The safety and reliability of mechatronics systems,particularly the high-end,large and key mechatronics equipment in service,can strongly influence on production efficiency,personnel safety,resources and environment.B...The safety and reliability of mechatronics systems,particularly the high-end,large and key mechatronics equipment in service,can strongly influence on production efficiency,personnel safety,resources and environment.Based on the demands of development of modern industries and technologies such as international industry 4.0,Made-in-China 2025 and Internet + and so on,this paper started from revealing the regularity of evolution of running state of equipment and the methods of signal processing of low signal noise ratio,proposed the key information technology of state monitoring and earlyfault-warning for equipment,put forward the typical technical line and major technical content,introduced the application of the technology to realize modern predictive maintenance of equipment and introduced the development of relevant safety monitoring instruments.The technology will play an important role in ensuring the safety of equipment in service,preventing accidents and realizing scientific maintenance.展开更多
随着人们对人数统计需求的不断增长,基于信道状态信息(channel state information,CSI)的人流量监测技术因其易于部署、保护隐私和适用性强等优势而备受关注.然而,在现有的人流量监测工作中,人数识别的准确率容易受到人群密集程度的影响...随着人们对人数统计需求的不断增长,基于信道状态信息(channel state information,CSI)的人流量监测技术因其易于部署、保护隐私和适用性强等优势而备受关注.然而,在现有的人流量监测工作中,人数识别的准确率容易受到人群密集程度的影响.为了保证监测精度,通常只能在人群稀疏的情况下进行监测,这导致了基于CSI的人流量监测技术缺乏实用性.为了解决这一问题,提出了一种能够识别连续性人流的监测方法.该方法首先利用解卷绕和线性相位校正算法,对原始数据进行相位补偿并消除随机相位偏移;然后通过标准差和方差提取连续性人流数据中的有效数据包;最后将时域上的相位差信息作为特征信号输入到深度学习的CLDNN(convolutional,long short-term memory,deep neural network)中进行人数识别.经过实验测试,该方法在前后排行人距离不小于1 m的情况下,分别实现了室外96.7%和室内94.1%的准确率,优于现有的人流量监测方法.展开更多
基金supported by National Natural Science Foundation of China(No.51275052)Beijing Natural Science Foundation(No.3131002)
文摘The safety and reliability of mechatronics systems,particularly the high-end,large and key mechatronics equipment in service,can strongly influence on production efficiency,personnel safety,resources and environment.Based on the demands of development of modern industries and technologies such as international industry 4.0,Made-in-China 2025 and Internet + and so on,this paper started from revealing the regularity of evolution of running state of equipment and the methods of signal processing of low signal noise ratio,proposed the key information technology of state monitoring and earlyfault-warning for equipment,put forward the typical technical line and major technical content,introduced the application of the technology to realize modern predictive maintenance of equipment and introduced the development of relevant safety monitoring instruments.The technology will play an important role in ensuring the safety of equipment in service,preventing accidents and realizing scientific maintenance.
