Infrared spectrum acquisition method based on Fourier transform infrared spectrum superposition type peak shape
A Fourier transform and infrared spectroscopy technology, applied in the fields of mathematical transformation, signal processing and infrared spectroscopy, can solve the problems of occupying computer storage space and multi-operation time, and achieve the effect of improving quality and extending the moving optical path.
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Embodiment 1
[0130] For the time signal, the Fourier transform full spectrum is obtained as usual, and the peak symmetry axis and baseline peak width are found one by one for spectral peak reconstruction and superimposed. Although doing so will get twice the result with half the effort, it is still a means. The characteristics of the spectral peaks in the frequency domain have been listed in Table 2 and Table 3. Since the peak width of the basic peak shape mainly depends on the sampling time T, after Fourier transform and superimposition using the symmetry of the basic peak shape, the peak intensity of each component can be achieved. Double the height, double the peak width. After phase difference correction and Gibbs amputation, the peak shape and peak shape coefficient of approximate Gaussian distribution are used to define symmetry, which is equivalent to superposition operation after deconvolution of the spectrum. Figure 8 are the simulated two infrared adjacent peaks, represented by...
Embodiment 2
[0132] The number of sampling points has been preset in the computer for Fourier transform, and these sampling points must be large enough to ensure that the signal frequency is not distorted. Existing Fourier transform infrared spectrometers must be preset to select the resolution, that is, the size of the optical difference, when performing interference spectrum analysis. According to any of the three peak shapes of the Fourier transform superposition operation provided above, that is, Equation 9, Equation 10 or Equation 11, all sampling frequency components ω 0 Perform superposition calculations to ensure that all infrared peaks in the entire measurement range are not missed. This is equivalent to taking N times the time to complete the superposition of N components. Further, the above-mentioned Fourier transform superposition operation can be optimized in technology, and the frequency components are properly grouped, and the new Fourier transform superposition is performed...
Embodiment 3
[0134] According to the existing Fourier transform theory, the signal f(t) composed of harmonics needs to be discretely sampled, and the number of samples is set to N, and a group of discrete signal points f(0), f(1), f(2) are intercepted. ), ..., f(k), ..., f(N-1). Discretized Fourier transform can obtain N data F(0), F(1), F(2), ··F(k), ···, F(N-1), expressed in the form of a square matrix as follows:
[0135]
[0136] In the formula, W=exp(-i2π / N) of the N×N Fourier transform matrix.
[0137] The superposition operation proposed by the present invention only needs to add a diagonal superposition matrix to the original Fourier transform matrix:
[0138]
[0139] Further, it is possible to scan column by column, or within the preset resolution condition ΔN area, to scan column by ΔN, and determine whether the diagonal matrix element is 2 or 0 by comparing the slope change between each scanning data point and the previous point, as follows shown.
[0140]
[0141]...
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