CN109239763A - Simulate the simulation spectrum curve emulation mode of nuclear decay process - Google Patents
Simulate the simulation spectrum curve emulation mode of nuclear decay process Download PDFInfo
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Abstract
The present invention relates to a kind of simulation spectrum curve emulation modes for simulating nuclear decay process, include the following steps: step S1, obtain practical nuclear spectrum curve graph；Step S2 handles to obtain simulation spectrum curve practical nuclear spectrum curve graph；Simulation spectrum curve emulation mode of the invention is by carrying out Curves Recognition to practical nuclear spectrum curve graph and spectrum curve quantizing, to obtain the numerical value (i.e. the counting rate of the energy level of nuclear spectrum and each energy level) of spectrum curve each point, again by this group of numerical value of the random direct sampling of Monte Carlo method to obtain the random number about each nuclear level, to simulate the randomness of nuclear decay process, statistical disposition finally is carried out to the random number again and obtains simulation spectrum curve, the reliability and accuracy of imitative nuclear signal generator are determined by inverting comparative simulation spectrum curve and practical spectrum curve.
Description
Technical field
The present invention relates to a kind of nuclear energy fields, more particularly to the simulation spectrum curve emulation mode of simulation nuclear decay process.
Background technique
Nuclear decay process occurs at random in time, and it is also random, but right that decay process, which discharges ray (energy),
Its time interval occurred and energy value take statistics analysis, it can be seen that nuclear decay process has following characteristic: in generation nuclear decay
Time interval on approximate obey exponential distribution；The energy (i.e. power spectrum) that nuclear decay process externally discharges is approximate to obey Gauss point
Cloth.
Based on nuclear decay process, there are the above characteristics, and the imitative nuclear signal generator of traditional approach is to obey different distributions
Random number simulates nuclear signal feature, i.e., to obey exponential distribution random number simulation nuclear signal in time interval statistical property；With
Random numbers of Gaussian distribution simulates statistical property of the nuclear signal in amplitude.But core is only simulated with the random number of Gaussian distributed
Statistical property of the signal in amplitude be it is inapt, the high phase distribution curve simulated and practical spectrum curve there is compared with
Big error cannot accurately reflect nuclear signal characteristic；At the same time, the power spectrum statistical property of each nucleic is not quite similar, therefore
The random numbers of Gaussian distribution for then needing to generate different parameters to the simulation of the amplitude characteristic of variety classes nucleic is matching, this is not
It is actual, it is difficult to realize in the operating process of border.
In view of various drawbacks existing for traditional imitative nuclear signal generator, set forth herein a kind of completely new approach to
Solve problem above.
Summary of the invention
The object of the present invention is to provide a kind of simulation spectrum curve emulation modes, are emulated with realizing to nuclear energy spectral line.
In order to solve the above-mentioned technical problems, the present invention provides a kind of simulation spectrum curve emulation modes, which is characterized in that
Include the following steps: step S1, obtains practical nuclear spectrum curve graph；And step S2, at practical nuclear spectrum curve graph
Reason is to obtain simulation spectrum curve.
Further, the simulation spectrum curve emulation mode further include: step S3 compares simulation spectrum curve by inverting
With practical spectrum curve, the error between spectrum curve and practical spectrum curve is simulated with acquisition.
Further, practical nuclear spectrum curve graph is handled to obtain the method packet of simulation spectrum curve in step S2
Include: step S21 carries out Curves Recognition to practical nuclear spectrum curve graph and spectrum curve quantizes, each to obtain spectrum curve
The numerical value of point；Step S22 is obtained by Monte Carlo method this group of numerical value of random direct sampling about the random of each nuclear level
Number, to simulate the randomness of nuclear decay process；And step S23, statistical disposition is carried out to the random number and obtains the simulation
Spectrum curve.
Further, Curves Recognition is carried out to practical nuclear spectrum curve graph in the step S21 and spectrum curve quantizes
With the method for obtaining the numerical value of spectrum curve each point include: by practical nuclear energy respectively set a song to music line chart image after filtering and noise reduction is handled
Practical spectrum curve figure is shown again, and copies each key of the nuclear energy spectral curve according to the practical spectrum curve figure of display
Point obtains spectrum curve data, to establish spectrum curve database；Or respectively the set a song to music image of line chart of practical nuclear energy is filtered, dropped
Pretreatment, Curves Recognition, curvilinear characteristic extraction, and progress interpolation processing make an uproar to improve and repair each point of missing spectrum curve
Data, to establish spectrum curve database.
Further, it is obtained by Monte Carlo method this group of numerical value of random direct sampling about each nuclear energy in step S22
The random number of grade includes: the simulation of nuclear signal time statistical property in the method for simulating the randomness of nuclear decay process；And core letter
Number amplitude statistics simulated behavior.
Further, the method for the nuclear signal time statistical property simulation includes: the random number by obeying exponential distribution
Realize the simulation of nuclear signal time statistical property, wherein
The random number of exponential distribution by (0,1] equally distributed random number by inverse function method converts to obtain, and (0,1]
Even distribution random numbers are suitable for acquiring by linear congruential method.
Further, the method for the nuclear signal amplitude statistics simulated behavior includes:
By to practical nuclear spectrum Curves Recognition and digitizing and obtaining each energy level amplitude and counting rate, then pass through Monte Carlo
Method direct sampling simultaneously exports the random number；Wherein
Identification and digitized process to practical nuclear energy spectral curve include:
Step S221 is filtered practical spectrum curve figure, noise reduction；
Step S222 finds out threshold value by split plot design between maximum kind, and by spectrum curve figure progress binary conversion treatment, then by
Pixel scanning method extracts the numerical value i.e. coordinate of each point on spectrum curve；
Step S223, repairs spectrum curve and is quantized.
Further, the method for passing through Monte Carlo method direct sampling and exporting the random number, i.e.,
It is a series of random to obtain by each point value on Monte Carlo method direct sampling spectrum curve and curve
Number, thus to simulate the randomness of nuclear decay process.
Further, the method practical spectrum curve figure being filtered in the step S221, i.e., to practical spectrum curve
Figure carries out Wiener filtering processing, to filter out the Gaussian noise in spectrum curve figure.
Further, the method repaired and quantized to spectrum curve in the step S223 includes: by sample three times
Interpolation method is stretched to fill up the data point lacked during spectrum curve feature extraction by the expansion of the ratio of coordinate to obtain
Obtain the numerical value of each point on spectrum curve figure.
The invention has the advantages that simulation spectrum curve emulation mode of the invention passes through to practical nuclear spectrum curve graph
It carries out Curves Recognition simultaneously spectrum curve quantizes, to obtain numerical value (the i.e. energy level of nuclear spectrum and each of spectrum curve each point
The counting rate of energy level), then by the random direct sampling of Monte Carlo method this group of numerical value with obtain about each nuclear level with
Machine number finally carries out statistical disposition to the random number again and obtains simulating and can set a song to music to simulate the randomness of nuclear decay process
Line, is determined by inverting comparative simulation spectrum curve and practical spectrum curve the reliability of imitative nuclear signal generator with accurately
Property.
Detailed description of the invention
Present invention will be further explained below with reference to the attached drawings and examples.
Fig. 1 is the functional block diagram of simulation spectrum curve emulation mode of the invention；
Fig. 2 is simulation spectrum curve emulation mode flow chart of the invention；
Fig. 3 is to be handled practical nuclear spectrum curve graph to obtain simulation spectrum curve in the step S2 of the invention
Method flow diagram；
Fig. 4 is generation n=10000 according to the present invention (0,1) uniform random number distribution maps；
Fig. 5 is exponential distribution random-number distribution figure of the invention；
Fig. 6 is of the invention to be evenly dividing 1000 group squares to the above exponential distribution random number value range and count
Statistical chart；
Fig. 7 is the spectrum curve characteristic pattern extracted of the invention；
Fig. 8 is spectrum curve Preliminary Simulation effect picture of the invention；
Fig. 9 is the effect picture after cubic spline interpolation of the invention；
Figure 10 is that the spectrum curve that finally obtains of the invention simulates effect picture；
Figure 11 shows the effect picture of the simulation random generating process of nuclear signal；
Figure 12 is shown using Monte Carlo method direct sampling final effect figure.
Specific embodiment
In conjunction with the accompanying drawings, the present invention is further explained in detail.These attached drawings are simplified schematic diagram, only with
Illustration illustrates basic structure of the invention, therefore it only shows the composition relevant to the invention.
As shown in Figure 1, simulation spectrum curve emulation mode of the invention is by carrying out curve to practical nuclear spectrum curve graph
It identifies and spectrum curve quantizes, to obtain numerical value (the i.e. meter of the energy level of nuclear spectrum and each energy level of spectrum curve each point
Digit rate), then by this group of numerical value of the random direct sampling of Monte Carlo method to obtain the random number about each nuclear level, thus
The randomness of nuclear decay process is simulated, statistical disposition finally is carried out to the random number again and obtains simulation spectrum curve, by anti-
Comparative simulation spectrum curve and practical spectrum curve are drilled to determine the reliability and accuracy of imitative nuclear signal generator.
A specific embodiment of the invention is as illustrated in the examples below.
As shown in Fig. 2, a kind of simulation spectrum curve emulation mode of the invention, includes the following steps:
Step S1 obtains practical nuclear spectrum curve graph；
Step S2 handles to obtain simulation spectrum curve practical nuclear spectrum curve graph.
Optionally, the simulation spectrum curve emulation mode further include:
Step S3 compares simulation spectrum curve and practical spectrum curve by inverting, to obtain simulation spectrum curve and reality
Error between the spectrum curve of border.
Further, as shown in figure 3, being handled practical nuclear spectrum curve graph to obtain simulation power spectrum in the step S2
The method of curve includes:
Step S21 carries out Curves Recognition to practical nuclear spectrum curve graph and spectrum curve quantizes, to obtain to set a song to music
The numerical value of line each point；Step S22 is obtained by Monte Carlo method this group of numerical value of random direct sampling about each nuclear level
Random number, to simulate the randomness of nuclear decay process；And step S23, random number progress statistical disposition is obtained described
Simulate spectrum curve.
Specifically, carrying out Curves Recognition to practical nuclear spectrum curve graph in the step S21 and spectrum curve quantizing
Include: in the method for obtaining the numerical value of spectrum curve each point
Respectively the set a song to music image of line chart of practical nuclear energy is again shown practical spectrum curve figure after filtering and noise reduction is handled,
And spectrum curve data are obtained according to each key point that the practical spectrum curve figure of display copies the nuclear energy spectral curve, to establish energy
Spectral curve database；Or by practical nuclear energy respectively set a song to music line chart image through filtering, noise reduction pretreatment, Curves Recognition, curvilinear characteristic
It extracts, and carries out interpolation processing to improve and repair each point data of missing spectrum curve, to establish spectrum curve database.
Wherein, it is obtained by Monte Carlo method this group of numerical value of random direct sampling about each core in the step S22
The random number of energy level includes: the simulation of nuclear signal time statistical property and nuclear signal in the method for simulating the randomness of nuclear decay process
Amplitude statistics simulated behavior.
The method of the nuclear signal time statistical property simulation includes: to realize core letter by obeying the random number of exponential distribution
The simulation of number time statistical property, wherein the random number of exponential distribution by (0,1] equally distributed random number passes through inverse function method change
Get in return, and (0,1] uniform random number be suitable for acquired by linear congruential method.
Specifically, acquired by linear congruential method (0,1] method of uniform random number is as follows:
The recurrence formula of linear congruential method is as follows:
xi+1≡λxi+c(mod M) (1)
Wherein λ, c are constant.The initial x1 chosen is known as seed, has certain influence, value to the generation quality of random number
Respectively 1~216It is chosen between=65535.For the ease of using on computers, usually take
M=2S, wherein S is binary maximum possible number of significant digit in computer.
Fig. 4 be take 10000 (0,1] random-number distribution situation
The production method of exponential distribution random number, i.e. exponential distribution random number can be realized that detailed process is such as by inverse function method
Under:
If the distribution function of stochastic variable X obeys exponential distribution:
F (x)=1-e-ax, x >=0 (3)
Wherein, a is a time constant, and e is the nature truth of a matter.
Can be with by above formula, F (x) ∈ [0,1), and the monotone decreasing in domain, therefore function F (x) must have in 0~+∞
Inverse function seeks its inverse function:
Due to 0 < 1-F (x)≤1, above formula can simplify for
By formula (5) it can be seen that by meet (0,1] equally distributed Random sampling obtains obeying exponential distribution random number x.
It takesThe exponential distribution random-number distribution generated by the equal distribution random numbers of the above unit by inverse function method
Figure such as Fig. 5.1000 group squares are evenly dividing to the above exponential distribution random number value range and are counted, final statistical chart is such as
Shown in Fig. 6.
The method of the nuclear signal amplitude statistics simulated behavior includes: by practical nuclear spectrum Curves Recognition and digitizing
Each energy level amplitude and counting rate are obtained, then passes through Monte Carlo method direct sampling and exports the random number；Wherein to reality
The identification of nuclear energy spectral curve and digitized process includes:
Step S221 is filtered practical spectrum curve figure, noise reduction；Step S222 is asked by split plot design between maximum kind
Threshold value out, and spectrum curve figure is subjected to binary conversion treatment, then the number of each point on spectrum curve is extracted by pixel scanning method
Value is coordinate；Step S223, repairs spectrum curve and is quantized.
Specifically, the method for passing through Monte Carlo method direct sampling and exporting the random number, i.e., special by covering
A series of each point value on Caro method direct sampling spectrum curve and curve, to obtain random random numbers, thus with mould
The randomness of nucleoid decay process.
The method being filtered in the step S221 to practical spectrum curve figure is tieed up practical spectrum curve figure
Filtering processing of receiving is interfered with filtering out the Gaussian noise in spectrum curve figure to reduce noise bring as far as possible.
The specific implementation process of the method for the nuclear signal amplitude statistics simulated behavior is as follows:
Practical spectrum curve figure is filtered in the step S221, the specific implementation step of noise reduction it is as follows:
Practical spectrum curve figure is filtered by Wiener filtering, noise reduction process, i.e., the described Wiener filter is one kind
Linear filter, and still it is a kind of based on minimum mean square error criterion, to the optimal estimation device of stationary process.
Assuming that Wiener filter input signal is s (t), superimposed noise n (t).Output signal x (t) passes through filter g (t)
It is obtained by following convolution algorithm:
X (t)=g (t) * (s (t)+n (t)) (6)
For the signal x (t) estimated, it is expected that being equal to s (t).
Its error are as follows: e (t)=s (t+d)-x (t) (7)
Variance are as follows: e2(t)=s2(t+d)-2s(t+d)x(t)+x2(t) (8)
Wherein s (t+d) is desired filter output.
Write x (t) as convolution integral, i.e.,
Square error can be calculated are as follows:
Wherein RsIt is the auto-correlation function of s (t), RxIt is the auto-correlation function of x (t), RxsIt is the auto-correlation of x (t) He s (t)
Function.The final purpose of Wiener filtering is exactly to seek optimal g (t), so that E (e2) minimum.
Threshold value is found out by split plot design between maximum kind in the step S222, and spectrum curve figure is carried out at binaryzation
It manages, then extracts the numerical value i.e. coordinate of each point on spectrum curve by pixel scanning method；
The specific algorithm process of maximum variance between clusters is as follows:
If the gray value of piece image is 1~m, the pixel number that wherein gray value is i is ni, N expression image pixel
Point sum, then gray value is the probability that i occurs are as follows:
Enabling gray value be greater than threshold value k is C1Group, i.e. C1={ 1~k }, gray value are then C greater than threshold value k's2Group, C2={ k+
1~m }, then C1And C2The probability of appearance is respectively as follows:
C is calculated1And C2Gray average are as follows:
Wherein,It can so obtain:
μr=ω1·μ1+ω2·μ2 (16)
Thus the variances sigma between two groups can be calculated2Are as follows:
σ2(k)=ω1(μ1-μr)2+ω2(μ2-μr)2 (17)
Formula (16) substitution formula (17) can be obtained: σ2(k)=ω1ω2(μ2-μ1)2
So optimal threshold
T*=Arg max { σ2(k) }, (18) 0≤k < m-1
Acquire segmentation threshold T*=0.6353.
Being repaired and quantized to spectrum curve in the step S223, specific step is as follows:
The numerical value that practical nuclear spectrum curve graph extracts each point on nuclear energy spectral curve after filtering and noise reduction, binaryzation is sat
Mark, need to extract spectrum curve feature, and curve is quantized.Detailed process is as follows:
Firstly, Straight Line Identification identifies straight in nuclear energy spectrogram that is, by the row and column of scanning nuclear energy spectral curve binary map
Line；
Secondly, fixed point, cross, the ordinate of coordinate system where judging spectrum curve by the straight line identified, and origin is positioned,
Generally from top to bottom, it scans from left to right, the straight line identified is just horizontal, ordinate；
Third, spectrum curve feature extraction.For the influence for reducing frame and coordinate pair curve in image, frame need to be filtered
It removes.Filter out after frame again by pixel scan method line by line or scan by column point that pixel is 0 (black is 0 in bianry image,
1) white is.
Finally, curve quantizes.After extracting curve, by calculating the spectrum curve available point scanned to scan origin
Row and stringer distance determine position of the pixel in figure, be somebody's turn to do finally by multiplied by the scale factor for expanding coordinate
The coordinate value of pixel.
Final extraction spectrum curve characteristic effect is as shown in Figure 7.
And spectrum curve Preliminary Simulation effect is as shown in Figure 8.
Further, it can be seen from Fig. 7 and Fig. 8, the spectrum curve figure of obtained simulation is compared with proper energy spectral curve in certain points
Data lack.To be truly reflected practical spectrum curve characteristic as far as possible, need that the data of missing fill up repairing
It is multiple.
Specifically, described fill up the number lacked during spectrum curve feature extraction by cubic spline interpolation
Strong point, and stretched by the expansion of the ratio of coordinate to obtain the numerical value of each point on spectrum curve figure, it is effective to the data of missing to realize
It fills up and repairs in ground.
The cubic spline interpolation fills up the specific of the data point lacked during spectrum curve feature extraction
Algorithm is as follows:
Piecewise function S (x) on interval of definition [a, b], if meeting:
1. S (x) is in each subinterval [xi, xi+1] on be a cubic polynomial function；
2. S (x) has continuous second dervative on entire section [a, b].
Then S (x) is referred to as on section [a, b] about a=x0< x1< ... < xnA cubic spline function of=b.To three
Secondary spline interpolation problem are as follows: the n+1 node x of given function g (x)0, x1..., xnObtain function y0, y1..., yn, ask one three
Secondary spline function S (x) makes its satisfaction:
S(xj)=yj, j=0,1 ..., n (19)
Wherein, function S (x) is known as the cubic spline functions of g (x).
If S (x) is the sample spline interpolation function three times of f (x), it must satisfy the following conditions:
1. interpolation condition, i.e.,
S(xj)=yj, j=0,1 ..., n-1
2. the condition of continuity, i.e.,
3. the first derivative condition of continuity, i.e.,
4. the second dervative condition of continuity, i.e.,
By the effect picture after cubic spline interpolation, as shown in figure 9, can see by its partial enlarged view, cubic spline
Data point after interpolation is more smooth, more approaches actual value.
Practical nuclear spectrum curve simulation effect finally obtains practical nuclear spectrum curve graph after above-mentioned image procossing
It is as shown in Figure 10 that the spectrum curve simulates effect picture.
Specifically, by each point value on Monte Carlo method direct sampling spectrum curve and curve, to obtain a system
Random random number is arranged, thus to simulate the randomness of nuclear decay process.
Figure 11 shows the effect picture of the simulation random generating process of nuclear signal；
Figure 12 shows that (this figure is by practical spectrum curve figure numerical value using Monte Carlo method direct sampling final effect figure
After obtaining energy level and counting rate this array after change, what random sampling procedure and counting obtained.This figure is suitable for proving by Meng Teka
The reasonability and accuracy of sieve sampling).
Numerical value (the abscissa of each point on simulation spectrum curve and curve has been obtained by numbers above image processing process
For road location Channel, ordinate is counting rate Count), then can be obtained with this group of data of Monte Carlo method direct sampling
(energy level such as, but not limited to passes through what multichannel analyzer quantified to a series of random energy levels, and road location refers to nuclear decay
What the energy of process release obtained after multichannel analyzer quantifies) random number, thus to simulate the randomness of nuclear decay process.Most
The random number is counted again afterwards, available simulation spectrum curve figure, on the one hand can verify the reliable of system in this way
Property and accuracy, on the other hand can also be with inverting in multichannel analyzer, to demarcate the accuracy of multichannel analyzer.
Simulation calculating is carried out to probability P (A)=p (unknown) that certain event A occurs using Monte Carlo method, it is specific to count
Calculation method:
(1) n times are carried out and repeat independent sampling test, calculating event A frequency is nA。
Introduce stochastic variable Xi, indicate event A frequency in i-th test, enable
Then have
(2) it calculates event A and repeats the occurrence frequency f in independent sampling test in n timesN, it is
(3) when N is sufficiently big, with probability fNAs probability P (A)=p estimated valueFor
(4) estimated value is requiredFor probability P (A)=p unbiased esti-mator, i.e.,
And direct sampling, the i.e. characteristic to nuclear signal on time and amplitude are with the random of two groups of obedience different distributions
Number is simulated, and random number be it is discrete, it is discontinuous.Sampling for discrete random sequence, the non-convention of direct sampling method
Think.
The specific sampling process of discrete distribution direct sampling method is as follows:
If the value range of discrete random variable X is Xi(i=0,1,2,3 ...), probability distribution are P (X=Xi)=Pi(i
=0,1,2,3...).Wherein Pi>=0,
(1) equally distributed random number r on (0,1) section is generated；
(2) positive integer n=0,1,2... are acquired, so that r meets
(3) sample value for extracting discrete random variable X is X=Xn.And as 0 < r≤P0When X=X0；
(4) step (1), (2), (3) are repeated until extracting n sample value.
Due to generation (0,1) if equally distributed random number r is in sectionProbability be
That is eventThe probability of appearance is equal to event X=XnThe probability of generation.
Again because random number r obeys being uniformly distributed on (0,1), probability density function is
Its distribution function is as follows:
Therefore it is X=x that the random number r generated, which draws sample value,nProbability be
It follows that being drawn into (X=X by direct sampling methodn) probability be equivalent to random number XnIn random number sequence X1,
X2... XnThe frequency of appearance.
It can be by following proof for direct sampling method reliability:
If X is discrete random variable, probability distribution Pi=P { X=Xi, wherein i=1,2 ....X is respectively with PiIt takes
Obtain Xi, thenEvent | X-E (X) | >=ε indicates that stochastic variable X acquirement is all and meets inequality | Xi- E (X) | >=ε's can
It can value Xi, then
Due to event X=XiThe probability that (i=0,1,2 ... N) occurs is pi(0 < pi< 1), then X ≠ XiProbability be then
1-pi, and each X=XiThe probability of generation is constant, and sampling results are unrelated with other each extraction results every time.Therefore X=
XiIndividual event is a bernoulli experiment, then sampling n times, then be n again Bernoulli trials.If enabling event A (X=Xi) occur
Number be nA, i.e. nA~B (n, p).Due to X1, X2..., XnBe n it is mutually indepedent and obey that the 0-1 that parameters are p is distributed with
Machine variable, and
Have
It is given
Any ε > 0 then has
It can be derived from by (4.31) formula
And
Therefore it can be derived from
Abbreviation obtains
I.e. when the frequency n of extraction is bigger, the frequency ratio of event A occurs after sampling number and population of samples is closer to thing
The probability that part A occurs.
Its error of random number is extracted by direct sampling are as follows:
It enablesTherefore
I.e.It is the unbiased esti-mator of p,
That is the number of sampling n is bigger, estimated valueCloser to theoretical value p.
Taking the above-mentioned ideal embodiment according to the present invention as inspiration, through the above description, relevant staff is complete
Various changes and amendments can be carried out without departing from the scope of the technological thought of the present invention' entirely.The technology of this invention
Property range is not limited to the contents of the specification, it is necessary to which the technical scope thereof is determined according to the scope of the claim.
Claims (1)
1. a kind of simulation spectrum curve emulation mode, which comprises the steps of:
Step S1 obtains practical nuclear spectrum curve graph；
Step S2 handles to obtain simulation spectrum curve practical nuclear spectrum curve graph；
Practical nuclear spectrum curve graph is handled in step S2 and includes: in the method for obtaining simulation spectrum curve
Step S21 carries out Curves Recognition to practical nuclear spectrum curve graph and spectrum curve quantizes, each to obtain spectrum curve
The numerical value of point；
Step S22 obtains the random number about each nuclear level by Monte Carlo method this group of numerical value of random direct sampling, with
Simulate the randomness of nuclear decay process；
Step S23 carries out statistical disposition to the random number and obtains the simulation spectrum curve；
Curves Recognition is carried out to practical nuclear spectrum curve graph in the step S21 and spectrum curve quantizes to obtain to set a song to music
The method of the numerical value of line each point includes:
Respectively the set a song to music image of line chart of practical nuclear energy is again shown practical spectrum curve figure after filtering and noise reduction is handled, and root
Spectrum curve data are obtained according to each key point that the practical spectrum curve figure of display copies the nuclear energy spectral curve, can be set a song to music with establishing
Line database；
In step S22 by Monte Carlo method this group of numerical value of random direct sampling obtain the random number about each nuclear level with
The method of randomness for simulating nuclear decay process includes:
The simulation of nuclear signal time statistical property；And nuclear signal amplitude statistics simulated behavior；
The method of the nuclear signal time statistical property simulation includes: when realizing nuclear signal by obeying the random number of exponential distribution
Between statistical property simulate, wherein
The random number of exponential distribution by (0,1] equally distributed random number by inverse function method converts to obtain, and (0,1] uniformly point
Cloth random number is suitable for acquiring by linear congruential method.
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| CN108416355B (en) * | 2018-03-09 | 2021-07-30 | 浙江大学 | Industrial field production data acquisition method based on machine vision |
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| CN111273337B (en) * | 2020-02-27 | 2022-11-29 | 成都工贸职业技术学院 | Nuclear energy spectrum processing method based on Monte Carlo pulse interpolation method |
| CN111553111B (en) * | 2020-04-30 | 2023-03-28 | 成都航空职业技术学院 | Digital imitation nuclear signal generator based on MCNP |
| CN112462675B (en) * | 2021-01-27 | 2021-05-07 | 泛华检测技术有限公司 | Cascaded dual-index nuclear pulse signal generating device and control method thereof |
| CN112462676B (en) * | 2021-01-27 | 2021-05-07 | 泛华检测技术有限公司 | Device capable of simulating overlapped nuclear pulse signal generation and control method thereof |
| CN114422041B (en) * | 2021-12-23 | 2023-03-24 | 中国原子能科学研究院 | Nuclear signal simulation method, device, terminal and storage medium |
| CN114241846A (en) * | 2021-12-24 | 2022-03-25 | 西安恒律模训科技发展有限公司 | Simulation gamma radioactive nuclide identification training method and system thereof |
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