a sensor array based on planar electromagnetic...

A SENSOR ARRAY BASED ON PLANAR ELECTROMAGNETIC SENSORS

FOR AGRO-ENVIRONMENTAL MONITORING

SYAHRUL HISHAM BIN MOHAMAD @ ABD. RAHMAN

A project report submitted in partial fulfilment

of the requirements for the award of the degree of

Master of Engineering (Electrical - Mechatronics and Automatic Control)

Faculty of Electrical Engineering

Universiti Teknologi Malaysia

JANUARY 2013

iii

Thanks to ALLAH S.W.T for giving me the strength to complete the project report

and my master, to my beloved mother and father who always pray for me, to my

wife lovely wife who stand by me and to my incoming child.

iv

ACKNOWLEDGEMENT

Praise to Allah S.W.T., the Most Gracious and the Most Merciful, whose blessing

and guidance have helped me to complete this project report. There is no

knowledge nor power without His permission, the Highest and the Greatest. Peace

and blessing of Allah be upon our Prophet Muhammad S.A.W. who has given light

to mankind.

I would like to express my deepest gratitude to my supervisors Dr

Mohd Amri Bin Md Yunos for his support and supervisions. Without his constant

invaluable guidance, help as well as constructive criticisms and opinions

throughout the research. This research would not have been completed.

Special thanks to my mother and father who their pray are always there for

me, my wife who stand with me, brothers, sisters and families for their wishes,

assistance, guidance, and patience whose sacrifices had made everything is

possible for me. I would like to express my sincere thanks to my classmates

for all of their support during the studies, my colleagues who provided guidance

and assistance during the research.

Last but not least, special thanks to the Ministry of Higher Education

(MOHE) of Malaysia and Universiti Teknikal Malaysia Melaka for providing me

with the financial support and granting leave to pursue my Master degree.

v

ABSTRACT

Agriculture is one of the important sectors in the country however due to

lack of management and knowledge, farmers usually ended up overusing pesticide

and fertilizers which can cause negative effects to the environment. Based on this

situation monitoring of the agro-environment is important in order to maintain the

permanence of the soils. As to date, available methods for contaminations detection

in agriculture soils commonly require tedious operational procedures which usually

involve purchase expensive equipments. This project suggests an alternative method

for the detection of contamination by developing a sensor array with the

combination of planar meander and interdigital electromagnetic sensors for

monitoring the content in agricultural soils and contamination. The main objective is

to fabricate the sensor array using printed circuit board (PCB). For this project three

new configuration of planar electromagnetic placement re introduced which are

parallel, wye and delta. An experimental setup consists of frequency waveform

generator, signal oscilloscope and Agilent software as the controller was developed

to study on the output of the system. A set of experiments were conducted to

determine the relationship between the sensor’s output and the soil’s parameters.

The performance of the system was observed where the sensors were tested with

soil samples taken with different concentration of water percentage. Based on the

result, the sensor array can be expected to be used to measure the contamination in

the soils and the data accuracy is compared.

vi

ABSTRAK

Pertanian merupakan salah satu sektor yang memainkan peranan penting

dalam pembangunan negara kita, namun disebabkan oleh kekurangan pengetahuan

dan sikap sambil lewa, para petani selalunya menggunakan racun dan baja secara

berlebigan dimana ini boleh memberikan kesan negative kepada alam sekitar.

Berdasarkan kepada situasi ini, pengawasan terhadap alam sekitar adalah penting

untuk memastikan kelestarian sumber tanah. Ketika ini, terdapat kaedah yang

digunakan untuk mengesan pecemaran di sector pertanian kebiasaanya melibatkan

prosedur yang rumit dan memerlukan pembelian peralatan yang mahal. Projek ini

mencadangkan satu kaedah alternatif untuk mengesan pencemaran didalam tanah

dengan menghasilkan planar sensor yang menggabungkan meander sensor dan

interdigital sensor. Objektif utama projek ini adalah untuk menghasilkan sensor

dengan menggunakan papan litar tercetak. Dalam projek ini tiga konfigurasi baru

sensor telah dicadangkan iaitu selari, wye dan delta. Satu sistem eksperimen telah

dibina dengan menggunakan penjana gelombang berfrekuensi, osiloskop and

perisian Agilent sebagai pengawal utama untuk mengkaji keluaran sistem sensor

tersebut. Beberapa set eksperimen telah dijalankan untuk mengetahui hubungan di

antara keluaran sensor terhadap parameter-parameter tanah. Prestasi sensor diuji

dengan kandungan air berbeza didalam tanah. Berdasarkan hasil ujikaji, kumpulan

sensor ini dapat digunakan untuk mengukur pencemaran dalam tanah dah ketepatan

data tersebut dapat diuji.

vii

TABLE OF CONTENTS

CHAPTER

TITLE PAGE

DECLARATION ii

DEDICATION iii

ACKNOWLEDGEMENTS iv

ABSTRACT v

ABSTRAK vi

TABLE OF CONTENTS vii

LIST OF TABLES x

LIST OF FIGURES xi

LIST OF SYMBOLS xvi

1 INTRODUCTION

1.1 Introduction to sensor 1

1.2 Environmental Sensor 3

1.3 Background of Problem 5

1.4 Objective of Study 7

1.5 Scope of Study 7

2 LITERATURE REVIEW

2.1 An Overview of Non-destructive Testing 9

2.2 Soils Contamination Detection Method 11

viii

2.2.1 Soils Contamination Detection using

Chromatography technique

12


Surface Plasmon Resonance (SPR)

14


Enzyme linked Immunosorbent Assay

(ELISA)

15

2.3 Planar Electromagnetic Sensor 16

2.3.1 Planar Meander, Mesh and Interdigital

Electromagnetic Sensor

16

2.4 Applicat ion and Development in

Planar Electromagnetic Sensor

20

3 RESEARCH METHODOLOGY

3.1 Introduction 24

3.2 Literature Review 25

3.3 Sensor Design And Fabrication 26

3.3.1 Sensor Design 26

3.3.2 Sensor Fabrication 33

3.4 Experimental setup 34

3.4.1 Hardware Development 35

3.4.2 Software Development 38

3.5 Experimental Work 43

3.5.1 Work Sensor Characteristic on Open Air

Experiment:

44

3.5.2 Sensor Characteristic on Soils and Water

Concentration on Soils Experiment:

44

3.6 Data Analysis and Verification 46

3.7 Report Writing 49

4 EXPERIMENTAL RESULTS AND

DISCUSSIONS

4.1 Introduction 50

ix

4.2 Description of the Selected Sensors 50

4.3 Characterization of the Sensors via Experiment 51

4.3.1 Characterization of the Sensors via

Open Air Experiment

52

4.3.2 Characterization Of The Sensors via

Water concentration in Soils experiment

55

4.3.3 Characterization of the Parallel

Configuration Sensors via water

concentration in soils experiment

56

4.3.4 Characterization of the Wye



64

4.3.5 Characterization of the Delta



72

4.4 Sensitivity studies of the soils 80

5 CONCLUSIONS AND FUTURE WORK

5.1 Conclusions 83

5.2 Future Works 85

REFERENCES 87

x

LIST OF TABLES

TABLE NO.

TITLE PAGE

4.1 R2

Regression value for parallel sensor 57

4.2 R2

Regression value for wye sensor 65

4.3 R2

Regression value for delta sensor 73

xi

LIST OF FIGURES

FIGURE NO.

TITLE PAGE

1.1 Transducer Used In Measurement Block Diagram 1

1.2 Percentage of Sensor According To Industries 2

1.3 Global Environmental Sensor And Monitoring Business By

Market Category

4

2.1 Configuration Of Planar Electromagnetic Sensors; (A)

Mesh-Type Sensor (B) Meander-Type Sensor

17

2.2 Electric Field Lines Of Parallel Plate Capacitors 18

2.3 Conventional Interdigital Sensor 19

2.4 Electric Field Formed Between Positive And Negative

Electrodes For Different Pitch Lengths, (l1, l2and l3)

19

3.1 Project research methodology flow chart 25

3.2 The planar electromagnetic sensor design a) Top side b)

Bottom side

26

3.3a Planar Electromagnetic Sensor Parallel Placement

(Overall Design)

28

3.3b Planar Electromagnetic Sensor Parallel Placement (Top

Side Design)

28

3.3c Planar Electromagnetic Sensor Parallel Placement

(Bottom Side Design)

28

3.4a Planar Electromagnetic Sensor Wye Placement (Overall 29

xii

Design)

3.4b Planar Electromagnetic Sensor Wye Placement (Top

Design)

30

3.4c Planar Electromagnetic Sensor Wye Placement (Bottom

Design)

30

3.5a Planar Electromagnetic Sensor Delta Placement (Overall

Design)

31

3.5b Planar Electromagnetic Sensor Delta Placement (Top

Design)

32

3.5c Planar Electromagnetic Sensor Parallel Placement

(Bottom Design)

32

3.6a Planar Electromagnetic Sensor Parallel Placement 33

3.6b Planar Electromagnetic Sensor Wye Placement 34

3.6c Planar Electromagnetic Sensor Delta Placement 34

3.7 Overall Experiment Setup 35

3.8 Agilent U2781A USB modular Chassis 36

3.9 Agilent U2761A USB modular function generator. 36

3.10 Agilent U2701A USB modular oscilloscope. 37

3.11 Overall Modular Experimental Setup. 38

3.12 Cyclic Frequency Increment Sub Program 40

3.13a Function Generator Initialize Setup 41

3.13b Function Generator Output Setup 41

3.14a Oscilloscope Initialization Setup 42

3.14b Oscilloscope Output Configuration Setup 42

3.15 Agilent VEE Modular Control Program. 43

3.16 Water concentration into soils experiment flow. 45

3.17 Soils are filled and weighted. 45

3.18 Sensor is attached to the polystyrene bag. 46

3.19 Equivalent Circuit of planar meander and interdigital

sensor.

48

4.1 Parallel configuration sensor characteristic via open air

experiment

53

4.2 Wye configuration sensor characteristic via open air 53

xiii

experiment

4.3 Delta configuration sensor characteristic via open air

experiment

54

4.4a Linear Parallel configuration sensor regression at 100

kHz

58

4.4b Linear Parallel configuration sensor regression at 200

kHz

58

4.4c Linear Parallel configuration sensor regression at 300

kHz

58

4.4d Linear Parallel configuration sensor regression at 400

kHz

59

4.4e Linear Parallel configuration sensor regression at 500

kHz

59

4.4f Linear Parallel configuration sensor regression at 600

kHz

59

4.4g Linear Parallel configuration sensor regression at 700

kHz

60

4.4h Linear Parallel configuration sensor regression at 800

kHz

60

4.4i Linear Parallel configuration sensor regression at 900

kHz

60

4.4j Linear Parallel configuration sensor regression at 1 MHz 61

4.5a Polynomial Parallel configuration sensor regression at

100 kHz

61

4.5b Polynomial Parallel configuration sensor regression at

200 kHz

61

4.5c Polynomial Parallel configuration sensor regression at

300 kHz

62

4.5d Polynomial Parallel configuration sensor regression at

400 kHz

62

4.5e Polynomial Parallel configuration sensor regression at

500 kHz

62

4.5f Polynomial Parallel configuration sensor regression at 63

xiv

600 kHz

4.5g Polynomial Parallel configuration sensor regression at

700 kHz

63

4.5h Polynomial Parallel configuration sensor regression at

800 kHz

63

4.5i Polynomial Parallel configuration sensor regression at

900 kHz

64

4.5j Polynomial Parallel configuration sensor regression at 1

MHz

64

4.6a Linear Wye configuration sensor regression at 100 kHz 66

4.6b Linear Wye configuration sensor regression at 200 kHz 66

4.6c Linear Wye configuration sensor regression at 300 kHz 66

4.6d Linear Wye configuration sensor regression at 400 kHz 67

4.6e Linear Wye configuration sensor regression at 500 kHz 67

4.6f Linear Wye configuration sensor regression at 600 kHz 67

4.6g Linear Wye configuration sensor regression at 700 kHz 68

4.6h Linear Wye configuration sensor regression at 800 kHz 68

4.6i Linear Wye configuration sensor regression at 900 kHz 68

4.6j Linear Wye configuration sensor regression at 1 MHz 69

4.7a Polynomial Wye configuration sensor regression at 100

kHz

69

4.7b Polynomial Wye configuration sensor regression at 200

kHz

69

4.7c Polynomial Wye configuration sensor regression at 300

kHz

70

4.7d Polynomial Wye configuration sensor regression at 400

kHz

70

4.7e Polynomial Wye configuration sensor regression at 500

kHz

70

4.7f Polynomial Wye configuration sensor regression at 600

kHz

71

4.7g Polynomial Wye configuration sensor regression at 700

kHz

71

xv

4.7h Polynomial Wye configuration sensor regression at 800

kHz

71

4.7i Polynomial Wye configuration sensor regression at 900

kHz

72

4.7j Polynomial Wye configuration sensor regression at 1

MHz

72

4.8a Linear Delta configuration sensor regression at 100 kHz 74

4.8b Linear Delta configuration sensor regression at 200 kHz 74

4.8c Linear Delta configuration sensor regression at 300 kHz 74

4.8d Linear Delta configuration sensor regression at 400 kHz 75

4.8e Linear Delta configuration sensor regression at 500 kHz 75

4.8f Linear Delta configuration sensor regression at 600 kHz 75

4.8g Linear Delta configuration sensor regression at 700 kHz 76

4.8h Linear Delta configuration sensor regression at 800 kHz 76

4.8i Linear Delta configuration sensor regression at 900 kHz 76

4.8j Linear Delta configuration sensor regression at 1 MHz 77

4.9a Polynomial Delta configuration sensor regression at 100

kHz

77

4.9b Polynomial Delta configuration sensor regression at 200

kHz

77

4.9c Polynomial Delta configuration sensor regression at 300

kHz

78

4.9d Polynomial Delta configuration sensor regression at 400

kHz

78

4.9e Polynomial Delta configuration sensor regression at 500

kHz

78

4.9f Polynomial Delta configuration sensor regression at 600

kHz

79

4.9g Polynomial Delta configuration sensor regression at 700

kHz

79

4.9h Polynomial Delta configuration sensor regression at 800

kHz

79

xvi

4.9i Polynomial Delta configuration sensor regression at 900

kHz

80

4.9j Polynomial Delta configuration sensor regression at 1

MHz

80

4.10 Sensitivity of real part for different water concentration

in soils at 100 kHz

82

4.11 Sensitivity of imaginary part for different water

concentration in soils at 100 kHz

82

xvii

LIST OF SYMBOLS

C - Capacitance

I - Current

L - Inductor

PCB - Printed Circuit Board

R - Resistance

V - Voltage

X - Reactance

Z - Impedance

Ω - Ohm

∅ - Angle

CHAPTER 1

INTRODUCTION

1.1 Introduction to Sensor

Sensor is a device that detects the parameter of show the quantity of the

measured parameter. Example of sensor is such thermocouples that detect and

sense the changes in the temperature. A transducer is a device that converts non

electrical parameters into electrical signal such as voltage and current that are

proportional to the physical value parameters that are being measured. Usually a

transducer involve a sensor and signal conditioning circuit or instruments in order

to translate or to read the value of the measurement. Figure 1.1 shows the block

diagram of transducer used in measurement.

Figure 1. 1: Transducer Used In Measurement Block Diagram

2

Sensor and transducer development is a rapid need as both of the

equipments are used in most all of the sectors and industry globally. The

implementation of sensor in most of the industries can been see with the

unprecedented growth of utilization of sensors in product and services, where

sensors play an important role in gaining important information for monitoring and

measuring process. A research done [1] show that the sensor influence of the

industrial sector globally. Figure 1.2 shows how the sensors influence within the

industries and market sector. The market sector which has most heavily used

sensors in their process is the health care sector where consist of 20% of the overall

sector. The second and third highest sector that influenced by the usage of sensor

within the industries are food processing sector which consist of 12% and the

environment sector which consist of 11% of overall market. Others area that

implemented the sensor in their sector is such as agriculture (8%), chemical

engineering (8%), domestic and other appliances (7%), security and defence (7%),

transport (6%), and energy (6%). Less development or application of sensor is used

or made in sectors such as construction/housing (3%), wood and textile (3%),

IT/communication (4%), and metal and plastic processing (5%) [1].

Figure 1. 2: Percentage of Sensor According To Industries

0

5

10

15

20

25

Percentage Of Sensor Used In Industries

Percentage

3

1.2 Environmental Sensor.

Environmental awareness has become one of the principal in technology and

industries development within these recent years. The future growth for environment

related sensor and environmental monitoring technologies are pre-ordained due to the

awareness within the global economies player on their responsibilities of environmental

impact or they may cause negative impact on themselves. This has made environmental

sensor become a substantially high technologies business. Two major trends can be

seen in influence of the environmental sensing and monitoring business, the first is that

the design and engineering of sensor components and engineering are going for a

technological revolution. Most of the individual sensors are moving forward toward

miniaturization process. The advantages of development of smaller sensor are that by

producing smaller sensor it lowers the material cost and also making the sensor to

become more energy efficient, it also large distributed networks possible. And

simultaneously environmental friendly aspect and clean-up are is more or less being

imbedded into the policy-making agenda, the advance progress in nanotechnology,

semiconductor and communication are supporting and facilitate the implementation and

development of sensors product.

Environmental sensors factually come in thousands of types, design and forms.

The sensors are usually base on a wide range of chemical and physical principles with

variable types of outputs for monitoring process. The field applications of

environmental sensors also tremendously varied. The areas of that has become the focus

for environmental sensor include vehicles emissions, fossil fuels combustion,

agricultural contamination, waste disposal for industrial and mine, ocean spilling and

dumping, extreme change in climate and weather monitoring.

The second influential factor is the rapid development of environmental sensor

and monitoring networks themselves. There is an outburst in the extent, capacity and

numbers for the mention networks, where the figure show in 2010 where the value of

global environmental sensor and is at $11.1 billion. Based on the current trendsetting

4

and forecast of future demand the environmental sensor market is expected to

reach $11.3 billion in 2011 and $15.3 billion in 2016. Where it can be say that there

will be a compound annual growth rate of 6.5% between 2011 and 2016. Shown in

Figure 1.3, which the range of expenditure for sensor can be divided into terrestrial

monitoring, atmospheric monitoring, oceanic monitoring, radon, GPS, remote sensing

and new technology.

Sensor networks allow real-time data visualization and analysis, distributed

sensing capacity, remote sensing data streams and integration of adjacent networks. The

main factor that contributed to the development of the networks are the availability of

computational capacity, the progress of massive data storage, the evolution of internet

and the reduction in size of electronics components. At this point the establishment of

environmental sensor network has been firm and large new network currently in

development process where the new environmental network rage from continental

monitoring scope until to those which only monitor on local situations. In terms of

monitoring variables are including CO2 combustion up to decadal shift in the

temperatures. The current sensor also can monitor biological and physical activities, as

well capable of measuring nutrient dynamics and groundwater fluxes. Due to these, the

development of environmental sensor is seen to be more crucial from time to time.

Figure 1. 3: Global Environmental Sensor and Monitoring Business by Market Category

5

1.3 Background of the problem

Soil is a valuable key natural source, where the 29 % of the world is cover by

land while the other 71 % of the world is primarily ocean. In the world ecosystem, soil

play an important role, which is to supports life and is a major requirement for maintain

a sustainable development in terrestrial environments. The possibility of degradation in

the aspect of quality for the topsoil layer play a particular interest as due to the topsoil

layer are exposed to natural geochemical processes, anthropogenic activities and

atmospheric deposition. Anthropogenic activities, especially in regions where

agriculture, mining land and industrial uses are practiced have significantly altered

natural background concentrations of the soils.

Soil contamination are a greater risk to the of individual who live in less

industrialize and less populated rural are compared to those whose live in the heavily

urbanized or industrialize area are due to the exposure of the contamination are higher

in time aspect of quantity and time for the rural area [2]. The contamination of urban

and agricultural soils by potentially toxic metals is also causing concern due to the

possible adverse effects on the ecosystem. Due to this matter, an improved monitoring

and understanding of the concentration of contamination in the soils in order to ensure a

long-term sustainability of food production. It is essentials to study the major, minor and

trace elements in the soils in order to understand the factor of nutrient deficiency,

bioavailability, pollution and the possible effect that can occurred to food chains and

geological eco-system. Therefore it is very important to have an ambient background

concentration data such as development of sites , toxicity and bioavailability for

potential uses [3].

The in order to safeguard human, animal and plant, there is need for

assessment, prevention, control and development of contaminated land through

regulatory organizations, which required continuous information on the soil condition.

Thus, it is important for the regulators to set guideline/standard values as a component

of environmental legislation for specific sites or wider geographical regions. One of the

6

most important objectives of background environmental monitoring is the identification

of any anomalies and anthropogenically introduced contaminants in any environmental

assessment program [4]. In Malaysia, there are currently no comprehensive soil

reference values available in order to assess levels of potentially contamination of

anomaly for various land uses such as industrial, recreational land, agriculture and

development. Based on this there is need for technology to assess the contamination

level of natural soil resources due to the process of industrialization, agriculture and

urbanization of soils in Malaysia.

Agriculture sector plays the role as one of the most significant economy

contributor in Malaysia where based on World Bank Indicator shows that around 24%

of Malaysia soil is used for agriculture. Correspond to the volume of the soils that are

used for agriculture, agro-environment monitoring is an important process in order to

maintain the permanence of the soils. However, the contaminations in the soils have

become a common thing in the agriculture soils due to the lack of knowledge within the

farmers. Overused of pesticides and fertilizers in the soil can cause negative effect to the

soil itself.

Although there are detection methods in assessing the contamination, there are

few drawbacks. The detection usually involved laborious measuring step, this will cause

the overall detection process consumes lots of time. Most of the detection process need

to be done within the laboratory and in order to extract the contain of contamination

within the soil and the process itself required controlled working condition and

preparation of extra reagent or chemical, this cause the detection result cannot be obtain

immediately. The detection process also are often expensive, this due to many

components are required in order to develops the experimental process for finding out

the soils contamination level and sometimes this process will required special

equipment which are specially designed. These requirements will become the

drawbacks as all the equipment are quite costly and are hard to be set up. Although all

the detection method is can give good results, most of the equipment are quite bulky

and the detection cannot be done on the site.

7

Based on the following drawbacks and hindrance of current detection method,

there is need to develop a sensor which can be integrated as a low cost, convenient,

and suitable for in-situ measurement system for soils quality monitoring,

particularly pesticide and fertilizer effect on soils contaminations.

1.4 Objective of the study

Looking at important of soil monitoring for the permanence of the environmental,

this research aims to achieve the following objectives:

1. To design and fabricate new planar sensor based on the combination of meander

and interdigital sensor.

2. To investigate the characteristic of the new planar sensor array based on

meander and interdigital sensor.

3. To conduct experimental work to determine relationship between the sensor

output and soils parameter.

1.5 Scope of the study

In order to achieve the objectives of the project, that is to investigate the soil

contaminations level due to pesticide and fertilizer used by the farmers for agriculture

process based on planar electromagnetic sensor development. The scopes of the project

need to be identified and implemented to make sure the aim is achieved. The scope of the

project is as follows:

8

1. Designing the sensor array using printed circuit board (PCB) designer software and

fabricating the sensor using printed circuit board (PCB). The scopes involve the

study of sensor sensitivity by three different placements of the sensor array where

the placements are parallel configuration, delta configuration and Y configuration.

2. Developing the experiment setup consists of frequency waveform generator as the

input signal, signal oscilloscope to detect the output of the sensor and to develop

output component analysis software by using Lab View to study on the

characteristic of the sensor.

3. Carry out set of experiments that will be conducted to determine the relationship

between the sensor’s output and the soil’s parameters, the suggested experiments is

on the soils permittivity versus moisture, soils permittivity versus pesticide and soils

permittivity versus fertilizer.

87

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