## 3 Processing Method of Vibration Piezoelectric Signal
### Results and Analyses of Maize Mixture Trials  
The drying temperature was set according to the intended use of the maize: (1) edible corn: 45 \({}^{\circ}\)C; (2) industrial corn for starch fermentation: 50 \({}^{\circ}\)C; (3) seed corn: 40 \({}^{\circ}\)C.  
The vibration frequency was fixed at 5.2 Hz. Prior to testing, the piezoelectric detection unit was evaluated ten times for each grain-impurity pair. The output signals recorded by the acquisition system consistently reflected accurate identification results, indicating the system's robustness against vibrational disturbances. Corn samples were individually weighed and mixed; then, they were uniformly distributed across the designated loading area of the vibrating tray. The feed rates were set at 2, 4, 6, and 8 kg/s. After the drying process, separated impurities or lost particles were collected and weighed. The corresponding data were transmitted in real time to a digital display unit via the integrated weight sensor, enabling the dynamic monitoring of mass variation throughout the drying process.  
\begin{table}
\begin{tabular}{c c c c} \hline
**Group** & **Mass of Burned Seeds/g** & \
\begin{tabular}{c} **Mass of Unburned** \\ **Seeds/g** \\ \end{tabular} &
\begin{tabular}{c} **Total Mass of Grains/g** \\ \end{tabular} \\ \hline Control group & 230 & 9770 & 10,000 \\ Experimental group & 40 & 9960 & 10,000 \\ \hline \end{tabular}
\end{table}
Table 5: Comparative analysis of seed burned mass.  
Table 6 illustrates the direct impact of feed rate on grain loss. As the feed rate increases, both the quantity and quality of lost grains rise significantly. When the system operates under high load conditions, the drying apparatus becomes processing-constrained, leading to greater grain damage and loss during the vibration-assisted drying process. Moreover, the quality of lost material is not uniform. Higher feed rates result in increased seed flow density, which intensifies inter-particle collisions and friction. This, in turn, reduces the effectiveness of the piezoelectric detection unit for seed-impurity separation, impairs detection accuracy, and contributes to a higher absolute error in loss rate measurements. Under these conditions, the detection unit is unable to reliably quantify the true loss rate of the seed material. Nevertheless, seed and impurity classification based on one-dimensional time-frequency signal features demonstrates strong generalizability and accuracy, providing a robust foundation for non-contact, real-time classification even under varying operating conditions.  
The weighing process of the maize mixture is shown in Figure 6, then evenly place the 7 kg, 7.5 kg, 8 kg, and 8.5 kg corn mixture into the designated areas of the oscillating grain tray.  
The composition, moisture loss measurements, and drying times were determined by field trials (see Table 7).  
According to the Table 7, we can conclude the following:  
1. The novel vibratory heating tray proposed in this study demonstrated strong experimental performance. After heating, the moisture loss rate of maize seeds consistently stabilized between 0.77% and 0.79%, indicating both effectiveness and repeatability.  
\begin{table}
\begin{tabular}{c c c} \hline \hline
**Feeding Rates** & **Number of Grain** & **Mass of Grain** \\
**(kg/s)** & **Loss/pc** & **Loss/g** \\ \hline
2.0 & 139 & 64.9 \\  & 125 & 59.9 \\  & 130 & 62.1 \\  & 131 & 63.2 \\
4.0 & 550 & 261.8 \\  & 530 & 251.9 \\  & 561 & 262.3 \\  & 547 & 261.5 \\
6.0 & 1019 & 497.4 \\  & 961 & 452.7 \\  & 983 & 467.1 \\  & 987 & 459.2 \\
8.0 & 1839 & 867.6 \\  & 1764 & 858.3 \\  & 1962 & 908.5 \\  & 1855 & 876.5 \\ \hline \hline \end{tabular}
\end{table}
Table 6: Grain loss rates with piezoelectric detection system.  
Figure 6: Vibration drying and transmission process of maize as an example.