Exeley Inc.

KOVAL, Viktor V.

PETRASHEVSKA, Angelina D.

POPOVA, Olga L.

MIKHNO, Inesa S.

GASKA, Krzysztof

METHODOLOGY OF ECODIAGNOSTICS ON THE EXAMPLE OF RURAL AREAS

Sobolewska-Ruta, Agnieszka

Zaleski, Piotr

CELL BANKS PREPARATION IN BIOPHARMACEUTICALS PRODUCTION

Ratajczak, Piotr

Kus, Krzysztof

Zaprutko, Tomasz

Szczepański, Mikołaj

Rusowicz, Sandra

Nowakowska, Elżbieta

Antidepressant and anxiolytic efficacy of single, chronic and concomitant use of vortioxetine, dapoxetine and fluoxetine in prenatally stressed rats

MUCCEE, FATIMA

EJAZ, SAMINA

1 
Supplementary materials for the article: 
Muccee F, Ejaz S. An investigation of Petrol Metabolizing Bacteria Isolated from 
Contaminated Soil Samples Collected from Various Fuel Stations.  
Pol J Microbiol. 2019, Vol. 68, No 2, 193–201. 
 
 
Table SI 
Primers used for amplification of 16S rRNA gene. 
Primer Name 5`-3` Sequence GC% 
Primer 
Tm 
Amplicon 
size 
Forward primer 
(F1) 
AGAGTTTGATCCTGGTCAGAACGAACGCT 48.3% 70.4°C 
1500bp 
Reverse primer 
(R1) 
CGTACGGCTACCTTGTTACGACTTCACCCC 56.7% 74.8°C 
 
 
Table SII 
Colony forming units (CFUs) of petrol metabolizing bacteria 
Bacterial isolate Dilution 
No. of colonies 
(CFUs) 
Colony forming units (CFUs)/1g of soil sample 
IUBP1 
10-1 875 875 x 101 IUBP2 
IUBP3 
IUBP5 
10-2 587 587 x 102 
IUBP7 
IUBP8 10-3 80 80 x 103 
IUBP13 10-4 19 19 x 104 
IUBP14 
10-5 
7 7 x 105 
IUBP15 15 15 x 105 
 
2 
Table SIII 
Biochemical characterization of isolated petrol metabolizing bacteria. 
Group Subgroup Isolates Biochemical Characters 
GroupI 
(Brevibacillus formosus) 
G1:G1A IUBP2 
Esculinase, glucosaminidase, phosphatase producer 
and mannitol, sorbitol and inulin fermenting 
G1:G1B IUBP3 
Arginine dehydrolase, esculinase, glucosaminidase, 
phosphatase producers, mannitol, sorbitol and 
inulin fermenting 
G1:G1C IUBP5 
Esculinase, phosphatase producer, sorbitol and 
inulin fermenting 
Group II 
(Brevibacillus agri) 
- IUBP1 
Esculinase, naphthylamidase and phosphatase 
producers 
Group III 
(Burkholderia lata) 
G3:G3A IUBP7, IUBP13 
Esculinase, phosphatase producer, mannitol, 
sorbitol and inulin fermenting 
G3:G3B IUBP8 
Esculinase, glucosaminidase, phosphatase producer 
and inulin fermenting 
G3:G3C IUBP14 
Arginine dehydrolase, esculinase, phosphatase 
producer and inulin fermenting 
Group IV 
(Burkholderia pyrrocinia) 
- IUBP15 
Esculinase, phosphatase producer, mannitol, 
sorbitol and inulin fermenting 
 
 
 
Table SIV 
Growth behavior of morphologically and biochemically similar isolates of group G3A. 
Group Isolate Lag phase Log phase Death phase Static phase 
G3A 
IUBP7 0 – 24 24 – 48 48 – 51 < 51 
IUBP13 0 – <6 6 – 27 27 – 30 0 – 48 
3 
Table SV 
Petrol removal efficiencies of isolated bacteria. 
Group Isolate Mean ± SD 
Group I 
(Brevibacillus formosus) 
IUBP2 62 ± 19.34 
IUBP3 66 ± 9.90 
IUBP5 55 ± 7.07 
Group II 
(Brevibacillus agri) 
IUBP1 41 ± 32.6 
Group III 
(Burkholderia lata) 
IUBP7 58.5 ± 10.61 
IUBP8 50.5 ± 6.36 
IUBP13 53.7 ± 4.95 
IUBP14 63 ± 1.41 
Group IV 
(Burkholderia pyrrocinia) 
IUBP15 69.5 ± 13.44 
4 
 
(a) G3A1 (b) G3A2 
Fig. S1. Growth study of isolated petrol metabolizing bacteria (G3A) having similar 
molecular and biochemical profile. 
 
5 
 
Fig. S2. Zone of inhibition for nine petrol metabolizing bacteria. 


An Investigation of Petrol Metabolizing Bacteria Isolated from Contaminated Soil Samples Collected from Various Fuel Stations

MOON, JI-HOI

NOH, MI HEE

JANG, EUN-YOUNG

YANG, SEOK BIN

KANG, SANG WOOK

KWACK, KYU HWAN

RYU, JAE-IN

LEE, JIN-YONG

Effects of Sodium Tripolyphosphate on Oral Commensal and Pathogenic Bacteria

KONECKA, EDYTA

MOKRACKA, JOANNA

KRZYMIŃSKA, SYLWIA

KAZNOWSKI, ADAM

Supplementary materials for the article: 
 
Konecka E. et al. Evaluation of The Pathogenic Potential of Insecticidal Serratia marcescens 
Strains to Humans. 
Pol J Microbiol. 2019. Article in Press. 
 
Table SI  
Production of siderophores of S. marcescens strains isolated from insects. 
Isolate 
Cross-feeding assay 
S. typhimurium 
TA 2700 
E. coli LG 
1522 
M. morganii 
SBK 3 
Y. enterocolitica 
5030 
MPU Si1 + - - - 
MPU Si2 + - - - 
MPU Si3 + - - - 
MPU Si4 + - - - 
MPU Si5 + - - - 
MPU Si6 + - - - 
MPU Si7 + - - - 
MPU Si8 + - - - 
 
 
 
  
 Fig. S1. Dendrogram (Dice/UPGMA) showing the similarity of DNA patterns of Serratia spp. 
strains obtained by the REP-PCR method. 


Evaluation of The Pathogenic Potential of Insecticidal Serratia marcescens Strains to Humans

KOPER, Piotr

JANKOWSKA, Marta

ADDITIONAL INSULATION MATERIALS IN A WINDOW FRAME: EXPERIMENTAL AND CFD ANALYSES

Shuping, Xu

Mengyao, Huang

Pei, Xu

International Journal of Advanced Network, Monitoring and Controls          Volume 03, No.03, 2018 
DOI: 10.21307/ijanmc-2019-008                       70 
Readings of Portable UV Spectrum Analyzer Data Based on Raspberry Pi 
Xu Shuping 
School of Computer Science and Engineering 
Xi’an Technological University 
Xi’an, 710021, China 
e-mail：xusp686@163.com 
Huang Mengyao, Xu Pei 
School of Computer Science and Engineering 
Xi’an Technological University 
Xi’an, 710021, China 
 
 
Abstract—Most of the spectrometer has the advantages of large 
volume, inconvenient carrying, slow data reading, long 
development cycle and high cost. In view of this situation, this 
paper presents a raspberry based portable spectrum analyzer. 
The general structure, working principle and data reading 
principle of the portable ultraviolet spectrum analyzer system 
based on raspberry faction are introduced in detail. And the 
raspberry sent a brief introduction, and finally introduced the 
raspberry pie to the development of the environment 
configuration, and the use of Python-Qt prepared control 
software for data read. The final test shows that the system 
interface is simple and friendly, stable operation, you can 
quickly read the data from the spectrometer, to meet the actual 
requirements. 
Keywords-Spectrometer; Raspberry Pi; Working Principle; 
Data Reading 
I. INTRODUCTION 
The micro-spectrometer has advantages of modular 
structure and flexible construction, so inpractice, only a 
spectrometer is needed, and the software can detect different 
samples in realtime [5]. At the same time, the 
micro-spectrometer has advantages of small size, easy to 
carry, compact internal structure, wide wavelength range, 
fast detection speed and low price. It has wide application 
development space in the field of industrial online 
monitoring and portable detection [8]. 
At present, the portable spectrometer in domestic and 
foreign market has two main methods: electrochemical 
analysis and infrared spectrometry[2]. The electrochemical 
analysis method has the advantages of simple structure and 
easy operation. It mainly depends on the gas sensor, and a 
gas sensor can only detect a corresponding gas, and the gas 
sensor also has a life limit, the use of a period of time, the 
sensitivity of the gas will be reduced, the need to replace gas 
sensors, and gas sensors are expensive, increasing the cost of 
use for the user. The main principle of the gas sensor is the 
use of gas oxidation or reduction reaction, the current, but if 
both the presence of oxidizing gas and reducing gas, the 
measurement results will be inaccurate [7]. Infrared 
spectroscopy overcomes the shortcomings of 
electrochemical analysis, but it can only measure the 
approximate concentration of NOx, and it cannot accurately 
measure the specific concentration of NO and NO2, and the 
infrared spectral analysis method is more complicated than 
the environment humidity, temperature, etc [6]. 
Based on the above problems, this paper presents a 
portable UV spectrometer developed using Maya2000Pro 
UV spectrometer and raspberry pi, according to the UV light 
wavelength 190nm-290nm, the gas has good absorption of 
ultraviolet light, and the measurement is absorbed by the gas, 
after the UV light, which can read through the spectrometer 
wavelength and photon number. The ultraviolet spectral 
analysis has the advantages of high reliability, strong 
anti-interference, and a variety of gases can be measured at 
the same time, accurate measurement and so on. The 
portable spectrometer has the advantages of fast data reading 
speed, low cost, convenient on-line debugging, stable 
operation and simple operation, and achieves practical 
requirements. 
 
International Journal of Advanced Network, Monitoring and Controls          Volume 03, No.03, 2018 
71 
II. SYSTEM ARCHITECTURE 
The portable UV spectrometer’s system architecture as 
shown in Fig.1, and system consists of three modules: data 
acquisition module, data processing module and 
man-machine interaction module. The data acquisition 
module is composed of sampling probe, flue gas sampling 
pump, ultraviolet light source and micro spectrum analyzer, 
and the main purpose is to complete the collection of gas, 
analyze the spectral data before and after the ultraviolet light 
source and micro-spectrometer, and transform the spectral 
data into digital signal to transmit to the data processing 
module. In fact, in the whole system, the micro-spectrometer 
is a very important sensor component, and the spectrometer 
is mainly composed of optical components, photoelectric 
conversion module (CCD), memory. The optical 
components are mainly for optical fiber incoming optical 
signal processing, photoelectric conversion module (CCD) 
after the optical processing of ultraviolet light into electrical 
signals, memory used to store electrical signals [3]. At the 
core of the data center is the Raspberry Pi Development 
Board, then the task is to calculate the specific concentration 
of gases in the mixed gas by using the relevant algorithm. 
The man-machine interaction module is composed of a 
keyboard and an LCD screen, which is designed to visualize 
the concentration of gas and other related settings on line 
monitoring. 
 
Figure 1. The overall architecture of the portable spectrometer 
The key component of the portable UV spectrum 
analyzer control and data processing is the Raspberry Pi 
Development Board. It is a micro-computer motherboard 
based on ARM (shown in Fig.2), and the board contains an 
arm cortex A53 microprocessor, then the main frequency is 
1.2GHz. It provides a 10m/100m Ethernet socket and four 
USB connectors, uses a normal SD card as a hard drive, 
supports C, C++, python and other development languages. 
The above parts are integrated in a motherboard, with the 
basic functions of ordinary computers, compared with the 
traditional embedded development platform such as ARM7, 
ARM9, Raspberry Pi in the development efficiency, 
operation speed, market price and so on have obvious 
advantages. 
 
Figure 2. Raspberry Pi 3B Development Board 
III. DATA ACQUISITION AND READING PRINCIPLE OF 
SPECTROMETER 
A. Principle of data acquisition 
The data acquisition of portable UV spectrometer is a 
process of collecting frames. When the spectrometer has 
collected a frame of data, will collect the spectral data into a 
queue, waiting for the Raspberry Pi sent instructions to read, 
and the Raspberry Pi reading spectral data is the process of 
USB or serial communication. The data read from the 
spectrometer is derived from the photoelectric conversion 
(CCD) module. The photoelectric conversion module used in 
the Maya 2000 pro series spectrometer is a thin photoelectric 
conversion (CCD) array on the back of the science level. 
 
 
International Journal of Advanced Network, Monitoring and Controls          Volume 03, No.03, 2018 
72 
 
Figure 3. Data reading sequence diagram of spectrometer 
The data reading sequence of UV spectrometer is shown 
in Figure 3. The spectrometer first receives the external 
triggering signal (high level, 100ns), at the same time, starts 
triggering the delay signal (low level), resets the CCD signal 
(low level signal), integration time signal (high level), and 
the data reads the signal (low level), Idle time signal (low 
level), after receiving the external trigger signal again, then a 
data acquisition process is over, and the collected data is 
stored in memory. 
B. Principle of data reading 
 
Figure 4. Schematic diagram of data reading of spectrometer 
 
International Journal of Advanced Network, Monitoring and Controls          Volume 03, No.03, 2018 
73 
One of the most important components of the UV 
spectrometer is the high-speed single-chip microcomputer. 
High-speed single-chip computer has a USB port (square 
port, USB2.0, mini B-type 4-Pin) and serial port two 
interface (serial port for the 30-PIN Ocean Spectrometer 
special interface) [4]. 
The data reading process and principle of UV 
spectrometer are as follows: 
First, the optical components of the ultraviolet light 
processing, ultraviolet light through the slit to the collimating 
mirror, after collimation, the grating is assembled onto the 
CCD after the grating is divided, and the photons with 
different wavelengths will hit the different CCD pixels after 
the light is divided, and then the CCD element converts the 
ultraviolet signal into the electrical signal. This completes 
the spectrometer and the detection function. The signal 
information obtained from the data will be stored in the 
memory, then, the raspberry pi is connected with the 
spectrometer through a USB port, and the raspberry and 
spectrometer communicate with each other through the USB 
interface. Finally, the raspberry sent to the spectrometer 
internal high-speed microcontroller to send instructions, and 
high-speed SCM will be based on instructions, from the 
memory to obtain relevant information, and return the 
information to the raspberry pi. 
IV. RASPBERRY PIE DEVELOPMENT ENVIRONMENT 
CONFIGURATION AND SOFTWARE PROGRAMMING 
A. Python-seabreeze Package Working principle 
 
 
Figure 5. How Python reads the Data development package works 
 
The Python-seabreeze package is a two-time 
development package developed by the Python language on 
the spectrometer and is the easiest way to access the 
Maya2000pro-type Ultraviolet spectrum analyzer in Python 
language. It communicates with the spectrometer using the 
Seabreeze Library provided by Ocean Optics. Any command 
sent by the raspberry pie to the ultraviolet spectrometer will 
use and rely on the Seabreeze library. Python-seabreeze is 
available as a prebuilt package on windows, Linux, macOS 
platforms in Python 2.7.x, 3.5.x, 3.6.x, and more. The 
package supports communication through the Cseabreeze 
backend with the Maya2000pro Series Ultraviolet 
spectrometer. In Figure 5, the Libseabreeze is a C + + 
language library ported from the Seabreeze 2.0 API. The 
back end is packaged for the Seabreeze Library and uses the 
Ocean Optics Open Source Seabreeze 2.0 API (using the 
"SeaBreezeAPI.h") interface. Almost all commands, such as 
the Format command for communication with the 
spectrometer, are completed in the C/S library. As shown in 
Figure 5, the Python language reads the data of the 
ultraviolet spectrum spectrometer through the Python 
programming interface provided by Python-seabreeze, and 
invokes Cseabreeze to read data from the ultraviolet 
spectrometer through the Libseabreeze library. 
B. Raspberry PiDevelopment environment configuration 
(Raspberry Pi Development Board configuration 
environment must be networked) 
 
International Journal of Advanced Network, Monitoring and Controls          Volume 03, No.03, 2018 
74 
1) Install the Python environment on Linux 
The typical Linux system has a Python environment and 
is already configured. If not, you will install it by yourself. 
Python 2.7 is used in this article. 
2) Install Python-seabreeze Package 
Method One: In the Linux Terminal Command Window 
input command (raspberry pie must be networked, 
Python-seabreeze installation process is longer, please wait 
patiently): Conda install-c Poehlmann Python-seabreeze, The 
raspberry pie will then download the Python-seabreeze and 
install the configuration automatically. 
Method Two: Download the Python-seabreeze 
installation package from the Internet, then copy the 
installation package to the installation directory, execute the 
python setup.py command in the command box, and install 
the configuration automatically. 
After completion of 3.1.1 and 3.1.2, the installation 
environment is configured. Because of the use of raspberry 
pie, so here is the recommended installation 
Berryconda3-2.0.0-linux-armv7l,berryconda3 itself is a 
Python development package, and contains a large number 
of scientific calculation package, easy to install Third-party 
expansion pack (can use Conda for rapid upgrade), support 
Cross-platform operation, easy program migration, improve 
development efficiency, and this will also automatically 
install the modules and dependencies required for the 
Cseabreeze backend, saving a lot of time. 
 
C. How Python reads data works 
 
Figure 6. Data Reading flowchart 
When the raspberry pie is reading the spectrometer data, 
it first reads the relevant information of the spectrometer 
equipment, and if it reads the equipment information of the 
spectrometer, initializes the spectrometer equipment, sets the 
integration time and so on; If you do not read the 
spectrometer device information, you will restart and read 
the spectrometer device information, cycle, until the device 
information is read. Second, after the spectrometer 
equipment initialization completes, the software starts to 
read the spectral data, and the basic data which reads from 
the spectrometer is the light wavelength and the photon 
number. This completes the spectrometer equipment data 
reads the work. 
D. Raspberry Pie Data Read part of the code as follows 
#Introduce related packages and device definitions 
importseabreeze. spectrometers as sb#Introduction of 
Python-seabreeze Two development kits 
devices=sb.list_devices()   #Define spectrometer 
equipment 
spec=sb. Spectrometer(devices[0]) 
 
#Device information 
printspec.serial_number  #Print output spectrometer 
factory serial number 
International Journal of Advanced Network, Monitoring and Controls          Volume 03, No.03, 2018 
75 
printspec.model  #Print output spectrometer model 
printspec.pixels  #Print output spectrometer number of 
pixels that can be read at a time 
 
#Spectrometer Data acquisition 
spec.integration_time_micros(10000) #Set the 
spectrometer integration time 
x=spec.wavelengths() 
print x    #Print spectrometer wavelength data 
y=spec.intensities()   #Print spectrometer photon 
Number data 
 
#Drawing images using the readout wavelength and 
photon number 
importmatplotlib.pyplot as plt 
plt.plot(x,y,color="green",linewidth=2) 
plt.xlabel("wavelengths") 
plt.ylabel("integration") 
plt.savefig("test2.png",dpi=120) 
plt.show() 
The drawing results are shown in the following 
illustration: 
 
Figure 7. Wavelength of dark spectrum and photon number 
 
Figure 8. Wavelength of light spectrum and number of photons 
Figures 7 and 8 are images drawn from the data (photon 
number and wavelength) that are read from the ultraviolet 
spectrometer. Fig. 7 is an image of the dark spectral 
wavelength and the number of photons, and fig. 8 is the 
wavelength of the light spectrum and the number of photons 
(the horizontal axis is the wavelength and the longitudinal 
axes are photon numbers). 
Dark spectrum, which means that without an external 
light source, and the spectral line caused by dark current in 
the CCD of Ultraviolet spectrometer, when the ultraviolet 
spectrum is actually carried out, the number of photons 
measured by the detected gas needs to be reduced by the 
number of dark photons in order to get the actual photon 
number of the detected gas. It is shown from Fig.7 that the 
number of dark spectral photons is about 2,800, and the 
number of photons is related to the ambient temperature. 
E. Software Simulation 
The application is programmed with the Python Qt GUI. 
After writing, then the software is simulated and tested on 
the raspberry pie to verify that the software function meets 
the design standard, and the software simulation results are 
shown in Figure 9. Finally, the raspberry pie and 
spectrometer were debugged online (Fig.10). 
International Journal of Advanced Network, Monitoring and Controls          Volume 03, No.03, 2018 
76 
 
Figure 9. Software Run interface 
 
Figure 10. Hardware and software online debugging 
V. CONCLUSIONS 
This paper mainly introduces the working principle of 
micro Ultraviolet spectrometer, data reading and so on, using 
the developed software after a long time test test shows: the 
theoretical analysis is correct, and the software has been 
written to achieve the raspberry pie from the 
micro-ultraviolet spectrometer read data, and work stable, 
fast, friendly interface, anti-interference ability, easy to 
operate and master. The system takes the raspberry pie as the 
core, realizes the data reading through two times 
development package, and carries on the software 
development through the python. The system has the 
advantages of short development cycle and stable operation, 
and achieves the practical goal. Next, based on this, the gas 
iterative algorithm is studied, and the actual concentration of 
various gases is calculated by using an iterative algorithm for 
the photon number read by the raspberry pie from the 
ultraviolet spectrometer. 
VI. ACKNOWLEDGMENT 
The authors wish to thank the cooperators. This research 
is partially funded by the Project funds in shanxi province 
department of education (15JF019) and the Project funds in 
shanxi province department of science industrial 
projects(2015GY067). 
 
REFERENCES 
[1] Xu Shuping, Lichao. Portable smoke analyzer based on arm [J]. 
Computer measurement and control. 2011.19 (7): 1788-1790 
[2] Lei Tianxue. Status of portable flue gas analyzer [J]. Environmental 
monitoring management and Technology, 1998, (4): 19. 
[3] Shi Baosong, Sun Shouhong, Zhang Wei. Application of CCD in 
Portable Spectral analyzer [J]. Electronic measurement Technology, 
2010 (11): 84-86 
[4] Juwu ,WuYihui. Micro-miniaturization of spectrometer [J].Journal of 
Instrumentation, 2003. 22 (4): 131-133 
[5] Yu Zhiqiang, Wenzhi Yu, XieYingke, Zhou Suyi. The control system 
of multi-parameter water quality tester based on raspberry pie [J]. 
Instrumentation technology and Sensors, 2015 (06): 20-23. 
[6] Han Xiao, Wenzhi Yu, XieYingke, Wei Kanglin, Zhou Xiaofeng. 
Software design of control and signal processing system for 
multi-parameter water quality tester [J]. Instrumentation technology 
and Sensors, 2014 (08): 20-22 
[7] Lichao. Design of a portable Smoke analyzer controller based on 
ARM [D]. Xian: Xi ' an University of Technology, 2012 
[8] Zhang Yi. Design of portable multifunctional flue gas analyzer [D]. 
Xian: Xi ' an University of Technology, 2012. 
 


English

Readings of Portable UV Spectrum Analyzer Data Based on Raspberry Pi

Liu, Feibi

International Journal of Advanced Network, Monitoring and Controls         Volume 03, No.03, 2018 
DOI: 10.21307/ijanmc-2019-011                       93 
Cheap and Simple Slip Sensor Based on the Optical Sensor 
Feibi Liu 
University of Southampton, Southampton, UK, SO17 1BJ 
e-mail: 2496909486@qq.com 
 
Abstract—The purpose of this project is to manufacture a 
cheap and simple slip sensor. The slip sensor is based on the 
optical sensor. The experiment divides into two parts, how to 
build sensor and how to test the features of the sensor. The slip 
sensor could be divided into three parts, cover, optical sensor 
and adaptor board, which will connect to the suitable resistors 
circuit to obtain the large gain. During the test, the participant 
applies the static state way to measure the relationship between 
input and output with a white cover and a gray cover. The slip 
sensor with the white cover has low hysteresis and high 
repeatability which are better than the gray cover. 
Keywords-Slip Sensor; Optical Sensor; Force Sensor; Static 
State; Reflective Object Sensor 
I. INTRODUCTION 
When humans try to grasp an object, they do not need to 
know the parameters (like mass) of the object. They just 
control the force of the hand which ensures the object will 
not fall by human ‘feeling’. For the robot hand, the slip 
sensors which fix on the fingertips could give the feedback 
(it is like human’s feeling) to the CPU which could control 
the force of the robot hand [1]. In a sense, the slip sensor is a 
kind of the force sensor, because the feedback of the slip 
sensor is related to the force which puts on the surface of slip 
sensor. Only different is the slip sensor focuses on the force 
changing between the object slipping and not slipping. 
There are many kinds of methods to build a slip sensor or 
a force sensor, which bases different theories. At the 
beginning, Luo used piezoresistive strain gauge on the robot 
links to detect the force and this was used in this field for a 
long time. However, this structure was a little complex 
comparing the new ways [2]. Cristina Cristalli and Michael 
R Neuman designed a kind of force sensor by changing the 
capacitance in dielectric structure[3].They used this sensor to 
measure the blood pressure and gain a good ratio between 
the input and output. However, in the experiment, they also 
found that the ratio between the input and output would 
change a little when they used the same way to build a same 
standard sensor. The reason is the different stray 
capacitances in the environment. Piezoresistive is very 
popular in industry and research field because of low cost, 
small and light-weight. However, piezoresistive exists low 
repeatability and large hysteresis, which will cause the low 
accuracy. L.Paredes-Madrid group improved the accuracy of 
piezoresistive by modeling the capacitance. Nevertheless, 
they still needed to consider how to reduce the force 
estimation errors [4]. Lorenzo Jamone and his group 
designed a kind of tactile sensor that based on the hall-effect 
theory. This sensor detected the changing of the magnetic 
field when the force pushed on the sensor to give a feedback 
to control. After the experiment, they found this kind of 
sensor had high sensitivity, low hysteresis, and good 
repeatability, but the experiment just tested the force on 
normal component [5]. 
Samir Boukhenous and Mokhtar Attari also used the 
Hall-effect theory to produce a pinch grip sensor, which had 
a good response to input and output. However, the 
experiment also focused on the normal direction [6]. Darko 
Belavic and his group completed an experiment about the 
low energy consumption of different types of pressure 
sensors which included the piezoelectric sensor. This 
piezoelectric sensor was based on the performances of the 
ferroelectric thick films, which could transform the pressure 
into shifted resonant frequency of diaphragm which could be 
regarded as an output signal. They concluded that the 
piezoelectric resonant sensor was suitable for low energy 
consumption and the energy consumption was mainly 
International Journal of Advanced Network, Monitoring and Controls         Volume 03, No.03, 2018 
94 
dependent on materials and structures, but it was not sample 
work to reduce consumption because of complete 
relationships between every component in sensor [7]. 
Shouhei Shirafuji and Koh Hosoda developed a robot hand 
which combined the strain gauge sensor and piezoelectric 
polyvingylidenefluoride (PVDF) sensor to measure stresses 
and detect slipping. The PVDF sensor could detect the 
variations of the force which was caused by the slipping of 
the object. However, the PVDF sensor needed the high 
reactive ability and high resolution to detect the slipping [8]. 
A. Persichetti, F. Vecchi and M. C. Carrozza, presented a 
contact sensor using optical theory, which based on detecting 
the changes of the light beams intensity. Figure 1 showed the 
structure of this kind of sensor, which included a soft silicone 
cover, a receiver (a phototransistor) and a transmitter (an 
infrared photodiode). When the force pressured on the cover, 
the intensity of the light which reflects the receiver will 
change. Therefore, this sensor has high sensitivity, fast 
response and could enhance the immunity to noise by 
adjusting the light intensity from the transmitter [9]. 
 
Figure 1. The structure of the optical sensor 
For this paper, the participant will utilize the optical 
theory to build a cheap, simple and low consumption slip 
sensor. Because the photodiode needs to emit high intensity 
light, the optical sensor will cost high consumption 
compared with other sensors [10]. Therefore, the participant 
tried to find a good material which could reduce the loss 
during reflecting, which could reduce the requirement of the 
light intensity which is emitted by the photodiode. This could 
reduce the consumption. For obtaining a good response, the 
participant also chooses suitable resistors to get large 
amplifier gain. Comparing with an optical sensor which is 
built by A. Persichetti and his friends [9], the most different 
in this paper is the participant use cast Perspex acrylic sheet 
to replace silicone (showing figure 1) as the cover. Because 
the cast Perspex acrylic sheet is harder than silicone, this 
replacement could increase the robustness of the sensor. 
However, this also means the slip sensor may sacrifice some 
sensitivity. 
II. METHODOLOGY 
The purpose of the experiment is to produce a cheap, 
simple and low consumption slip sensor. Therefore, the 
experiment could be divided into two parts, the first part is to 
build the slip sensor and the second part is to test the slip 
sensor as figure 2. 
 
 
Figure 2. The slip sensor with resistors 
A. Design 
The slip sensor includes three parts, cover, optical sensor 
and adapter board. Figure 3 shows the slip sensor. Therefore, 
first step, the participant needs to choose a suitable optical 
sensor. 
International Journal of Advanced Network, Monitoring and Controls         Volume 03, No.03, 2018 
95 
 
Figure 3. The slip sensor 
The QRE1113RG-Minature Reflective Object Sensor is 
used as the optical sensor because it is mini. As Figure 4 
showing, the photodiode (transmitter) which is between the 
pin 1 and pin 2 emits the light and the phototransistor 
(receiver) which will receive the reflected light from the 
cover is fixed between pin 3 and pin 4 [11].  
 
 
Figure 4. The structure of the QRE1113RG sensor 
Second step, the participant needs to produce a suitable 
cover. The cover is made by the 1mm thickness clear cast 
Perspex acrylic sheet. There are some advantages to using 
this material. Firstly, the weight is light. Secondly, the cost 
of the material is low. Thirdly, it is easy to build which just 
needs a laser cutter. Fourthly, the cast Perspex acrylic sheet 
has high tensile strength and rigidity, so it could protect the 
optical sensor which is under the cover. Fifthly, the clear 
Perspex acrylic could transmit 92% of the visible light, 
which is simple to the participant to change the color of the 
cover and detect the influence of the color of the cover [12]. 
Figure 5 shows the blueprint of the cover. Figure 6 shows the 
cover after gluing. 
 
Figure 5. The cover's blueprint 
 
 
Figure 6. Cover 
Third step, solder the optical sensor on the adapter board 
as the figure 7.  
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96 
 
Figure 7. The optical sensor with adaptor 
 
 
Figure 8. The circuit's schematic structure 
Fourth step, choose the suitable resistors to build the 
circuit. Figure 8 shows the equivalent circuit diagram. RF is 
used to keep the photodiode (transmitter) working in the 
ideal voltage range. RC is to amplify the voltage signal. 
According to the specification of the QRE1113RG, the 
participant assumes IF =0.028A, which could ensure the 
photodiode work well at room temperature. 
 
Figure 9. Forward current VS Forward Voltage 
From figure 9, the forward voltage (VF ) should be about 
1.33V. According equation 1,RF=168Ω. 

Because the participant wants to get the largest reflection 
light from the cover, the participant puts a white thin paper 
on the top of the cover during the test. The distance between 
the top surface of the cover and the top surface of the optical 
sensor is about 2mm. According to the figure 10, it could 
easy find that the real collector current IC is 0.45 which is 
half of collector current at distance 1mm.  
 
Figure 10. Normalized Collector Current VS Distance between 
When IF =0.028A and distance is 1mm, the collector 
current is around 1.08mA in according specification, so the 
real collector current IC is0.54mA. Assume the 
collector-emitter voltage (VCE) is 3.3V which could get 
International Journal of Advanced Network, Monitoring and Controls         Volume 03, No.03, 2018 
97 
larger gain. Using the equation 2 gets the collector resistor 
(RC= 5000Ω). 

B. Test 
These devices were applied in the experiment. EL 155R 
Power Supply (6V and 0.028A);Amprobe 30XR-A 
multimeter; Compression testing machine;MDO4054B-3 
Mixed Domain Oscilloscope;HMC 8012 digital Multimeter. 
Figure 11 shows the schematic during testing.  
 
Figure 11. The assembly schematic 
First step, the participant put a white paper on the cover 
to detect the relationship between the force and voltage. 
Because the output voltage was more than 2V which is 
exceed the range of the Amprobe 30XR-A multimeter, the 
second power supply gave 1V reverse voltage as the offset 
voltage. Second step, the participant put a weight (1 N) on 
Compression testing machine and recorded the voltage. 
Third step, repeated step 2 until there were six weights (6N) 
on the machine. Fourth step, took the weight (1N) one by 
one from the machine and recorded the voltage after each 
operation. After these steps, one group of data was 
completed. To obtain stable data, the participant repeated 
five times of these steps and got five groups of data. 
Next, the participant changed the color of the cover into 
gray, which just put nothing between the probe and cover, 
because the probe is in gray. Then, used the same way to get 
five groups of data. The output voltage is not more than 2V, 
so the offset voltage does not need. The second power supply 
is 0V. 
III. RESULT AND ANALYSES 
Figure 12 and figure 13, show the relationship between 
the output voltage and force using white cover. The trend 
line in each figure could quantize the relationship between 
the output and input. The R-square shows on each figure 
mean the reliability of the trend line. When the value is more 
near the 1, the points should more near the trend line. 
Usually, when the value is larger than 0.75, the trend line 
could predict the relationship between the input and output. 
In each of figure 12 and figure 13, the R-square is larger than 
0.98, which means the trend line has high predictability. 
From these two figures, it is easy to find that the coefficients 
of these two trend lines are close. Therefore, the sensor has 
low hysteresis and high repeatability in white color. The 
offset voltage is around 2.77V, which is a little high. The 
reason is that the white color reflects almost light which 
enhances the power that phototransistor received. 
 
 
Figure 12. Meaning of Voltage Vs Force when force is increasing 
 
International Journal of Advanced Network, Monitoring and Controls         Volume 03, No.03, 2018 
98 
 
Figure 13. Meaning of Voltage Vs Force when force is reducing 
Figure 14 and figure 15 show the relationship between 
the output voltage and force using gray cover. However, it is 
easy to find that the R-square in these two figures is much 
lower than figure 12 and figure 13. The reason is that the 
features of the optical sensor between collector current and 
distance getting from the specification are based on the white 
paper. All assumes are also based on that condition, using 
white paper (90% reflective). Therefore, the accuracy of the 
trend line is low during using gray cover. However, the gain 
using gray cover (around 0.01) is two times than the gain 
using white cover (around 0.005). The participant speculates 
one of group data in figure 14 and 15 is not reliable. From 
the figure 14 and figure 15, the max output points are much 
higher than average output points, because one group of the 
value is much higher than others. This may be caused by 
hysteresis. Nevertheless, to ensure the authenticity of the 
experiment. The participant still recorded this group of value. 
 
 
Figure 14. Meaning of Voltage Vs Force when force is increasing 
 
Figure 15. Meaning of Voltage Vs Force when force is reducing 
IV. CONCLUSIONS 
During the experiment, the participant used a cheap and 
simple way to build a slip sensor. The participant also found 
that white cover of the sensor has high repeatability, low 
hysteresis, and high predictability. However, the gray cover 
of the sensor has low repeatability and low accuracy. 
Comparing with other slip sensors which use the optical 
theory, this slip sensor has high robustness. 
In the test, the participant used static state way to test the 
feature of the slip sensor, which could obtain the quantized 
function information between input and output. However, in 
the future work, the participant could improve the 
experiment from these two aspects. First one, the participant 
should try to detect the response of slip sensor in the 
dynamic state which means the object is slipping on the 
sensor. Second one, the participant should design a black box 
to control the external light. This could help the participant 
understand the influence of the light in the environment to 
the sensor cover and find a high resistance of cover to the 
external light. 
 
REFERENCES 
[1] Paul H Chappell, Darryl P J Cotton, Andy Cranny and Neil M White 
“EXPERIMENTAL LEAD ZIRCONATE TITANATE (PZT) SLIP 
SENSOR”, MEC '08 Measuring Success in Upper Limb Prosthetics, 
Aug.2008 
[2] R. Luo, “A Microcomputer-Based intelligent sensor for Multiaxis 
Force/Torque Measurement”, in IEEE Transactions on Industrial 
Electronics, vol. 35 pp. 26-30. February 1998. 
[3] C. Cristalli and M. R. Neuman, “A capacitive pressure sensor for 
measurement of interfacial pressure between a sphygmomanometer 
cuff and the arm," Engineering in Medicine and Biology Society, 
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99 
1995., IEEE17th Annual Conference, Montreal, Que., 1995, pp. 
1541-1542 vol.2.  
[4] L. Paredes-Madrid, L. Emmi and P. Gonzalez de Santos, "Improving 
the performance of piezoresistive force sensors by modeling sensor 
capacitance," 2010 IEEE International Symposium on Industrial 
Electronics, Bari, 2010, pp. 458-463.doi: 10.1109/ISIE.2010.5637681 
[5] L. Jamone, L. Natale, G. Metta and G. Sandini, "Highly Sensitive 
Soft Tactile Sensors for an Anthropomorphic Robotic Hand," in IEEE 
Sensors Journal, vol. 15, no. 8, pp. 4226-4233, Aug. 2015. doi: 
10.1109/JSEN.2015.2417759 
[6] S. Boukhenous and M. Attari, "An easy made pinch grip sensor to 
quantify fingertip pressure," 2008 2nd International Conference on 
Signals, Circuits and Systems, Monastir, 2008, pp. 1-3. doi: 
10.1109/ICSCS.2008.4746929 
[7] D. Belavic et al., “Low energy consumption thick-_lm pressure 
sensors," Microelectronics and Packaging Conference, 2009. EMPC 
2009.European, Rimini, 2009, pp. 1-6. 
[8] S. Shirafuji and K. Hosoda, “Detection and prevention of slip using 
sensors with different properties embedded in elastic artificial skin on 
the basis of previous experience," Advanced Robotics (ICAR), 
201115th International Conference on, Tallinn, 2011, pp. 459-464.  
[9] A. Persichetti, F. Vecchi and M. C. Carrozza, “Optoelectronic Based 
Flexible Contact Sensor for Prosthetic Hand Application,"2007 IEEE 
10th International Conference on Rehabilitation Robotics, Noordwijk, 
2007, pp. 415-420. 
[10] P. H. Chappell, “Making sense of artificial hands,” Journal of Medical 
Engineering Technology, 2011, vol.35 
[11] “QRE1113 PDF Datasheet Reflective Object Sensor”, 
Fairchildsemi.com, 2002. 
<https://www.fairchildsemi.com/products/optoelectronics/infrared/ref
lective-sensors/QRE1113.html?keyword=QRE1113GR.> 
(01-Sep-2016). 
[12] “Perspex Design Guide - guidance for fabricators and designers. - 
Perspex", Perspex.co.uk. 
<http://www.perspex.co.uk/technical-library/brochures-and-workboo
ks/perspex-design-guide/> (01- Sep- 2016). 
 


Cheap and Simple Slip Sensor Based on the Optical Sensor

Chen, Jie

Zhao, Li

Image Transformation Based on Generative Adversarial Networks

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