A water quality detection method, system, device and storage medium

Abstract

The present invention relates to the technical field of water quality detection, and discloses a water quality detection method, system, device and storage medium. The present invention can provide a wider absorption spectrum and cover the range of water quality multi-parameter characteristic regions through a wide-spectrum pulsed xenon lamp emitting light source, and can fully reflect the water quality spectral characteristics. At the same time, the wide-spectrum pulsed xenon lamp emitting light source has high repeatability, which solves the problem of unstable water quality spectral characteristics in existing water quality detection methods. Furthermore, through a turbidity compensation algorithm based on a multi-segment absorption spectrum, the true water quality absorption spectrum of the water body to be detected can be obtained. Furthermore, the water quality of the water body to be detected is detected in combination with a multi-water quality parameter detection model, which solves the problem that the existing water quality detection method can only detect a single water quality parameter, and improves the accuracy of water quality detection.

Description

Technical Field

[0001] The present invention relates to the technical field of water quality detection, and in particular to a water quality detection method, system, device and storage medium. Background Art

[0002] Water quality testing is an important way to understand the quality of water and an important measure to monitor the safety of water sources. Its importance can be summarized into the following aspects: (1) Quantifying the degree of water pollution. Water quality testing can determine whether the water contains harmful substances and microorganisms, find out the degree of pollution of the water source, and determine the different causes and sources of pollution; (2) Ensure the safety of the ecological environment. Water quality testing can check the environmental conditions around the water source, ensure the safety of the ecological environment and prevent environmental pollution and disasters caused by over-exploitation or human activities; (3) Rational use of water resources. Water quality testing can check the water quality of the water source, which is conducive to selecting a suitable water source, improving the utilization efficiency of water resources, and ensuring the standardized and rational use of water resources; (4) Ensure the quality of water used in production and life. Water quality testing can detect the quality of industrial and agricultural water, and can promptly detect harmful substances in the water to ensure the quality and safety of water used in production and life.

[0003] At present, the detection methods for multi-parameter indicators of water quality in surface water, domestic sewage and other water bodies, such as chemical oxygen demand (COD), total phosphorus (TP) and total nitrogen (TN), are mainly divided into chemical methods, biological methods and physical methods. (1) Traditional water quality detection mainly relies on chemical analysis methods. This method has stable effects, but the required chemical reagents are polluted, the chemical digestion experimental process is relatively complicated, the cost is high and it takes a long time, so it cannot be widely used. (2) Biological detection technology mainly refers to the analysis and detection of pollutants or their metabolites in water bodies through biological materials or bioactive agents. However, biological detection technology faces problems such as difficulty in selecting microorganisms, complex operations and lack of standardization of detection methods. (3) Physical methods are mainly based on the absorption spectroscopy method of the Beer-Lambert law. It has the advantages of rapid detection, low cost, no pollution, high stability and simultaneous detection of multiple parameters, and has become one of the important means of water quality detection.

[0004] However, there are still some problems with water quality detection methods based on absorption spectroscopy: (1) It is difficult to obtain real water quality parameter information due to interference from signals such as turbidity and suspended matter in the water; (2) The composition of the water body is complex, and the use of a single absorption wavelength or a small range of bands cannot fully reflect the spectral characteristics of water quality to a large extent; (3) There are wavelength differences in the absorption peaks corresponding to different water quality parameters. At the same time, the water quality content of some application scenarios such as reservoirs and sewage treatment plants varies greatly. These all put forward better requirements for light sources, spectrometers, optical path system design, higher water quality detection range accuracy, better sensitivity, and higher detection band range; (4) Commonly used spectral water quality detection equipment can only detect a single water quality parameter, and multi-parameter detection requires multiple sets of equipment to be used simultaneously. Summary of the invention

[0005] In view of this, the present invention provides a water quality detection method, system, device and storage medium to solve the problem that the existing water quality detection method can only detect a single water quality parameter and the water quality spectral characteristics are unstable.

[0006] In a first aspect, the present invention provides a water quality detection method for a control system, wherein the control system is connected to a hardware optical system, wherein the hardware optical system includes a wide spectrum pulsed xenon lamp; the method includes:

[0007] After the wide-spectrum pulsed xenon lamp emits light, the initial reference transmission signal collected by the hardware optical path system and the initial transmission signal of the water body to be detected are obtained; the initial reference transmission signal and the initial transmission signal are processed respectively to obtain the initial water body absorption spectrum of the water body to be detected; based on the initial water body absorption spectrum, a preprocessing method and a turbidity compensation algorithm based on a multi-segment absorption spectrum are processed to obtain a target water quality absorption spectrum of the water body to be detected; based on the target water quality absorption spectrum, a multi-water quality parameter detection model is used to process to obtain the water quality detection result of the water body to be detected.

[0008] The water quality detection method provided by the present invention can provide a wider absorption spectrum and cover the range of water quality multi-parameter characteristic regions through a wide-spectrum pulsed xenon lamp emitting light source, and can fully reflect the water quality spectral characteristics. At the same time, the wide-spectrum pulsed xenon lamp emitting light source has high repeatability, which solves the problem of unstable water quality spectral characteristics in existing water quality detection methods. Furthermore, through a turbidity compensation algorithm based on a multi-segment absorption spectrum, the true water quality absorption spectrum of the water body to be detected can be obtained. Furthermore, the water quality of the water body to be detected is detected in combination with a multi-water quality parameter detection model, which solves the problem that the existing water quality detection method can only detect a single water quality parameter, and improves the accuracy of water quality detection.

[0009] In an optional implementation, the initial reference transmission signal and the initial transmission signal are processed respectively to obtain an initial water body absorption spectrum of the water body to be detected, including:

[0010] The initial reference transmission signal and the initial transmission signal are processed respectively to obtain a target reference transmission signal and a target transmission signal; based on the target reference transmission signal and the target transmission signal, the initial water absorption spectrum of the water body to be detected is obtained by calculation according to the Lambert-Beer law.

[0011] In an optional embodiment, based on the initial water body absorption spectrum, a target water quality absorption spectrum of the water body to be tested is obtained through a preprocessing method and a turbidity compensation algorithm based on a multi-segment absorption spectrum, including:

[0012] The initial water absorption spectrum is processed by a preprocessing method to obtain a target water absorption spectrum of the water body to be detected; the target water absorption spectrum is processed by a turbidity compensation algorithm based on a multi-segment absorption spectrum to obtain a target water quality absorption spectrum of the water body to be detected.

[0013] The present invention can evaluate the authenticity and quality of the initial water body absorption spectrum and the retrograde through the preprocessing method to obtain the final target water body absorption spectrum. Furthermore, through the turbidity compensation algorithm based on the multi-segment absorption spectrum, the real water quality absorption spectrum of the water body to be tested can be obtained, which provides support for the subsequent improvement of the accuracy of water quality detection.

[0014] In an optional embodiment, the absorption spectrum of the target water body is processed by a turbidity compensation algorithm based on a multi-segment absorption spectrum to obtain a target water quality absorption spectrum of the water body to be tested, including:

[0015] Obtain a priori turbidity compensation model and a reference water body absorption spectrum; construct a turbidity prior absorption spectrum library based on the target water body absorption spectrum and the prior turbidity compensation model; determine the target water quality absorption spectrum of the water body to be tested based on the turbidity prior absorption spectrum library, the reference water body absorption spectrum and the target water body absorption spectrum.

[0016] In an optional embodiment, based on the absorption spectrum of the target water body and the prior turbidity compensation model, a turbidity prior absorption spectrum library is constructed, including:

[0017] Based on the absorption spectrum of the target water body, the characteristic law of the turbidity absorption spectrum at different wavelengths is determined; based on the characteristic law, the prior turbidity compensation model is calculated to obtain multiple turbidity prior absorption spectra; based on the multiple turbidity prior absorption spectra, a turbidity prior absorption spectrum library is constructed.

[0018] In an optional embodiment, based on the turbidity prior absorption spectrum library, the reference water body absorption spectrum and the target water body absorption spectrum, determining the target water quality absorption spectrum of the water body to be tested includes:

[0019] Based on the turbidity prior absorption spectrum library, the reference water body absorption spectrum and the target water body absorption spectrum, a first reference water quality absorption spectrum is obtained through a preset calculation method; a polynomial fitting curve is established based on the reference water body absorption spectrum, and a second reference water quality absorption spectrum is determined based on the polynomial fitting curve; based on the first reference water quality absorption spectrum and the second reference water quality absorption spectrum, a target water quality absorption spectrum of the water body to be tested is determined.

[0020] In an optional embodiment, before obtaining the water quality detection result of the water body to be detected based on the target water quality absorption spectrum and processed by the multi-water quality parameter detection model, the method further includes:

[0021] An initial water quality detection model is obtained; the initial water quality detection model is improved to obtain a multi-water quality parameter detection model.

[0022] The present invention obtains a multi-water quality parameter detection model by improving the initial water quality detection model, which can improve the robustness and generalization ability of the model.

[0023] In an optional implementation, the initial water quality detection model is improved to obtain a multi-water quality parameter detection model, including:

[0024] An initial autoencoder network of an initial water quality detection model is obtained; the initial autoencoder network is improved to obtain a target autoencoder network; and a multi-water quality parameter detection model is determined based on the target autoencoder network and the initial water quality detection model.

[0025] In an optional implementation, based on the target water quality absorption spectrum, after being processed by a multi-water quality parameter detection model, a water quality detection result of the water body to be detected is obtained, including:

[0026] The target water quality absorption spectrum is processed by a multi-water quality parameter detection model to obtain multiple weight information corresponding to the target water quality absorption spectrum; based on the target water quality absorption spectrum and the multiple weight information, multiple water quality parameters of the water body to be detected are calculated; based on the multiple water quality parameters, the water quality detection result of the water body to be detected is determined.

[0027] The present invention can directly calculate multiple water quality parameters of the water body to be detected through the obtained target water quality absorption spectrum and multiple weight information, and can effectively solve the problem of adaptive adjustment of weights as the spectral characteristics of the water sample change.

[0028] In a second aspect, the present invention provides a water quality detection system, including: a hardware optical path system and a control system, the hardware optical path system including a wide spectrum pulsed xenon lamp;

[0029] The hardware optical path system is used to collect the initial reference transmission signal and the initial transmission signal of the water body to be detected after the wide-spectrum pulsed xenon lamp emits the light source, and send the initial reference transmission signal and the initial transmission signal to the control system; the control system is used to obtain the water quality detection result of the water body to be detected based on the initial reference transmission signal and the initial transmission signal through the water quality detection method of the first aspect or any corresponding embodiment thereof.

[0030] The water quality detection system provided by the present invention can provide a wider absorption spectrum and cover the range of water quality multi-parameter characteristic regions through a wide-spectrum pulsed xenon lamp emitting light source, and can fully reflect the spectral characteristics of water quality. At the same time, the wide-spectrum pulsed xenon lamp emitting light source has high repeatability, which solves the problem that the existing water quality detection method can only detect a single water quality parameter. Furthermore, through the water quality detection method processing of the first aspect of the present invention or any corresponding embodiment thereof, the accuracy of the water quality detection results of the water body to be detected is improved.

[0031] In an optional embodiment, the hardware optical path system also includes: a first convex lens, a second convex lens and a spectrometer, the first convex lens and the second convex lens are respectively arranged on the left and right sides of the target water pool; a wide-spectrum pulse xenon lamp, which is used to emit a first light source when deionized water is injected into the target water pool, so that the first light source forms an initial reference transmission signal after passing through the first convex lens, the target water pool and the second convex lens respectively; the wide-spectrum pulse xenon lamp is also used to emit a second light source when the target water pool is injected with water to be detected, so that the second light source forms an initial transmission signal after passing through the first convex lens, the target water pool and the second convex lens respectively; the spectrometer is used to receive the initial reference transmission signal and the initial transmission signal, and send the initial reference transmission signal and the initial transmission signal to the control system.

[0032] In a third aspect, the present invention provides a water quality detection device for a control system, wherein the control system is connected to a hardware optical system, wherein the hardware optical system includes a wide spectrum pulsed xenon lamp; the device includes:

[0033] The first acquisition module is used to acquire the initial reference transmission signal collected by the hardware optical path system and the initial transmission signal of the water body to be detected after the wide-spectrum pulsed xenon lamp emits the light source; the first processing module is used to process the initial reference transmission signal and the initial transmission signal respectively to obtain the initial water body absorption spectrum of the water body to be detected; the second processing module is used to obtain the target water quality absorption spectrum of the water body to be detected based on the initial water body absorption spectrum through a preprocessing method and a turbidity compensation algorithm based on a multi-segment absorption spectrum; the third processing module is used to obtain the water quality detection result of the water body to be detected based on the target water quality absorption spectrum through a multi-water quality parameter detection model.

[0034] In an optional embodiment, the first processing module includes:

[0035] The first processing submodule is used to perform signal processing on the initial reference transmission signal and the initial transmission signal respectively to obtain the target reference transmission signal and the target transmission signal; the first calculation submodule is used to calculate the initial water body absorption spectrum of the water body to be detected based on the target reference transmission signal and the target transmission signal through the Lambert-Beer law.

[0036] In an optional embodiment, the second processing module includes:

[0037] The second processing submodule is used to process the initial water body absorption spectrum through a preprocessing method to obtain a target water body absorption spectrum of the water body to be detected; the third processing submodule is used to process the target water body absorption spectrum through a turbidity compensation algorithm based on a multi-segment absorption spectrum to obtain a target water quality absorption spectrum of the water body to be detected.

[0038] In a fourth aspect, the present invention provides a computer-readable storage medium having computer instructions stored thereon, the computer instructions being used to enable a computer to execute the water quality detection method of the first aspect or any corresponding embodiment thereof.

[0039] In a fifth aspect, the present invention provides a computer device, comprising: a memory and a processor, the memory and the processor being communicatively connected to each other, the memory storing computer instructions, and the processor executing the water quality detection method of the first aspect or any corresponding embodiment thereof by executing the computer instructions. BRIEF DESCRIPTION OF THE DRAWINGS

[0040] In order to more clearly illustrate the specific implementation methods of the present invention or the technical solutions in the prior art, the drawings required for use in the specific implementation methods or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are some implementation methods of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0041] Figure 1 is a structural block diagram of a water quality detection system according to an embodiment of the present invention;

[0042] Figure 2 is a schematic flow chart of a water quality detection method according to an embodiment of the present invention;

[0043] Figure 3 is a schematic flow chart of another water quality detection method according to an embodiment of the present invention;

[0044] Figure 4 is a flow chart of another water quality detection method according to an embodiment of the present invention;

[0045] Figure 5is a schematic diagram of the network structure of an initial water quality detection model according to an embodiment of the present invention;

[0046] Figure 6 is a schematic diagram of a network structure of a multi-water quality parameter detection model according to an embodiment of the present invention;

[0047] Figure 7 is a schematic structural diagram of a water quality multi-parameter detection device based on a wide absorption spectrum according to an embodiment of the present invention;

[0048] Figure 8 is a schematic diagram of a water quality detection process of a water quality multi-parameter detection device based on a wide absorption spectrum according to an embodiment of the present invention;

[0049] Fig. 9 is a structural block diagram of a water quality detection device according to an embodiment of the present invention;

[0050] Fig.10 It is a schematic diagram of the hardware structure of a computer device according to an embodiment of the present invention. DETAILED DESCRIPTION

[0051] In order to make the purpose, technical solution and advantages of the embodiments of the present invention clearer, the technical solution in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative work are within the scope of protection of the present invention.

[0052] The embodiment of the present invention provides a water quality detection method, which performs detection by emitting a light source through a wide-spectrum pulsed xenon lamp and combining a turbidity compensation algorithm based on a multi-segment absorption spectrum and a multi-water quality parameter detection model, thereby solving the problem that the existing water quality detection method can only detect a single water quality parameter and improving the accuracy of water quality detection.

[0053] According to an embodiment of the present invention, a water quality detection method embodiment is provided. It should be noted that the steps shown in the flowchart of the accompanying drawings can be executed in a computer system such as a set of computer executable instructions, and although a logical order is shown in the flowchart, in some cases, the steps shown or described can be executed in an order different from that shown here.

[0054] In this embodiment, a water quality detection method is provided, which can be used in a control system, such as Figure 1 As shown, the control system 12 is connected to the hardware optical system 11 . Further, the hardware optical system 11 includes a wide spectrum pulse xenon lamp 111 .

[0055] Figure 2is a flow chart of a water quality detection method according to an embodiment of the present invention. Figure 2 As shown, the process includes the following steps:

[0056] Step S201, after the wide spectrum pulse xenon lamp emits light, an initial reference transmission signal collected by the hardware optical path system and an initial transmission signal of the water body to be detected are obtained.

[0057] Among them, pulse xenon lamp refers to a xenon lamp that uses stored electrical energy or chemical energy to produce high-intensity flash in a very short time. Its working principle is to control the brightness of the light by controlling the width of the pulse signal.

[0058] Specifically, the wide-spectrum pulsed xenon lamp emission light source used in this embodiment can provide a wider absorption spectrum and cover the range of water quality multi-parameter characteristic regions, thereby being able to fully reflect the spectral characteristics of water quality.

[0059] Furthermore, after the wide spectrum pulse xenon lamp 111 emits light, the hardware optical system 11 can collect the corresponding initial reference transmission signal and the initial transmission signal of the water body to be detected, and send the collected reference transmission signal and initial transmission signal to the corresponding control system 12.

[0060] Among them, the initial reference transmission signal is the transmission signal after the wide-spectrum pulsed xenon lamp emits light into the pool filled with deionized water; the initial transmission signal is the transmission signal after the wide-spectrum pulsed xenon lamp emits light into the pool filled with water to be tested.

[0061] Step S202 , processing the initial reference transmission signal and the initial transmission signal respectively to obtain an initial water body absorption spectrum of the water body to be detected.

[0062] Specifically, in the control system 12, by processing the collected initial reference transmission signal and the initial transmission signal, the real water body absorption spectrum of the water body to be detected, that is, the initial water body absorption spectrum, can be obtained.

[0063] Step S203, based on the initial water body absorption spectrum, a target water quality absorption spectrum of the water body to be detected is obtained through a preprocessing method and a turbidity compensation algorithm based on a multi-segment absorption spectrum.

[0064] Specifically, the initial water absorption spectrum is preprocessed by a preprocessing method, and further, combined with a turbidity compensation algorithm based on a multi-segment absorption spectrum, the real water quality absorption spectrum of the water body to be detected, that is, the target water quality absorption spectrum, can be obtained.

[0065] Step S204, based on the target water quality absorption spectrum, the water quality detection result of the water body to be detected is obtained through processing by a multi-water quality parameter detection model.

[0066] Specifically, after obtaining the real water quality absorption spectrum of the water body to be detected, the water quality detection result of the water body to be detected can be obtained by processing it through a multi-water quality parameter detection model.

[0067] The water quality detection method provided in this embodiment can provide a wider absorption spectrum and cover the range of water quality multi-parameter characteristic regions through a wide-spectrum pulsed xenon lamp emission light source, and can fully reflect the water quality spectral characteristics. At the same time, the wide-spectrum pulsed xenon lamp emission light source has high repeatability, which solves the problem of unstable water quality spectral characteristics in existing water quality detection methods. Furthermore, through a turbidity compensation algorithm based on a multi-segment absorption spectrum, the true water quality absorption spectrum of the water body to be detected can be obtained. Furthermore, the water quality of the water body to be detected is detected in combination with a multi-water quality parameter detection model, which solves the problem that the existing water quality detection method can only detect a single water quality parameter, and improves the accuracy of water quality detection.

[0068] In this embodiment, a water quality detection method is provided, which can be used in the above-mentioned control system 12 . The control system 12 is connected to the hardware optical system 11 . Further, the hardware optical system 11 includes a wide-spectrum pulsed xenon lamp 111 . Figure 3 is a flow chart of a water quality detection method according to an embodiment of the present invention. Figure 3 As shown, the process includes the following steps:

[0069] Step S301, after the wide spectrum pulse xenon lamp emits light, the initial reference transmission signal collected by the hardware optical system and the initial transmission signal of the water body to be detected are obtained. Figure 2 Step S201 of the illustrated embodiment will not be described in detail here.

[0070] Step S302: Process the initial reference transmission signal and the initial transmission signal respectively to obtain an initial water body absorption spectrum of the water body to be detected.

[0071] Specifically, the above step S302 includes:

[0072] Step S3021, performing signal processing on the initial reference transmission signal and the initial transmission signal respectively to obtain a target reference transmission signal and a target transmission signal.

[0073] Specifically, the initial reference transmission signal acquired by the hardware optical path system 11 and the initial transmission signal of the water body to be detected are preprocessed to obtain corresponding target reference transmission signals and target transmission signals.

[0074] Step S3022: Based on the target reference transmission signal and the target transmission signal, the initial water body absorption spectrum of the water body to be detected is obtained by calculation according to the Beer-Lambert law.

[0075] Among them, Lambert-Beer law represents the basic law of spectrophotometry, which describes the relationship between the strength of a substance's absorption of light of a certain wavelength and the concentration of the absorbing substance and the thickness of its liquid layer.

[0076] Specifically, using the Lambert-Beer law, the initial water absorption spectrum of the water body to be detected can be calculated, as shown in the following equation (1):

[0077]

[0078] Where: A represents absorbance; I o I represents the reference background, i.e. the target reference transmission signal; t represents the target transmission signal; T represents the projection ratio; K represents the absorption coefficient; l represents the thickness of the absorbing medium; and c represents the concentration of the absorbing substance.

[0079] Furthermore, the corresponding initial water absorption spectrum can be determined by the calculated absorbance.

[0080] Step S303, based on the initial water body absorption spectrum, a target water quality absorption spectrum of the water body to be detected is obtained through a preprocessing method and a turbidity compensation algorithm based on a multi-segment absorption spectrum.

[0081] Specifically, the above step S303 includes:

[0082] Step S3031, the initial water body absorption spectrum is processed by a preprocessing method to obtain a target water body absorption spectrum of the water body to be detected.

[0083] Specifically, the authenticity evaluation and quality control of the initial water absorption spectrum of the water body to be detected are performed through a preprocessing method.

[0084] First, start the light source preheating to ensure that the optical power fluctuation amplitude is less than 1% before the water sample spectrum signal (initial reference transmission signal and initial transmission signal) can be collected; select the most suitable DC background noise filtering algorithm to reduce the noise of the hardware optical path system. During the test, collect the light intensity signal collected when the light source passes through the cavity and injects deionized water from time to time. Compare with the factory setting parameters to determine and correct the zero drift and other problems in the instrument. Select a variety of filtering algorithms to reduce noise in the signal reception, absorption spectrum calculation and other processes, and use the multi-source spectrum preprocessing comprehensive evaluation method to evaluate the authenticity and quality of the calculated absorption spectrum.

[0085] Step S3032, the absorption spectrum of the target water body is processed by a turbidity compensation algorithm based on multiple absorption spectra to obtain a target water quality absorption spectrum of the water body to be detected.

[0086] The change in water absorption intensity caused by impurities such as turbidity and suspended solids can account for more than 50% of the total intensity, which is the main factor affecting the extraction of real water quality information. Generally, large particles and impurities insoluble in water can be solved by physical methods such as static sedimentation and filter screens. For tiny particles (radius less than millimeters) or impurities soluble in water, turbidity compensation processing is required.

[0087] In some optional implementations, the above step S3032 includes:

[0088] Step a1, obtaining a priori turbidity compensation model and reference water absorption spectrum.

[0089] Step a2: constructing a turbidity prior absorption spectrum library based on the target water body absorption spectrum and the prior turbidity compensation model.

[0090] Step a3, determining the target water quality absorption spectrum of the water body to be tested based on the turbidity prior absorption spectrum library, the reference water body absorption spectrum and the target water body absorption spectrum.

[0091] The reference water absorption spectrum represents the absorption spectrum lines after 350nm selected in the real water detection.

[0092] Furthermore, the a priori turbidity compensation model mainly includes:

[0093] (1) The Mie scattering model is a physical model used to describe the scattering phenomenon of light by particulate matter. In the Mie scattering model, particulate matter is regarded as a scattering center of electromagnetic waves. After light interacts with particulate matter, it is scattered, and the intensity of the scattered light can be calculated.

[0094] Specifically, in the Mie scattering model, in order to obtain the particle size distribution function of multiple discrete systems of particulate matter, a multi-discrete particle system integral model based on a single particle size distribution can be established under the assumption of spherical approximation and uncorrelated monodispersity. For small particles, the volume frequency particle size distribution function can be used to represent the distribution of polydisperse particle matter, as shown in the following relationship (2).

[0095]

[0096] in, represents the extinction coefficient, and its result is related to m, D and λ; m represents the relative complex refractive index of the particles; D represents the particle size; and λ represents the wavelength.

[0097] Furthermore, based on the particle size distribution mapping model, the corresponding relationship between the extinction spectrum E and the particle size distribution F is established, as shown in the following equation (3):

[0098] E=TF (3)

[0099] Wherein, E represents the extinction spectrum of polydisperse particles; F represents the particle size distribution of particles; and T represents the particle size distribution mapping matrix.

[0100] Specifically, the particle size distribution function when a single particle exists is as shown in the following equation (4):

[0101]

[0102] Furthermore, the particle size distribution function matrix when there are multiple particles is shown in the following equation (5):

[0103] F=[f v (D1),f v (D2),...,f v (D j )] T (5)

[0104] (2) Spectral correlation analysis. The empirical model first measures the turbidity (N) and absorbance spectra (A) of all water samples, and then analyzes the two water samples (A) corresponding to the maximum and minimum turbidity values. max and A min ) for filtration. The absorbances of the two water samples after filtration correspond to and The turbidity of the two water samples is N max and N min . Based on the premise that there is no turbidity influence on the filtered water sample, the changes in absorbance caused by turbidity of the two water samples are ( and ). Further, on this basis, the linear fitting result of the absorbance spectrum of any intermediate turbidity value is calculated. As shown in the following relation (6):

[0105]

[0106] Finally, the absorption spectrum obtained after turbidity compensation can be obtained by subtracting the turbidity absorption spectrum from the original spectrum.

[0107] In the embodiment of the present invention, a corresponding turbidity priori absorption spectrum library can be constructed using the obtained target water body absorption spectrum and the priori turbidity compensation model.

[0108] Furthermore, based on the turbidity prior absorption spectrum library, the target water quality absorption spectrum of the corresponding water body to be tested can be determined in combination with the reference water body absorption spectrum and the target water body absorption spectrum.

[0109] In some optional implementations, the above step a2 includes:

[0110] Step a21, based on the absorption spectrum of the target water body, determine the characteristic rules of the turbidity absorption spectrum at different wavelengths.

[0111] Step a22, based on the characteristic law, calculate the prior turbidity compensation model to obtain multiple turbidity prior absorption spectra.

[0112] Step a23, constructing a turbidity prior absorption spectrum library based on multiple turbidity prior absorption spectra.

[0113] Firstly, according to the obtained absorption spectrum of the target water body, the characteristic laws of the turbidity absorption spectrum at different wavelengths can be determined.

[0114] Secondly, a priori turbidity compensation model is calculated according to the characteristic law of the turbidity absorption spectrum at different wavelengths, so that multiple turbidity prior absorption spectra can be obtained.

[0115] Then, according to the calculated multiple turbidity prior absorption spectra, a corresponding turbidity prior absorption spectrum library can be constructed.

[0116] Finally, the target water quality absorption spectrum of the water body to be tested can be determined based on the obtained turbidity prior absorption spectrum library, the reference water body absorption spectrum and the target water body absorption spectrum.

[0117] In some optional implementations, the above step a3 includes:

[0118] Step a31, based on the turbidity prior absorption spectrum library, the reference water body absorption spectrum and the target water body absorption spectrum, a first reference water quality absorption spectrum is obtained through a preset calculation method.

[0119] Step a32, establishing a polynomial fitting curve based on the reference water body absorption spectrum, and determining a second reference water quality absorption spectrum based on the polynomial fitting curve.

[0120] Step a33, determining a target water quality absorption spectrum of the water body to be detected based on the first reference water quality absorption spectrum and the second reference water quality absorption spectrum.

[0121] Firstly, after selecting the absorption line after 350nm, i.e., the reference water body absorption spectrum, the similarity of the band or specific wavelength of the turbidity prior absorption spectrum and the absorption spectrum of the water sample to be tested, i.e., the target water body absorption spectrum, is calculated, and the turbidity absorption spectrum and the water quality absorption spectrum in the water body to be tested are collaboratively decoupled to obtain the corresponding first reference water quality absorption spectrum.

[0122] Then, by establishing a polynomial fitting curve for the absorption spectrum after a wavelength of 350nm, the turbidity absorption spectrum and water quality absorption spectrum before 350nm are deduced, and the corresponding second reference water quality absorption spectrum is obtained. According to experimental experience, the polynomial fitting curve can be fitted by an exponential or power function polynomial, and in special cases, the least squares model can be used for fitting.

[0123] Finally, the real water quality absorption spectrum of the water body to be detected, that is, the target water quality absorption spectrum, can be determined based on the obtained first reference water quality absorption spectrum and the second reference water quality absorption spectrum.

[0124] Among them, for a type of water, such as high-quality waters such as water sources, due to the low content of pollutants in the water, when the turbidity absorption spectrum and the water quality absorption spectrum are collaboratively decoupled, there may be a band where the water quality absorption spectrum is zero or even less than zero. The results of this band can be processed using filtering or nonlinear spectral correction algorithms.

[0125] Step S304: Based on the target water quality absorption spectrum, the water quality detection result of the water body to be detected is obtained through processing by the multi-water quality parameter detection model. Figure 2 Step S204 of the illustrated embodiment will not be described in detail here.

[0126] The water quality detection method provided in this embodiment can evaluate the authenticity and quality of the initial water absorption spectrum and the retrograde through the preprocessing method to obtain the final target water absorption spectrum. Furthermore, through the turbidity compensation algorithm based on the multi-segment absorption spectrum, the real water quality absorption spectrum of the water body to be detected can be obtained. Furthermore, the water quality of the water body to be detected is detected in combination with the multi-water quality parameter detection model, which solves the problem that the existing water quality detection method can only detect a single water quality parameter and improves the accuracy of water quality detection.

[0127] In this embodiment, a water quality detection method is provided, which can be used in the above-mentioned control system 12 . The control system 12 is connected to the hardware optical system 11 . Further, the hardware optical system 11 includes a wide-spectrum pulsed xenon lamp 111 . Figure 4 is a flow chart of a water quality detection method according to an embodiment of the present invention. Figure 4 As shown, the process includes the following steps:

[0128] Step S401, after the wide spectrum pulse xenon lamp emits light, the initial reference transmission signal collected by the hardware optical system and the initial transmission signal of the water body to be detected are obtained. Figure 2 Step S201 of the illustrated embodiment will not be described in detail here.

[0129] Step S402: Process the initial reference transmission signal and the initial transmission signal respectively to obtain the initial water absorption spectrum of the water body to be detected. Figure 3 Step S302 of the illustrated embodiment will not be described in detail here.

[0130] Step S403: Based on the initial water absorption spectrum, the target water quality absorption spectrum of the water body to be tested is obtained through a preprocessing method and a turbidity compensation algorithm based on a multi-segment absorption spectrum. Figure 3 Step S303 of the illustrated embodiment will not be described in detail here.

[0131] Step S404, obtaining an initial water quality detection model.

[0132] Specifically, traditional water quality detection models usually utilize dual-wavelength differential indices, or calculate by matching the absorption bands with the strongest correlation with different pollutants and establishing statistical regression models, or based on autoencoder networks.

[0133] Among them, the initial water quality detection model in this embodiment is a traditional water quality detection model based on an autoencoder network.

[0134] Step S405, improving the initial water quality detection model to obtain a multi-water quality parameter detection model.

[0135] Specifically, Figure 5 As shown, the initial water quality detection model uses compressed sensing technology, that is, extracting spectral feature information after fusion processing through network training, and then calculating water quality parameters using the acquired spectral features.

[0136] Furthermore, due to the limited number of water samples and the acquired features, the pre-trained models are difficult to directly apply to unknown waters or situations where the waters are changing. Not only can the autoencoder network not fully acquire the spectral fusion features of new water samples, but also, because the weight information corresponding to the spectral features comes from prior knowledge, it cannot be adaptively adjusted according to changes in the spectral features of the waters. Therefore, these models are too dependent on the water quality spectral features and empirical weight results of existing water sample data sets, and the model robustness and generalization ability are relatively weak.

[0137] Therefore, by improving the initial water quality detection model, the corresponding multi-water quality parameter detection model is obtained.

[0138] Specifically, the above step S405 includes:

[0139] Step S4051, obtaining an initial autoencoder network of an initial water quality detection model.

[0140] Specifically, according to the description of step S405 above, an initial autoencoder network in the initial water quality detection model is obtained.

[0141] Step S4052, improving the initial autoencoding network to obtain a target autoencoding network.

[0142] Among them, the improved target autoencoder network uses the basic autoencoder skeleton network to directly solve the water quality parameters by multiplying the spectral feature vector obtained by autoencoding and the original spectrum.

[0143] Step S4053, determining a multi-water quality parameter detection model based on the target autoencoder network and the initial water quality detection model.

[0144] Specifically, by improving the initial autoencoder network in the initial water quality detection model into a target autoencoder network, the corresponding multi-water quality parameter detection model can be obtained, such as Figure 6 shown.

[0145] Among them, in the process of training the multi-water quality parameter detection model, the input data is the absorption spectrum of the water sample after being processed by the turbidity compensation algorithm based on the multi-segment absorption spectrum. Through the self-encoder skeleton network training, the output result is the weight information corresponding to the absorption spectrum.

[0146] Furthermore, based on the improved target autoencoder network, the corresponding relationship between the absorption spectrum intensity and weight distribution of different water samples can be learned. At the same time, the multi-water quality parameter detection model can also fully consider the correlation between the absorption spectra of water samples, thereby further optimizing the model parameters. By verifying the feasibility and reliability of the absorption spectrum modeling principle and the detection model migration process, combined with the development advantages of artificial intelligence technology, the proposed multi-water quality parameter detection model not only has regional adaptability and high generalization ability, but also can solve the problem that small sample training models are difficult to generalize, and can accurately detect four water quality parameters: NTU, COD, TP and TN.

[0147] Step S406, based on the target water quality absorption spectrum, the water quality detection result of the water body to be detected is obtained through processing by a multi-water quality parameter detection model.

[0148] Specifically, the above step S406 includes:

[0149] Step S4061, processing the target water quality absorption spectrum through a multi-water quality parameter detection model to obtain a plurality of weight information corresponding to the target water quality absorption spectrum.

[0150] Specifically, according to the description of step S405 above, after the target water quality absorption spectrum is input into the multi-water quality parameter detection model, the spectral fusion features can be extracted from the improved multi-water quality parameter detection model in the multi-water quality parameter detection model as the weight information corresponding to the spectral fusion features, thereby effectively solving the problem of adaptive adjustment of weights as the spectral characteristics of water samples change.

[0151] Step S4062, calculating multiple water quality parameters of the water body to be detected based on the target water quality absorption spectrum and multiple weight information.

[0152] Specifically, according to the description of step S405 above, multiple water quality parameters of the water body to be detected can be calculated through vector operations between the target water quality absorption spectrum and multiple weight information.

[0153] Furthermore, since chemical oxygen demand COD, total phosphorus TP, and total nitrogen TN have unique absorption peaks and corresponding absorption spectrum response bands, different water quality parameter results can be obtained by performing the above model processing on different absorption spectrum bands.

[0154] Step S4063, determining the water quality test result of the water body to be tested based on multiple water quality parameters.

[0155] Specifically, the water quality parameters can reflect the water quality of the water body to be detected. Therefore, the water quality detection result of the water body to be detected can be determined according to the obtained multiple different water quality parameters.

[0156] The water quality detection method provided in this embodiment can directly calculate multiple water quality parameters of the water body to be detected through the obtained target water quality absorption spectrum and multiple weight information, which can effectively solve the problem of adaptive adjustment of weights as the spectral characteristics of the water sample change. Furthermore, the constructed multi-water quality parameter detection model can solve the problem that the small sample training model is difficult to generalize, and can accurately detect the four water quality parameters of NTU, COD, TP and TN.

[0157] In this embodiment, a water quality detection system is provided. Figure 1 As shown, the water quality detection system 1 includes: a hardware optical path system 11 and a control system 12.

[0158] The hardware optical path system 11 includes a wide-spectrum pulsed xenon lamp 111 , a first convex lens 112 , a second convex lens 113 and a spectrometer 114 .

[0159] The first convex lens 112 and the second convex lens 113 are respectively arranged on the left and right sides of the target pool.

[0160] Furthermore, the functions of the above system are described.

[0161] Preferably, the hardware optical system 11 is used to collect an initial reference transmission signal and an initial transmission signal of the water body to be detected after the wide spectrum pulse xenon lamp 111 emits light, and send the initial reference transmission signal and the initial transmission signal to the control system 12 .

[0162] First, deionized water is injected into the target water pool, and a wide-spectrum pulse xenon lamp 111 is used to emit a first light source, so that the emitted first light source passes through the first convex lens 112, the target water pool and the second convex lens 113 respectively to form a corresponding initial reference transmission signal.

[0163] Secondly, water to be tested is injected into the target water pool, and a wide-spectrum pulse xenon lamp 111 is used to emit a second light source, so that the emitted second light source passes through the first convex lens 112, the target water pool and the second convex lens 113 respectively, forming a corresponding initial transmission signal.

[0164] Finally, the spectrometer 114 is used to receive the formed initial reference transmission signal and the initial transmission signal, and the initial reference transmission signal and the initial transmission signal are sent to the corresponding control system 12 .

[0165] Preferably, after receiving the initial reference transmission signal and the initial transmission signal, the control system 12 processes the initial reference transmission signal and the initial transmission signal by the water quality detection method provided in the above embodiment of the present invention, and can obtain the corresponding water quality detection result of the water body to be detected.

[0166] Among them, the specific water quality detection process refers to the description of the water quality detection method provided in the above embodiment of the present invention, and will not be repeated here.

[0167] The water quality detection system provided in this embodiment can provide a wide absorption spectrum and cover the range of water quality multi-parameter characteristic regions through the wide-spectrum pulsed xenon lamp emission light source, and can fully reflect the water quality spectral characteristics. At the same time, the wide-spectrum pulsed xenon lamp emission light source has high repeatability, which solves the problem that the existing water quality detection method can only detect a single water quality parameter. Furthermore, through the water quality detection method provided by the above embodiment of the present invention, the accuracy of the water quality detection results of the water body to be detected is improved.

[0168] In one example, a water quality multi-parameter detection device based on a wide absorption spectrum is provided, such as Figure 7 As shown. The light source can be obtained by emitting a wide-spectrum pulsed xenon lamp; the algorithm modeling can include two processing processes: turbidity compensation and water quality prediction, namely, the processing processes of the turbidity compensation algorithm based on the multi-segment absorption spectrum and the multi-water quality parameter detection model in the water quality detection method provided by the above embodiment of the present invention.

[0169] Further, based on Figure 7 The water quality multi-parameter detection device based on wide absorption spectrum provides a corresponding water quality detection process, such as Figure 8 shown.

[0170] In the present embodiment, a water quality detection device is also provided, and the device is used to realize the above-mentioned embodiment and preferred implementation mode, and the description that has been made will not be repeated. As used below, the term "module" can realize the combination of software and / or hardware of predetermined functions. Although the device described in the following embodiments is preferably realized with software, the realization of hardware, or the combination of software and hardware is also possible and conceived.

[0171] This embodiment provides a water quality detection device, which can be used in the above-mentioned control system 12, the control system 12 is connected to the hardware optical system 11, and further, the hardware optical system 11 includes a wide spectrum pulse xenon lamp 111. Fig. 9As shown, the device comprises:

[0172] The first acquisition module 901 is used to acquire the initial reference transmission signal collected by the hardware optical path system and the initial transmission signal of the water body to be detected after the wide spectrum pulse xenon lamp emits light.

[0173] The first processing module 902 is used to process the initial reference transmission signal and the initial transmission signal respectively to obtain an initial water body absorption spectrum of the water body to be detected.

[0174] The second processing module 903 is used to obtain a target water quality absorption spectrum of the water body to be detected based on the initial water body absorption spectrum through a preprocessing method and a turbidity compensation algorithm based on multiple absorption spectra.

[0175] The third processing module 904 is used to obtain the water quality detection result of the water body to be detected based on the target water quality absorption spectrum through processing by a multi-water quality parameter detection model.

[0176] In some optional implementations, the first processing module 902 includes:

[0177] The first processing submodule is used to perform signal processing on the initial reference transmission signal and the initial transmission signal respectively to obtain a target reference transmission signal and a target transmission signal.

[0178] The first calculation submodule is used to obtain an initial water body absorption spectrum of the water body to be detected based on the target reference transmission signal and the target transmission signal through the Lambert-Beer law.

[0179] In some optional implementations, the second processing module 903 includes:

[0180] The second processing submodule is used to process the initial water body absorption spectrum through a preprocessing method to obtain a target water body absorption spectrum of the water body to be detected.

[0181] The third processing submodule is used to process the absorption spectrum of the target water body through a turbidity compensation algorithm based on multiple absorption spectra to obtain the target water quality absorption spectrum of the water body to be detected.

[0182] In some optional implementations, the third processing submodule includes:

[0183] The acquisition unit is used to acquire a priori turbidity compensation model and a reference water absorption spectrum.

[0184] The construction unit is used to construct a turbidity prior absorption spectrum library based on the target water body absorption spectrum and the prior turbidity compensation model.

[0185] The determination unit is used to determine the target water quality absorption spectrum of the water body to be detected based on the turbidity prior absorption spectrum library, the reference water body absorption spectrum and the target water body absorption spectrum.

[0186] In some optional embodiments, the building block includes:

[0187] The first determination subunit is used to determine the characteristic rules of the turbidity absorption spectrum at different wavelengths based on the absorption spectrum of the target water body.

[0188] The first calculation subunit is used to calculate the priori turbidity compensation model based on the characteristic law to obtain a plurality of turbidity priori absorption spectra.

[0189] A construction subunit is used to construct a turbidity prior absorption spectrum library based on multiple turbidity prior absorption spectra.

[0190] In some optional implementations, the determining unit includes:

[0191] The second calculation subunit is used to obtain a first reference water quality absorption spectrum through a preset calculation method based on a turbidity prior absorption spectrum library, a reference water body absorption spectrum and a target water body absorption spectrum.

[0192] The establishing and determining subunit is used to establish a polynomial fitting curve based on the reference water body absorption spectrum, and to determine a second reference water quality absorption spectrum based on the polynomial fitting curve.

[0193] The second determination subunit is used to determine a target water quality absorption spectrum of the water body to be detected based on the first reference water quality absorption spectrum and the second reference water quality absorption spectrum.

[0194] In some optional embodiments, the device further comprises:

[0195] The second acquisition module is used to acquire an initial water quality detection model.

[0196] The improvement module is used to improve the initial water quality detection model to obtain a multi-water quality parameter detection model.

[0197] In some optional embodiments, the improvement module includes:

[0198] The acquisition submodule is used to obtain the initial autoencoder network of the initial water quality detection model.

[0199] The improvement submodule is used to improve the initial autoencoder network to obtain the target autoencoder network.

[0200] The first determination submodule is used to determine a multi-water quality parameter detection model based on a target autoencoder network and an initial water quality detection model.

[0201] In some optional implementations, the third processing module 904 includes:

[0202] The fourth processing submodule is used to process the target water quality absorption spectrum through the multi-water quality parameter detection model to obtain multiple weight information corresponding to the target water quality absorption spectrum.

[0203] The second calculation submodule is used to calculate multiple water quality parameters of the water body to be detected based on the target water quality absorption spectrum and multiple weight information.

[0204] The second determination submodule is used to determine the water quality detection result of the water body to be detected based on multiple water quality parameters.

[0205] The further functional description of each of the above modules and units is the same as that of the above corresponding embodiments and will not be repeated here.

[0206] The water quality detection device in this embodiment is presented in the form of a functional unit, where the unit refers to an ASIC (Application Specific Integrated Circuit) circuit, a processor and memory that executes one or more software or fixed programs, and / or other devices that can provide the above functions.

[0207] The embodiment of the present invention also provides a computer device having the above Fig. 9 The water quality testing device shown.

[0208] See also Fig.10 , Fig.10 is a schematic diagram of the structure of a computer device provided by an optional embodiment of the present invention, such as Fig.10 As shown, the computer device includes: one or more processors 10, a memory 20, and interfaces for connecting various components, including high-speed interfaces and low-speed interfaces. Various components are connected to each other using different buses for communication, and can be installed on a common mainboard or installed in other ways as needed. The processor can process the instructions executed in the computer device, including instructions stored in or on the memory to display the graphical information of the GUI on an external input / output device (such as, a display device coupled to the interface). In some optional embodiments, if necessary, multiple processors and / or multiple buses can be used together with multiple memories and multiple memories. Similarly, multiple computer devices can be connected, and each device provides some necessary operations (for example, as a server array, a group of blade servers, or a multi-processor system). Fig.10 A processor 10 is taken as an example.

[0209] The processor 10 may be a central processing unit, a network processor or a combination thereof. The processor 10 may further include a hardware chip. The hardware chip may be a dedicated integrated circuit, a programmable logic device or a combination thereof. The programmable logic device may be a complex programmable logic device, a field programmable gate array, a general purpose array logic or any combination thereof.

[0210] The memory 20 stores instructions executable by at least one processor 10, so that at least one processor 10 executes the method shown in the above embodiment.

[0211] The memory 20 may include a program storage area and a data storage area, wherein the program storage area may store an operating system, an application required for at least one function; the data storage area may store data created according to the use of the computer device, etc. In addition, the memory 20 may include a high-speed random access memory, and may also include a non-transient memory, such as at least one disk storage device, a flash memory device, or other non-transient solid-state storage device. In some optional embodiments, the memory 20 may optionally include a memory remotely arranged relative to the processor 10, and these remote memories may be connected to the computer device via a network. Examples of the above-mentioned network include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and combinations thereof.

[0212] The memory 20 may include a volatile memory, such as a random access memory; the memory may also include a non-volatile memory, such as a flash memory, a hard disk or a solid state drive; the memory 20 may also include a combination of the above types of memory.

[0213] The computer device further comprises a communication interface 30 for the computer device to communicate with other devices or a communication network.

[0214] The embodiment of the present invention also provides a computer-readable storage medium. The method according to the embodiment of the present invention can be implemented in hardware, firmware, or can be implemented as a computer code that can be recorded in a storage medium, or can be implemented as a computer code that is originally stored in a remote storage medium or a non-temporary machine-readable storage medium and will be stored in a local storage medium through a network download, so that the method described herein can be stored in such software processing on a storage medium using a general-purpose computer, a dedicated processor, or programmable or dedicated hardware. Among them, the storage medium can be a magnetic disk, an optical disk, a read-only storage memory, a random access memory, a flash memory, a hard disk or a solid-state hard disk, etc.; further, the storage medium can also include a combination of the above types of memories. It can be understood that a computer, a processor, a microprocessor controller, or programmable hardware includes a storage component that can store or receive software or computer code. When the software or computer code is accessed and executed by a computer, a processor, or hardware, the method shown in the above embodiment is implemented.

[0215] Although the embodiments of the present invention have been described in conjunction with the accompanying drawings, those skilled in the art may make various modifications and variations without departing from the spirit and scope of the present invention, and such modifications and variations are all within the scope defined by the appended claims.

Claims

1. A water quality detection method, characterized in that: Used for a control system, the control system is connected to a hardware optical system, the hardware optical system includes a wide spectrum pulse xenon lamp; the method includes: After the wide-spectrum pulsed xenon lamp emits light, an initial reference transmission signal collected by the hardware optical path system and an initial transmission signal of the water body to be detected are obtained, wherein the initial reference transmission signal is a transmission signal after the wide-spectrum pulsed xenon lamp emits light to a water pool injected with deionized water, and the initial transmission signal is a transmission signal after the wide-spectrum pulsed xenon lamp emits light to a water pool injected with water body to be detected; Processing the initial reference transmission signal and the initial transmission signal respectively to obtain an initial water body absorption spectrum of the water body to be detected; Based on the initial water body absorption spectrum, a target water quality absorption spectrum of the water body to be detected is obtained through a preprocessing method and a turbidity compensation algorithm based on a multi-segment absorption spectrum; Based on the target water quality absorption spectrum, the water quality detection result of the water body to be detected is obtained through processing by a multi-water quality parameter detection model; Wherein, based on the initial water body absorption spectrum, after a preprocessing method and a turbidity compensation algorithm based on a multi-segment absorption spectrum, the target water quality absorption spectrum of the water body to be detected is obtained, including: Obtain a priori turbidity compensation model and reference water absorption spectrum; Based on the absorption spectrum of the target water body, determining the characteristic law of the turbidity absorption spectrum at different wavelengths; Based on the characteristic law, the priori turbidity compensation model is calculated to obtain a plurality of turbidity priori absorption spectra; Constructing the turbidity priori absorption spectrum library based on the multiple turbidity priori absorption spectra; Determining the target water quality absorption spectrum of the water body to be detected based on the turbidity priori absorption spectrum library, the reference water body absorption spectrum and the target water body absorption spectrum; Wherein, based on the target water quality absorption spectrum, after being processed by a multi-water quality parameter detection model, the water quality detection result of the water body to be detected is obtained, including: Processing the target water quality absorption spectrum through a multiple water quality parameter detection model to obtain multiple weight information corresponding to the target water quality absorption spectrum, wherein the multiple water quality parameter detection model adopts an improved autoencoder skeleton network; Calculating a plurality of water quality parameters of the water body to be detected based on the target water quality absorption spectrum and the plurality of weight information; Based on the multiple water quality parameters, the water quality detection result of the water body to be detected is determined.

2. The method according to claim 1, characterized in that The initial reference transmission signal and the initial transmission signal are processed respectively to obtain an initial water body absorption spectrum of the water body to be detected, including: performing signal processing on the initial reference transmission signal and the initial transmission signal respectively to obtain a target reference transmission signal and a target transmission signal; Based on the target reference transmission signal and the target transmission signal, the initial water body absorption spectrum of the water body to be detected is obtained through calculation according to Beer-Lambert law.

3. The method according to claim 1, characterized in that Based on the initial water body absorption spectrum, the target water quality absorption spectrum of the water body to be detected is obtained through a preprocessing method and a turbidity compensation algorithm based on a multi-segment absorption spectrum, including: Processing the initial water body absorption spectrum by a preprocessing method to obtain a target water body absorption spectrum of the water body to be detected; The target water body absorption spectrum is processed by a turbidity compensation algorithm based on multiple absorption spectra to obtain the target water quality absorption spectrum of the water body to be detected.

4. The method according to claim 1, characterized in that: Determining the target water quality absorption spectrum of the water body to be detected based on the turbidity priori absorption spectrum library, the reference water body absorption spectrum and the target water body absorption spectrum includes: Based on the turbidity prior absorption spectrum library, the reference water body absorption spectrum and the target water body absorption spectrum, a first reference water quality absorption spectrum is obtained through a preset calculation method; Establishing a polynomial fitting curve based on the reference water body absorption spectrum, and determining a second reference water quality absorption spectrum based on the polynomial fitting curve; The target water quality absorption spectrum of the water body to be detected is determined based on the first reference water quality absorption spectrum and the second reference water quality absorption spectrum.

5. The method according to claim 1, characterized in that Based on the target water quality absorption spectrum, before obtaining the water quality detection result of the water body to be detected through processing by a multi-water quality parameter detection model, the method further includes: Obtaining an initial water quality detection model; The initial water quality detection model is improved to obtain the multiple water quality parameter detection model.

6. The method according to claim 5, characterized in that The initial water quality detection model is improved to obtain the multi-water quality parameter detection model, including: Obtaining an initial autoencoder network of the initial water quality detection model; Improving the initial autoencoder network to obtain a target autoencoder network; Based on the target autoencoder network and the initial water quality detection model, the multiple water quality parameter detection model is determined.

7. A water quality detection system, characterized in that: include: A hardware optical system and a control system, wherein the hardware optical system comprises a wide spectrum pulsed xenon lamp; The hardware optical path system is used to collect an initial reference transmission signal and an initial transmission signal of a water body to be detected after the wide-spectrum pulse xenon lamp emits a light source, and send the initial reference transmission signal and the initial transmission signal to the control system, wherein the initial reference transmission signal is a transmission signal after the wide-spectrum pulse xenon lamp emits a light source to a water pool injected with deionized water, and the initial transmission signal is a transmission signal after the wide-spectrum pulse xenon lamp emits a light source to a water pool injected with water body to be detected; The control system is used to obtain the water quality detection result of the water body to be detected based on the initial reference transmission signal and the initial transmission signal, after being processed by the water quality detection method according to any one of claims 1 to 6.

8. The system according to claim 7, characterized in that The hardware optical path system further includes: a first convex lens, a second convex lens and a spectrometer, wherein the first convex lens and the second convex lens are respectively arranged on the left and right sides of the target pool; The wide spectrum pulse xenon lamp is used to emit a first light source when deionized water is injected into the target water pool, so that the first light source forms an initial reference transmission signal after passing through the first convex lens, the target water pool and the second convex lens respectively; The wide spectrum pulse xenon lamp is also used to emit a second light source when the target water pool is injected into the water body to be detected, so that the second light source forms an initial transmission signal after passing through the first convex lens, the target water pool and the second convex lens respectively; The spectrometer is used to receive the initial reference transmission signal and the initial transmission signal, and send the initial reference transmission signal and the initial transmission signal to the control system.

9. A water quality detection device, characterized in that: Used to perform the water quality detection method according to any one of claims 1 to 6, wherein the water quality detection method is used for a control system, wherein the control system is connected to a hardware optical system, and the hardware optical system comprises a wide spectrum pulsed xenon lamp; The device comprises: A first acquisition module is used to acquire the initial reference transmission signal collected by the hardware optical path system and the initial transmission signal of the water body to be detected after the wide spectrum pulse xenon lamp emits the light source; A first processing module is used to process the initial reference transmission signal and the initial transmission signal respectively to obtain an initial water body absorption spectrum of the water body to be detected; A second processing module is used to obtain a target water quality absorption spectrum of the water body to be detected based on the initial water body absorption spectrum through a preprocessing method and a turbidity compensation algorithm based on a multi-segment absorption spectrum; The third processing module is used to obtain the water quality detection result of the water body to be detected based on the target water quality absorption spectrum and processed by a multi-water quality parameter detection model.

10. The device according to claim 9, characterized in that The first processing module comprises: A first processing submodule, configured to perform signal processing on the initial reference transmission signal and the initial transmission signal respectively to obtain a target reference transmission signal and a target transmission signal; The first calculation submodule is used to obtain the initial water body absorption spectrum of the water body to be detected based on the target reference transmission signal and the target transmission signal through Lambert-Beer law calculation.

11. The device according to claim 9, characterized in that The second processing module comprises: The second processing submodule is used to process the initial water body absorption spectrum through a preprocessing method to obtain a target water body absorption spectrum of the water body to be detected; The third processing submodule is used to process the absorption spectrum of the target water body through a turbidity compensation algorithm based on multiple absorption spectra to obtain the target water quality absorption spectrum of the water body to be detected.

12. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores computer instructions, and the computer instructions are used to enable a computer to execute the water quality detection method according to any one of claims 1 to 6.

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