Accurate gamma ray spectrum analysis

The problem of gamma ray spectrum analysis has been is studied. The difficulties encountered by different methods are explained. An empirical method which uses an experimental peak for the analysis of spectrum is developed. This method utilizes the simple algorithm of linear least squares and is able to analyze the multiplets. It gives more accurate results than other ones. It is well adapted for automatic treatment of gamma ray spectra by small computers.     

Gamma ray spectrum smoothing by one-pass method

One-pass method with a piecewise cubic polynomial was used as a smoothing technique in gamma ray spectrum analysis. By this method, smoothed results of spectrum region is represented to several divided intervals each of which are fitted with a cubic polynomial calculated by least square technique, respectively. From the smoothing procedure of simulated photoelectric peaks and actual gamma ray spectra, following results were obtained. Photoelectric peaks which had more than 10 channels of FWHM (full width at half maximum) were fitted correctly and low count spectra of about 100 counts per channel could also be fitted smoothly. These smooth results can not easily be obtained by Savitzky's convolution technique. In conclusion, this one-pass method was found to be effective for gamma ray spectra, especially for photoelectric peaks of large FWHM and Compton region.     

Activation analysis with standards containing two or more active nuclides A computerized method of calculation involving decay and gamma spectral resolution

The resolution of the gamma spectra of activities induced in materials by fast neutron, charged particle and gamma photon activation is complicated by the fact that many elements produce more than one active nuclide in significant amounts. Direct resolution by least-squares fitting of the spectra of standards is only possible in these circumstances if the standard and sample spectra are obtained at the same time after irradiation, as the shapes of the standard spectra change with time. An alternative to the practical collection of spectra in this way is the correction of the standard spectra to the mid-time of counting of a sample spectrum. This may be achieved by recording spectra for a standard at different times and resolving the decay curves obtained for each channel on the basis of the half-lives of the component nuclides, which may be decay-independent or related or both. From the component nuclide count-rates in each channel at some arbitrary time, the standard spectrum at the time of counting of the sample can be generated and then used in a conventional least squares-fit of the sample spectrum. A FORTRAN IV program has been written to carry out this type of calculation on an IBM 360 65 computer. The feasibility of using this method is demonstrated by its application to activation analyses involving standards containing decay-related and independent nuclides.     

一种基于光谱信息计算解析的液相色谱滤噪新方法

提出一种基于光谱信息计算解析的高效液相色谱滤噪新方法.对于HPLC/DAD所获得的二维量测数据,取半峰高以上色谱数据点所对应的各列光谱数据进行计算处理,求得在检测波长下的单位标准光谱,并根据光谱维数据与单位标准光谱的关系,采用最小二乘法重构计算求出色谱维数据,从而去除色谱噪声.仿真实验和实测谱图的滤噪结果表明,该方法能有效滤除常见噪声,与中值滤波算法相比较,滤噪性能明显优于后者,是提高色谱定量分析准确度的有力工具.     

Robust curve fitting method for optical spectra by least median squares (LMedS) estimator with particle swarm optimization (PSO).

A curve fitting technique for optical spectra based on a robust estimator, least median squares (LMedS), is introduced in this study. For the effective calculation of LMedS, particle swarm optimization (PSO) is also introduced. Unlike a standard curve fitting method using least squares (LS) estimator, the method based on LMedS estimator is less influenced by outliers in experimental data. Two kinds of data sets, simulated data with outliers and temperature-dependent near-infrared (NIR) spectra of oleic acid (OA) are applied for the demonstration of the proposed method. The results clearly reveal that, compared with the LS estimator, the proposed method can effectively reduce undesirable effects of low SN ratio and can yield more accurate fitting results.     

Numerical simulation on scintillator detector response for determining element content in PGNAA system

For selecting gamma ray detector to determining element content using prompt gamma neutron activation analysis technique, the response of BGO and LaBr₃ scintillator detectors was compared with Monte Carlo simulation method. The simulation models under different formation composed of various elements were established by MCNP, and then gamma ray spectrum was processed by least squares method. It is concluded that the element calculation accuracy will be different when scintillator was changed. With higher energy resolution, LaBr₃ scintillator can be used to improve the accuracy of the element content calculation result, and is more suitable for plentiful element formation.

     

Monte Carlo simulation of Cu,Ni and Fe grade determination in borehole by PGNAA technique

A prompt gamma neutron activation analysis borehole logging method for copper, nickel and iron grade estimation is proposed. The performance of the method was simulated by MCNP5 code. Based on the theory of neutron–gamma distribution on the borehole condition, the BGO scintillator and ³He neutron tube are adopted to record gamma ray spectrum and thermal neutron simultaneously, and least square method is used for the characteristic gamma ray counts calculation in the high energy range. The results of detection limit of metal grade in borehole condition indicate that the effectiveness of this logging method.     

Characterization of a Stable Adaptive Calibration Model Using Near-Infrared Spectroscopy and Partial Least Squares with a Kalman Filter

The calibration model of near-infrared (NIR) spectra established using the Kalman filter-partial least square (partial least squares combined with a Kalman filter) method can be adapted to outdated equipment, environmental changes, external samples, and other applications. However, the variance of the measurement noise estimation for NIR spectrum measurements cannot be easily obtained using Kalman filter-partial least squares; therefore, the variance in the measurement noise is often assumed to be zero for the Kalman filter-partial least square calibration model, which affects the stability of the model. In this study, the measured input and output data were used effectively, and the gamma test method for estimating the measurement noise variance was used to improve the stability of the Kalman filter-partial least square calibration model. First, an accurate estimation of the measurement noise variance was obtained, and accurate modeling was then performed using Kalman filter-partial least squares. Finally, 600 abandoned drilling fluid samples were used to confirm the validity of the proposed method. The Kalman filter-partial least square and gamma test-Kalman filter-partial least square methods are compared. Testing of external samples 401–600 demonstrated that the stability of the Kalman filter-partial least square model decreased. The root mean square error of the prediction of the Kalman filter-partial least square model was 27.135, which was worse than that of the gamma test-Kalman filter-partial least square model (20.307). The validation results show that the proposed method has better stability in tracking the evolution of the NIR spectrometer’s measurement state.     

Combined application of Monte Carlo method and neural networks to simulate qualitative prompt gamma neutron activation analysis

Prompt gamma spectrum produced by thermal neutron absorption and fast neutron inelastic scattering is simulated using Monte Carlo code MCNP4C. The simulated spectrum is analyzed with artificial neural network techniques. The neural network in our study is trained based on back-propagation algorithm with 138 gamma ray spectra. Elements existing in the 20 different substances are specified. The ANN could identify elements correctly in 96% of input cases.     

动力学过程的精确模拟

采用加权最小二乘法更精确地模拟了化学动力学过程,结出了几种常见动力学模型的权重函数。用普通最小二乘法和加权最小二乘法对聚时苯二甲酸乙二酯的结晶动力学过程进行了处理。方差分析表明,两种加权最小二乘法的标准差均小于普通最小二乘法的标准差,所得斜率和截距也有明显不同,示出了模拟的相对结晶度及其导数曲线。     

Standardization of near infrared spectra measured on multi-instrument

Calibration model transfer is essential for practical applications of near infrared (NIR) spectroscopy because the measurements of the spectra may be performed on different instruments and the difference between the instruments must be corrected. An approach for calibration transfer based on alternating trilinear decomposition (ATLD) algorithm is proposed in this work. From the three-way spectral matrix measured on different instruments, the relative intensity of concentration, spectrum and instrument is obtained using trilinear decomposition. Because the relative intensity of instrument is a reflection of the spectral difference between instruments, the spectra measured on different instruments can be standardized by a correction of the coefficients in the relative intensity. Two NIR datasets of corn and tobacco leaf samples measured with three instruments are used to test the performance of the method. The results show that, for both the datasets, the spectra measured on one instrument can be correctly predicted using the partial least squares (PLS) models built with the spectra measured on the other instruments.     

Study of Doppler broadening of gamma-ray spectra in 14-MeV neutron activation analysis

Neutron reactions producing characteristic photons of isotopes are important for nondestructive analysis of materials. Technique to determine the intensity of neutron induced gamma rays by fitting a spectrum with a Gaussian function using detector resolution curves derived from isotopic sources may fail if the peak is Doppler-broadened. This leads to the miscalculation of the area of the peak and, therefore, to misidentification of the material. This work shows that Doppler broadening occurs in the 14-MeV neutron analysis with photons emitted in inelastic scattering reactions on light nuclei with excited states whose lifetimes are much smaller than the time of flight of a recoiling nucleus in the material. It provides groundwork for analysis of gamma ray spectra utilizing detector response functions measured with a 14-MeV neutron source using actual geometry of an active interrogation system.     

A new maximum likelihood approach with asymmetric residual distribution for multicomponent mass spectra analysis

This paper proposes a new maximum likelihood approach for the deconvolution of identity and quantity of individual compounds based on the multicomponent mass spectra measured by mass spectrometry (MS). Mixture analysis of multicomponent mass spectra is, typically, based on a linear multicomponent mass spectrum model, where the compounds of the measured spectra to be solved are explicitly stated and assumed to be known. In many cases, however, the measured spectrum may contain unknown compounds that are not explicitly stated in the model and a commonly used least square (LS) solution fails. Moreover, a standard improvement over the LS method in these cases, namely the M-estimation (ME) approach, also suffers from this same problem. Our method overcomes the limitations of the LS and ME methods by modeling the effect of the unknown compound(s) to the residual of the linear model. The experimental results presented show that this new approach can separate more robustly the complex multicomponent mass spectra into their individual constituents compared to the LS and ME methods.     

Calibration transfer of near‐infrared spectra for extraction of informative components from spectra with canonical correlation analysis

A new calibration transfer method that applies canonical correlation analysis (CCA) to transfer the informative components extracted from a spectral dataset is proposed to reduce the interference of noise, background and non‐predicted properties. This method employs the partial least squares method to extract the informative components related to the predicted properties from the raw spectra and then corrects the informative components based on CCA. The performance of this algorithm was tested using three pairs of spectra batches: two pairs of corn spectra and one pair of tri‐component solvent spectra. The results showed that this method can significantly reduce prediction errors compared with CCA and piecewise direct standardization. Copyright © 2014 John Wiley & Sons, Ltd.     

Performance of UniSampo-Shaman with gamma-ray spectra containing known traces of fission products

A set of 100 gamma-ray spectra with known traces of anthropogenic nuclides was utilized in the First System-Wide Performance Test (SPT1) of the Comprehensive Nuclear-Test-Ban Treaty Organization (CTBTO) in June 2005. The spectrum set was very realistic, since it is based on real measured spectra. Yet, the correct spectrum contents are known, when anthropogenic peaks with known areas have been synthesized into the spectra. This paper investigates the key performance indicators for the UniSampo-Shaman software package when applied to these spectra, concentrating on results from automated pipeline analysis. In summary, the UniSampo-Shaman performance is very satisfactory and fully in line with previous evaluations.     

A system for the neutron activation analysis of trace elements in samples of biological and environmental interest

A neutron activation, ion exchange group separation and iterative least squares γ-ray spectroscopy method has been evaluated. This technique is suitable for multiple trace element analysis in a wide range of biological and environmental materials, since the major contaminants,²⁴Na,³²P, and⁴²K, are removed by an anion exchange resin and do not interfere with the analysis of the majority of the trace elements present. The iterative least squares method was tested with a mixture of standards. The reproducibility and accuracy varied from 3 to 26%. The larger uncertainties resulted from (1) the limited statistical accuracy associated with a low counting rate, and (2) bias introduced by the contaminants in the library of standard spectra even though radiochemical purity exceeded 99.8%. The rigorous least squares method can accurately compensate for instrumental drifts so that the sensitivity approaches the limit imposed by the statistical accuracy of the data and of the standard spectra. Minor components of the complex γ-spectrum were resolved and proved to be present at levels as low as 0.8% of the integral counting rate.     

Asymmetric least squares for multiple spectra baseline correction

In this paper, based on asymmetric least squares smoothing, a new algorithm for multiple spectra baseline correction is proposed. By means of the similarity among the multiple spectra, the algorithm estimates the baselines by penalizing the differences in the baseline corrected signals, which makes the algorithm possible to eliminate scatter effects on the spectra. In addition, a relaxation factor which measures the similarity of the baseline corrected spectra is incorporated into the optimization model and an alternate iteration strategy is used to solve the optimization problem. The proposed algorithm is fast and can output multiple baselines simultaneously. Experimental results on both simulated data and real data demonstrate the effectiveness and efficiency of the algorithm.     

混合线性分析-分光光度法同时测定微量锌、镉、汞

提出了以2－（5－溴－2－吡啶偶氮）－5－二乙氨基酚为显色剂分光光度法同时测定锌、镉、汞的新方法。由于在可见区3种络合物的吸收光谱具有相似的特征和严重重叠,本文采用混合线性分析进行光谱分辨,各组分的纯光谱则用最小二乘法从校正集中求出。讨论了显色条件,波长选择,纯光谱的确定和吸光度加合性等因素对测定的影响。方法具有简单,快速,准确等优点。已成功地应用于混合试样中锌、镉、汞的同时测定,并与同条件下偏最小二乘法的计算结果进行了对比。     

An emergency response intercomparison exercise using a synthetically generated gamma-ray spectrum

Although high resolution gamma ray spectrometry serves as the primary analytical technique in emergency response situations, chances for laboratories to practice analysing the type of spectra that may be expected in the early phase of such a situation are limited. This problem is more acute for laboratories in countries that have no nuclear facilities. The analysis of synthetically generated spectra may serve as a useful surrogate for actual spectra; this paper reports the results of a multilateral intercomparison exercise conducted using such a spectrum. Results indicate that the laboratories involved appear to have no problems identifying radioactive isotopes that regularly appear in national and international intercomparisons or exercises. However, some problems are evident for isotopes that are less often encountered which may, however, occur during the early phases of a nuclear accident. Isotopes prone to true coincidence summation proved also to be difficult with regard to correction of activities in some cases. The synthesized spectrum constituted a useful means of comparative analysis of complex spectra multilaterally without the impracticalities of using a sample drawn from a reactor.