

Section: вісник аграрної наукиunclassified

Fluctuations dynamics of the root crops cleaner heads from the remnants of tops on the root

Bulgakov¹,

Adamchuk²,

Nadykto³

et al. 2023

Visnyk agrarnoi nauky

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“…Most previous studies on tractor tires, in particular, had the limitation of lab tests being unable to represent actual driving conditions but were conducted at static condition or unloaded condition. For example, Cuong et al [9] and Enlai et al [10] conducted drop tests with steel weights to determine the stiffness and damping coefficient. However, the drop test might yield different results as the test was not carried out in the driving condition, and could not reflect the dynamic effect of a rubber tire.…”

Section: Introduction mentioning

confidence: 99%

Measurement of stiffness and damping coefficient of rubber tractor tires using dynamic cleat test based on point contact model

Yoo¹,

Oh²,

Chung³

et al. 2021

International Journal of Agricultural and Biological Engineering

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The ride vibration of a tractor is affected mostly by the stiffness and damping coefficient of the seat suspension, cabin suspension, cabin rubber mounts, and rubber tires. However, in the case of rubber tractor tires, the stiffnesses and damping coefficients have not been researched adequately thus far, and it is not simple to measure these characteristics . In this study, a method for measuring and analyzing the stiffnesses and damping coefficients of rubber tractor tires, which were the input parameters for the tractor ride vibration simulation, was proposed. The cleat test, proposed in this study, did not require separate and complicated test equipment, unlike the conventional methods. The test was conducted simply by measuring acceleration under the driving conditions of the vehicle without detaching tires from the vehicle body or setting up additional test equipment. Based on the ground-vertical acceleration data obtained, the stiffness was calculated using the logarithmic decrement method, and the damping coefficient was calculated using least squares exponential curve fitting. The result of the cleat test indicated that the front tires had stiffnesses of 486.08-570.69 kN/m and damping coefficients of 4.02-4.52 kN• s/m; the rear tires had stiffnesses of 409.42-483.79 kN/m and damping coefficients of 2.21-2.67 kN• s/m. During the test, 40 mm height cleats were installed on the track and the speed of the tractor was set to 7 and 10 km/h, which were the most common speeds during the operation. This study is meaningful in that it has presented a new method that improves the practicality of results, reduces cost, and simplifies the test process for measuring the stiffnesses and damping coefficients of rubber tractor tires.

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Investigation into the vibration characteristics of agricultural wheeled tractor-implement system with hydro-pneumatic suspension on the front axle

Cited by 25 publications

References 36 publications

Perceiving Excitation Characteristics from Interactions between Field Road and Vehicle via Vibration Sensing

Perceiving Excitation Characteristics from Interactions between Field Road and Vehicle via Vibration Sensing

Fluctuations dynamics of the root crops cleaner heads from the remnants of tops on the root

Measurement of stiffness and damping coefficient of rubber tractor tires using dynamic cleat test based on point contact model

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