Name: Thermal Behavior and Power Efficiency Comparison of AC vs. DC Electrical Heating in a Distillation Column Using Infrared Thermography Analysis (Video) | JoVE Journal
Uploaded: 2025-12-05T14:05:00.000+00:00
Duration: 6 min 21 s
Description: Learn thermal behavior analysis in distillation columns using infrared thermography to compare AC and DC power efficiency. This method helps optimize heating performance and reduce energy costs.

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The authors thank the TecNM postgraduate program for providing its laboratories during testing, as well as the funding provided by Secihti and TecNM.

1. Configuration and procedures for mixture preparation, process execution from the local interface, and power supply startup
<ol>
	<li>Preparation of the mixture to be used in the process inside the boiler (Figure 1).
	<ol>
		<li>Place 1 L of ethanol and 1 L of distilled water in separate flasks.</li>
		<li>Place the contents of each flask inside the plate boiler plate.</li>
		<li>Ensure the instrumentation is correctly positioned.
		<ol>
			<li>Check the hose connections on the condenser from the cooling water pump.</li>
			<li>Check the placement of the sensors on the plates of the distillation column body.</li>
			<li>Check the conditions of the cooling water pump actuators, heating resistor, and reflux actuator.</li>
		</ol>
		</li>
	</ol>
	</li>
	<li>Execute the local interface on the PC and data acquisition card (Figure 2).
	<ol>
		<li>On the local PC, open the &#34;distillation column&#34; software.</li>
		<li>Connect the data acquisition card to the local PC.</li>
		<li>Verify communication between the data acquisition card and the local PC.
		<ol>
			<li>Validate the items in the pop-up window.</li>
		</ol>
		</li>
		<li>Select the mixture to be used in the local interface.</li>
		<li>Start the process from the local interface by clicking the Start button.
		<ol>
			<li>Verify receipt of information from local sensors in each of the interface windows on the local PC. 
			NOTE: Although the experiment is limited to a binary mixture of ethanol and water, the interface allows for the observation of different mixtures. Since heat transfer between the RTD and the liquid depends on general thermal properties such as heat capacity and conductivity, it can be assumed that the methodology employed, which relies on experimental data to define thermal behavior, is valid for other mixtures under controlled conditions. This approach is supported by studies on distillation columns that dynamically model ideal binary mixtures9,10,11.</li>
		</ol>
		</li>
	</ol>
	</li>
	<li>Preparing for AC or DC power supplies to power the heating resistor.
	<ol>
		<li>Using a multimeter as a voltmeter, set the output voltage value from the front panel of the power supply, as appropriate (AC or DC). Once configured, turn off the power supply.</li>
		<li>Connect the voltage supply to the resistance thermometer installed in the boiler plate.</li>
		<li>Energize the heating resistor by turning on the power supply.</li>
		<li>Verify current and voltage monitoring from the local interface. 
		NOTE: Table 1 indicates the voltage and current values used for the experiment for both AC and DC.</li>
	</ol>
	</li>
</ol>
2. Setup, acquisition, and analysis of thermograms and temperature data on the in-process boiler plate
<ol>
	<li>Setup and acquisition of thermograms using the in-process boiler plate thermal camera. 
	NOTE: For the experiment, operating hours and measurements were performed from 1 to 3 PM, when the ambient temperature inside the laboratory was 22&#176; to 24.5 &#176;C.
	<ol>
		<li>Select the Iron color palette from the thermal camera menu.</li>
		<li>Set the emissivity correction value to 0.95 from the thermal camera menu. 
		NOTE: The camera can be self-calibrated and is periodically calibrated by trained personnel. The emissivity value is selected based on the roughness, thickness, and transparency characteristics of the glass that makes up the boiler tank. Therefore, an emissivity value of 0.95 was considered for the thermal measurement13. Since the difference is minimal, the impact on the temperature estimate is negligible within the experiment&#39;s operating range.</li>
		<li>Position the thermal camera approximately 80 cm away from the boiler plate. 
		NOTE: The measurement in 2.1.3 was considered based on the camera&#39;s minimum operating distance (0.6 m) due to its resolution (140 x 140 pixels) and field of view (29&#176; x 29&#176;)12, therefore, the distance used allows capturing relevant thermal details without compromising the pressure measurement on the boiler plate.</li>
		<li>Holding the thermal camera approximately 60 cm above the floor, locate the camera pointing toward the boiler plate in the distillation column. 
		NOTE: The measurement in 2.1.4 was selected based on the height of the plate boiler.</li>
		<li>Press the save button to record the thermogram to the thermal camera&#39;s memory. 
		NOTE: Because the transient state is slower depending on the decrease in the supply voltage applied to the heating resistor, the action in step 2.1.5. can be performed at 20 to 30, 50, or 60 s for 20 V (AC and DC).
		<ol>
			<li>Capture every 5 s during samples 1 to 1500 indicated on the local interface, repeat for 20, 60, and 100 V for both AC and DC.</li>
			<li>For 100 V (AC and DC), capture every 10 s during samples 1500 to 2800 indicated on the local interface, for 20 V (AC and DC), capture during the sample interval 1500 to 5500, and for 60 V (AC and DC), capture every 15 s during samples 1500 to 4000.</li>
			<li>For 100 V (AC and DC), capture every 20 s from sample 2800 until steady state is reached, for 60 V (AC and DC), capture every 30 s from sample 4000 until steady state is reached, and for 20 V (AC and DC), capture every 20 s from sample 5500 until steady state is reached.</li>
		</ol>
		</li>
		<li>Record the name of the captured thermogram and the value of the boiler plate temperature sample displayed in the local interface.</li>
	</ol>
	</li>
	<li>Acquisition of boiler plate temperature data through the local process interface. 
	NOTE: Figure 3D,E show the process mentioned in 2.2 in detail.
	<ol>
		<li>Store the temporary files generated by the interface.</li>
		<li>Rename and save the files in the current process folder.</li>
		<li>Collect the .csv files generated during the test and generate a single file with all the data obtained from the process. 
		NOTE: The interface stores process data every 1020 samples, which is equivalent to one section of the process. These are temporary files that must be stored for later processing. 0.5 s is the sampling time for each sample. The saved numerical data corresponds to the dynamic behavior of the process generated by a temperature sensor measuring the vapor inside the boiler.</li>
	</ol>
	</li>
	<li>Preparation of boiler plate temperature data and captured process thermograms. 
	NOTE: Figures 3A,B,C,F,G show the process mentioned in 2.3.
	<ol>
		<li>Extract thermograms from the thermal camera. 
		NOTE: The thermograms show the temperature distribution resulting from the RTD heating according to the voltage used.</li>
		<li>Review the thermograms and discard any unwanted ones.</li>
		<li>Manually mark a reference point on the thermograms.</li>
		<li>Create the process temperature overview graph using the process data file generated in 2.2.3.</li>
		<li>Relate the boiler temperature data from the local interface to the captured process thermograms.</li>
	</ol>
	</li>
</ol>
3. Analysis and processing of thermograms for the boiler plate process
<ol>
	<li>Development of an algorithm for thermogram processing.
	<ol>
		<li>Preparation of graphs for visualizing average trends.
		<ol>
			<li>Load the image into a variable.</li>
			<li>Define the size of the vectors for the graph axes, using the image variable.</li>
			<li>Define the area for detecting minimum and maximum temperature ranges based on the analysis image.</li>
			<li>Prepare the figure for graphing.</li>
		</ol>
		</li>
	</ol>
	</li>
	<li>Processing thermograms (Figure 4).
	<ol>
		<li>Load the image into a variable.</li>
		<li>Define a search area for the reference point marked in 2.3.3.</li>
		<li>Isolate the reference point and obtain its coordinate.</li>
		<li>Indicate the analysis area using the coordinates in 3.2.3.</li>
		<li>Convert the analysis area to grayscale.</li>
		<li>Calculate the mean of the area defined by 3.2.5.</li>
		<li>Isolate the maximum and minimum temperature areas in the image.</li>
		<li>Convert the graphical numbers to numeric text.</li>
		<li>Convert the mean values to scaled maximum and minimum temperatures according to the image ranges.</li>
		<li>Store the total mean values and labels.</li>
		<li>Plot the total mean results.</li>
	</ol>
	</li>
</ol>

<ol><li>Heras-Cervantes, M., Anzurez-Marin, J., Téllez-Anguiano, A. D. C., García-Ramírez, M., Correa-Gómez, J. Modelling a heating-power actuator for a distillation column boiler. <a target="_blank" href="http://scholar.google.com/scholar?hl=en&safe=off&q=author%3aHeras-Cervantes%2C+M+%22IEEE+Int.+Autumn+Meet.+Power+Electron.+Comput.+%28ROPEC%29%22">IEEE Int. Autumn Meet. Power Electron. Comput. (ROPEC)</a>. , https://www.proceedings.com/content/033/033329webtoc.pdf (2016).</li>
<li>Mendoza, D. F., Riascos, C. A. M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Methodology+for+design%2C+analysis+and+thermodynamic+optimization+of+distillation+columns+with+internal+heat+exchangers%5BTitle%5D)+AND+%22Rev.+Mex.+Ing.+Qu%C3%ADm%22%5BJournal%5D)">Methodology for design, analysis and thermodynamic optimization of distillation columns with internal heat exchangers.</a> Rev. Mex. Ing. Quím. 14 (2), 523-542 (2015).</li>
<li>Cervantes Vallejo, F., Gómez, K., Soto, G., Navarro, C., Mendoza, H. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Optimization+of+the+heating+system+by+electrical+resistances+in+a+rapid+thermal+response+mold+based+on+MSR-PSO-FEM%5BTitle%5D)+AND+%22Rev.+Int.+M%C3%A9tod.+Num%C3%A9r.+C%C3%A1lc.+Dis.+Ing%22%5BJournal%5D)">Optimization of the heating system by electrical resistances in a rapid thermal response mold based on MSR-PSO-FEM.</a> Rev. Int. Métod. Numér. Cálc. Dis. Ing. 35 (3), 1-12 (2019).</li>
<li>Demurie, S. N., De Mey, G. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Parasitic+capacitance+effects+of+planar+resistors%5BTitle%5D)+AND+%22IEEE+Trans.+Compon.+Hybrids+Manuf.+Technol%22%5BJournal%5D)">Parasitic capacitance effects of planar resistors.</a> IEEE Trans. Compon. Hybrids Manuf. Technol. 12 (3), 348-351 (2002).</li>
<li>Calor y Control. <a target="_blank" href="http://scholar.google.com/scholar?hl=en&safe=off&q=%22Tendencias+tecnol%C3%B3gicas+en+las+resistencias+el%C3%A9ctricas+industriales%22">Tendencias tecnológicas en las resistencias eléctricas industriales</a>. , Calor y Control. (2025).</li>
<li>Arneth, S., Stichlmair, J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Characteristics+of+thermosiphon+reboilers%5BTitle%5D)+AND+%22Int.+J.+Therm.+Sci%22%5BJournal%5D)">Characteristics of thermosiphon reboilers.</a> Int. J. Therm. Sci. 40 (4), 385-391 (2001).</li>
<li>Pinto, F. S., Zemp, R., Jobson, M., Smith, R. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Thermodynamic+optimisation+of+distillation+columns%5BTitle%5D)+AND+%22Chem.+Eng.+Sci%22%5BJournal%5D)">Thermodynamic optimisation of distillation columns.</a> Chem. Eng. Sci. 66 (13), 2920-2934 (2011).</li>
<li>Goedecke, R., Scholl, S. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Modelling+and+simulation+of+a+pillow+plate+thermosiphon+reboiler%5BTitle%5D)+AND+%22Heat+Mass+Transf%22%5BJournal%5D)">Modelling and simulation of a pillow plate thermosiphon reboiler.</a> Heat Mass Transf. 55 (1), 95-104 (2019).</li>
<li>Melkikh, A., Skripov, P. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Thermal+conductivity+of+liquid+mixtures%3A+Model+of+the+dependence+on+concentration%5BTitle%5D)+AND+%22Int.+J.+Thermophys%22%5BJournal%5D)">Thermal conductivity of liquid mixtures: Model of the dependence on concentration.</a> Int. J. Thermophys. 44 (2), 23(2023).</li>
<li>Mancera-Apolinar, J. A., Mendoza, D. F., Andersson, R., Riascos, C. A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Heat+and+mass+transfer+study+of+top-heat-integrated+distillation+column+%28T-HIDiC%29+using+CFD%5BTitle%5D)+AND+%22Chem.+Eng.+Trans%22%5BJournal%5D)">Heat and mass transfer study of top-heat-integrated distillation column (T-HIDiC) using CFD.</a> Chem. Eng. Trans. 117, 871-876 (2025).</li>
<li>Ränger, L. M., Halvorsen, I. J., Grützner, T., Skogestad, S. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Understanding+temperature+profiles+of+distillation+columns%5BTitle%5D)+AND+%22Ind.+Eng.+Chem.+Res%22%5BJournal%5D)">Understanding temperature profiles of distillation columns.</a> Ind. Eng. Chem. Res. 63 (10), 4533-4546 (2024).</li>
<li>de Azpeitia, F. I. P. P. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((The+thermographic+camera%3A+A+fascinating+view+of+physics%5BTitle%5D)+AND+%22Rev.+Esp.+F%C3%ADs%22%5BJournal%5D)">The thermographic camera: A fascinating view of physics.</a> Rev. Esp. Fís. 35 (2), (2021).</li>
<li>Emissivity of common surfaces. , Fluke Process Instruments. 
 <a target="_blank" href="https://www.flukeprocessinstruments.com/es/servicio-y-soporte/centro-de-conocimiento/ir/emisividad-superficies-comunes">https://www.flukeprocessinstruments.com/es/servicio-y-soporte/centro-de-conocimiento/ir/emisividad-superficies-comunes</a> (2025).</li>
</ol>

The authors have nothing to disclose.

The procedure presented provides a general idea of the importance of correctly selecting the feed for a chemical process such as a distillation column; however, the process has some critical points that must be addressed with great care to avoid unfavorable results.
When capturing thermograms, it is important to consider using a tripod to locate the camera. This prevents accidental movement while capturing thermograms.
Files generated by the local interface must be ...

Heat exchange systems are fundamental devices in chemical engineering, used to facilitate the transfer of thermal energy between two process streams, even without direct physical contact. Their incorporation into equipment such as distillation columns allows for optimizing energy consumption, improving component separation efficiency, and maintaining stable operating conditions through precise control of temperature profiles1.
A power actuator in a distillation column is considered a heat exchange system, composed of an electrical resistance that, in both direct current (DC) and alternating current (AC), obeys Ohm&#39;s law, establishing a direct relationship between voltage, current, and resistance. However, the behavior of the resistor when using AC is more complex due to the influence of frequency, impedance, and the inductive and capacitive effects of the system. However, it offers certain advantages in specific industrial applications2,3.
The behavior of a real resistor differs from its ideal because physical materials can induce phenomena such as parasitic inductance and, in certain cases, parasitic capacitance4. These effects depend on the AC signal frequency, being distinguished in terms of frequency values. In one case, the reactive effects (inductive or capacitive) are practically negligible; therefore, the resistor behaves linearly and obeys Ohm&#39;s law almost perfectly. Thus, its response is comparable to that of an ideal resistor used in DC, when considering low frequencies.
For high frequencies, the actual resistance begins to exhibit an inductive component, especially if its construction includes elements such as windings or long connections5. The improper use of electrical resistors in distillation processes can cause thermal shocks in the column boiler, especially when the equilibrium of the thermosiphon effect is altered, a phenomenon that occurs due to the interaction between heat transfer and the natural flow of the liquid induced by density differences6.
The heat transfer rate in the boiler is determined by the effective length of the heating and evaporation zones, as well as by the geometric design of the exchanger7. Furthermore, this rate depends significantly on the operating pressure and vapor content, since the heat transfer coefficient in the evaporation zone is considerably higher than in the preheating zone8.
This work proposes a comparative study between AC and DC power supplies to feed a heating resistor inside a distillation column, evaluating their impact on the thermal efficiency of the process, temperature profile in the boiler, energy consumption, and stability during the distillation cycle. The main characteristics of the plant are: a 2 L boiler plate, a 300 W heating resistor, bottom product extraction, a double spiral condenser, a L reservoir tank for distilled products, and on-off reflux valve.

<table><tbody><tr><td>Camera</td><td>FLIR</td><td>i7</td><td>Thermogram capture equipment</td></tr><tr><td>Distillation pilot plant</td><td></td><td>EDF-1000</td><td>Distillation pilot plant</td></tr><tr><td>Distilled water</td><td>Tecnologia y control ambiental</td><td>CAS-7732-18-5</td><td>Mixture component</td></tr><tr><td>Ethanol</td><td>JR</td><td></td><td>Mixture component</td></tr><tr><td>Multimeter&amp;nbsp;</td><td>FLUKE</td><td></td><td>Measuring equipment</td></tr><tr><td>NI myRIO</td><td>National Instruments</td><td>1900</td><td>Data acquisition card</td></tr><tr><td>Power supply</td><td></td><td>SPS1203</td><td>DC Power Supply Voltage&amp;nbsp;</td></tr><tr><td>Python</td><td></td><td>3.12</td><td>Software for image processing</td></tr><tr><td>Temperature sensor</td><td></td><td>PT100</td><td>Sensors installed in the plant for direct temperature measurement on some process plates.</td></tr><tr><td>Thermal resistance</td><td>Sunny</td><td>SGH-380</td><td>73 ohm value</td></tr></tbody></table>

thermal behavior and power efficiency comparison of ac vs. dc electrical heating in a distillation column using infrared thermography analysis

Thermal Behavior and Power Efficiency Comparison of AC vs. DC Electrical Heating in a Distillation Column Using Infrared Thermography Analysis

Infrared thermography (IRT) is a widely used non-contact technique for quantifying thermal performance in industrial heating systems. This study employs IRT to analyze and compare the thermal behavior and electrical power efficiency of a heating resistor within a distillation column boiler under alternating current (AC) and direct current (DC) power supply. Experiments were conducted using a distillation pilot plant, which included a 130 W heating resistor powered by an AC (60 Hz) source and an equivalent DC source considering different voltage-current configurations. Thermal dynamics were captured using a calibrated mid-wave IR camera (7.5 to 13 &#181;m spectral range), in parallel with electrical power measurements from a data-acquisition card embedded system.
The proposed methodology establishes an IRT protocol for quantifying thermal responses via IRT images, allowing for mapping 2D temperature heterogeneity through emissivity-corrected thermograms.
Power efficiency analyses showed DC reduced Joule losses while AC exhibited superior thermal stability during prolonged operation. This IRT-integrated approach provides actionable insights for optimizing distillation energy systems and aligns with industrial electrification initiatives. The protocol is scalable for infrared-based monitoring of thermo-electric processes in chemical, pharmaceutical, and renewable energy applications.

The results are from six tests developed with the values mentioned in Table 1. Thermal information was considered for the analysis, as well as data obtained through the local interface.
Comparative analysis for a 100 V AC-DC supply voltage 
The data obtained from the process using the local interface indicated that for a DC power supply, the temperature measurement varies throughout the process, while using AC (Figure 5A), the ...

This article presents a comparative study on the thermal behavior and energy efficiency of a heating element within a distillation column boiler, powered by alternating current (AC) and direct current (DC), evaluating its performance from statistical results such as minimum and maximum temperature, the mean of the thermal data and the coefficient of variation.

Infrared thermography (IRT) is a widely used non-contact technique for quantifying thermal performance in industrial heating systems. This study employs ...

The scope of my research is to demonstrate advantage of using AC and DC power supply in a heating element within a distillation column boiler. Recent studies address thermographic analysis in AC/DC powered distillation column separately, but no work combined both approaches. To begin, set up the thermal camera for acquisition.Select the iron color palette from the thermal camera menu, and ensure it is correctly applied before proceeding. Set the emissivity correction value to 0.95 from the thermal camera menu. Then position the thermal camera approximately 80 centimeters away from the boilerplate.Holding the thermal camera approximately 60 centimeters above the floor, orient the camera toward the boilerplate in the distillation column. Press the save button to record the thermogram to the thermal camera memory. Capture thermograms every five seconds during samples one to 1, 500 on the local interface.Repeat the acquisition for 20, 60, and 100 volts under alternating current and direct current conditions. Record the name of each captured thermogram and the corresponding boilerplate temperature sample displayed on the local interface. To begin acquisition of boilerplate temperature data, store the temporary files generated by the local process interface.Rename and save the stored files into the current process folder. Collect the CSV files generated during the test, and generate a single file containing all acquired process data. Save the consolidated file for analysis.To begin preparation of the data, extract thermograms from the thermal camera. Transfer all image files to the analysis workstation. Review the extracted thermograms and discard any unwanted images.Manually mark a reference point on each thermogram. Then create a process temperature overview graph using the previously generated process data file. Relate the boiler temperature data from the local interface to the captured process thermograms.To develop an algorithm for thermogram processing, first load an image into a variable within the analysis environment. Define the size of the vectors for the graph axes using the image variable. Then, define the area for detecting minimum and maximum temperature ranges based on the analysis image.Prepare the figure for graphing. Next, load the thermogram image into a variable for processing. Define a search area for the previously marked reference point.Isolate the reference point and obtain its coordinates. Then, use the coordinates to indicate the analysis area. Now, convert the analysis area to grayscale.Calculate the mean temperature value of the grayscale area. Isolate the maximum and minimum temperature areas in the image. Convert the graphical numbers to numeric text.Convert the mean values to scaled maximum and minimum temperatures according to the image ranges, and store the total mean values and corresponding labels. Lastly, plot the total mean results to visualize the processed thermogram data. The temperature measurements using 100 volt DC varied throughout the process, while the measurements using 100 volt AC remained more stable.At 100 volt DC, thermal variation across the boiler section was higher than with alternating current. DC presented more controlled areas due to smoother progression and increasing, but not abrupt dispersion. Under 60 volt conditions, temperature measurements were more stable with AC.Thermal evolution using 60 volt AC showed a gradual temperature increase during startup, whereas with 60 volt DC, the heating was more pronounced and rapid.The graphical temperature trend at 20 volts showed noticeable variation for DC, while AC resulted in a more gradual and stable profile. Thermograms under 20 volt AC showed temperatures ranging from 22.8 degrees Celsius to 26.3 degrees Celsius. Our protocol used TIR analysis to provide a clearer view of the thermal behavior in relation to power source within the process.Our findings show that selecting appropriate AC or DC supply optimizes performance, reduce energy costs, and improve distillation quality. Future research will investigate thermogram bases thoroughly for detection methods, and how thermal actuator fatigue influences process transient behavior.

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Learn thermal behavior analysis in distillation columns using infrared thermography to compare AC and DC power efficiency. This method helps optimize heating performance and reduce energy costs.

Thermal Behavior and Power Efficiency Comparison of AC vs. DC Electrical Heating in a Distillation Column Using Infrared Thermography Analysis (Video) | JoVE Journal

Thermal Behavior and Power Efficiency Comparison of AC vs. DC Electrical Heating in a Distillation Column Using Infrared Thermography Analysis

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