随着物联网技术在煤化工领域的应用和发展,对煤化工机电设备运行状态进行监测和故障报警已经成为首要解决问题。根据煤化工机电设备连续作业,存在信息采集困难、利用效率低下、动态管理棘手等问题,提出一款基于WinCE系统,在Visual Studi...随着物联网技术在煤化工领域的应用和发展,对煤化工机电设备运行状态进行监测和故障报警已经成为首要解决问题。根据煤化工机电设备连续作业,存在信息采集困难、利用效率低下、动态管理棘手等问题,提出一款基于WinCE系统,在Visual Studio 2008下使用ARM9处理器,采用SVDD算法研发的设备预警平台。实验表明:该平台通过Zigbee传感网络对煤化工机电设备进行信息实时采集及传输,经过平台阈值处理模块,可以判断当前设备运行状态,划分设备故障报警等级,向设备管理员发送报警通知,进而实现对煤化工机电设备状态的预测报警功能。展开更多
The study found that strong magnetic anomalies repeatedly took place before big earthquakes. Based on geomagnetic record analysis results,we discussed a possible pattern of the magnetic anomalies prior to earthquake. ...The study found that strong magnetic anomalies repeatedly took place before big earthquakes. Based on geomagnetic record analysis results,we discussed a possible pattern of the magnetic anomalies prior to earthquake. In meizoseismal area or epicenter,in a time period of 36 h to about 10 min before earthquake,the exceptional big geomagnetic change increases with the magnitude of earthquake. We calculated that,in a place of 1 km from the epicenter,the magnetic anomaly before destructive earthquakes of Ms 6～9 can reach to 102～104 nT(the magnitude of earth magnetic field is 104 nT) ,rather than the magnitude of 10 nT from seismomagnetic effect theories since 1960s. From this we speculated the abnormal magnetic ULF near epicenter before earthquake seems to be an "intermittent magnetic eruption". Accordingly,we proposed that geomagnetic induction earthquake alarm can be a new pre-warning method to surmount hardship in solving the puzzledom of earthquake imminent prediction.展开更多
Alarm systems play important roles for the safe and efficient operation of modern industrial plants. Critical alarms are configured with a higher priority and are safety related among many other alarms. If critical al...Alarm systems play important roles for the safe and efficient operation of modern industrial plants. Critical alarms are configured with a higher priority and are safety related among many other alarms. If critical alarms can be predicted in advance, the operator will have more time to prevent them from happening. In this paper,we present a dynamic alarm prediction algorithm, which is a probabilistic model that utilizes alarm data from distributed control system, to calculate the occurrence probability of critical alarms. It accounts for the local interdependences among the alarms using the n-gram model, which occur because of the nonlinear relationships between variables. Finally, the dynamic alarm prediction algorithm is applied to an industrial case study.展开更多
文摘随着物联网技术在煤化工领域的应用和发展,对煤化工机电设备运行状态进行监测和故障报警已经成为首要解决问题。根据煤化工机电设备连续作业,存在信息采集困难、利用效率低下、动态管理棘手等问题,提出一款基于WinCE系统,在Visual Studio 2008下使用ARM9处理器,采用SVDD算法研发的设备预警平台。实验表明:该平台通过Zigbee传感网络对煤化工机电设备进行信息实时采集及传输,经过平台阈值处理模块,可以判断当前设备运行状态,划分设备故障报警等级,向设备管理员发送报警通知,进而实现对煤化工机电设备状态的预测报警功能。
文摘The study found that strong magnetic anomalies repeatedly took place before big earthquakes. Based on geomagnetic record analysis results,we discussed a possible pattern of the magnetic anomalies prior to earthquake. In meizoseismal area or epicenter,in a time period of 36 h to about 10 min before earthquake,the exceptional big geomagnetic change increases with the magnitude of earthquake. We calculated that,in a place of 1 km from the epicenter,the magnetic anomaly before destructive earthquakes of Ms 6～9 can reach to 102～104 nT(the magnitude of earth magnetic field is 104 nT) ,rather than the magnitude of 10 nT from seismomagnetic effect theories since 1960s. From this we speculated the abnormal magnetic ULF near epicenter before earthquake seems to be an "intermittent magnetic eruption". Accordingly,we proposed that geomagnetic induction earthquake alarm can be a new pre-warning method to surmount hardship in solving the puzzledom of earthquake imminent prediction.
基金Supported by the National High Technology Research and Development Program of China(2013AA040701)
文摘Alarm systems play important roles for the safe and efficient operation of modern industrial plants. Critical alarms are configured with a higher priority and are safety related among many other alarms. If critical alarms can be predicted in advance, the operator will have more time to prevent them from happening. In this paper,we present a dynamic alarm prediction algorithm, which is a probabilistic model that utilizes alarm data from distributed control system, to calculate the occurrence probability of critical alarms. It accounts for the local interdependences among the alarms using the n-gram model, which occur because of the nonlinear relationships between variables. Finally, the dynamic alarm prediction algorithm is applied to an industrial case study.
