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An Enhanced Data Visualization Method for Diesel Engine Malfunction Classification Using Multi-Sensor Signals 期刊论文
SENSORS, 2015, 卷号: 15, 期号: [db:dc_citation_issue], 页码: 26675-26693
作者:  Li, Yiqing;  Wang, Yu;  Zi, Yanyang;  Zhang, Mingquan
收藏  |  浏览/下载:5/0  |  提交时间:2019/12/02
Application MEMS multi-sensors for monitoring the forming load of stamping press 会议论文
作者:  Zhang, Chun;  Liang, Jing;  Yu, Dehong;  Xiao, Haifeng;  Wang, Min
收藏  |  浏览/下载:2/0  |  提交时间:2019/12/10
The signal extraction of fetal heart rate based on wavelet transform and BP neural network (EI CONFERENCE) 会议论文
Third International Conference on Experimental Mechanics and Third Conference of the Asian Committee on Experimental Mechanics, November 29, 2004 - December 1, 2004, Singapore, Singapore
Hong Y. X.; Cheng Z. B.; Dai F. H.
收藏  |  浏览/下载:14/0  |  提交时间:2013/03/25
This paper briefly introduces the collection and recognition of bio-medical signals  the other threading is analyzing data. Using the method  designs the method to collect FM signals. A detailed discussion on the system hardware  it is broaden to analyze the signal in real-time. Wavelet transform to remove the main interference in the FM and by adding time-window to recognize with BP network  structure and functions is also given. Under LabWindows/CVI  Finally the results of collecting signals and BP networks are discussed.8 pregnant women's signals of FM were collected successfully by using the sensor. The correctness rate of BP network recognition is about 83.3% by using the above measure.  the hardware and the driver do compatible  the hardware equipment work properly actively. The paper adopts multi threading technology for real-time analysis and makes use of latency time of CPU effectively  expedites program reflect speed  improves the program to perform efficiency. One threading is collecting data  


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