|کد مقاله||کد نشریه||سال انتشار||مقاله انگلیسی||ترجمه فارسی||نسخه تمام متن|
|209183||461659||2016||6 صفحه PDF||سفارش دهید||دانلود رایگان|
این مقاله ISI می تواند منبع ارزشمندی برای تولید محتوا باشد.
- تولید محتوا برای سایت و وبلاگ
- تولید محتوا برای کتاب
- تولید محتوا برای نشریات و روزنامه ها
پایگاه «دانشیاری» آمادگی دارد با همکاری مجموعه «شهر محتوا» با استفاده از این مقاله علمی، برای شما به زبان فارسی، تولید محتوا نماید.
• Experimental studies for Turkish lignite in a fixed-bed dryer were carried out.
• ANFIS was applied to predict coal moisture level in drying process
• ANFIS network achieves quite satisfying scientific results.
• Results show the applicability of ANFIS in the coal drying.
• This is the first attempt of using ANFIS for moisture estimation in coal drying process.
In this study, a new methodology was applied to estimate the coal moisture content during the drying process. Adaptive-network-based fuzzy inference system (ANFIS) was applied to predict the coal moisture content at any time during the drying process. The experiments were carried out for different drying air temperatures (70, 100, 130 and 160 °C), drying air velocities (0.4, 0.7 and 1.1 m/s), bed heights (80, 130 and 150 mm) and sample sizes (20, 35 and 50 mm), and the experimental results were used to validate applicability of the ANFIS in the coal drying process. The ANFIS network achieves quite satisfying scientific results with acceptable deviations. The MSE and R2 values were calculated as 1.899 and 0.998, respectively, for the testing stage. The results of this study show the applicability of the ANFIS in the coal drying processes to predict the coal moisture content at any time. Therefore, it is not necessary to carry out all the experiments: by using the ANFIS, the drying curves of some other cases which are not performed can be estimated easily. Herewith, the necessary number of the experiments decreases.
Journal: Fuel Processing Technology - Volume 147, 15 June 2016, Pages 12–17