CN112710648B - Method, system and computer storage medium for identifying object to be detected by using Raman spectrum - Google Patents
Method, system and computer storage medium for identifying object to be detected by using Raman spectrum Download PDFInfo
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Abstract
The invention relates to a method and a system for identifying an object to be detected by using Raman spectrum and a computer storage medium. The method for identifying the object to be detected by using the Raman spectrum provided by the invention calculates the detection times according to the relation between the detection times and the signal-to-noise ratio, and then performs superposition detection on the Raman spectrum of the object to be detected according to the detection times so as to identify the object to be detected. By means of the method, the pulse superposition detection process can be controlled, a solution is provided for solving the problem that the pulse superposition detection time is uncontrollable under the condition of poor signal-to-noise ratio, and the object to be detected is more stably and reliably identified by using the Raman spectrum.
Description
Technical Field
The invention relates to the field of Raman spectrum detection, in particular to a method and a system for identifying an object to be detected by utilizing Raman spectrum and a computer storage medium.
Background
The Raman spectroscopy is a scattering spectrum, and the Raman spectroscopy analysis method is an analysis method for analyzing a scattering spectrum with a frequency different from that of incident light based on a Raman scattering effect found by indian scientists c.v. Raman (Raman) to obtain information on molecular vibration and rotation, and applying the information to molecular structure research.
The existing CCD detection Raman spectrometer usually adopts multi-channel detection, for example, pulse superposed signal detection is carried out on collected spectrum signals, but the traditional signal-to-noise ratio evaluation method cannot obtain detector fluctuation spectrogram noise through single detection, then the detector responds to random fluctuation to calculate the times of superposition, and only after the signals are actually superposed, whether the conditions are met or not is judged according to the superposed signal-to-noise ratio to finish the detection, so that the detection without time limitation on unknown substances possibly occurs under the condition of poor signal-to-noise ratio, and the detection efficiency is greatly reduced. Therefore, a method for identifying an object to be detected by using a raman spectrum, which can control pulse superposition detection, is needed, so that detection and identification of the object to be detected without time limitation under the condition of poor signal-to-noise ratio are effectively avoided, and detection and identification of unknown substances are more stable and reliable.
Disclosure of Invention
The method aims to solve the technical problems of the existing method for identifying the object to be detected by using the Raman spectrum. The invention provides a method and a system for identifying an object to be detected by using Raman spectrum and a computer storage medium.
One of the technical solutions of the present invention for solving the above technical problems is as follows:
a method for identifying an analyte using raman spectroscopy, comprising:
performing primary superposition detection on the Raman spectrum of the object to be detected to obtain a primary detection signal;
according to the formula n = (p/r) 2 Calculating the detection times n, wherein p is a preset value, and r is the signal-to-noise ratio of the primary detection signal;
based on the primary detection signal, carrying out superposition detection on the Raman spectrum of the object to be detected for n-1 times to obtain an nth detection signal;
and identifying the object to be detected according to the nth detection signal.
The invention has the beneficial effects that: the detection times n obtained through calculation are used for controlling the superposition detection process, so that the problem that whether the superposition signal-to-noise ratio meets the preset condition or not to control the superposition detection process when the Raman spectrum is used for identifying the object to be detected is solved, the superposition detection time cannot be controlled under the condition of poor signal-to-noise ratio, the identification efficiency of the object to be detected is effectively improved, and the identification of the Raman spectrum on the object to be detected is more stable and reliable.
On the basis of the technical scheme, the invention can be further improved as follows.
Further, the process of the primary superposition detection or the n-1 times of superposition detection comprises:
continuously carrying out pulse detection on the object to be detected for multiple times to obtain multiple pulse Raman spectrum signals;
performing superposition processing on the plurality of pulse Raman spectrum signals to obtain superposed signals;
and filtering a fluorescence background signal from the superposed signal to obtain a detection signal.
The beneficial effect who adopts above-mentioned improvement scheme is: the signal intensity is enhanced by superposing a plurality of pulse Raman spectrum signals, and the interference caused by the fluorescence background signal is removed from the superposed signals, so that a detection signal capable of correctly reflecting the self attribute of the object to be detected is obtained, and the accuracy of the object to be detected identification is improved.
Further, the filtering out the fluorescence background signal from the superimposed signal to obtain a detection signal includes:
acquiring a resolution value of a detection spectrometer, and taking the integral resolution value as a value of iteration times m;
acquiring a plurality of data points of the superimposed signal to form a data point sequence { y } k }；
According to the formula
Obtaining the data point sequence { y } k Data point sequence after one iteration calculation (y) k+1 In which y k (i) Is the data point sequence y k The ith data point in (i) }, y k+1 (i) Is the data point sequence y k+1 The ith data point in the (m) is the iteration time;
each time iteration is carried out, subtracting 1 from the value of the iteration number m, and repeatedly carrying out the iteration process until the iteration number m =1 to obtain a first data point sequence;
and taking the first data point sequence as a fluorescence background signal, and filtering the fluorescence background signal from the superposed signal to obtain a detection signal.
The beneficial effect who adopts above-mentioned improvement scheme is: the half-peak width of the detection spectrometer is used as the iteration number to measure the fluorescent background signal distance, so that the inflection point of the fluorescent background signal is found, and the method is small in calculation amount, simple and practical.
Further, when the raman spectrum of the object to be detected continues to be subjected to superposition detection for n-1 times, the step of carrying out superposition processing on the plurality of pulse raman spectrum signals to obtain a superposition signal comprises the following steps:
taking a detection signal obtained in the previous superposition detection as a signal to be superposed;
and superposing the plurality of pulse Raman spectrum signals and the signal to be superposed to obtain the superposed signal.
The beneficial effect who adopts above-mentioned improvement scheme is: by carrying out superposition detection on the object to be detected according to the detection times n, the accuracy of the Raman spectrum obtained by accumulative summation is ensured while the superposition detection time is reasonably controlled, so that the effectiveness of the identification of the object to be detected is improved.
Further, before the performing the n-1 times of superposition detection on the raman spectrum of the object to be detected based on the primary detection signal to obtain the nth detection signal, the method further includes:
judging whether the signal-to-noise ratio r of the primary detection signal is greater than a preset value;
if the Raman spectrum of the object to be detected is larger than the preset value, based on the primary detection signal, carrying out n-1 times of superposition detection on the Raman spectrum of the object to be detected to obtain an nth detection signal;
and if the signal intensity is not greater than the preset value, improving the laser power and/or the integration time of the detection spectrometer, and performing primary superposition detection on the Raman spectrum of the object to be detected again to obtain a new primary detection signal.
The beneficial effect who adopts above-mentioned improvement scheme is: the effectiveness of the identification of the analyte is improved by increasing the laser power and/or integration time of the detection spectrometer to increase the signal intensity.
The second technical solution of the present invention for solving the above technical problems is as follows:
the invention also provides a system for identifying the object to be detected by using the Raman spectrum, which comprises a detection module, a calculation module and an identification module;
the detection module is used for carrying out primary superposition detection on the Raman spectrum of the object to be detected to obtain a primary detection signal, and carrying out n-1 times of superposition detection on the Raman spectrum of the object to be detected to obtain an nth detection signal based on the primary detection signal;
the calculation module is used for calculating the equation n = (p/r) 2 Calculating the detection times n, wherein p is a preset value, and r is the signal-to-noise ratio of the primary detection signal;
and the identification module is used for identifying the object to be detected according to the nth detection signal.
The invention has the beneficial effects that: the superposition detection process is controlled through the detection times n obtained through calculation, the problem that when the Raman spectrum is used for identifying the object to be detected, whether the superposition signal-to-noise ratio meets the preset condition or not is judged to control the superposition detection process, so that the superposition detection time is uncontrollable under the condition of poor signal-to-noise ratio is solved, the identification efficiency of the object to be detected is effectively improved, and the object to be detected is identified more stably and reliably by utilizing the Raman spectrum.
On the basis of the technical scheme, the invention can be further improved as follows.
Further, the detection module comprises a first detection module, a superposition module and a processing module;
the first detection module is used for continuously carrying out pulse detection on the object to be detected for multiple times to obtain multiple pulse Raman spectrum signals;
the superposition module is used for carrying out superposition processing on the plurality of pulse Raman spectrum signals to obtain superposed signals;
and the processing module is used for filtering a fluorescence background signal from the superposed signal to obtain a detection signal.
The beneficial effect who adopts above-mentioned improvement scheme is: the signal intensity is enhanced by superposing a plurality of pulse Raman spectrum signals, and the interference caused by the fluorescence background signal is removed from the superposed signals, so that a detection signal capable of correctly reflecting the self attribute of the object to be detected is obtained, and the accuracy of the identification of the object to be detected is improved.
Further, the processing module is specifically configured to acquire a resolution value of the spectrometer, obtain the integral resolution value as a value of an iteration number m, acquire a plurality of data points of the superimposed signal, and form a data point sequence { y } k According to the formula
Obtaining the data point sequence { y k Data point sequence after one iteration calculation (y) k+1 In which y k (i) Is the data point sequence y k The ith data point in (i) }, y k+1 (i) Is the data point sequence y k+1 In (1)And the ith data point m is the iteration number, wherein each time iteration is performed, 1 is subtracted from the value of the iteration number m, the iteration process is repeatedly performed until the iteration number m =1 to obtain a first data point sequence, the first data point sequence is used as a fluorescence background signal, and the fluorescence background signal is filtered from the superposition signal to obtain a detection signal.
The beneficial effect who adopts above-mentioned improvement scheme is: the half-peak width of the detection spectrometer is used as the iteration number to measure the fluorescent background signal distance, so that the inflection point of the fluorescent background signal is found, and the method is small in calculation amount, simple and practical.
Further, the superposition module is specifically configured to, when the raman spectrum of the object to be detected continues to be subjected to superposition detection for n-1 times, use a detection signal obtained in the previous superposition detection as a signal to be superposed, and superpose the plurality of pulse raman spectrum signals and the signal to be superposed to obtain the superposed signal.
The beneficial effect who adopts above-mentioned improvement scheme is: by carrying out superposition detection on the object to be detected according to the detection times n, the accuracy of the Raman spectrum obtained by accumulative summation is ensured while the superposition detection time is reasonably controlled, so that the effectiveness of the identification of the object to be detected is improved.
The third technical scheme for solving the technical problems is as follows:
the present invention also provides a computer-readable storage medium storing a computer program which, when executed by a processor, implements the steps of the method for identifying an object to be measured using raman spectroscopy as described above.
The invention has the beneficial effects that: the detection times n obtained through calculation are used for controlling the superposition detection process, so that the problem that whether the superposition signal-to-noise ratio meets the preset condition or not to control the superposition detection process when the Raman spectrum is used for identifying the object to be detected is solved, the superposition detection time cannot be controlled under the condition of poor signal-to-noise ratio, the identification efficiency of the object to be detected is effectively improved, and the identification of the Raman spectrum on the object to be detected is more stable and reliable.
Additional aspects of the invention and its advantages will be set forth in part in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention.
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In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only some embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to the structures shown in the drawings without creative efforts.
Fig. 1 is a schematic flow chart illustrating a method for identifying an object to be detected by using raman spectroscopy according to an embodiment of the present invention;
fig. 2 is a schematic flow chart of the raman spectrum superposition detection for an object to be detected according to the embodiment of the present invention;
fig. 3 is a schematic structural diagram of a system for identifying an object to be measured by using raman spectroscopy according to an embodiment of the present invention;
fig. 4 is a schematic structural diagram of a detection module according to an embodiment of the present invention.
Detailed Description
In the following description, for purposes of explanation and not limitation, specific details are set forth such as the particular system architecture, interfaces, techniques, etc., in order to provide a thorough understanding of the present invention. It will be apparent, however, to one skilled in the art that the present invention may be practiced in other embodiments that depart from these specific details. In other instances, detailed descriptions of well-known systems, circuits, and methods are omitted so as not to obscure the description of the present invention with unnecessary detail.
These and other aspects of embodiments of the invention will be apparent with reference to the following description and attached drawings. In the description and drawings, particular embodiments of the invention have been disclosed in detail as being indicative of some of the ways in which the principles of the embodiments of the invention may be practiced, but it is understood that the scope of the embodiments of the invention is not limited correspondingly. On the contrary, the embodiments of the invention include all changes, modifications and equivalents coming within the spirit and terms of the claims appended hereto.
Referring to fig. 1, the present invention provides a method for identifying an object to be measured by using raman spectroscopy, including:
s1, performing primary superposition detection on a Raman spectrum of an object to be detected;
s2, calculating the detection times according to the signal-to-noise ratio of the obtained primary detection signal;
s3, performing multiple overlapping detection on the Raman spectrum of the object to be detected according to the detection times;
and S4, identifying the object to be detected.
Optionally, before the step S2, the method further includes:
calculating a signal-to-noise ratio r according to a signal obtained after primary superposition detection, judging whether the signal-to-noise ratio r of the primary detection signal is greater than a preset value, and if so, entering a step S2;
if the signal-to-noise ratio is not greater than the preset value, the signal-to-noise ratio r is too low, the laser power and/or the integration time of the detection spectrometer need to be increased to enhance the signal intensity, and the primary superposition detection is carried out on the Raman spectrum of the object to be detected again.
Specifically, in this embodiment, as shown in fig. 2, the process of performing the primary overlay detection on the raman spectrum of the object to be measured or performing the multiple overlay detection on the raman spectrum of the object to be measured includes:
s11, continuously carrying out pulse detection on the object to be detected for multiple times;
s12, overlapping the obtained plurality of pulse Raman spectrum signals;
step S13, filtering a fluorescence background signal from the obtained superposition signal;
step S14, obtaining a detection signal.
It should be noted that, in the prior art, the signal intensity of the raman spectrum is generally increased by prolonging the exposure time, but in an actual raman spectrum detection apparatus, in order to avoid an adverse effect on the apparatus caused by an excessive optical power or an excessively long time, the raman spectrum signal acquired at a single time is often limited, and in the embodiment of the present application, the raman spectrum of the object to be detected is continuously measured, and a plurality of acquired pulse raman spectrum signals are superimposed to enhance the signal intensity, so as to ensure the validity of the detection times calculated from the raman spectrum signal obtained by the superimposed detection. Wherein said "plurality" may for example be 2, 3, 5, 10, 50, etc.
In the method for identifying the object to be detected by using the raman spectrum according to the embodiment, the detection frequency is calculated by the detection signal obtained by single detection, so that the superposition detection process is controlled according to the detection frequency, a solution is provided for solving the problem that the pulse superposition detection time is uncontrollable under the condition of poor signal-to-noise ratio, and the object to be detected is identified more stably and reliably by using the raman spectrum.
Further, in one embodiment, the method comprises the steps of:
step (1): continuously carrying out pulse detection on the object to be detected for multiple times to obtain a pulse Raman spectrum signal;
step (2): superimposing the plurality of pulsed raman spectral signals to form a superimposed signal;
and (3): the fluorescence background signal is filtered from the superimposed signal.
In a specific embodiment of the present invention, the fluorescence background signal is calculated by:
step (3.1) obtaining a plurality of CCD data points of the pulse superposition signal;
step (3.2) calculating a fluorescence background signal by a minimum method based on a plurality of CCD data points of the pulse superposition signal;
step (3.3) subtracts the fluorescent background signal from the pulse-superimposed signal.
The minimum value connecting method measures the distance of the fluorescence background signal by using the half-peak width of the Raman spectrometer detected by the CCD as the iteration number, thereby finding the inflection point of the fluorescence background signal.
In order to calculate the fluorescence background signal, the superimposed signal needs to have a discrete numerical form, and if the superimposed signal is a continuous analog curve, it needs to be converted into a discrete numerical form by sampling. In practice, however, the superimposed signal is often already in the form of discrete values, in which case a plurality of CCD data points may be acquired directly.
Specifically, in the specific embodiment of the present invention, the fluorescence background signal in the step (3.2) is calculated as follows:
assuming that the resolution of the detection spectrometer is m, for all CCD data point sequences y { n }, wherein n is the number of CCD pixels, firstly obtaining sequences z { n } of all minimum values, wherein m is the number of iterations, rounding m and starting iteration from high to low, wherein the value taking method of z { n } is as follows: z { i } = min { y { i }, (y { i-m } + y { i + m })/2 }, obtaining a new sequence y { i } = z { i }, repeating the iteration until m =1, and finally obtaining a fluorescence background signal z { n }.
And (4): and obtaining a Raman characteristic signal for next superposition.
And (5): deducing the detection times n = (p/r) according to the signal-to-noise ratio rule 2 。
It should be noted that in the above formula, "min {. Cndot.,. Cndot. }" represents the minimum operation, and it is obvious that the sequence number of the data point participating in each iteration should satisfy that i-m is greater than zero and i + m does not exceed the total length n of the data point sequence y { n }. The numerical points which do not satisfy the condition can keep the original value unchanged in the iterative operation process.
In the specific embodiment of the invention, for the noise characteristics of the raman spectrometer detected by the CCD, it is assumed that the return signal of the raman spectrometer includes three parts:
1. a sample spectral signal S;
2. dark current instrument noise N1;
3. optical noise N2 generated by the optical system.
The signal-to-noise ratio of the CCD detection Raman spectrometer is defined as: r = S max /N1 std I.e. S of the maximum value of the signal max Standard deviation from instrument noise N1 std The ratio of (a) to (b).
The integration time cannot be too large for weak raman signals limited by detector saturation. The synchronous superposition averaging algorithm becomes one of means for continuously improving the signal-to-noise ratio of the Raman spectrum. The principle of the superposition-averaging algorithm is based on the fact that random noise accumulations are added according to a statistical average, while useful signals are added according to an arithmetic addition. According to the principle, the signal-to-noise ratio can be improved after n-time spectrum superposition
And (4) multiplying. The number of detections can be calculated based on this principle.
Assuming that the signal-to-noise ratio is r and the detection times n satisfy the functional relationship of f (n) = r, the first detection is f (1) = r 1 Obtaining the Nth detection signal-to-noise ratio according to the above principle to satisfy the condition
The process of (2) is as follows:
assuming that the nth detection satisfies the condition that the signal-to-noise ratio threshold is p, there is
The nth detection can be deduced to satisfy the condition n ≦ (p/r) 1 ) 2 So that n = (p/r) can be deduced 1 ) 2 。
Repeating the steps (1) to (4) in each superposition scheme, and obtaining the accumulated summation Raman spectrum after the fluorescence background signal is filtered out through pulse superposition n times of detection. By using the method, the Raman characteristic spectrum capable of accurately controlling the detection times of the pulse can be obtained, so that the object to be detected can be effectively identified.
It should be understood that, in the above embodiments of the present invention, the sequence numbers of the above processes do not mean the execution sequence, and the execution sequence of the processes should be determined by their functions and inherent logic, and should not constitute any limitation on the implementation process of the embodiments of the present invention.
Referring to fig. 3, the present invention further provides a system 10 for identifying an object to be detected by using raman spectroscopy, including a detection module 20, a calculation module 30, and an identification module 40;
the detection module 20 is configured to perform primary superposition detection on the raman spectrum of the object to be detected to obtain a primary detection signal, and based on the primary detection signal, perform n-1 times of superposition detection on the raman spectrum of the object to be detected to obtain an nth detection signal;
the calculating module 30 is configured to calculate the equation n = (p/r) 2 Calculating the detection times n, wherein p is a preset value, and r is the signal-to-noise ratio of the primary detection signal;
and the identification module 40 is configured to identify the object to be detected according to the nth detection signal.
The system 10 for identifying the object to be detected by using the raman spectrum provided by the above embodiment calculates the detection times through the detection signal obtained by single detection, thereby controlling the superposition detection process according to the detection times, providing a solution for solving the problem of uncontrollable pulse superposition detection time under the condition of poor signal-to-noise ratio, and enabling the object to be detected to be identified by using the raman spectrum to be more stable and reliable.
Optionally, in an embodiment, referring to fig. 4, the detection module 20 includes a first detection module 201, a superposition module 202, and a processing module 203;
the first detection module 201 is configured to perform multiple pulse detections on an object to be detected continuously to obtain multiple pulse raman spectrum signals;
the superposition module 202 is configured to perform superposition processing on the plurality of pulse raman spectrum signals to obtain a superposed signal;
the processing module 203 is configured to filter a fluorescence background signal from the superimposed signal to obtain a detection signal.
According to the system for identifying the object to be detected by using the Raman spectrum, the signal intensity is enhanced by superposing the plurality of pulse Raman spectrum signals, and the detection signal capable of correctly reflecting the self attribute of the object to be detected is obtained by removing the interference caused by the fluorescence background signal from the superposed signal, so that the accuracy of identifying the object to be detected is improved.
Optionally, in an embodiment, the processing module 203 is specifically configured to useObtaining a resolution value of a detection spectrometer, taking the integral resolution value as a value of iteration times m, obtaining a plurality of data points of the superposed signal, and forming a data point sequence { y } k H according to formula y k+1 (i)＝min{y k+1 (i)，(y k (i-m)+y k (i + m))/2 } to obtain the data point sequence { y } k Data point sequence after one iteration calculation (y) k+1 In which y k (i) For the data point sequence y k The ith data point in (c) }, y k+1 (i) Is the data point sequence y k+1 And (4) the ith data point in the sequence, wherein m is the iteration frequency, and 1 is subtracted from the value of the iteration frequency m when each iteration is performed, the iteration process is repeatedly performed until the iteration frequency m =1 to obtain a first data point sequence, the first data point sequence is used as a fluorescence background signal, and the fluorescence background signal is filtered from the superposition signal to obtain a detection signal.
The system 10 for identifying the object to be detected by using the raman spectrum provided by the above embodiment measures the fluorescent background signal distance by using the half-peak width of the detection spectrometer as the iteration number, thereby finding the inflection point of the fluorescent background signal, and having small calculation amount, simplicity and practicability.
Optionally, in an embodiment, the superposition module 202 is specifically configured to, when the raman spectrum of the object to be detected continues to be subjected to n-1 times of superposition detection, use a detection signal obtained in the previous superposition detection as a signal to be superposed, and superpose the plurality of pulse raman spectrum signals and the signal to be superposed to obtain the superposed signal.
According to the system 10 for identifying the object to be detected by using the raman spectrum provided by the embodiment, the object to be detected is subjected to superposition detection according to the detection times n, the superposition detection time is reasonably controlled, and meanwhile, the accuracy of the raman spectrum obtained by accumulative summation is ensured, so that the effectiveness of identifying the object to be detected is improved.
Optionally, in an embodiment, the system 10 for identifying an object to be measured by using raman spectroscopy further includes a control module;
the control module is used for judging whether the signal-to-noise ratio r of the primary detection signal is greater than a preset value;
if the Raman spectrum of the object to be detected is larger than the preset value, calling the detection module 20 to continuously perform n-1 times of superposition detection on the Raman spectrum of the object to be detected based on the primary detection signal to obtain an nth detection signal;
and if the signal is not greater than the preset value, the laser power and/or the integration time of the detection spectrometer are/is increased, and the detection module 20 is called to perform primary superposition detection on the Raman spectrum of the object to be detected again to obtain a new primary detection signal.
The system for identifying the object to be detected by using the raman spectrum provided by the above embodiment ensures that the intensity of the detection signal can reflect the property of the object to be detected by the preset value set according to the actual condition, and for the detection signal with the intensity not meeting the condition, enhances the signal intensity by improving the laser power and/or the integration time of the detection spectrometer, thereby improving the effectiveness of identifying the object to be detected.
The present invention further provides a computer readable storage medium, which stores a computer program, and when the computer program is executed by a processor, the computer program implements the steps of the method for identifying an object to be measured by using raman spectroscopy as described above.
In particular, in a particular embodiment of the invention, the computer readable storage medium, when executed by the processor, performs the steps of: performing primary superposition detection on the Raman spectrum of the object to be detected to obtain a primary detection signal; according to the formula n = (p/r) 2 Calculating the detection times n, wherein p is a preset value, and r is the signal-to-noise ratio of the primary detection signal; based on the primary detection signal, carrying out superposition detection on the Raman spectrum of the object to be detected for n-1 times to obtain an nth detection signal; and identifying the object to be detected according to the nth detection signal.
Optionally, the computer readable storage medium when executed by the processor implements the steps of: continuously carrying out pulse detection on the object to be detected for multiple times to obtain multiple pulse Raman spectrum signals; superposing the plurality of pulse Raman spectrum signals to obtain superposed signals; and filtering a fluorescence background signal from the superposed signal to obtain a detection signal.
Optionally, the computer readable storage medium when executed by the processor implements the steps of: acquiring a resolution value of a detection spectrometer, and taking the integral resolution value as a value of iteration times m; acquiring a plurality of data points of the superposed signal to form a data point sequence { y } k }; according to the formula
Obtaining the data point sequence { y } k Data point sequence after one iteration calculation (y) k+1 In which y k (i) For the data point sequence y k The ith data point in (c) }, y k+1 (i) Is the data point sequence y k+1 The ith data point in (j), m is the number of iterations; each time iteration is carried out, subtracting 1 from the value of the iteration number m, and repeatedly carrying out the iteration process until the iteration number m =1 to obtain a first data point sequence; and taking the first data point sequence as a fluorescence background signal, and filtering the fluorescence background signal from the superimposed signal to obtain a detection signal.
Optionally, when the raman spectrum of the object to be detected continues to be subjected to n-1 times of superposition detection, the computer-readable storage medium, when executed by the processor, implements the following steps:
taking a detection signal obtained in the previous superposition detection as a signal to be superposed;
and superposing the plurality of pulse Raman spectrum signals and the signal to be superposed to obtain the superposed signal.
Optionally, before the raman spectrum of the object to be detected continues to be subjected to n-1 times of superposition detection based on the primary detection signal to obtain an nth detection signal, the computer-readable storage medium implements the following steps when being executed by the processor: judging whether the signal-to-noise ratio r of the primary detection signal is greater than a preset value or not;
if the Raman spectrum of the object to be detected is larger than the preset value, based on the primary detection signal, carrying out n-1 times of superposition detection on the Raman spectrum of the object to be detected to obtain an nth detection signal;
and if the signal intensity is not greater than the preset value, improving the laser power and/or the integration time of the detection spectrometer, and performing primary superposition detection on the Raman spectrum of the object to be detected again to obtain a new primary detection signal.
That is, in the embodiment of the present invention, when the computer program is executed by the processor, the steps of the method for identifying an object to be detected by using a raman spectrum are implemented, and the superimposed detection process is controlled by the detection number n obtained through calculation, so that the problem that when the object to be detected is identified by using the raman spectrum, the superimposed detection time is uncontrollable under the condition of poor signal-to-noise ratio due to the fact that the superimposed detection process is controlled by judging whether the superimposed signal-to-noise ratio meets the preset condition is solved, the identification efficiency of the object to be detected is effectively improved, and the object to be detected is identified more stably and reliably by using the raman spectrum.
Since the computer program is executed by the processor to implement the steps of the method for identifying an object to be tested by using raman spectroscopy, all embodiments of the method for identifying an object to be tested by using raman spectroscopy are applicable to the computer-readable storage medium, and can achieve the same or similar beneficial effects.
The above embodiments of identifying an analyte by using a raman spectrum can be used for identifying and analyzing organic and inorganic substances, and the raman spectrum signals obtained by the above multiple superposition detection can obtain the vibration and rotation energy level of the substance, thereby identifying the substance and the property of the analyte.
Through the above description of the embodiments, those skilled in the art will clearly understand that the method of the above embodiments can be implemented by software plus a necessary general hardware platform, and certainly can also be implemented by hardware, but in many cases, the former is a better implementation manner. Based on such understanding, the technical solutions of the present invention or portions thereof contributing to the prior art may be embodied in the form of a software product, which is stored in a storage medium (such as ROM/RAM, magnetic disk, optical disk) and includes several instructions for enabling a terminal (which may be a computer, a server, or a network device) to execute the methods according to the embodiments of the present invention.
The above description is only a preferred embodiment of the present invention, and is not intended to limit the present invention, and the detection frequency calculation method based on the snr rule provided by the present invention can be popularized and used in spectrum overlay detection combining snr, such as overlay detection of infrared, IMS (ion mobility), and mass spectrum, for example.
Therefore, any modification, equivalent replacement, improvement and the like made within the spirit and principle of the present invention should be included in the protection scope of the present invention.
Claims (9)
1. A method for identifying an object to be detected by using Raman spectrum is characterized by comprising the following steps:
performing primary superposition detection on the Raman spectrum of the object to be detected to obtain a primary detection signal;
according to the formula n = (p/r) 2 Calculating the detection times n, wherein p is a preset value, and r is the signal-to-noise ratio of the primary detection signal;
based on the primary detection signal, carrying out superposition detection on the Raman spectrum of the object to be detected for n-1 times to obtain an nth detection signal;
identifying the object to be detected according to the nth detection signal;
wherein, based on the primary detection signal, the method further comprises the following steps of carrying out superposition detection on the Raman spectrum of the object to be detected for n-1 times, and before obtaining the nth detection signal:
judging whether the signal-to-noise ratio r of the primary detection signal is greater than a preset value;
if the Raman spectrum of the object to be detected is larger than the preset value, based on the primary detection signal, carrying out n-1 times of superposition detection on the Raman spectrum of the object to be detected to obtain an nth detection signal;
and if the signal intensity is not greater than the preset value, improving the laser power and/or the integration time of the detection spectrometer, and performing primary superposition detection on the Raman spectrum of the object to be detected again to obtain a new primary detection signal.
2. The method for identifying an analyte by using raman spectroscopy according to claim 1, wherein the process of the primary overlay detection or the n-1 overlay detections comprises:
continuously carrying out pulse detection on the object to be detected for multiple times to obtain multiple pulse Raman spectrum signals;
performing superposition processing on the plurality of pulse Raman spectrum signals to obtain superposed signals;
and filtering a fluorescence background signal from the superposed signal to obtain a detection signal.
3. The method of claim 2, wherein filtering the fluorescence background signal from the superimposed signal to obtain a detection signal comprises:
acquiring a resolution value of a detection spectrometer, and taking the integral resolution value as a value of iteration times m;
acquiring a plurality of data points of the superimposed signal to form a data point sequence { y } k }；
According to the formula
Obtaining the data point sequence { y k Data point sequence after one iteration calculation (y) k+1 In which y k (i) For the data point sequence y k The ith data point in (i) }, y k+1 (i) Is the data point sequence y k+1 The ith data point in the (m) is the iteration time;
each time iteration is carried out, subtracting 1 from the value of the iteration number m, and repeatedly carrying out the iteration process until the iteration number m =1 to obtain a first data point sequence;
and taking the first data point sequence as a fluorescence background signal, and filtering the fluorescence background signal from the superposed signal to obtain a detection signal.
4. The method of claim 2, wherein when the raman spectrum of the test object is subjected to the superposition detection n-1 times, the step of superposing the plurality of pulse raman spectrum signals to obtain a superposed signal comprises:
taking a detection signal obtained in the previous superposition detection as a signal to be superposed;
and superposing the plurality of pulse Raman spectrum signals and the signal to be superposed to obtain the superposed signal.
5. A system for identifying an object to be detected by using Raman spectrum is characterized by comprising a detection module, a calculation module and an identification module;
the detection module is used for carrying out primary superposition detection on the Raman spectrum of the object to be detected to obtain a primary detection signal, and carrying out n-1 times of superposition detection on the Raman spectrum of the object to be detected to obtain an nth detection signal based on the primary detection signal;
the calculation module is used for calculating the equation n = (p/r) 2 Calculating the detection times n, wherein p is a preset value, and r is the signal-to-noise ratio of the primary detection signal;
the identification module is used for identifying the object to be detected according to the nth detection signal;
wherein, based on the primary detection signal, the method further comprises the following steps of continuously performing n-1 times of superposition detection on the Raman spectrum of the object to be detected, and before obtaining the nth detection signal:
judging whether the signal-to-noise ratio r of the primary detection signal is greater than a preset value;
if the Raman spectrum of the object to be detected is larger than the preset value, based on the primary detection signal, carrying out n-1 times of superposition detection on the Raman spectrum of the object to be detected to obtain an nth detection signal;
and if the signal intensity is not greater than the preset value, improving the laser power and/or the integration time of the detection spectrometer, and performing primary superposition detection on the Raman spectrum of the object to be detected again to obtain a new primary detection signal.
6. The system for identifying an object to be measured by using Raman spectroscopy of claim 5, wherein the detection module comprises a first detection module, a superposition module and a processing module;
the first detection module is used for continuously carrying out pulse detection on the object to be detected for multiple times to obtain multiple pulse Raman spectrum signals;
the superposition module is used for carrying out superposition processing on the plurality of pulse Raman spectrum signals to obtain a superposition signal;
and the processing module is used for filtering a fluorescence background signal from the superposed signal to obtain a detection signal.
7. The system of claim 6, wherein the processing module is specifically configured to obtain a resolution value of a detection spectrometer, obtain the integral resolution value as a value of an iteration number m, obtain a plurality of data points of the superposition signal, and form a data point sequence { y } k According to the formula
Obtaining the data point sequence { y k Data point sequence after one iteration calculation (y) k+1 In which y k (i) Is the data point sequence y k The ith data point in (i) }, y k+1 (i) Is the data point sequence y k+1 The ith data point in the sequence, m is the iteration frequency, wherein, every time iteration is carried out, the value of the iteration frequency m subtracts 1, the iteration process is repeatedly carried out until the iteration frequency m =1, and a first data point sequence is obtainedAnd taking the first data point sequence as a fluorescence background signal, and filtering the fluorescence background signal from the superposed signal to obtain a detection signal.
8. The system for identifying an object to be detected by using a raman spectrum according to claim 6, wherein the superposition module is specifically configured to, when the raman spectrum of the object to be detected is subjected to n-1 times of superposition detection, use a detection signal obtained in the previous superposition detection as a signal to be superposed, and superpose the plurality of pulse raman spectrum signals and the signal to be superposed to obtain the superposed signal.
9. A computer-readable storage medium, in which a computer program is stored, which, when being executed by a processor, carries out the steps of the method for identifying an object to be measured using raman spectroscopy according to any one of claims 1 to 4.
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