Portable water quality pollution intelligent monitoring method and system based on color recognition

Abstract

The invention provides a portable water quality pollution intelligent monitoring method and system based on color identification, and relates to the technical field of water quality index analysis based on color identification, and the method comprises the steps: obtaining an actual reaction color according to a water quality detection point position sequence, and then obtaining a reaction color change trend chart; the method comprises the following steps: dividing a plurality of initial color intervals and variable color intervals, analyzing and sorting detection index data of the initial color intervals and the variable color intervals to obtain a detection index data sequence, carrying out relevance judgment on the initial detection index data sequence, and then carrying out splitting judgment on the initial color intervals to obtain a detection index data sequence; according to the method, multiple initial color update broken links are obtained, the initial color update broken links are subjected to combinatorial analysis, an initial color update sequence is obtained, and accurate recognition of colors and detection index data of multiple target monitoring point positions and analysis of remote online change association influences are achieved.

Description

Technical Field

[0001] This invention proposes a portable intelligent water pollution monitoring method and system based on color recognition, which relates to the field of water quality analysis technology, specifically to the field of water quality index analysis technology based on color recognition. Background Art

[0002] Currently, the detection of ammonia nitrogen in water bodies mainly falls into two categories: sample collection and laboratory testing, and rapid on-site testing. Among these:

[0003] Laboratory testing is more accurate, but less timely; on-site testing is faster, but the results are less clear.

[0004] Although more accurate color-identification nitrogen ammonia concentration acquisition devices exist in the field, traditional methods are difficult to analyze color changes and flow trends of nitrogen ammonia concentration at multiple points in the entire monitoring area, and are also difficult to acquire dynamic trend paths of dynamic water flow. Summary of the Invention

[0005] This invention provides a portable intelligent water pollution monitoring method and system based on color recognition to solve the above-mentioned problems:

[0006] The present invention proposes a portable intelligent water pollution monitoring method and system based on color recognition. The system includes a color acquisition circuit, a microcontroller control circuit, a power supply circuit, a clock circuit, a 4G communication module, a GPS positioning module, a reset circuit, and a liquid crystal display circuit.

[0007] The color signal output terminal of the color acquisition circuit is connected to the color signal input terminal of the microcontroller control circuit. The power signal output terminal of the power supply circuit is connected to the power signal input terminal of the microcontroller control circuit. The clock signal output terminal of the clock circuit is connected to the clock signal input terminal of the microcontroller control power supply. The reset signal output terminal of the reset circuit is connected to the reset signal input terminal of the microcontroller control circuit. The digital signal output terminal of the microcontroller control circuit is connected to the digital signal input terminal of the liquid crystal display circuit. The position signal input terminal of the liquid crystal display circuit is connected to the position signal output terminal of the GPS positioning module. The digital signal output terminal of the liquid crystal display circuit is connected to the 4G communication module.

[0008] Furthermore, the method includes:

[0009] Establish the sequence of water quality monitoring points based on each target monitoring point in the preset water quality monitoring map, obtain the actual reaction color of the target monitoring points, and then obtain the reaction color change trend map of the preset water quality monitoring map.

[0010] The reaction color change trend map is divided into multiple initial color intervals. Based on the initial color intervals, the color change intervals are further divided. The detection index data of the initial color intervals and the color change intervals are analyzed and sorted to obtain the initial detection index data sequence and the color change detection index data sequence. The correlation of the initial detection index data sequence is determined based on the color change detection index data sequence. Then, the initial color intervals are split and determined to obtain multiple initial color update breaks. The initial color update breaks are combined and analyzed to obtain the initial color update sequence.

[0011] The beneficial effects of this invention are as follows: It obtains a detection route, performs detection according to a predetermined route, improving detection efficiency and acquiring a data sequence basis for detection adjustment, enabling standardized data analysis; it acquires the actual reaction color of the target monitoring points, thereby obtaining a reaction color change trend chart of a preset water quality detection map; it visualizes the color changes of multiple target monitoring points and acquires a data basis for data splitting and combination; it divides the changes of the same specifications of every two adjacent target monitoring points, and acquires detection index data through initial color blocks and / or changed color blocks, avoiding errors in acquiring detection indexes caused by inconsistent specifications of each point, facilitating unified analysis of multiple initial color blocks and / or changed color blocks, determining whether two adjacent initial color intervals are related to detection indicators based on nitrogen and ammonia concentration change data, and then splitting and judging unrelated (relatively speaking) initial color intervals to obtain multiple initial color update breaks, thus reducing the data analysis workload of independent blocks while enhancing the correlation of initial detection index data sequences, and performing combined analysis of initial color update breaks to obtain initial color update sequences. Attached Figure Description

[0012] Figure 1 A schematic diagram of a portable intelligent water pollution monitoring method based on color recognition;

[0013] Figure 2 This is a circuit diagram of a color-recognition-based nitrogen and ammonia detection and analysis system in water. Detailed Implementation

[0014] The preferred embodiments of the present invention are described below with reference to the accompanying drawings. It should be understood that the preferred embodiments described herein are only used to illustrate and explain the present invention, and are not used to limit the present invention.

[0015] In one embodiment of the present invention, a portable intelligent water pollution monitoring method and system based on color recognition is proposed, the method comprising:

[0016] Establish the sequence of water quality monitoring points based on each target monitoring point in the preset water quality monitoring map, obtain the actual reaction color of the target monitoring points, and then obtain the reaction color change trend map of the preset water quality monitoring map.

[0017] The reaction color change trend map is divided into multiple initial color intervals. Based on the initial color intervals, changing color intervals are further divided. The detection index data of the initial and changing color intervals are analyzed and sorted to obtain initial and changing detection index data sequences. The correlation of the initial detection index data sequences is determined based on the changing detection index data sequences. Then, the initial color intervals are further split and determined to obtain multiple initial color update break chains. These break chains are then combined and analyzed to obtain the initial color update sequence, such as... Figure 1 As shown.

[0018] The working principle and technical effects of the above technical solution are as follows:

[0019] The color reaction principle of Nessler's reagent spectrophotometry is applied. The color intensity of the reaction result is identified by electronic components of a "color recognizer". The microcontroller displays the three color elements (RGB) data, and then the standard curve of the detection index is calculated and plotted using Euclidean distance (D). Finally, the detection index is reflected in the data in actual water quality rapid testing.

[0020] The detection indicators include ammonia nitrogen concentration or nitrate, etc.

[0021] By establishing the sequence of water quality monitoring points based on each target monitoring point in the preset water quality monitoring map, a monitoring route can be obtained. Monitoring can be carried out according to the predetermined route, improving monitoring efficiency and obtaining a data sequence basis for monitoring adjustment, enabling standard data analysis. The actual reaction color of the target monitoring points can be obtained, thereby obtaining a reaction color change trend map of the preset water quality monitoring map. By obtaining the actual reaction color, and then obtaining a reaction color change trend map composed of multiple actual reaction colors, the color changes of multiple target monitoring points can be visualized, and a data basis for data splitting and combination can be obtained.

[0022] The reaction color change trend map is divided into multiple initial color intervals. By dividing the initial color intervals, color blocks of the same specification are obtained for each target monitoring point, realizing the division of each target monitoring point into the same specification. Based on the initial color intervals, changing color intervals are divided, and color blocks of the same specification are obtained for every two adjacent target monitoring points, realizing the division of every two adjacent target monitoring points into the same specification. The detection index data is analyzed and sorted by the initial color intervals and changing color intervals, realizing the acquisition of detection index data through initial color blocks and / or changing color blocks. This avoids the error in the acquisition of detection index caused by the different specifications of each point, and facilitates the unified analysis of multiple initial color blocks and / or changing color blocks to obtain the initial detection index data sequence and the changing detection index data sequence.

[0023] By determining the correlation between the initial detection index data sequence and the change detection index data sequence, it is possible to determine whether two adjacent initial color intervals are related based on the nitrogen and ammonia concentration change data. Then, the initial color intervals that are not related (relatively speaking) can be split and determined to obtain multiple initial color update breaks. This reduces the amount of data analysis for independent blocks and enhances the correlation of the initial detection index data sequence. The initial color update breaks can be combined and analyzed to obtain the initial color update sequence.

[0024] In one embodiment of the present invention, S1 includes:

[0025] Obtain a preset water quality monitoring map, and determine the target monitoring point location on the preset water quality map; the target monitoring point is a target water quality detection area;

[0026] The optimal detection route is determined based on the target monitoring points, and the order of water quality monitoring points is determined based on the optimal detection route; the optimal detection route is the shortest route for the entire detection process.

[0027] The actual reaction colors at multiple different time points for each target monitoring point were obtained by using a colorimetric reaction method in sequence according to the water quality monitoring points.

[0028] The actual reaction colors of each target monitoring point at the same time point in the sequence of water quality monitoring points are combined to obtain a trend chart of reaction color changes.

[0029] The working principle and technical effects of the above technical solution are as follows:

[0030] A preset water quality monitoring map is obtained in advance. The map is constructed based on Geographic Information System (GIS) technology and integrates the geographic information of water bodies such as rivers, lakes, and reservoirs. By analyzing the map structure, target monitoring points are determined in the preset water quality map. These points represent a target water quality monitoring area.

[0031] By combining the geographical location information of the target monitoring points and taking the shortest total detection distance as the objective, the optimal detection route is determined, the shortest path from the starting point to each monitoring point and finally back is calculated, and the order of water quality monitoring points is determined.

[0032] Nessler's reagent spectrophotometry is used for water quality testing. During on-site monitoring according to the determined sequence of water quality monitoring points, water samples are collected at different time points at each target monitoring point. After adding Nessler's reagent, the system hardware device of this application obtains optical parameters such as absorbance corresponding to the actual reaction color. These parameters have a correlation with the color and can indirectly reflect the water quality indicators.

[0033] The actual reaction colors of each target monitoring point at the same time point, collected in sequence according to the water quality monitoring locations, are combined. The color data of different monitoring points at the same time point are then arranged horizontally to obtain a reaction color change trend chart, which visually displays the color changes of water quality at different monitoring points.

[0034] By determining the optimal detection route, the distance and time that monitoring personnel travel between monitoring points are reduced, improving the overall efficiency of water quality monitoring. This enables the detection of multiple target monitoring points to be completed in a shorter time, reducing manpower, material resources, and time costs.

[0035] By conducting tests at multiple different time points at the target monitoring location and generating a trend chart of color change, the changing patterns of water quality at different monitoring locations can be clearly displayed.

[0036] By analyzing the detection data from multiple monitoring points and combining it with the reaction color change trend map, the preliminary water quality color distribution on the map can be efficiently obtained.

[0037] In one embodiment of the present invention, the step of obtaining the actual reaction color at multiple different time points of each target monitoring point according to the sequence of water quality monitoring points using a colorimetric reaction method includes:

[0038] The color of the reagent is obtained by performing a colorimetric reaction.

[0039] The actual reaction color is obtained by identifying the color of the reagent reaction using a color recognizer.

[0040] The colorimetric reaction methods include Nessler's reagent spectrophotometry, etc.

[0041] This invention can achieve colorimetric reactions by combining various detection indicators with corresponding reagents to obtain a variety of colorimetric reaction colors;

[0042] The color recognition device identifies and analyzes various color reaction colors.

[0043] This invention allows for the setting and selection of detection index options;

[0044] Specific examples are as follows:

[0045] For example, the colorimetric reaction of ammonia nitrogen using Sodium's reagent is colorless to yellow, and the colorimetric reaction of nitrate is colorless to pink. Information on the colorimetric reactions of different indicators can be obtained by purchasing rapid water quality testing kits. Color identifiers can convert gradients such as the saturation of yellow into numerical values; similarly, other colors and other indicators can be detected. Simply change the coefficients of the standard curve (the standard curve is generally a linear equation y = ax + b, modifying a and b) and set the detection indicator options on the machine to achieve the desired detection function.

[0046] The working principle and technical effects of the above solution are as follows: Based on the principle that Nessler's reagent reacts chemically with water components (such as ammonia nitrogen) to form specific colored complexes, the reagent reaction color is obtained through reagent color reaction. This allows for precise identification of the reagent reaction color, converting visual color into quantifiable data, thus improving the accuracy and objectivity of color judgment. After accurately obtaining the actual reaction color, combined with the principle of Nessler's reagent spectrophotometry, the content of water components can be analyzed more accurately. Automated color recognition reduces the subjectivity and time consumption of manual judgment, and can quickly complete the color recognition of a large number of samples, improving overall detection efficiency.

[0047] In one embodiment of the present invention, S2 includes:

[0048] The color intervals are divided according to the actual reaction color of each target monitoring point to obtain multiple initial color intervals in the sequence of water quality monitoring points.

[0049] Obtain half of each adjacent initial color interval, combine them to obtain multiple changing color intervals in the sequence of water quality monitoring points;

[0050] Identify the initial color range to obtain the initial range color data;

[0051] Identify the changing color ranges and obtain the color data for those ranges;

[0052] The initial color data of the interval is sorted according to the order of water quality monitoring points to obtain the initial color data sequence;

[0053] The color data of the changing intervals are sorted according to the order of water quality monitoring points to obtain the color change data sequence;

[0054] Generate an initial detection index data sequence based on the initial color data sequence;

[0055] Generate a change detection index data sequence based on the color change data sequence;

[0056] The initial correlation sequence is obtained by sorting the initial detection index data sequence according to the influence linkage based on the change detection index data sequence.

[0057] The working principle and technical effect of the above technical solution are as follows: the color interval is divided according to the actual reaction color of each target monitoring point to obtain multiple initial color intervals in the sequence of water quality monitoring points; the actual reaction color of each target monitoring point is an initial color interval; by obtaining multiple initial color intervals, the standardized color analysis and sorting of multiple target monitoring points is realized, and the color contrast of multiple intervals is realized.

[0058] Half of each adjacent initial color interval is obtained and combined to obtain multiple changing color intervals in the sequence of water quality monitoring points. By obtaining the changing color intervals, the color changes of adjacent initial color intervals can be identified and monitored. The color change transition data of each pair of adjacent initial color intervals is obtained, thereby understanding the color difference between the two adjacent initial color intervals.

[0059] Identify the initial color range to obtain the initial range color data;

[0060] The color variation range is identified to obtain the color variation range data; the color variation range data includes the average value of the color data of two adjacent color ranges;

[0061] By acquiring initial interval color data and changing interval color data, the intermediate changing color (changing color data) of two adjacent initial color intervals was obtained, thus enabling an understanding of the color change transition.

[0062] The initial color data of the interval is sorted according to the order of water quality monitoring points to obtain the initial color data sequence;

[0063] The color data of the changing intervals are sorted according to the order of water quality monitoring points to obtain the color change data sequence;

[0064] By acquiring color data sequences of preliminary interval color data and color data of changing intervals, the sorting of color data at multiple target monitoring points was understood, enhancing the identifiability and analyzability of color quantification sorting.

[0065] Generate an initial detection index data sequence based on the initial color data sequence;

[0066] A change detection index data sequence is generated based on the change color data sequence; the change detection index data sequence includes the average value of the initial detection index data of color data in two adjacent color ranges; the color data is a single data point obtained by transforming the three data points using Euclidean distance.

[0067] By acquiring initial and changing detection index data, the changes in detection indexes at different target monitoring points were monitored.

[0068] The initial detection index data sequence is sorted by influence linkage based on the change detection index data sequence to obtain the initial correlation sequence. By performing influence linkage sorting, the transition order of mutual influence between various target monitoring points after the dynamic flow of water quality is reordered, thereby obtaining the data influence path based on the dynamic flow changes of water quality.

[0069] In one embodiment of the present invention, the acquisition of the detection index data includes:

[0070] The actual reaction color is converted into a color recognition digital value through an A / D converter, and the color recognition digital value is processed by a microcontroller to obtain RGB color data;

[0071] By generating a standard curve of detection indicators from RGB color data using Euclidean distance, rapid water quality testing information is obtained, and the rapid water quality testing information is remotely uploaded in real time via a 4G communication module.

[0072] The working principle and technical effects of the above solution are as follows: The A / D converter converts the actual reaction color obtained by the color acquisition circuit into a color recognition digital quantity; the microcontroller analyzes and processes this digital quantity to obtain RGB color data; using the Euclidean distance algorithm (which converts three values ​​into one value), based on the known RGB color data corresponding to different detection indicators, the distance between the RGB color data of the sample to be tested and the standard sample is calculated, generating a standard curve for the detection indicator, and then obtaining rapid water quality detection information (such as ammonia nitrogen concentration) from the curve. The combination of A / D conversion and microcontroller processing enables rapid digitization and analysis of color data. Combined with the Euclidean distance algorithm, water quality detection indicators can be quickly derived from the standard curve, improving detection speed and accuracy. The entire process is automated, reducing manual intervention, minimizing human error, and improving the reliability and consistency of detection results. The generated RGB color data and standard curve for the detection indicator enable the storage, retrieval, and further analysis of water quality data.

[0073] In one embodiment of the present invention, the step of performing influence linkage sorting on the initial detection index data sequence based on the change detection index data sequence to obtain the initial correlation sequence includes:

[0074] Each change detection index data in the change detection index data sequence is compared with a preset change detection index threshold to obtain concentration change comparison information; the above threshold is a setting that can be made in this field based on historical experience data.

[0075] Based on the concentration change comparison information, the data of each change detection index are judged to obtain the ammonia nitrogen change judgment information;

[0076] Based on the ammonia nitrogen change determination information of each color change interval, the correlation determination of the color data of the two initial intervals corresponding to the color change interval is performed to obtain the correlation determination information.

[0077] Based on the correlation determination information, the initial color intervals corresponding to the two initial interval color data are split and determined to obtain the initial split determination information;

[0078] The initial color data sequence is combined and updated based on the initial splitting determination information to obtain the initial color update sequence.

[0079] The above-mentioned impact linkage ranking process is to use the online water quality monitoring platform to link and rank the water quality impacts of multiple target monitoring points.

[0080] The working principle and technical effect of the above technical solution are as follows: each change detection index data in the change detection index data sequence is compared with the preset change detection index threshold to obtain concentration change comparison information; the preset change detection index threshold is the standard value of the detection index; by comparing the change data and the threshold, the acquisition of abnormal change data (large transition data) is realized.

[0081] The ammonia nitrogen change determination information is obtained by comparing the concentration changes and judging each change detection index data; the ammonia nitrogen change determination information is used to determine the corresponding interval of abnormal change data.

[0082] Based on the ammonia nitrogen change determination information for each color change interval, the correlation determination is performed on the color data of the two initial intervals corresponding to the color change interval to obtain correlation determination information; when the change detection index data is greater than the preset change detection index threshold, the change detection index data is determined to be an abnormal concentration change, and then the two initial interval color data of the color change interval are determined to be non-correlated; by performing correlation determination through the change detection index data determination information of the color change interval, it is realized that when the change data is large, the correlation is small, and vice versa.

[0083] Based on the correlation determination information, the initial color intervals corresponding to the color data of the two initial intervals are split and determined to obtain the initial split determination information; when the non-correlation determination is obtained, the initial color intervals corresponding to the color data of the two initial intervals are split; by splitting according to correlation, the splitting of two uncorrelated adjacent initial color intervals is realized, thereby realizing the recombination of the originally weakly correlated sequence and enhancing the correlation of the original initial color sequence.

[0084] The initial color data sequence is combined and updated based on the initial splitting determination information to obtain the initial color update sequence.

[0085] In one embodiment of the present invention, the step of combining and updating the initial color data sequence based on the initial splitting determination information to obtain the initial color update sequence includes:

[0086] When the initial combination splitting determination information of each changing color interval is a splitting determination, the initial color interval corresponding to the two initial interval color data of the changing color interval is split to obtain two initial color update broken chains after splitting; when the combination of the two initial color intervals is split, the two initial color intervals still have other initial color intervals of their respective combinations, so what is obtained after splitting is the initial color update broken chain.

[0087] Based on the splitting information of the initial color interval by all the changed color intervals, multiple initial color update breaks are obtained;

[0088] For multiple initial color update broken chains, determine the correlation between every two initial color update broken chains to obtain correlation determination information;

[0089] Based on the correlation determination information, the two initial color update chain breaks are combined and determined to obtain initial combination determination information;

[0090] The initial color data sequence is updated based on the initial combination determination information to obtain the initial color update sequence.

[0091] Obtain the position change information of each initial color interval from the initial association sequence to the initial color update sequence, and calculate the position change coefficient of the initial color interval based on the position change information;

[0092] The formula for calculating the position change coefficient is:

[0093]

[0094] Where QW is the position change coefficient, DI is the position index of the initial color data of the initial color interval in the initial association sequence (the position index of the first interval is 1), CI is the corresponding position index of the initial color interval in the initial color update sequence, and N is the total position index (total "length") of the initial color update sequence.

[0095] Obtain the position change coefficients of all initial color intervals, and calculate the water quality fluctuation anomaly coefficient based on the position change coefficients of all initial color intervals;

[0096] The formula for calculating the water quality fluctuation anomaly coefficient is as follows:

[0097]

[0098] Where SY is the water quality fluctuation anomaly coefficient, q is the total number of initial color intervals, and QW i BO is the position change coefficient of the i-th initial color interval, and BO is the position change threshold;

[0099] BO is the permissible standard for location changes set based on historical water flow experience.

[0100] Based on the location change coefficient, water quality change analysis can be performed on a single target monitoring point;

[0101] The water quality fluctuation anomaly coefficient can be used to perform comprehensive water quality change analysis on all target monitoring points, and then early warning can be issued based on the calculation results.

[0102] The location change coefficient (QW) and water quality fluctuation anomaly coefficient (SY) are used to objectively assess the severity of water quality changes and help to identify pollution events or abnormal situations.

[0103] It supports the splitting, merging, and recombining of initial color ranges to adapt to dynamic changes in water quality at different monitoring points and improve the accuracy of data representation;

[0104] Reduce human intervention and achieve intelligent identification and visual adjustment of water quality fluctuations;

[0105] Suitable for multi-monitoring point linkage analysis.

[0106] The working principle and technical effect of the above technical solution are as follows: traverse each changing color interval, and if its initial combination splitting judgment information is "split judgment", then perform a splitting operation on the initial color interval represented by the two initial interval color data corresponding to the changing color interval. Since the split initial color interval may still have combination relationships with other initial color intervals, the splitting result is an initial color update break, that is, a segment of interval that has been split but is still related to other parts.

[0107] By combining the splitting of the initial color interval by all the changing color intervals, multiple initial color update break chains are obtained.

[0108] For multiple initial color update broken chains, the correlation between each pair is determined to obtain correlation determination information, which indicates whether there is a correlation between each pair of initial color update broken chains and the degree of correlation.

[0109] Based on the correlation determination information, a combination determination is performed on every two initial color update broken chains. It is then determined whether these two broken chains can be recombined into a new color component.

[0110] Based on the initial combination determination information, the initial color data sequence is adjusted. If two initial color update breaks are determined to be combinable, they are merged into a new color interval data and updated in the initial color data sequence; if they are determined not to be combinable, they remain as independent breaks in the sequence, and then their correlation with other breaks is determined to finally obtain the initial color update sequence.

[0111] By splitting the color ranges and making subsequent combination judgments, color ranges can be divided more accurately, unreasonable combinations can be removed, and color data can more accurately reflect the actual situation.

[0112] The initial color update sequence obtained after splitting and combining operations has a more reasonable data structure, reduces the number of two weakly correlated intervals being connected together, and improves the organization efficiency of color data.

[0113] The above splitting method avoids splitting parts that need to be split, thus increasing the amount of data processing, while at the same time enabling the splitting of parts that need to be split, avoiding connections to related parts.

[0114] In one embodiment of the present invention, the step of determining the correlation between every two initial color update break chains to obtain correlation determination information includes:

[0115] Set the initial color range of the broken end of each broken chain to the broken chain endpoint range;

[0116] Obtain the absolute value of the difference between the change detection index data of the change color interval of each initial color update breakpoint interval and the change detection index threshold of each other initial color update breakpoint interval;

[0117] The absolute value of the difference between all change detection index data of the initial color update break and the preset change detection index threshold is used to obtain the initial color update break corresponding to the lowest absolute value of the difference, thus obtaining the relative break.

[0118] Combine the relative broken chains of each initial color update broken chain to obtain the initial color update sequence;

[0119] The changes in ammonia nitrogen concentration and path in the water are obtained through the initial color update sequence.

[0120] The aforementioned correlation determination process involves using an online water quality monitoring platform to determine the water quality correlation between multiple target monitoring points.

[0121] The working principle and technical effect of the above technical solution are as follows: the initial color range of the broken end of each initial color update broken chain is set as the broken chain endpoint range; by obtaining the broken chain endpoint range, the correlation analysis of each endpoint range can be realized, avoiding the complexity of performing correlation analysis on each range.

[0122] The absolute value of the difference between the change detection index data of the changed color interval of each initial color update breakpoint interval and the change detection index data of the changed color interval of each other initial color update breakpoint interval and the preset change detection index threshold is obtained; the breakpoint interval is the initial color interval at the endpoint after the initial color update sequence is broken; by obtaining the absolute value of the difference, the maximum correlation interval can be obtained, which improves the accuracy and uniqueness of the correlation judgment.

[0123] The absolute values ​​of the differences between all change detection index data of the initial color update break chain and the preset change detection index threshold are used to obtain the initial color update break chain corresponding to the lowest absolute value of the difference, thus obtaining a relative break chain. The initial color update break chain corresponding to the lowest absolute value of the difference includes the initial color update break chain corresponding to the break chain endpoint corresponding to the change color interval corresponding to the lowest change detection index data. By obtaining the relative break chain, the unique corresponding interval that most needs to be associated for each break chain endpoint interval can be obtained.

[0124] Combine the relative broken chains of each initial color update broken chain to obtain the initial color update sequence;

[0125] The changes in ammonia nitrogen concentration and path in the water are obtained through the initial color update sequence.

[0126] In one embodiment of the present invention, the system includes a color acquisition circuit, a microcontroller control circuit, a power supply circuit, a clock circuit, a 4G communication module, a GPS positioning module, a reset circuit, and a liquid crystal display circuit;

[0127] The color signal output terminal of the color acquisition circuit is connected to the color signal input terminal of the microcontroller control circuit. The power signal output terminal of the power supply circuit is connected to the power signal input terminal of the microcontroller control circuit. The clock signal output terminal of the clock circuit is connected to the clock signal input terminal of the microcontroller control power supply. The reset signal output terminal of the reset circuit is connected to the reset signal input terminal of the microcontroller control circuit. The digital signal output terminal of the microcontroller control circuit is connected to the digital signal input terminal of the liquid crystal display circuit. The position signal input terminal of the liquid crystal display circuit is connected to the position signal output terminal of the GPS positioning module. The digital signal output terminal of the liquid crystal display circuit is connected to the 4G communication module.

[0128] The working principle and technical effect of the above technical solution are as follows: The system includes a color acquisition circuit, a microcontroller control circuit, a power supply circuit, a clock circuit, a 4G communication module, a GPS positioning module, a reset circuit, and an LCD display circuit;

[0129] The color signal output terminal of the color acquisition circuit is connected to the color signal input terminal of the microcontroller control circuit. The power signal output terminal of the power supply circuit is connected to the power signal input terminal of the microcontroller control circuit. The clock signal output terminal of the clock circuit is connected to the clock signal input terminal of the microcontroller control circuit. The reset signal output terminal of the reset circuit is connected to the reset signal input terminal of the microcontroller control circuit. The digital signal output terminal of the microcontroller control circuit is connected to the digital signal input terminal of the liquid crystal display circuit. The position signal input terminal of the liquid crystal display circuit is connected to the position signal output terminal of the GPS positioning module, and the digital signal output terminal of the liquid crystal display circuit is connected to the 4G communication module.

[0130] The 4G communication module is wirelessly connected to the online water quality monitoring platform.

[0131] Color data is acquired through a color acquisition circuit and output to a microcontroller control circuit for color data processing and conversion of detection index data to obtain water quality detection data. Further analysis and processing of water quality data from multiple target monitoring points is then performed to obtain the analysis results. These results are displayed on an LCD screen, and power, timing, and reset functions are provided by a power supply circuit, a clock circuit, and a reset circuit. This system achieves a complete process of analysis and linkage from color data to nitrogen and ammonia concentration data, improving the accuracy of color acquisition and detection index conversion, and enhancing the linkage of data processing.

[0132] In the urban river water environment management industry, there is a need for rapid on-site water sample testing using portable testing equipment, and a need for a water quality monitoring data platform that reports data in real time. This is because existing water quality monitoring stations suffer from problems such as large data errors and untimely reporting. When a real emergency occurs, such as a sewage overflow at a discharge point, timely detection and reporting to the online monitoring website are particularly important.

[0133] The water quality testing data platform can display information such as time, location, and concentration of the tested substances. Historical records will be retained, and it can also perform upgrade functions such as historical data analysis and water quality change trends at that location.

[0134] By incorporating GPS positioning and 4G communication modules, remote transmission of information collected and analyzed at the current location can be achieved. This enables centralized acquisition and visualization of water quality status at various sampling locations through an online water quality monitoring platform, overcoming the shortcoming of traditional portable testing instruments that cannot report data online.

[0135] In one embodiment of the present invention, the color acquisition circuit is used to acquire color data of target monitoring points on a preset water quality detection map to obtain real-time color reflections;

[0136] The microcontroller control circuit is used to analyze the changes in the detection indicators of the real-time reflected colors of the preset water quality detection map.

[0137] The power supply circuit is used to supply power to the microcontroller control circuit;

[0138] The clock circuit is used to keep time for the microcontroller control circuit;

[0139] The reset circuit is used to reset the microcontroller control circuit;

[0140] The liquid crystal display circuit is used to display the output information of the microcontroller control circuit and to display the output of digital information;

[0141] The GPS positioning module is used to locate the current collection and analysis location and obtain positioning information;

[0142] The 4G communication module is used for remote transmission of location information and displayed digital information.

[0143] The working principle and technical effects of the above technical solution are as follows: The color acquisition circuit includes the TCS3200 color sensor, a full-color color detector, comprising a TCS3200RGB sensing chip and four white LEDs. The TCS3200 can detect and measure almost all visible light within a certain range. It is suitable for colorimeter measurement applications.

[0144] The sample chamber can consist of a color sensor and four ordinary LED light sources. Alternatively, it can be modified to have three color sensors arranged in a triangle (each outputting three data points, and the average value is taken), along with LED light sources whose wavelength can be controlled; for example, when detecting ammonia nitrogen, the light wavelength is 420nm. When the light wavelength is difficult to change, several groups of four can be installed inside the sample chamber, with the corresponding wavelength of light illuminating depending on the selected detection index.

[0145] The microcontroller control circuit can establish the sequence of water quality monitoring points according to each target monitoring point in the preset water quality monitoring map, obtain the actual reaction color of the target monitoring point, and then obtain the reaction color change trend map of the preset water quality monitoring map.

[0146] The reaction color change trend map is divided into multiple initial color intervals. Based on the initial color intervals, the color change intervals are further divided. The detection index data of the initial color intervals and the color change intervals are analyzed and sorted to obtain the initial detection index data sequence and the color change detection index data sequence. The correlation of the initial detection index data sequence is determined based on the color change detection index data sequence. Then, the initial color intervals are split and determined to obtain multiple initial color update breaks. The initial color update breaks are combined and analyzed to obtain the initial color update sequence.

[0147] The power supply circuit is used to supply power to the microcontroller control circuit;

[0148] The clock circuit is used to keep time for the microcontroller control circuit;

[0149] The reset circuit is used to reset the microcontroller control circuit;

[0150] The liquid crystal display circuit is used to display the output information of the microcontroller control circuit.

[0151] The functions of the circuits described above enable dynamic correlation monitoring of nitrogen and ammonia in the water, resulting in more accurate and correlated water quality color data and nitrogen and ammonia concentration data.

[0152] Obviously, those skilled in the art can make various modifications and variations to this invention without departing from its spirit and scope. Therefore, if these modifications and variations fall within the scope of the claims of this invention and their equivalents, this invention also intends to include these modifications and variations.

Claims

1. A portable intelligent water pollution monitoring method based on color recognition, characterized in that, The method includes: S1. Establish the water quality monitoring point sequence according to each target monitoring point in the preset water quality monitoring map, obtain the actual reaction color of the target monitoring point, and then obtain the reaction color change trend map of the preset water quality monitoring map. S2. Divide the reaction color change trend map into multiple initial color intervals, and divide the color change intervals into variable color intervals based on the initial color intervals. Analyze and sort the detection index data of the initial color intervals and variable color intervals to obtain the initial detection index data sequence and the variable detection index data sequence. Determine the correlation of the initial detection index data sequence based on the variable detection index data sequence, and then split and determine the initial color intervals to obtain multiple initial color update breaks. Perform a combined analysis on the initial color update breaks to obtain the initial color update sequence.

2. The portable intelligent water pollution monitoring method based on color recognition according to claim 1, characterized in that, S1 includes: Obtain a preset water quality monitoring map and determine the target monitoring points on the preset water quality map; Determine the optimal detection route based on the target monitoring points, and determine the sequence of water quality monitoring points based on the optimal detection route; The actual reaction colors at multiple different time points for each target monitoring point were obtained by using a colorimetric reaction method in sequence according to the water quality monitoring points. The actual reaction colors of each target monitoring point at the same time point in the sequence of water quality monitoring points are combined to obtain a trend chart of reaction color changes.

3. The portable intelligent water pollution monitoring method based on color recognition according to claim 2, characterized in that, The method of obtaining the actual reaction color at multiple different time points for each target monitoring point according to the order of water quality monitoring points using a colorimetric reaction method includes: The color of the reagent is obtained by performing a colorimetric reaction. The actual reaction color is obtained by identifying the color of the reagent reaction using a color recognizer.

4. The portable intelligent water pollution monitoring method based on color recognition according to claim 1, characterized in that, S2 includes: The color intervals are divided according to the actual reaction color of each target monitoring point to obtain multiple initial color intervals in the sequence of water quality monitoring points. Obtain half of each adjacent initial color interval, combine them to obtain multiple changing color intervals in the sequence of water quality monitoring points; Identify the initial color range to obtain the initial range color data; Identify the changing color ranges and obtain the color data for those ranges; The initial color data of the interval is sorted according to the order of water quality monitoring points to obtain the initial color data sequence; The color data of the changing intervals are sorted according to the order of water quality monitoring points to obtain the color change data sequence; Generate an initial detection index data sequence based on the initial color data sequence; Generate a change detection index data sequence based on the color change data sequence; The initial correlation sequence is obtained by sorting the initial detection index data sequence according to the influence linkage based on the change detection index data sequence.

5. The portable intelligent water pollution monitoring method based on color recognition according to claim 4, characterized in that, The acquisition of the detection index data includes: The actual reaction color is converted into a color recognition digital value through an A / D converter, and the color recognition digital value is processed by a microcontroller to obtain RGB color data; By generating a standard curve of detection indicators from RGB color data using Euclidean distance, rapid water quality testing information can be obtained.

6. The portable intelligent water pollution monitoring method based on color recognition according to claim 4, characterized in that, The step of sorting the initial detection index data sequence based on the change detection index data sequence to obtain the initial correlation sequence includes: Each change detection index data in the change detection index data sequence is compared with a preset change detection index threshold to obtain concentration change comparison information; Based on the concentration change comparison information, the data of each change detection index are judged to obtain the ammonia nitrogen change judgment information; Based on the ammonia nitrogen change determination information of each color change interval, the correlation determination of the color data of the two initial intervals corresponding to the color change interval is performed to obtain the correlation determination information. Based on the correlation determination information, the initial color intervals corresponding to the two initial interval color data are split and determined to obtain the initial split determination information; The initial color data sequence is combined and updated based on the initial splitting determination information to obtain the initial color update sequence.

7. The portable intelligent water pollution monitoring method based on color recognition according to claim 6, characterized in that, The step of combining and updating the initial color data sequence based on the initial splitting determination information to obtain the initial color update sequence includes: When the initial combination splitting determination information for each changing color interval is a splitting determination, the initial color interval corresponding to the two initial interval color data corresponding to the changing color interval is split to obtain the two initial color update broken chains after splitting. Based on the splitting information of the initial color interval by all the changed color intervals, multiple initial color update breaks are obtained; For multiple initial color update broken chains, determine the correlation between every two initial color update broken chains to obtain correlation determination information; Based on the correlation determination information, the two initial color update chain breaks are combined and determined to obtain initial combination determination information; The initial color data sequence is updated based on the initial combination determination information to obtain the initial color update sequence.

8. The portable intelligent water pollution monitoring method based on color recognition according to claim 7, characterized in that, The process of determining the correlation between every two initial color update break chains to obtain correlation determination information includes: Set the initial color range of the broken end of each broken chain to the broken chain endpoint range; Obtain the absolute value of the difference between the change detection index data of the change color interval of each initial color update breakpoint interval and the change detection index threshold of each other initial color update breakpoint interval; The absolute value of the difference between all change detection index data of the initial color update break and the preset change detection index threshold is used to obtain the initial color update break corresponding to the lowest absolute value of the difference, thus obtaining the relative break. Combine the relative broken chains of each initial color update broken chain to obtain the initial color update sequence; The changes in ammonia nitrogen concentration and path in the water are obtained through the initial color update sequence.

9. A system for implementing the portable intelligent water pollution monitoring method based on color recognition as described in claim 1, characterized in that, The system includes a color acquisition circuit, a microcontroller control circuit, a power supply circuit, a clock circuit, a 4G communication module, a GPS positioning module, a reset circuit, and an LCD display circuit. The color signal output terminal of the color acquisition circuit is connected to the color signal input terminal of the microcontroller control circuit. The power signal output terminal of the power supply circuit is connected to the power signal input terminal of the microcontroller control circuit. The clock signal output terminal of the clock circuit is connected to the clock signal input terminal of the microcontroller control power supply. The reset signal output terminal of the reset circuit is connected to the reset signal input terminal of the microcontroller control circuit. The digital signal output terminal of the microcontroller control circuit is connected to the digital signal input terminal of the liquid crystal display circuit. The position signal input terminal of the liquid crystal display circuit is connected to the position signal output terminal of the GPS positioning module. The digital signal output terminal of the liquid crystal display circuit is connected to the 4G communication module.

10. The system of the portable intelligent water pollution monitoring method based on color recognition according to claim 9, characterized in that, The color acquisition circuit is used to acquire color data of target monitoring points on a preset water quality detection map to obtain real-time color reflections. The microcontroller control circuit is used to analyze the changes in the detection indicators of the real-time reflected colors of the preset water quality detection map. The power supply circuit is used to supply power to the microcontroller control circuit; The clock circuit is used to keep time for the microcontroller control circuit; The reset circuit is used to reset the microcontroller control circuit; The liquid crystal display circuit is used to display the output information of the microcontroller control circuit and to display the output of digital information; The GPS positioning module is used to locate the current collection and analysis location and obtain positioning information; The 4G communication module is used for remote transmission of location information and displayed digital information.

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