| 钾肥生产原卤井无线传感器网络监测系统 |
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| 引用本文： | 张小栓,刘贺,崔衍,祝天宇,傅泽田.钾肥生产原卤井无线传感器网络监测系统[J].农业工程学报,2017,33(Z1):199-205. |
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| 作者姓名： | 张小栓 刘贺 崔衍 祝天宇 傅泽田 |
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| 作者单位： | 1. 中国农业大学工学院,北京,100083;2. 中国农业大学信息与电气工程学院,北京,100083 |
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| 基金项目： | 青海省科学技术厅资助项目（2015-GX-Q10） |
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| 摘 要： | 针对钾肥生产中原卤井位置分散、人工巡检不及时、工作环境恶劣和采卤泵故障率高的现状,设计了基于无线传感器网络(wireless sensor network,WSN)的钾肥生产原卤井监测系统。系统包括集成CC2530和传感器构成的采集终端,结合ZigBee与GPRS技术完成数据汇总和远距离传输的汇聚终端和利用PHP与My Sql开发的用于数据接收、存储、显示,管理和决策支持的远程管理系统。系统测试表明监测系统能够可靠地监测采卤井,准确地反映采卤泵运行状态和采卤井液位。可靠性测试表明传感器节点有13.5个月的有效生存时间;在30 m通信范围内,发射功率大于1 d Bm时,节点丢包率小于3.6%,具有较高的通信可靠性。
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| 关 键 词： | 无线传感器网络 监测 钾 ZigBee 可靠性 |
| 收稿时间： | 2016/11/11 0:00:00 |
| 修稿时间： | 2016/12/23 0:00:00 |
Monitoring system for brine well in production of potash fertilizer based on wireless sensor network |
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| Zhang Xiaoshuan,Liu He,Cui Yan,Zhu Tianyu and Fu Zetian.Monitoring system for brine well in production of potash fertilizer based on wireless sensor network[J].Transactions of the Chinese Society of Agricultural Engineering,2017,33(Z1):199-205. |
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| Authors: | Zhang Xiaoshuan Liu He Cui Yan Zhu Tianyu and Fu Zetian |
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| Institution: | 1. College of Engineering, China Agricultural University, Beijing 100083, China;,2. College of Information and Electrical Engineering, China Agricultural University, Beijing 100083, China;,2. College of Information and Electrical Engineering, China Agricultural University, Beijing 100083, China;,2. College of Information and Electrical Engineering, China Agricultural University, Beijing 100083, China; and 1. College of Engineering, China Agricultural University, Beijing 100083, China; |
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| Abstract: | Underground brine of Qinghai Saline Lake, which contains many kinds of mineral deposits such as potash, magnesium, sodium, and lithium, is a kind of important raw material for chemical products such as salt, potash fertilizer, and lithium carbonate. The pumps are easily prone to be out of order due to the fact they must keep running around the clock in a complicated climate environment around the saline lake mining sites. However, traditional monitoring for the chemical brine pump in Qinghai Saline Lake is a manual monitoring technology with high cost, non-real time, inflexibility and high energy consumption. This paper proposed a remote monitoring system based on the wireless sensor network (WSN) for the brine well in the production of potash. It consists of 2 units: one is real-time monitoring unit based on WSN with ZigBee protocol and CC2530 wireless sensor SoC, and the other unit is remote management information system (RMIS) of brine well based on a PHP (Hypertext Preprocessor) software platform. The real-time monitoring unit based on WSN is responsible for acquiring and transmitting the data, which consists of a number of sensor or router nodes and a network coordinator, and is deployed at the site of the brine well mining. Meanwhile, the RMIS serves as the management system for end-users, which has 4 functions: 1) Managing static information of the brine well; 2) Maintaining the database for the data acquired by the WSN; 3) Providing functions to automatically control the speed of brine pump according to real-time operating state data of the brine pump or shut down the brine pump when the monitoring indicators exceed the threshold; 4) And generating a list of mining brine failure reports of mining equipment. The system is evaluated by testing the power consumption of sensor nodes first. The experimental results showed that the package loss ratio (PLR) of the nodes gradually decreased with the increase of the transmission power. However, the battery consumption increased with the increase of the transmission power. The transmission power was configured as 1 dBm which could prolong the lifetime of sensor nodes to 13.5 months. And then the PLR and RSSI (received signal strength indicator) of sensor nodes were tested in different distance and transmitting power, respectively. In the case of the same transmission power, the PLR and RSSI had the opposite change trend with the change of distance: The PLR increased and the RSSI decreased with the increase of the distance. The effective transmission distance of the nodes was 30 m when they were placed on the ground and their PLR was less than 3.6%. Last, the RSSI was also tested within 24 h, to analyze the influence of the field deployment environment on the link quality. The experimental results showed the RSSI was relatively better during the daytime (5:40–19:20) which ranged from-80 to-56 dBm. And during the night (00:00–5:40 and 21:30–24:00), the RSSI had a significant drop (around-85 and-95 dBm, respectively). And the system test under the potash production environment proves that monitoring data can accurately reflect the operating status of the pump and the brine level. |
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| Keywords: | wireless sensor networks monitoring potash ZigBee reliability |
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