Muhammad Rivai

Electronic nose based on partition column integrated with gas sensor for fruit identification and classification

We studied an alternative e-nose based on gas chromatographic system for fruit classification.Combination of partition column - gas sensor could generate a separable chromatogram profile.PCA based feature extraction can be used to improve the identification accuracy. An alternative model of electronic nose systems by applying a combination of partition column with gas sensor was investigated for fruit classification and identification. The principle of physical and chemical separation in chromatography analysis known as an interaction between stationary phase material and compounds is able to profile the flavor sample; thus it is potentially implemented to substitute function of the sensor array on the conventional electronic nose. The electronic nose consists of a sample handling with combination of solenoid valves, a packed partition column coupled with a gas sensor as detector operated under a controlled temperature and data analysis software by using a neural network. The system was tested to classify three different flavors of fruit, i.e. durian, jackfruit, and mango. The result showed that it can generate reliable and repeatable chromatograms, from which, a unique pattern among samples can be extracted. Therefore, the patterns are able to be clearly classified with the neural network. The experiment showed that it can recognize the three different flavors with the level of accuracy of 82%.

Study on Electronic-Nose-Based Quality Monitoring System for Coffee Under Roasting

Roasting process needs to be monitored and carefully controlled because it plays as the most important stage for determining flavor quality on the final product in the secondary coffee processing. Common quality monitoring method by applying parameters namely roasting time, roasting temperature and grain color may have disadvantages especially for nonuniform quality of green beans and stirring mechanism of regular roasters; therefore, an alternative quality monitoring model is necessary. Because emitted vapor during roasting may represent the occurred reaction stage, it is possible to indicate the roast degree of the coffee grain. This study evaluated the application of an electronic nose based on semiconductor sensor array for quality monitoring of coffee roasting. The electronic nose designed with gas sensor array was integrated to a mini batch coffee roaster. Data including sensor array response, vapor humidity and temperature were recorded in line to the roasting process and compared to the coffee grain color measured with a universal colorimeter. The experiment showed that the gas sensors respond to the emitted coffee flavors, from which a logarithmic profile as a function of grain color was obtained with the highest slope of −1.6V/color difference of roasted coffee. Aroma patterns obtained from sensor responses were then analyzed with principle component analysis (PCA), by which a distinctive profile between initial and final phases of roasting is obtained. Although the corresponding analysis is still unable to distinguish the levels of light, medium and dark (LMD); high sensor responses indicate a further benefit of this system for developing an analogous quality monitoring system.

Design and implementation of a submerged capacitive sensor in PID controller to regulate the concentration of non-denatured ethyl alcohol

Ethyl alcohol (ethanol) is one of the most common organic compounds used in medical and industrial applications. Because of its human amiability, ethanol has become a perfect solvent for organic matter with varying concentration levels for different purposes. Nevertheless, ethanol has a unique character that makes it evaporates at a level of temperature, which is called flash point. Storing ethanol above its flash point would reduce its concentration as well as its functionality. In this research, a device has been developed to control ethanol concentration in water. The concentration of ethanol is measured based on the signal of a square wave oscillator connected to a cylindrical aluminum capacitive sensor. Thus, the output frequency is imputed to a microcontroller programmed as a PID controller to produce the control signals that are used to operate two peristaltic pumps connected to two reservoirs containing non-denatured ethanol and distilled water, respectively. Magnetic stirrer is added to improve the dilution process. Overall, the designed sensor is able to identify various levels of ethanol concentration from 0.0-0.9 m3/m3. Furthermore, the implemented controller is capable to maintain the volumetric concentration of ethanol with set point ranging from 0.0-0.5 m3/m3 within 90% of success rate.

Identification of cracking sound during coffee roasting using neural network

Many methods of coffee roasting in the market today are only based on the temperature in the certain time period. However, if the coffee beans have no uniformity in size, weight, and moisture, the roasting process will not produce the consistent results. In this study, the measurement and identification of cracking sounds of coffee beans under roasting are applied to determine the temperature control mechanism. Roaster uses an oven-type controlled by heating element at a temperature of 260°C. In the roasting process, there are the first and second cracking sounds in the time span of 3–10 minutes. Voice Activity Detection is used to identify the cracking sound using Fast Fourier Transform to determine the starting point of sound recording. The data would be learned by the Neural Network to recognize the cracking sounds automatically. The Neural Network can obtain the best result during the period of 1-second recording with success rate of 100%.

Mixed vapour identification using partition column-QCMs and Artificial Neural Network

This Paper presents the identification of mixed vapour using electronic nose system composed of Quartz Crystal Microbalance (QCM) sensor array and a partition column of gas chromatography. The polymer coated QCMs produced a specific frequency shift. The data set was processed by an Artificial Neural Network using Backpropagation algorithm as a pattern recognition. The result showed that this equipment was able to identify five types of vapours namely benzene, acetone, isopropyl alcohol, non-polar and polar mixture (i.e. benzene and acetone), and also polar and polar mixture (i.e. isopropyl alcohol and acetone) with the identification rate of 96%.

Implementation of fuzzy logic control in robot arm for searching location of gas leak

It is a problem for humans to search and check the source of gas leakage containing poisonous, inflammable or exploding gas. In this research, a robot arm for searching the location of gas leak has been developed. The robot arm is designed for three degrees of freedom equipped with four metal oxide gas sensors. The evaporating liquid ethanol is used as gas source to simulate the gas leakage. A fuzzy logic control system is applied to navigate the robot arm to locate the gas source. The experiment result showed that the robot arm is able to find the gas source in three different locations with accuracy is over 90% and response time is under 10 seconds.

Pengarah Suara Pada Sistem Audio Berdasarkan Beda Phasa

Pemberian informasi seperti pengumuman, ceramah, dan musik sering dilakukan dalam berbagai acara yang memerlukan ruangan yang luas. Supaya pemberian informasi hanya mencapai target yang dituju dan tidak mengganggu pengunjung lain maka suara harus diarahkan untuk lokasi tertentu. Pada penelitian ini telah dilakukan sebuah perancangan dan realisasi sistem deret speaker dimana intensitas sinyal suara dapat diarahkan dengan sudut kemiringan antara -90o sampai 90o. Untuk menghindari munculnya intensitas suara pada arah yang berlawanan maka jarak antar titik pusat speaker untuk frekuensi 2Khz adalah 8,6 centimeter. Pengarahan suara dilakukan dengan cara memberikan waktu tunda di setiap speaker dengan menggunakan Field Programable Gate Array ALTERA DE-2. Sinyal audio dikonversi dengan menggunakan Analog to Digital Converter 24-bit. Waktu tunda tersebut dihasilkan dengan menggunakan sub program 8-bit D flip-flop dengan clock input sebasar 1 mikro detik. Data pengujian dengan menggunakan osiloskop menunjukkan untuk waktu tunda pada beda phasa 90o sampai 90o memiliki rata-rata kesalahan 3,5%. Data hasil pengujian lobe deret speaker menunjukkan rerata kesalahan pengarahan suara sebesar 19%. Sistem dapat diterapkan pada berbagai acara komersil sehingga meningkatkan efisiensi penggunaan daya dan mengurangi noise lingkungan.

Sistem Pendeteksi Kepatahan Mata Bor pada Mesin Cetak PCB Berdasarkan Analisa Getaran Spindle Menggunakan Teensy Board

Pemanfaatan Computer Numerical Control (CNC) adalah salah satu bentuk penerapan teknologi industri yang membuat hasil produksi lebih presisi dan akurat. CNC juga dapat diterapkan pada proses pencetakan Printed Circuit Board (PCB) menggantikan proses pelarutan secara kimiawi yang tidak ramah lingkungan. Akan tetapi penggunaan pencetak PCB berbasis CNC memiliki risiko yakni patahnya mata bor. Pada penelitian ini telah dibuat suatu sistem pendeteksian kepatahan mata bor berdasarkan analisa getaran. Sensor yang digunakan untuk dapat mendeteksi getaran adalah MEMS accelerometer yang mempunyai kemampuan pengukuran sampai 3,6g. Untuk dapat mengenali kepatahan mata bor, perlu dilakukan pengolahan sinyal dengan menggunakan Fast Fourier Transform. Lebar spektrum frekuensi yang digunakan adalah 0-1000Hz. Pola spektrum frekuensi tersebut digunakan sebagai input Artificial Neural Network untuk dapat mengenali kepatahan mata bor. Pemrosesan Fast Fourier Transform dan Artificial Neural Network dilakukan pada Teensy 3.2 development board. Hasil eksperimen dengan kecepatan putaran spindle 30000 RPM menunjukkan bahwa Artificial Neural Network dapat mendeteksi kepatahan mata bor dengan tingkat keberhasilan 80%. Penggunaan jenis PCB yang lebih keras dapat meningkatkan keberhasilan menjadi 91.67%. Sistim ini diharapkan dapat diterapkan pada CNC sebagai pencetak PCB sehingga dapat lebih efisien pada konsumsi daya dan waktu.

Rancang Bangun Robot Omni untuk Mencari Sumber Gas Menggunakan Kontrol Logika Fuzzy Berbasis Mikrokontroler ARM STM-32

Kebocoran gas yang tidak terdeteksi dapat menyebabkan bahaya yang dapat mengancam penggunanya, seperti tejadinya kebakaran, atau meledaknya sebuah tabung gas. Untuk itu dibutuhkan sebuah metode penanganan cepat untuk mengetahui letak terjadinya kebocoran gas. Pada penelitian ini telah dirancang dan dibuat suatu Omni Directional Wheels Robot yang berfungsi sebagai gas tracker untuk mendeteksi letak kebocoran gas. Rancang bangun gas tracker ini menggunakan platform lingkaran yang dilengkapi dengan tiga buah sensor gas semikonduktor MQ-4, yang ditempatkan pada tiap 120 udut platform robot. Robot ini menggunakan sistem fuzzy logic controller yang diolah menggunakan STM32F4-Discovery. Robot ini akan mencari sumber kebocoran gas dengan menggunakan hasil pendeteksian dari sensor gas. Input fuzzy logic berupa perubahan nilai tegangan sensor gas. Pada proses defuzzifikasi dihasilkan output berupa sudut datang dan jarak sumber gas terhadap robot. Hasil deffuzifikasi kemudian akan berfungsi sebagai input gerak robot sesuai dengan perhitungan kinematika robot. Dari hasil pengujian menunjukkan bahwa robot ini dapat menuju ke sumber gas dengan nilai rata-rata tertinggi adalah 93,33 % saat sudut 210

Path planning mobile robot using waypoint for gas level mapping

The study implemented the path planning mobile robot equipped with a Global Positioning System and a gas sensor for mapping activities to detect the harmful gases in a certain location. The mobile robot was moving to some high risk places exposed to some dangerous gases on the path planning by using the waypoint. Proportional Integral Derivative controller was used to control the differential speed steering mobile robot. The experimental results showed that the average compass error was about 5% and the GPS error in navigating the waypoint was about 3 meters. Wind direction and speed exceeding 5 km/h affected the value of gas concentration reading. The system has deviation distance of less than 5 meters in following the route of the waypoint providing the information of gas levels during the trip as a source of information map.