Reducing vibration by matching the right seat for forestry applications
Lower-back injury is a major health issue among heavy machinery operators and exposure to heavy vibrations during work is a contributing factor. A new model has been developed that could help reduce vibrations by matching the right seats to the machine and operator.
Canadian researchers from the Western University and Laurentian University have developed a neural network (NN) model to characterise the vibration attenuation properties of five commercial industrial seats. The industrial seats were mounted on a robotic platform and measurements were recorded of their translational accelerations and rotational velocities. Ten subjects with no history of lower-back pain were also tested to further develop the model.
The dynamic response of each industrial seat was successfully identified based on a NN concept model implemented in Excel. Although the correlations were typically smaller in the validations compared to the models development, excellent correlations for both the training and validation sets were achieved for all of the seats.
Click here for source (Taylor & Francis Online)
Photo: Xiaoxu Ji