Wireless Hybrid Vehicle Three-Phase Motor Diagnosis Using Z-Freq Due to Unbalance Fault

Online diagnostics of three phase motor rotor faults of hybrid vehicle can be identified using a method called machine learning. Unfortunately, there is still a constraint in achieving a high success rate because a huge volume of training data is required. These faults were represented on its frequency content throughout the Fast Fourier Transform (FFT) algorithm to observe data acquired from multi-signal sensors. At that point, these failure-induced faults studies were improved using an enhanced statistical frequency-based analysis named Z-freq to optimize the study. This analysis is an investigation of the frequency domain of data acquired from the turbine blade after it runs under a specific condition. During the experiment, the faults were simulated by equipment with all those four conditions including normal mode. The failure induced by fault signals from static, coupled and dynamic were measured using high sensitivity, space-saving and a durable piezo-based sensor called a wireless accelerometer. The obtained result and analysis showed a significant pattern in the coefficient value and distribution of Z-freq data scattered for all flaws. Finally, the simulation and experimental output were verified and validated in a series of performance metrics tests using accuracy, sensitivity, and specificity for prediction purposes. This outcome has a great prospect to diagnose and monitor hybrid electric motor wirelessly. &nbsp

Wireless Hybrid Vehicle Three-Phase Motor Diagnosis Using Z-Freq Due to Unbalance Fault

Online diagnostics of three phase motor rotor faults of hybrid vehicle can be identified using a method called machine learning. Unfortunately, there is still a constraint in achieving a high success rate because a huge volume of training data is required. These faults were represented on its frequency content throughout the Fast Fourier Transform (FFT) algorithm to observe data acquired from multi-signal sensors. At that point, these failure-induced faults studies were improved using an enhanced statistical frequency-based analysis named Z-freq to optimize the study. This analysis is an investigation of the frequency domain of data acquired from the turbine blade after it runs under a specific condition. During the experiment, the faults were simulated by equipment with all those four conditions including normal mode. The failure induced by fault signals from static, coupled and dynamic were measured using high sensitivity, space-saving and a durable piezo-based sensor called a wireless accelerometer. The obtained result and analysis showed a significant pattern in the coefficient value and distribution of Z-freq data scattered for all flaws. Finally, the simulation and experimental output were verified and validated in a series of performance metrics tests using accuracy, sensitivity, and specificity for prediction purposes. This outcome has a great prospect to diagnose and monitor hybrid electric motor wirelessly. &nbsp

Patterns of Coptotermes SP. Termite Attack on Shorea Leprosula Miq in Khdtk Sebulu, East Kalimantan

Red meranti (Shorea leprosula Miq) as a major commercial timber has been widely planted in Dipterocarp forests. Coptotermes sp. termite often attacks S. leprosula Miq to its death, but the attack patterns are unknown. This research aims to get data on the frequency, intensity, and patterns of Coptotermes sp. attack in KHDTK Sebulu, East Kalimantan. Methods used were observation, recording, and mapping on S. leprosula Miq trees attacked by termites in KHDTK Sebulu. The results showed that the frequency of termite attacks on S. leprosula Miq in KHDTK Sebulu was 6.4-30.5% and termite attacks intensity was 4.7-22.1%. Termite attack patterns tended to spread and were followed by the formation of the nest to produce colonies

Serangan Kumbang Pemakan Daun Tanaman Jenis Dipterokarpa di PT Inhutani II, Pulau Laut, Kalimantan Selatan

Tanaman jenis dipterokarpa (Shorea leprosula dan S. ovalis) di areal hutan PT Inhutani II, Pulau Laut, Kalimantan Selatan diserang kumbang (Scarabaeidae, Coleoptera) yang mengakibatkan tajuk tanaman menjadi gundul. Tujuan penelitian ini adalah untuk mengetahui frekuensi dan intensitas serangan kumbang pada tanaman S. leprosula dan S. ovalis. Untuk maksud tersebut dibuat jalur pengamatan pada beberapa petak tanaman. Hasil penelitian menunjukkan bahwa frekuensi serangan kumbang berkisar 97,5 – 100,0% dengan intensitas serangan berkisar 28,9 – 62,8%. Selain kumbang menyerang tanaman S. leprosula dan S. ovalis, juga ditemukan menyerang daun S. johorensis, Duabanga molluccana dan Arthocarpus anysophyllus yang tumbuh secara alami

Pemangsa Biji Dipterocarpaceae

Penelitian bama biji Dipterocarpaceae dilakukan di Butan Penelitian Wanariset Samboja. Dari inventarisasi pohon dewasa diperoleh sembilan spesies yang sedang berbuah dan diteliti hama yang merusak biji. Di bawah tajuk dari sembilan spesies dipasang sejumlah perangkap biji. Biji Shorea pauciflora King, S leprosula Miq., S faguetiana Heirn, S parvifolia Dyer, Dipterocarpus cornutus Dyer, S. johorensis Foxw., S. smithiana Sym., S. ovalis Blume dan Cotylelobium sp. di kumpulkan dan diteliti serangga Perusaknya. Persentase kerusakan biji akibat serangan Perusak biji serangga adalab sebagai berikut: S. smithiana Sym. (6,83%), S. pauciflora King (0,08%), S. leprosula Miq. (12,30%), S. parvifolia Dyer (3,60%) dan S. faguetiana Heim (0,75%). Untuk S. johorensis, D. cornutus dan Cotylelobium sp. tidak ditemukan serangan dati serangga Perusak biji. Kerusakan biji pra-pencar (predispersal) disebabkan oleb Nanophyes sp. dan Alcidodes sp. Berdasarkan type kerusakan di duga tupai memiliki andil dalam Perusakan biji pra-pencar. Babi Butan (Sus barbatus) teramati sebagai Perusak biji pasea-penear di lantai hutan (post-dispersal seed predation)