Device, method and system for detecting water quality through full-automatic collection and positioning

Abstract

The invention discloses a device, method and system for detecting water quality through full-automatic collection and positioning, and the method comprises the steps: firstly putting a device cabin into a target water body, and recording geographic position information by a Beidou satellite navigation system; the automatic water sample collecting device collects a water quality sample and pumps the water quality sample to the liquid storage tank, the coloring agent feeding device injects a coloring agent to form a mixed solution, and the mixed solution is conveyed to the color-sensitive sensing device through a third metering pump; the color-sensitive sensing device acquires image information and transmits the image information to the data acquisition and processing device; extracting an RGB proportion value, distinguishing polluted and unpolluted areas through a critical relationship method, calculating matrix entropy and average information amount in combination with an information entropy theory, and evaluating the pollution degree; an evaluation result and a geographic position are fused to generate a pollution path map, a Beidou satellite navigation system plans a route, and a displacement device drives a device cabin to move towards a low-pollution area; and repeating the sampling evaluation process, and dynamically updating the pollution path diagram until the pollution source is locked. The problems of insufficient pollution source positioning accuracy and efficiency and the like in the prior art are solved.

Description

Technical Field

[0001] This invention relates to the field of water environment monitoring technology, specifically to a fully automatic water quality acquisition, positioning, and detection device, method, and system. Background Technology

[0002] In the field of water environment monitoring, with the rapid penetration of artificial intelligence, big data, and the Internet of Things (IoT) technologies, water quality monitoring equipment has gradually shifted from traditional manual sampling and laboratory analysis to automation and intelligence. Currently, intelligent automatic sampling vessels and unmanned vessels are widely used for water quality monitoring in rivers, lakes, and oceans. These devices, equipped with GPS or BeiDou satellite navigation systems, can autonomously complete river patrol operations along preset routes and integrate multiple sensor interfaces to achieve real-time monitoring and remote transmission of more than ten water quality indicators, such as water temperature, pH value, and dissolved oxygen. Simultaneously, automatic pollution source monitoring systems, through the collaborative operation of network monitoring computer centers, monitoring stations, and quality assurance laboratories, have constructed a continuous monitoring system for water pollution sources, significantly reducing the risks and errors of manual operation and improving the overall efficiency of monitoring work.

[0003] However, existing water quality monitoring technologies still have significant limitations, making it difficult to meet the needs of precise and comprehensive water environment management. On the one hand, traditional monitoring methods mostly rely on single parameter measurements, failing to comprehensively reflect the overall pollution status of water bodies. Furthermore, while dye tracer technology provides a new approach to pollution source location, it has not yet been systematically integrated with color channel analysis technology, lacking precise means of identifying polluted areas. On the other hand, information entropy theory, as an effective tool for measuring non-uniform characteristics, is still in the exploratory stage of application in water quality monitoring, making it difficult to reveal the spatial distribution patterns of pollutants through quantitative analysis. In addition, the insufficient synergy between the BeiDou satellite positioning system and water quality monitoring technologies has prevented the formation of efficient pollution source tracing models, resulting in poor accuracy and efficiency in pollution source location and an inability to quickly pinpoint pollution sources. These problems all constrain the further development of water environment monitoring and management.

[0004] Therefore, there is an urgent need for a fully automated water quality acquisition and positioning device and method to solve the problems of existing technologies, such as difficulty in comprehensively reflecting the water pollution status, lack of systematic means of identifying pollution areas, and insufficient accuracy and efficiency in locating pollution sources. Summary of the Invention

[0005] To address these issues, this invention provides a fully automated water quality monitoring device, method, and system for sampling, locating, and detecting water quality. This system solves the problems of existing water quality monitoring methods, such as difficulty in comprehensively reflecting water pollution status, lack of systematic means of identifying pollution areas, and insufficient accuracy and efficiency in locating pollution sources. It enables fully automated sampling, real-time detection, and precise location of pollution sources.

[0006] To achieve the above objectives, the present invention provides the following technical solution: a fully automatic water quality collection and positioning device, characterized in that it includes a device chamber, an automatic water sample collection device, a dye dispensing device, a color-sensitive sensor, and a data acquisition and processing device; the automatic water sample collection device is connected to a storage tank via a delivery pipeline; the storage tank is connected to the color-sensitive sensor via a third metering pump and the delivery pipeline; the dye dispensing device is connected to the delivery pipeline between the automatic water sample collection device and the storage tank via a second metering pump and the delivery pipeline; the color-sensitive sensor communicates with the data acquisition and processing device via a signal transmission line; the data acquisition and processing device is connected to a BeiDou satellite navigation system and an acoustic obstacle avoidance device via the signal transmission line; the BeiDou satellite navigation system and the acoustic obstacle avoidance device are connected to a displacement device that controls the displacement of the device chamber; the automatic water sample collection device is equipped with a first metering pump that controls the sampling volume; the device chamber is equipped with a power supply system that supplies power to the device; the displacement device respectively controls the actions of the automatic water sample collection device, the dye dispensing device, and the overall displacement of the device chamber.

[0007] As a preferred solution for a fully automated water quality acquisition and processing device, the data acquisition and processing device is equipped with... R, G, B The system includes a signal acquisition unit, a critical relationship calculation unit, an information entropy calculation unit, an average information content calculation unit, and a matrix entropy calculation unit.

[0008] As a preferred embodiment of a fully automated water quality acquisition and positioning device, the color-sensitive sensor is used to acquire a color signal of a set pixel size and extract the red channel from the color signal. R Green Channel G Blue Channel B The proportion value.

[0009] This invention also provides a fully automated method for collecting, locating, and detecting water quality, comprising: The device cabin was deployed to the target body of water, and its current geographical location information was recorded using the BeiDou satellite navigation system. Water samples are collected using an automatic water sample collection device; the water samples are pumped to a storage tank via an infusion pipeline; a dyeing agent dispensing device injects a standard dose of dye into the storage tank via an infusion pipeline, so that the water samples and the dye are fully mixed to form a mixture; the mixture is then delivered to a color-sensitive sensing device via an infusion pipeline and a third metering pump. Image information is acquired by the color-sensitive sensing device; the image information is then transmitted to the data acquisition and processing device via a signal transmission line. The red channel is extracted from the image information using the data acquisition and processing device. RGreen Channel G and the blue channel B The proportion value; based on the proportion value, the stained and unstained areas are distinguished by the critical relationship method to obtain the contaminated area and the uncontaminated area; for the contaminated area, the matrix entropy and average information content are calculated by the information entropy theory; the degree of contamination of the contaminated area is comprehensively evaluated by the matrix entropy and the average information content to obtain the degree of contamination evaluation result; A pollution path map is generated based on the pollution level assessment results and the geographical location information; based on the pollution path map, an optimal movement route is planned using the BeiDou satellite navigation system; based on the optimal movement route, the device cabin is driven to move towards a low-pollution area by controlling the displacement device; Repeat the water quality sample collection and pollution level assessment operations, and dynamically update the pollution path map until the pollution source is identified.

[0010] As a preferred solution for a fully automated water quality acquisition and positioning method, in the process of distinguishing between stained and unstained areas using the critical relationship method, the expression of the critical relationship method is: ; ;

[0011] In the formula, R Red channel; G Provide a green channel; B The blue channel. , , , All of these are fitting parameters.

[0012] As a preferred solution for a fully automated water quality acquisition and positioning method, this method distinguishes between stained and unstained areas through calculation. G / R ratio and B / R The ratio is used as an auxiliary factor in the judgment; the staining region is described G / R Ratio and the aforementioned B / R The ratios were all lower than those in the unstained areas.

[0013] As a preferred method for fully automated water quality acquisition and location detection, the matrix entropy is calculated using the following formula: ;

[0014] In the formula, The matrix entropy; K For one A positive definite matrix usually represents a correlation matrix; The trace of the matrix; d Let be the dimension of the matrix.

[0015] As a preferred method for fully automated water quality acquisition and location detection, the formula for calculating the average information content is: ;

[0016] In the formula, This represents the average information content. For the event The probability of occurrence; n The total number of possible events; It is a logarithm with base 2.

[0017] The present invention also provides a fully automatic water quality acquisition and positioning detection system, comprising: a water quality sampling and staining module, a water quality detection and data processing module, a positioning, navigation and movement control module, and a power supply guarantee module; The water sampling and staining module includes: an automatic water sample collection device, a storage tank, a staining agent dispensing device, a first metering pump, a second metering pump, and a third metering pump; the water sampling and staining module is used for quantitative water sample collection, precise staining agent dispensing, and mixed solution preparation. The water quality detection and data processing module includes a color-sensitive sensor and a data acquisition and processing device; the water quality detection and data processing module is used for acquiring images of the mixed solution. R , G , B Channel value extraction and contamination level analysis based on critical relationship method and information entropy theory; The positioning, navigation, and movement control module includes: a BeiDou satellite navigation system, an acoustic obstacle avoidance device, and a displacement device; the positioning, navigation, and movement control module is used to record geographical location, plan movement routes, and drive the displacement of the device cabin; The power supply module provides power support for each functional block; each module transmits data and energy in coordination through infusion pipelines or signal transmission lines to complete fully automatic water quality monitoring and pollution source location.

[0018] As a preferred solution for a fully automated water quality acquisition and positioning system, a distributed monitoring network is constructed using several sets of fully automated water quality acquisition and positioning devices. The distributed monitoring network achieves collaborative analysis of pollution status in multiple regions through data interaction. The distributed monitoring network is used for water environment monitoring tasks in rivers, lakes, oceans, and pollution-prone areas.

[0019] This invention has the following advantages: First, it integrates multiple core technologies, and through the collaboration of dye tracing, color channel analysis, information entropy theory and Beidou positioning, it comprehensively reflects the overall pollution status of water bodies, breaking through the limitations of single parameter monitoring.

[0020] Secondly, it achieves full automation of the sampling, staining, detection, data analysis, and automatic movement processes, eliminating the need for manual intervention, significantly improving monitoring efficiency, and reducing operational risks and costs.

[0021] Third, the pollution area is accurately identified. By using the critical relationship method, ratio analysis, and information entropy quantitative assessment, combined with dynamic path planning, the pollution source can be quickly located with higher positioning accuracy.

[0022] Fourth, its modular design makes it highly adaptable, allowing for standalone operation or the formation of a distributed monitoring network. It is suitable for various scenarios such as rivers, lakes, and pollution-free zones, and has a wide range of applications. Attached Figure Description

[0023] To more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings in the following description are merely exemplary, and those skilled in the art can derive other embodiments based on the provided drawings without creative effort.

[0024] The structures, proportions, sizes, etc. illustrated in this specification are only for the purpose of assisting those skilled in the art in understanding and reading the content disclosed herein, and are not intended to limit the conditions under which the present invention can be implemented. Therefore, they have no substantial technical significance. Any modifications to the structure, changes in the proportions, or adjustments to the size, without affecting the effects and objectives that the present invention can produce, should still fall within the scope of the technical content disclosed in the present invention.

[0025] Figure 1 This is a schematic diagram of a fully automatic water quality acquisition and positioning device provided in Embodiment 1 of the present invention.

[0026] Figure 2 This is a schematic diagram of the data acquisition and processing device in a fully automatic water quality acquisition and positioning detection device provided in Embodiment 1 of the present invention.

[0027] Figure 3 This is a flowchart illustrating a fully automated water quality acquisition and positioning method provided in Embodiment 2 of the present invention.

[0028] Figure 4 This is a schematic diagram of the architecture of a fully automatic water quality acquisition and positioning detection system provided in Embodiment 3 of the present invention.

[0029] Figure 1 The components are as follows: 1. Device compartment; 2. Automatic water sample collection device; 3. Dye dispensing device; 4. Color-sensitive sensor device; 5. Data acquisition and processing device; 6. Infusion pipeline; 7. Storage tank; 8. Third metering pump; 9. Second metering pump; 10. Signal transmission line; 11. Beidou satellite navigation system and acoustic obstacle avoidance device; 12. Displacement device; 13. First metering pump; 14. Power supply system. Detailed Implementation

[0030] The following specific embodiments illustrate the implementation of the present invention. Those skilled in the art can easily understand other advantages and effects of the present invention from the content disclosed in this specification. Obviously, the described embodiments are only some, not all, of the embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0031] Example 1

[0032] See Figure 1 Embodiment 1 of the present invention provides a fully automatic water quality collection and positioning detection device, including a device chamber 1, an automatic water sample collection device 2, a dye dispensing device 3, a color-sensitive sensor 4, and a data acquisition and processing device 5; the automatic water sample collection device 2 is connected to a storage tank 7 via a delivery pipeline 6; the storage tank 7 is connected to the color-sensitive sensor 4 via a third metering pump 8 and the delivery pipeline 6; the dye dispensing device 3 is connected to the delivery pipeline 6 between the automatic water sample collection device 2 and the storage tank 7 via a second metering pump 9 and the delivery pipeline 6; the color-sensitive sensor 4 is connected via a signal transmission line. The data acquisition and processing device 5 communicates with the data acquisition and processing device 5; the data acquisition and processing device 5 is connected to the Beidou satellite navigation system and the acoustic obstacle avoidance device 11 through the signal transmission line 10; the Beidou satellite navigation system and the acoustic obstacle avoidance device 11 are connected to the displacement device 12 that controls the displacement of the device compartment 1; the automatic water sample collection device 2 is equipped with a first metering pump 13 that controls the sampling volume; the device compartment 1 is equipped with a power supply system 14 that supplies power to the device; the displacement device 12 controls the actions of the automatic water sample collection device 2, the dye dispensing device 3, and the overall displacement of the device compartment 1 respectively.

[0033] Specifically, the device compartment 1, as the overall supporting unit, provides installation and fixing space and protection for all internal modules, ensuring stable operation of the device in complex aquatic environments such as rivers and lakes. The automatic water sample collection device 2, as the core of water sample acquisition, has its output end connected to the input end of the storage tank 7 through a sealed infusion pipeline 6. A first metering pump 13 is installed at the connection node between the automatic water sample collection device 2 and the infusion pipeline 6. The quantitative control function of the first metering pump 13 enables the regulation of the sampling volume.

[0034] The output of the dye dispensing device 3 is connected to a branch infusion pipeline 6 via a second metering pump 9. This branch pipeline seamlessly connects to the main infusion pipeline 6 between the automatic water sample collection device 2 and the storage tank 7, ensuring that the dye can be injected into the water sample in the main pipeline and enter the storage tank 7 along with the water sample. The output of the storage tank 7 is connected to the input of the third metering pump 8 via the infusion pipeline 6. The output of the third metering pump 8 is then connected to the inlet of the color-sensitive sensor 4 via the infusion pipeline 6, forming a mixed liquid delivery channel.

[0035] The signal output of the color-sensitive sensor 4 is connected to the signal input of the data acquisition and processing device 5 via a shielded signal transmission line 10, ensuring interference-free transmission of image data. Similarly, the signal output of the data acquisition and processing device 5 is connected to the signal input of the BeiDou satellite navigation system and the acoustic obstacle avoidance device 11 via the signal transmission line 10, enabling bidirectional interaction between control commands and data. The control output of the BeiDou satellite navigation system and the acoustic obstacle avoidance device 11 is connected to the signal input of the displacement device 12, which, through a mechanical transmission structure, is connected to the drive mechanism of the automatic water sample collection device 2, the dye dispensing device 3, and the device compartment 1, respectively, achieving multi-component motion control. Furthermore, the built-in power system 14 within the device compartment 1 is electrically connected to the device via wires, providing stable and continuous power support for the entire device.

[0036] In this embodiment, the data acquisition and processing device 5 is internally equipped with R, G, B The system includes a signal acquisition unit, a critical relationship calculation unit, an information entropy calculation unit, an average information content calculation unit, and a matrix entropy calculation unit.

[0037] Specifically, such as Figure 2 As shown, the data acquisition and processing device 5 serves as the "core brain" of the entire water quality monitoring device, and its internal components include... R, G, B The signal acquisition unit, critical relationship calculation unit, information entropy calculation unit, average information content calculation unit, and matrix entropy calculation unit work in a progressive and collaborative manner in the logical order of "data input-preprocessing-analysis-quantitative evaluation" to construct a complete water quality data processing chain.

[0038] The interaction logic relationships between the units are as follows: R, G, B The signal acquisition unit is the "front-end input module" for data processing. Its output is directly connected to the input of the critical relationship calculation unit, and it is responsible for converting the raw image signal into an analyzable digital signal. The output of the critical relationship calculation unit is divided into two paths: one path is connected to the input of the information entropy calculation unit, and the other path directly outputs the preliminary judgment result of the polluted area, providing a basis for subsequent quantitative analysis. As the core analysis module, the information entropy calculation unit establishes data interaction relationships with the average information content calculation unit and the matrix entropy calculation unit, respectively. By distributing raw processed data, it drives the two sub-units to complete the entropy value calculation in different dimensions. The outputs of the average information content calculation unit and the matrix entropy calculation unit are jointly aggregated to the main control module of the data acquisition and processing device. Combined with geographical location information, the final pollution level assessment result and pollution path map are generated, forming a closed-loop logic of "input-preprocessing-detailed calculation-aggregated output".

[0039] In this embodiment, the color-sensitive sensing device 4 is used to acquire a color signal of a set pixel size and extract the red channel from the color signal. R Green Channel G Blue Channel B The proportion value.

[0040] Specifically, the color-sensitive sensor 4, as the core component for water coloring signal acquisition, integrates high-precision image acquisition, optical signal analysis, and data preprocessing functions. Its core task is to acquire color signals with a set pixel specification and extract a stable and reliable red channel from them. R Green Channel G Blue Channel B The proportional values ​​provide basic optical data for subsequent identification of polluted areas and assessment of pollution levels. Further details are as follows: The device uses an industrial-grade high-resolution color-sensitive sensor as its core detection element, and has a built-in 256 The 256-pixel image acquisition array, with pixel specifications calibrated and verified multiple times in the laboratory, ensures that the acquisition accuracy meets the requirements for RGB channel subdivision extraction while controlling the data volume to avoid transmission and processing delays, thus adapting to the real-time monitoring characteristics of the device. The device contains a standard image acquisition block with a transparent, sealed structure. Its inner wall is treated to prevent reflection and adhesion. After the mixed liquid is injected through the infusion pipe, a uniform liquid layer is formed, ensuring no refraction distortion when light passes through, providing a stable optical environment for color signal acquisition.

[0041] During signal acquisition, the built-in LED supplementary lighting module of the color-sensitive sensor 4 emits a uniform white light source. This light shines perpendicularly onto the mixed liquid within the standard image acquisition block. The reflected light, after absorption and reflection by the mixed liquid, is captured by the image acquisition array of the color-sensitive sensor, converted into an electrical signal, and generated as color image data. To avoid interference from ambient light, the device casing employs a light-shielding design, and the brightness of the supplementary lighting module can be automatically adjusted according to the concentration of the mixed liquid, ensuring that mixed liquids with varying levels of contamination can generate clear color signals.

[0042] After the color signal is generated, the internal signal preprocessing module performs noise reduction on the original image data. It uses a Gaussian filtering algorithm to filter out random noise from pixels and corrects distortion errors at image edges, ensuring the integrity and accuracy of the image data. Subsequently, the signal analysis module initiates a channel separation program. Based on the principle of primary color decomposition, it separates the red, green, and blue light components in the color signal, and calculates the intensity ratio of each color to convert it into corresponding... R, G, B Channel scaling value. This scaling value is expressed in a quantization range of 0-255, for example, the pure red area. R The value is close to 255. G, B The value is close to 0, while the staining mixture... R, G, B The proportion will change regularly with the degree of pollution.

[0043] In addition, the color-sensitive sensor 4 has a built-in reference calibration module, which can periodically call up standard color card data preset in the laboratory for calibration. R, G, B The extraction accuracy of the proportional value is calibrated to avoid measurement errors caused by device aging or changes in ambient temperature. (The extraction is complete.) R, G, B The ratio values ​​are transmitted in real time to the data acquisition and processing device via a shielded signal transmission line. The transmission process uses differential signal transmission to effectively resist electromagnetic interference and ensure that the data is distortion-free in the transmission link, providing high-quality basic data support for subsequent analysis based on the critical relationship method.

[0044] In summary, the working principle of this invention is as follows: After the device is started, the power system 14 first supplies power to each module to ensure that all components are in a ready state. The Beidou satellite navigation system and the acoustic obstacle avoidance device 11 are started simultaneously, locating the current geographical location of the device cabin 1 and recording the coordinate information, while simultaneously detecting the surrounding environment in real time to avoid collision risks.

[0045] Subsequently, the first metering pump 13 starts according to preset parameters, controlling the automatic water sample collection device 2 to collect a quantitative water quality sample from the target water body. The water sample is transported to the storage tank 7 through the infusion pipeline 6. During this process, the second metering pump 9 starts simultaneously, driving the dyeing agent dispensing device 3 to release a standard dose of dye. The dye is injected into the main pipeline through the branch infusion pipeline 6, and after mixing with the water sample, it enters the storage tank 7 together. In the storage tank 7, it is fully mixed by the built-in stirring structure to form a uniform dyeing mixture.

[0046] After the mixture is prepared, the third metering pump 8 is started, pumping the mixture in the storage tank 7 through the delivery pipeline 6 to the standard image acquisition block of the color-sensitive sensor 4. The color-sensitive sensor 4 immediately starts the image acquisition function to acquire 256 The image information is 256 pixels in color and is transmitted in real time to the data acquisition and processing device 5 via the signal transmission line 10.

[0047] After receiving the image information, the data acquisition and processing device 5 quickly extracts the red channel from the image. R Green Channel G and the blue channel B The proportion value, combined with the built-in critical relationship calculation unit and information entropy calculation unit, is used to analyze the critical relationship method and information entropy theory to complete the differentiation of stained and unstained areas and the assessment of the degree of pollution, generating pollution data. Subsequently, the data acquisition and processing device 5 integrates the pollution data with the geographical location information transmitted by the Beidou satellite navigation system and the acoustic obstacle avoidance device 11 to generate a pollution path map.

[0048] The BeiDou satellite navigation system and acoustic obstacle avoidance device 11 plan the optimal movement route based on the pollution path map and send control commands to the displacement device 12. The displacement device 12 drives the device compartment 1 to move towards the low-pollution area, while simultaneously controlling the timing of the automatic water sample collection device 2 and the dyeing agent dispensing device 3 to ensure the continuity of the sampling, staining, and testing processes during the movement. The above process is repeated until the device locates the pollution source, completing the water quality monitoring and pollution location tasks.

[0049] Example 2

[0050] See Figure 3 Embodiment 1 of the present invention provides a fully automated method for collecting, locating, and detecting water quality, comprising the following steps: S1. Deploy the device cabin to the target water body and record the current geographical location information through the Beidou satellite navigation system; S2. Collect water quality samples using an automatic water sample collection device; pump the water quality samples to a storage tank via an infusion pipeline; inject a standard dose of dye into the storage tank via an infusion pipeline using a dyeing agent dispensing device, so that the water quality samples and the dye are fully mixed to form a mixture; transport the mixture to a color-sensitive sensing device via an infusion pipeline and a third metering pump. S3. Image information is acquired through the color-sensitive sensing device; the image information is transmitted to the data acquisition and processing device through the signal transmission line. S4. Extract the red channel from the image information using the data acquisition and processing device. R Green Channel G and the blue channel B The proportion value; based on the proportion value, the stained and unstained areas are distinguished by the critical relationship method to obtain the contaminated area and the uncontaminated area; for the contaminated area, the matrix entropy and average information content are calculated by the information entropy theory; the degree of contamination of the contaminated area is comprehensively evaluated by the matrix entropy and the average information content to obtain the degree of contamination evaluation result; S5. Generate a pollution path map based on the pollution level assessment results and the geographical location information; plan the optimal movement route using the BeiDou satellite navigation system based on the pollution path map; and drive the device cabin to move towards a low-pollution area using a control displacement device based on the optimal movement route. S6. Repeat the water quality sample collection and pollution level assessment operations, and dynamically update the pollution path map until the pollution source is identified.

[0051] In this embodiment, in step S1, the device cabin is deployed to the target water body, and the current geographical location information is recorded through the Beidou satellite navigation system.

[0052] Specifically, firstly, according to the planned target monitoring area, the device cabin is smoothly placed into the target water body using hoisting or deployment equipment, ensuring stable floating and that none of the modules are damaged by water impact. After the device cabin enters the water, the power system automatically starts and supplies power to the BeiDou satellite navigation system. This system quickly searches for and locks onto at least four BeiDou satellites, calculating the current latitude and longitude coordinates of the device cabin using triangulation principles. Simultaneously, the system automatically verifies coordinate accuracy, eliminates abnormal data caused by signal interference, and stores the final determined geographical location information in the comprehensive database of the data acquisition and processing device. This provides an initial spatial reference for subsequent pollution path mapping and movement route planning, achieving a one-to-one correspondence between "monitoring data" and "geographical location."

[0053] In this embodiment, in step S2, image information is acquired by the color-sensitive sensing device; the image information is then transmitted to the data acquisition and processing device via a signal transmission line.

[0054] Specifically, firstly, the data acquisition and processing device sends a sampling command to the automatic water sample collection device. The first metering pump starts and controls the water sample extraction according to the preset sampling volume. The sampling port of the automatic water sample collection device extends into the water body to a preset depth. After collecting a representative sample of the target water body, the water sample is pumped to the storage tank through a sealed infusion pipeline. At the same time, the dye dosing device receives a synchronization command, and the second metering pump is driven to release a standard dose of highly stable and highly soluble dye. The dye is injected into the main pipeline through a branch infusion pipeline and flows into the storage tank along with the water sample. The storage tank has a built-in low-speed stirring mechanism. After starting, it drives the water sample and dye to mix thoroughly, ensuring that the dye is evenly dispersed in the water sample to form a mixture that reflects the pollution status. After mixing, the third metering pump starts at a preset flow rate and smoothly delivers the mixture to the standard image acquisition block of the color-sensitive sensor through a dedicated infusion pipeline. During the delivery process, the anti-fouling treatment on the inner wall of the pipeline avoids residue of the mixture and ensures the accuracy of the detection.

[0055] In this embodiment, in step S3, image information is acquired by the color-sensitive sensing device; the image information is then transmitted to the data acquisition and processing device via a signal transmission line.

[0056] Specifically, after the mixture fills the standard image acquisition block of the color-sensitive sensor, the built-in photoelectric sensor detects the liquid's presence signal and then activates the LED supplementary lighting module, emitting a stable white light source to vertically illuminate the mixture, avoiding interference from ambient light. The color-sensitive sensor has 256... A 256-pixel acquisition array rapidly captures the reflected light signal from the mixed liquid, converting the light signal into an electrical signal to generate a color image that displays the color distribution characteristics of the mixed liquid. Subsequently, a signal preprocessing module performs noise reduction and edge correction on the original image, eliminating random noise and image distortion. The processed image information is transmitted to the data acquisition and processing device in differential signal form via a shielded signal transmission line. During transmission, electromagnetic interference is effectively resisted, ensuring the integrity and distortion-free nature of the image data and providing high-quality raw material for RGB channel extraction.

[0057] In this embodiment, in step S4, the red channel is extracted from the image information by the data acquisition and processing device. R Green Channel G and the blue channel B The proportion value is determined; based on the proportion value, the stained and unstained areas are distinguished by the critical relationship method to obtain the contaminated and uncontaminated areas; for the contaminated areas, the matrix entropy and average information content are calculated by the information entropy theory; the degree of contamination of the contaminated areas is comprehensively evaluated by the matrix entropy and the average information content to obtain the degree of contamination evaluation result.

[0058] Specifically, firstly, the data acquisition and processing device R, G, B The signal acquisition unit parses the received image information and extracts each pixel based on the principle of three primary colors separation. R, G, B The channel ratio values ​​are used to generate a standardized RGB data matrix. Subsequently, the critical relationship calculation unit calls a preset critical relationship expression, combined with... G / R , B / R A ratio threshold is used to analyze the RGB data. Areas with ratios below the threshold are classified as stained areas (i.e., contaminated areas), while areas above the threshold are classified as unstained areas (i.e., uncontaminated areas), and the pixel range of the contaminated areas is marked. Next, the information entropy calculation unit normalizes the contaminated area data, generating an event probability distribution and correlation matrix, which are then transmitted to the average information content calculation unit and the matrix entropy calculation unit, respectively. The average information content reflects the uniformity of contamination distribution, while the matrix entropy calculation reflects the spatial correlation of contamination. Finally, the main control module integrates the two entropy results with the laboratory-calibrated contamination level standards to generate a quantitative assessment of the contamination level, such as light contamination, moderate contamination, or heavy contamination.

[0059] The expression for the critical relationship method is as follows: ; ;

[0060] In the formula, R Red channel; G Provide a green channel; B The blue channel. , , , All of these are fitting parameters.

[0061] In this embodiment, during the process of distinguishing between stained and unstained areas, calculations are performed. G / R ratio and B / R The ratio is used as an auxiliary factor in the judgment; the staining region is described G / R Ratio and the aforementioned B / R The ratios were all lower than those in the unstained areas.

[0062] In this embodiment, the formula for calculating the matrix entropy is: ;

[0063] In the formula, The matrix entropy; KFor one A positive definite matrix usually represents a correlation matrix; The trace of the matrix; d Let be the dimension of the matrix.

[0064] The formula for calculating the average information content is: ;

[0065] In the formula, This represents the average information content. For the event The probability of occurrence; n The total number of possible events; It is a logarithm with base 2.

[0066] In this embodiment, in step S5, a pollution path map is generated based on the pollution level assessment results and the geographical location information; based on the pollution path map, the optimal movement route is planned using the BeiDou satellite navigation system; based on the optimal movement route, the device cabin is driven to move towards a low-pollution area by controlling the displacement device.

[0067] Specifically, firstly, the data acquisition and processing device integrates the pollution level assessment results with the current geographical location information recorded by the BeiDou Navigation Satellite System, marking the pollution level of the current location on an electronic map. Combined with historical data, a preliminary pollution path map is drawn, clearly showing the pollution concentration gradient distribution. Subsequently, the BeiDou Navigation Satellite System analyzes the location of low-pollution areas based on the pollution path map, comprehensively considering factors such as water flow velocity and obstacle distribution to plan the optimal movement route, ensuring the shortest route, highest movement efficiency, and no collision risk. Finally, the BeiDou Navigation Satellite System sends control commands to the displacement device. The displacement device, through a mechanical transmission structure, drives the propellers in the device cabin to move smoothly towards the low-pollution area along the planned route, providing real-time feedback of position information during the movement to ensure accuracy.

[0068] In this embodiment, in step S6, the water quality sample collection and pollution level assessment operations are repeated, and the pollution path map is dynamically updated until the pollution source is identified.

[0069] Specifically, after the device moves to the new location, it immediately repeats the entire process of steps S2-S5: water samples are re-collected at the new location, and after staining, testing, and data analysis, new pollution level assessment results are obtained. The original pollution path map is dynamically updated based on the new geographical location information, and new pollution concentration gradient data is added to make the pollution diffusion trend clearer. After each cycle, the device adjusts its movement target towards areas with higher pollution concentrations. Through multiple iterations, the range of the pollution source is gradually narrowed. When the pollution level at the location collected three consecutive times reaches its peak and tends to stabilize, and the pollution path map shows that the pollution concentration is concentrating at that location, the pollution source is determined to be locked. The device stops moving and sends a positioning signal, completing the monitoring task.

[0070] The application scenarios of this invention are as follows: In the scenario of tracing the source of sudden pollution in rivers, this invention can be quickly deployed to suspected polluted waters. Through fully automated sampling, dyeing tracing and positioning, the source of pollution can be located in a short time, providing timely support for emergency response. In the scenario of monitoring water quality across the entire lake area, this invention can be used as a standalone unit or to form a distributed monitoring network to continuously monitor the pollution status of different areas, dynamically draw pollution path maps, and assist in the comprehensive management of the lake water environment. In the scenario of monitoring nearshore marine pollution, this invention, through the synergistic effect of acoustic obstacle avoidance and BeiDou positioning, resists wind and wave interference, tracks the diffusion paths of ship sewage discharge and land-based pollution, and safeguards nearshore ecological security. In the scenario of industrial wastewater discharge supervision, this invention can be deployed downstream of the enterprise's sewage outlet to monitor the degree of wastewater pollution and the spread range in real time, and automatically record the time period and geographical location of pollution exceeding the standard, providing data basis for environmental law enforcement. In pollution-free zone monitoring scenarios, this invention eliminates the need for manual intervention and completes water quality testing and pollution source location through fully automated operation, thus avoiding personnel safety risks. In the context of protecting drinking water sources in reservoirs, this invention enables routine patrols of the waters surrounding the water source, timely detection of potential pollution hazards and identification of the source, thereby ensuring the safety of drinking water quality.

[0071] It should be noted that the method of this embodiment can also be applied to a distributed scenario, where multiple devices cooperate to complete the task. In such a distributed scenario, one of these devices may execute only one or more steps of the method in this embodiment, and the multiple devices will interact with each other to complete the method described.

[0072] It should be noted that the above description describes some embodiments of this disclosure. Other embodiments are within the scope of the appended claims. In some cases, the actions or steps recorded in the claims can be performed in a different order than that shown in the above embodiments and still achieve the desired result. Furthermore, the processes depicted in the drawings do not necessarily require a specific or sequential order to achieve the desired result. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0073] Example 3

[0074] See Figure 4 Embodiment 2 of the present invention also provides a fully automatic water quality acquisition and positioning detection system, including: a water quality sampling and staining module 001, a water quality detection and data processing module 002, a positioning, navigation and movement control module 003 and a power supply guarantee module 004; The water quality sampling and staining module 001 includes: an automatic water sample collection device, a storage tank, a staining agent dispensing device, a first metering pump, a second metering pump, and a third metering pump; the water quality sampling and staining module is used for quantitative water sample collection, staining agent dispensing, and mixed solution preparation. The water quality detection and data processing module 002 includes: a color-sensitive sensor and a data acquisition and processing device; the water quality detection and data processing module is used for acquiring images of the mixed solution. R , G , B Channel value extraction and contamination level analysis based on critical relationship method and information entropy theory; The positioning, navigation, and movement control module 003 includes: a BeiDou satellite navigation system, an acoustic obstacle avoidance device, and a displacement device; the positioning, navigation, and movement control module is used to record geographical location, plan movement routes, and drive the displacement of the device cabin; The power supply module 004 provides power support for each functional block; each module transmits data and energy in coordination through infusion pipelines or signal transmission lines to complete fully automatic water quality monitoring and pollution source location.

[0075] In this embodiment, a distributed monitoring network is constructed using several sets of fully automated water quality acquisition and positioning devices; the distributed monitoring network achieves collaborative analysis of pollution status in multiple regions through data interaction; the distributed monitoring network is used for water environment monitoring tasks in rivers, lakes, oceans, and pollution-prone areas.

[0076] It should be noted that the information interaction and execution process between the modules of the above system are based on the same concept as the method embodiment in Embodiment 2 of this application, and the resulting technical effects are the same as those in the method embodiment of this application. For details, please refer to the description in the method embodiment shown above in this application, and it will not be repeated here.

[0077] Although the present invention has been described in detail above with general descriptions and specific embodiments, modifications or improvements can be made to it, which will be obvious to those skilled in the art. Therefore, all such modifications or improvements made without departing from the spirit of the present invention fall within the scope of protection claimed by the present invention.

Claims

1. A fully automatic water quality device for collecting, positioning and detecting, characterized in that, The device cabin (1), the water sample automatic collection device (2), the dyeing agent delivery device (3), the color-sensitive sensing device (4) and the data acquisition and processing device (5) are included. The water sample automatic collection device (2) is connected with the liquid storage tank (7) through the liquid delivery pipeline (6); the liquid storage tank (7) is connected with the color-sensitive sensing device (4) through the third metering pump (8) and the liquid delivery pipeline (6). The dyeing agent delivery device (3) is connected with the liquid delivery pipeline (6) between the water sample automatic collection device (2) and the liquid storage tank (7) through the second metering pump (9) and the liquid delivery pipeline (6). The color-sensitive sensing device (4) communicates with the data acquisition and processing device (5) through the signal transmission line (10); the data acquisition and processing device (5) is connected with the Beidou satellite navigation system and the sound wave obstacle avoidance device (11) through the signal transmission line (10). The Beidou satellite navigation system and the sound wave obstacle avoidance device (11) are connected with the displacement device (12) for controlling the displacement of the device cabin (1); the water sample automatic collection device (2) is provided with the first metering pump (13) for controlling the sampling amount; the device cabin (1) is provided with the power supply system (14) for supplying power to the device; the displacement device (12) controls the actions of the water sample automatic collection device (2) and the dyeing agent delivery device (3) and the overall displacement of the device cabin (1) respectively.

2. The fully automatic water quality detecting device of claim 1, wherein, The data acquisition and processing device (5) is internally provided with R 、 G 、 B signal acquisition unit, critical relation calculation unit, information entropy calculation unit, average information quantity calculation unit and matrix entropy calculation unit.

3. The fully automatic water quality detecting device of claim 2, wherein, The color-sensitive sensing device (4) is used to acquire a color signal of a set pixel size and extract the red channel from the color signal. R Green Channel G Blue Channel B The proportion value.

4. A method for automatically collecting, positioning and detecting water quality, characterized in that, It comprises: The device cabin is delivered to the target water body, and the current geographic position information is recorded by the Beidou satellite navigation system; The water quality sample is collected by the water sample automatic collection device; The water quality sample is pumped to the liquid storage tank through the liquid delivery pipeline; the dyeing agent delivery device injects the standard dose of dyeing agent into the liquid storage tank through the liquid delivery pipeline, so that the water quality sample and the dyeing agent are fully mixed to form a mixed liquid; the mixed liquid is transported to the color-sensitive sensing device through the liquid delivery pipeline and the third metering pump; The color-sensitive sensing device acquires images to obtain image information; the image information is transmitted to the data acquisition and processing device through the signal transmission line; The red channel is extracted from the image information using the data acquisition and processing device. R Green Channel G and the blue channel B The proportion value; Based on the ratio value, the dyeing and non-dyeing areas are distinguished by the critical relationship method to obtain the pollution area and the non-pollution area; for the pollution area, the matrix entropy and the average information amount are calculated based on the information entropy theory; the pollution degree of the pollution area is comprehensively evaluated based on the matrix entropy and the average information amount to obtain the pollution degree evaluation result; Based on the pollution degree evaluation result and the geographic position information, a pollution path diagram is generated; based on the pollution path diagram, the Beidou satellite navigation system plans the best moving route; Based on the best moving route, the displacement device drives the device cabin to move to the low pollution area by controlling the displacement device; The water quality sample collection and pollution degree evaluation operations are repeated, and the pollution path diagram is dynamically updated until the pollution source is locked.

5. The method according to claim 4, wherein, In the process of distinguishing the dyeing and non-dyeing areas by the critical relationship method, the expression of the critical relationship method is: ； ； wherein R is the red channel; G is the green channel; B is the blue channel; , , , are fitting parameters.

6. The method according to claim 5, wherein, In the process of distinguishing between stained and unstained areas, calculations are performed. G / R ratio and B / R The ratio is used as an auxiliary factor in the judgment; the staining region is described G / R Ratio and the aforementioned B / R The ratios were all lower than those in the unstained areas.

7. The method according to claim 6, wherein, The calculation formula of the matrix entropy is: ； wherein is the matrix entropy; K is a positive definite matrix, usually denoting a correlation matrix; is the trace of the matrix; d is the dimension of the matrix.

8. The method according to claim 7, wherein, The calculation formula of the average information amount is: ； where is the average information content; is the probability that an event occurs; n is the total number of possible events; is the logarithm to the base 2.

9. A fully automatic water quality sampling, positioning and detecting system, characterized in that, It comprises: The water quality sampling and dyeing module, the water quality detection and data processing module, the positioning navigation and movement control module and the power supply guarantee module are connected through the liquid pipeline or the signal transmission line to realize data and energy transmission and cooperation, and complete the full-automatic water quality monitoring and pollution source positioning. Through a plurality of sets of full-automatic collection positioning detection water quality devices, a distributed monitoring network is constructed; the distributed monitoring network realizes multi-region pollution situation cooperative analysis through data interaction; the distributed monitoring network is used for river, lake, ocean and pollution restricted area water environment monitoring tasks. The water quality detection and data processing module comprises a color-sensitive sensing device and a data acquisition and processing device; the water quality detection and data processing module is used for collecting mixed liquid images, R , G , B channel value extraction and pollution degree analysis based on critical relation method and information entropy theory; ​ ​ 10. The system according to claim 9, wherein the system is fully automatic. ​

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