<p>Electrical properties of a propane flame was investigated to improve detection of the flame in absorption refrigerators. The principle of flame rectification, which uses the diode property of the flame, was studied. A DC voltage in the range 0–130V was applied, between the burner and an electrode in the flame, and the current through the flame in the forward and reverse direction was measured. This measurements were performed with the electrode top in different horizontal and vertical positions. AC voltages at various frequencies was also applied and the average current through the flame was measured.</p><p>A linear relation was found between the applied DC voltage and the current through the flame which means that the resistance, in the investigated voltage range, is independent of the applied voltage. The resistance in the forward direction was almost constant for different electrode positions but the reverse resistance varied many hundred MOhm­ when the electrode was moved vertically away from the burner. The gas flow also influenced the reverse resistance to a large extent.</p> / <p>Elektriska egenskaper hos en propanlåga undersöktes i syfte att förbättra detekteringen av lågan i absorptionskylskåp. Rektifieringsprincipen, vilken utnyttjar lågans diodegenskap, undersöktes. En likspänning i intervallet 0–130V lades på, mellan brännaren och en elektrod i lågan, och strömmen genom lågan i fram- och backriktningen mättes. Dessa mätningar gjordes med elektroden i olika horisontella och vertikala positioner. Växelspänning med olika frekvenser lades också på och medelvärdet av strömmen genom lågan mättes.</p><p>Ett linjärt samband upptäcktes mellan pålagd likspänning och strömmen genom lågan vilket betyder att resistansen, i det undersökta spänningsintervallet, är oberoende av pålagd spänning. Resistansen i framriktningen var i princip konstant vid olika elektrodplaceringar medan backresistansen varierade flera hundra MOhm när elektroden flyttades bort från brännaren vertikalt. Gasflödet påverkade också backresistansen i stor utsträckning.</p>

Electrical properties of a propane flame was investigated to improve detection of the flame in absorption refrigerators. The principle of flame rectification, which uses the diode property of the flame, was studied. A DC voltage in the range 0–130V was applied, between the burner and an electrode in the flame, and the current through the flame in the forward and reverse direction was measured. This measurements were performed with the electrode top in different horizontal and vertical positions. AC voltages at various frequencies was also applied and the average current through the flame was measured. A linear relation was found between the applied DC voltage and the current through the flame which means that the resistance, in the investigated voltage range, is independent of the applied voltage. The resistance in the forward direction was almost constant for different electrode positions but the reverse resistance varied many hundred MOhm­ when the electrode was moved vertically away from the burner. The gas flow also influenced the reverse resistance to a large extent. / Elektriska egenskaper hos en propanlåga undersöktes i syfte att förbättra detekteringen av lågan i absorptionskylskåp. Rektifieringsprincipen, vilken utnyttjar lågans diodegenskap, undersöktes. En likspänning i intervallet 0–130V lades på, mellan brännaren och en elektrod i lågan, och strömmen genom lågan i fram- och backriktningen mättes. Dessa mätningar gjordes med elektroden i olika horisontella och vertikala positioner. Växelspänning med olika frekvenser lades också på och medelvärdet av strömmen genom lågan mättes. Ett linjärt samband upptäcktes mellan pålagd likspänning och strömmen genom lågan vilket betyder att resistansen, i det undersökta spänningsintervallet, är oberoende av pålagd spänning. Resistansen i framriktningen var i princip konstant vid olika elektrodplaceringar medan backresistansen varierade flera hundra MOhm när elektroden flyttades bort från brännaren vertikalt. Gasflödet påverkade också backresistansen i stor utsträckning.

This master’s thesis deals with flame detection methods. The purpose of the project was to create a flame detector, which uses the alternative method of flame detection. The introduction of this thesis gives the summary overview of the existing methods for flame detection. Further, the existing flame detectors and their applications are described. Two alternative algorithms for flame detection which are based on the digital signal analysis were realized on the PC. Flame detector, which utilizes the digital analysis of audio signal, was realized on 8 bit microcontroller Atmega128 and achieved results are presented.

Práce se zabývá fyzikálními vlastnostmi pyroelektrických senzorů a jejich praktickým využitím. Součástí práce je návrh a realizace měřící aparatury, jež bude využita k měření fyzikálních vlastností senzorů. Pro měření signálů pyroelektrického senzoru bude navržen nízkošumový zesilovač. Součástí práce je také návrh a realizace algoritmu pro lokalizaci infračerveného zdroje záření (plamene) v prostoru, na základě vyhodnoceného analogového signálu.

Quick and accurate detection of flame inside a gas turbine is very crucial to mitigaterisks in power generation. Failure of flame detection increases downtime and maintenancecosts and on rare occasions it may cause explosions due to buildup of incombustible fuel inside the combustion chamber.The aim of this thesis is to investigate the applicability ofmachine learning methods to detect the presence of flame within a gas turbine. Traditionally,this is done using an optical flame detection which converts the infrared radiation toa differential reading, which is further converted as a digital signal to the control systemand gives the flame status (1 for flame ON and 0 for flame OFF). The primary purpose ofthis alternative flame detection method is to reduce the instrument cost per gas turbine. Amachine learning model is trained with the data collected over several runs of the turbineengine and would estimate if there is an occurrence of the flame, to decide if the machineshould be ON or OFF. To reduce the instrumentation cost, the presented flame predictionmethod based on deep learning methods is employed, which takes standard data such as dynamic pressure and temperature values as input. These variables are observed to have a high correlation with the flame status. The pressure is measured using a piezocryst sensorand the temperature is measured using a thermocouple. A Study is performed by trainingon several machine learning models and coming up with which model among them have worked the best on this data.The Logistic is used as a baseline and is compared with othermodels such as KNN,SVM,Naïve Bayes,RandomForest and XGBoost is trained with thedata collected over several runs of the turbine and tested on to predict flame status insidethe gas turbine.It was observed that KNN and Random Forest performed exceptionallywell as compared to the baseline model. It is recorded that the minimum time for estimation of the flame status by the machine is 0.6 seconds and if the model implementedcan give a high accuracy with the same time then the proposed method can be an effective alternate flame detection method.