Construction of multi-factor identification model for real-time monitoring and early warning of mine water inrush

As a new technical means that can detect abnormal signs of water inrush in advance and give an early warning,the automatic monitoring and early warning of water inrush in mines has been widely valued in recent years.Due to the many factors affecting water inrush and the complicated water inrush mechanism,many factors close to water inrush may have precursory abnormal changes.At present,the existing monitoring and early warning system mainly uses a few monitoring indicators such as groundwater level,water influx,and temperature,and performs water inrush early warning through the abnormal change of a single factor.However,there are relatively few multi-factor comprehensive early warning identification models.Based on the analysis of the abnormal changes of precursor factors in multiple water inrush cases,11 measurable and effective indicators including groundwater flow field,hydrochemical field and temperature field are proposed.Finally,taking Hengyuan coal mine as an example,6 indicators with long-term monitoring data sequences were selected to establish a single-index hierarchical early-warning recognition model,a multi-factor linear recognition model,and a comprehensive intelligent early-warning recognition model.The results show that the correct rate of early warning can reach 95.2%.

Design on Vibration Monitoring and Fault Diagnosis System of Large Water Pump Motor

Large water pump motor,whose operation decides the reliability of the whole production line,plays a very important role.Therefore,its online condition monitoring can help companies better know its operation,process fault analysis and protection.The essay mainly studies and designs large water pump motor′s real time vibration monitoring and fault diagnosis system.The essay completes the systems project design,the establishment of the system and performance test.Eddy-currentsensor,XM-120 vibration module,XM-320 axial translation module,XM-362 temperature module,XM-360 process amount module and XM-500 gateway module are used to measure the axial vibration and displacement of main motors.Laboratory tests prove that the system can meet the requirements of motor vibration monitoring.

Efficient Approach for Monitoring and Controlling Water Parameters Utilizing Integrated Treatment Based on WSNs

Research works of Wireless Sensor Networks (WSNs) applications and its constraints solutions occupy wide area around the world and attract many researchers. In this paper, an important one of environmental WSN applications is presented that is the water monitoring applications. An efficient approach for monitoring and controlling water parameters in real-time is implemented utilizing merging between WSN and designed simple workstation. For implementation simplicity, two water parameters (pH and temperature) are monitored and controlled in the proposed approach. Most of past work of water monitoring presented different proposed monitoring scenarios for different water parameters only. This research work utilizes the concept of interactive WSN nodes. The interactive nodes interact with the monitored water parameters to control its value. In the base station, the collected data is analyzed and the real-time value of the monitored parameters appears on the designed Graphic User Interface (GUI). The GUI is designed using the Matlab program. Through the GUI, the operator can switch the control between automatic and manual. ZigBee module is used for implementing the wireless communications between the nodes and the workstation. Due to the cost and simplicity, two sensors only are used in the proposed approach. Different real-time experiments are performed to test and measure the effectiveness and performance of the presented approach. These experiments reveal that the presented approach is effective for water treatment and efficient more than the past proposed water monitoring scenarios.

An IoT-Based Aquaculture Monitoring System Using Firebase

Indonesia is a producer in the fisheries sector,with production reaching 14.8 million tons in 2022.The production potential of the fisheries sector can be optimally optimized through aquaculture management.One of the most important issues in aquaculture management is how to efficiently control the fish pond water conditions.IoT technology can be applied to support a fish pond aquaculture monitoring system,especially for catfish species(Siluriformes),in real-time and remotely.One of the technologies that can provide this convenience is the IoT.The problem of this study is how to integrate IoT devices with Firebase’s cloud data system to provide reliable and precise data,which makes it easy for fish cultivators to monitor fishpond conditions in real time and remotely.The IoT aquaculture fishpond monitoring use 3 parameters:(1)water temperature;(2)pHwater level;and(3)turbidity level of pond water.IoT devices use temperature sensors,pH sensors,and turbidity sensors,which are integrated with a microcontroller and Wi-Fi module.Data from sensor readings are sent to the Firebase cloud via theWi-Fi module so that it can be accessed in real time by end users with an Androidbased mobile app.The findings are(1)the IoT-based aquaculture monitoring system device has a low error rate in measuring temprature,pH,and turbidity with a percentage of 1.75%,1.94% and 9.78%,respectively.Overall,the total average error of the three components is 4.49%;(2)in cost analysis,IoT-based has a cost-effectiveness of 94.21% compared to labor costs.An IoT-based aquaculture monitoring system using Firebase can be effectively used as a technology for monitoring fish pond conditions in real-time and remotely for fish cultivators that contribute to providing an IoT-based aquaculture monitoring system that produces valid data,is precise,is easy to implement,and is a low-cost system.

Real-time remote monitoring system for aquaculture water quality

A multi-parameters monitoring system based on wireless network was set up to achieve remote real-time monitoring of aquaculture water quality,in order to improve the quality of aquaculture products and solve such problems as being difficult in wiring and high costs in current monitoring system.In the system solar cells and lithium cells were used for power supply.The YCS-2000 dissolved oxygen sensor,pH electrode,Pt1000 temperature sensor and ammonia nitrogen sensor were used to monitor the parameters of aquaculture water quality;STM32F103 chip was used for data processing;Zigbee and GPRS modules were used for data transmission to the remote monitoring center,where the data were stored and displayed.The system was connected with aerator to realize automatic control of dissolved oxygen concentration.The test results showed high confidence level of data transmission with a packet loss rate of 0.43%.Therefore,the system could fulfill the real-time remote monitoring of aquaculture water quality and had great practical significance in reduction of labor intensity,improvement of quality of aquatic products and protection of water environment.

Optimization of DNA Staining Technology for Development of Autonomous Microbe Sensor for Injection Seawater Systems

Microbial activity in the water injection system in oil and gas industry leads to an array of challenges, including biofouling, injectivity loss, reservoir plugging, and microbiologically influenced corrosion (MIC). An effective mitigation strategy requires online and real-time monitoring of microbial activity and growth in the system so that the operators can apply and adjust counter-measures quickly and properly. The previous study [1] identified DNA staining technology-with PicoGreen and SYBR Green dyes—as a very promising method for automated, online determination of microbial cell abundance in the vast Saudi Aramco injection seawater systems. This study evaluated DNA staining technology on detection limit, automation potential, and temperature stability for the construction of automated sensor prototype. DNA staining with SYBR Green dye was determined to be better suited for online and real-time monitoring of microbial activity in the Saudi Aramco seawater systems. SYBR Green staining does not require sample pre-treatment, and the fluorescence signal intensity is more stable at elevated temperatures up to 30℃. The lower detection limit of 2 × 103/ml was achieved under the optimized conditions, which is sufficient to detect microbial numbers in Saudi Aramco injection seawater. Finally, the requirements for design and construction of SYBR-based automated sensor prototype were determined.

智慧水务大数据平台建设

笔者阐述了智慧水务大数据平台的架构设计及实施建议,并说明了子系统珠海供水实时监控系统的建设情况,阐述了大数据平台建设所需资源。智慧水务作为智慧城市的一部分,是体现城市管理信息化水平的标志之一,是智慧城市发展的必然产物。希望该研究为同行提供一定的参考。

利用珠海CORS监测大气可降水量

依托珠海城市连续运行参考站(continuously operating reference stations,CORS)系统,采用地基全球导航卫星系统(global navigation satellite system,GNSS)反演大气可降水量(precipitable water vapor,PWV),展开大气可降水量监测系统的应用研究。系统采用精密单点定位(Precise Point Positioning,PPP)技术与IGS(International GNSS Service)轨道、钟差产品实时或事后估计CORS站点上的大气可降水量,可实时更新发布水汽监测数据。通过对监测系统的内符合精度与外符合精度的测试,表明本大气可降水量监测系统对PWV的估计精度优于2 mm,能实现对珠海北斗CORS(ZHBDCORS)网中站点间小区域的水汽监测,区分各站之间的水汽变化,能满足实时对流层水汽监测及其他气象应用需求,有效地拓展ZHBDCORS系统的服务领域。