基于无物联网输出通道的污水处理厂(WWTP)原型监测与控制

I. Iswanto, Fachrudin Hunaini, Dedi Usman Effendy
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引用次数: 1

摘要

最大的水污染是由于工业部门的废物处理造成的,而一些水污染则来自家庭部门。在劳动密集型工业部门和家庭部门,产生了家庭液体废物。高水平的废液污染可以通过使用污水处理厂(WWTP)来克服。根据已有的研究,废水参数pH、浊度和氨是非常重要的参数,也是影响排放到环境中的废水质量的主要因素。在本研究中,通过测量废水参数和基于物联网(IoT)的泵输出控制系统,设计了一个在输出通道上监测和控制污水处理厂的原型。该原型机具有2种模式选项,即自动模式,控制系统根据具有目标限值的程序命令工作,即pH 6 - 9,浊度< 300 NTU,氨< 20 PPM,如果废水测量值符合目标,系统将激活输出泵。直接排放到环境中。同时,如果达不到目标,系统启动处理泵,将废水送回污水处理厂。然后是手动模式,即控制系统,通过使用Blynk应用程序直接操作操作员在智能手机上激活输出或处理泵。在自动和手动模式下,可以使用Blynk应用程序在智能手机上监测废水参数。所有使用的传感器都已用2种校准器溶液校准。校准结果表明,pH传感器的误差值为0.115,浊度传感器的误差值为0.075,氨传感器的误差值为0.115。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Prototype Monitoring and Controlling of Wastewater Treatment Plant (WWTP) on IoT-Free Output Channels 
The largest water pollution occurs due to the disposal of waste from the industrial sector, while some of it comes from the household sector. In the labor-intensive industrial sector and the household sector, domestic liquid waste is generated. The high level of liquid waste pollution can be overcome by using a wastewater treatment plant (WWTP). Wastewater parameters according to research that has been done, namely pH, Turbidity, and Ammonia are very important parameters and the main priority for the quality of wastewater discharged into the environment. In this study, a prototype monitoring and controlling WWTP on the output channel was designed by measuring wastewater parameters and an Internet of Things (IoT) based pump output control system. This prototype is programmed with 2 mode options, namely auto mode where the controlling system works based on program commands with target limits, namely pH 6 – 9, Turbidity < 300 NTU, and Ammonia < 20 PPM, if the wastewater measurement value is on target, the system activates the outgoing pump. for direct disposal to the environment. Meanwhile, if it does not meet the target, the system activates the treatment pump to return the wastewater back to the WWTP. Then the manual mode, which is the controlling system, works by operating the operator directly to activate the outgoing or treatment pump on a smartphone using the Blynk application. In Auto and Manual mode, wastewater parameters can be monitored on a smartphone using the Blynk application. All sensors used have been calibrated with 2 calibrator solutions. The calibration results show an error value of 0.115 for the pH sensor, an error value of 0.075 for the Turbidity sensor, and an error value of 0.115 for the Ammonia sensor.  
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