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11 results on '"Wang Wang-Long"'

4. The Innovative Design of Intelligent Mechanical Ventilation Bed

Author

Yan Xiao-ling, Liu Zaiwen, Xu Jiping, and Wang Wang-long

Subjects
Mechanical ventilation, Engineering, business.industry, medicine.medical_treatment, Medical equipment, Control engineering, Diaphragm (mechanical device), GeneralLiterature_MISCELLANEOUS, law.invention, Synchronization (alternating current), law, Ventilation (architecture), medicine, Breathing, business, Intelligent control, Simulation, Tidal volume
Abstract

A new intelligent Mechanical Ventilation Bed is introduced for the first time. The method of change posture synchronized with respiratory and change pressure to hanging abdomen on prostrate position obliquely is used cleverly. Through the role of gravity and inertia force, the breathing potential of diaphragm is mobilized and plays its role fully, so that the lung tidal volume multiplied. The innovative design of mechanical bed reflects the principles of humanization of medical equipment fully. On intelligent control algorithms, the fake-period algorithm is used innovatively, not only the assistant ventilation synchronized with breath ventilation is realized, but also the synchronization control, security and stability of the system is improved.

Published
2010
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9. De-Noising of Ultrasonic Signals Based on Entropy Theory and Recognition of Defect in Material.

Author

Yan Xiao-Ling, Dong Shi-Yun, Liu Bin, Xu Bin-Shi, and Wang Wang-Long

Subjects
ENTROPY, SIGNAL detection, NOISE control, WAVELETS (Mathematics), MANUFACTURING defects, VEHICLE motors
Abstract

In order to eliminate the noise which exists in ultrasonic detection signal and improve the diagnostic accuracy of defects inside the material, the method of de-noising ultrasonic signal by applying adaptive threshold(EAT) based on entropy theory is put forward in this paper. The searching algorithm of best wavelet packet basis adopting Shannon entropy is analyzed. The state of signal with noise is characterized by entropy and the threshold of wavelet packet decomposed in different scales is determined according to the entropy of the wavelet packet energy spectrum. Experiment of processing ultrasonic signal which comes from Steyr engine crankshaft with flaws has been implemented. Information that characterizes defect size and location could be extracted accurately from the processing results. The result indicates that the proposed EAT method has better de-noising performance and it has benefit to enhancing the degree of accuracy for quantitatively analyzing the defect inside material. [ABSTRACT FROM AUTHOR]

Published
2012

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