Color sorting machine using color light to frequency converter
- 1. Color sorting machine using color light to frequency converter Assia HAMZA assia.hamza@etu.usthb.dz Merwan KHENAK merwan.khenak@etu.usthb.dz University of science and technology Houari Boumediene BP 32, El Alia, Bab Ezzouar, 16111 Algiers, Algeria Department of instrumentation and control December 20, 2018 Abstract In our daily life, our vision and actions are influenced by an abundance of geometry and color infor- mation to identify a technical apparatus for identification. Only by analyzing color information do we subsequently decide whether we are to continue. In the industry, color processing is gaining a greater importance in digital signal processing. With technological advancement optical sensors for reading operations in the visible spectrum with inte- grated electronic readout circuits are getting affordable, that’s why we chose to use a low cost color light to frequency converter to build a color sorting machine. Our project was made in for pedagogical use but a further development using robust materials and compo- nents could lead to an industrial color sorting machine for a use in the color sorting industry of recyclable materials. Keywords : Color sorting machine - Programmable color light to frequency converter - TCS230 - Op- tical detector - Smart sensor - Arduino Robot - Colorimetry 1 Introduction Humans have been quite interested in color for many centuries. However, the scientific beginning of color studies goes back only to Newton when he performed his classic experiment with a prism. Light is a narrow range of electromagnetic waves that the eye can detect. Electromagnetic waves can have many different wavelengths and frequencies in a range known as the electromagnetic spectrum. Different wavelengths of light produce different perceptions of color. The longest wavelengths produce the percep- tion of red, while the shortest ones produce the percep- tion of violet. The spectrum in the visible, ultraviolet (UV), and infrared (IR) regions is classified in a spec- ified way. The measurement of color is a very important issue with applications in many types of industrial activi- ties. The light to frequency converter TCS230 is a small, highly integrated color sensing device packaged in a clear plastic 8-pin. It reports, as analog frequency, the amount of short-wave (blue), medium-wave (green), long-wave (red), and wideband (white) optical power incident onto the device. It can be used in a variety of color sensing applications. In our case we use it to command a smart color sort- ing machine with Arduino Nano controller. We tried to make the most compact prototype and give it a prac- tical use. We are going to introduce you how we made a color sorting machine that which sorts bottles caps in different boxes. 2 Materials and methods In our project we only use Arduino Software IDE, but a multitude of hardware components such as : Light to frequency converter TCS230 : The TCS3200 programmable color light-to-frequency converter combines configurable silicon photodiodes and a current-to-frequency converter on a single monolithic CMOS integrated circuit. The output is a square wave with frequency directly proportional to light intensity (irradiance). The full-scale output fre- quency can be scaled by one of three preset values via two control input pins. Digital inputs and digital out- put allow direct interface to a microcontroller or other logic circuitry. Output enable (OE) places the output 1
- 2. in the high-impedance state for multiple-unit sharing of a microcontroller input line. In the TCS3200, the light-to-frequency converter reads an 8*8 array of pho- todiodes. Sixteen photodiodes have blue filters, 16 photodiodes have green filters, 16 photodiodes have red filters, and 16 photodiodes are clear with no fil- ters. The four types (colors) of photodiodes are inter- digitated to minimize the effect of non-uniformity of incident irradiance. All photodiodes of the same color are connected in parallel. Pins S2 and S3 are used to select which group of photodiodes (red, green, blue, clear) are active. The benefits and features of TCS3200 Programmable Color Light-to-Frequency Converter are that it : - Enables High-Resolution Conversion of Light Inten- sity to Frequency. - Disables the Output into a Hi-Impedance State when OE Input Pin is Low. - Enables Output Range to be Optimized for a Variety of Low-Cost Measurement Techniques. - Reduces Board Space Requirements while Simplify- ing Designs. - Nonlinearity Error Typically 0.2 at 50kHz. - Communicates Directly with a Microcontroller. The functional blocks of this device are shown below in figure 1: Figure 1: Functional blocks of the TCS3200 And the TCS3200 pin assignments are described below in figure 2: figure 1: Figure 2: TCS3200 pin assignments Arduino Nano Arduino Nano is a small microcontroller good for compact prototypes, it comes with a crystal oscillator of frequency 16 MHz. It is used to produce a clock of precise frequency using constant voltage. Two Sg90 servo motor We chose this specified servo motor because it is the lightest on sale. It weights 90g and its engine couple is up to 1,6 kg.cm on 4,8 Vcc ideal for our compact prototype. we use two servo motors one on the top and the 2nd at the bottom. The top servo is used to bring the bottle caps under our sensor, and the second servo is used to deliver the bottle cap to the exact box of it’s color. 5V AC power battery We chose to make an on-board power supply system to power our electronics easily anywhere we want to expose our prototype. Switch To disconnect or connect the conducting path in an electrical circuit, interrupting the electric current or di- verting it from one conductor to another and make the machine ON or OFF. Breadboard The breadboard lets you easily insert electronic com- ponents to to build and test an early version of the elec- tronic circuit of the prototype. Wires It is necessary to connect our components in order to make communication. We connect the components together according to the following circuit schematics in figure 3: Figure 3: Schematics of the color sorting machine The most important part beside the schematics is how we calibrate the program to order the servo motor to move for each color a specified direction. So we chose 3 different colors bottle caps, red, white and blue. 2
- 3. We pass each color under the sensor different times and each time in the arduino real time monitor we reg- ister the RGB colors variations for each bottle cup. By recovering these datas we can put in our program spec- ified RGB variation for each bottle cap color so the servo motor moves to the correct wanted position each time the sensor detects a bottle cap. 3 Results The final machine prototype made is illustred in fig- ure 4: The manner how it mechanically works is that nitially, the colored bottle caps which are held in the charger drop into the platform attached on the top servo motor. Then the servo motor rotates and brings the colored bottle caps to the color sensor which detects its color. After that the bottom servo motor rotates to the partic- ular position and then the top servo motor rotates again till the skittle drop into the guide rail. Figure 4: Our final color sorting machine prototype 4 Conclusion An automated color sorting machine was made at the end of this project. Using color to frequency converter sensor technology we learned how to make a low cost equipment. It’s important to admire how much sensor supplements technology has developed in the last decade, and it’s all fun to learn how to deal with it. Color perception is so important for human interac- tions, so as the industry. So making intelligent auto- mated machine that can do tasks alone is a big invest- ment of time for industries. As many applications in the future require sensor systems we want to participate in the creation of those systems, and we won’t be able to achieve our goals unless we master a variety of sensors. Acknowledgement The authors would like to express their special thanks of gratitude to mr Dejan Nedelkovski founder of ’How to mecatronics’ who made this work open source to everyone wanting to learn about it. 3
- 4. References Gaurav Sharma 2003, Electrical engineering and applied signal processing series, Digital Color Imaging Hand- book Andreas Koschan, Mongi Abidi 2008, Digital color image processing Christine Fernandez - Maloigne 2013, Advanced Color Image Processing and Analysis Asch, Georges 2015, Acquisition de donnees : Du capteur aa l’ordinateur David C. Swanson 2000, Signal Processing for Intelligent Sensor Systems Forrest M. Mims III 1996, Engineer’s Mini-Notebook: Sensor Projects Daniel Malacara 2011, Color Vision and Colorimetry THEORY and APPLICATIONS 4