A MICROCONTROLLER−BASED, FEEDBACK POWER CONTROL SYSTEM FOR MICROWAVE DRYING PROCESSES Z. Li, N. Wang, G. S. V. Raghavan, W. Cheng ABSTRACT. Microwave drying is an energy-efficient method, resulting in large energy savings. Microwave power and temperature of the products during drying process have significant influence on the quality of final products. To provide an automatically controlled microwave power and stabilize temperature variations during a drying process, a microcontroller-based, temperature-feedback power control system was developed. Two temperature sensors, a thermocouple probe, and an infrared sensor, were used and compared. A fiber-optic thermometer was also used for temperature calibration. Within 180 min, a carrot sample was dried to 14.63% moisture content (wet basis) and no carrot was burned. Keywords. Zero-crossing detection, Fast-switching method, Infrared temperature sensor, Automatic control, Fiber-optic thermometer.
A
s an important and widely used method for postharvest process of agricultural products, drying processes greatly improve effectiveness of food preservation, storage, and transportation. With the development of microwave technology, microwave-drying method has been introduced to food processing procedures and found advantages of higher drying rate, shorter drying time, lower energy consumption, and better quality of the dried products (Sanga et al., 2000; Mullin, 1995; Gerard and Roberts, 2004). Microwave is a high frequency electromagnetic wave with a wavelength range of 1 mm to 1 m, corresponding to a frequency range of 300 MHz to 300 GHz. When food and biological materials are exposed under microwave energy, the water molecules, which are dipoles, begin to spin at the same frequency as the electromagnetic field (Buffler, 1993). This high frequency agitation of water molecules and other mechanisms (e.g., polarization of charged ions) generates heat within the material and eventually leads to moisture evaporation. In a drying process, output power of a magnetron is one of the major factors to determine the quality of final products. Due to large variations of inherent properties, bio-products react differently under microwave. Each bio-product may need a specific power scheme, which is affected by size, quantity, moisture content, and other properties of the material. Moreover, the temperature variation of a bio-prod-
Article was submitted for review in November 2004; approved for publication by the Information & Electrical Technologies Division of ASABE in December 2005. Presented at the 2004 ASAE Annual Meeting as Paper No. 043127. The authors are Zhenfeng Li, ASABE Student Member, Ning Wang, ASABE Member Engineer, Assistant Professor, G.S.V. Raghavan, ASABE Member Engineer, Professor, and Weimin Cheng, Graduate Student, Department of Bioresource Engineering, McGill University, Quebec, Canada. Corresponding author: Ning Wang, Department of Bioresource Engineering, McGill University, Macdonald Campus 21111, Lakeshore Ave., Ste-Anne-de-Bellevue, Quebec H9X 3V9, Canada; phone: 514-398-7731; fax: 514-398-8387; e-mail:
[email protected].
uct during drying is always a critical factor for the quality of final products. To optimize drying processes, researchers have studied various microwave power control methods, including intermittent methods (integral cycle control) or continuous methods (linear resistive control). Each method provided its unique supply power profile (Venkatachalapathy and Raghavan, 2000; Cheng et al., 2005). For example, many researchers have been investigating the best ratio between the number of “ON-cycles” and the number of “OFF-cycles” within a predefined time interval for intermittent microwave operations. Changrue et al. (2004) recommended that, to achieve an efficient drying process, carrot cubes (1 cm3) should be dried under a fixed power density of 1 W/g with 70°C hot air. The power to the magnetron was manually controlled with a pattern of “55s ON and 5s OFF” and a pattern of “30s ON and 30s OFF” when the moisture content of the carrot cubes was below 30% (wet basis). Sunjka (2003) tested different pulse modes and power levels combined with mechanical and chemical pretreatment to improve cranberry drying process and found that high-quality dried cranberries could be obtained by a time-average microwave power of 1.25 W/g with a longer power-off time (30s “ON” and 45s “OFF”). Liang et al. (2003) concluded a ratio of 10s ON and 45s OFF is suitable for rose flower drying. However, there is no report emphasizing on investigating the effects of a fast-switching power control scheme with a real-time temperature monitoring capability during a drying process. In this study, a microwave power control system was developed with a temperature feedback so that the power supplied to a magnetron at each time instant was adjusted dynamically according to the temperature of the product. A fast-switching method was used incorporating with a microcontroller to form an intelligent power controller. The main objective was to evaluate the performance of the developed power control method for microwave drying process incorporating a real-time feedback temperature measurement. The secondary objective was to evaluate the effectiveness of the common temperature sensors in providing temperature feedback. Finally, drying processes were conducted to evaluate the performance of the developed control system.
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MATERIALS AND METHODS HARDWARE DESIGN A feedback, power control system (fig. 1) was developed. It consisted of a commercial microwave oven, a temperature sensor, a triac control circuit, a zero-crossing detection circuit, and a microcontroller with a keypad. The commercial microwave oven (Danby, SMC Microwave products Co., Ltd, China) with a nominal power of 950 W at a frequency of 2450 MHz was used as a test platform. To quickly exhaust moisture during dry processes, an air fan (5.88 W, 12 V) was mounted outside the cavity and close to a wind outlet. Two small holes (4 mm in diameter each) and a big hole (24 mm in diameter) were drilled on the ceiling of the cavity to guide temperature sensors. The big hole accommodated an infrared sensor, while the two small holes accommodated a thermocouple and a fiber-optic probe. All the three holes were properly sealed to prevent microwave leakage from the cavity. To achieve uniform temperature distribution, a turntable was used. Originally, the microwave oven was controlled by a power switch and a timer based on integrated cycle control method. The power level was either 100% or 0%. The microwave power was determined by a ratio between the number of ON-cycles and the number of OFF-cycles within a predefined time period. In this study, the original control circuits were modified so that the developed control system could be attached to the microwave oven. Three temperature sensors, including a thermocouple, an infrared (IR) temperature sensor, and a fiber-optic thermometer, were used to measure the temperature of products during drying. A T-type thermocouple probe with grounded sheath (HTQss-116, Omega, Stamford, Conn.) was used to measure the temperature of water during microwave heating. The thermocouple was inserted into a water sample through a small hole on the ceiling of the cavity. A signal conditioning circuit, including cold-junction compensation, signal amplification, and noise reduction, was designed to regulate the measured signal to a range of 0 to 3.93 V for a temperature range of 0 to 99°C before it can be read by the microcontroller. Only can well-grounded thermocouples be used in microwave environment. Problems may still occur when drying thin food products. The thin, pointed metal rod of the thermocouple may pick up and concentrate microwave energy in the vicinity of the probe, causing the temperature around the probe to be greater than that in the body of the food itself. Moreover, if the metal probe is left in an empty oven or in a very dry sample, metal-to-metal arcing may occur between the probe and the cavity wall, or even between different layers of the probe itself. Hence, thermocouple is not an ideal sensor used in microwave environment in comparison with non-metal sensors. A low-cost infrared temperature sensor (OS100, Omega, Stamford, Conn.) was used to nondestructively measure the temperature of test samples. The IR sensor was mounted outside of the big hole on the ceiling of the cavity. The distance between the sensor and measured samples was 16 cm. The field of view was 2.6 cm in diameter. The output voltage range of the sensor was 0.16 to 1.05 V for the temperature range of 0 to 99°C. A signal conditioning circuit was designed to amplify the signal to 0 to 3.93 V to achieve a higher resolution for the A/D conversion. The circuit can
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Zero−crossing Detector
Keypad Microcontroller 68HC11
Temperature Sensor
PC
Triac Control
Transformer to the magnetron
Figure 1. Block diagram of the feedback, power control system.
also be used to adjust the signal difference of infrared sensor due to different emissivity of different products. A fluorescence fiber-optical thermometer (755 FluoropiticR, Luxtron Corp., Santa Clara, Calif.) was used to provide calibration temperatures. This thermometer has an absolute accuracy of ±0.5°C. The fiber-optic probe was inserted to the test products through the small holes on the ceiling of the cavity. The temperature readings were recorded on-line by a computer through an RS-232 port. A power triac (fast power switch) (Q4025L6, 25A, Teccor Electronics, Irving, Tex.) was used to control the AC source (110 V, 60 Hz) to a high-voltage transformer in order to control the magnetron based on a phase-control principle. The triac was in series with the primary coil (the low-voltage side) of the high-voltage transformer. A zero-crossing detection circuit was developed to provide a trigger signal to the microcontroller for phase-control. The circuit consisted of a current limiter, a full-wave rectifier, and an opto-coupled Schmitt Trigger. Its output signal was a pulse with a width of 720 µs. Figure 2 shows the concept of phase control. A single-board development system for Motorola 68HC11 microcontroller (CME11E9-EVBU, Axiom Manufacturing, Tex.) formed the core of the microwave power control system. The main functions included 1) collecting the temperature data from a temperature sensor, reading a user-preset temperature from a keypad, 2) collecting a trigger signal from the zero-crossing circuit, 3) calculating the conduction angle based on the measured temperature and preset temperature, 4) outputting a square wave to control the conduction time of the power triac in order to control the power level to the high-voltage transformer, and 5) communicating with a personal computer (PC) for programming, debugging, and data uploading. The 68HC11 is a powerful 8-bit data, 16-bit address microcontroller. It has built-in EEPROM, RAM, digital I/O, timers, A/D converter, PWM generator, and synchronous and
Figure 2. The concept of phase control (Courtesy: Teccor Electronics Inc.).
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asynchronous (RS-232) communication channels. An analog input channel collect temperature data from the temperature sensors (thermocouple or IR temperature sensor). Four channels of a digital I/O port were used to collect the keypad readings of the user-preset temperature. Two channels of another digital I/O port read falling edges of trigger pulses from the zero-crossing detection circuit and output a square-wave to control the conduction of the power triac, respectively. The duty cycle of the square wave was determined by the calculated conduction angle. This square wave was sent to an opto-isolator, which turned on the triac when the signal was “HIGH.” This opto-isolator protected the microcontroller and allowed switching of highly inductive loads, such as the transformer, through triac. A PC was connected to the 68HC11 through a serial communication module (RS-232) to download program, upload data, and debug the program. Thus, the PC is not an essential part of the system, and the system can operate normally without the PC. SOFTWARE DESIGN The system software included a program for data acquisition and preprocessing, a program to calculate the triggering angle, and a program to generate a control waveform for the power triac. All programs were written in assembly language for Motorola 68HC11 (Greenfield, 1992), compiled and debugged using the Buffalo Development Tools (Axiom Manufacturing, Garland, Tex.), and were running on the 68HC11 microcontroller. At every zero-crossing point of the AC power source (two points in every cycle), a falling edge generated by the zero-crossing circuit was detected by the 68HC11. This falling edge triggered a data reading from the temperature sensor (thermocouple or IR sensor). Because the AC power source signal had a frequency of 60 Hz, 120 temperature readings were collected within a second. The maximum value among the 120 readings was selected to calculate the triggering angle for triac control. This triggering angle was updated every second. The triggering angle, in second, was calculated (eq. 1) based on the capacity of the oven, the user-preset temperature (temp 0), and the measured temperature (temp1), when temp0 is higher than tepm1. If temp0 is lower than or equal to temp1, the triggering angle will be 0.
Triggering Angle = k × (temp0 − temp1 ) + c
(1)
where k and c are constants that depended on the capacity of microwave ovens (k = 5, c = 80 in this study). The 68HC11 generated a square wave based on the calculated triggering angle to switch the triac (fig. 3). The period of the square wave was the same as the AC source (16.7 ms). The calculated triggering angle determined the time of “LOW” (or 0) within a period. The triac conducted only when the output wave was in the “HIGH” (or 1) stage. SYSTEM TESTS Figure 4 shows a test setup using the IR sensor to provide the feedback temperature signal and the fiber-optic thermometer to provide a calibration temperature to examine the control performance. Tap water in a plastic container was used to evaluate the performance of the developed system and to compare the results from the system with two different temperature
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Figure 3. The triac conduction control using a square wave.
sensors (a thermocouple and an IR sensor). Then carrots of unknown cultivar were used to evaluate drying processes with the developed system. Carrots were cut into 1-cm3 cubes. These cubes were placed on a plastic sample tray, forming a single layer. The total weight of carrot cubes within a sample was 200 ± 5 g. The bulk weight in each carrot sample was measured every 10 min for 1.5 h by removing the sample from the cavity. The sample was placed back in the microwave oven within 1 min for further drying. A non-interference weight measurement was not applied. Three sets of tests were conducted to evaluate the performance of the power control system. In Test 1, the thermocouple probe was used as a temperature feedback sensor to measure the temperature of a water sample inside the cavity of the microwave oven. A fiber-optical temperature probe was used to calibrate and verify the temperature control effects. The tips of both probes were close to each other. Various target temperatures ranging from 35°C to 85°C with 10°C intervals were preset using the keypad. The temperature readings were acquired repeatedly based on time and the maximum error was calculated according to the user-defined temperature, which was used to evaluate the performance of the system. The test was repeated three times and the mean data set was presented. Test 2 followed the same procedures of Test 1, but used the IR sensor to measure water temperature as a feedback signal. The emissivity is 0.95 to 0.96 for water and about 0.90 for carrots. Effectiveness of the temperature controls using the thermocouple and the IR sensor were compared.
Figure 4. A test setup for the feedback power control system.
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The maximum error to the user-defined temperature was ±6°C. The error was introduced by the electrical discharging, signal perturbations, and extensive shield heating of the thermocouple (Ramaswamy et al., 1991). Large oscillation was observed in the controlled temperature with a preset temperature of 85°C. At this temperature, many bubbles were generated, resulting in non-uniformity of temperature distribution within the water sample.
Test 3 was to evaluate the microwave drying process for carrots. The IR sensor was used to monitor the temperature of a carrot sample and feedback the measurement to the controller. A turntable was used to achieve a uniform temperature distribution. Surface color of dried carrot samples were measured in terms of L*, a*, and b* using a chromameter (CR-300, Minolta Camera Co. Ltd., Japan). The results were compared with those dried with a microwave control system using a forced airflow system based on a study of Changrue et al. (2004).
TEST 2 - THE TEMPERATURE CONTROL IN A WATER SAMPLE USING IR SENSOR Figure 6 shows the temperature control in a water sample using the IR sensor to provide the feedback temperature signal. The preset temperatures were also reached within 5 min. The maximum error was ±1.5°C. The control accuracy of the IR sensor was much better than that of the thermocouple. The IR sensor measurement was not influenced by the EM field and could measure the average temperature of the
RESULTS AND DISCUSSION TEST 1 - TEMPERATURE CONTROL IN A WITH THE THERMOCOUPLE PROBE
WATER SAMPLE
Figure 5 shows the temperature control results for the water sample using the thermocouple probe to provide the feedback temperature. The preset temperature for each test was marked in the figure. All the preset temperatures were reached within 6 min. 100 90
Preset 85°C
Temperature(degree)
80 Preset 75°C
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Preset 65°C
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Preset 55°C
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Preset 45°C
40 Preset 35°C
30 20 10 0 0
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Time(s) Figure 5. Temperature control curves using the thermocouple probe.
100 90 Preset 80°C
Temperature(degree)
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Preset 60°C
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Time(s) Figure 6. Temperature control curves using the IR sensor.
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surface within the field of view. Therefore, it was able to filter out the temperature variations to provide a more stable feedback control signal. With its non-destructive nature, the IR sensor could be a good candidate to be used for temperature monitoring under a microwave environment. TEST 3 - PERFORMANCE OF THE DRYING PROCESS USING THE FEEDBACK POWER CONTROL SYSTEM Figure 7 shows a carrot sample before and after drying for 180 min. Based on the data provided by Techasena et al. (1992), the preset drying temperature was set at 70°C. The drying curve is showed in figure 8. Within 180 min, the carrot sample was dried from 83.10% to 14.63% moisture content (wet basis). During the drying process, less than 2% of the carrot cubes were partially or completely burned. The drying rate was slower than that of the microwave drying system with the forced airflow system, which achieved 12% moisture ratio within 90 min (Changrue et al., 2004). Although the existing test setup did not install the forced airflow system, the developed control system could be easily attached a balance to record weight of sample in a real-time fashion. The surface color of dried carrots was obviously lighter (L* [ 46.30) than those (L* < 11.00) dried with a microwave system with forced airflow system (Changrue et al., 2004). To achieve an optimum drying effect, a uniform temperature distribution inside the cavity of a microwave oven was needed. Although it could help maintain the uniformity, a turntable was difficult to work with contact temperature
(a)
Figure 8. Drying curve of the carrot sample.
sensors when the sample was moving. The infrared sensor could collaborate with the turntable owing to its non-contact nature. The disadvantage of the infrared sensor is its weak penetration capability. It can only measure the surface temperature. Further study needs to be conducted to model heat distributions within the products, from the center to the surface. The feedback control system will then be based on these models to determine optimal control strategies for every product to achieve the best drying effect. In this study, three temperature sensors were used: a thermocouple probe with grounded sheath, a fiber-optic thermometer, and an infrared sensor. Each sensor has its pros and cons. The thermocouple probe is inexpensive, accurate, but easy to cause sparks in the microwave oven. The fiber-optic thermometer is very accurate, stable, but very costly. Both the thermocouple probe and the fiber-optic probe are contact-type sensors. They are difficult to use when a turntable is needed in the microwave oven. The major advantage of the infrared sensor is its non-contact nature. IR sensors are relatively cheap and accurate, and they can be used with a turntable. Although an IR sensor only measures the surface temperature, it still can be used for feedback temperature control in the microwave environment by combining modeling techniques and software corrections.
CONCLUSIONS
(b) Figure 7. A carrot sample (a) before drying (b) after drying for 180 min.
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Overall performance of the power control system for the microwave oven was within the design criteria. The zerocrossing detection circuit detected the zero points of sine waves successfully. The TRIAC could be controlled by a digital output signal of the microcontroller, which was used as its gate trigger signal and could successfully turn on and off the line power for the microwave oven. Two temperature sensors, a thermocouple probe and an IR sensor were tested with the control system, respectively. The IR sensor demonstrated its advantages as a non-contact measurement device. The system software completely fulfilled the design objectives. Employing the thermocouple probe and the IR sensor to provide feedback control signal, the system was tested with water samples. For the temperature controls, the maximum
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errors to the target temperature were ±6°C and ±1.5°C, when using the thermocouple probe and the IR sensor to provide feedback temperature readings, respectively. The control system was also tested with carrot samples using the IR sensor to monitor temperature variations of the sample. The carrot samples lost 85.37% of their water content in 180 min with no sign of damage due to burning. The color of the dried samples was better than those dried with a microwave system with a forced, airflow system.
REFERENCES Buffler, C. R. 1993. Microwave Cooking and Processing. New York: Van Nostrand Reinhold. Changrue, V., P. S. Sunjka, Y. Gariepy, G. S. V. Raghavan, and N. Wang. 2004. Real-time control of microwave drying process. The Proceedings of The 14 th International Drying Symposium. Sao Paulo, Brazil. DTF/FEQ/Unicamp, ISBN: 85-904573-1-1. Vol. B: 941-948. Cheng, W. M., G. S. V. Raghavan, M. Ngadi, and N. Wang. 2005. Microwave power control strategies on the drying process. Development and evaluation of new microwave drying system. Journal of Food Engineering In press and available on-line. http://www.sciencedirect.com/science/journal/02608774. Gerard, K. A., and J. S. Roberts, 2004. Microwave heating of apple mash to improve juice yield and quality. Lebensmittel-Wissenschaft und-Technologie 37(5): 551-557.
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Greenfield, J. D. 1992. The 68HC11 Microcontroller. Fort Worth, Tex.: Saunders College Publisher. Liang L., Z. Mao, and T. Cheng. 2003. Study on the Application of Freeze Drying and Microwave Drying to Flowers. ASAE Paper No. 036075. St. Joseph, Mich.: ASAE. Mullin, J. 1995. Microwave processing. New Methods of Food Preservation, 120-121. London, UK: Blachie Academic & Professional. Ramaswamy, H. S., F. R. Van de Voort, G. S. V. Raghavan, D. Lightfoot, and G. Timbers. 1991. Feedback temperature control system for microwave ovens using a shielded thermocouple. J. of Food Science 56(2): 550-552. Sanga, E., A. S. Mujumdar, and G. S. V. Raghavan. 2000. Principles and application of microwave drying. In Drying Technology in Agriculture and Food Sciences. Enfield, N.H.: Oxford and IBH Publishing Inc. Sunjka, P. S. 2003. Microwave/vacuum and osmotic drying of cranberries. MSc. thesis. Montreal, Canada: McGill University , Department of Agricultural and Biosystems Engineering. Techasena, O., A. Lebert, and J. J. Bimbenet. 1992. Simulation of deep bed drying of carrots. J. of Food Engineering 16(4): 267-281. Venkatachalapathy, K., and G. S. V. Raghavan. 2000. Microwave drying of whole, sliced and pureed strawberries. International Agricultural Engineering Journal 9(1): 29-39.
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