Development of Multifrequency-Swept Microwave Sensing System for Moisture Measurement of Sweet Corn With Deep Neural Network
| العنوان: | Development of Multifrequency-Swept Microwave Sensing System for Moisture Measurement of Sweet Corn With Deep Neural Network |
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| المؤلفون: | Jun Wang, Dongdong Du, Zhang Jinyang, Yin Bao, Wei Zhenbo |
| المصدر: | IEEE Transactions on Instrumentation and Measurement. 69:6446-6454 |
| بيانات النشر: | Institute of Electrical and Electronics Engineers (IEEE), 2020. |
| سنة النشر: | 2020 |
| مصطلحات موضوعية: | Boosting (machine learning), Artificial neural network, Moisture, 020208 electrical & electronic engineering, Ranging, 02 engineering and technology, Signal, 0202 electrical engineering, electronic engineering, information engineering, AdaBoost, Electrical and Electronic Engineering, Instrumentation, Water content, Microwave, Remote sensing, Mathematics |
| الوصف: | Moisture measurement has long been a challenge for agricultural products with high moisture content (MC). In this article, a novel microwave sensing system embedded with multifrequency-swept technique was built with off-the-shelf components and applied to moisture measurement of sweet corn [MC is approximately 80% wet basis (w.b.)]. In order to collect sufficient moisture information, a frequency-swept signal (contains 41 frequencies from 2.60 to 3.00 GHz) was taken as the original measurement signal. A total of 20 redundant frequencies were removed from the original measurement signal according to the frequency selection for further measurements. Four different algorithms, including deep neural network (DNN), random forest (RF), adaptive boosting (AdaBoost), and extreme gradient boosting (XGBoost), were employed to establish moisture prediction models. The proposed six-layer DNN showed the best performance ( $R^{2}=0.980$ , $RMSE =2.023\%$ , and $MAE =1.556\%$ ) in predicting the MC of sweet corn (ranging from 15.45% to 81.19% w.b.). The results showed that the developed microwave sensing system was capable of measuring the MC of sweet corn and could potentially be applied to moisture determination of other agricultural products with high MC in food processing industry. |
| تدمد: | 1557-9662 0018-9456 |
| DOI: | 10.1109/tim.2020.2972655 |
| URL الوصول: | https://explore.openaire.eu/search/publication?articleId=doi_________::61191d1f9257dac9bc9bb2a03a23fb18 https://doi.org/10.1109/tim.2020.2972655 |
| Rights: | CLOSED |
| رقم الانضمام: | edsair.doi...........61191d1f9257dac9bc9bb2a03a23fb18 |
| قاعدة البيانات: | OpenAIRE |
| تدمد: | 15579662 00189456 |
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| DOI: | 10.1109/tim.2020.2972655 |