CN115266603A - Turbidity compensation method, device, equipment and storage medium - Google Patents
Turbidity compensation method, device, equipment and storage medium Download PDFInfo
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Abstract
The invention provides a turbidity compensation method, a turbidity compensation device, turbidity compensation equipment and a storage medium, wherein the method comprises the following steps: acquiring initial spectrum data of a water body to be detected, and determining the water body type of the water body to be detected according to the initial spectrum data; constructing a turbidity compensation model corresponding to the water body to be detected based on the water body type; and carrying out turbidity compensation on the initial spectral data of the water body to be detected by using the turbidity compensation model. According to the turbidity compensation method provided by the invention, the turbidity compensation model is established based on the water body type of the water body to be detected, so that the turbidity compensation of different types of water bodies can be realized, the influence of suspended particles in the water body to be detected on spectral data is offset through the turbidity compensation, the measurement precision of water quality parameters is improved, and the accuracy of the water quality detection result of the water body to be detected is improved.
Description
Technical Field
The invention relates to the technical field of water quality detection, in particular to a turbidity compensation method, a turbidity compensation device, turbidity compensation equipment and a storage medium.
Background
The physical property and chemical composition of water are the comprehensive characteristics of water under the action of environment, and water in nature is a complex composed of various substances with solubility and/or non-solubility. Water of different purposes has different requirements on water quality, and for example, domestic water, industrial water, farmland irrigation water and the like have different requirements on water quality. The water contains suspended and colloidal tiny particles, so that the original colorless and transparent water generates a turbidity phenomenon, and the turbidity degree is called turbidity. Turbidity is an optical effect, and is the degree of obstruction when light penetrates through a water layer, and represents the scattering and absorption capacity of a water body to the light. The turbidity of the water body is related to the content of suspended particles, the components, the particle size, the shape and the surface of the water body, and the light reflection performance of the water body, and the turbidity influences the light absorption condition of the water body, further influences the measurement of water quality parameters and finally influences the water quality detection result.
Disclosure of Invention
The invention provides a turbidity compensation method, a turbidity compensation device, turbidity compensation equipment and a turbidity compensation storage medium, which are used for solving the problem that the light scattering and absorption characteristics of suspended particles in a water body influence a water quality detection result and improving the accuracy of the water quality detection result.
The invention provides a turbidity compensation method, which comprises the following steps:
acquiring initial spectrum data of a water body to be detected, and determining the water body type of the water body to be detected according to the initial spectrum data;
constructing a turbidity compensation model corresponding to the water body to be detected based on the water body type;
and carrying out turbidity compensation on the initial spectral data of the water body to be detected by using the turbidity compensation model.
According to the turbidity compensation method provided by the invention, the step of constructing the turbidity compensation model corresponding to the water body to be detected based on the water body type comprises the following steps:
acquiring training spectrum data corresponding to the water body to be detected according to the water body type, and performing turbidity compensation on the training spectrum data to generate compensation spectrum data;
and acquiring a preset basic model to be trained, and performing iterative training on the basic model to be trained by using the training spectrum data and the compensation spectrum data to obtain a turbidity compensation model corresponding to the water body to be tested.
According to the turbidity compensation method provided by the invention, the step of acquiring the training spectral data corresponding to the water body to be detected according to the water body type, performing turbidity compensation on the training spectral data and generating the compensation spectral data comprises the following steps:
collecting spectral data of different turbidities of water body samples of various water body types to generate a spectral data set;
acquiring spectral data corresponding to the water body to be detected from the spectral data set according to the water body type of the water body to be detected, and acquiring training spectral data corresponding to the water body to be detected;
and carrying out turbidity compensation on the training spectrum data by using a preset turbidity compensation algorithm to obtain compensation spectrum data corresponding to the water body to be detected.
According to the turbidity compensation method provided by the invention, the basic model to be trained is a deep learning model.
According to the turbidity compensation method provided by the invention, the step of determining the water body type of the water body to be detected according to the initial spectrum data comprises the following steps:
carrying out normalization processing on the initial spectrum data to obtain target spectrum data;
and fitting the target spectrum data into a spectrum curve, and determining the water body type of the water body to be detected according to the shape of the spectrum curve.
According to the turbidity compensation method provided by the invention, the step of performing turbidity compensation on the initial spectral data by using the turbidity compensation model comprises the following steps:
analyzing the particle size of scattering particles of the initial spectral data by using the turbidity compensation model, and reconstructing the particle size distribution of suspended particles in the water body to be detected;
estimating an absorbance value of the suspended particulate matter caused in a range from ultraviolet to visible light based on the particle size distribution;
and subtracting the absorbance value on the basis of the initial spectral data to perform turbidity compensation on the initial spectral data of the water body to be detected.
According to the turbidity compensation method provided by the invention, after the step of performing turbidity compensation on the initial spectral data of the water body to be detected by using the turbidity compensation model, the method further comprises the following steps:
fitting the spectral data of the water body to be detected after turbidity compensation into a spectral curve;
and determining the water quality parameter of the water body to be detected according to the spectrum curve, and determining the water quality of the water body to be detected according to the water quality parameter.
The present invention also provides a turbidity compensating apparatus, comprising:
the system comprises a spectrum acquisition module, a water quality detection module and a water quality detection module, wherein the spectrum acquisition module is used for acquiring initial spectrum data of a water body to be detected and determining the water body type of the water body to be detected according to the initial spectrum data;
the model construction module is used for constructing a turbidity compensation model corresponding to the water body to be detected based on the water body type;
and the turbidity compensation module is used for performing turbidity compensation on the initial spectral data of the water body to be detected by using the turbidity compensation model.
The present invention also provides an electronic device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, wherein the processor implements the turbidity compensation method as described in any of the above when executing the program.
The invention also provides a non-transitory computer readable storage medium having stored thereon a computer program which, when executed by a processor, implements a turbidity compensation method as described in any one of the above.
The invention also provides a computer program product comprising a computer program which, when executed by a processor, implements a method of turbidity compensation as described in any one of the above.
According to the turbidity compensation method, the turbidity compensation device, the turbidity compensation equipment and the storage medium, the turbidity compensation model is established based on the water body type of the water body to be detected, the turbidity compensation of different types of water bodies can be realized, the influence of suspended particles in the water body to be detected on spectral data is counteracted through the turbidity compensation, the measurement precision of water quality parameters is improved, and therefore the accuracy of the water quality detection result of the water body to be detected is improved.
Drawings
In order to more clearly illustrate the technical solutions of the present invention or the prior art, the drawings needed for the description of the embodiments or the prior art will be briefly described below, and it is obvious that the drawings in the following description are some embodiments of the present invention, and those skilled in the art can also obtain other drawings according to the drawings without creative efforts.
FIG. 1 is one of the flow diagrams of the turbidity compensation method provided by the present invention;
FIG. 2 is a schematic structural diagram of a turbidity compensating apparatus provided in the present invention;
fig. 3 is a schematic structural diagram of an electronic device provided in the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention clearer, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings, and it is obvious that the described embodiments are some, but not all embodiments of the present invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Referring to fig. 1, fig. 1 is a schematic flow chart of a turbidity compensation method provided by the present invention, and based on fig. 1, the turbidity compensation method provided by the present invention includes the following steps:
when carrying out turbidity compensation, the initial spectral data of the water body to be measured is firstly collected, and the initial spectral data can be collected based on a water body sample extracted from the water body to be measured or can be directly collected based on the water body to be measured. The water body type of the water body to be detected is determined according to the acquired initial spectrum data, and therefore, the water bodies with different purposes, such as domestic water, industrial water, farmland irrigation water and the like, have different standard requirements on the physical properties, the total mineralization degree, the total hardness, the contents of bacteria and harmful substances and the like of water, and the turbidity of the water bodies is different, so that the scattering and absorption capacities of the water bodies on light rays are different. Therefore, the water type may be classified according to different criteria such as the usage of the water, the turbidity of the water, and the like, and is not limited herein. It can be understood that the water body types of the water body to be measured are determined according to the characteristics of the acquired spectral data, wherein the spectral data of the water body are different in corresponding spectral form, namely the spectral data have different characteristics.
Further, step 100 may further include:
step 101, performing normalization processing on the initial spectrum data to obtain target spectrum data;
and 102, fitting the target spectrum data into a spectrum curve, and determining the water body type of the water body to be detected according to the shape of the spectrum curve.
When the water body type of the water body to be detected is determined, firstly, normalization processing is carried out on the collected spectral data, target spectral data obtained after normalization processing are fitted, the target spectral data are fitted into a spectral curve, and the water body type of the water body to be detected is determined according to the shape of the spectral curve. The reason is that the spectral shapes corresponding to the spectral data of different types of water bodies are different, so that the spectral curves obtained by fitting the spectral data have different characteristics, and the characteristics of the spectral curves are reflected on the shapes of the curves, so that the water bodies can be classified according to the shapes of the spectral curves, which are different in characteristics, i.e., the shapes of the spectral curves. And classifying according to the shape of the spectrum curve, and basically superposing the spectrum data of the same water body type after normalization.
200, constructing a turbidity compensation model corresponding to the water body to be detected based on the water body type;
after the water body type of the water body to be detected is determined, modeling is carried out on the water body to be detected based on the water body type, and a turbidity compensation model corresponding to the water body to be detected is constructed. It should be noted that the turbidity compensation models corresponding to the water bodies of different water body types may be the same, or each type of water body may correspond to one turbidity compensation model. That is, can construct a multi-classification turbidity compensation model, carry out turbidity compensation to the water of different grade type respectively through this multi-classification turbidity compensation model, also can carry out turbidity compensation to the water of different grade type respectively through different turbidity compensation models. The constructed turbidity compensation model comprises one or more of a Mie model based on Mie scattering theory, a model based on filtering and statistical principles, and a multiple regression model, and is not limited herein.
And 300, performing turbidity compensation on the initial spectral data of the water body to be detected by using the turbidity compensation model.
And carrying out turbidity compensation on the initial spectral data of the water body to be measured by using the constructed turbidity compensation model, thereby eliminating the influence of the turbidity of the water body to be measured on the measured water quality parameters.
Specifically, step 300 may specifically include:
301, performing scattering particle size analysis on the initial spectral data by using the turbidity compensation model, and reconstructing particle size distribution of suspended particles in the water body to be detected;
step 302, estimating an absorbance value of the suspended particles caused in the range from ultraviolet to visible light based on the particle size distribution;
and 303, subtracting the absorbance value on the basis of the initial spectrum data to perform turbidity compensation on the initial spectrum data of the water body to be detected.
When the initial spectral data of the water body to be detected is subjected to turbidity compensation, the pre-trained turbidity compensation model is utilized to analyze the particle size of scattering particles in the initial spectral data, and the particle size distribution of suspended particles in the water body to be detected is reconstructed. Based on the particle size distribution, the content, the particle size and the shape of the suspended particles in the water body to be detected and the reflection performance of the surface of the water body to light and other information related to the performance of the suspended particles for scattering and absorbing light can be determined. Therefore, based on the particle size distribution, the absorbance value of the suspended particles of the water body to be measured, which is caused in the range from ultraviolet to visible light wave bands, can be estimated by utilizing the pre-trained turbidity compensation model, and the absorbance value caused by the suspended particles is subtracted on the basis of the initial spectral data, so that the turbidity compensation of the initial spectral data can be realized, and the spectral data after the turbidity compensation is obtained.
In a preferred embodiment, when the turbidity compensation model is used for analyzing the particle size of the initial spectral data of the water body to be measured, the spectrum with the wave band of 450-1000nm in the spectral data is selected for particle size analysis of the suspended particles, and the particle size distribution of the suspended particles in the water body to be measured is reconstructed. And estimating the absorbance value of suspended particles in the water body to be detected in the range from ultraviolet to visible light wave bands of 200-450nm based on the reconstructed particle size distribution, and subtracting the absorbance value of the corresponding wave band on the basis of the initial spectrum data to obtain the spectrum data of the water body to be detected after turbidity compensation. The above-mentioned wavelength range is only used for exemplary illustration, and is not limited to the turbidity compensation method provided by the embodiment of the present invention, and in practical application, the above-mentioned wavelength range can be properly adjusted according to the actual turbidity compensation requirement, so as to achieve better compensation effect.
Further, after step 300, the method may further include:
and 320, determining the water quality parameter of the water body to be detected according to the spectrum curve, and determining the water quality of the water body to be detected according to the water quality parameter.
After initial spectral data of the water body to be detected is subjected to turbidity compensation, the spectral data subjected to turbidity compensation is fitted into a spectral curve, water quality parameters of the water body to be detected are determined according to the spectral curve, the influence of turbidity of suspended particles in the water body to be detected on the spectral data is reduced, measurement errors of the water quality parameters caused by the suspended particles in the water body to be detected are eliminated, the precision of the water quality parameters is improved, and therefore accurate detection of the water quality is achieved.
In this embodiment, construct the turbidity compensation model through the water type based on the water that awaits measuring, can realize offsetting the influence of the suspended particles thing to the spectral data in the water that awaits measuring through turbidity compensation to the turbidity compensation of different grade type water, improve the measurement accuracy of water quality parameter to improve the degree of accuracy of the water quality testing result of the water that awaits measuring.
Furthermore, based on the spectrum form corresponding to the curve shape of the spectrum data, the water body types are classified, and turbidity compensation models are respectively constructed by using the spectrum data according to different forms, so that accurate turbidity compensation is performed on different types of water bodies, and the accuracy of turbidity compensation is improved.
In one embodiment, step 200 may further comprise:
step 201, acquiring training spectrum data corresponding to the water body to be detected according to the water body type, and performing turbidity compensation on the training spectrum data to generate compensation spectrum data;
step 202, obtaining a preset basic model to be trained, and performing iterative training on the basic model to be trained by using the training spectrum data and the compensation spectrum data to obtain a turbidity compensation model corresponding to the water body to be tested.
When a turbidity compensation model of the water body to be detected is established based on the water body type of the water body to be detected, training spectrum data of the water body to be detected is obtained according to the water body type of the water body to be detected, and turbidity compensation is performed based on the training spectrum data to generate compensation spectrum data. And acquiring a preset basic model to be trained, and performing iterative training on the basic model to be trained by using the acquired training spectrum data and the acquired compensation spectrum data as a training sample data set to obtain a turbidity compensation model corresponding to the water body to be tested.
The basic model to be trained is a deep learning model, such as a semantic segmentation model unet, and different types of water bodies can construct a turbidity compensation model based on the same basic model or the same basic model to be trained, and can also construct a turbidity compensation model based on different basic models to be trained. And carrying out turbidity compensation on the training spectrum data to eliminate the influence of scattering on the spectrum caused by uniform particle distribution, different particle sizes and the like, and generating compensation spectrum data. Meanwhile, the deep learning model is trained by utilizing the acquired training spectral data and the acquired compensation spectral data, the corresponding relation between turbidity and particle size distribution and the absorbance value can be established, and model construction is respectively carried out based on different water body types, so that a turbidity compensation model for carrying out turbidity compensation on different types of water bodies is obtained.
Still further, step 201 may further include:
step 2011, collecting spectral data of different turbidities of water samples of each water type to generate a spectral data set;
step 2012, acquiring spectral data corresponding to the water body to be detected from the spectral data set according to the water body type of the water body to be detected, so as to obtain training spectral data corresponding to the water body to be detected;
step 2013, performing turbidity compensation on the training spectrum data by using a preset turbidity compensation algorithm to obtain compensation spectrum data corresponding to the water body to be detected
When training spectral data are obtained, spectral data of water body samples of different water body types are collected to generate a spectral data set, and the spectral data set comprises spectral data of water body samples of different turbidities of various water bodies. And acquiring the spectral data of the water body samples with the same type and different turbidities from the spectral data set according to the water body type of the water body to be detected, and using the spectral data as training spectral data of the water body to be detected. And carrying out turbidity compensation on the training spectral data by using a preset turbidity compensation algorithm to obtain turbidity-compensated spectral data, namely compensation spectral data.
The preset turbidity compensation algorithm comprises one or more of a Mie scattering algorithm, a multivariate scattering correction algorithm (MSC), a diffusion multiplicative scattering correction algorithm (EMSC), a correction algorithm based on filtering and statistical principles and a multivariate regression algorithm. Taking a Mie scattering algorithm as an example, when carrying out turbidity compensation on training spectrum data, reconstructing the particle size distribution of particles in a water body sample based on the originally collected training spectrum data with different turbidities, estimating the absorbance value of the particles in the water body sample in a visible light wave band based on the particle size distribution, and subtracting the absorbance value on the basis of an original spectrum data point to obtain corresponding compensation spectrum data.
Further, in a training sample data set construction stage, turbidity compensation is carried out on spectral data of a water body sample by adopting a conventional turbidity compensation method to obtain compensation spectral data, the originally acquired spectral data and the compensation spectral data are simultaneously used as training samples, a basic deep learning model to be trained is trained to obtain a turbidity compensation model constructed based on a preset turbidity compensation algorithm, the turbidity compensation model can determine turbidity of the water body to be detected according to the spectral data, an optimal turbidity compensation value is determined according to a spectral curve of the water body to be detected, turbidity compensation is carried out on the spectral data of the water body to be detected based on the optimal turbidity compensation value, compared with the conventional turbidity compensation algorithm, the influence of turbidity on water quality detection can be eliminated to the greatest extent, and the accuracy of a water quality detection result is improved.
In this embodiment, through the original spectral data with the different turbidity water samples of each water type, and carry out the compensation spectral data that turbidity compensation obtained based on this original spectral data and carry out the deep learning model training as the training sample simultaneously, establish the corresponding relation between spectral data and the best turbidity compensation value, obtain turbidity compensation model, utilize the turbidity compensation model that trains, can confirm best turbidity compensation value according to the spectral data of the water that awaits measuring, thereby can eliminate the influence of turbidity to water quality testing to the at utmost, improve the degree of accuracy of water quality testing result.
The turbidity compensating apparatus provided by the present invention is described below, and the turbidity compensating apparatus described below and the turbidity compensating method described above can be referred to each other correspondingly.
Referring to fig. 2, a turbidity compensating apparatus according to an embodiment of the present invention includes:
the spectrum acquisition module 10 is used for acquiring initial spectrum data of a water body to be detected and determining the water body type of the water body to be detected according to the initial spectrum data;
the model building module 20 is used for building a turbidity compensation model corresponding to the water body to be detected based on the water body type;
and the turbidity compensation module 30 is configured to perform turbidity compensation on the initial spectral data of the water body to be detected by using the turbidity compensation model.
In one embodiment, the spectrum collection module 10 is further configured to:
carrying out normalization processing on the initial spectrum data to obtain target spectrum data;
and fitting the target spectrum data into a spectrum curve, and determining the water body type of the water body to be detected according to the shape of the spectrum curve.
In one embodiment, the model building module 20 is further configured to:
acquiring training spectrum data corresponding to the water body to be detected according to the water body type, and performing turbidity compensation on the training spectrum data to generate compensation spectrum data;
obtaining a preset basic model to be trained, performing iterative training on the basic model to be trained by using the training spectrum data and the compensation spectrum data, and obtaining a turbidity compensation model corresponding to the water body to be detected.
In one embodiment, the model building module 20 is further configured to:
collecting spectral data of different turbidities of water body samples of various water body types to generate a spectral data set;
acquiring spectral data corresponding to the water body to be detected from the spectral data set according to the water body type of the water body to be detected, and acquiring training spectral data corresponding to the water body to be detected;
and carrying out turbidity compensation on the training spectrum data by using a preset turbidity compensation algorithm to obtain compensation spectrum data corresponding to the water body to be detected.
In one embodiment, the base model to be trained is a deep learning model.
In one embodiment, the turbidity compensation module 30 is further configured to:
analyzing the particle size of scattering particles of the initial spectral data by using the turbidity compensation model, and reconstructing the particle size distribution of suspended particles in the water body to be detected;
estimating an absorbance value of the suspended particulate matter caused in a range from ultraviolet to visible light based on the particle size distribution;
and subtracting the absorbance value on the basis of the initial spectral data to perform turbidity compensation on the initial spectral data of the water body to be detected.
In one embodiment, the turbidity compensating apparatus further comprises a water quality detecting module for:
fitting the spectral data of the water body to be detected after turbidity compensation into a spectral curve;
and determining the water quality parameters of the water body to be detected according to the spectrum curve, and determining the water quality of the water body to be detected according to the water quality parameters.
Fig. 3 illustrates a physical structure diagram of an electronic device, which may include, as shown in fig. 3: a processor (processor) 310, a communication Interface (communication Interface) 320, a memory (memory) 330 and a communication bus 340, wherein the processor 310, the communication Interface 320 and the memory 330 communicate with each other via the communication bus 340. The processor 310 may invoke logic instructions in the memory 330 to perform a turbidity compensation method comprising:
acquiring initial spectrum data of a water body to be detected, and determining the water body type of the water body to be detected according to the initial spectrum data;
constructing a turbidity compensation model corresponding to the water body to be detected based on the water body type;
and carrying out turbidity compensation on the initial spectral data of the water body to be detected by using the turbidity compensation model.
In addition, the logic instructions in the memory 330 may be implemented in the form of software functional units and stored in a computer readable storage medium when the software functional units are sold or used as independent products. Based on such understanding, the technical solution of the present invention may be embodied in the form of a software product, which is stored in a storage medium and includes instructions for causing a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the steps of the method according to the embodiments of the present invention. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk or an optical disk, and other various media capable of storing program codes.
In another aspect, the present invention also provides a computer program product, the computer program product comprising a computer program, the computer program being storable on a non-transitory computer-readable storage medium, the computer program, when executed by a processor, being capable of executing the turbidity compensation method provided by the above methods, the method comprising:
acquiring initial spectrum data of a water body to be detected, and determining the water body type of the water body to be detected according to the initial spectrum data;
constructing a turbidity compensation model corresponding to the water body to be detected based on the water body type;
and carrying out turbidity compensation on the initial spectral data of the water body to be detected by using the turbidity compensation model.
In yet another aspect, the present invention also provides a non-transitory computer readable storage medium having stored thereon a computer program which, when executed by a processor, implements a method for performing turbidity compensation provided by the above methods, the method comprising:
acquiring initial spectrum data of a water body to be detected, and determining the water body type of the water body to be detected according to the initial spectrum data;
constructing a turbidity compensation model corresponding to the water body to be detected based on the water body type;
and carrying out turbidity compensation on the initial spectral data of the water body to be detected by using the turbidity compensation model.
The above-described embodiments of the apparatus are merely illustrative, and the units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of the present embodiment. One of ordinary skill in the art can understand and implement it without inventive effort.
Through the above description of the embodiments, those skilled in the art will clearly understand that each embodiment can be implemented by software plus a necessary general hardware platform, and certainly can also be implemented by hardware. With this understanding in mind, the above-described technical solutions may be embodied in the form of a software product, which can be stored in a computer-readable storage medium such as ROM/RAM, magnetic disk, optical disk, etc., and includes instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to execute the methods described in the embodiments or some parts of the embodiments.
Finally, it should be noted that: the above examples are only intended to illustrate the technical solution of the present invention, but not to limit it; although the present invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; and such modifications or substitutions do not depart from the spirit and scope of the corresponding technical solutions of the embodiments of the present invention.
Claims (10)
1. A method of turbidity compensation, comprising the steps of:
acquiring initial spectrum data of a water body to be detected, and determining the water body type of the water body to be detected according to the initial spectrum data;
constructing a turbidity compensation model corresponding to the water body to be detected based on the water body type;
and carrying out turbidity compensation on the initial spectral data of the water body to be detected by using the turbidity compensation model.
2. The turbidity compensation method according to claim 1, wherein the step of constructing the turbidity compensation model corresponding to the water body to be measured based on the water body type comprises:
acquiring training spectrum data corresponding to the water body to be detected according to the water body type, and performing turbidity compensation on the training spectrum data to generate compensation spectrum data;
and acquiring a preset basic model to be trained, and performing iterative training on the basic model to be trained by using the training spectrum data and the compensation spectrum data to obtain a turbidity compensation model corresponding to the water body to be tested.
3. The turbidity compensation method according to claim 2, wherein the step of obtaining training spectral data corresponding to the water body to be measured according to the water body type, performing turbidity compensation on the training spectral data, and generating compensated spectral data comprises:
collecting spectral data of different turbidities of water body samples of various water body types to generate a spectral data set;
acquiring spectral data corresponding to the water body to be detected from the spectral data set according to the water body type of the water body to be detected, and acquiring training spectral data corresponding to the water body to be detected;
and carrying out turbidity compensation on the training spectrum data by using a preset turbidity compensation algorithm to obtain compensation spectrum data corresponding to the water body to be detected.
4. A turbidity compensation method according to claim 2, wherein said basic model to be trained is a deep learning model.
5. A turbidity compensation method according to claim 1, wherein said step of determining the water type of said water body to be measured from said initial spectral data comprises:
normalizing the initial spectrum data to obtain target spectrum data;
and fitting the target spectrum data into a spectrum curve, and determining the water body type of the water body to be detected according to the shape of the spectrum curve.
6. The method of turbidity compensation according to claim 1, wherein said step of turbidity compensating said initial spectral data using said turbidity compensation model comprises:
performing scattering particle size analysis on the initial spectral data by using the turbidity compensation model, and reconstructing the particle size distribution of suspended particles in the water body to be detected;
estimating an absorbance value of the suspended particulate matter caused in a range from ultraviolet to visible light based on the particle size distribution;
and subtracting the absorbance value on the basis of the initial spectrum data to perform turbidity compensation on the initial spectrum data of the water body to be detected.
7. The turbidity compensation method according to claim 1, wherein after the step of performing turbidity compensation on the initial spectral data of the water body to be measured by using the turbidity compensation model, the method further comprises:
fitting the spectral data of the water body to be detected after turbidity compensation into a spectral curve;
and determining the water quality parameters of the water body to be detected according to the spectrum curve, and determining the water quality of the water body to be detected according to the water quality parameters.
8. A turbidity compensating apparatus, comprising:
the spectrum acquisition module is used for acquiring initial spectrum data of the water body to be detected and determining the water body type of the water body to be detected according to the initial spectrum data;
the model construction module is used for constructing a turbidity compensation model corresponding to the water body to be detected based on the water body type;
and the turbidity compensation module is used for performing turbidity compensation on the initial spectral data of the water body to be detected by using the turbidity compensation model.
9. An electronic device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, wherein the processor, when executing the program, implements the turbidity compensation method according to any of claims 1 to 7.
10. A non-transitory computer-readable storage medium, on which a computer program is stored, wherein the computer program, when executed by a processor, implements the turbidity compensation method according to any one of claims 1 to 7.
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