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机构地区:[1]北京航空航天大学惯性技术重点实验室,北京100191
出 处:《农业工程学报》2012年第20期217-222,共6页Transactions of the Chinese Society of Agricultural Engineering
基 金:国家公益行业重大专项(GYHY2007060003);国家自然基金创新群体项目资助(61121003)
摘 要:针对气体绝对压力小于40kPa的低压、宽温(-70~+80℃)状态下流量的测量,目前仍无简便有效的质量流量测量手段的问题,该文基于动态平衡原理提出了一种流量测量方法,设计了一套流量标定装置,其原理为低压、宽温状态下,流经调节阀的流量取决于阀前、后压力、阀门开度、气流温度4个变量。通过对由流量标定装置采集的原始数据样本的分析,利用BP神经网络方法建立了流量与阀前、后压力、阀门开度、气流温度的关系表达式。试验结果表明模型计算值与实测流量偏差小于1.8%,验证了该文所提出的流量测量方法有效性。The effective and convenient method to measure mass flow rate is absent now when absolute gas pressure less than 40 kPa and gas temperature from negative 70 to positive 80℃. For this case, a flow rate measurement method based on dynamic equilibrium principle was proposed and a novel flow metering device was designed. In low pressure and wide temperature, the flow rate through a control valve is determined by four factors: upstream pressure of valve, downstream pressure of valve, temperature and valve opening. With the data samples obtained from the metering system, the expression of the relationship between the flow rate and the four factors was established based on BP neural network method. The experimental results indicated the relative error of flow rate calculation was less than 1.8% and the proposed flow rate measurement method was effective.
关 键 词:气体流量 测量 神经网络 BP 调节阀 动态平衡
分 类 号:TH814[机械工程—仪器科学与技术]
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