Browsing by Author "Wang, Yu-Hsuan"

Now showing 1 - 3 of 3

A study of fault diagnosis in a scooter using adaptive order tracking technique and neural network
(2009-01-01)
Wu, Jian-Da
;
Wang, Yu-Hsuan
;
Chiang, Peng-Hsin
;
Bai, Mingsian R.
;
機械工程學系
An expert system for scooter fault diagnosis using sound emission signals based on adaptive order tracking and neural networks is presented in this paper. The order tracking technique is one of the important approaches for fault diagnosis in rotating machinery. The different faults present different order. figures and they can be used to determine the fault in mechanical systems. However, many breakdowns are hard to classify correctly by human experience in fault diagnosis. In the present study, the order tracking problem is treated as a parametric identification and the artificial neural network technique for classifying faults. First, the adaptive order tracking extract the order features as input for neural network in the proposed system. The neural networks are used to develop the training module and testing module. The artificial neural network techniques using a back-propagation network and a radial basis function network are proposed to develop the artificial neural network for fault diagnosis system. The performance of two techniques are evaluated and compared through experimental investigation. The experimental results indicated that the proposed system is effective for fault diagnosis under various engine conditions. (C) 2007 Elsevier Ltd. All rights reserved.
Development of an expert system for fault diagnosis in scooter engine platform using fuzzy-logic inference
(2007-11-01)
Wu, Jian-Da
;
Wang, Yu-Hsuan
;
Bai, Mingsian R.
;
機械工程學系
;
Department of Mechanical Engineering
In the present study, a fault diagnosis system using acoustic emission with an adaptive order tracking technique and fuzzy-logic interference for a scooter platform is described. Order tracking of acoustic or vibration signal is a well-known technique that can be used for fault diagnosis of rotating machinery. Unfortunately, most of the conventional order-tracking methods are primarily based on Fourier analysis with the revolution of the machinery. Thus, the frequency smearing effect often arises in some critical conditions. In the present study, the order tracking problem is treated as the tracking of frequency-varying bandpass signals and the order amplitudes can be calculated with high resolution. The order amplitude figures are then used for creating the data bank in the proposed intelligent fault diagnosis system. A fuzzy-logic inference is proposed to develop the diagnostic rules of the data base in the present fault diagnosis system. The experimental works are carried to evaluate the effect of the proposed system for fault diagnosis in a scooter platform under various operation conditions. The experimental results indicated that the proposed expert system is effective for increasing accuracy in fault diagnosis of scooters. (c) 2006 Elsevier Ltd. All rights reserved.
Mechanical stretch induces hair regeneration through the alternative activation of macrophages
(2019-04-03)
Chu, Szu-Ying
;
Chu, Chih-Hung
;
Hsien-DaHuang
;
Yen, Meng-Hua
;
Hong, Hsiao-Chin
Tissues and cells in organism are continuously exposed to complex mechanical cues from the environment. Mechanical stimulations affect cell proliferation, differentiation, and migration, as well as determining tissue homeostasis and repair. By using a specially designed skinstretching device, we discover that hair stem cells proliferate in response to stretch and hair regeneration occurs only when applying proper strain for an appropriate duration. A counterbalance between WNT and BMP-2 and the subsequent two-step mechanism are identified through molecular and genetic analyses. Macrophages are first recruited by chemokines produced by stretch and polarized to M2 phenotype. Growth factors such as HGF and IGF-1, released by M2 macrophages, then activate stem cells and facilitate hair regeneration. A hierarchical control system is revealed, from mechanical and chemical signals to cell behaviors and tissue responses, elucidating avenues of regenerative medicine and disease control by demonstrating the potential to manipulate cellular processes through simple mechanical stimulation.