| Summary: | 博士 === 國立中興大學 === 生物產業機電工程學系 === 92 === This study develops a nondestructive inspection method and quality index construction model to evaluate the quality of agricultural products using digital signal processing and statistical discriminate analysis. A pendulum device is designed to impact and measure the response signal of products. The impact parameters which correspond to the change in the quality of agricultural products are obtained from the amplitude spectrum, real-part spectrum, imaginary-part spectrum and the slope, curvature and micro-fluctuation signal of the impact force-time curve. The analysis of variance (95% confidence interval) is used to determine the effective frequency and amplitude of the spectra of amplitude, real-part and imaginary-part as the inspection parameters for the quality of agricultural products. Analyses indicate that a three-order lowpass digital filter can smoothen the raw impact force-time curves to calculate their exact slope and curvature using finite difference. The maximum and minimum slopes, maximum and minimum curvatures and time of inflection point are valid impact parameters from the curve. Additionally, the power spectral density of the micro-fluctuation signal obviously reflects the variation in the texture of soft products using the Wiener-Khintchine theorem. The accuracies are lower than 70% using an impact parameter to classify the quality of guavas, mangos and tomatoes, as well as to egg variety. However, the classification accuracies can be improved by more than 10% when using high accuracy indices with parameters selected from the time and frequency domains, as well as their combinations, which are established using statistical discriminate analysis. Test results demonstrate that the accuracy reaches 82.7%, 81.0%, 85.7%, 80.0% and 82.5% in quality classification of guava maturity, mango maturity, mango acidity and tomato maturity and recognition classification of egg variety, respectively.
|
|---|
