作者：杨健健¹, 王超¹, 杨伟伟², 张强¹, 王子瑞¹, 韩松¹, 王晓林¹

作者单位：1. 中国矿业大学（北京）机电与信息工程学院, 北京 100083;
2. 山东省工程建设标准定额站, 山东 济南 250000

关键词：物联网;煤化工;SVDD;机电设备;预测报警

摘要：

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。

Development of an early warning platform for unattended equipment in coal chemical industry based on SVDD
YANG Jianjian¹, WANG Chao¹, YANG Weiwei², ZHANG Qiang¹, WANG Zirui¹, HAN Song¹, WANG Xiaolin¹
1. School of Mechanical Electronic and Information Engineering, China University of Mining and Technology (Beijing), Beijing 100083, China;
2. Shandong Provincial Engineering Construction Standard Station, Jinan 250000, China
Abstract: With the application and development of the Internet of things technology in the field of coal chemical industry, monitoring and fault alarm of electromechanical equipment in coal chemical industry have become the primary problem to be solved. According to the continuous operation of mechanical and electrical equipment in coal chemical industry, there are problems such as difficulty in information collection, low utilization efficiency and intractable dynamic management, etc., this paper proposes a device warning platform based on WinCE system, which uses ARM9 processor in Visual Studio 2008 and SVDD algorithm. Experiments show that the platform through the Zigbee sensor network for chemical mechanical and electrical equipment for real-time information acquisition and transmission, through platform threshold processing module, judging the current equipment running status, division of equipment malfunction alarm level, send alarm notification to the device manager, and then realize the prediction of the chemical mechanical and electrical equipment alarm function.
Keywords: IOT;coal chemical industry;SVDD;electromechanical device;forecast alarm
2019, 45(10):135-138  收稿日期: 2019-01-16;收到修改稿日期: 2019-02-28
基金项目:
作者简介: 杨健健(1988-),男,山东济宁市人,硕士生导师,博士,主要研究方向为智能监测与控制、设备状态监测与故障诊断、无线传感器及其网络等
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