CN115656144A

CN115656144A - Method and device for measuring seawater salinity in situ based on photoacoustic information fusion and application

Info

Publication number: CN115656144A
Application number: CN202211233694.4A
Authority: CN
Inventors: 田野; 王蓓蓓; 宋文华; 郑荣儿
Original assignee: Ocean University of China
Current assignee: Ocean University of China
Priority date: 2022-10-10
Filing date: 2022-10-10
Publication date: 2023-01-31

Abstract

The invention belongs to the technical field of underwater laser spectrum signal processing, and discloses a method and a device for measuring seawater salinity in situ based on photoacoustic information fusion and application of the method and the device. The method comprises the following steps: collecting underwater LIBS spectrums of seawater samples with different salinity and plasma sound wave signals; processing the collected LIBS spectrum and the plasma sound wave signal; establishing a salinity inversion model under the fusion of the spectrum and the acoustic wave signals, and performing the inversion of the salinity of the seawater; and establishing a seawater element concentration prediction model to predict salinity change information caused by chemical element change in seawater. The salinity inversion process of the invention adopts the correlation function of PCA and SVM algorithms, but no precedent of seawater salinity information inversion by utilizing LIBS spectrum signals and plasma sound wave signals is found at present. The method provided by the invention can realize the in-situ, accurate and pollution-free quick inversion of the salinity of the seawater.

Description

Method and device for measuring seawater salinity in situ based on photoacoustic information fusion and application

Technical Field

The invention belongs to the technical field of underwater laser spectrum signal processing, and particularly relates to a method and a device for measuring seawater salinity in situ based on photoacoustic information fusion and application of the method and the device.

Background

Seawater is an important research object of marine environment, and seawater salinity is an important characterization parameter of seawater state and represents the content of seawater components. The chemical components contained in seawater are very complex, the contents of all elements are greatly different, and the research on the salinity and the distribution of the seawater has great significance for determining the change of marine environment, the change of marine meteorology and marine hydrological movement. At present, the traditional methods commonly adopted in the measurement method of seawater salinity comprise a conductivity method, a refractive index method, a specific gravity method, a microwave remote sensing technology, a Brillouin scattering method, a Raman spectroscopy method and the like. Although the existing seawater salinity measuring methods are various, certain limitations exist more or less.

When high-energy pulse laser with short pulse width is focused in the seawater body, transient plasma can be generated based on the interaction between high-power laser and substances, and the generation of the plasma is accompanied with the generation of optical signals, acoustic signals and cavitation pulsation phenomena. The spectral signals of plasma atoms or ion radiation are analyzed, and element information contained in seawater can be obtained, namely, the Laser-induced breakdown spectroscopy (LIBS) technology has the advantages of no need of complex sample pretreatment, multi-element detection, real-time in-situ detection and the like. Meanwhile, supersonic shock waves are generated by outward expansion of the plasma under high temperature and high pressure, the shock waves are attenuated to normal sound velocity after a period of evolution, and the velocity of the sound signal is directly related to environmental parameters such as salinity, temperature and pressure of seawater. Therefore, by simultaneously measuring the spectrum and the sound wave signals of the plasma in the seawater, the light and sound signals are combined, so that the seawater salinity concentration can be accurately inverted, the content information of the element components can be obtained, the characteristics of the light and sound signals are combined, the measurement process is simplified, the sample volume is reduced, the measurement precision can be improved, a new method is provided for future measurement of the seawater salinity, and the in-situ measurement of parameters such as the seawater salinity is expected to be realized.

The detection method and the limitations in the prior art are as follows:

conductivity method: the conductivity, temperature and depth need to be detected simultaneously, the problem of parameter detection asynchronous error may exist, and the electrode is easily polluted by water quality and electromagnetic interference, and the measurement precision is influenced.

Buoy detection: the salinity measurement of large-area seawater cannot be realized, and the data resolution is low.

The specific gravity method comprises the following steps: the requirement on the stability and the stability of the measuring platform is high, and meanwhile, the platform on the seawater measuring site is required to have extremely high stability on the ocean.

Refractive index method: the fiber core of the optical fiber is exposed outside and directly contacts with the liquid to be detected, precipitates are easily formed on the contact surface to influence the measurement, the operation is complex, the measurement range is small, and real-time detection cannot be carried out.

Microwave remote sensing technology: the penetration ability of microwave radiation in seawater is weak, and the propagation loss in seawater is serious, so that only the salinity of the seawater surface can be detected.

Raman spectroscopy: raman spectroscopy is not only related to salinity but also to seawater temperature, requiring parameter assumptions that make the accuracy measurements relatively low.

Brillouin scattering: parameters such as Brillouin scattering frequency shift quantity are influenced by seawater salinity and temperature, and further the measurement precision is influenced.

Through the above analysis, the problems and defects of the prior art are as follows:

(1) The existing traditional measurement methods have certain effect on seawater salinity inversion, most of the existing seawater detection methods indirectly quantify salinity value by measuring the electrical or optical parameters of seawater, but the concentration change of each component of seawater salinity cannot be accurately detected, so that the obtained data information has low precision.

(2) Although the above methods can perform a certain degree of inversion on salinity, the obtained seawater chemical composition information is limited. The existing method cannot obtain the salinity value of seawater, simultaneously judges the salinity information change caused by the element component change, cannot reduce the detection cost, and does not have precedent for performing salinity inversion by adopting the fusion of the spectral signal and the acoustic signal of the underwater laser induced plasma.

Disclosure of Invention

In order to overcome the problems in the related art, the disclosed embodiment of the invention provides a method, a device and an application for in-situ measurement of seawater salinity based on photoacoustic information fusion. The invention aims to perform seawater salinity in-situ measurement by fusing the spectrum of the underwater laser-induced plasma and the acoustic wave signal, so that the seawater salinity value can be obtained, and the salinity information change caused by the element component change can be judged.

The technical scheme is as follows: a seawater salinity in-situ measurement method based on photoacoustic information fusion comprises the following steps:

s1, collecting underwater LIBS spectrums and plasma sound wave signals of seawater samples with different salinity;

s2, processing the collected LIBS spectrum and the plasma sound wave signal;

s3, establishing a salinity inversion model under the spectrum-sound wave signal fusion, and performing the inversion of the salinity of the seawater; and establishing a seawater element concentration prediction model to predict salinity change information caused by chemical element change in seawater.

In one embodiment, in step S1, acquiring LIBS spectra and plasma acoustic signals of seawater samples with different salinity by using an underwater LIBS spectrum and plasma acoustic experimental apparatus, generating laser pulses by using a laser, adjusting laser pulse energy by using a half-wave plate and a glan prism, reflecting a part of each laser pulse by using a cube beam splitter, and transmitting the part of each laser pulse to a photodiode connected with an oscilloscope; expanding the laser beam of the other part of the laser pulse by using a laser beam expander, and focusing the laser beam into a quartz water tank filled with a seawater sample by using an achromatic double cemented lens for generating plasma;

collecting sound waves generated by the plasma by a hydrophone vertically placed above the plasma and storing the sound waves in an oscilloscope; light generated by the plasma is converged by the lateral lens group and coupled into the spectrometer by the optical fiber and controlled by the digital delay pulse generator; and acquiring underwater LIBS spectra and plasma sound wave signals of seawater samples with different salinity.

In one embodiment, in step S2, the processing of the collected LIBS spectrum and plasma acoustic wave signals comprises the following steps:

(1) Performing spectral line element attribution on the obtained n spectral signals, and performing full-spectrum normalization processing after baseline subtraction; on one hand, PCA analysis is carried out on the normalized spectrum to obtain a spectrum training matrix PC after dimension reduction _sp ；

(2) For the n collected sound wave signals, obtaining a sound wave training matrix Fea according to the intensity information and the position information of the sound signals _ac ；

(3) Training a matrix PC for the obtained spectrum _sp And acoustic training matrix Fea _ac And combining to obtain a new training characteristic matrix Vec.

In one embodiment, in step (1), the spectrum training matrix PC _sp Is n multiplied by m, which represents the matrix size of n rows and m columns of the matrix, wherein m is the number of principal components, and the optimal number m of the principal components is determined according to the percentage of the variance of the principal component interpretation original data; on the other hand, the normalized spectrum respectively carries out feature extraction in the spectral line range of Na, K and Ca elements to obtain feature matrixes of the Na, K and Ca elements respectively as V _Na 、V _K 、V _Ca The matrix is n × p, which represents the matrix size of n rows and p columns of the matrix, and p is determined by the spectrum length of the range in which the elements Na, K and Ca are located.

In one embodiment, in step (2), the acoustic training matrix Fea _ac Is n × s, the matrix size of n rows and s columns of the matrix, and s is the characteristic number of the acoustic signal.

In one embodiment, in step (3), the training feature matrix Vec is n × (m + s), which represents the matrix size of n rows and m + s columns of the matrix, m is the number of principal components, and s is the number of acoustic signal features.

In one embodiment, in step S3, the establishing of the salinity inversion model under the spectrum-acoustic signal fusion comprises the following steps:

performing SVM regression by using the obtained training characteristic matrix Vec as an independent variable of a sample and using the salinity of seawater as a dependent variable to obtain an inversion model of salinity; and for a measurement sample with unknown salinity, acquiring a spectrum signal and a sound wave signal, repeating the step S2 to obtain Vec 'of the prediction sample, and substituting the Vec' into the established SVM salinity inversion model to obtain the salinity value of the measurement sample.

In one embodiment, in step S3, the building of the seawater element concentration prediction model includes the following steps:

the feature matrix V of the obtained elements _Na 、V _K 、V _Ca Respectively serving as independent variables of the samples, and respectively serving as dependent variables of the element concentration to perform SVM regression to respectively establish prediction models of Na, K and Ca element concentrations; for a measurement sample with unknown salinity, acquiring spectral signals to obtain a Na, K and Ca element characteristic matrix V _Na ’、V _K ’、V _Ca ' the matrix is n multiplied by p, the matrix represents the size of the matrix of n rows and p columns of the matrix, and p is the number of spectral bands in the range of Na, K and Ca elements, and the Na, K and Ca elements are respectively substituted into the established SVM prediction models of Na, K and Ca to obtain the concentrations of the Na, K and Ca elements of the measured samples.

The invention also aims to provide an experimental device for acquiring underwater LIBS spectrum and plasma sound wave based on the photoacoustic information fusion seawater salinity in-situ measurement method.

The invention also aims to provide an application of the method for measuring seawater salinity in situ based on photoacoustic information fusion in the in-situ measurement of seawater salinity parameters of different sea areas.

By combining all the technical schemes, the invention has the advantages and positive effects that:

first, aiming at the technical problems existing in the prior art and the difficulty in solving the problems, the technical problems to be solved by the technical scheme of the present invention are closely combined with results, data and the like in the research and development process, and how to solve the technical scheme of the present invention is deeply analyzed in detail, so that some creative technical effects are brought after the problems are solved. The specific description is as follows:

aiming at the defects existing in the prior art, the invention provides a novel technical method for measuring seawater salinity information. A beam of pulse laser is focused in a seawater body to generate plasma, the physical process can simultaneously generate an LIBS spectrum signal and a plasma sound wave signal, the spectrum signal can be collected by a spectrometer, and the sound wave signal can be collected by a hydrophone. Feature information extraction is carried out on the spectral signals by using a Principal Component Analysis (PCA) algorithm, position and intensity feature information is extracted from the acoustic signals, feature layer data of the two signals are fused, then an inversion model of seawater salinity is established by using a Support Vector Machine (SVM) algorithm, and meanwhile, the change of the chemical Component content of salinity is obtained by using an LIBS spectrum, so that real-time in-situ, simple and pollution-free rapid inversion of seawater salinity is realized. The LIBS spectrum and the sound wave of the plasma are two phenomena in the same physical process, the signal collection process is simple, rapid and easy to operate, the two signals cannot interfere with each other, and the data processing process is easy to operate. If the salinity inversion is carried out only by utilizing the LIBS spectrum, the obtained concentration value of the salinity has a larger error, and the precision of the salinity value prediction is not high; if the salinity is predicted only by using the plasma acoustic wave signals, the specific change trend of Na, K and Ca elements causing salinity change cannot be obtained; therefore, compared with a method only using LIBS signals or plasma acoustic wave signals, the established inversion model can obtain a more accurate measured seawater salinity value and can also measure the content changes of Na, K and Ca elements in seawater.

Secondly, regarding the technical solution as a whole or from the perspective of products, the technical effects and advantages of the technical solution to be protected by the present invention are specifically described as follows:

the salinity inversion method provided by the invention utilizes the characteristic that a spectrum signal and an acoustic wave signal can be simultaneously generated in the process of generating plasma by underwater laser induction, adopts the synchronous acquisition of the spectrum signal and the acoustic wave signal by a spectrometer and a hydrophone respectively, fuses the spectrum signal and the acoustic wave signal, and is used for establishing an inversion model of seawater salinity in a machine learning algorithm, combines the advantages of the acoustic wave signal and the spectrum signal generated by the underwater laser induction plasma, not only can obtain the seawater salinity concentration information, but also can detect the content change of element components, and realizes the effective prediction of the seawater salinity information.

Although the spectrum correction process adopts a correlation function of PCA and SVM algorithms, no precedent that seawater salinity information inversion is carried out by combining LIBS spectrum signals and plasma sound wave signals is found at present. The salinity inversion method using photoacoustic information fusion provided by the invention is also different from other salinity inversion methods. Therefore, the method is still different from the existing salinity inversion method, and has novelty.

Compared with the prior art, the invention has the advantages that:

(1) The method provided by the invention can not only measure the salinity information of the seawater surface, but also can not damage the product, and can realize the direct measurement of the salinity information of the seawater, rather than indirectly quantifying the salinity value by utilizing electrical or optical parameters. The method provided by the invention only needs to collect LIBS spectrum signals and acoustic signals generated by the underwater laser-induced plasma, utilizes two types of signals generated in the same physical process, not only considers a single parameter in the signals, but also has the advantages that compared with a mode of only using the information contained in the spectrum signals or the acoustic signals, the proposed LIBS spectrum and plasma acoustic fusion mode is more comprehensive and more specific, the error of inversion effect caused by information deviation due to the fact that only a single variable is considered cannot be generated, and the collection of the LIBS spectrum signals and the plasma acoustic signals cannot interfere with each other, so that the LIBS spectrum signals and the plasma acoustic signals are simple and easy to collect. The salinity inversion model established based on the PCA algorithm and the SVM algorithm is reasonable and effective. Meanwhile, the concentration information of chemical elements causing the salinity change of the seawater can be judged, and the method provided by the invention has the advantages of low cost, simplicity in operation and obvious inversion effect.

(2) The invention utilizes the physical process that a beam of pulse laser is focused on the seawater body to generate plasma, and utilizes a spectrometer and a hydrophone to realize the effective acquisition of two types of signals of the generated LIBS spectrum and the plasma sound wave.

(3) According to the invention, the LIBS spectrum signal and the plasma acoustic wave signal are fused, and an SVM algorithm is utilized to establish an inversion model of seawater salinity, so that the effective inversion of the seawater salinity is realized. Meanwhile, the salinity change caused by the change of the chemical elements can be effectively judged by utilizing the spectral information.

(4) In the innovation points, the collection of the underwater LIBS spectrum and the plasma acoustic signal is not limited by the environment, only depends on the stability of collection equipment, has the advantages of in-situ, real-time, multi-component and rapid detection, and can be applied to the LIBS spectrum and the plasma acoustic signal in extreme environments such as deep sea cold springs, submarine hot liquids and the like in marine environments. The salinity in the marine environment can be directly measured by utilizing the steps of the method provided by the invention on the acquired signals.

Third, as an inventive supplementary proof of the claims of the present invention, there are also presented several important aspects:

(1) In the future, the technical scheme of the invention can be used for integrally manufacturing corresponding detecting instruments and is tried to be applied to the actual detection of the salinity of the marine environment.

(2) In the current research, an in-situ measurement example of applying the underwater LIBS spectrum and the plasma acoustic signal to the ocean salinity information in a combined manner is not available, the method provided by the invention can show the advantages of the LIBS spectrum and the plasma acoustic signal, and the method for measuring the seawater salinity by integrating the photoacoustic information has creativity and advancement.

(3) The technical scheme provided by the invention provides a novel method for in-situ measurement of the ocean salinity environment, and has certain inspiration on further research on the measurement of the ocean salinity environment.

(4) The invention provides a possible application of photoacoustic information in ocean combined detection, and provides a direction for combined application of photoacoustic information in ocean in the future.

Drawings

The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present disclosure and, together with the description, serve to explain the principles of the disclosure.

FIG. 1 is a flow chart of a method for measuring seawater salinity in situ based on photoacoustic information fusion, provided by an embodiment of the present invention;

FIG. 2 is a schematic diagram of a method for measuring seawater salinity in situ based on photoacoustic information fusion provided by an embodiment of the present invention;

FIG. 3 is a schematic diagram of an experimental apparatus for collecting an underwater LIBS spectrum and a plasma acoustic wave according to an embodiment of the present invention;

FIG. 4 is a typical LIBS spectrum acquired by the experimental apparatus of FIG. 3 provided by an embodiment of the present invention;

FIG. 5 is a graph of a typical plasma acoustic signal collected by the experimental apparatus of FIG. 3, provided in accordance with an embodiment of the present invention;

FIG. 6 (a) is a calibration curve diagram of LIBS spectrum inversion corresponding to calibration curves of 17 sample salinities used under different inversion methods provided by the embodiment of the invention;

FIG. 6 (b) is a calibration curve graph of salinity of 17 samples used in different inversion methods corresponding to inversion with plasma acoustic waves;

fig. 6 (c) is a calibration curve diagram of the inversion by fusion of acoustic waves and spectra according to the present invention in calibration curves of salinity of 17 samples under different inversion methods according to the embodiment of the present invention;

FIG. 7 (a) is a calibration graph of Na element of 17 samples used in a univariate inversion method according to an embodiment of the present invention;

FIG. 7 (b) is a calibration graph of K elements of 17 samples used in a univariate inversion method according to an embodiment of the present invention;

FIG. 7 (c) is a calibration graph of 17 sample Ca elements used in a univariate inversion method according to an embodiment of the present invention;

FIG. 8 (a) is a calibration graph of the Na elements of 17 samples used in the example of the present invention under the SVM element inversion method proposed by the present invention;

FIG. 8 (b) is a plot of the scaling curves for the 17 sample K elements used in the example of the present invention under the SVM element inversion method proposed by the present invention;

FIG. 8 (c) is a calibration graph of 17 sample Ca elements used in the example of the present invention under the SVM element inversion method proposed by the present invention;

in the figure: 1. a laser; 2. a half-wave plate; 3. a Glan prism; 4. a cube beam splitter; 5. a laser beam expander; 6. an achromatic doublet; 7. a hydrophone; 8. a spectrometer; 9. an oscilloscope; 10. a digital delay pulse generator; 11. an optical fiber; 12. a photodiode.

Detailed Description

In order to make the aforementioned objects, features and advantages of the present invention 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 invention. This invention may, however, be embodied in many different forms and should not be construed as limited to the embodiments set forth herein, but rather should be construed as broadly as the present invention is capable of modification in various respects, all without departing from the spirit and scope of the present invention.

High-power laser is focused on a seawater body to generate transient plasma after interaction, spectral signals can be collected by plasma characteristic radiation light, and meanwhile, the plasma expands outwards to generate sound wave signals. The spectral signal directly reflects the element composition content in seawater and is the space-time integral of plasma radiation light; the acoustic signal comprises energy conversion information in the breakdown process and related information of the plasma expansion process, and the waveform and position information of the acoustic signal can well reflect the change of the seawater environment. Therefore, the spectrum signal and the acoustic wave signal can provide more reliable information about the physical process of the underwater laser induced plasma after being fused, namely the seawater composition information is more easily reflected, and therefore, the inversion of the seawater salinity information by combining the LIBS spectrum signal and the plasma acoustic wave signal is a feasible method.

1. Illustrative examples are illustrated:

the method for measuring seawater salinity in situ based on photoacoustic information fusion provided by the embodiment of the invention utilizes a physical process that a beam of pulse laser is focused on a seawater body to generate plasma, and utilizes a spectrometer 8 and a hydrophone 7 to realize effective collection of two types of signals of the generated LIBS spectrum and the plasma sound wave.

By fusing the LIBS spectrum signal and the plasma acoustic wave signal, an inversion model of the seawater salinity is established by utilizing an SVM algorithm, and effective inversion of the seawater salinity is realized. Meanwhile, the salinity change caused by the change of chemical elements can be effectively judged by utilizing the spectral information.

Example 1

As shown in fig. 1, the method for in-situ measurement of seawater salinity based on photoacoustic information fusion (method for performing seawater salinity information inversion based on LIBS spectrum signal combined with plasma acoustic signal) provided by the embodiment of the present invention includes the following steps:

step 1: and (4) collecting underwater LIBS spectrum and plasma sound wave signals.

Seawater samples with different salinity are changed, and underwater LIBS spectrum signals and plasma sound wave signals are acquired under the condition that the laser energy is 20mJ.

Step 2: processing of LIBS spectra and plasma acoustic signals.

Firstly, preprocessing n acquired spectrum signals, specifically performing spectral line element attribution, and performing full spectrum normalization processing after baseline subtraction. On one hand, PCA analysis is carried out on the normalized spectrum to obtain a spectrum training matrix PC after dimension reduction _sp (the matrix is n multiplied by m, which represents the matrix size of n rows and m columns of the matrix, and m is the number of principal components), wherein the optimal number m of the principal components is determined according to the percentage of the variance of the principal component interpretation original data; on the other hand, the normalized spectrum is respectively subjected to characteristic extraction in the spectral line range of Na, K and Ca elements to obtain V _Na 、V _K 、V _Ca (n × p, representing the matrix size of n rows and p columns of the matrix, and p is determined by the spectrum length of the range where Na, K and Ca elements are locatedFixed). For n collected sound wave signals, obtaining a sound wave training matrix Fea according to the intensity information and the position information of the sound signals _ac (the matrix is n × s, the matrix size of n rows and s columns of the matrix, and s is the number of acoustic signal features). Training matrix PC for the obtained spectrum _sp And acoustic training matrix Fea _ac Combining the two to obtain a new training characteristic matrix Vec (the matrix is n x (m + s) and represents the matrix size of n rows and m + s columns of the matrix, wherein m is the number of principal components, and s is the characteristic number of the sound signal).

And step 3: and (3) establishing a salinity inversion model under the spectrum-sound wave signal fusion.

And (3) performing SVM regression by using the characteristic matrix Vec obtained in the step (2) as an independent variable of the sample and using the salinity of the seawater as a dependent variable to obtain an inversion model of the salinity. For a measurement sample with unknown salinity, collecting a spectrum signal and a sound wave signal of the measurement sample, repeating the steps to obtain Vec 'of a prediction sample, and substituting the Vec' into the established SVM salinity inversion model to obtain a salinity value of the measurement sample (the process is carried out by using a written algorithm in MATLAB R2017b software).

And 4, step 4: and (5) building a seawater element concentration prediction model.

The inversion of the salinity value of seawater can already be obtained by the first 3 steps. The method provided by the invention can also predict salinity information change caused by chemical element change in seawater. The feature matrix V of the elements obtained in the step 2 _Na 、V _K 、V _Ca Respectively serving as independent variables of the sample, and respectively serving as dependent variables of the element concentration to perform SVM regression to respectively establish a prediction model of Na, K and Ca element concentration. For a measurement sample with unknown salinity, collecting the spectral signal to obtain a characteristic matrix V of Na, K and Ca _Na ’、V _K ’、V _Ca ', respectively substituting the Na, K and Ca into the established SVM prediction models of Na, K and Ca to obtain the concentrations of Na, K and Ca elements of the measured sample (the process is carried out in MATLAB R2017b software by using a written algorithm).

Example 2

As shown in fig. 2, the method for in-situ measurement of seawater salinity based on photoacoustic information fusion (method for performing seawater salinity information inversion based on LIBS spectrum signal combined with plasma acoustic signal) provided by the embodiment of the present invention includes the following steps:

step 1: and (4) collecting LIBS spectra and plasma sound wave signals under seawater samples with different salinity. The method comprises the steps of changing solutions with different salinity, and collecting LIBS spectrum and plasma sound wave signals under seawater samples with different salinity by using the experimental device for the underwater LIBS spectrum and the plasma sound wave shown in FIG. 3. A laser 1 is adopted to generate laser pulses with the wavelength of 1064nm, a half-wave plate 2 and a Glan prism 3 are utilized to adjust the energy of the laser pulses to be 20mJ, and 10% of each laser pulse is reflected by a cubic beam splitter 4 and sent to a photodiode 12 connected with an oscilloscope 9; expanding the laser beam by a laser beam expander 5 for 90% of the laser pulse, and focusing the laser beam into a quartz water tank filled with a sample by an achromatic double cemented lens 6 for generating plasma;

the sound waves generated by the plasma are collected by a hydrophone 7 vertically arranged above and stored in an oscilloscope 9; light generated by the plasma is converged by lateral lens groups (L2 and L3) and coupled into a spectrometer 8 through an optical fiber 11, and is controlled by a digital delay pulse generator 10; collecting underwater LIBS spectrum and plasma sound wave signals of the prepared seawater samples with different salinity.

The experimental device for collecting the underwater LIBS spectrum and the plasma sound wave as shown in fig. 3 in the embodiment of the present invention includes: the Laser comprises a Laser 1 (Laser), a half-wave plate 2 (HWP), a Glan prism 3 (GP), a cube beam splitter 4 (BS), a Laser beam expander 5 (LBE), a lens 6 (L1), a Hydrophone 7 (Hydrophone), a Spectrometer 8 (Spectrometer), an Oscilloscope 9 (Oscilloscope), a digital time Delay pulse Generator 10 (Delay Generator 645), an optical Fiber 11 (Fiber) and a photodiode 12 (PD).

And 2, step: firstly, preprocessing n acquired spectrum signals, specifically performing spectral line element attribution, and performing full spectrum normalization processing after baseline subtraction. On one hand, PCA analysis is carried out on the normalized spectrum to obtain a spectrum training matrix PC after dimension reduction _sp (matrix is n x m, m is the number of principal components), wherein, the optimal principal is determined according to the percentage of the variance of the principal component interpretation original dataA component number m; on the other hand, the normalized spectrum is respectively subjected to characteristic extraction in the spectral line range of Na, K and Ca elements to obtain V _Na 、V _K 、V _Ca (the matrix is n × p, and p is determined by the spectrum length of the range where the elements of Na, K and Ca are located). For the n collected sound wave signals, obtaining a sound wave training matrix Fea according to the intensity information and the position information of the sound signals _ac (the matrix is n × s, s is the number of acoustic signal features). Training matrix PC for the obtained spectrum _sp And acoustic training matrix Fea _ac Combining the two to obtain a new training characteristic matrix Vec (the matrix is n x (m + s)).

And 3, step 3: and (3) taking the characteristic matrix Vec obtained in the step (2) as an independent variable of the sample, taking the salinity value of the seawater as a dependent variable, carrying out SVM regression analysis by using an SVM algorithm, establishing a salinity inversion model, calculating evaluation parameters of the salinity inversion model, and evaluating the analysis effect of the model on the precision, the accuracy and the stability.

And 4, step 4: the feature matrix V of each element obtained in the step 2 _Na 、V _K 、V _Ca And respectively serving as independent variables of the sample, and respectively serving the concentration of each element as a dependent variable to perform SVM regression analysis, and respectively establishing an inversion model of the concentrations of Na, K and Ca elements.

And 5: and verifying the built inversion model and the prediction model by using the prediction set. For a measurement sample with unknown salinity, collecting a spectrum signal and an acoustic signal of the measurement sample, repeating the steps to obtain Vec 'of a prediction sample, and substituting the Vec' into the established SVM salinity inversion model to obtain a salinity value of the measurement sample; the Na, K and Ca characteristic matrix V of the measurement sample with unknown salinity _Na ’、V _K ’、V _Ca ' the concentrations of Na, K and Ca elements contained in the measured sample can be obtained by respectively substituting the Na, K and Ca elements into the established SVM prediction models. And finally, establishing a calibration curve according to the salinity information, and calculating evaluation parameters of the model to evaluate the analysis effect of the model on the precision and the accuracy.

Example 3

In one scheme, the equipment for acquiring the acoustic wave signals of the laser-induced plasma in the water is a needle hydrophone 7 and an oscilloscope 9, but other equipment capable of detecting and acquiring the acoustic wave signals can also realize the method, so that the scheme of adopting other acoustic wave signal acquisition equipment can be used as an alternative scheme for the plasma acoustic wave acquisition. The substitution scheme is only a substitution of a previous-stage data acquisition method, and the core of the invention is to establish a salinity inversion model by using the acquired LIBS spectrum and the plasma sound wave based on a PCA algorithm and an SVM algorithm so as to realize detailed analysis of seawater salinity information. For the substitution of the data acquisition experimental device, in principle, only the collected LIBS spectrum and sound wave signals can be ensured, and good signal quality can be obtained.

In the above embodiments, the description of each embodiment has its own emphasis, and reference may be made to the related description of other embodiments for parts that are not described or recited in any embodiment.

For the information interaction, execution process and other contents between the above devices/units, the specific functions and technical effects brought by the method embodiments of the present invention based on the same concept can be referred to the method embodiments, and are not described herein again.

It should be clear to those skilled in the art that, for convenience and simplicity of description, the foregoing division of the functional units and modules is only used for illustration, and in practical applications, the above function distribution may be performed by different functional units and modules as needed, that is, the internal structure of the apparatus may be divided into different functional units or modules to perform all or part of the above described functions. Each functional unit and module in the embodiments may be integrated in one processing unit, or each unit may exist alone physically, or two or more units are integrated in one unit, and the integrated unit may be implemented in a form of hardware, or in a form of software functional unit. In addition, specific names of the functional units and modules are only for convenience of distinguishing from each other, and are not used for limiting the protection scope of the present invention. The specific working processes of the units and modules in the system may refer to the corresponding processes in the foregoing method embodiments, and are not described herein again.

2. The application example is as follows:

an embodiment of the present invention further provides a computer device, where the computer device includes: at least one processor, a memory, and a computer program stored in the memory and executable on the at least one processor, the processor implementing the steps of any of the various method embodiments described above when executing the computer program.

Embodiments of the present invention further provide a computer-readable storage medium, where a computer program is stored, and when the computer program is executed by a processor, the steps in the above method embodiments may be implemented.

The embodiment of the present invention further provides an information data processing terminal, where the information data processing terminal is configured to provide a user input interface to implement the steps in the above method embodiments when implemented on an electronic device, and the information data processing terminal is not limited to a mobile phone, a computer, or a switch.

The embodiment of the present invention further provides a server, where the server is configured to provide a user input interface to implement the steps in the above method embodiments when implemented on an electronic device.

Embodiments of the present invention provide a computer program product, which, when running on an electronic device, enables the electronic device to implement the steps in the above method embodiments when executed.

The integrated unit, if implemented in the form of a software functional unit and sold or used as a stand-alone product, may be stored in a computer readable storage medium. Based on such understanding, all or part of the flow of the method according to the embodiments of the present invention may be implemented by a computer program, which may be stored in a computer-readable storage medium, and when the computer program is executed by a processor, the steps of the method embodiments described above may be implemented. Wherein the computer program comprises computer program code, which may be in the form of source code, object code, an executable file or some intermediate form, etc. The computer readable medium may include at least: any entity or device capable of carrying computer program code to a photographing apparatus/terminal apparatus, a recording medium, computer memory, read-only memory (ROM), random Access Memory (RAM), electrical carrier signal, telecommunications signal, and software distribution medium. Such as a usb-disk, a removable hard disk, a magnetic or optical disk, etc.

3. Evidence of the relevant effects of the examples:

the method provided by the invention is applied to the inversion of the seawater salinity information in a laboratory, and fig. 3 is a schematic diagram of an experimental device for collecting an underwater LIBS spectrum and a plasma sound wave in the laboratory, so as to illustrate the favorable advantages of the method provided by the invention applied to the inversion of the seawater salinity information, so that the underwater laser induced plasma sound wave signal and the spectrum signal can exert the advantages in other application aspects, thereby showing the practical significance of the invention and being an example for proving the practical application effect of the invention.

The experimental process of collecting the underwater LIBS spectrum signal and the plasma sound wave signal is as follows:

17 groups of samples with different salinity are prepared and shown in the table 1, and the samples comprise Na, K and Ca elements in different proportions. For a sample with a certain salinity, the sample is placed in a sample cell of a quartz water tank, a laser 1 generates pulsed laser with the wavelength of 1064nm and the frequency of 1Hz, the generated laser firstly passes through a half-wave plate 2 (HWP) and a Glan prism 3 (GP), and the pulse energy of the laser is controlled at 20mJ. A fraction (10%) of the laser pulse is reflected by the cube beam splitter 4 (BS) and sent to a photodiode 12 (PD) connected to an Oscilloscope 9 (oscillososcope) to monitor the stability of the laser energy. The other part of the laser pulse is expanded by a laser beam expander 5 (LBE), the expanded laser is focused into a quartz water tank sample pool through an achromatic double cemented lens 6 (L1) to generate plasma, and a generated sound wave signal is collected by a hydrophone 7 vertically placed above the plasma and stored in an oscilloscope 9; the light generated by the plasma is collected by lateral lens groups (L2, L3) and coupled into a Spectrometer 8 (Spectrometer) via an optical fiber 11, controlled by a digital Delay pulse Generator (Delay Generator 645). And then sequentially replacing the quartz water tank with samples with other salinity to obtain underwater LIBS spectra and plasma sound wave signals of seawater samples with all salinity.

The resulting typical LIBS spectrum is shown in fig. 4, and the typical plasma acoustic wave signal is shown in fig. 5. Calibration curves (fig. 6 (a) corresponds to a calibration curve inverted by LIBS spectrum, fig. 6 (b) corresponds to a calibration curve inverted by plasma acoustic wave, and fig. 6 (c) corresponds to a calibration curve inverted by the combination of acoustic wave and spectrum provided by the invention) of 17 groups of seawater samples with different salinity under different inversion methods are obtained, wherein a solid graph represents a training set sample for establishing an inversion model, a hollow graph represents a prediction set sample for verifying the model, and the prediction set and the training set of the sample are marked with marks (corresponding to the numbers) in a sample 1 table. Using a correlation coefficient (R) ² ) The prediction ability of the calibration curve is characterized by the root mean square error (RMSEP/RMSEC) of the prediction set and the training set, the relative standard deviation (RSD _ P, RSD _ C) of the prediction set and the training set and the average relative error (ARE _ P, ARE _ C) of the prediction set and the training set, and the evaluation parameters of the prediction ability of the different salinity inversion methods on the salinity of the sample ARE shown in the table 2.

The calibration curves of the Na, K and Ca elements of the 17 samples under the univariate method are respectively as follows: FIG. 7 (a) is a calibration graph of Na elements of 17 samples used in a univariate inversion method according to an embodiment of the present invention; FIG. 7 (b) is a calibration graph of K elements of 17 samples used in a univariate inversion method according to an embodiment of the present invention; FIG. 7 (c) is a calibration graph of Ca elements of 17 samples used in a univariate inversion method according to an embodiment of the present invention;

the calibration curves of the used 17 samples of Na, K and Ca under the SVM element prediction method provided by the invention are respectively as follows: FIG. 8 (a) is a calibration graph of the Na elements of 17 samples used in the example of the present invention under the SVM element inversion method proposed by the present invention; FIG. 8 (b) is a plot of the scaling curves for the 17 sample K elements used in the example of the present invention under the SVM element inversion method proposed by the present invention; FIG. 8 (c) is a calibration graph of 17 sample Ca elements used in the example of the present invention under the SVM element inversion method proposed by the present invention;

wherein, fig. 7 (a) and fig. 8 (a) are prediction models of Na element, fig. 7 (b) and fig. 8 (b) are prediction models of K element, fig. 7 (c) and fig. 8 (c) are prediction models of Ca element, a solid graph represents a training set sample for establishing an inversion model, an open graph represents a prediction set sample for verifying the model (Na element: circle, K element: triangle, ca element: pentagram), and the comparison of evaluation parameters of Na, K, ca element calibration curves under the two methods is shown in table 3.

Table 1 salinity and Na, K, ca element concentrations of the 17 sample solutions used;

TABLE 2 evaluation parameters of calibration curves for different salinity inversion methods

TABLE 3 evaluation parameters of Na, K, ca element calibration curve under two methods

The results of fig. 6 and table 2 show that the calibration curve established by the salinity inversion model of spectrum and acoustic fusion provided by the invention has very high correlation coefficient, compared with the method only adopting spectrum inversion or only adopting acoustic signal inversion, R ² The value of (A) is increased from 0.9 and 0.99 to more than 0.999; the RMSEP is reduced to 0.5 per thousand from more than 5 per thousand and 0.7 per thousand, and the RMSEC is reduced to less than 0.5 per thousand from more than 3 per thousand and more than 0.6 per thousand; the ARE _ P is reduced to be lower than 2% from higher than 19% and 2.5%, the ARE _ C is reduced to be lower than 1.5% from higher than 12% and higher than 2%, and the results show that the salinity inversion model of photoacoustic information fusion provided by the invention has high accuracy and precision, and meanwhile, the RSD of the built inversion model is lower than 1.5%, which means that the inversion model has high stability and predicts that the inversion model has high stabilityThe error is relatively low.

The results of fig. 7, fig. 8 and table 3 show that, compared with the traditional univariate method, for the inversion of the concentrations of Na, K and Ca elements contained in the sample, the SVM multivariate inversion model provided by the invention obtains R of the calibration curve of Na and K elements ² The value is above 0.999, R of the Ca element calibration curve ² The fitting effect is greatly improved compared with a univariate value when the fitting effect is more than 0.996; meanwhile, the prediction precision and error are far better than those of the traditional univariate method, the average RMSEP of the three elements is reduced from 1003.68mg/L to 190.71mg/L, the average RMSEC is reduced from 725.87mg/L to 134.25mg/L, and the prediction precision of the elements is obviously improved; the average RSD _ P of the three elements is reduced from 12.12% to 5.89%, the average RSD _ C is reduced from 10.50% to 4.54%, the RSD _ C is improved by about 50%, and the stability is greatly improved. The average ARE _ P of the three elements is reduced from 22.21% to 6.70%, and the average ARE _ C is reduced from 18.55% to 3.47%. The model prediction accuracy is greatly improved by about 70%. The results show that the established inversion model of the Na, K and Ca elements can effectively predict the concentrations of the Na, K and Ca elements, namely, the analysis of the concentration of the main elements causing the salinity change of the seawater can be realized.

In summary, compared with a salinity inversion method only using LIBS spectral signals, the salinity inversion method provided by the invention can achieve extremely high inversion accuracy and extremely low inversion error; compared with a salinity inversion method only using plasma acoustic signals, the salinity inversion method provided by the invention can further improve the inversion accuracy and can effectively predict the content change of Na, K and Ca elements causing salinity change. The method provided by the invention can achieve high precision for the inversion of the seawater salinity, and the provided inversion model has extremely high availability and reflects the feasibility of the method provided by the invention.

Compared with the existing method for measuring the salinity of the conductivity seawater, the method provided by the invention only needs to collect the LIBS spectrum and the plasma sound wave signals, and the collection of data is not affected, so that the method is not like an error caused by asynchronous detection of a conductivity method; compared with a refractive index method salinity measuring method, the method provided by the invention is simple to operate, can carry out real-time detection, and cannot be greatly corroded; compared with a buoy method salinity measuring method, the method provided by the invention can not only be fixed at a certain position for detection, can realize large-area seawater salinity measurement, and has higher data resolution.

The results show that the salinity inversion model established by the SVM algorithm after fusion of the acoustic wave and the spectral signal has great improvement in both stability improvement and analysis accuracy compared with the method only utilizing the spectral signal or the acoustic wave signal, and has excellent salinity inversion effect, and the method provided by the invention has good application potential and popularization in the salinity in-situ measurement.

The above description is only for the purpose of illustrating the preferred embodiments of the present invention, and the scope of the present invention should not be limited thereto, and any modifications, equivalents and improvements made by those skilled in the art within the technical scope of the present invention as disclosed in the present invention should be covered thereby.

Claims

1. A seawater salinity in-situ measurement method based on photoacoustic information fusion is characterized by comprising the following steps:

s2, processing the collected LIBS spectrum and plasma sound wave signals;

2. The method for in-situ measurement of seawater salinity based on photoacoustic information fusion according to claim 1, characterized in that in step S1, the LIBS spectrum and the plasma acoustic wave signal of seawater samples with different salinity are collected by using an underwater LIBS spectrum and plasma acoustic wave experimental device, laser pulses are generated by using a laser (1), the laser pulse energy is adjusted by using a half-wave plate (2) and a glan prism (3), and a part of each laser pulse is reflected by a cube beam splitter (4) and sent to a photodiode (12) connected with an oscilloscope (9); the other part of the laser pulse expands the laser beam by a laser beam expander (5), and the laser beam is focused into a quartz water tank filled with a seawater sample by an achromatic double cemented lens (6) for generating plasma;

the sound wave generated by the plasma is collected by a hydrophone (7) vertically arranged above the plasma and is stored in an oscilloscope (9); light generated by the plasma is converged by a lateral lens group and coupled into a spectrometer (8) through an optical fiber (11), and is controlled by a digital delay pulse generator (10); obtaining underwater LIBS spectra and plasma sound wave signals of seawater samples with different salinity.

3. The method for in-situ measurement of seawater salinity based on photoacoustic information fusion of claim 1, wherein in step S2, processing the collected LIBS spectrum and plasma acoustic wave signals comprises the following steps:

(1) Performing spectral line element attribution on the obtained n spectral signals, and performing full spectrum normalization processing after baseline subtraction; on one hand, PCA analysis is carried out on the normalized spectrum to obtain a spectrum training matrix PC after dimension reduction _sp ；

(2) For n collected sound wave signals, obtaining a sound wave training matrix Fea according to the intensity information and the position information of the sound signals _ac ；

(3) Training matrix PC for the obtained spectrum _sp And acoustic training matrix Fea _ac And combining to obtain a new training feature matrix Vec.

4. The method for in-situ measurement of seawater salinity based on photoacoustic information fusion as claimed in claim 3, wherein in step (1), the spectrum training matrix PC _sp Is n × m, and represents the matrix size of n rows and m columns of the matrix, m is the number of principal components, wherein the maximum value is determined according to the percentage of the variance of the principal component interpretation raw dataThe number m of the preferred main components; on the other hand, the normalized spectrum respectively carries out feature extraction in the spectral line range of Na, K and Ca elements to obtain feature matrixes of the Na, K and Ca elements respectively as V _Na 、V _K 、V _Ca The matrix is n × p, which represents the matrix size of n rows and p columns of the matrix, and p is determined by the spectrum length of the range where the elements Na, K and Ca are located.

5. The method for in-situ measurement of seawater salinity based on photoacoustic information fusion as claimed in claim 3, wherein in step (2), the acoustic wave trains the matrix Fea _ac Is n × s, the matrix size of n rows and s columns of the matrix, and s is the characteristic number of the acoustic signal.

6. The method for in-situ measurement of seawater salinity based on photoacoustic information fusion as defined in claim 3, wherein in step (3), the training feature matrix Vec is n x (m + s) and represents the matrix size of n rows and m + s columns of the matrix, m is the number of principal components, and s is the feature number of acoustic signals.

7. The photoacoustic information fusion-based seawater salinity in-situ measurement method of claim 3, wherein in step S3, establishing a salinity inversion model under the spectrum-acoustic signal fusion comprises the following steps:

performing SVM regression by using the obtained training feature matrix Vec as an independent variable of a sample and using the salinity value of the seawater as a dependent variable to obtain an inversion model of the salinity; and for a measurement sample with unknown salinity, acquiring a spectrum signal and a sound wave signal, repeating the step S2 to obtain Vec 'of the prediction sample, and substituting the Vec' into the established SVM salinity inversion model to obtain the salinity value of the measurement sample.

8. The photoacoustic information fusion-based seawater salinity in-situ measurement method of claim 3, wherein in step S3, establishing a seawater element concentration prediction model comprises the following steps:

the obtained element feature matrix V _Na 、V _K 、V _Ca The matrix is n × p, representing the matrixThe matrix size of n rows and p columns, wherein p is determined by the range spectrum length of Na, K and Ca elements and is respectively used as independent variables of the sample, the concentration of the elements is respectively used as dependent variables to carry out SVM regression, and prediction models of the concentrations of the Na, K and Ca elements are respectively established;

for a measurement sample with unknown salinity, acquiring spectral signals to obtain a Na, K and Ca element characteristic matrix V _Na ’、V _K ’、V _Ca And respectively substituting the concentrations of Na, K and Ca elements of the measured sample into the established SVM prediction models of Na, K and Ca.

9. An experimental device for acquiring underwater LIBS spectrum and plasma sound wave by implementing the photoacoustic information fusion-based seawater salinity in-situ measurement method according to any one of claims 1 to 8.

10. Use of the method for in-situ measurement of seawater salinity based on photoacoustic information fusion according to any one of claims 1-8 for in-situ measurement of seawater salinity parameters in different sea areas.