Görüntü İşleme ve Makine Öğrenmesi Yöntemleri ile Baca Gazı Sıcaklığının Tahmin Edilmesi

Year 2019, Issue: 16, 283 - 291, 31.08.2019

Sedat Golgiyaz , Muhammed Fatih Talu , Cem Onat

https://doi.org/10.31590/ejosat.568348

Cited By: 8

Abstract

Bu makalede,
küçük ölçekli fındık kömürü yakıtlı brülörde baca gazı sıcaklığı tahmini ile
ilgili deneysel bir çalışma sunulmaktadır. Baca gazı sıcaklığı yakıt türüne
göre belli bir aralıkta olması gerekir aksi durumda kazanda korozyona sebep
olmaktadır. Bu çalışma kapsamında alev görüntüsünden öznitelikler elde
edilmiştir. Bu öznitelikler ve DVR modeli ile baca gazı sıcaklığı tahmin
edilmiştir. Alev görüntüsü CCD kamera ile alınmıştır. Aynı zamanda referans
baca gazı sıcaklığı, baca gazı analizörü ile alınmıştır.  Alev görüntüsü ve sıcaklık değeri aynı
bilgisayara kaydedilmiştir. Alev görüntüsü gri seviye görüntüsüne çevrilerek
öznitelikler elde edilmiştir. Öznitelikler elde edilirken alev görüntüsünün
yoğunluk dağılımı kullanılmıştır. Bu işlem için iki tip dağılım kullanılmıştır.
Birincisi görüntünün histogramı alınarak konumdan bağımsız yoğunluk dağılımının
elde edilmesidir. İkincisi satır ve sütun toplamlarını kullanarak uzamsal
yoğunluk dağılımının elde edilmesidir. Bu iki özniteliğin kombinasyonlarından
elde edilen öznitelikler 6 çeşit DVR modeli ile gerçekleştirilmiştir. En iyi
sonuçlar, her iki dağılımdan elde edilen özniteliklerin birlikte kullanıldığı
öznitelik çıkarma yöntemi için kübik DVR modeli ile elde edilmiştir. Önerilen
modelde baca sıcaklığı (T °C) doğruluk ile tahmin edilmiştir. Elde edilen
sonuçlar baca gazı sıcaklığı ile alev görüntüsü arasında yüksek oranda bir
ilişki olduğunu göstermektedir.

Keywords

Baca gazı sıcaklığı tahmini, alev görüntüsü, destek vektör regresyon

Supporting Institution

Türkiye Bilimsel ve Teknolojik Araştırma Kurumu (TÜBİTAK)

Project Number

117M121

Thanks

Bu çalışma, MIMSAN AŞ ve Türkiye Bilimsel ve Teknolojik Araştırma Kurumu (TÜBİTAK, Proje no: 117M121) tarafından desteklenmiştir.

Estimation of Flue Gas Temperature by Image Processing and Machine Learning Methods

Abstract

This paper presents an experimental study on the flue gas temperature estimation in small-scale nut coal-fired boiler. The flue gas temperature must be within a certain range depending on the fuel type, otherwise it causes corrosion in the boiler. Within the scope of this study, features were obtained from flame image. The flue gas temperature was estimated with these features and the SVR model. The flame image was taken with a CCD camera. At the same time, the reference flue gas temperature was taken with the flue gas analyzer. The flame image and temperature are recorded on the same computer. Flame image is converted to gray scale image and features are obtained. The intensity distribution of the flame image was used when obtaining the features. Two types of distribution were used for this process. The first is the histogram of the flame image to obtain a location independent intensity distribution. The second is to obtain a spatial intensity distribution using row and column sums. The attributes obtained from the combinations of these two type features were performed with 6 kinds of SVR models. The best results were obtained for the cubic SVR model for the feature extraction method in which the attributes obtained from both distributions were used together. In the proposed model the flue temperature (T ° C) was estimated with R = 0.97 accuracy. The results show that there is a high correlation between the flue gas temperature and the flame image.

Keywords

Flue gas temperature estimation, flame image, support vector regression

Project Number

117M121

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