Biomechanical analysis of real‐time vibration exposure during mini combine harvester operation: A hybrid ANN–GA approach

Abstract

AbstractThis research focuses on designing and evaluating ergonomic self‐propelled machinery seats to reduce whole‐body vibration (WBV) exposure among male and female agricultural workers. Subjects without musculoskeletal disorders were selected, and their anthropometric parameters were analyzed. An ergonomically refined seat, considering anthropometric dimensions and vibration reduction, was developed and tested. Vibration isolators using piezoelectric material enhanced operator comfort. In a laboratory experiment, real‐time one‐third octave band WBV data were collected using various seat types and engine speeds. At 1200 rpm, female operators experienced WBV levels between 3.42 and 13.40 m/s², while males ranged from 3.13 to 12.20 m/s². At 1600 rpm, females (T‐1) had WBV levels of 20.20–42.39 m/s², and males recorded 18.90–40.12 m/s². At 2000 rpm (T‐1), female operators WBV ranged from 246.71 to 303.45 m/s², and males from 248.10 to 300.13 m/s². At 2400 rpm (T‐1), female operators experienced WBV from 385.29 to 457.87 m/s², and males from 381.57 to 445.50 m/s². An integrated approach with artificial neural networks and genetic algorithms optimized machine operating parameters, resulting in minimum WBV levels. The highly accurate Multilayer Feed‐Forward Artificial Neural Network model (2‐10‐1) had a correlation (R) of 0.996 and a low mean‐squared error of 0.198. This research underscores the effectiveness of seat isolators in reducing vibrations and highlights the importance of considering both seat design and engine speed, especially concerning gender‐specific differences in vibration tolerance. It provides valuable insights for improving the comfort and safety of self‐propelled machinery operators in agriculture.