Water quality detection data online analysis method and system

Abstract

The invention discloses a water quality detection data online analysis method, and belongs to the technical field of water quality detection and intelligent Internet of Things. The water quality detection data online analysis method is suitable for an intelligent water quality detection device. The method comprises the following steps: S1, obtaining water quality parameter data of a target water body; s2, preprocessing the water quality parameter data to generate a standardized data set; the preprocessing comprises data filtering, abnormal value elimination and standardization processing; s3, inputting the standardized data set into an analysis model to obtain an analysis result, wherein the analysis result comprises water quality grade and pollutant standard exceeding early warning information; and S4, transmitting an analysis result to a cloud server and a local monitoring terminal in real time through a communication module, and generating a visual report. Through the mode, the real-time performance, the accuracy and the automation level of water quality detection are remarkably improved.

Description

Technical Field

[0001] The present invention belongs to the technical field of water quality detection and intelligent Internet of Things, and specifically relates to an online analysis method and system for water quality detection data. Background Art

[0002] Water quality testing, as the name suggests, involves mixing the water to be tested with relevant reagents and then performing digestion and / or colorimetric testing to obtain the corresponding indicator data. Traditional water quality testing methods rely primarily on manual labor, with the test data then aggregated and statistically analyzed.

[0003] With the rapid development of science and technology, intelligent water quality detectors have emerged. These devices typically integrate a detection module, a display module, and a control module. These devices can directly test the water being tested. The control module acquires the test results from the detection module in real time and displays them on the display module, ultimately allowing users to access relevant data. However, the test data from these intelligent water quality detectors remains fragmented, requiring manual aggregation of large amounts of test data to generate relevant analysis results. These devices suffer from weak real-time performance, significant lags, and low accuracy and efficiency. Summary of the Invention

[0004] Therefore, the technical problem to be solved by the present invention is how to improve the detection efficiency and accuracy while ensuring the real-time performance of the detection.

[0005] To solve the above technical problems, the present invention provides a method for online analysis of water quality detection data, which is applicable to an intelligent water quality detection device. The method comprises:

[0006] S1: Obtain water quality parameter data of the target water body;

[0007] S2: Preprocessing the water quality parameter data to generate a standardized data set; the preprocessing includes data filtering, outlier removal and standardization;

[0008] S3: Inputting the standardized data set into an analysis model to obtain analysis results, wherein the analysis results include water quality grades and pollutant exceeding standard warning information;

[0009] S4: The analysis results are transmitted to the cloud server and the local monitoring terminal in real time through the communication module, and a visual report is generated.

[0010] In one embodiment, the intelligent water quality detection device includes a delivery module and a detection module, and obtaining water quality parameter data of the target water body specifically includes:

[0011] The target water body and the reagent reacting with the target water body are transported to the detection module via the transport module;

[0012] The detection module detects and analyzes the mixed liquid of the target water body and the reagent to obtain the water quality parameter data; the water quality parameter data includes at least one of chemical oxygen demand, ammonia nitrogen, total phosphorus, total nitrogen, pH value and heavy metal concentration.

[0013] In one embodiment, the detection module includes a digestion unit and a colorimetric unit. The detection module performs detection and analysis on the mixed liquid of the target water body and the reagent to obtain the water quality parameter data, specifically including:

[0014] Determine the water quality of the target water body to determine the detection technology means of the target water body, wherein the detection technology means includes digestion detection and / or colorimetric detection;

[0015] Obtain detection technology means for the target water body and upload them to the cloud server.

[0016] In one embodiment, the digestion unit includes a heating element and a blowing element;

[0017] The target water body detection technical means includes the following: during the digestion detection, the heating element and the blowing element are started and operated;

[0018] The operating parameters of the heating element and the blowing element are obtained so as to control the heating element and the blowing element to operate with the same operating parameters when the same target water body is subsequently detected.

[0019] In one embodiment, the detection module further includes a detection element, and the detection element is used to detect the mixed liquid of the target water body and the reagent;

[0020] The detection data of the detection element is obtained to be combined with other result data to form the water quality parameter data.

[0021] In one embodiment, the preprocessing further includes smoothing the water quality parameter data using a sliding window algorithm;

[0022] and / or, using wavelet transform to remove high-frequency noise from the water quality parameter data;

[0023] And / or, missing data of the water quality parameter data are filled by interpolation based on the spatiotemporal correlation of historical data.

[0024] In one embodiment, inputting the standardized data set into an analysis model specifically includes:

[0025] The analysis model classifies water quality status based on a dynamic threshold algorithm or a machine learning model; wherein the machine learning model is any one of a time series prediction model based on an LSTM neural network, a multi-parameter classification model based on a random forest, and an anomaly detection model based on a support vector machine.

[0026] In one embodiment, the visualization report includes one or more of a real-time data trend graph, a pollutant concentration heat map, and a water quality health index dynamic score.

[0027] In one embodiment, the method further comprises:

[0028] A control instruction is triggered according to the analysis result, and the control instruction is used to adjust the operating parameters of the water treatment equipment or start the emergency treatment process.

[0029] The present invention also provides a water quality detection data online analysis system, comprising:

[0030] A data acquisition module is used to obtain water quality parameter data of the target water body;

[0031] A data processing module, configured to pre-process the water quality parameter data to generate a standardized data set; the pre-processing includes data filtering, outlier removal, and standardization;

[0032] A result analysis module, configured to input the standardized data set into an analysis model to obtain analysis results, wherein the analysis results include water quality grades and warning information on pollutant exceeding standards;

[0033] The result transmission module is used to transmit the analysis results to the cloud server and local monitoring terminal in real time through the communication module, and generate a visual report.

[0034] The technical solution provided by the present invention has the following advantages: the present invention obtains water quality parameter data of the target water body and preprocesses the water quality parameter data to generate a standardized data set, then inputs the standardized data set into the analysis model to obtain analysis results, and finally transmits the analysis results to the cloud server and local monitoring terminal in real time through the communication module, and generates a visual report, which significantly improves the real-time, accuracy and automation level of water quality detection. BRIEF DESCRIPTION OF THE DRAWINGS

[0035] In order to more clearly illustrate the specific embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the specific embodiments or the description of the prior art. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0036] Figure 1 This is a schematic flow chart of the online analysis method for water quality detection data provided in Example 1 of the present invention. DETAILED DESCRIPTION

[0037] The technical solutions of the present invention will be described clearly and completely below in conjunction with the accompanying drawings. Obviously, the embodiments described are only some embodiments of the present invention, not all embodiments. The present invention will be described in detail below with reference to the accompanying drawings and in conjunction with the embodiments. It should be noted that the embodiments of the present invention and the features therein may be combined with each other unless there is a conflict.

[0038] It should be noted that the terms "first", "second", etc. in the description and claims of the present invention and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence.

[0039] In the present invention, unless otherwise specified, the directional words used, such as "up, down, top, bottom", usually refer to the directions shown in the drawings, or to the components themselves in the vertical, perpendicular or gravity direction; similarly, for ease of understanding and description, "inside and outside" refer to the inside and outside relative to the outline of each component itself, but the above directional words are not used to limit the present invention.

[0040] Example 1

[0041] This embodiment provides an online analysis method for water quality testing data, applicable to an intelligent water quality testing device. This intelligent water quality testing device can be used for real-time water quality testing, pollution warning, and automated control in scenarios such as rivers, lakes, and sewage treatment plants. The specific application is not limited here and depends on the actual situation.

[0042] This intelligent water quality testing device comprises a delivery module and a detection module. The delivery module includes a pump and a channel connected to the pump. Operation of the pump allows the target water to enter the channel. The detection module comprises a digestion unit and a colorimetric unit. The digestion unit comprises a tank, a heater disposed within the tank, and a blower disposed outside the tank. The heater heats the liquid, while the blower cools the heated liquid. The detection module also includes a detector for detecting the light transmittance of the liquid within the colorimetric unit.

[0043] The aforementioned heating element, blowing element, and detection element are all conventional structures. For example, the heating element can be a heating wire, the blowing element can be a fan, and the heating element can be a silicon photodiode. It is worth noting that the colorimetric unit usually also includes a light source, and the light emitted by the light source cooperates with the silicon photodiode to perform colorimetric detection.

[0044] Current intelligent water quality testing devices usually display the test results. The test data of this type of intelligent water quality testing instrument is still relatively scattered, and it is still necessary to manually summarize a large amount of test data to form relevant analysis results. The real-time performance is weak, the lag is serious, and the accuracy and efficiency are low.

[0045] In order to solve the above technical problems, the online analysis method of water quality detection data in this embodiment includes at least the following steps:

[0046] S1: Obtain water quality parameter data of the target water body;

[0047] S2: Preprocess the water quality parameter data to generate a standardized data set; preprocessing includes data filtering, outlier removal and standardization;

[0048] S3: Input the standardized data set into the analysis model to obtain analysis results, which include water quality grades and pollutant exceeding standard warning information;

[0049] S4: The analysis results are transmitted to the cloud server and local monitoring terminal in real time through the communication module, and a visual report is generated.

[0050] The target water body may be river water or sewage, which is not specifically limited here and depends on the actual situation.

[0051] Specifically, obtaining the water quality parameter data of the target water body in step S1 specifically includes:

[0052] The target water body and the reagent that reacts with the target water body are transported to the detection module through the transport module;

[0053] The detection module detects and analyzes the mixed liquid of the target water body and the reagent to obtain water quality parameter data; the water quality parameter data includes at least one of chemical oxygen demand, ammonia nitrogen, total phosphorus, total nitrogen, pH value and heavy metal concentration.

[0054] As can be seen from the above, the target water body can be river water or sewage. When the target water body is river water (i.e., when testing river water quality), the water quality parameter data includes COD, ammonia nitrogen, dissolved oxygen data, total phosphorus, total nitrogen, etc. When the target water body is sewage (i.e., when testing sewage), the water quality parameter data includes pH value and heavy metal concentration.

[0055] The detection module detects and analyzes the mixed liquid of the target water and the reagent to obtain water quality parameter data, specifically including:

[0056] Determine the water quality of the target water body and determine the detection technology means of the target water body, including digestion detection and / or colorimetric detection;

[0057] Obtain detection technology means for target water bodies and upload them to the cloud server.

[0058] For example, when testing a target water body for the first time, the system manually sets the water quality of the target water body to require both digestion testing and colorimetric testing. After acquiring the digestion and colorimetric test data in real time, the target water body's detection technology is marked and uploaded to the cloud server. When the same target water body is subsequently detected, the intelligent water quality testing device automatically determines whether the detection technology for the target water body is digestion testing and colorimetric testing, eliminating the need for manual setting, thereby improving the real-time and efficiency of the test.

[0059] As can be seen from the foregoing, the digestion unit includes a heater and a blower. Therefore, when the target water body detection technology includes digestion detection, the heater and blower are activated. The operating parameters of the heater and blower are obtained so that the heater and blower can be controlled to operate with the same operating parameters during subsequent detection of the same target water body. This approach further improves detection efficiency during subsequent detections, ensuring real-time and convenient detection.

[0060] Similarly, as can be seen from the above, the detection module also includes a detection element, which is used to detect the mixed liquid of the target water body and the reagent; and obtains the detection data of the detection element to be combined with other result data to form water quality parameter data.

[0061] The pre-processing in step S2 also includes smoothing the water quality parameter data using a sliding window algorithm;

[0062] and / or, using wavelet transform to remove high frequency noise from water quality parameter data;

[0063] and / or, filling missing data of water quality parameter data by interpolation based on the spatiotemporal correlation of historical data.

[0064] The sliding window smoothing method can be: a window size of 10 minutes to eliminate instantaneous noise. The wavelet denoising method can be: using the Daubechies wavelet basis to remove high-frequency interference. The spatiotemporal interpolation method can be: filling missing values based on the spatiotemporal correlation of historical data (such as weighted averaging of adjacent sensor data). The above three methods are all conventional technologies and are not specifically limited here.

[0065] Inputting standardized data sets into analytical models involves:

[0066] The analysis model classifies water quality status based on a dynamic threshold algorithm or a machine learning model; the machine learning model can be any of a time series prediction model based on an LSTM neural network, a multi-parameter classification model based on a random forest, or an anomaly detection model based on a support vector machine. Similarly, when the machine learning model is a time series prediction model based on an LSTM neural network, it can predict water quality changes over the next 72 hours; when the machine learning model is a multi-parameter classification model based on a random forest, it can identify pollution source types through multi-parameter classification; and when the machine learning model is an anomaly detection model based on a support vector machine, it can detect sudden abnormal events, such as industrial leaks.

[0067] Visual reports include one or more of real-time data trend charts, pollutant concentration heat maps, and dynamic water quality health index scores.

[0068] The online analysis method for water quality detection data of this embodiment also includes:

[0069] Control instructions are triggered based on the analysis results. The control instructions are used to adjust the operating parameters of the water treatment equipment or start the emergency treatment process.

[0070] For example, when the data in the analysis results of the target water body exceeds the standard, the operating parameters of the water quality treatment equipment are adjusted to improve the corresponding water quality.

[0071] The water quality detection data online analysis system provided by the embodiment of the present invention includes:

[0072] A data acquisition module is used to obtain water quality parameter data of the target water body;

[0073] The data processing module is used to pre-process the water quality parameter data to generate a standardized data set; the pre-processing includes data filtering, outlier removal and standardization;

[0074] The result analysis module is used to input the standardized data set into the analysis model to obtain analysis results, including water quality grades and pollutant exceeding standard warning information;

[0075] The result transmission module is used to transmit the analysis results to the cloud server and local monitoring terminal in real time through the communication module and generate a visual report.

[0076] For relevant details, please refer to the above method embodiment.

[0077] It should be noted that the online water quality data analysis system provided in the above embodiment only illustrates the division of the above functional modules when performing network access. In actual applications, the above functions can be assigned to different functional modules as needed, that is, the internal structure of the online water quality data analysis system can be divided into different functional modules to complete all or part of the functions described above. In addition, the online water quality data analysis system and the online water quality data analysis method embodiment provided in the above embodiment are based on the same concept. The specific implementation process is detailed in the method embodiment and will not be repeated here.

[0078] In summary: The present invention obtains water quality parameter data of the target water body and preprocesses the water quality parameter data to generate a standardized data set, then inputs the standardized data set into the analysis model to obtain analysis results, and finally transmits the analysis results to the cloud server and local monitoring terminal in real time through the communication module, and generates a visual report, which significantly improves the real-time, accuracy and automation level of water quality detection.

[0079] Obviously, the embodiments described above are only part of the embodiments of the present invention, rather than all of the embodiments. Based on the embodiments of the present invention, those skilled in the art may make other different forms of changes or modifications without making any creative work, and all of these should fall within the scope of protection of the present invention.

Claims

1. A method for online analysis of water quality detection data, applicable to an intelligent water quality detection device, characterized in that: The method comprises: S1: Obtain water quality parameter data of the target water body; S2: Preprocessing the water quality parameter data to generate a standardized data set; the preprocessing includes data filtering, outlier removal and standardization; S3: Inputting the standardized data set into an analysis model to obtain analysis results, wherein the analysis results include water quality grades and pollutant exceeding standard warning information; S4: The analysis results are transmitted to the cloud server and the local monitoring terminal in real time through the communication module, and a visual report is generated.

2. The method according to claim 1, wherein The intelligent water quality detection device includes a delivery module and a detection module, and the acquisition of water quality parameter data of the target water body specifically includes: The target water body and the reagent reacting with the target water body are transported to the detection module via the transport module; The detection module detects and analyzes the mixed liquid of the target water body and the reagent to obtain the water quality parameter data; the water quality parameter data includes at least one of chemical oxygen demand, ammonia nitrogen, total phosphorus, total nitrogen, pH value and heavy metal concentration.

3. The method according to claim 2, wherein The detection module includes a digestion unit and a colorimetric unit. The detection module performs detection and analysis on the mixed liquid of the target water body and the reagent to obtain the water quality parameter data, specifically including: Determine the water quality of the target water body to determine the detection technology means of the target water body, wherein the detection technology means includes digestion detection and / or colorimetric detection; Obtain detection technology means for the target water body and upload them to the cloud server.

4. The method according to claim 3, wherein The digestion unit includes a heating element and a blowing element; The target water body detection technical means includes the following: during the digestion detection, the heating element and the blowing element are started and operated; The operating parameters of the heating element and the blowing element are obtained so as to control the heating element and the blowing element to operate with the same operating parameters when the same target water body is subsequently detected.

5. The method according to claim 3, wherein The detection module further includes a detection element, which is used to detect the mixed liquid of the target water body and the reagent; The detection data of the detection element is obtained to be combined with other result data to form the water quality parameter data.

6. The method according to claim 1, wherein The pre-processing further comprises smoothing the water quality parameter data by a sliding window algorithm; and / or, using wavelet transform to remove high-frequency noise from the water quality parameter data; And / or, missing data of the water quality parameter data are filled by interpolation based on the spatiotemporal correlation of historical data.

7. The method according to claim 1, wherein The step of inputting the standardized data set into the analysis model specifically includes: The analysis model classifies water quality status based on a dynamic threshold algorithm or a machine learning model; wherein the machine learning model is any one of a time series prediction model based on an LSTM neural network, a multi-parameter classification model based on a random forest, and an anomaly detection model based on a support vector machine.

8. The method according to claim 1, wherein The visualization report includes one or more of a real-time data trend graph, a pollutant concentration heat map, and a water quality health index dynamic score.

9. The method according to any one of claims 1 to 8, characterized in that The method further comprises: A control instruction is triggered according to the analysis result, and the control instruction is used to adjust the operating parameters of the water treatment equipment or start the emergency treatment process.

10. A water quality detection data online analysis system, characterized in that: include: A data acquisition module is used to obtain water quality parameter data of the target water body; A data processing module, configured to pre-process the water quality parameter data to generate a standardized data set; The preprocessing includes data filtering, outlier removal and standardization; A result analysis module, configured to input the standardized data set into an analysis model to obtain analysis results, wherein the analysis results include water quality grades and warning information on pollutant exceeding standards; The result transmission module is used to transmit the analysis results to the cloud server and local monitoring terminal in real time through the communication module, and generate a visual report.

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