Multimode cavity efficiency optimization by optimum load location-experimental approach

Requena-Perez, M.E.; Pedreño-Molina, J.L.; Monzó‐Cabrera, Juan; Díaz‐Morcillo, Alejandro

doi:10.1109/tmtt.2005.848767

Cited by 20 publications

(12 citation statements)

References 7 publications

(7 reference statements)

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“…6, the point where the reflection coefficient is high). This situation can be shown by means of (23), which has already expressed the power efficiency [2].…”

Section: Numerical Resultsmentioning

confidence: 99%

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Analysis of Microwave Cavity Loaded With Lossy Dielectric Slab by Means of Mode Matching Method and Optimization of Load Location

Süle

Kent²

2010

PIER M

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Abstract-An analysis is presented by means of a mode matching method for two microwave cavities of different sizes which are fed by a TE 10 waveguide and loaded with lossy dielectric slab type material. The accuracy of the results obtained is presented together with a comparison of the results which are obtained by the HFSS numerical method. Optimization of the load location was performed in order to maximize the electrical field on the material. The principle of this optimization is based on finding the existence of the positions in which the reflection coefficient S 11 is the lowest. When the feeding guide for the two different microwave cavities was at the centre of the resonator, the change in the reflection coefficient distribution was detected according to the different positions of the material in the oven, and then the lowest positions were found. The changes in the electric field in the detected positions were recorded.

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“…6, the point where the reflection coefficient is high). This situation can be shown by means of (23), which has already expressed the power efficiency [2].…”

Section: Numerical Resultsmentioning

confidence: 99%

“…However, it is rather difficult to design an appropriate system according to the material which will be heated in spite of the present numerical methods, and very few studies have been carried out in this field [2][3][4][5].…”

Section: Introductionmentioning

confidence: 99%

Analysis of Microwave Cavity Loaded With Lossy Dielectric Slab by Means of Mode Matching Method and Optimization of Load Location

Süle

Kent²

2010

PIER M

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“…6 and 7 show the online procedure diagram, which consists of sweeping the impedance space by displacing a high-loss dielectric sample inside the cavity over a nylon cartload along the main axis of the oven as described in [17]. Then, for each position of the cartload, both the measured with the VNA and the eight sampled voltage values corresponding to standing wave inside the ten-port are recorded at the computer.…”

Section: B Neural Network Training Methodologymentioning

confidence: 99%

“…7(a), since sample position modification is capable of providing high impedances variations [17]. In this case, the dielectric load has consisted of a 1.5 L sample, which has provided values ranging from 0.1 to 0.8.…”

Section: A Training Procedures and Analysis Of The Neural Structurementioning

confidence: 99%

A Novel Design of a Robust Ten-Port Microwave Reflectometer With Autonomous Calibration by Using Neural Networks

Monzó‐Cabrera

Pedreño-Molina

Guerrero

et al. 2008

IEEE Trans. Microwave Theory Techn.

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Abstract-In this study, a novel ten-port waveguide microwave sensor is designed, implemented, calibrated and tested in order to obtain the reflection coefficient magnitude and phase. This reflectometer is based on the well known six-port structure but the number of detectors has been increased to eight in order to improve the sampling procedure of the standing wave present within the waveguide. In addition, a learning method based on neural networks' usage has been implemented for autonomous calibration from the data collected by a vector network analyzer. An automated procedure consisting of a moving sample within a multimode cavity has enabled different reflection coefficients to be obtained. Neural networks have been employed in order to learn the relationship between the actual reflection parameter and the acquired signals from eight power detectors. This novel device has been calibrated with a neural architecture based on radial basis functions and the error of device measurements has been analyzed. This new design and the incorporated neural network calibration allow one to avoid problems caused by fault or nonlinearity of the detectors, and to get robustness, flexibility and adaptability characteristics for the presented device.

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“…On the other hand, several previous experimental tests have shown that for a multimode microwave cavity, microwave power efficiency varies according to frequency, dielectric properties, position inside the cavity and geometric characteristics of the heated material [7,8]. In fact, in that work it is shown that for several dielectric samples, the efficiency varies with the distance to the magnetron by following a non-linear curve.…”

Section: Introductionmentioning

confidence: 94%

Feedback control procedure for energy efficiency optimization of microwave-heating ovens

2009

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Multimode cavity efficiency optimization by optimum load location-experimental approach

Cited by 20 publications

References 7 publications

Analysis of Microwave Cavity Loaded With Lossy Dielectric Slab by Means of Mode Matching Method and Optimization of Load Location

Analysis of Microwave Cavity Loaded With Lossy Dielectric Slab by Means of Mode Matching Method and Optimization of Load Location

A Novel Design of a Robust Ten-Port Microwave Reflectometer With Autonomous Calibration by Using Neural Networks

Feedback control procedure for energy efficiency optimization of microwave-heating ovens

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