Falling Damage Behavior Analysis and Degree Prediction for Wooden Pallet Based on Piezoelectric Effect and Acoustic Emission

Abstract

Wooden pallets can straightforwardly sustain fractures during storage and transportation. This shortens their service life. To minimize the economic losses caused by damage to wooden pallets, this study aimed to 1) investigate the falling damage behavior of wooden pallets by piezoelectric technology and acoustic emission (AE) and 2) evaluate a nondestructive method for damage-degree detection. The piezoelectric signal of the wooden pallets during the falling process was collected and analyzed for the variation law. The corresponding AE parameters were obtained when the different damage status occurred. It was observed that the peak voltage piezoelectric signal of the pallets decreased with an increase in the number of falls, and rebounded after damage occurred. The rebounding amplitude depended on the damage degree. The AE parameters of ringing count, energy, and amplitude reduced significantly as the pallet damage degree aggravated. The high-frequency proportion of the AE signal was observed to decrease as the damage strengthened. From undamaged to completely broken, the damage behavior of the wooden pallet generally underwent four stages: nondestructive, nail loosening, nail withdrawal, and the deck board off stage. The boundary of each damage stage could be clearly identified and read from the profile of the piezoelectric signal. Moreover, each stage could be effectively monitored and characterized by the AE parameters. Therefore, the combination of piezoelectric sensors and AE technology is capable of determining the structural health status of wooden pallets in use and predicting the remaining life.