This paper presents whole-body vibration prediction in an agricultural tractor based on selected operational parameters using machine learning. Experiments were performed using a Landini Powerfarm 100 model tractor on farmlands and service roads located at the Osijek School of Agriculture and Veterinary Medicine. The methodology adhered to the HRN ISO 5008 protocols for establishing test surfaces, including a smooth 100 m track and a rugged 35 m track. Whole-body vibrational exposure assessments were carried out in alignment with the HRN ISO 2631-1 and HRN ISO 2631-4 guidelines, which outline procedures for evaluating mechanical oscillations in occupational settings. The obtained whole-body vibration data were divided into three datasets (one for each axis) and processed using linear regression as a baseline and compared against three machine learning models (gradient boosting regressor; support vector machine regressor; multi-layer perception). The most accurate machine learning model according to the R² metric was the gradient boosting regressor for the x-axis (R²: 0.98) and the y-axis (R²: 0.98), and for the z-axis (R²: 0.95), the most accurate machine learning model was the SVM regressor. The application of machine learning methods indicates that machine learning models can be used to predict whole-body vibrations more accurately than linear regression.

This paper presents research on the impact of vibrations on the hand–arm and body system of agricultural tractor operators as ergonomic indicators in relation to certain operational parameters. The measurements were conducted on a LANDINI POWERFARM 100 tractor on agricultural production areas and access roads of the Agricultural and Veterinary School in Osijek. The measurements followed the ISO 5008:2015 standard, which describes the creation of test tracks: a smooth track of 100 m in length and a rough track of 35 m in length. Body vibration measurements were conducted according to the prescribed standards HRN ISO 2631-1: 1999/A1:2019 and HRN ISO 2631-4:2010. Hand–arm system vibration measurements were performed according to the prescribed standards HRN ISO 5349-1:2008 and HRN ISO 5349-2:2008/A1:2015. After the measured data were processed, a three-factor analysis of variance was performed, where some operational parameters were designated as A—agrotechnical surfaces (6 types), B—tractor speed (6 speeds), and C—tire air pressure (3 pressures), along with multiple regression analysis and the AHP (analytical hierarchical process). This research determined that none of the measured hand–arm system vibrations exceeded the warning (2.5 ms⁻²) or limit (5 ms⁻²) values of daily exposure. Furthermore, vibrations affecting the operator’s body in the x-axis at higher speeds and pressures C2 and C3, in the y-axis at higher speeds and pressures C1 and C2, and in the z-axis at the highest speed and pressures C1 and C2 were found to exceed the daily exposure warning value of 0.5 ms⁻². It was concluded that the operator’s health is at risk, and it is recommended that the seat’s air suspension system be inspected to prevent further complications in a timely manner.

The paper presents a study of the influence of an uneven surface and number of tractor hours on vibration that is transmitted to the operator's hand-arm system during operation. The study was conducted on the asphalt, gravel and grass traversal during 2015 and 2016. The results indicate that the movement of a tractor on different agrotechnical surfaces generates vibrations of varying intensity that affect the hand-arm system of the operator. The highest vibration values were recorded on the asphalt, while the least vibrations were measured on the grass. The measured maximum vibration values are lower than the permissible 5 m·s−2 in the direction of all three axes, making it possible to assume that they are not harmful to the health of the operator.

This study analyzes the vibrations to which the WBV of an agricultural tractor operator is exposed during the performance of three different tillage’s: Standard Tillage (ST), System Deep (CTD) and System Shallow (CTS). Measurements were carried out according to ISO 2631-1 and ISO 2631-4 in three coordinate axes (x, y, z). The analysis and statistical processing carried out indicates that none of the mean vibration values exceeds the prescribed limit value of 1.15 m/s² according to Directive 2002/44/EC, but exceeds the daily warning value of 0.5 m/s². From the above, it can be assumed that the operator of the investigated tractor may be exposed to the occurrence of occupational diseases by long-term exposure to such vibrations. The highest vibrations in the x and y axes were recorded when working with the ripper, while in the z-axis they were the highest in the loosener. Although the measured values are within safe (permissible) limits, further research on this topic and optimization of operation can further reduce the burden on the operator.

This study analyzes whole-body vibration (WBV) exposure of an agricultural tractor operator during three different primary tillage systems: Standard Tillage (ST), Conservation Tillage Deep (CTD), and Conservation Tillage Shallow (CTS). Measurements were conducted in accordance with ISO 2631-1 and ISO 2631-4 along three orthogonal axes (x, y and z) at the operator’s seat. Descriptive and inferential statistical analyses indicate that while none of the mean vibration values exceeded the regulatory limit value of 1.15 m/s² defined in Directive 2002/44/EC, several measurements—particularly in the y-axis during ST (0.715 m/s²)—surpassed the exposure action value of 0.5 m/s². These findings suggest that prolonged daily exposure under similar operational conditions may pose long-term health risks for tractor operators. The highest mean WBV values were recorded in the x- and y-axes during CTS (0.354 m/s² and 0.446 m/s², respectively), whereas the z-axis exhibited the highest values during ST (0.426 m/s²). Conservation Tillage Deep (CTD) demonstrated the most favorable vibration profile in the vertical axis (0.344 m/s²), indicating its potential dual benefit for soil structure preservation and operator ergonomics. Although all measured values remained below the regulatory limit, the frequent exceedance of the action value underscores the importance of exposure time management, regular maintenance of suspension systems, and implement selection as practical mitigation strategies. This comparative assessment provides baseline WBV data for reduced-tillage systems on hydromorphic soils and offers axis-specific guidance for optimizing operator comfort in sustainable mechanization practices.