Kemal Fidanboylu

Prediction of force measurements of a microbend sensor based on an artificial neural network.

Artificial neural network (ANN) based prediction of the response of a microbend fiber optic sensor is presented. To the best of our knowledge no similar work has been previously reported in the literature. Parallel corrugated plates with three deformation cycles, 6 mm thickness of the spacer material and 16 mm mechanical periodicity between deformations were used in the microbend sensor. Multilayer Perceptron (MLP) with different training algorithms, Radial Basis Function (RBF) network and General Regression Neural Network (GRNN) are used as ANN models in this work. All of these models can predict the sensor responses with considerable errors. RBF has the best performance with the smallest mean square error (MSE) values of training and test results. Among the MLP algorithms and GRNN the Levenberg-Marquardt algorithm has good results. These models successfully predict the sensor responses, hence ANNs can be used as useful tool in the design of more robust fiber optic sensors.

An enhanced time-domain approach for dielectric characterization using stripline geometry

A time-domain approach for dielectric characterization using a stripline geometry is presented. The technique uses both time-domain reflectometry (TDR) and time-domain transmission (TDT) measurements for determining an optimum frequency-dependent lossy transmission-line model for the stripline under test. The optimization is done in the time domain by comparing the experimental TDR and TDT response waveforms with the simulated ones using a nonlinear least squares fit. The material properties such as the complex permittivity of the dielectric material are determined from the optimum lossy transmission line model. Both simulated and experimental results are presented.<<ETX>>

A NOVEL FIBER OPTIC SYSTEM FOR MEASURING THE DYNAMIC STRUCTURAL BEHAVIOR OF PARACHUTES

A novel approach has been developed for real-time characterization of a parachute during inflation. Two techniques were applied to measure static and dynamic stresses in a parachute canopy fabric material and suspension lines: the modal power distribution (MPD) technique and the fiber Bragg grating (FBG) technique. Several tests were conducted under various loading conditions, using a bi-axial tensile tester. The MPD technique was used to measure the transverse stresses in the parachute canopy fabric material and was applied using two experimental set-ups: one using a CCD camera and the other using a photo-detector. The FBG technique was used to measure the axial stresses in the parachute canopy fabric material. The tests were performed using the spectrum analyzer set-up with the bi-axial machine. Finally, a drop test was performed on the parachute canopy fabric material using the MPD technique with the photo-detector set-up.

A new time-domain approach for determining the complex permittivity using stripline geometry

A time-domain approach for determining the complex permittivity of materials using stripline geometry is presented. The technique uses time-domain reflectometry (TDR) measurements and computer simulation to determine an optimum lossy transmission-line model characterizing the stripline under test. The line model is then used for determining the complex permittivity of the dielectric material. The validity of the technique is demonstrated by using a stripline constructed from Rogers RT/Duroid composite laminate and one constructed from thick-film paste. Accurate estimates for both the Duroids and the thick film pastes dielectric constant were obtained. The technique is incapable of determining the loss tangent if the mismatch between the step generator and the stripline under test is very high and the loss tangent is fairly small. >

Performance analysis and modeling of two-tier cellular networks with queuing handoff calls

One way of improving the performance of a cellular network is to build a second tier (layer) called the macrocell on top of the single-tier called the microcell. Multi-tier cellular networks provide mobility solutions to both the high speed and low speed users. Since dropping an ongoing call when a mobile user moves from one cell to another is an undesirable event, several techniques have been previously proposed to solve this problem. In a cellular network, this problem can be solved by delaying the handoff call using a queue, until its able to maintain a channel. In this paper, a new Markov model is developed for a two-tier cellular network having a FIFO queue in the macrocell, which takes into account the mobility and the queue time of users. Later, the analytical model of the cellular system is solved and its performance is calculated. The results are then compared with previously proposed models.

Rotation Angle Estimation Algorithms for Textures and Their Real-Time Implementation on the FU-SmartCam

In this paper, we study rotation angle estimation algorithms for textures and discuss their real-time implementation on the FU-SmartCam. Rotation angle estimation for textures is closely related to the weft-straightening problem encountered in the textile industry. Earlier weft-straightening machines were based on simpler sensors and hardware, but with the increased complexity of fabric types, and demand for faster and more accurate machines, the whole industry started to switch to real-time machine vision based systems. For example, one of the leading companies in this area, Erhardt+Leimer, started to implement realtime machine vision systems based on the tattile smart camera. In this work, we both study rotation angle estimation algorithms for textures, and their real-time implementation on the locally developed Fatih University smart camera (FU-SmartCam). We also compare the FU-SmartCam with the tattile smart camera used in the Erhardt+Leimer system, both in terms of hardware and ease of prototyping.

A New Approach to Planar Structure Characterization Using Time Domain Techniques

A new approach for planar transmission line characterization is presented. The approach is based on using time domain techniques for characterizing the coaxial to planar adapter probes used in the measurements. The characterization is achieved by developing an equivalent network model for the probes with the aid of a transient circuit analysis computer program.

Design of intelligent fiber optic statistical mode sensors using novel features and artificial neural networks

In this paper, novel statistical features namely first moment and second moment were proposed in the analysis of fiber optic statistical mode sensors to design consistent and sensitive sensors. These features used first time in literature. Experiments were conducted to measure force using statistical mode sensors and analyses were implemented using proposed statistical features. Good results were concluded and it was seen that these statistical features can be used in the design of statistical mode sensors. After that, Artificial Neural Networks (ANNs) with sensor fusion, intelligent sensor architecture was proposed to predict the force values measured by statistical mode sensors. It was seen that using the statistical features with sensor fusion provides better prediction of force values. Multilayer Perceptron (MLP) with different algorithms were used in ANN model. All of them can predict the force values with considerable errors. Statistical mode sensors can be calibrated and fault tolerance of the sensor can be decreased, hence more reliable sensors can be designed.

A novel time domain synthesis technique

This paper presents a novel time domain synthesis technique which has several applications in microwave measurements and material characterization. The proposed technique models a device under test by a cascade of N transmission lines. The model is based on the devices time domain reflectometry response waveform.<<ETX>>

An optimization technique for time domain applications

An optimization technique for time domain applications is presented. The technique uses a modification of Powells (1964) algorithm to obtain the best non-linear least squares fit between the simulated and experimental time domain responses. This set is said to be an optimal solution for the optimization process. From the optimal solution, the material properties of the stripline under test are obtained.<<ETX>>