IR法在线测定高浓度重水过程中的气泡识别

    Bubble Identification in On-Line Determination of High Concentration Heavy Water via IR

    • 摘要: 在反应堆中,高浓度重水作为中子慢化剂和冷却剂,其浓度精度直接影响反应堆的运行性能与安全可靠性。为了确保反应堆的安全和操作人员的健康,对高浓度重水进行高准确度的在线定量监测至关重要。采用红外光谱法在线测定重水浓度过程中,测量数据易受工艺系统中气泡干扰,具体表现为:气泡导致重水红外光谱图形状发生畸变,从而引发重水浓度定量偏差。针对此问题,本研究提出了一种通过红外光谱图在线识别高浓度重水中气泡的有效方法。(1) 数据采集:系统采集高浓度重水在有气泡和无气泡两种状态下的红外吸收光谱图和单光束光谱图。(2) 特征提取与方法比较:分别提取有气泡存在时的吸收光谱图和单光束光谱图特征。经比较,基于单光束光谱图的方法在重水浓度在线定量分析上更有优势。(3) 方法开发:结合TQ Analyst软件、Micro Basic软件和Omnic 8.0软件,开发并建立了集重水浓度在线定量分析与气泡识别功能于一体的程序化分析方法。(4) 气泡识别准确率测试:应用所开发的方法对500个高浓度重水样本进行了气泡识别准确率测试,结果表明,气泡识别准确率为100%。

       

      Abstract: High concentration heavy water is used as moderator and coolant in a reactor, and its concentration closely related to the safety and performance of the reactor. It is very important for the reactor safety as well as health of operating personnel to quantify the heavy water concentration accurately. The bubble is one of the main factors that affect the accuracy of determination for heavy water concentration via infrared spectrometry. Specifically, bubbles cause distortion in the infrared spectrum of heavy water, leading to quantitative deviation in heavy water concentration. A method for on-line identification of bubbles in high concentration heavy water based on single beam spectrum was proposed as the bubble effects the appearance of infrared spectrum. Firstly, absorption spectrum and the single beam spectrum were acquired respectively with or without bubble. Secondly, the characteristics of absorption spectrum and the single beam spectrum with bubbles were extracted respectively. Research shows that the method based on single beam spectrum has more advantages than the method based on absorption spectrum in on-line quantitative analysis of heavy water concentration. Thirdly, a program method for quantitative analysis of high concentration heavy water and bubble identification based TQ Analyst, Micro Basic and Omnic 8.0 is established. Fourth, the concentration of heavy water was quantified and the presence of bubbles in the cell was identified. The accuracy of bubble identification by absorption spectrum and single beam spectrum is 100% when the number of the samples is 500. Consequently, the technical challenge of detecting abnormal data caused by air bubbles during the on-line infrared spectrometric determination of high-concentration heavy water is successfully overcome.

       

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