Sistem pintar pengecaman bentuk agregat berasaskan rangkaian neural

Penghasilan sesebuah konkrit bergantung kepada kandungan agregat (batu baur) yang terkandung di dalam konkrit tersebut. Bentuk agregat-agregat yang terdapat di dalam konkrit dikatakan mempengaruhi kualiti konkrit yang akan dihasilkan. Agregat yang mempunyai bentuk yang dikatakan elok (well-shaped) akan menghasilkan konkrit yang bermutu tinggi dengan mengurangkan kadar air kepada simen di dalam konkrit. Sebaliknya, bentuk agregat-agregat yang buruk (poor-shaped) selalunya menyebabkan penghasilan sesebuah konkrit itu memerlukan kadar air kepada simen yang tinggi. Kebiasaannya, kualiti sesebuah konkrit ditentukan dengan mengira kadar peratusan kandungan agregat yang elok kepada agregat yang buruk yang terkandung di dalam konkrit. Masalah penentuan secara manual ini ialah lambat, terlalu subjektif dan memerlukan tenaga buruh yang ramai, sekaligus menyebabkan tidak efektif dan mahal. Dalam usaha untuk mengurangkan masalah ini, penyelidikan yang dilakukan telah memfokuskan kepada pembangunan sistem pengecaman pintar bentuk agregat berasaskan rangkaian neural. Sistem yang dibangunkan menggunakan teknik pemprosesan imej digital dan rangkaian neural untuk mengkelaskan bentuk-bentuk agregat yang diperolehi kepada dua kategori, "elok" dan "buruk". Sistem ini merangkumi dua bahagian utama iaitu pengekstrakan ciri-ciri imej dan pengecaman. Dalam bahagian pengekstrakan ciri-ciri imej, ciri-ciri yang dipertimbangkan ialah momen Zernike, momen Hu, saiz dan ukurlilit. Pengekstrakan ciri-ciri momen Zernike dan momen Hu dikira berdasarkan kepada saiz dan ukurlilit objek. Disebabkan momen Hu peringkat tinggi lebih sensitif kepada hingar, maka hanya momen Hu peringkat pertama dan kedua sahaja digunakan. Bagi ciri momen Zernike pula, nilai momen yang digunakan ialah jumlah penambahan nilai momen Zernike dari tertib 0 hingga tertib 4 kerana ia memberikan keputusan perkelompokan yang lebih baik. Dalam bahagian pengecaman, rangkaian neural yang dibangunkan ialah rangkaian hibrid berbilang lapisan perceptron (HMLP). Rangkaian tersebut telah dilatih menggunakan algoritma ralat ramalan berulang terubahsui (MRPE) dan memberikan prestasi pengecaman sebanyak 85.53%. Ini membuktikan sistem pengecaman bentuk agregat secara automatik yang dibangunkan berjaya mengkelaskan bentuk-bentuk agregat kepada dua kategori iaitu "elok" dan "buruk". Sebagai langkah awal untuk menghasilkan sistem pengecaman bentuk agregat mudah alih, sistem pengecaman menggunakan mikro pengawal juga telah dihasilkan dan dibuktikan keberkesanan dan kebolehpercayaannya. Sistem pengecaman yang berasaskan mikro pengawal ini telah menghasilkan peratus pengecaman yang sama nilainya dengan peratus pengecaman yang diperolehi menggunakan komputer peribadi

Modulation techniques for GPR system radargram

Ground Penetrating Radar (GPR) system ability to detect embedded object underground is dependent on the ultra-wideband antenna use. Based on this antenna type, the fractional bandwidth used by the GPR system is usually greater or equal to 1. On the other hand, the GPR system using fractional bandwidth less than 1 will produce unsmooth GPR radargram, as the consequences of high signal ripples generated in the system output signals. Based on fractional bandwidth parameter, this study focuses in developing a digital signal processing of the GPR system to produce a smooth GPR radargram. The proposed GPR signal processing system is based on envelope detector technique of Asynchronous Half-Wave (AHW), Asynchronous Full-Wave (AFW) and Asynchronous Real Square Law (ARSL). The Pulse Modulation (PM), Stepped Frequency Continuous Wave (SFCW) and Hybrid GPR system simulation are modeled using CST Studio Suite and MATLAB software. The selected fractional bandwidth of the GPR system simulation modeled is 0.46 and 0.4 for Microstrip Vivaldi and Horn antennas respectively. In addition, a practical implementation of the SFCW and Hybrid GPR system using fabricated Microstrip Vivaldi antenna having a fractional bandwidth of 0.46 and VNA equipment, was conducted. Based on the analysis results of the proposed PM GPR system simulation, the AFW technique produces clearer PM GPR radargram. The detection rate for PM GPR system simulation using AFW technique is 87% and 51.3% using Horn and Microstrip Vivaldi antennas respectively. Practical implementation of SFCW and Hybrid GPR systems using AFW technique and Microstrip Vivaldi antenna can detect an iron and a bottle filled with water object

A Design of Low Power Single Axis Solar Tracking System Regardless of Motor Speed

Solar power generation had been used as a renewable energy since years ago. Residential that uses solar power as their alternative power supply will bring benefits to them. The main objective of this paper is to present development of an automatic solar tracking system whereby the system will caused solar panels will keep aligned with the Sunlight in order to maximize in harvesting solar power. The system focuses on the controller design whereby it will caused the system is able to tracks the maximum intensity of Sunlight is hit. When the intensity of Sunlight is decreasing, this system automatically changes its direction to get maximum intensity of Sunlight. LDR light detector acts as a sensor is used to trace the coordinate of the Sunlight by detecting brightness level of Sunlight. While to rotate the appropriate position of the panel, a DC-geared motor is used. The system is controlled by two relays as a DC-geared motor driver and a microcontroller as a main processor. This project is covered for a single axis and is designed for low power and residential usage applications. From the hardware testing, the system is able to track and follow the Sunlight intensity in order to get maximum solar power at the output regardless motor speed

A comparative study on image compression method using stand-alone DWT techniques and hybrid of DWT with huffman coding technique for WSN application

The advent of wireless technologies nowadays gives high impact toward many users to communicate to each other. Wireless Sensor Net-work is a network of nodes which connect to each other by using a device. In addition, transmitting and receiving messages and files are common in most users. There are many platform of network which contributes the same aim that is communication purposes. A ZigBee network is known as one of a platform with its own Standard (IEEE 802.15.4). Unfortunately, ZigBee has a low data rate which limits the capacity of storage in transmitting data. Thus, a large multimedia such as image data are hard to transmit via ZigBee network. Therefore, image compression are necessary in transmission process due to the ability in reducing dimension size and removing redundant image data. In this paper, three method are observed which are stand-alone DWT, stand-alone Huffman, and Hybrid of DWT and Huffman Coding. After conducting a comprehensive observation, it is found that DWT technique are able to compress the image data with less time taken while Huffman technique are suitable in maintaining the quality of image but need a long time to process. Hence, hybrid of DWT with Huffman method are proposed to support each other in terms of compression, computing time and quality of image

A Comparative Study on Improvement of Image Compression Method using Hybrid DCT - DWT Techniques with Huffman Encoding for Wireless Sensor Network Application

Nowadays, the demands on the usage of wireless network are increasing rapidly from year to year. Wireless network is a large scale of area where many nodes are connecting to each other to communicate using a device. Primarily, wireless network also tend to be as a link to transmit and receive any multimedia such as image, sound, video, document and etc. In order to receive the transmitted media correctly, most type of media must be compressed before being transmitted and decompressed after being received by the device or else the device used must have the ability to read the media in a compressed way. In this paper, a hybrid compression of Discrete Cosine Transform (DCT) and Discrete Wavelet Transform (DWT) with Huffman encoding technique are proposed for Wireless Sensor Network (WSN) application. Data compression is very useful to remove the redundant data and reduce the size of image. After conducting a comprehensive observation, it is found that hybrid compression is suitable due to the process consist of the combination of multiple compression techniques which suits for Wireless Sensor Network’s application focusing on ZigBee platform

Development of Car Tyre Air Pressure System (CTAPMS) Using Node MCU ESP8266 Board

CTAPMS is an electronic system designed in this work to monitor the air pressure inside pneumatic tyres on various types of vehicles. A crucial issue in monitoring air pressures of a tyre was most users are too lazy and do not check their car tyre condition daily or before starting a journey. As an assist device for the user to monitor their car air tyre pressure daily, this project has developed the CTAPMS using a BMP180 sensor and Node MCU 8266 microcontroller board. Based on the system, the measured car air tyre pressure can be visualized from the ThingSpeak IoT platform through a smartphone. The performance of the developed system has been validated through a series of experimental works. The result indicates a reliable measurement with an error of less than 10% as compare to the existing system. Further, this product will be commercialized for future use

Three-Phase Induction Motor Speed Estimation Using Recurrent Neural Network

In induction motor speed control method, the development of the field-oriented control (FOC) algorithm which can control torque and flux separately enables the motor to replace many roles of DC motors. Induction motor speed control can be done by using a close loop system which requires a speed sensor. Referring to the speed sensor weaknesses such as less accurate of the measurement, this is due to the placement of the sensor system that is too far from the control system. Therefore, a speed sensorless method was developed which has various advantages. In this study, the speed sensorless method using an artificial neural network with recurrent neural network (RNN) as speed observer on three-phase induction motor has been discussed. The RNN can maintain steady-state conditions against a well-defined set point speed, so that the observer is able and will be suitable if applied as input control for the motor drives. In this work, the RNN has successfully estimated the rotor flux of the induction motor in MATLAB R2019a simulation as about 0.0004Wb. As based on speed estimation error, the estimator used has produced at about 26.77%, 8.7% and 6.1% for 150rad/s, 200rad/s and 250rad/s respectively. The future work can be developed and improved by creating a prototype system of the induction motor to get more accurate results in real-time of the proposed RNN observer

Development of Car Tyre Air Pressure System (CTAPMS) Using Node MCU ESP8266 Board

CTAPMS is an electronic system designed in this work to monitor the air pressure inside pneumatic tyres on various types of vehicles. A crucial issue in monitoring air pressures of a tyre was most users are too lazy and do not check their car tyre condition daily or before starting a journey. As an assist device for the user to monitor their car air tyre pressure daily, this project has developed the CTAPMS using a BMP180 sensor and Node MCU 8266 microcontroller board. Based on the system, the measured car air tyre pressure can be visualized from the ThingSpeak IoT platform through a smartphone. The performance of the developed system has been validated through a series of experimental works. The result indicates a reliable measurement with an error of less than 10% as compare to the existing system. Further, this product will be commercialized for future use

Development of Vehicle Lighting System Using LED Application

A Light Emitting Diode (LED) is a semiconductor device which converts electricity into light. LEDs are preferred over incandescent lamps because of their long life and their availability in various colors and brightness levels. The aim of this paper is to present the development of vehicle lighting system using LED application. In this system, high power LEDs type is chosen as automobile headlight model and controller circuit using microcontroller is considered. The LEDs are driven using buck converter circuit with appropriate Pulse Width Modulation (PWM) signal whereby the PWM signals are generated by microcontroller. The system is divided into 2 modes of operation, manual and automatic. The automatic mode of operation will be operating when the LDR senses the level of light brightness whereby the level of brightness is proportion to duty cycle of PWM. Meanwhile, for the manual mode of operation, 3 switches which are SW2 with 20% duty cycle, SW3 with 40% duty cycle and SW3 with 80% duty cycle are developed. The result shows that the maximum brightness of LED is about 127.6 Lumen at 80% of duty cycle for manual operation mode. Besides, by varying theduty cycle of PWM signal for both modes of operation, manual and automatic, LED brightness can be controlled

Design and Development of a portable Pulse Oximetry system

Heart is the most important part in human body. Thus, it is important to follow-up and monitor its condition. Heart rate (HR) and blood oxygen saturation (SpO2) are important indicators directly related to heart-pulmonary system. Monitoring of HR and SpO2 offers us a good indication of heart functionality. Therefore, it is crucial to design and develop a homemade inexpensive device for measuring HR and SpO2. Pulse Oximeter (PO) is an opto-electronic non-invasive medical instrument capable of measuring and recording the changes of HR and SpO2 at the finger tip. In this paper we will demonstrate the overall process involved in the development of a portable (PO) system which can be used for health condition monitoring or for educational and research purposes