Optimization of Straight Movement 6 Dof Robot Arm with Genetic Algorithm

This paper proposes a genetic algorithm (GA) to optimize the straight movement of the robot arm for 6 DOF. The objective function of the GA is proposed to find the optimal values of the movement of the robot arm in a straight line trajectory. As more and more levels of Degree of Freedom (DoF), the more difficult to achieve precision, especially during straight motion from the starting point (initial point) to the point of destination (final point), which is affected by the determination of the swivel angle of each actuator, the linearity of the trajectory length straight-effector motion, and the number of Intermediate Point required. Forward kinematics is used to find the coordinates of the end effector, and a linear function of a straight line from the starting point (initial point) to the point of destination (final point) is used as the objective function of GA

Ekstrasi Ciri dan Pengenalan Suara Vokal Bahasa Indonesia Berdasarkan Jenis Kelamin secara Real TIME

Suara manusia memiliki ciri yang beraneka ragam, sehingga dapat dijadikan media komunikasi yang efektif. Oleh karena itu banyak penelitian yang berkaitan dengan suara manusia dilakukan untuk meningkatkan pengenalan suara. Proses pengembangan pengenalan suara dilakukan secara realtime berdasarkan jenis kelamin untuk menghasilkan akurasi yang tepat dalam batas waktu yang telah ditentukan. Metode Discrete Wavelet Transform (DWT) level 3 dan Dynamic Time Wraping (DTW) digunakan sebagai metode ekstrasi ciri dan metode pengenalan suara. Pada metode ekstrasi ciri Discrete Wavelet Transform (DWT) level 3 didapatkan 8 buah ciri. Sedangkan metode pengenalan suara menggunakan Dynamic Time Wraping (DTW) dilakukan dengan menghitung diskriminasi jarak terkecil antara dua ciri yang berbeda tanpa dilakukan pelatihan terlebih dahulu. Pengenalan suara diujikan pada 6 orang penutur pria dan 6 orang penutur wanita secara bergantian dengan masing-masing data pengukuran 900 pasang. Hasil persentase rata-rata pengenalan akurasi terbaik mencapai 54,6% dari pengujian terhadap 6 orang penutur pria secara bergantian dan 54,17 % dari pengujian terhadap 6 orang penutur wanita secara bergantian dari masing-masing pasangan data yang diperoleh secara realtime

Detection and Identification of Detonation Sounds in an Internal Combustion Engine Using Wavelet and Regression Analysis

Improving efficiency and power in an internal combustion engine is always impeded by detonation (knock) problems. This detonation problem has not been explained fully yet. Quick and accurate detection of detonation is also in the development stage. This research used a new method of detonation sound detection which uses microphone sensors, analysis of discrete wavelet transform (DWT), and analysis of the regression function envelope to identify the occurrence of detonation. The engine sound was captured by the microphone; it was recorded on a computer; it was proceeded using a DWT decomposition filtering technique; it was then subjected to normalization and regression function envelope to get the shape of the wave pattern for the vibration. Vibrational wave patterns were then compared to a reference using the Euclidean distance calculation method, in order to identify and provide an assessment decision as to whether or not detonation had occurred. The new method was applied using Matlab and it has yielded results which are quite effective for the detection and identification of detonation and it is also capable of producing an assessment decision about the occurrance of detonation