CN116466384A

CN116466384A - Method and device for processing scintillation pulse, electronic equipment and storage medium

Info

Publication number: CN116466384A
Application number: CN202310706671.9A
Authority: CN
Inventors: 田正光; 付乙; 吕旭东; 谢庆国
Original assignee: Raycan Technology Co Ltd
Current assignee: Raycan Technology Co Ltd
Priority date: 2023-06-15
Filing date: 2023-06-15
Publication date: 2023-07-21
Anticipated expiration: 2043-06-15
Also published as: CN116466384B

Abstract

The application provides a processing method and device of scintillation pulse, electronic equipment and storage medium, wherein the processing method comprises the following steps: carrying out Gaussian shaping on the pulse to be processed; segmenting the pulse to be processed after Gaussian shaping into a first section of Gaussian waveform and a second section of Gaussian waveform according to a preset method; processing the first section of Gaussian waveform and/or the second section of Gaussian waveform by adopting a preset calculation method to enable the first section of Gaussian waveform and the second section of Gaussian waveform to be symmetrical; the symmetrically processed gaussian waveform is adopted to fit the shape of the pulse to be processed. The processing method provided by the application acts on the digitized pulse signals, on one hand, the scintillation pulse can be symmetrically processed under the condition that the pulse to be processed is ensured not to be greatly widened, the fitting degree is improved, the FPGA is easy to realize, the pulse counting efficiency is improved, and the detection performance is improved; on the other hand, the purposes of reducing the complexity of the front-end analog circuit, reducing the power consumption on a board, reducing the occupied space of the shaping circuit and simplifying the energy fitting process can be achieved.

Description

Method and device for processing scintillation pulse, electronic equipment and storage medium

Technical Field

The present invention relates to the field of data processing, and in particular, to a method and apparatus for processing scintillation pulse, an electronic device, and a storage medium.

Background

Energetic particles, for example: gamma particles, alpha particles, protons and the like can be applied to various detection scenes such as security check, food safety, geological exploration, nuclear medicine and the like to realize corresponding functions. The main equipment used for high-energy particle detection comprises a detector, an upper computer and the like. The detector generally comprises a scintillation crystal, a photoelectric conversion device and readout electronics, wherein the energy of the energetic particles is deposited through the scintillation crystal to convert the energetic particles into visible light, and the photoelectric conversion device further converts the visible light into electrical pulses. The electric pulse is digitized by a digitizing method integrated in the read-out electronics part, and the upper computer performs subsequent processing on the digitized data to obtain the energy spectrum and time spectrum of the high-energy particles.

After the high-energy particles are digitized, the original multiple sampling points are transmitted to an upper computer in the modes of Ethernet, serial ports, wireless networks and the like, and then the energy is calculated through a software iterative algorithm. In the existing method, because pulse signals have the characteristic of short-term burst, such as common neutron petroleum logging, the pulse number can reach 100KCPS, an average pulse can be generated every 10 mu s, a plurality of original sampling points are transmitted, the extremely high bandwidth can be occupied certainly, the counting rate is reduced, and when the pulse signals are fitted on an upper computer, the ultra-high CPU time is occupied for fitting each pulse because of repeated iteration.

In order to solve the above problems, in the prior art, an original pulse is shaped into a gaussian signal by a gaussian shaping circuit, then the gaussian signal is sampled by using a multi-voltage threshold sampling Method (MVT), and a plate-level fitting is performed on the acquired gaussian signal by using a least square method, and the method does not use a server or a computer or other equipment with strong computing capability. However, when the method is adopted, more than three stages of amplifying circuits are usually needed when the original pulse is shaped into Gaussian pulse, and the original pulse with the length of only 100ns is widened to be more than 1 mu s, so that the method reduces the resource occupation amount of an FPGA fitting algorithm, but additionally introduces a multi-stage front-end analog shaping circuit, the pulse counting rate is reduced in the shaping process, the probability of pulse stacking is increased, the effective pulse counting amount in unit time is reduced, the detection performance is reduced, the circuit board area and the board upper power consumption are increased, the requirement on a power supply part is more strict, and the development difficulty is increased.

Disclosure of Invention

The application provides a method and a device for processing scintillation pulses, electronic equipment and a storage medium, so as to solve at least one of the problems.

According to an aspect of the present application, there is provided a processing method of scintillation pulse, the processing method including: carrying out Gaussian shaping on the pulse to be processed; segmenting the pulse to be processed after Gaussian shaping into a first section of Gaussian waveform and a second section of Gaussian waveform according to a preset method; processing the first section of Gaussian waveform and/or the second section of Gaussian waveform by adopting a preset calculation method so as to enable the first section of Gaussian waveform and the second section of Gaussian waveform to be symmetrical; and fitting the shape of the pulse to be processed by adopting a Gaussian waveform subjected to symmetrical processing.

According to some embodiments, the preset method comprises dividing the gaussian shaped pulse to be processed into the first segment of gaussian waveform and the second segment of gaussian waveform by a peak of the pulse to be processed.

According to some embodiments, the processing the first segment of gaussian waveform and/or the second segment of gaussian waveform using a preset calculation method includes: acquiring a first expected fitting equation of the first section of Gaussian waveform; acquiring a second expected fitting equation of the second Gaussian waveform; obtaining a corresponding relation model of the first expected fitting equation and the second expected fitting equation; and processing the first section of Gaussian waveform and/or the second section of Gaussian waveform according to the corresponding relation model so as to enable the first section of Gaussian waveform and the second section of Gaussian waveform to be symmetrical.

According to some embodiments, the first expected fit equation is:the second expected fit equation is: />Wherein, the liquid crystal display device comprises a liquid crystal display device,a is the peak value of the pulse to be processed, x ₁ X represents any time in the first segment of Gaussian waveform ₂ Representing any time in the second Gaussian waveform, b is the time corresponding to the peak value of the pulse to be processed, x ₁ ＜b＜x ₂ ，y ₁ Represented by the sum x in the first segment Gaussian waveform ₁ Corresponding amplitude, y ₂ Represented by the sum x in the second segment Gaussian waveform ₂ Corresponding amplitude, c ₁ And c ₂ Are all constant.

According to some embodiments, the processing the first and/or second gaussian waveforms according to the correspondence model comprises: processing the first section of Gaussian waveform by adopting a first corresponding relation model to enable the first section of Gaussian waveform to be symmetrical to the second section of Gaussian waveform;

the first correspondence model is:wherein L is ₁ Representing the time corresponding to a particular amplitude on said first gaussian waveform,/for a particular amplitude>Representing a first target time,/->The absolute value of the difference from b is equal to L ₂ An absolute value of the difference from b, b being the time corresponding to the peak value of the pulse to be processed, c ₁ And c ₂ Are all constant.

According to some embodiments, the processing the first and/or second gaussian waveforms according to the correspondence model comprises:

Processing the second section of Gaussian waveform by adopting a second corresponding relation model to enable the second section of Gaussian waveform to be symmetrical to the first section of Gaussian waveform;

the second correspondence model is:wherein L is ₂ Representing the corresponding time of a specific amplitude on said second gaussian waveform,/for each of the two different phases>Representing a second target time,/->The absolute value of the difference from b is equal to L ₁ An absolute value of the difference from b, b being the time corresponding to the peak value of the pulse to be processed, c ₁ And c ₂ Are all constant.

According to some embodiments, the pulses to be processed are pulse data acquired by a detector and digitized.

According to some embodiments, the method for digitizing the pulses to be processed includes a multi-voltage threshold sampling method, a peak hold method, and an ADC sampling method.

According to some embodiments, the fitting the shape of the pulse to be processed with a symmetrically processed gaussian waveform comprises: and fitting the shape of the pulse to be processed by using a least square method by adopting a Gaussian waveform subjected to symmetrical processing.

According to some embodiments, the gaussian shaping of the pulse to be processed comprises: and carrying out Gaussian shaping on the pulse to be processed according to a preset Gaussian shaping circuit.

According to some embodiments, the shape of the pulse to be processed is used to obtain energy information of the pulse to be processed.

According to an aspect of the present application, there is provided a processing apparatus of scintillation pulses, the processing apparatus comprising: the shaping module is used for carrying out Gaussian shaping on the pulse to be processed; the segmentation module is used for segmenting the pulse to be processed after Gaussian shaping into a first segment of Gaussian waveform and a second segment of Gaussian waveform according to a preset method; the processing module is used for processing the first section of Gaussian waveform and/or the second section of Gaussian waveform by adopting a preset calculation method so as to enable the first section of Gaussian waveform and the second section of Gaussian waveform to be symmetrical; and the fitting module is used for fitting the shape of the pulse to be processed by adopting the Gaussian waveform subjected to symmetrical processing.

According to some embodiments, the processing module processes the first and/or second gaussian waveforms by: acquiring a first expected fitting equation of the first section of Gaussian waveform; acquiring a second expected fitting equation of the second Gaussian waveform; obtaining a corresponding relation model of the first expected fitting equation and the second expected fitting equation; and processing the first section of Gaussian waveform and/or the second section of Gaussian waveform according to the corresponding relation model to enable the first section of Gaussian waveform and/or the second section of Gaussian waveform to be symmetrical.

According to some embodiments, the first expected fit equation is:the second expected fit equation is: />Wherein a is the peak value of the pulse to be processed, and x is ₁ X represents any time in the first segment of Gaussian waveform ₂ Representing any time in the second Gaussian waveform, b is the time corresponding to the peak value of the pulse to be processed, x ₁ ＜b＜x ₂ ，y ₁ Represented by the sum x in the first segment Gaussian waveform ₁ Corresponding amplitude, y ₂ Represented by the sum x in the second segment Gaussian waveform ₂ Corresponding amplitude, c ₁ And c ₂ Are all constant.

According to some embodiments, the processing module processes the first segment of gaussian waveform and/or the second segment of gaussian waveform according to the correspondence model further comprises: processing the first section of Gaussian waveform by adopting a first corresponding relation model to enable the first section of Gaussian waveform to be symmetrical to the second section of Gaussian waveform;

According to some embodiments, the processing module processes the first segment of gaussian waveform and/or the second segment of gaussian waveform according to the correspondence model further comprises: processing the second section of Gaussian waveform by adopting a second corresponding relation model to enable the second section of Gaussian waveform to be symmetrical to the first section of Gaussian waveform;

According to some embodiments, the fitting module fits the shape of the pulse to be processed using a symmetrically processed gaussian waveform comprises: and fitting the shape of the pulse to be processed by using a least square method by adopting a Gaussian waveform subjected to symmetrical processing.

According to some embodiments, the shaping module performs gaussian shaping on the pulse to be processed, including: and shaping the pulse to be processed according to a preset Gaussian shaping circuit.

According to some embodiments, the processing device further comprises an energy acquisition module that integrates according to the shape of the pulse to be processed to acquire energy information of the pulse to be processed.

According to an aspect of the present application, there is provided an electronic device including: one or more processors; a storage means for storing one or more programs; the one or more programs, when executed by the one or more processors, cause the one or more processors to implement the method of processing scintillation pulses as described above.

According to an aspect of the present application, an electronic device is provided, including the processing apparatus of scintillation pulse.

According to an aspect of the present application, there is provided a storage medium having stored thereon computer program instructions which, when executed by a processor, cause the processor to implement a spatial encoding method or a spatial decoding method as described above.

According to some example embodiments of the present application, the processing method of scintillation pulse provided by the present application acts on the digitized pulse signal, on one hand, the scintillation pulse can be symmetrically processed under the condition of ensuring that the pulse to be processed is not greatly widened, the fitting degree is improved, the implementation of the FPGA is easy, the pulse counting efficiency is improved, and the detection performance is further improved; on the other hand, the purposes of reducing the complexity of the front-end analog circuit, reducing the power consumption on a board, reducing the occupied space of the shaping circuit and simplifying the energy fitting process can be achieved.

Drawings

The present application will be further illustrated by way of example embodiments, which will be described in detail with reference to the accompanying drawings. The embodiments are not limiting, in which like reference numerals designate like structure, wherein:

FIG. 1 shows a flow diagram of a method of processing scintillation pulses in accordance with an example embodiment of the present application;

FIG. 2 shows a schematic diagram of a pulse to be processed according to an example embodiment of the present application;

FIG. 3 shows a schematic diagram of a shaped scintillation pulse in accordance with an example embodiment of the present application;

FIG. 4 shows a flow diagram of a method of processing scintillation pulses in accordance with an example embodiment of the present application;

FIG. 5 shows a schematic diagram of another shaped scintillation pulse in accordance with an example embodiment of the present application;

FIG. 6 shows a schematic diagram of a transformed scintillation pulse in accordance with an example embodiment of the present application;

fig. 7 shows a schematic structural diagram of a processing device of scintillation pulses according to an exemplary embodiment of the present application;

fig. 8 shows an electronic device according to an example embodiment of the present application.

Detailed Description

In order to make the above objects, features and advantages of the present application more comprehensible, embodiments accompanied with figures are described in detail below. In the following description, numerous specific details are set forth in order to provide a thorough understanding of the present application. This application is, however, susceptible of embodiment in many other forms than those described herein and similar modifications can be made by those skilled in the art without departing from the spirit of the application, and therefore the application is not to be limited to the specific embodiments disclosed below.

It will be understood that when an element is referred to as being "fixed to" another element, it can be directly on the other element or intervening elements may also be present. When an element is referred to as being "connected" to another element, it can be directly connected to the other element or intervening elements may also be present. The terms "vertical," "horizontal," "left," "right," and the like are used herein for illustrative purposes only. The described features, structures, or characteristics may be combined in any suitable manner in one or more embodiments. In the following description, numerous specific details are provided to give a thorough understanding of embodiments of the present application. One skilled in the relevant art will recognize, however, that the aspects of the application can be practiced without one or more of the specific details, or with other methods, components, materials, devices, operations, etc. In these instances, well-known structures, methods, devices, implementations, materials, or operations are not shown or described in detail.

The flow diagrams depicted in the figures are exemplary only, and do not necessarily include all of the elements and operations/steps, nor must they be performed in the order described. For example, some operations/steps may be decomposed, and some operations/steps may be combined or partially combined, so that the order of actual execution may be changed according to actual situations.

The terms first, second and the like in the description and in the claims of the present application and in the above-described figures, are used for distinguishing between different objects and not for describing a particular sequential order. Furthermore, the terms "comprise" and "have," as well as any variations thereof, are intended to cover a non-exclusive inclusion. For example, a process, method, system, article, or apparatus that comprises a list of steps or elements is not limited to only those listed steps or elements but may include other steps or elements not listed or inherent to such process, method, article, or apparatus. The term "and/or" and/or "includes any and all combinations of one or more of the associated listed items.

Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs. The terminology used herein in the description of the application is for the purpose of describing particular embodiments only and is not intended to be limiting of the application.

Specific embodiments according to the present application will be described in detail below with reference to the accompanying drawings.

As described in the background art above, the method of processing scintillation pulses employed in the prior art has some problems. For example, taking the application scenario of petroleum logging as an example, the digitization of scintillation pulses is generally performed by the MVT method or the ADC method in this scenario. However, the method is limited by the computational power of the chip, and the fitting method is too complex, and the fitting algorithm adopted after the digitization cannot be completed on embedded chips such as FPGA, STM32, DSP, and the like, so that the obtained original sampling points are required to be transmitted to an upper computer in the modes of Ethernet, serial ports, wireless networks, and the like, and then the energy is calculated through the algorithm of software iteration. In the petroleum logging process, the scintillation pulse event shows the characteristic of periodic burst, the data volume of original sampling points can reach 10Mbps to 1Gbps, and is limited in the use scene of petroleum detection, the underground depth is as high as ten thousand meters, the characteristic that the environment temperature is high, the transmission mode can only adopt the mode of carrier communication to transmit, the bandwidth is only about 100Kbps, the requirement cannot be met, the count rate is reduced, and the ultra-high CPU time is occupied. The prior processing method reduces the resource occupation amount of the FPGA fitting algorithm, but additionally introduces a multi-stage front-end analog shaping circuit, thereby not only increasing the area of a circuit board, but also increasing the power consumption on the board, having more strict requirements on a power supply part and greatly reducing the counting rate due to the influence on pulse width.

In order to solve the technical problems provided by the background technology, the application provides a method and a device for processing scintillation pulse, electronic equipment and a storage medium.

According to an embodiment of the present application, there is provided a method for processing a scintillation pulse, as shown in fig. 1, generally including the steps of:

s100: and carrying out Gaussian shaping on the pulse to be processed.

The method for performing gaussian shaping on the pulse to be processed can comprise shaping by using a gaussian circuit. Specifically, the step S100 may further include:

and shaping the pulse to be processed according to a preset Gaussian shaping circuit.

The preset Gaussian shaping circuit can be designed according to a shape characteristic model of the pulse to be processed.

Of course, it will be understood by those skilled in the art that other manners of shaping the gaussian circuit may be adopted in the prior art, and the shaping method is not limited to the manner of adopting the gaussian shaping circuit, for example, the ADC may be adopted to collect the pulse to be processed, and then the digital filter may be adopted to process the pulse to be processed, and the pulse to be processed may be shaped.

The pulses to be processed may include pulse data acquired by the detector and digitized.

The detector includes a semiconductor detector or a scintillation detector, etc. The scintillation detector may include structures such as a scintillation crystal including bismuth germanate, lanthanum bromide, sodium iodide, and a photoelectric conversion device including a photodiode, an Avalanche Photodiode (APD), a silicon photomultiplier (SiPM), and the like.

The digitizing method comprises a high-speed ADC direct digitizing method, a peak hold method, an MVT method and the like. The method of direct digitization of the high-speed ADC firstly shapes and widens the scintillation pulse signal, and then uses the high-speed ADC (for example, the processing speed is higher than 1 GSps) to conduct digitization sampling. Peak-hold methods lock the amplitude of a pulse signal, such as an electrical pulse signal, and then acquire the amplitude using a corresponding device, such as an ADC, to obtain energy information of the pulse. The MVT method is used for fixing a plurality of thresholds, such as voltage thresholds, and only digitally sampling the time when the scintillation pulse passes through the thresholds, such as the voltage thresholds, so that a plurality of sampling points are acquired in a rapid rising edge stage, a series of time-threshold pair information is obtained, and then the particle energy deposition information is acquired by a pulse fitting method.

S200: segmenting the pulse to be processed after Gaussian shaping into a first section of Gaussian waveform and a second section of Gaussian waveform according to a preset method.

Generally, the model of the digitized scintillation pulse is:wherein V is the amplitude of the scintillation pulse waveform, V _p Is the peak size of the scintillation pulse waveform, t is the time, t _p Is the time corresponding to the peak value, t ₀ Is the start time and ζ is the decay time constant of the falling edge of the scintillation pulse waveform.

As described above with reference to fig. 2, a typical pulse to be processed includes a fast rising edge and an exponentially falling edge, where the signal amplitude changes drastically in unit time, and the high frequency component is more, and the signal amplitude changes relatively gently in unit time.

In one example of the present application, the preset method includes dividing the gaussian shaped pulse to be processed into a first gaussian waveform and a second gaussian waveform with a peak of the pulse to be processed as a boundary. As shown in fig. 3, the shaped pulse to be processed includes a first gaussian waveform and a second gaussian waveform, wherein the dashed line is a dividing line.

S300: and processing the first section of Gaussian waveform and/or the second section of Gaussian waveform by adopting a preset calculation method so as to make the first section of Gaussian waveform and the second section of Gaussian waveform symmetrical.

The step S300 includes processing the first gaussian waveform to be symmetrical to the second gaussian waveform, processing the second gaussian waveform to be symmetrical to the first gaussian waveform, and processing the first gaussian waveform and the second gaussian waveform to be symmetrical to each other.

As shown in fig. 4, in an example of the present application, the step S300 includes:

s310: acquiring a first expected fitting equation of a first section of Gaussian waveform;

s320: acquiring a second expected fitting equation of a second section of Gaussian waveform;

s330: obtaining a corresponding relation model of a first expected fitting equation and a second expected fitting equation;

s340: and processing the first section of Gaussian waveform and/or the second section of Gaussian waveform according to the corresponding relation model so as to make the first section of Gaussian waveform and the second section of Gaussian waveform symmetrical.

Illustratively, as shown in fig. 3, the left side of the dotted line is a first segment of gaussian waveform, the right side is a second segment of gaussian waveform, and the equation of the first segment of gaussian waveform is:wherein a is ₁ For peak value of pulse to be processed, x ₁ Representing any time in the first segment of the Gaussian waveform, b ₁ For pulses to be processedTime corresponding to peak value of x ₁ ＜b ₁ ，y ₁ Represented by the sum x in the first segment of Gaussian waveform ₁ Corresponding amplitude, c ₁ Is constant.

The equation for the second segment of gaussian waveform is:wherein a is ₂ For peak value of pulse to be processed, x ₂ Representing any time in the second segment of the Gaussian waveform, b ₂ For the time corresponding to the peak value of the pulse to be processed, x ₂ ＞b ₂ ，y ₂ Represented by the sum x in the second segment Gaussian waveform ₂ Corresponding amplitude, c ₂ Is constant.

In the two equations above, a ₁ And a ₂ For the peak value of the Gaussian function, the two peak values are identical, therefore, a ₁ =a ₂ And b ₁ And b ₂ Time corresponding to peak value, therefore b ₁ =b ₂ . And (3) unifying the a and the b in the equations to obtain a first expected fitting equation and a second expected fitting equation.

That is, the first expected fit equation is:where a is the peak value of the pulse to be processed, x ₁ Representing any time in the first Gaussian waveform, b is the time corresponding to the peak value of the pulse to be processed, x ₁ ＜b，y ₁ Represented by the sum x in the first segment of Gaussian waveform ₁ Corresponding amplitude, c ₁ Is constant.

The second expected fit equation is:where a is the peak value of the pulse to be processed, x ₂ Representing any time in the second Gaussian waveform, b is the time corresponding to the peak value of the pulse to be processed, x ₂ ＞b，y ₂ Represented by the sum x in the second segment Gaussian waveform ₂ Corresponding amplitude, c ₂ Is constant.

Combining the first expected fit equation and the second The expected fit equation may find that the two differ only in c ₁ And c ₂ 。

Transforming the gaussian function with y as the unknown can result in:further, for a set of time pairs L of acquired amplitude y=m ₁ And L ₂ Can be expressed as: />For L ₁ And L ₂ Can be further explained as L ₁ Representing the corresponding time of a specific amplitude on the first Gaussian waveform, L ₂ Representing the time at which the particular amplitude corresponds on the second gaussian waveform. Typically the scintillation pulse may cross the same threshold twice, once during the rising phase of the scintillation pulse, the amplitude of the scintillation pulse may cross the threshold from low to high and above the threshold. Once in the falling phase of the scintillation pulse, the amplitude of the scintillation pulse may cross the threshold value from high to low and below the threshold value. Whichever is crossed, the comparator may generate a jump and record the time when the amplitude crossed the threshold.

The processing method provided by the application can be applied to common scintillation pulse digitizing methods, such as MVT (mechanical vapor recomposition) method and high-speed ADC (analog to digital converter) direct digitizing method.

As shown in fig. 5, in practical application, taking the digitizing method of the pulse to be processed as MVT as an example, it should be specifically noted that in the MVT scenario, L ₁ And L ₂ Are unknown, and therefore L needs to be eliminated in the following calculation ₁ And L ₂ . The absolute time of the rising edge acquired by the ith threshold value is recorded as t _ip The absolute time acquired by the falling edge is recorded as t _in . By adopting the method, the collected pulse to be processed can be converted into the common Gaussian pulse if the absolute time of the falling edge is subjected to linear conversion. The linear transformation is as follows: from the following componentsAvailable->And->Thereby can obtainObtain->Further, the method can further comprise, in a first embodiment,，/>，/>wherein b is the time corresponding to the peak value of the pulse to be processed, and also the time corresponding to the symmetry axis of the Gaussian pulse, and b is unknown, so that +.>，/>I.e. the absolute time of the transformed falling edge, fig. 6 shows a schematic diagram of a transformed scintillation pulse according to an exemplary embodiment of the present application, as shown in fig. 6, the transformed waveform is an axis pair

Called graphics.

The absolute time of the rising edge is linearly transformed to transform the acquired pulse to be processed into a common Gaussian pulse. The linear transformation is as follows: from the following componentsAvailable->And->Thereby obtaining +.>Further, the->ObtainingFurther, the->，/>，/>Wherein b is the time corresponding to the peak value of the pulse to be processed, and also the time corresponding to the symmetry axis of the Gaussian pulse, and b is unknown, so that +. >，/>The absolute time of the rising edge after the transition.

In another example of the present application, the correspondence model may include a first correspondence model and a second correspondence model. At a known L ₁ And L ₂ In the case of (a), for example, when the pulse to be processed is digitized by direct digitizing by high-speed ADC, if the first Gaussian waveform is processed by the first correspondence model to be symmetrical with the second Gaussian waveform, then the method is applied to L ₁ Transforming according to a first corresponding relation model:wherein, represents L ₁ Representing the time at which a particular amplitude corresponds on the first gaussian waveform,/for a particular amplitude>Representing a first target time,/->The absolute value of the difference from b is equal to L ₂ The absolute value of the difference from b, b being the time corresponding to the peak of the pulse to be processed, c ₁ And c ₂ Are all constant.

If the second Gaussian waveform is processed by adopting the second corresponding relation model to be symmetrical with the first Gaussian waveform, then the method is applied to L ₂ Transforming according to the following second corresponding relation model:wherein L is ₂ Representing the time at which a particular amplitude corresponds on the second segment of the gaussian waveform,/for a given period of time>Representing a second target time,/->The absolute value of the difference from b is equal to L ₁ The absolute value of the difference from b, b being the time corresponding to the peak of the pulse to be processed, c ₁ And c ₂ Are all constant.

Illustratively, taking the method of direct digitizing of high-speed ADC as an example, the sampling point is (X _i ，Y _i ) Wherein X is _i For time, Y _i The voltage value is defined as the peak voltage acquired in one frame pulse as a boundary line, and the left sampling point is defined as (X) _ip ，Y _ip ) On the right side is (X _in ，Y _in ) The peak point is (X _m ，Y _m ）。

If the right sampling point (X _in ，Y _in ) The transformation is due to，/>According to a second correspondence model->Obtain->Due to->Thus, it is，/>To the time of the right after the transformation.

If the left sampling point (X _ip ，Y _ip ) The transformation is due to，/>According to the first correspondence model->Obtain->Due to->Thus, it is，/>To the time of the left after the transformation.

According to one example of the application, for symmetric processing of the pulse to be processed, it is also possible to process both the first gaussian waveform and the second gaussian waveform. For example, some wavelets in the first segment of gaussian waveform and the second segment of gaussian waveform can be selected for symmetric processing according to the actual situation of the symmetrically processed gaussian waveform, for example, a first sub-band is selected in the first segment of gaussian waveform, symmetric processing is performed through a first corresponding relation model, a second sub-band is selected in the second segment of gaussian waveform, symmetric processing is performed through a second corresponding relation model, and it can be understood that the positions corresponding to the first sub-band and the second sub-band in the two waveforms are different, and thus, the symmetric processing is performed on the wavelets needing to perform the symmetric processing in the first segment of gaussian waveform and the second segment of gaussian waveform, so that the first segment of gaussian waveform and the second segment of gaussian waveform are symmetric.

S400: the symmetrically processed gaussian waveform is adopted to fit the shape of the pulse to be processed.

The step S400 may include:

the shape of the pulse to be processed is fitted by using a least square method by using a gaussian waveform which is processed symmetrically.

The shape of the pulse to be processed is used for acquiring energy information of the pulse to be processed; the least square method is a common method for performing signal fitting in the prior art, and a person skilled in the art can easily combine the method and the device to perform fitting processing on corresponding data according to the technical scheme of the application, so that the description is omitted.

The processing method of the scintillation pulse provided by the application acts on the digitized scintillation pulse signal, on one hand, the scintillation pulse can be symmetrically processed under the condition of ensuring that the pulse to be processed is not greatly widened, the fitting degree is improved, the FPGA is easy to realize, the pulse counting efficiency is improved, and the detection performance is further improved; on the other hand, the purposes of reducing the complexity of the front-end analog circuit, reducing the power consumption on a board, reducing the occupied space of the shaping circuit and simplifying the energy fitting process can be achieved.

Corresponding to the processing method, the application also provides a processing device of the scintillation pulse. As shown in fig. 7. The processing device provided by the application generally comprises: shaping module 10, segmentation module 20, processing module 30, and fitting module 40. The shaping module 10 is used for performing gaussian shaping on the pulse to be processed. The segmentation module 20 is configured to segment the pulse to be processed after gaussian shaping into a first segment of gaussian waveform and a second segment of gaussian waveform according to a preset method. The processing module 30 is configured to process the first gaussian waveform and/or the second gaussian waveform by using a preset calculation method so that the first gaussian waveform and the second gaussian waveform are symmetrical. The fitting module 40 is configured to fit the shape of the pulse to be processed with a symmetrically processed gaussian waveform.

Further, the shaping module 10 shapes the pulse to be processed according to a preset gaussian shaping circuit. The preset Gaussian shaping circuit can be designed according to a shape characteristic model of the pulse to be processed.

The detector includes a semiconductor detector or a scintillation detector, etc. The scintillation detector comprises a scintillation crystal, a photoelectric conversion device and the like, wherein the scintillation crystal comprises bismuth germanate, lanthanum bromide, sodium iodide and the like, and the photoelectric conversion device comprises a photodiode, an Avalanche Photodiode (APD), a silicon photomultiplier (SiPM) and the like.

As with the model described above, a typical pulse to be processed includes an approximately straight, rapidly rising edge in which the signal amplitude varies drastically per unit time, and an exponentially falling edge in which the signal amplitude varies relatively gently.

In one example of the present application, the preset method includes dividing the gaussian shaped pulse to be processed into a first gaussian waveform and a second gaussian waveform with a peak of the shaped pulse to be processed as a boundary.

Illustratively, segmentation module 20 is configured to process the first segment of the gaussian waveform to be symmetrical to the second segment of the gaussian waveform, process the second segment of the gaussian waveform to be symmetrical to the first segment of the gaussian waveform, or process the first and second segments of the gaussian waveform to be symmetrical to the first and second segments of the gaussian waveform.

Illustratively, the processing module 30 processes the first segment of the gaussian waveform and/or the second segment of the gaussian waveform includes: acquiring a first expected fitting equation of a first section of Gaussian waveform; acquiring a second expected fitting equation of a second section of Gaussian waveform; obtaining a corresponding relation model of a first expected fitting equation and a second expected fitting equation; and processing the first section of Gaussian waveform and/or the second section of Gaussian waveform according to the corresponding relation model so as to make the first section of Gaussian waveform and the second section of Gaussian waveform symmetrical.

Wherein the first expected fit equation is:the second expected fit equation is:where a is the peak value of the pulse to be processed, x ₁ Expressed at any time in the first segment of Gaussian waveform, x ₂ Indicated in the second sectionAny time in the Gaussian waveform, b is the time corresponding to the peak value of the pulse to be processed, x ₁ ＜b＜x ₂ ，y ₁ Represented by the sum x in the first segment of Gaussian waveform ₁ Corresponding amplitude, y ₂ Represented by the sum x in the second segment Gaussian waveform ₂ Corresponding amplitude, c ₁ And c ₂ Are all constant.

It can be found that the first expected fit equation and the second expected fit equation are different from each other only in c ₁ And c ₂ 。

The processing device provided by the application can be applied to a common scintillation pulse digitizing method, such as an MVT method and a high-speed ADC direct digitizing method.

In practical application, taking the digitizing method of the pulse to be processed as MVT as an example, it should be specifically described that in MVT scene, L ₁ And L ₂ Are unknown, and therefore L needs to be eliminated in the following calculation ₁ And L ₂ . The absolute time of the rising edge acquired by the ith threshold value is recorded as t _ip The absolute time acquired by the falling edge is recorded as t _in . By adopting the method, the collected pulse to be processed can be converted into the common Gaussian pulse if the absolute time of the falling edge is subjected to linear conversion. The linear transformation is as follows: from the following components Available->And->Thereby can obtainObtain->Further, the method can further comprise, in a first embodiment,，/>，/>wherein b is the time corresponding to the peak value of the pulse to be processed, and also the time corresponding to the symmetry axis of the Gaussian pulse, and b is unknown, so that +.>，/>I.e. the absolute time of the falling edge after the transformation.

The collected pulse to be processed can be converted into a common Gaussian pulse if the absolute time of the rising edge is linearly converted. The linear transformation is as follows: from the following componentsAvailable->And->Thereby obtaining +.>Further, the->ObtainingFurther, the->，/>，/>Wherein b is the time corresponding to the peak value of the pulse to be processed, and is also the time corresponding to the symmetry axis of the Gaussian pulse, b is unknown,thereby obtaining +.>，/>The absolute time of the rising edge after the transition.

In another example of the present application, the correspondence model may include a first correspondence model and a second correspondence model. At a known L ₁ And L ₂ In the case of (a), for example, when the pulse to be processed is digitized by direct digitizing by high-speed ADC, if the first Gaussian waveform is processed by the first correspondence model to be symmetrical with the second Gaussian waveform, then the method is applied to L ₁ Transforming according to a first corresponding relation model: Wherein L is ₁ Representing the time at which a particular amplitude corresponds on the first gaussian waveform,/for a particular amplitude>Representing a first target time,/->The absolute value of the difference from b is equal to L ₂ The absolute value of the difference from b, b being the time corresponding to the peak of the pulse to be processed, c ₁ And c ₂ Are all constant.

If the second Gaussian waveform is processed by adopting the second corresponding relation model to be symmetrical with the first Gaussian waveform, then the method is applied to L ₂ Transforming according to the following second corresponding relation model:wherein L is ₂ Representing the corresponding time of a specific amplitude on said second gaussian waveform,/for each of the two different phases>Representing a second target time,/->The absolute value of the difference from b is equal to L ₁ An absolute value of the difference from b, b being the time corresponding to the peak value of the pulse to be processed, c ₁ And c ₂ Are all constant.

Illustratively, the fitting module 40 fits the shape of the pulse to be processed using a least squares method using a symmetrically processed gaussian waveform.

The processing device further comprises an energy acquisition module, wherein the energy acquisition module integrates according to the shape of the pulse to be processed to acquire energy information of the pulse to be processed; the least square method is a common method for performing signal fitting in the prior art, and a person skilled in the art can easily combine the method and the device to perform fitting processing on corresponding data according to the technical scheme of the application, so that the description is omitted.

The processing device for the scintillation pulse provided by the application acts on the digitized pulse signal, on one hand, the scintillation pulse can be symmetrically processed under the condition that the pulse to be processed is ensured not to be widened greatly, the fitting degree is improved, the FPGA is easy to realize, the pulse counting efficiency is improved, and the detection performance is further improved; on the other hand, the purposes of reducing the complexity of the front-end analog circuit, reducing the power consumption on a board, reducing the occupied space of the shaping circuit and simplifying the energy fitting process can be achieved.

According to an example of the present application, there is provided an electronic device, which includes the scintillation pulse processing apparatus provided in any one of the above examples, and it is understood that the electronic device can achieve the technical effect achieved by the scintillation pulse processing apparatus provided in any one of the above examples.

According to one example of the present application, another electronic device is also provided. As shown in fig. 8, the electronic device is in the form of a general purpose computing device. The components of the electronic device may include, but are not limited to: at least one processor 910, at least one memory 920, a bus 930 that connects the different system components (including the memory 920 and the processor 910), a display unit 940, and so forth. Wherein the memory 920 stores program code that can be executed by the processor 910 to cause the processor 910 to perform the methods described herein according to various exemplary embodiments of the present application. For example, the processor 910 may perform the methods as shown in fig. 1 and 4.

The memory 920 may include readable media in the form of volatile memory units, such as Random Access Memory (RAM) 9201 and/or cache memory 9202, and may further include Read Only Memory (ROM) 9203.

Memory 920 may also include a program/utility 9204 having a set (at least one) of program modules 9205, such program modules 9205 include, but are not limited to: an operating system, one or more application programs, other program modules, and program data, each or some combination of which may include an implementation of a network environment.

The bus 930 may be one or more of several types of bus structures including a memory unit bus or memory unit controller, a peripheral bus, an accelerated graphics port, a processing unit, or a local bus using any of a variety of bus architectures.

The electronic device may also communicate with one or more external devices 900 (e.g., keyboard, pointing device, bluetooth device, etc.), one or more devices that enable a user to interact with the electronic device, and/or any devices (e.g., routers, modems, etc.) that enable the electronic device to communicate with one or more other computing devices. Such communication may occur through an input/output (I/O) interface 950. Moreover, the electronic device may also communicate with one or more networks such as a Local Area Network (LAN), a Wide Area Network (WAN), and/or a public network, such as the Internet, through network adapter 960. The network adapter 960 can communicate with other modules of the electronic device via the bus 930. It should be appreciated that although not shown, other hardware and/or software modules may be used in connection with an electronic device, including but not limited to: microcode, device drivers, redundant processing units, external disk drive arrays, RAID systems, tape drives, data backup storage systems, and the like.

From the above description of embodiments, those skilled in the art will readily appreciate that the example embodiments described herein may be implemented in software, or may be implemented in software in combination with the necessary hardware. The technical solution according to the embodiments of the present application may be embodied in the form of a software product, which may be stored in a computer readable storage medium (may be a CD-ROM, a U-disk, a mobile hard disk, etc.) or on a network, and includes a number of computer program instructions to cause a computing device (may be a personal computer, a server, or a network device, etc.) to perform the above-described method according to the embodiments of the present application.

The software product may employ any combination of one or more readable media. The readable medium may be a readable signal medium or a readable storage medium. The readable storage medium can be, for example, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or a combination of any of the foregoing. More specific examples (a non-exhaustive list) of the readable storage medium would include the following: an electrical connection having one or more wires, a portable disk, a hard disk, random Access Memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

The computer readable storage medium may include a data signal propagated in baseband or as part of a carrier wave, with readable program code embodied therein. Such a propagated data signal may take any of a variety of forms, including, but not limited to, electro-magnetic, optical, or any suitable combination of the foregoing. A readable storage medium may also be any readable medium that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device. Program code embodied on a readable storage medium may be transmitted using any appropriate medium, including but not limited to wireless, wireline, optical fiber cable, RF, etc., or any suitable combination of the foregoing.

Program code for carrying out operations of the present application may be written in any combination of one or more programming languages, including an object oriented programming language such as Java, C++ or the like and conventional procedural programming languages, such as the C programming language or similar programming languages. The program code may execute entirely on the user's computing device, partly on the user's device, as a stand-alone software package, partly on the user's computing device, partly on a remote computing device, or entirely on the remote computing device or server. In the case of remote computing devices, the remote computing device may be connected to the user computing device through any kind of network, including a Local Area Network (LAN) or a Wide Area Network (WAN), or may be connected to an external computing device (e.g., connected via the Internet using an Internet service provider).

The computer readable medium carries one or more program instructions which, when executed by one of the devices, cause the computer readable medium to perform the aforementioned functions.

Those skilled in the art will appreciate that the modules may be distributed throughout several devices as described in the embodiments, and that corresponding variations may be implemented in one or more devices that are unique to the embodiments. The modules of the above embodiments may be combined into one module, or one module may be further split into a plurality of sub-modules.

According to some example embodiments of the present application, on one hand, the scintillation pulse can be symmetrically processed under the condition of ensuring that the pulse to be processed is not greatly widened, so that the fitting degree is improved, the FPGA is easy to realize, the pulse counting efficiency is improved, and the detection performance is further improved; on the other hand, the purposes of reducing the complexity of the front-end analog circuit, reducing the power consumption on a board, reducing the occupied space of the shaping circuit and simplifying the energy fitting process can be achieved.

Although the present application provides method operational steps as in the above-described embodiments or flowcharts, more or fewer operational steps may be included in the method based on routine or non-inventive labor. In steps where there is logically no necessary causal relationship, the execution order of the steps is not limited to the execution order provided in the embodiments of the present application.

In this specification, each embodiment is described in a progressive manner, and identical and similar parts of each embodiment are all referred to each other, and each embodiment mainly describes differences from other embodiments.

The foregoing has outlined rather broadly the more detailed description of embodiments of the present application, wherein specific examples have been provided herein to illustrate the principles and embodiments of the present application, and wherein the above examples are provided to assist in the understanding of the methods and concepts of the present application. Meanwhile, based on the ideas of the present application, those skilled in the art can make changes or modifications on the specific embodiments and application scope of the present application, which belong to the scope of the protection of the present application. In view of the foregoing, this description should not be construed as limiting the application.

Claims

1. A method of processing a scintillation pulse, the method comprising:

carrying out Gaussian shaping on the pulse to be processed;

segmenting the pulse to be processed after Gaussian shaping into a first section of Gaussian waveform and a second section of Gaussian waveform according to a preset method;

processing the first section of Gaussian waveform and/or the second section of Gaussian waveform by adopting a preset calculation method so as to enable the first section of Gaussian waveform and the second section of Gaussian waveform to be symmetrical;

and fitting the shape of the pulse to be processed by adopting a Gaussian waveform subjected to symmetrical processing.

2. The processing method according to claim 1, wherein the preset method includes dividing the gaussian-shaped pulse to be processed into the first segment of gaussian waveform and the second segment of gaussian waveform with a peak of the pulse to be processed as a boundary.

3. The processing method according to claim 1, wherein the processing the first segment of gaussian waveform and/or the second segment of gaussian waveform by using a preset calculation method includes:

acquiring a first expected fitting equation of the first section of Gaussian waveform;

acquiring a second expected fitting equation of the second Gaussian waveform;

obtaining a corresponding relation model of the first expected fitting equation and the second expected fitting equation;

And processing the first section of Gaussian waveform and/or the second section of Gaussian waveform according to the corresponding relation model so as to enable the first section of Gaussian waveform and the second section of Gaussian waveform to be symmetrical.

4. A method of processing according to claim 3, wherein the first expected fit equation is:the second expected fit equation is: />Wherein a is the peak value of the pulse to be processed, and x is ₁ X represents any time in the first segment of Gaussian waveform ₂ Representing any time in the second Gaussian waveform, b is the time corresponding to the peak value of the pulse to be processed, x ₁ ＜b＜x ₂ ，y ₁ Indicated at the firstSegment gaussian waveform and x ₁ Corresponding amplitude, y ₂ Represented by the sum x in the second segment Gaussian waveform ₂ Corresponding amplitude, c ₁ And c ₂ Are all constant.

5. The processing method according to claim 3, wherein the processing the first segment of gaussian waveform and/or the second segment of gaussian waveform according to the correspondence model comprises:

processing the first section of Gaussian waveform by adopting a first corresponding relation model to enable the first section of Gaussian waveform to be symmetrical to the second section of Gaussian waveform; the first correspondence model is:wherein L is ₁ Representing the time corresponding to a particular amplitude on said first gaussian waveform,/for a particular amplitude >Representing a first target time,/->The absolute value of the difference from b is equal to L ₂ An absolute value of the difference from b, b being the time corresponding to the peak value of the pulse to be processed, c ₁ And c ₂ Are all constant.

6. The processing method according to claim 3, wherein the processing the first segment of gaussian waveform and/or the second segment of gaussian waveform according to the correspondence model comprises:

processing the second section of Gaussian waveform by adopting a second corresponding relation model to enable the second section of Gaussian waveform to be symmetrical to the first section of Gaussian waveform; the second correspondence model is:wherein L is ₂ Representing the corresponding time of a specific amplitude on said second gaussian waveform,/for each of the two different phases>Representing a second target time,/->The absolute value of the difference from b is equal to L ₁ An absolute value of the difference from b, b being the time corresponding to the peak value of the pulse to be processed, c ₁ And c ₂ Are all constant.

7. The processing method according to claim 1, wherein the pulse to be processed is pulse data acquired by a detector and digitized.

8. The processing method according to claim 7, wherein the digitizing method of the pulse to be processed includes a multi-voltage threshold sampling method, a peak hold method, and an ADC sampling method.

9. The method of processing according to claim 1, wherein said fitting the shape of the pulse to be processed with the symmetrically processed gaussian waveform comprises:

and fitting the shape of the pulse to be processed by using a least square method by adopting a Gaussian waveform subjected to symmetrical processing.

10. The method of processing according to claim 1, wherein the gaussian shaping of the pulse to be processed comprises:

and carrying out Gaussian shaping on the pulse to be processed according to a preset Gaussian shaping circuit.

11. A processing method according to claim 1, characterized in that the shape of the pulse to be processed is used to obtain energy information of the pulse to be processed.

12. A processing device for scintillation pulses, the processing device comprising:

the shaping module is used for carrying out Gaussian shaping on the pulse to be processed;

the segmentation module is used for segmenting the pulse to be processed after Gaussian shaping into a first segment of Gaussian waveform and a second segment of Gaussian waveform according to a preset method;

the processing module is used for processing the first section of Gaussian waveform and/or the second section of Gaussian waveform by adopting a preset calculation method so as to enable the first section of Gaussian waveform and the second section of Gaussian waveform to be symmetrical;

And the fitting module is used for fitting the shape of the pulse to be processed by adopting the Gaussian waveform subjected to symmetrical processing.

13. The processing apparatus according to claim 12, wherein the preset method includes dividing the gaussian-shaped pulse to be processed into the first segment of gaussian waveform and the second segment of gaussian waveform with a peak of the pulse to be processed as a boundary.

14. The processing device of claim 12, wherein the processing module processes the first and/or second gaussian waveforms comprises:

acquiring a second expected fitting equation of the second Gaussian waveform;

15. The processing apparatus of claim 14, wherein the first expected fit equation is:the second expected fit equation is: / >Wherein a is the peak value of the pulse to be processed, and x is ₁ X represents any time in the first segment of Gaussian waveform ₂ Representing any time in the second Gaussian waveform, b is the time corresponding to the peak value of the pulse to be processed, x ₁ ＜b＜x ₂ ，y ₁ Represented by the sum x in the first segment Gaussian waveform ₁ Corresponding amplitude, y ₂ Represented by the sum x in the second segment Gaussian waveform ₂ Corresponding amplitude, c ₁ And c ₂ Are all constant.

16. The processing device of claim 14, wherein the processing module processes the first and/or second gaussian waveforms according to the correspondence model further comprises:

processing the first section of Gaussian waveform by adopting a first corresponding relation model to enable the first section of Gaussian waveform to be symmetrical to the second section of Gaussian waveform; the first correspondence model is:wherein L is ₁ Representing the time corresponding to a particular amplitude on said first gaussian waveform,/for a particular amplitude>Representing a first target time,/->The absolute value of the difference from b is equal to L ₂ An absolute value of the difference from b, b being the time corresponding to the peak value of the pulse to be processed, c ₁ And c ₂ Are all constant.

17. The processing device of claim 14, wherein the processing module processes the first and/or second gaussian waveforms according to the correspondence model further comprises:

Processing the first data by using a second correspondence modelThe two-section Gaussian waveform is symmetrical to the first-section Gaussian waveform; the second correspondence model is:wherein L is ₂ Representing the corresponding time of a specific amplitude on said second gaussian waveform,/for each of the two different phases>Representing a second target time,/->The absolute value of the difference from b is equal to L ₁ An absolute value of the difference from b, b being the time corresponding to the peak value of the pulse to be processed, c ₁ And c ₂ Are all constant.

18. The processing device of claim 12, wherein the pulses to be processed are pulse data acquired by a detector and digitized.

19. The processing apparatus of claim 18, wherein the detector comprises a semiconductor detector or a scintillation detector.

20. The processing apparatus of claim 12, wherein the fitting module fits the shape of the pulse to be processed using a symmetrically processed gaussian waveform comprises:

21. The processing apparatus of claim 12, wherein the shaping module performs gaussian shaping on the pulses to be processed, comprising:

22. The processing device of claim 12, further comprising an energy acquisition module that integrates according to the shape of the pulse to be processed to acquire energy information of the pulse to be processed.

23. An electronic device, the electronic device comprising:

one or more processors;

a storage means for storing one or more programs;

when the one or more programs are executed by the one or more processors, the one or more processors are caused to implement the method for processing scintillation pulses of any one of claims 1-11.

24. An electronic device, the electronic device comprising: the scintillation pulse processing apparatus according to any one of claims 12 to 22.

25. A storage medium having stored thereon computer program instructions which, when executed by a processor, cause the processor to implement the method of processing scintillation pulses of any one of claims 1-11.