## 3 Processing Method of Vibration Piezoelectric Signal
### Calibrate and Select Vibration Frequency  
1. The selection of vibration frequency is tailored to the physical properties of different grain types and is determined through controlled experimental testing. Trials were conducted on various grains--including corn, wheat, and soybean--to assess the effectiveness of grain separation under different vibration frequencies. The motion behavior of grains during vibration was carefully observed to ensure consistent separation from the tray while avoiding excessive vibration that could lead to mechanical damage. The frequency range was adjusted according to grain size and morphology. For instance, larger grains generally required lower frequencies (e.g., 4-5 Hz), whereas smaller grains responded better at higher frequencies (e.g., 6-7 Hz). The optimal vibration frequency range for each grain type was determined empirically based on these observations.  
2. Frequency calibration was performed through an experimental stepwise adjustment method. Beginning at a reference frequency of 5.2 Hz, as reported in the literature, the frequency was incrementally increased or decreased in 0.1 Hz intervals. For each frequency setting, the effectiveness of grain separation and the signal quality from the piezoelectric sensor were evaluated. Key experimental metrics--such as seed loss rate and moisture monitoring accuracy--were recorded at each step. The frequency that yielded the best overall performance was identified as the calibrated optimal frequency.  
Comparison of multiple experiments: To validate the selected frequency ranges, multiple experiments were conducted to evaluate the drying performance of different seed types under varying vibration frequencies. Statistical analysis methods, such as analysis of variance (ANOVA), were employed to compare experimental outcomes across frequency settings.  
3. Calibration was also conducted through detailed analysis of the piezoelectric sensor's output signal using SEGER J-Scope V6.11 or comparable signal acquisition software. Key signal characteristics--including amplitude, frequency, and waveform--were analyzed to identify a vibration frequency that could effectively distinguish between crop grains and impurities. The vibration frequency was then optimized to enhance the signal-to-noise ratio (SNR), reduce the signal outage probability (OP), and improve the system's real-time monitoring and feedback capabilities. During the drying process, the piezoelectric signal was continuously monitored. Based on the real-time signal quality, the vibration frequency was dynamically adjusted to accommodate varying drying conditions and differences in grain physical properties.  
4. Frequency scanning experiment: A series of experiments were conducted across a range of vibration frequencies (e.g., 4 Hz to 6 Hz) to evaluate their effect on seed separation efficiency and the occurrence of thermal damage (burning). During the tests, airflow speed was maintained at a constant 3 m/s. Corn was used as the representative crop for analysis. Key performance metrics recorded included burn rate, moisture monitoring accuracy, and signal outage probability. The results are presented in Table 4.  
As shown in the table, a vibration frequency of 5.2 Hz yielded the most favorable outcomes: it achieved the lowest seed burn rate, the highest monitoring accuracy for moisture variation, and the minimal signal outage probability. Accordingly, 5.2 Hz was identified as the optimal vibration frequency following calibration.