A semi-empirical detector response function(DRF)model is established to fit characteristic X-ray peaks recorded in Si-PIN spectra,which is mainly composed of four components:a truncated step function,a Gaussian-shaped full-energy peak,a Gaussian-shaped Si escape peak and an exponential tail.A simple but useful statistical distribution-based analytic method(SDA)is proposed to achieve accurate values of standard deviation for characteristic X-ray peaks.And the values of the model parameters except for the standard deviation are obtained by weighted least-squares fitting of the pulse-height spectra from a number of pure-element samples.A Monte Carlo model is also established to simulate the X-ray measurement setup.The simulated flux spectrum can be transformed by Si-PIN detector response function to real pulse height spectrum as studied in this work.Finally,the fitting result for a copper alloy sample was compared with experimental spectra,and the validity of the present method was demonstrated.
A new statistical fitting approach, named Statistical Distribution-Based Analytic （SDA） method, is proposed to fit single Gaussian-shaped Ka and KI3 X-ray peaks recorded by Si（PIN） and silicon drift detector （SDD）. In this method, we use the dis- crete distribution theory to calculate standard deviation of energy resolution a. The calibration of cr and energy （E） for two de- tectors between the energy ranges of 4.5-26 keV are also completed by measuring characteristic X-ray spectra of nineteen types of pure elements. With the spectrum fraction （SF） parameter proposed in this paper, the SDA method can be used to re- solve overlapping peaks. In measured spectra, the Gaussian part of X-ray peaks can be fitted by a Gaussian function with two parameters, ~ and SF. This new fitting approach is simpler than traditional methods and it achieves relatively good results when fitting the complex X-ray spectra of national standard alloy samples detected by Si（PIN） and SDD detectors. The 3（2 values are obtained for each spectrum to assess fitting results, and the SDA fitting method gives a preferable fit for the SDD detector.
