Water quality detection device and method based on water environment pollution prevention and control

Abstract

The application relates to the technical field of water quality detection, and particularly discloses a water quality detection device and method based on water environment pollution prevention and treatment. The device comprises a water quality sampling assembly, which is used for collecting stratified water quality samples at different depths of a water area to be detected; a sample processing assembly, which is connected with the water quality sampling assembly and is used for mixing the stratified water quality samples; a water quality data detection assembly, which comprises a first water quality data collector and a second water quality data collector; and a data processing assembly, which is electrically connected with the water quality data detection assembly, is used for processing stratified water quality index data and mixed water quality index data and outputting the data, and comprises a data preprocessing unit and a multidimensional data fusion unit which are connected with each other and are used for outputting standardized water quality data, and the multidimensional data fusion unit is used for fusing and processing the standardized water quality data, so that the detection precision of the water quality detection device is improved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of water quality detection, and specifically discloses a water quality detection device and method based on water environment pollution prevention. BACKGROUND

[0002] Water quality detection is the core link of water environment pollution prevention work, and its fundamental purpose is to accurately obtain the content of pollutants, the concentration of beneficial substances and other key indicators in water body, so as to provide scientific basis for water environment quality evaluation, pollution tracing, treatment scheme formulation and effect evaluation. With the acceleration of industrialization process and the intensification of human activities, water body eutrophication, heavy metal exceeding standard and organic pollutant accumulation have become increasingly prominent, which not only destroys the balance of aquatic ecological system, but also poses a serious threat to drinking water safety, agricultural irrigation and fishery production. Therefore, mastering the pollution status of water area through efficient and accurate water quality detection technology has become the prerequisite for curbing water environment deterioration and protecting water ecological safety, and is also an important support for realizing sustainable utilization of water resources.

[0003] In the current water quality detection field, the existing technology mainly realizes water quality data collection and analysis through two types of ways; one type is the mode of manual sampling combined with laboratory detection, which uses a water sampler to select representative points in the water area to be detected by the staff, collects water samples at different depths, and then brings them back to the laboratory for index determination by using chemical analysis instruments. Although this method can obtain more comprehensive index data, it has problems such as long sampling period, high labor cost and poor real-time performance. The other type is an automatic monitoring device, which is mostly fixed on the shore or a specific position in the water body, and directly collects water quality data through the sensors mounted thereon. Some devices have a layered sampling function, which can obtain samples of different water layers through sampling bottles with preset depths, and then process the layered information by mechanical mixing or simple data superposition. The data standardization mostly uses uniform threshold conversion, and the weight of each layer in the fusion process is usually a fixed value.

[0004] However, the existing water quality detection technology still has significant defects in actual application, which is difficult to meet the needs of refined pollution prevention. On the one hand, there are limitations in the sampling link: single-depth sampling devices cannot capture the water quality differences in vertical stratification of water body, resulting in one-sided data; even if the devices have a layered sampling function, the sampling depth is mostly fixed, lacking a mechanism to dynamically adapt to changes in water depth during the sampling process, which is easy to cause deviation of the actual sampling depth due to water disturbance, affecting the representativeness of water samples. On the other hand, the data processing link is insufficient: some technologies only detect mixed water samples, losing the layered original index information, which ultimately leads to deviation between the detection results and the actual water quality, affecting the accuracy of water quality detection. SUMMARY

[0005] The present application aims to provide a water quality detection device based on water environment pollution prevention to at least solve one of the above problems in the prior art.

[0006] Specifically, the present invention is achieved through the following technical solution:

[0007] A water quality testing device based on water environment pollution prevention and control, the device comprising:

[0008] Water sampling unit, used to collect stratified water samples at different depths in the water body to be tested;

[0009] The sample processing component is connected to the water quality sampling component and is used to mix stratified water quality samples.

[0010] The water quality data detection component includes a first water quality data acquisition unit and a second water quality data acquisition unit. The first water quality data acquisition unit is used to collect stratified water quality index data of stratified water samples, and the second water quality data acquisition unit is used to collect mixed water quality index data after mixing.

[0011] The data processing component, electrically connected to the water quality data detection component, is used to process and output stratified and mixed water quality index data. The data processing component includes a data preprocessing unit and a multi-dimensional data fusion unit, which are interconnected. The data preprocessing unit performs standardization preprocessing on the stratified and mixed water quality index data to output standardized water quality data.

[0012] Standardized water quality data includes standard stratified water quality data and standard mixed water quality data;

[0013] The multi-dimensional data fusion unit is used to fuse standardized water quality data to output intermediate water quality fusion data.

[0014] It should be understood that based on the above scheme, the water quality sampling assembly is arranged at the sampling link to collect stratified water quality samples at different depths of the water area to be measured, which solves the problem of fixed stratified sampling depth in the prior art and deviation caused by water disturbance, ensures the representativeness of water samples at different depths, and then the sample processing assembly is in communication with the sampling assembly to realize mixing of stratified water quality samples, and the water quality data detection assembly collects stratified water quality index data and mixed water quality index data through the first and second water quality data collectors, which not only retains the original index information of each water layer, but also obtains mixed data reflecting the overall water quality. Subsequently, the preprocessing unit of the data processing assembly standardizes and preprocesses the two types of water quality index data, and the multi-dimensional data fusion unit fuses the stratified and mixed water quality index data after standardization to output water quality fusion intermediate data, forming a complete technical process of stratified sampling-double data collection-differentiated preprocessing-multi-dimensional fusion. Then, by retaining stratified water quality index data and mixed water quality index data, using a differentiated preprocessing method to restore index characteristics, and then calculating and realizing data fusion through a multi-dimensional fusion unit, the problems of one-sided water quality data caused by single depth sampling in the prior art and deviation of water quality detection results from the true water quality condition caused by loss of stratified water quality information of mixed water samples are effectively solved. The precise capture of stratified water quality characteristics of the water area to be measured and the scientific fusion of multi-dimensional data are realized, the water quality fusion intermediate data output is closer to the true water quality condition of the water area to be measured, and the overall water quality index data of the water area to be measured is more fully reflected, which effectively improves the comprehensiveness, accuracy and reliability of water quality detection, and provides strong technical support for fine water environment pollution prevention and control decision-making.

[0015] Further, in the above technical scheme, the water quality sampling assembly comprises a vertically arranged sampling rod, a plurality of sampling bottles are equidistantly arranged outside the sampling rod, the plurality of sampling bottles and the sampling rod are slidably connected through a sliding mechanism, and one end of the sampling bottle is provided with a sampling valve.

[0016] The technical scheme is characterized in that a vertical sampling rod is arranged in the water quality sampling assembly, a plurality of sampling bottles are arranged equidistantly outside the sampling rod, and the sampling bottles and the sampling rod are connected through a sliding mechanism, and a sampling valve is arranged at one end of the sampling bottle, when the sampling valve is opened to collect water samples, the gravity of the sampling bottle increases as the water sample gradually flows in, and the sampling bottle can slide along the sampling rod under the action of the sliding mechanism to adjust the sampling depth of the sampling bottle, so that the sampling bottle can dynamically adapt to the subtle depth changes of the non-uniform distribution of pollutants, and the representative water quality samples at each depth can be accurately collected, the problem of insufficient sample representativeness caused by subtle differences in pollutant distribution when the sampling bottles are fixed at different positions for stratified sampling is solved, the accurate capture of pollution characteristics at different depths is realized, the stratified water quality samples can fully reflect the pollution conditions at each depth of the water area to be measured, a more reliable sample basis is provided for subsequent water quality index detection and data fusion, and the detection accuracy of the detection device is finally improved.

[0017] Further, the sample processing assembly includes a floating plate arranged at the upper part of the sampling rod and a processing bin arranged on the floating plate, a plurality of water sample temporary storage cavities corresponding to and communicating with the sampling bottles are arranged in the processing bin, the water sample temporary storage cavities are hollow columnar cavities and are used for temporarily storing the stratified water quality samples collected by the sampling bottles, a water sample mixing cavity is arranged at the middle position of the plurality of water sample temporary storage cavities, the water sample mixing cavity and the plurality of water sample temporary storage cavities are connected through a proportional control valve, and a stirrer is further arranged in the water sample mixing cavity.

[0018] Based on the above scheme, the plurality of water sample temporary storage cavities in the processing bin correspond to and communicate with the sampling bottles, the stratified water quality samples can be independently temporarily stored, the stratified samples are prevented from being mixed before processing, and the original characteristics of the stratified samples are ensured not to be disturbed, when the mixed water quality sample is needed, the proportional control valve is controlled to be opened, the flow of the stratified samples in each water sample temporary storage cavity into the water sample mixing cavity can be flexibly adjusted, and the mixed water quality sample is formed after uniform stirring by the stirrer, the complete retention of the stratified water quality sample data and the accurate adjustment of the mixed water quality sample are realized, the accurate detection of the stratified water quality sample index data is ensured, the mixed water quality sample index data can comprehensively reflect the characteristics of the stratified water quality samples and is uniform and stable, a reliable overall water quality detection sample is provided for subsequent water quality detection, and the comprehensiveness and data reliability of the water quality detection are finally improved through the dual data support of the stratified water quality and the mixed water quality sample.

[0019] Preferably, the first water quality data collector is arranged in the water sample temporary storage cavity, the second water quality data collector is arranged in the water sample mixing cavity, and the first water quality data collector and the second water quality data collector both adopt a multi-parameter sensor array.

[0020] The hierarchical water quality index data and the mixed water quality index data both include pollution type water quality index data and beneficial type water quality index data.

[0021] Based on the above scheme, the problems of one-sided data caused by single index detection, split hierarchical and mixed data, and undistinguished index characteristics in the prior art are solved, and finally comprehensive, accurate and clearly classified raw data are provided for the data processing component, supporting the scientificity and reliability of the water quality detection result.

[0022] It should be further explained that the pollution type water quality index data mainly includes indexes reflecting the pollution degree of water body, such as chemical oxygen demand (COD, representing the pollution degree of organic matter that can be oxidized in water body), heavy metal content (such as lead, cadmium, etc., which will harm aquatic organisms and human health), ammonia nitrogen (a key index reflecting the risk of water eutrophication), etc.

[0023] The beneficial type water quality index data covers indexes beneficial to the water ecosystem, such as dissolved oxygen (DO, a necessary condition for the survival of aquatic organisms), chlorophyll a (reflecting the photosynthetic capacity of aquatic plants, indirectly representing the productivity of water body), appropriate amount of calcium and magnesium ions (maintaining the balance of water body pH, promoting the growth of aquatic organisms), etc.

[0024] Specifically, the data processing component is arranged in the processing chamber.

[0025] Based on the above scheme, through the integrated layout of the data processing component arranged in the processing chamber, close cooperation with the sample processing and data acquisition components is realized, data transmission interference is reduced, and the compactness of the device structure is improved.

[0026] Preferably, the standardization preprocessing of the data preprocessing unit on the hierarchical water quality index data and the mixed water quality index data includes:

[0027] The outliers in the hierarchical water quality index data and the mixed water quality index data are removed;

[0028] The upper limit standardization processing is taken for the pollution type water quality index data in the hierarchical water quality index data and the mixed water quality index data;

[0029] The lower limit standardization processing is taken for the beneficial type water quality index data in the hierarchical water quality index data and the mixed water quality index data.

[0030] It should be noted that the scheme purifies the data by removing outliers to avoid the interference of extreme values on the analysis results, improves the reliability of the original data, and solves the distortion of the meaning of the indicators caused by unified standardization by retaining the inherent characteristics of the two types of indicators through classification standardization. Through the above preprocessing logic, different dimensions and different characteristics of the indicators are converted into comparable standardized data, providing a consistent basis for subsequent multi-dimensional data fusion, ensuring that the fusion results can accurately map the comprehensive situation of water quality, and ultimately improving the scientificity and reliability of water quality detection and evaluation.

[0031] Further preferably, the multi-dimensional data fusion unit is configured to perform fusion processing on the standardized water quality data, including:

[0032] Based on the actual water depth data of each layer fed back by the sampling assembly in real time, and combining the water quality index types, dynamic weights are calculated respectively;

[0033] The standard layered water quality data and the corresponding dynamic weights are weighted to obtain a layered fusion value;

[0034] The deviation compensation fusion algorithm is used to process the standard mixed water quality data and the layered fusion value to calculate a deviation coefficient;

[0035] The deviation coefficient is compared with a preset deviation coefficient threshold, and water quality fusion intermediate data is output.

[0036] It should be understood that the above scheme effectively solves the problems of fixed sampling weight, loss of layered information and insufficient data fusion accuracy in existing water quality detection technology by constructing a dynamic weight model, layered fusion calculation and deviation compensation fusion algorithm. For pollution indicators, it uses a deep sensitive weight algorithm to dynamically adjust the weight according to water depth fluctuations. For beneficial indicators, it inversely proportionally allocates the weight based on the concentration gradient difference, achieving adaptive optimization of the weight of data in different water layers, avoiding the problem of weakening of layered characteristics caused by fixed weight, and retaining the water quality difference characteristics of each depth through layered fusion value calculation. In combination with the deviation compensation fusion algorithm, the deviation coefficient of the layered fusion value and the mixed data is compared, and a threshold is set for each type of indicator, and the fusion intermediate data is output by weighted average or abnormal marking. The scheme integrates the detailed information of the layered data and the overall characteristics of the mixed data, and ensures data reliability through the abnormal marking mechanism, finally realizes the fine optimization of water quality data from layered sampling to fusion processing, significantly improves the accuracy and representativeness of water quality detection data, provides a more accurate quantitative basis for water environment quality detection, and greatly improves the detection accuracy of the detection device.

[0037] Further, the data processing assembly further comprises a data correction unit connected with the multi-dimensional data fusion unit, and an error correction model is preset in the data correction unit, which is used to correct the water quality fusion intermediate data to obtain the water quality detection data of the water area to be detected.

[0038] Based on the above technical scheme, the data correction unit corrects the water quality fusion intermediate data by the preset error correction model, effectively eliminates systematic errors and random errors caused by factors such as stratified sampling deviation, sensor drift and environmental interference, significantly improves the absolute accuracy and stability of the water quality detection data, and finally improves the accuracy of the water quality detection result of the detection device.

[0039] Further specifically, the device further comprises a detection result output assembly arranged at the top of the processing bin and connected with the data correction unit and the external terminal, which is used to output the water quality detection data to the external terminal.

[0040] Based on the above scheme, the detection result output assembly is a hardware module integrated with data transmission function, which can be realized by a wireless communication module or a standard data interface, and is used to establish a data transmission channel with the external device, which realizes automatic and instant transmission of the corrected water quality data and eliminates the time loss caused by manual export.

[0041] A water quality detection method based on water environment pollution prevention and control, according to a water quality detection device based on water environment pollution prevention and control, the method comprises:

[0042] Step 1: arrange the detection device to the water area to be detected, so that the detection bin floats on the water surface through the floating plate, and ensure that the sampling rod is inserted into the water body of the water area to be detected;

[0043] Step 2: after the sampling rod is inserted into the water body, the sampling valve of the sampling bottle is controlled to be opened, so that the water samples at different depths in the water body of the water area to be detected enter into each sampling bottle, and when the water sample enters into the sampling bottle, the sampling bottle slides along the sliding groove of the sampling rod by the sliding mechanism, and the spring between the sliding block and the sliding groove is compressed to dynamically adapt to the change of water depth, so as to complete the stratified water quality sample collection;

[0044] Step 3: close the sampling valve, control the water sample temporary storage cavity of the sample processing assembly to be connected with the sampling bottle, so that the stratified water quality samples in each sampling bottle are correspondingly transported into the water sample temporary storage cavity; the first water quality data collector detects the stratified water quality samples in the water sample temporary storage cavity to collect stratified water quality index data;

[0045] Step 4: After the layered water quality index data collection is completed, the proportional control valve is controlled to be opened, so that the layered water quality samples in the temporary storage cavities enter the water sample mixing cavity, and the mixer is stirred to form mixed water quality samples; the second water quality data collector detects the mixed water quality samples to collect mixed water quality index data;

[0046] Step 5: The layered water quality index data and the mixed water quality index data are received by the processing assembly, are preprocessed by the data preprocessing unit, are fused by the multi-dimensional data fusion unit to output water quality fusion intermediate data, the water quality fusion intermediate data are corrected by the data correction unit through an error correction model to obtain water quality detection data, and the detection result output assembly transmits the water quality detection data to a terminal outside to complete water quality detection.

[0047] Based on the above scheme, the sampling depth is adaptively adjusted, the spatial error caused by water flow disturbance is eliminated, the original layered data and the mixed comprehensive data are synchronously acquired through the parallel detection structure of the layered temporary storage cavity and the mixing cavity, the fusion weight is dynamically allocated based on the coefficient of variation, the detection result takes into account the layered characteristics and the overall distribution law, the problem that the water sample representativeness is insufficient due to the fixed sampling depth is solved, the accuracy of the water sample collection position at different depths is ensured through the dynamic adaptation mechanism, the layered and mixed dual-mode data collection avoids the information loss of a single detection mode, and the vertical pollution distribution characteristics of the water body are completely retained. The differential standardization processing eliminates the dimension difference of the data of the pollution type and the beneficial type, the dynamic weight fusion algorithm improves the collaborative analysis precision of the layered data and the mixed data, the error correction model further corrects the system deviation, and finally the reliability and adaptability of the water quality detection result in the complex water body environment are improved.

[0048] Compared with the prior art, the present application has at least the following advantages and beneficial effects:

[0049] (1) The sliding mechanism and the spring of the water quality sampling assembly are designed, so that the sampling bottle dynamically adapts to the water depth with the change of gravity, the sampling deviation problem of the fixed depth is solved, the accurate collection of the representative water sample at different depths is realized, and the reliability of the layered sample is improved.

[0050] (2) The temporary storage cavity and the mixing cavity of the sample processing assembly are in parallel structure, so that the layered original data and the mixed comprehensive data are synchronously retained, the information loss of a single detection mode is avoided, and the vertical pollution characteristics of the water body are completely captured.

[0051] (3) The dynamic weight and the deviation compensation algorithm of the multi-dimensional fusion unit are used to adaptively integrate the layered and mixed data, the abnormal marking mechanism is combined, the fine fusion of the water quality data is realized, and the water quality detection precision of the detection device is improved. BRIEF DESCRIPTION OF DRAWINGS

[0052] The drawings used herein for illustrative purposes provide further understanding of embodiments of the present application, and form a part of the present application. In the drawings:

[0053] Fig. 1 It is a whole block diagram of the device of the present application;

[0054] Fig. 2 It is a whole structure diagram of the device of the present application;

[0055] Fig. 3 It is a step diagram of the detection method of the present application.

[0056] In the above drawings, the reference signs represent: 1, sampling assembly; 11, sampling rod; 12, sampling bottle; 121, sampling valve; 131, sliding groove; 132, sliding block; 133, spring; 2, sample processing assembly; 21, processing bin; 22, water sample temporary storage cavity; 23, water sample mixing cavity; 231, stirrer; 24, proportional control valve; 25, floating plate; 3, water quality data detection assembly; 31, first water quality data collector; 32, second water quality data collector; 4, data processing assembly; 5, detection result output assembly. DETAILED DESCRIPTION

[0057] In order to make the objects, technical solutions and advantages of the present application clearer, further detailed description will be made to the present application in combination with embodiments, the illustrative embodiments and the description thereof are only used to explain the present application, and do not limit the present application, the following described embodiments are part of the embodiments of the present application, but not all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative labor belong to the scope of protection of the present application.

[0058] In the following description, a large number of specific details are set forth in order to provide a thorough understanding of the present application. However, it is apparent to those skilled in the art that the present application can be practiced without these specific details. In other embodiments, well-known structures, materials or methods are not specifically described in order to avoid obscuring the present application. The materials, instruments and reagents used in the following embodiments, etc. can be obtained from commercial channels unless otherwise specified. The technical means used in the embodiments is well known to those skilled in the art unless otherwise specified.

[0059] In addition, the terms "first", "second" are only used for descriptive purposes, and cannot be understood as indicating or implying relative importance or implicitly indicating the number of the indicated technical features. Therefore, the features limited by "first", "second" can explicitly or implicitly include one or more features. In the description of the present application, the meaning of "multiple" is two or more, unless otherwise specifically limited.

[0060] Embodiment 1:

[0061] Please see Figs. 1-2 As shown in the drawings, the embodiment discloses a water quality detection device based on water environment pollution prevention and treatment. The device comprises: a water quality sampling assembly 1, which is used for collecting stratified water quality samples at different depths of a water area to be measured; a sample processing assembly 2, which is in communication with the water quality sampling assembly 1 and is used for mixing the stratified water quality samples; a water quality data detection assembly 3, which comprises a first water quality data collector 31 and a second water quality data collector 32, the first water quality data collector 31 is used for collecting stratified water quality index data of the stratified water quality samples, and the second water quality data collector is used for collecting mixed water quality index data after mixing; a data processing assembly 4, which is electrically connected with the water quality data detection assembly 3 and is used for processing and outputting the stratified water quality index data and the mixed water quality index data, the data processing assembly 4 comprises: a data preprocessing unit and a multi-dimensional data fusion unit which are in signal connection, the data preprocessing unit is used for standardizing and preprocessing the stratified water quality index data and the mixed water quality index data to output standardized water quality data, wherein the standardized water quality data comprises standard stratified water quality data and standard mixed water quality data; and the multi-dimensional data fusion unit is used for fusion processing of the standardized water quality data to output water quality fusion intermediate data.

[0062] It should be noted that the embodiment sets the water quality sampling assembly 1 to collect the stratified water quality samples of different depths of the water area to be measured in the sampling link, solves the problem of fixed stratified sampling depth in the prior art, and avoids the deviation caused by water disturbance, ensures the representativeness of the water samples at each depth, and then the sample processing assembly 2 is communicated with the sampling assembly 1 to realize the mixing of the stratified water quality samples, and the water quality data detection assembly 3 collects the stratified water quality index data and the mixed water quality index data through the first and second water quality data collectors 32, respectively, which not only retains the original index information of each water layer, but also obtains the mixed data reflecting the overall water quality. Subsequently, the preprocessing unit of the data processing assembly 4 standardizes the two types of water quality index data, and the multi-dimensional data fusion unit fuses the stratified and mixed water quality index data after standardization to output water quality fusion intermediate data, forming a complete technical process of stratified sampling-double data acquisition-differentiated preprocessing-multi-dimensional fusion, and then by retaining the stratified water quality index data and the mixed water quality index data, using the differentiated preprocessing method to restore the index characteristics, and then calculating and realizing data fusion through the multi-dimensional fusion unit, the problem of one-sided water quality data caused by single depth sampling in the prior art is effectively made up, and the problem of deviation between the water quality detection result and the real water quality condition caused by losing stratified information of water quality data by detecting only mixed water samples is solved. The precise capture of the stratified water quality characteristics of the water area to be measured and the scientific fusion of multi-dimensional data are realized, so that the water quality fusion intermediate data output is closer to the real water quality condition of the water area to be measured, and the overall water quality index data of the water area to be measured is more fully reflected, which effectively improves the comprehensiveness, accuracy and reliability of water quality detection, and provides strong technical support for fine water environment pollution prevention and control decision-making.

[0063] It should be noted that in the above scheme, although the stratified water quality sample collection at different depths of the water body to be tested is realized through the several sampling bottles 12, due to the complexity of the water environment, water disturbance, water flow impact and other factors, the water quality index data at different depths may have significant differences, especially in the actual water environment, the distribution of pollutants often shows subtle differences due to water temperature stratification, water flow disturbance, pollution source diffusion characteristics, etc. For example, some heavy metal pollutants may be enriched in the lower layer of the water body due to their greater density, while organic pollutants may form a concentration peak in the middle layer of the water body due to the difference in solubility, and even different points at the same depth may have fluctuations in pollutant concentration due to local circulation. If a fixed position stratified sampling method is used, the sampling bottle 12 cannot dynamically adapt to the non-uniform distribution of pollutants, and may miss the key area with high pollutant concentration or representativeness, resulting in deviation of the collected water quality index data (such as pollutant concentration, proportion of dissolved pollutants, etc.) from the actual distribution, and the stratified water quality sample cannot truly reflect the pollution characteristics at each depth of the water body to be tested, and the stratified water quality sample still cannot fully reflect the pollution of the water body to be tested, which may lead to incomplete capture of the characteristics of the key pollution area based on the subsequent detection of the stratified water quality index data, and further affect the accuracy of the final water quality detection result.

[0064] Therefore, in the preferred embodiment, the water quality sampling assembly 1 comprises a vertically arranged sampling rod 11, and a plurality of sampling bottles 12 are equidistantly arranged outside the sampling rod 11. The sampling bottles 12 and the sampling rod 11 are connected by a sliding mechanism, and a sampling valve 121 is installed at one end of the sampling bottle 12.

[0065] Based on the above embodiment, the present embodiment sets a vertical sampling rod 11 in the water quality sampling assembly 1, equidistantly arranges a plurality of sampling bottles 12 outside the sampling rod 11, and connects the sampling bottles 12 and the sampling rod 11 by a sliding mechanism, while installing a sampling valve 121 at one end of the sampling bottle 12. When the sampling valve 121 is opened to collect water samples, the gravity of the sampling bottle 12 increases as the water sample flows in, and the sampling bottle 12 can slide along the sampling rod 11 under the action of the sliding mechanism to adjust the sampling depth position of the sampling bottle 12, so that the sampling bottle 12 can dynamically adapt to the subtle depth changes of the non-uniform distribution of pollutants, thereby accurately collecting representative water quality samples at each depth, solving the problem of insufficient sample representativeness caused by subtle differences in pollutant distribution when the sampling bottle 12 is fixed at a stratified sampling position, accurately capturing the pollution characteristics at different depths, ensuring that the stratified water quality sample can fully reflect the pollution at each depth of the water body to be tested, and providing a more reliable sample basis for subsequent water quality index detection and data fusion, and finally improving the detection accuracy of the detection device.

[0066] In addition, the sliding mechanism comprises a sliding groove 131 formed in the side surface of the sampling rod 11, a sliding block 132 is slidingly arranged in the sliding groove 131, a spring 133 is arranged between the sliding block 132 and the sliding groove 131, and one side of the sliding block 132 extends to the outside of the sliding groove 131 and is connected with the sampling bottle 12.

[0067] In the initial state, the sampling bottle 12 is hung in the sliding groove 131 of the sampling rod 11 through the sliding block 132, the sliding block 132 and the spring 133 at the bottom of the sliding groove 131 are in a natural extension and contraction state, and at this time, the sampling bottle 12 is in a preset initial stratification position under the balance of gravity; when the sampling valve 121 is opened, the water samples at different depths of the water area to be measured begin to enter the sampling bottle 12, so that the weight of the sampling bottle 12 changes, the spring 133 is compressed, the sliding block 132 slides in the sliding groove 131, and the longitudinal position of the sampling bottle 12 is flexibly adjusted, so that the sampling bottle 12 realizes synchronous depth position sliding in the stratified sampling process, and then it is ensured that the sampling bottle 12 can collect representative water samples in each depth of water body due to the slight difference in pollutant distribution (such as heavy metal enrichment layer and organic pollutant concentration peak area) when sampling stratified water quality;

[0068] As a further preferred, the spring 133 can be made of springs 133 with different elasticities, for example, the elastic force gradually decreases along the depth direction of the sliding groove 131. This elastic gradient setting can more accurately adapt to the weight change of water samples at different depths: that is, when the pollutant concentration in a certain depth of water body is relatively high, the density of the water sample increases, the weight of the sampling bottle 12 increases, the spring 133 with decreasing elastic force is more easily compressed in the lower area, so that the sampling bottle 12 driven by the sliding block 132 can continue to be finely adjusted downward along the sliding groove 131, so as to accurately stay at the key depth of pollutant enrichment, and when the pollutant concentration in the water sample is relatively low and the weight is relatively light, the spring 133 with relatively large elastic force in the upper area can drive the sliding block 132 to move upward slightly, so as to avoid that the sampling bottle 12 deviates from the target stratification due to excessive settlement by gravity. This dynamic sliding adjustment mechanism combined with the elastic gradient design significantly improves the adaptive sensitivity of the sampling bottle 12 to the non-uniform distribution of pollutants in the water body, so that the sampling bottle 12 can track the depth difference formed by the change of the pollutant concentration in real time, ensures that the stratified water quality sample collected truly reflects the pollution characteristics of the corresponding depth, lays a reliable foundation for the first water quality data collector 31 to obtain accurate stratified water quality index data, and thus improves the detection precision of the detection device.

[0069] Further in the embodiment, the sample processing assembly 2 comprises a floating plate 25 arranged at the upper portion of the sampling rod 11 and a processing bin 21 arranged on the floating plate 25, and the processing bin 21 is internally provided with a plurality of water sample temporary storage cavities 22 corresponding to and in communication with the sampling bottles 12. The water sample temporary storage cavities 22 are hollow columnar cavities and are used for temporarily storing the stratified water quality samples collected by the sampling bottles 12. A water sample mixing cavity 23 is arranged at the middle position of the plurality of water sample temporary storage cavities 22. The water sample mixing cavity 23 is in communication with the plurality of water sample temporary storage cavities 22 through a proportional control valve 24. The water sample mixing cavity 23 is further provided with a stirrer 231. The proportional control valve 24 is controlled to be opened, so that the stratified water quality samples in the water sample temporary storage cavities 22 enter the water sample mixing cavity 23 and form mixed water quality samples after being stirred by the stirrer 231.

[0070] For example, the proportional control valve 24 in the embodiment refers to a valve for adjusting the proportion of stratified water samples entering the mixing cavity. Specifically, the proportional control valve 24 can be realized by an electromagnetic valve or a flow regulating valve driven by a stepping motor. The opening degree or opening time of the valve is controlled to realize accurate regulation and control of the proportion of water samples. The stirrer 231 refers to a mechanical device for mixing stratified water samples. Specifically, the stirrer 231 can be realized by propeller type or turbine type stirring blades. The different stratified water samples are fully mixed by rotating motion.

[0071] In addition, as a preferred arrangement, the water sample temporary storage cavities 22 and the corresponding sampling bottles 12 are in communication through water conveying pipelines, and a water pump is arranged on the water conveying pipelines. The water quality samples collected in the sampling bottles 12 are pumped into the corresponding water sample temporary storage cavities 22 through the water pump and the water conveying pipelines.

[0072] In the embodiment, the plurality of water sample temporary storage cavities 22 in the processing bin 21 are in one-to-one correspondence with the sampling bottles 12, so that the stratified water quality samples can be independently temporarily stored, and the stratified samples are prevented from being mixed before processing, so as to ensure that the original characteristics of the stratified samples are not disturbed. When mixed water quality samples are needed, the proportional control valve 24 is controlled to be opened, so that the flow of stratified samples in each water sample temporary storage cavity 22 entering the water sample mixing cavity 23 can be flexibly adjusted. After being uniformly stirred by the stirrer 231, the mixed water quality samples are formed, so as to realize complete reservation of stratified water quality sample data and accurate regulation of mixed water quality sample data. That is, the accurate detection of stratified water quality sample index data is ensured, and the mixed water quality sample index data can comprehensively reflect the characteristics of stratified water quality samples and is uniform and stable, so as to provide reliable overall water quality detection samples for subsequent water quality detection. Finally, through the dual data support of stratified water quality and mixed water quality samples, the comprehensiveness and data reliability of water quality detection are improved.

[0073] In some preferred embodiments, the first water quality data collector 31 is arranged in the water sample temporary storage cavity 22, the second water quality data collector 32 is arranged in the water sample mixing cavity 23, and the first water quality data collector 31 and the second water quality data collector 32 both adopt a multi-parameter sensor array.

[0074] The stratified water quality index data and the mixed water quality index data both include pollution type water quality index data and beneficial type water quality index data.

[0075] It should be understood that the multi-parameter sensor array refers to a detection module composed of multiple independent sensor units, each of which can be configured to detect a specific water quality parameter, such as a dissolved oxygen sensor, a pH sensor, a heavy metal ion sensor, and an organic pollutant sensor, which can be integrated in the array to obtain multi-dimensional data in a single detection. They are all prior art, and their collection and specific principles are not within the protection scope of the present application, which is not particularly limited herein. Those skilled in the art can learn about the related technology from the existing public channels (such as market purchase).

[0076] Based on the above embodiments, the multi-parameter sensor array can synchronously detect multiple water quality indexes (such as pollution type COD, heavy metals, and beneficial type dissolved oxygen, chlorophyll, etc.), breaking through the limitation of single parameter detection, improving the data collection efficiency, and the first collector directly detects the stratified sample in the water sample temporary storage cavity 22 to ensure that the stratified water quality index data truly reflects the original characteristics at each depth. The second collector detects the uniformly mixed sample in the mixing cavity to ensure the representativeness of the overall water quality index data. The explicit classification of pollution type and beneficial type indexes provides a basis for the differential standardization (upper / lower limit processing) of the subsequent data preprocessing unit, avoids distortion of index characteristics, solves the one-sidedness of data caused by single index detection, stratified and mixed data fragmentation, and undistinguished index characteristics in the prior art, and finally provides comprehensive, accurate, and clearly classified original data for the data processing component 4, supporting the scientificity and reliability of the water quality detection result.

[0077] It should be further explained that the pollution type water quality index data mainly includes indexes reflecting the pollution degree of water body, such as chemical oxygen demand (COD, representing the pollution degree of organic matter that can be oxidized in water body), heavy metal content (such as lead, cadmium, etc., which will harm aquatic organisms and human health), ammonia nitrogen (a key index reflecting the risk of water body eutrophication), etc.

[0078] The beneficial type water quality index data covers indexes beneficial to the water ecosystem, such as dissolved oxygen (DO, a necessary condition for the survival of aquatic organisms), chlorophyll a (reflecting the photosynthetic capacity of aquatic plants and indirectly reflecting the productivity of water body), appropriate calcium and magnesium ions (maintaining the balance of water body pH, promoting the growth of aquatic organisms), etc.

[0079] In further embodiments, the data processing component 4 is arranged in the processing bin 21.

[0080] The embodiment realizes close cooperation with the sample processing and data acquisition assembly, reduces data transmission interference, and improves the compactness of the device structure through the integrated layout of the data processing assembly 4 arranged in the processing bin 21.

[0081] As a preferred embodiment, the standardization preprocessing of the stratified water quality index data and the mixed water quality index data by the data preprocessing unit includes:

[0082] Removing outliers in the stratified water quality index data and the mixed water quality index data;

[0083] Performing upper limit standardization processing on pollution type water quality index data in the stratified water quality index data and the mixed water quality index data;

[0084] Performing lower limit standardization processing on beneficial type water quality index data in the stratified water quality index data and the mixed water quality index data.

[0085] It should be noted that the embodiment purifies data by removing outliers to avoid interference of extreme values on analysis results and improve the reliability of original data. Further, in removing outliers, a three-sigma principle based on a statistical method or an outlier detection algorithm based on a machine learning model can be used to filter non-real data caused by device fluctuations, sampling interference, etc., and based on the statistical distribution characteristics of water quality index data, outliers deviating from the normal fluctuation range (such as jump values caused by sensor instantaneous failure) are identified to ensure that the retained data can truly reflect the actual state of the water body. Based on the same classification standardization processing to retain the inherent characteristics of the two types of indicators (mixed water quality and stratified water quality), the distortion problem of the meaning of the indicators caused by unified standardization (such as the opposite meaning of “high and low” of pollution type and beneficial type indicators) is solved. Through the above preprocessing logic, indicators of different dimensions and different characteristics are converted into comparable standardized data, providing a consistent basis for subsequent multi-dimensional data fusion, ensuring that the fusion result can accurately map the comprehensive condition of water quality, and finally improving the scientificity and reliability of water quality detection and evaluation. For example:

[0086] When upper limit standardization processing is performed on pollution type water quality index data, the processing formula is:

[0087] ,

[0088] wherein, is the standard value of the pollution type water quality index data, is the measured value of the pollution type water quality index data, is the historical minimum value of the pollution type water quality index data, is the national standard maximum allowable value of the pollution type water quality index data;

[0089] For the beneficial water quality index data, the processing formula is:

[0090] ,

[0091] Wherein, is the standard value of the beneficial water quality index data, is the measured value of the beneficial water quality index data, is the best threshold lower limit of the beneficial water quality index data, is the national standard safety threshold upper limit of the beneficial water quality index data.

[0092] It should be noted that the above data standardization processing for pollution type water quality index and beneficial water quality index, the core technical purpose is to eliminate the interference of different types of indicators caused by unit and value range difference through targeted processing, and to convert the measured value into a unified dimension of standardized value, that is, through the upper limit standardization processing of pollution type water quality index data, the characteristics of "the larger the measured value, the higher the pollution degree quantization value" are realized, and through the lower limit standardization processing of beneficial water quality index data, the characteristics of "the larger the measured value, the higher the beneficial degree quantization value" are realized, so that the two types of indicators have the property of "pollution degree and beneficial degree can be directly compared" in the same scale, which ensures that the actual contribution weight of each index can be accurately reflected during subsequent hierarchical and mixed water quality data fusion, avoids the distortion of fusion results caused by original value difference, and lays a foundation for effective fusion of water quality detection data.

[0093] As a further preferred embodiment, the multi-dimensional data fusion unit is used for fusion processing of the standardized water quality data, including:

[0094] Based on the real-time feedback of each hierarchical actual water depth data of the sampling assembly, and combining with the water quality index type, the dynamic weight is calculated respectively;

[0095] The depth sensitive weight algorithm is used for the pollution type water quality index data, and the calculation formula is:

[0096] ,

[0097] Wherein, is the dynamic weight of the pollution type water quality index data of the first layer, is the basic weight of the pollution type water quality index data of the first layer (based on historical water quality pollution data calibration preset), is the water depth fluctuation sensitive coefficient (which is calibrated through a limited number of pre-hierarchical sampling experiments), is the deviation value of the actual sampling water depth of the first layer and the preset sampling water depth;

[0098] The concentration gradient weight method is adopted to distribute weight in inverse proportion to the concentration gradient difference for the beneficial index, and the calculation formula is:

[0099] ;

[0100] Among them, is the dynamic weight of the beneficial water quality index data of the first layer, is the concentration difference of the sampling water quality of the first layer and the water quality index data of the adjacent layer, is the number of stratified sampling;

[0101] The standard stratified water quality data and the corresponding dynamic weight are weighted to obtain the stratified fusion value, and the calculation formula is:

[0102] ;

[0103] Among them, is the stratified water quality data fusion value, is the standard stratified water quality index data of the first layer (the pollution water quality index data corresponds to , and the beneficial water quality index data corresponds to ), is the dynamic weight of the first layer (the pollution water quality index corresponds to , and the beneficial water quality index corresponds to );

[0104] The deviation compensation fusion algorithm is adopted to process the standard mixed water quality data and the stratified fusion value to calculate the deviation coefficient, and the calculation formula of the deviation coefficient is:

[0105] ,

[0106] Among them, is the deviation coefficient, is the mixed water quality data after standardization preprocessing (the pollution mixed water quality index data corresponds to and is recorded as , and the beneficial mixed water quality index data corresponds to and is recorded as );

[0107] The deviation coefficient is compared with the preset deviation coefficient threshold, and the water quality fusion intermediate data is output;

[0108] Among them, the preset deviation coefficient threshold includes the pollution index threshold and the beneficial index threshold , The deviation coefficient 95% calculated based on the pollution index of the historical normal water sample (select at least 30 groups of continuous normal working condition layering and mixed water quality detection data in the past 3 years in the water area to be tested, calculate the deviation coefficient of each group of data and arrange in ascending order, and take the 95% quantile value as the pollution index threshold), The deviation coefficient 90% calculated based on the beneficial index of the historical normal water sample (the deviation coefficient of the beneficial index is arranged in ascending order, and the 90% quantile value is taken as the beneficial index threshold); the comparison output process includes:

[0109] If , the water quality fusion intermediate data is the weighted average of the layering water quality data fusion value and the pollution mixed water quality data, and the calculation formula is: ,

[0110] In the above formula, is the fusion coefficient of the pollution layering water quality index data (calibrated through a limited number of experiments, and );

[0111] If , the water quality fusion intermediate data is the weighted average of the layering water quality data fusion value and the beneficial mixed mixed data, and the calculation formula is: ,

[0112] In the above formula, is the fusion coefficient of the beneficial layering water quality index data (calibrated through a limited number of experiments, and );

[0113] If or , mark the pollution mixed data (or the beneficial mixed data) as abnormal, and take the layering water quality data fusion value as the water quality fusion intermediate data output.

[0114] It should be understood that the above embodiment effectively solves the problems of fixed sampling weight, hierarchical information loss and insufficient data fusion accuracy in the existing water quality detection technology by constructing a dynamic weight model, hierarchical fusion calculation and bias compensation fusion algorithm. For pollution indicators, the depth sensitive weight algorithm is used to dynamically adjust the weight according to the water depth fluctuation. For beneficial indicators, the weight is inversely proportional to the concentration gradient difference. The adaptive optimization of the data weight of different water layers is realized, and the hierarchical feature weakening problem caused by fixed weight is avoided. The water quality difference characteristics of each depth are retained by calculating the hierarchical fusion value. In combination with the bias compensation fusion algorithm, the deviation coefficient of the hierarchical fusion value and the mixed data is compared, and the threshold is set according to the index type, and the fusion intermediate data is output by weighted average or abnormal marking. The details of the hierarchical data and the overall characteristics of the mixed data are integrated, the data reliability is ensured through the abnormal marking mechanism, the fine optimization of the water quality data from hierarchical sampling to fusion processing is finally realized, the accuracy and representativeness of the water quality detection data are significantly improved, a more accurate quantitative basis for water environment quality detection is provided, and the detection accuracy of the detection device is greatly improved.

[0115] In a further embodiment, the data processing assembly 4 further comprises a data correction unit connected to the multi-dimensional data fusion unit. The data correction unit is pre-installed with an error correction model. The water quality fusion intermediate data output is corrected by the error correction model to obtain the water quality detection data of the water area to be detected.

[0116] It should be pointed out that the data correction unit in the embodiment refers to a functional module for receiving the intermediate data output by the multi-dimensional data fusion unit and performing secondary correction. It can be realized by using an embedded processor or an independent operation chip. Its function is to eliminate the residual systematic error or random noise in the fusion process. The error correction model refers to an algorithm model for identifying and correcting data deviation. It can be realized by using a machine learning model or a statistical regression model trained based on historical data, such as a random forest algorithm or a multiple linear regression model. Its function is to dynamically adjust the abnormal fluctuations in the fusion intermediate data by using the pre-set correction rules to accurately correct the water quality fusion intermediate data, effectively eliminating the systematic error and random error caused by factors such as hierarchical sampling deviation, sensor drift and environmental interference, thereby significantly improving the absolute accuracy and stability of the water quality detection data, and finally making the water quality detection result of the detection device more accurate.

[0117] For example, the construction of the error correction model is based on a large amount of historical detection data. First, the water quality fusion intermediate data and the laboratory standard detection true value (the authoritative data measured by high-precision instruments) of the same water area are synchronously collected, and the environmental auxiliary parameters such as water temperature, pH value, and water flow speed are recorded. Then, the fusion intermediate data and the environmental parameters are taken as input features, the difference between the laboratory true value and the fusion intermediate data is taken as the target output, and a multivariate linear regression or BP neural network algorithm is used for model training. For example, for the correction of COD (pollution index) of a certain river basin, the model parameters are iteratively optimized to minimize the prediction error, and finally a correction function that can dynamically adapt to different water quality scenes is formed.

[0118] It should be noted that in the present embodiment, the error correction model is not the innovation to be protected by the present application. Its essential logic is a conventional data correction method in the art, which belongs to the prior art. The present application only uses it as a standardized link in the data processing process, and the purpose is to eliminate the residual errors in the fusion data by using mature model technology, rather than improving the structure or algorithm of the model. In actual use, the technical personnel can select the corresponding model construction method according to the specific application scene (such as the pollution type of the detection water area and the water quality stability), for example, in the scene where the water quality fluctuates less, a multivariate linear regression model is used, and in the scene where the water quality is complex and changeable, a machine learning model such as random forest or BP neural network is used. Only by training the model through historical data to achieve the preset correction accuracy can it be used.

[0119] As a further specific embodiment, the device further comprises a detection result output component 5 disposed at the top of the processing bin 21 and connected with the data correction unit and the external terminal signal, for outputting the water quality detection data to the external terminal.

[0120] Based on the above embodiment, the detection result output component 5 refers to a hardware module integrated with data transmission function, which can be realized by using a wireless communication module or a standard data interface, for establishing a data transmission channel with an external device, which realizes automatic and instant transmission of the corrected water quality data, eliminating the time loss caused by the manual export link.

[0121] Embodiment 2:

[0122] The present embodiment is based on the water quality detection device for water environment pollution prevention and control of the above-mentioned embodiment 1, and proposes a water quality detection method based on water environment pollution prevention and control. Specifically, the method comprises:

[0123] Step 1: The detection device is arranged in the water area to be detected, so that the detection bin is floated on the water surface by the floating plate 25, and the sampling rod 11 is inserted into the water body of the water area to be detected;

[0124] Step 2: After the sampling rod 11 is inserted into the water body, the sampling valve 121 of the sampling bottle 12 is controlled to open, so that the water samples at different depths in the water body to be measured enter the respective sampling bottles 12, and as the water samples enter the sampling bottles 12, the sampling bottles 12 slide downward along the sliding groove 131 of the sampling rod 11 by the sliding mechanism, and the spring 133 between the sliding block 132 and the sliding groove 131 is compressed to dynamically adapt to the change of water depth, thereby completing the collection of stratified water quality samples;

[0125] Step 3: The sampling valve 121 is closed, and the water sample temporary storage chamber 22 of the sample processing assembly 2 is controlled to communicate with the sampling bottle 12, so that the stratified water quality samples in the respective sampling bottles 12 are correspondingly transported into the water sample temporary storage chamber 22; the first water quality data collector 31 detects the stratified water quality samples in the water sample temporary storage chamber 22 to collect stratified water quality index data;

[0126] Step 4: After the stratified water quality index data collection is completed, the proportional control valve 24 is controlled to open, so that the stratified water quality samples in the respective water sample temporary storage chambers 22 enter the water sample mixing chamber 23, and the mixed water quality sample is formed after being stirred by the stirrer 231; the second water quality data collector 32 detects the mixed water quality sample to collect mixed water quality index data;

[0127] Step 5: The data processing assembly 4 receives the stratified water quality index data and the mixed water quality index data, which are preprocessed by the data preprocessing unit and then fused by the multi-dimensional data fusion unit to output water quality fusion intermediate data; the data correction unit corrects the water quality fusion intermediate data by an error correction model to obtain water quality detection data, which is transmitted to an external terminal by the detection result output assembly 5 to complete the water quality detection work.

[0128] In the above embodiment, the detection method realizes adaptive adjustment of the sampling depth, eliminates spatial errors caused by water flow disturbance, and simultaneously acquires original stratified data and mixed comprehensive data through the parallel detection structure of the stratified temporary storage chamber and the mixing chamber, and dynamically allocates fusion weights based on the coefficient of variation, so that the detection result takes into account both stratified characteristics and overall distribution law. It solves the problem of insufficient water sample representativeness caused by fixed sampling depth, and ensures the accuracy of water sample collection position at different depths through dynamic adaptation mechanism. The stratified and mixed dual-mode data collection avoids information loss in single detection mode, and completely retains the vertical pollution distribution characteristics of the water body. The differential standardization processing eliminates the dimension difference of the data of pollution and beneficial indicators, the dynamic weight fusion algorithm improves the collaborative analysis accuracy of stratified data and mixed data, the error correction model further corrects the system deviation, and finally realizes the reliability and adaptability improvement of the water quality detection result in complex water body environment.

[0129] In addition, the structures, proportions, sizes, etc. shown in the drawings attached to the present specification are schematic diagrams, which are only used to cooperate with the disclosed content to help those skilled in the art to understand and read, and are not used to limit the implementation conditions of the present application, so they do not have technical significance. Any modification of the structure, change of the proportional relationship or adjustment of the size, without affecting the effects and purposes that can be achieved by the present application, should still fall within the scope of the technical content disclosed by the present application.

[0130] At the same time, the terms such as "upper", "lower", "left", "right", "middle" and the like mentioned in the present specification are only for the convenience of clear description, and are not used to limit the implementation range of the present application. The change or adjustment of the relative relationship, without substantially changing the technical content, is also considered as the implementation scope of the present application.

[0131] The above is only the preferred embodiment of the present application, and does not limit the patent scope of the present application. Any equivalent structure or equivalent process transformation using the content of the present specification and drawings, or direct or indirect application in other related technical fields, is also included in the patent protection scope of the present application.

Claims

1. A water quality testing device based on water environment pollution prevention and control, characterized in that, The device includes: Water quality sampling component (1), the water quality sampling component (1) is used to collect stratified water quality samples at different depths of the water body to be tested; The sample processing component (2) is connected to the water quality sampling component (1) and is used to mix stratified water quality samples. The water quality data detection component (3) includes a first water quality data collector (31) and a second water quality data collector (32). The first water quality data collector (31) is used to collect the stratified water quality index data of the stratified water quality sample, and the second water quality data collector is used to collect the mixed water quality index data after mixing. A data processing component (4) is electrically connected to the water quality data detection component (3) and is used to process and output stratified water quality index data and mixed water quality index data. The data processing component (4) includes a data preprocessing unit and a multi-dimensional data fusion unit that are interconnected by signals. The data preprocessing unit is used to perform standardized preprocessing on the stratified water quality index data and mixed water quality index data to output standardized water quality data. The standardized water quality data includes standard stratified water quality data and standard mixed water quality data. The standardized preprocessing includes: Outliers were removed from stratified water quality index data and mixed water quality index data; Upper limit standardization is applied to pollutant water quality indicators in stratified and mixed water quality indicator data; the upper limit standardization satisfies the following: ， in, These are the standard values ​​for water quality indicators related to pollution. These are measured values ​​of water quality indicators classified as pollutants. This represents the lowest historical value for polluted water quality indicators. The maximum permissible value of national standards for water quality indicators related to pollution; For beneficial water quality indicators in stratified and mixed water quality indicator data, lower limit standardization is applied; the lower limit standardization satisfies the following: ， in, The standard values ​​for beneficial water quality indicators. These are measured values ​​of beneficial water quality indicators. This represents the lower limit of the optimal threshold for beneficial water quality indicators. The upper limit of the national standard safety threshold for beneficial water quality indicators; The multi-dimensional data fusion unit is used to fuse standardized water quality data to output intermediate water quality fusion data; wherein, the fusion process includes: Based on the real-time feedback of actual water depth data for each stratum from the water quality sampling components, and combined with the water quality index types, dynamic weights are calculated respectively; among them, The depth-sensitive weighting algorithm is used for polluted water quality index data, and its calculation formula is as follows: ， in, For the first Dynamic weighting of water quality indicators related to sedimentary contamination. For the first Basic weights for water quality indicators related to sedimentary pollution. The water depth fluctuation sensitivity coefficient, For the first The deviation between the actual sampling water depth and the preset sampling water depth; For beneficial indicators, the concentration gradient weighting method is used to allocate weights inversely proportional to the concentration gradient difference. The calculation formula is as follows: ； in, For the first Dynamic weighting of beneficial water quality indicators in the strata. For the first The concentration difference of beneficial water quality indicators between the sampled layer and the adjacent layer. This represents the number of stratified samples; The standard stratified water quality data are weighted with the corresponding stratified dynamic weights to obtain the stratified fusion value, and the calculation formula is as follows: ； in, This is a fusion value of stratified water quality data. For the first Standard stratified water quality index data for each layer. No. Dynamic weights of layers; A deviation compensation fusion algorithm is used to process standard mixed water quality data and stratified fusion values, and the deviation coefficient is calculated. The formula for calculating the deviation coefficient is as follows: ； in, The deviation coefficient, For standardized pretreated mixed water quality data, the corresponding polluted mixed water quality index data are... And recorded as Beneficial mixed water quality index data corresponding to And recorded as ; The data is compared with the preset deviation coefficient threshold, and intermediate water quality fusion data is output. Among them, the preset deviation coefficient threshold includes pollution index thresholds. and beneficial index thresholds The comparison output process includes: like The intermediate water quality data is a weighted average of the stratified water quality data and the mixed polluted water quality data. The calculation formula is as follows: , In the above formula, The fusion coefficient for stratified water quality index data of pollution categories was determined through a limited number of experiments, and ; like The intermediate water quality data is a weighted average of the stratified water quality data and the mixed data of beneficial categories, and its calculation formula is as follows: , In the above formula, The fusion coefficient for beneficial water quality index data was determined through a limited number of experiments, and ; like or If the mixed data of pollutants or beneficial substances is marked as abnormal, then the stratified water quality data will be merged. As intermediate data output for water quality fusion.

2. The water quality testing device based on water environment pollution prevention and control according to claim 1, characterized in that, The water quality sampling assembly (1) includes a vertically arranged sampling rod (11), and a number of sampling bottles (12) are equidistantly arranged outside the sampling rod (11). The sampling bottles (12) are slidably connected to the sampling rod (11) through a sliding mechanism. A sampling valve (121) is installed at one end of the sampling bottle (12).

3. The water quality testing device based on water environment pollution prevention and control according to claim 2, characterized in that, The sample processing assembly (2) includes a float plate (25) located on the upper part of the sampling rod (11) and a processing chamber (21) located on the float plate (25). The processing chamber (21) has several water sample storage chambers (22) that correspond one-to-one with the sampling bottle (12) and are connected to each other. The water sample storage chamber (22) is a hollow cylindrical cavity used to temporarily store the stratified water quality samples collected by the sampling bottle (12). A water sample mixing chamber (23) is provided in the middle of the several water sample storage chambers (22). The water sample mixing chamber (23) is connected to the several water sample storage chambers (22) through a proportional control valve (24). The water sample mixing chamber (23) is also provided with a stirrer (231). The proportional control valve (24) is controlled to open, so that the stratified water quality samples in the water sample storage chamber (22) enter the water sample mixing chamber (23) and are mixed by the stirrer (231) to form a mixed water quality sample.

4. A water quality testing device based on water environment pollution prevention and control according to claim 3, characterized in that, The first water quality data acquisition device (31) is located in the water sample storage chamber (22), and the second water quality data acquisition device (32) is located in the water sample mixing chamber (23). Both the first water quality data acquisition device (31) and the second water quality data acquisition device (32) adopt a multi-parameter sensor array. The stratified water quality index data and the mixed water quality index data both include polluted water quality index data and beneficial water quality index data.

5. A water quality testing device based on water environment pollution prevention and control according to claim 3, characterized in that, The data processing component (4) is located inside the processing compartment (21).

6. A water quality testing device based on water environment pollution prevention and control according to claim 5, characterized in that, The data preprocessing unit performs standardized preprocessing on the stratified water quality index data and the mixed water quality index data, including: Outliers were removed from stratified water quality index data and mixed water quality index data; Upper limit standardization is applied to polluting water quality indicators in stratified water quality indicator data and mixed water quality indicator data; For beneficial water quality indicators in stratified water quality indicator data and mixed water quality indicator data, lower limit standardization is adopted.

7. A water quality testing device based on water environment pollution prevention and control according to claim 6, characterized in that, The multi-dimensional data fusion unit is used to fuse standardized water quality data, including: Based on the real-time feedback of the actual water depth data of each layer from the water quality sampling component (1), and combined with the water quality index type, dynamic weights are calculated respectively. The standard stratified water quality data are weighted and calculated with the corresponding stratified dynamic weights to obtain the stratified fusion value; A deviation compensation fusion algorithm was used to process standard mixed water quality data and stratified fusion values, and the deviation coefficient was calculated. The system compares the deviation coefficient with a preset deviation coefficient threshold and outputs intermediate water quality fusion data.

8. A water quality testing device based on water environment pollution prevention and control according to claim 7, characterized in that, The data processing component (4) also includes a data correction unit that is signal-connected to the multi-dimensional data fusion unit. The data correction unit has a preset error correction model. The output water quality fusion intermediate data is corrected by the error correction model to obtain the water quality detection data of the water area to be tested.

9. A water quality testing device based on water environment pollution prevention and control according to claim 8, characterized in that, The device also includes a detection result output component (5), which is located on the top of the processing chamber (21) and connected to the data correction unit and the external terminal signal, for outputting water quality detection data to the external terminal.

10. A water quality detection method based on water environment pollution prevention and control, and a water quality detection device based on water environment pollution prevention and control according to any one of claims 1-9, characterized in that, The method includes: Step 1: Deploy the detection device to the water area to be tested, so that the detection chamber floats on the water surface through the float plate (25), and ensure that the sampling rod (11) is inserted into the water body of the water area to be tested; Step 2: After the sampling rod (11) is inserted into the water body, the sampling valve (121) of the sampling bottle (12) is opened, so that water samples at different depths in the water body to be tested enter each sampling bottle (12). When the water sample enters the sampling bottle (12), as the weight of the sampling bottle (12) increases, the sampling bottle (12) slides down along the slide groove (131) of the sampling rod (11) through the sliding mechanism, compressing the spring (133) between the slider (132) and the slide groove (131) to dynamically adapt to the changes in water depth, thereby completing the collection of stratified water quality samples. Step 3: Close the sampling valve (121) and connect the water sample storage chamber (22) of the sample processing component (2) to the sampling bottle (12) so that the stratified water quality samples in each sampling bottle (12) are transported to the water sample storage chamber (22); the first water quality data collector (31) detects the stratified water quality samples in the water sample storage chamber (22) and collects the stratified water quality index data; Step 4: After the stratified water quality index data collection is completed, the proportional control valve (24) is opened to allow the stratified water quality samples in each water sample storage chamber (22) to enter the water sample mixing chamber (23) and be stirred by the stirrer (231) to form a mixed water quality sample; the second water quality data collector (32) detects the mixed water quality sample and collects the mixed water quality index data. Step 5; The data processing component (4) receives the stratified water quality index data and the mixed water quality index data. After the data preprocessing unit standardizes and preprocesses the data, the multi-dimensional data fusion unit performs fusion processing to output the water quality fusion intermediate data. The data correction unit corrects the water quality fusion intermediate data through the error correction model to obtain the water quality detection data. The detection result output component (5) transmits the water quality detection data to the external terminal to complete the water quality detection work.

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