当前位置: 首页>博士论文>资源详情
基于激光诱导击穿光谱技术的复合肥成分实验测量与分析研究
中文摘要

复合肥成分的快速、原位检测对化肥生产企业的生产过程控制、产品质量控制具有重要的意义。与传统复合肥成分检测方法相比,激光诱导击穿光谱技术具有检测速度快、可实现实时现场多元素同时检测、简单的样品制备等优点,因而非常适用于复合肥成分的快速、现场检测。 由于激光诱导击穿光谱技术受到复合肥样品的基体效应、磷元素谱线较弱、现场检测环境、无法精确定量等问题的影响,为了实现该技术在复合肥生产过程的现场检测应用,本论文针对复合肥成分激光诱导击穿光谱检测系统的系统参数优化、样品特性、环境参数影响以及不同定量分析方法的实际应用开展了如下研究工作: (1)针对复合肥成分选取了氮磷钾元素的分析线分别为746.8nm、214.9nm、 769.9nm。开展了复合肥成分的时间和空间演化特性研究。针对复合肥成分中不同元素的延迟特性,确定多元素同时检测的延迟时间1.28μs,积分时间1.05ms;开展了复合肥成分的等离子体收集角度和探测高度对复合肥光谱特性的影响研究,确定最佳的等离子体收集角度为与水平方向呈30°,探测高度为距离复合肥样品表面2㎜处。 (2)研究了激光器参数对复合肥成分等离子体信号的影响,主要包括激光能量、重复频率、焦点位置。当激光能量小于110mJ时,复合肥成分的谱线强度与信背比随激光脉冲能量近似成线性关系,当能量超过110mJ,谱线强度呈非线性关系,而信背比基本保持不变。调节激光重复频率,得到谱线强度在激光重复频率为1Hz时最大;激光诱导击穿光谱的稳定性随重复频率先增加后减小,并在7Hz时最稳定。分析了激光焦点位置位于复合肥样品下方不同处时,激光诱导击穿光谱的特性,确定当激光焦点位于复合肥样品表面下方3㎜时,谱线强度最大,信号最稳定。最终确定复合肥激光诱导击穿光谱检测系统的激光能量为100mJ,重复频率为1Hz,激光焦点位于复合肥样品下方3㎜,每次测量进行20次平均测量。 (3)系统研究了复合肥样品的粒径、疏松度及背景气体等对激光诱导击穿光谱特性的影响,并进行了理论分析。通过对复合肥样品进行简单预处理,改变其物理性质,使复合肥样品变得均匀紧实。制备了7种不同粒径的复合肥样品,开展了不同粒径下元素谱线强度、信背比及稳定性的研究,当复合肥样品的粒径在0.18-0.25㎜范围时,信号的信背比和相对标准偏差最好,这主要是因为这种情况下,每次激光脉冲只作用在一个复合肥颗粒上,从而信号的稳定性和重复性都较好。通过对复合肥样品的施加9种不同压力,当所施加的压强小于8MPa时,元素特征谱线和信背比渐增大;当压强在8MPa-20MPa时,谱线强度和信背比基本趋于稳定,因此确定在实际应用过程中对复合肥样品施加8MPa压强压制成型。研究了不同复合肥样品在空气和氩气环境下,复合肥激光等离子体光谱特性。当采用氩气为背景气体时,磷元素的谱线强度提高将近2倍,信背比提高约5倍,同时,等离子体寿命及元素的定标曲线相关性都得到不同程度的提高。 (4)利用定标曲线法、内标法和多元非线性回归等定量反演方法对复合肥成分进行了分析。采用定标曲线法对复合肥样品中的总氮、五氧化二磷和氧化钾进行定量分析,计算得到三种成分含量的检测限分别为0.02%、0.13%和0.25%。建立了以硅元素为内标元素对复合肥中五氧化二磷成分进行分析的内标曲线,线性相关性提高到0.975。采用建立的曲线对4个验证样品中的五氧化二磷含量进行预测,得到平均相对误差为1.03%,这说明内标法可提高激光诱导击穿光谱测量的准确性。研究了多元非线性回归在激光诱导击穿光谱技术中的应用,以复合肥氧化钾含量为分析目标,选取10个样品用于建模、4个样品用于验证,得到建模和验证样品的激光诱导击穿光谱的预测值与真实值间的相关系数提高到0.981和0.978,计算得到多元非线性回归法的预测相对误差为0.51%。以上结果表明:多元非线性回归法极大地提高了激光诱导击穿光谱定量分析的预测准确性。 (5)重点研究了基于支持向量机回归的激光诱导击穿光谱数据分析方法。结合激光诱导击穿光谱与核变换技巧,建立了适用于激光击穿光谱探测的自适应混合核支持向量机回归算法模型。研究了以复合肥中五氧化二磷含量为分析目标的支持向量机回归算法,分别采用网格搜索法、粒子群算法和遗传算法进行参数寻优并建立模型。结果表明,三种参数寻优方法的训练样本的相关系数分别为0.980、0.987和0.985,测试样本的相关系数分别为和0.991、0.976和0.993;平均绝对误差分别为0.043%、0.38%、0.81%,最大绝对误差分别为0.1%、0.1%、 0.16%。实验结果说明支持向量机回归算法可以应用于复合肥成分激光诱导击穿光谱定量分析,且整体效果较优。 研究结论为激光诱导击穿光谱技术用于复合肥成分的快速、现场检测提供了数据支撑与方法支持。 关键词:复合肥;激光诱导击穿光谱;快速检测;定量分析

英文摘要

The rapid and in situ detection of compound fertilizer components is of great significance to the production process control and product quality control for fertilizer production enterprises. Compared with the traditional methods of detecting the composition of compound fertilizers, laser-induced breakdown spectroscopy (LIBS) has the advantages of fast detection speed, simultaneous detection of multiple elements in real-time field, and simple sample preparation. Therefore, it is very suitable for rapid on-site detection of compound fertilizer components. Due to the LIBS technique, which is affected by the matrix effect of compound fertilizer samples, the weak spectral line of phosphorus element, the in-situ detection environment, and the inability to accurately quantify problems. In order to realize the on-site detection and application of this technology in the process of compound fertilizer production, in this dissertation, the following research work is carried out by the optimization of system parameters, the characteristics of samples, the influence of environmental parameters and the application of different quantitative analysis methods for LIBS of compound fertilizer components: (1)According to the components of compound fertilizers, the analytical lines of N, P and K elements were 746.8nm, 214.9nm and 769.9nm, respectively. The research on the temporal and spatial evolution characteristics of compound fertilizers was carried out. According to the delay characteristics of different elements in compound fertilizers, the delay time of simultaneous detection of multiple elements was determined as 1.28 μs and the integration time was 1.05 ms. The influence of plasma collection angle and detection height on the spectral characteristics of compound fertilizer was also studied. The best plasma collection angle was 30 with the horizontal direction, and the detection height was 2mm from the surface of the compound fertilizer sample. (2)The effects of laser parameters on the plasma signal of compound fertilizer components were studied, including laser energy, repetition frequency and focal position. When the laser energy is less than 110mJ, the spectral line intensity and the signal-to-background ratio of the compound fertilizer have a linear relationship with the laser pulse energy. When the laser energy exceeds 110mJ, the line intensity is nonlinear and the signal-to-background ratio remains basically unchanged. The laser repetition frequency was adjusted, and the maximum spectral line intensity was got when the laser repetition frequency was 1 Hz. The stability of the laser induced breakdown spectrum first increased and then decreased with repetition frequency and at 7 Hz was the most stability. The characteristics of LIBS spectrum were analyzed when the laser focus position was located at different locations below the compound fertilizer sample. The largest spectral intensity and the most stable signal were obtained, when the laser focus was 3㎜ below the surface of the compound fertilizer sample. Finally, the laser energy of the LIBS detection system for compound fertilizer was 100 mJ, the repetition frequency was 1 Hz, the laser focus was 3 ㎜ below the compound fertilizer sample, and the average measurement was performed 20 times for each measurement. (3)The effects of particle size, porosity of complex fertilizer and background gas on LIBS were systematically studied and analyzed theoretically. By simple pretreatment of compound fertilizer samples to change their physical properties, the compound fertilizer samples became even and compact. Seven kinds of compound fertilizer samples with different particle sizes were prepared. The spectral line intensity, signal-to-background ratio and stability under different particle sizes were studied. When the particle size of the sample was between 0.18-0.25㎜, the signal-to-background ratio and relative standard deviations were best. It was because each pulse of laser only act on one particle of composite fertilizer, making the signal more stable and reproducible. By applying 9 different pressures on the compound fertilizer samples, the elemental characteristic line and the signal-to-background ratio gradually increased when the applied pressure was less than 8 MPa. When the pressure was between 8 MPa and 20 MPa, the line intensity and the signal-to-background ratio were tend to be stable. Therefore, it was determined that the pressure of 8 MPa was applied to the sample of compound fertilizer during the actual application. The spectral characteristics of laser plasma of compound fertilizer were studied under different atmospheres of air and argon for compound fertilizer samples. When argon was used as the background gas, the spectral line intensity of phosphorus element increased nearly two times, and the signal-to-background ratio increased about five times. At the same time, the correlation between plasma lifetime and element calibration curve has been improved to some extent. (4)The components of compound fertilizers were analyzed by using quantitative methods such as calibration curve method, internal standard method and multivariate nonlinear regression. The calibration curves of total nitrogen, phosphorus pentoxide and potassium oxide in compound fertilizer samples were quantitatively analyzed. The detection limits of the three components were 0.02%, 0.13% and 0.25% , respectively. The internal standard curve for the analysis of phosphorus pentoxide concentration in compound fertilizer with silicon as internal standard element was established. The linear correlation was increased to 0.975. The concentrations of P₂O₅ in the four validated samples were calculated under the established internal curve. The average relative error was 1.03%, which showed that the internal standard method can improve the accuracy of LIBS. The application of multivariate nonlinear regression in LIBS was also studied. Potassium oxide concentration of compound fertilizer was taken as the target of the analysis. Ten samples were selected for modeling and four samples were used for validation. The correlation coefficient between the predicted value of LIBS and the true value for modeling and verification were increased to 0.981 and 0.978, respectively. The relative error of the prediction of multivariate nonlinear regression was 0.51%. The above results showed that multivariate nonlinear regression method was greatly improved the prediction accuracy of quantitative analysis of LIBS. (5)Focusing on the LIBS data analysis based on support vector machine regression. Combined with LIBS and nuclear transformation techniques, an adaptive hybrid kernel support vector machine regression model suitable for LIBS detection was established. The regression model of support vector machine, which was based on the analysis of phosphorus pentoxide concentration in compound fertilizer, was studied. The parameters of grid search, particle swarm optimization and genetic algorithm were optimized and the models were established, respectively. The results showed that the correlation coefficients of training samples with three parameters optimization methods were 0.980,0.987 and 0.985, respectively. The correlation coefficients of the test samples were 0.991, 0.976 and 0.993, respectively. The average absolute errors were 0.043%, 0.38% and 0.81% , and the maximum absolute error is 0.1%, 0.1%, 0.16%, respectively. Experimental results showed that support vector machine regression algorithm can be applied to the quantitative analysis of LIBS of compound fertilizer components, and the overall effect was better. The conclusion of the study provided data support and method support of LIBS for the rapid on-site detection of compound fertilizer components. Keywords: Compound Fertiliter; Laser-induced breakdown spectroscopy; Fast Detection; Quantitative Analysis

作者相关
主题相关
看过该书的人还在看哪些书