摘要
针对当前水质环境监测中存在的布线难、覆盖范围低、成本高等问题,设计了一种基于MSP430F149的水质监测数据采集系统。该系统以MSP430F149为主控芯片,硬件系统由MSP430F149控制电路、串口无线通信电路、传感器电路、调理电路、电源电路等构成。其中,调理电路采用四级放大电路用于对传感器采集信号的滤波与放大;RS-232与SIM900A以串口无线通信方式,实现水质环境因子温度、pH值和浑浊度的远程实时监测;电源电路由太阳能光伏板、锂电池、继电器、稳压芯片等组成,可实现太阳能光伏供电与锂电池供电这两种模式的自动双向切换。Multisim仿真及实测试验表明,在两种模式下均可产生稳定的±5 V电压。系统上位机采用LaBVIEW设计,具有界面友好、功能完备和操作简单等特点。在实验室对系统进行模拟试验和数据分析。结果表明,采集数据波动在可接受范围内,具有一定的参考价值。
A data acquisition for water quality monitoring based on MSP430F149 is designed aiming at the problems of difficult wiring,low coverage and high cost in past water quality environmental monitoring.The MSP430F149 as the main control chip is applied with the peripheries such as serial wireless communication circuit,sensor circuit,conditioning circuit,power supply circuit,etc.Among those,the conditioning circuit consists of four-stage amplifier circuit to filter and amplify the sensor signal;the serial communication circuit via RS-232 and SIM900A comes to realize remote real-time monitoring of temperature,pH value and turbidity of water quality environmental factors;and the power supply circuit consists of solar photovoltaic panels,lithium batteries,relays,voltage regulator chips,etc.to realize that the power supply circuit can automatically be switched between lithium battery power supply mode and the solar photovoltaic panel mode in case the solar panel circuit is insufficient.In addition,the simulation is performed by Multisim;and the test results show that stable±5 V voltage can be generated in both modes.Since the upper computer of the system is equipped with LabVIEW,friendly interface,complete function and simple operation are accordingly provided.With the laboratory simulation and data analysis for this system,the results indicate that the fluctuation of collected data is within acceptable range.The work covered is referable and significant.
作者
陈博行
马俊
方卫强
刘承桥
CHEN Bohang;MA Jun;FANG Weiqiang;LIU Chengqiao(College of Physics and Electronic Information Engineering,Qinghai Normal University,Xining 810008,China)
出处
《自动化仪表》
CAS
2019年第12期6-9,13,共5页
Process Automation Instrumentation
基金
国家自然科学基金资助项目(61761040)
教育部春晖计划基金资助项目(Z2015062)
青海省135高层次人才资助和青海省物联网重点实验室建设专项基金资助项目(2017-ZJ-Y21)