Flame Failures and Recovery in Industrial Furnaces: A Neural Network Steady-State Model for the Firing Rate Setpoint Rearrangement
المؤلفون المشاركون
Chaibakhsh, Ali
Adili, Tahmineh
Rostamnezhad, Zohreh
Jamali, Ali
المصدر
International Journal of Chemical Engineering
العدد
المجلد 2018، العدد 2018 (31 ديسمبر/كانون الأول 2018)، ص ص. 1-15، 15ص.
الناشر
Hindawi Publishing Corporation
تاريخ النشر
2018-06-20
دولة النشر
مصر
عدد الصفحات
15
الملخص EN
Burner failures are common abnormal conditions associated with industrial fired heaters.
Preventing from economic loss and major equipment damages can be attained by compensating the lost heat due to burners’ failures, which can be possible by defining appropriate setpoints to rearrange the firing rates for healthy burners.
In this study, artificial neural network models were developed for estimating the appropriate setpoints for the combustion control system to recover an industrial fired-heater furnace from abnormal conditions.
For this purpose, based on an accurate high-order mathematical model, constrained nonlinear optimization problems were solved using the genetic algorithm.
For different failure scenarios, the best possible excess firing rates for healthy burners to recover the furnace from abnormal conditions were obtained and data were recorded for training and testing stages.
The performances of the developed neural steady-state models were evaluated through simulation experiments.
The obtained results indicated the feasibility of the proposed technique to deal with the failures in the combustion system.
نمط استشهاد جمعية علماء النفس الأمريكية (APA)
Adili, Tahmineh& Rostamnezhad, Zohreh& Chaibakhsh, Ali& Jamali, Ali. 2018. Flame Failures and Recovery in Industrial Furnaces: A Neural Network Steady-State Model for the Firing Rate Setpoint Rearrangement. International Journal of Chemical Engineering،Vol. 2018, no. 2018, pp.1-15.
https://search.emarefa.net/detail/BIM-1170130
نمط استشهاد الجمعية الأمريكية للغات الحديثة (MLA)
Adili, Tahmineh…[et al.]. Flame Failures and Recovery in Industrial Furnaces: A Neural Network Steady-State Model for the Firing Rate Setpoint Rearrangement. International Journal of Chemical Engineering No. 2018 (2018), pp.1-15.
https://search.emarefa.net/detail/BIM-1170130
نمط استشهاد الجمعية الطبية الأمريكية (AMA)
Adili, Tahmineh& Rostamnezhad, Zohreh& Chaibakhsh, Ali& Jamali, Ali. Flame Failures and Recovery in Industrial Furnaces: A Neural Network Steady-State Model for the Firing Rate Setpoint Rearrangement. International Journal of Chemical Engineering. 2018. Vol. 2018, no. 2018, pp.1-15.
https://search.emarefa.net/detail/BIM-1170130
نوع البيانات
مقالات
لغة النص
الإنجليزية
الملاحظات
Includes bibliographical references
رقم السجل
BIM-1170130
قاعدة معامل التأثير والاستشهادات المرجعية العربي "ارسيف Arcif"
أضخم قاعدة بيانات عربية للاستشهادات المرجعية للمجلات العلمية المحكمة الصادرة في العالم العربي
تقوم هذه الخدمة بالتحقق من التشابه أو الانتحال في الأبحاث والمقالات العلمية والأطروحات الجامعية والكتب والأبحاث باللغة العربية، وتحديد درجة التشابه أو أصالة الأعمال البحثية وحماية ملكيتها الفكرية. تعرف اكثر