The Impact of Sound Pressure Level, Loudness, Roughness, Sharpness, Articulation Index, Hand Vibration, and Seat Vibration on Subjective Comfort Perception of Tractor Drivers

Abstract

Long-term exposure to high levels of vibration and noise can have detrimental effects on the health of tractor drivers. This study aimed to evaluate the subjective comfort experienced by drivers operating large-horsepower tractors. A total of 10 tractors sourced from 5 different manufacturers were subjected to testing. The assessment encompassed three operational conditions, namely, idle, maximum torque, and rated power. Objective measurements, including A-weighted sound pressure level (A-SPL), loudness, sharpness, roughness, articulation index (AI), hand vibration, and seat vibration, were collected. Additionally, subjective comfort evaluations were carried out using a paired comparison test. To predict the subjective comfort of tractor drivers, a novel prediction model was developed by employing a simulated annealing (SA) algorithm to optimize a backpropagation neural network (BPNN). The model successfully achieved accurate predictions of subjective comfort, yielding a maximum prediction error of 4.4%. The study findings revealed that vibration had a more pronounced impact on driver comfort in environments with lower-amplitude noise, whereas high-decibel noise exerted a masking effect on vibration-induced discomfort. In conclusion, the SA-BPNN model, utilizing A-SPL, loudness, sharpness, roughness, AI, hand vibration, and seat vibration as objective parameters, effectively predicted the subjective comfort of tractor drivers. This discovery holds significant implications for tractor manufacturers, who can employ the model to optimize the design of tractor cabs and enhance driver comfort.