results of the in-beam testw3.atomki.hu/numex02/talks/01_03_erturk_debrecen... · results of the...

Results of the In-Beam Test

Sefa ERTÜRK

and

Vakkas BOZKURT

Ömer Halisdemir University,

Physics Dept., Nigde, Turkey

Outlines

MotivationIn Beam test ExperimentProducing Calibration CoefficientsChecking Resolution K-parametersFuture plan

TESTING NUMEXO2 WITH 2 EXOGAM

58Ni beam (180 MeV) on 58Ni target

With NUMEXO2

K-parameters

2 µs

5 µs

10 µs

Distribution of Source Data (60Co and 152Eu*)

* : 344.785, 778.904, 1112.074, 1408.006

**

*

*

Distribution of Source Data (60Co and 152Eu*)

*

** *

* : 344.785, 778.904, 1112.074, 1408.006

Function of Calibration Parameters from Source Data

Calibrated Source Data

Uncalibrated Data for K5µs Parameters

Calibrated Data for K5µs Parameters

Resolution for Source Data

Low Medium High

Low Medium High


Low

Low Medium

Medium

High

High


Low

Low

Medium

Medium

High

High

Resolution for K2µs Parameters from Data

Low

Low

Medium

Medium

High

High


Low

Low

Medium

Medium

High

High

Measured Resolution for K2 µs (LSB)

Crystal Number Low Medium High

B110-A 30.93 40.21 36.75

B110-B 32.34 42.11 39.20

B112-A 30.81 40.47 39.95

B112-B 38.77 53.11 51.42

B113-A 39.24 36.52 35.02

B113-B 38.47 37.22 36.92

B116-A 47.66 47.54 46.88

B116-B 47.59 48.20 44.27

Measured Resolution (2.35σ)



B110-A 15.15 19.96 19.69

B110-B 14.71 19.85 16.69

B112-A 13.81 18.87 18.15

B112-B 21.60 25.92 25.24

B113-A 21.58 19.65 17.91

B113-B 20.80 18.74 16.97

B116-A 21.86 20.80 19.19

B116-B 22.39 20.90 21.01




B110-A 11.98 18.65 19.58

B110-B 12.12 17.46 15.62

B112-A 12.17 17.62 16.31

B112-B 20.10 23.24 23.30

B113-A 20.19 18.41 16.18

B113-B 19.47 17.21 13.63

B116-A 21.76 19.36 15.57

B116-B 19.88 18.05 16.21


Measured Resolution for Calibration Data (LSB)


B110-A 10.55 12.09 14.19

B110-B 10.55 12.06 14.07

B112-A 10.36 11.85 13.63

B112-B 17.19 17.69 19.64

B113-A 12.65 13.97 15.75

B113-B 11.48 12.88 15.08

B116-A 14.46 15.73 17.53

B116-B 13.22 14.31 16.44


Distribution

of K10µs

Distribution

of K5µs

Distribution

of K2µs

Future Plan

Precise Measurement Understand the behavior of CrystalCheck the resolution for 96Cd Exp.May need another in-beam test Exp.

35

Personel Info

Dr. Remzi İNAN

Research Assistant in Electrical and Electronics Engineering

Mehmet Muzaffer KÖSTEN

Research Assistant in Computer Engineering

PHD Candidate in Electrical and Electronics Engineering

36

Personel Info

Interests: Induction Motor, Speed-sensorless Control, FPGA and DSP Based

Controllers, Field-Weakening Operation

Interests:

Embedded Systems

FPGA Based Design

GPU Programming (CUDA)

Machine Learning

37

Seminars, Books, Papers

•Seminars:

•Fuat Karakaya, Mehmet Ali Çavuşlu, Mehmet Muzaffer Kösten, "FPGA Based Signal and Image Processing", IEEE 24thSignal Processing and Communications Applications, 2016

•Book:

•Mehmet Ali Çavuşlu, Mehmet Muzaffer Kösten, "VHDL ile Sayısal Tasarım ve FPGA Uygulamaları (Digital Design withVHDL and FPGA Applications)", KODLAB 03.2015

•Papers:

•Mehmet Muzaffer KÖSTEN, Mehmet Önder EFE, "Implementation of Discrete Time Sliding Mode Control with Floating Point Arithmetic on an FPGA", Otomatik Kontrol Türk Milli Komitesi Otomatik Kontrol Ulusal Toplantısı -TOK 2015, pp. 79-83, Denizli, Türkiye, 10.09.2015

•Mehmet Muzaffer Kösten, Gökmen Avcı, Fuat Karakaya, Halis Altun, “Analysis of Activation Function ImplementationMethods and Arithmetic Representation in Terms of Hardware Resource, Precision and Speed Dilemma on FPGA”,International Symposium on INnovations in Intelligent SysTems and Applications, 392-396, June 29-July 1, 2009, Trabzon

•Gökmen Avcı, Mehmet Muzaffer Kösten, Fuat Karakaya, Halis Altun, Mehmet Ali Çavuşlu, “Implementation of anHybrid Approach on FPGA for License Plate Detection Using Genetic Algorithm and Neural Networks”, InternationalSymposium on INnovations in Intelligent SysTems and Applications, 392-396, June 29-July 1, 2009, Trabzon

38

Seminars, Books, Papers

•Inan Remzi and Barut Murat (2015). Speed-Sensorless Direct Vector Control Of Induction Motor with The EKF Based Stator Resistance Estimation on FPGA. IEEE Conference on ACEMP-OPTIM-ELECTROMOTION-JOINT CONFERENCE (ACEMP 2015), 343-347

•Inan Remzi, Barut Murat, and Karakaya Fuat (2014). FPGA Implementation of Extended Kalman Filter for Speed-Sensorless Control of Induction Motors. 7th IET International Conference on Power Electronics, Machines and Drives (PEMD 2014), 1, 1-6. (Cited by 2 Papers)

•Inan Remzi, Barut Murat ve Karakaya Fuat (2012). Comparison of MATLAB Software and FPGA Hardware Environment Calculations Using the Induction Motor Model , Otomatik Kontrol Türk Milli Komitesi Otomatik Kontrol Ulusal Toplantısı (TOK’2012), 1, 835-839.

•Inan Remzi, Barut Murat ve Karakaya Fuat (2012). Extended Kalman Filter Based FPGA Implementation for Speed-Sensorless Control of the Induction Motors. Otomatik Kontrol Türk Milli Komitesi Otomatik Kontrol Ulusal Toplantısı (TOK’2012), 1, 469-473.

•Master and Doctorate Thesis:

•Extended Kalman Fılter Based FPGA Implementatıon For Speed-Sensorless Control Of Inductıon Motors, Remzi INAN (MS)

•Effective Implementation of Tracking Algorithms on FPGA for Real-Time Application, Mehmet Muzaffer KÖSTEN (MS)

•Development and Real-Time Implementations of IM Control Algorithms on FPGA, Remzi INAN (PHD)

39

Lab Equipments

Xilinx Virtex-5 XC5VLX110T FPGA

Xilinx Virtex-5 XC5VSX50T FPGA

Xilinx Artix-7 FPGA XC7A100T FPGA

Xilinx Artix-7 FPGA XC7A200T FPGA

Xilinx Zynq Z7020 FPGA

40

FPGA Properties

Virtex5SX50T

Virtex5LX110T

Artix7XC7A100

T

Artix7XC7A200

T

Zynq7020

Logic Cells (K)

52 110 101 215 85

DSP Slices 288 64 240 740 220

Memory (Mb)

4.64 5.18 4.74 12.83 4.9

Thank you for your attention

This work was supported by the

Turkish Scientific and Research Council (TÜBİTAK)

with Grant Number 114F173

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