独立气体报警系统用mq系列气体传感器电路参数的图形化测定方法

A. T. Ajiboye, J. F. Opadiji, Adebimpe Ruth Ajayi
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引用次数: 0

摘要

背景:mq系列气体传感器属于金属氧化物半导体(MOS)传感器家族,可以感知多种气体的存在。这些传感器在气体报警系统中作为关键部件得到了应用。虽然在独立气体报警系统中需要必要的传感器电路输出电压值,但需要哪些传感器电路参数的确切组合?迄今为止,这些电路参数的确定在研究界还没有得到很大的重视。目的:这项工作的目的是探索一种结构化的图形方法来确定MQ系列气体传感器电路参数,用于一个独立的气体报警系统,产生所需的传感器电路输出电压值的报警点;该研究的主要目的是建立数学模型方程,将:(i)传感器电阻(RS)与气体浓度(x)和清洁空气中传感器基础气体的标准校准浓度(Ro)以及(ii)传感器电路输出电压(VRL),负载电阻(RL)和传感器电阻(RS)联系起来。从所建立的模型方程中,可以期望产生传感器电路参数的图形相关性。使用这些图,MQ-4气体传感器在LPG影响下的特定情况下,将确定在1000ppm LPG报警点下产生所需传感器电路输出电压为2V的参数。方法:建立了传感器动力学模型方程,并基于模型方程,绘制了MQ-4气体传感器对LPG响应情况下所需传感器参数的确定图。结果与讨论:当报警设置为1000ppm,期望传感器电路输出电压为2v时,结果得出R_O、R_S和R_L的最优值分别为20 kΩ、30 kΩ和20 kΩ。在确定的参数基础上,建立了给定仿真LPG浓度下确定最佳浓度值的标定方程。采用本研究提出的方法,使mq系列气体传感器电路参数的确定过程变得更简单,因为它们的值可以很容易地从结果图中得到。结论:采用结构化图形方法测定独立气体报警系统中mq -系列气体传感器报警点电路参数表明,以MQ-4气体传感器和LPG为目标气体,当LPG浓度为1000ppm时,报警点传感器电路输出电压为2v时,得到的R_O、R_S和R_L对应值分别为20 kΩ、30 kΩ和20 kΩ。因此,对于受伴生气影响的独立气体报警系统,采用结构化图形化方法确定MQ系列气体传感器电路参数是合适的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
GRAPHICAL METHOD FOR DETERMINATION OF MQ-SERIES GAS SENSOR CIRCUIT PARAMETERS FOR A STAND-ALONE GAS ALARM SYSTEM
Background: MQ-series gas sensors belong to the metal oxide semiconductor (MOS) family of sensors that can sense the presence of many gases. These sensors find their application in gas alarm systems as key components. While necessary sensor circuit output voltage value for alarm point in a stand-alone gas alarm system is desirable, but what exact combination of the sensor circuit parameters is required? Hitherto, the determination of these circuit parameters has not been given much attention in the research community. Aim: the purpose of this work is to explore a structured graphical approach of determination of MQ series gas sensor circuit parameters for a stand-alone gas alarm system that yields desired sensor circuit output voltage value for the alarm point; the main objective of the study was to develop mathematical model equations that relate the: (i) sensor resistance (RS) with the gas concentration (x) and the sensor resistance at standard calibration concentration of the sensor base gas in the clean air (Ro) and (ii) sensor circuit output voltage (VRL), load resistance (RL) and sensor resistance (RS). It is expected from the model equations developed that graphical correlations of the sensor circuits parameters will be generated. Using these graphs for a particular case of an MQ-4 gas sensor under the influence of LPG, the parameters that yield desired sensor circuit output voltage of 2V for 1000 ppm of LPG alarm point will be determined. Methods: Model equations were developed for the sensor dynamics, and based on these model equations, graphs for the determination of required sensor parameters were plotted for a case of MQ-4 gas sensor response to LPG. Results and Discussion: The results yielded optimal values for R_O,R_S and R_L of 20 kΩ, 30 kΩ and 20 kΩ respectively, for alarm settings of 1000 ppm and a desired sensor circuit output voltage of 2 V. Based on determined parameters, the calibration equation for determination of best concentration value for a given value of emulated LPG concentration was developed. Using the method proposed in this study makes the process of determining the MQ-series gas sensor circuit parameters less cumbersome as their value can easily be obtained from the resulting graphs. Conclusions: a structured graphical approach for determination of MQ-series gas sensor circuit parameters for alarm points in a stand-alone gas alarm system showed that using MQ-4 gas sensor and LPG as the target gas, and for a sensor circuit output voltage of 2 V for alarm point at 1000 ppm of LPG, the corresponding value of R_O, R_S and R_L obtained were 20 kΩ, 30 kΩ, and 20 kΩ respectively. Hence, a structured graphical approach is suitable for determining MQ series gas sensor circuit parameters for a stand-alone gas alarm system under the influence of its associated gases.
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