Water quality standard exceeding early warning method and device, electronic equipment and storage medium

Abstract

The invention relates to the technical field of sewage treatment, in particular to a water quality standard exceeding early warning method and device, electronic equipment and a storage medium, and the method comprises the following steps: collecting current water quality index data of a current sewage treatment station; inputting the current water quality index data into a water quality index prediction model to obtain predicted water quality index data in a future preset time, the water quality index prediction model being obtained by training a preset autoregressive integral moving average model by a water quality index public data set; and if the predicted water quality index data exceeds the preset water quality standard exceeding threshold, generating early warning information according to the predicted water quality index data. Therefore, the problems of long time consumption, incapability of reflecting the water quality change condition in real time, incapability of predicting the water quality change trend and the like in related technologies are solved, and accurate early warning of the water quality standard exceeding condition in the future is realized through data preprocessing and efficient prediction model training by utilizing the existing water quality public data. Therefore, operation and maintenance personnel can take countermeasures in time.

Description

Technical Field

[0001] The present application relates to the technical field of sewage treatment, and in particular to a method, device, electronic equipment and storage medium for early warning of excessive water quality. Background Art

[0002] With the rapid development of industrialization and urbanization, water pollution is becoming increasingly serious, posing a serious threat to human health and the ecological environment. In order to effectively monitor and manage water quality and ensure the sustainable use of water resources, real-time monitoring of water quality exceeding the standard is particularly important.

[0003] In related technologies, water quality monitoring usually relies on regular sampling and analysis by operation and maintenance personnel.

[0004] However, the monitoring methods of related technologies are time-consuming and cannot reflect changes in water quality in real time. In addition, traditional water quality monitoring methods lack the ability to predict water quality change trends, resulting in the inability to take effective response measures in a timely manner when water quality exceeds the standard, which urgently needs to be solved. Summary of the invention

[0005] The present application provides a water quality exceeding standard warning method, device, electronic device and storage medium to solve the problems that the related technology is time-consuming, cannot reflect the water quality change in real time and cannot predict the water quality change trend. By using the existing water quality public data, through data preprocessing and efficient prediction model training, accurate warning of future water quality exceeding standard can be achieved, so as to facilitate operation and maintenance personnel to take countermeasures in time.

[0006] The first embodiment of the present application provides a water quality exceeding standard warning method, comprising the following steps:

[0007] Collect current water quality index data for current wastewater treatment sites;

[0008] Input the current water quality index data into a water quality index prediction model to obtain predicted water quality index data within a preset time in the future, wherein the water quality index prediction model is obtained by training a preset autoregressive integrated moving average (ARIMA) model using a public water quality index data set;

[0009] If the predicted water quality index data exceeds a preset water quality exceeding standard threshold, an early warning message is generated according to the predicted water quality index data.

[0010] According to one embodiment of the present application, before inputting the current water quality index data into the water quality index prediction model, the method further includes:

[0011] Acquire the public water quality index data set, wherein the public water quality index data set includes historical water quality index data of multiple target sewage treatment sites;

[0012] Preprocessing the public water quality index data set, and dividing the preprocessed public water quality index data set into a training set and a validation set according to a preset division ratio;

[0013] Using the training set to train the preset autoregressive integrated moving average model, and using the verification set to verify the preset autoregressive integrated moving average model to obtain a verification result;

[0014] If the verification result meets the preset verification conditions, the preset autoregressive integrated moving average model is used as the water quality index prediction model; otherwise, after readjusting the preset division ratio, the preset autoregressive integrated moving average model is retrained based on the new training set until the new verification result meets the preset verification conditions to obtain the water quality index prediction model.

[0015] According to an embodiment of the present application, preprocessing the public water quality index dataset to obtain the preprocessed public water quality index dataset includes:

[0016] Screening out data that meets a preset screening condition from the public water quality index data set to obtain a screened public water quality index data set;

[0017] Using a preset linear interpolation method to interpolate the data in the screened public water quality index data set to obtain a public water quality index data set after interpolation;

[0018] The time resolution of the data in the water quality index public data set after the interpolation processing is uniformly processed to obtain the pre-processed water quality index public data set.

[0019] According to an embodiment of the present application, after generating early warning information according to the predicted water quality index data, the method further includes:

[0020] Matching a target emergency response strategy from a preset emergency response strategy library according to the warning information;

[0021] Water quality treatment is performed based on the target emergency response strategy, and the warning information and the target emergency response strategy are sent to a preset terminal.

[0022] According to an embodiment of the present application, generating early warning information according to the predicted water quality index data includes:

[0023] Determining the estimated time when water quality exceeds the standard according to the predicted water quality index data and the preset water quality exceeding standard threshold;

[0024] Early warning information is generated based on the predicted water quality index data and the estimated time when the water quality exceeds the standard.

[0025] According to one embodiment of the present application, the current water quality index data includes at least one of temperature, pH value, dissolved oxygen, chemical oxygen demand, ammonia nitrogen and total phosphorus.

[0026] According to the water quality exceeding standard warning method of the embodiment of the present application, the current water quality index data of the current sewage treatment site is input into the water quality index prediction model to obtain the predicted water quality index data within the preset time in the future, wherein the water quality index prediction model is obtained by training the preset autoregressive integral sliding average model with the water quality index public data set; if the predicted water quality index data exceeds the preset water quality exceeding standard threshold, then the warning information is generated according to the predicted water quality index data. Thus, the problems of the relevant technology being time-consuming, unable to reflect the water quality changes in real time, and unable to predict the water quality change trend are solved, and the existing water quality public data is used, through data preprocessing and efficient prediction model training, to achieve accurate warning of future water quality exceeding standard, so as to facilitate the operation and maintenance personnel to take timely countermeasures.

[0027] The second aspect of the present application provides a water quality exceeding standard warning device, comprising:

[0028] The collection module is used to collect the current water quality index data of the current sewage treatment site;

[0029] A model output module, used to input the current water quality index data into a water quality index prediction model to obtain predicted water quality index data within a preset time in the future, wherein the water quality index prediction model is obtained by training a preset autoregressive integrated moving average model using a public data set of water quality indicators;

[0030] The early warning module is used to generate early warning information according to the predicted water quality index data if the predicted water quality index data exceeds a preset water quality exceeding standard threshold.

[0031] According to one embodiment of the present application, before inputting the current water quality index data into the water quality index prediction model, the model output module is further used to:

[0032] Acquire the public water quality index data set, wherein the public water quality index data set includes historical water quality index data of multiple target sewage treatment sites;

[0033] Preprocessing the public water quality index data set, and dividing the preprocessed public water quality index data set into a training set and a validation set according to a preset division ratio;

[0034] Using the training set to train the preset autoregressive integrated moving average model, and using the verification set to verify the preset autoregressive integrated moving average model to obtain a verification result;

[0035] If the verification result meets the preset verification conditions, the preset autoregressive integrated moving average model is used as the water quality index prediction model; otherwise, after readjusting the preset division ratio, the preset autoregressive integrated moving average model is retrained based on the new training set until the new verification result meets the preset verification conditions to obtain the water quality index prediction model.

[0036] According to one embodiment of the present application, the model output module is used to:

[0037] Screening out data that meets a preset screening condition from the public water quality index data set to obtain a screened public water quality index data set;

[0038] Using a preset linear interpolation method to interpolate the data in the screened public water quality index data set to obtain a public water quality index data set after interpolation;

[0039] The time resolution of the data in the water quality index public data set after the interpolation processing is uniformly processed to obtain the pre-processed water quality index public data set.

[0040] According to an embodiment of the present application, after generating warning information according to the predicted water quality index data, the warning module is further used to:

[0041] Matching a target emergency response strategy from a preset emergency response strategy library according to the warning information;

[0042] Water quality treatment is performed based on the target emergency response strategy, and the warning information and the target emergency response strategy are sent to a preset terminal.

[0043] According to one embodiment of the present application, the early warning module is used to:

[0044] Determining the estimated time when water quality exceeds the standard according to the predicted water quality index data and the preset water quality exceeding standard threshold;

[0045] Early warning information is generated based on the predicted water quality index data and the estimated time when the water quality exceeds the standard.

[0046] According to one embodiment of the present application, the current water quality index data includes at least one of temperature, pH value, dissolved oxygen, chemical oxygen demand, ammonia nitrogen and total phosphorus.

[0047] According to the water quality exceeding standard warning device of the embodiment of the present application, the current water quality index data of the current sewage treatment site is input into the water quality index prediction model to obtain the predicted water quality index data within the preset time in the future, wherein the water quality index prediction model is obtained by training the preset autoregressive integral sliding average model with the water quality index public data set; if the predicted water quality index data exceeds the preset water quality exceeding standard threshold, the warning information is generated according to the predicted water quality index data. Thus, the problems of the relevant technology being time-consuming, unable to reflect the water quality changes in real time, and unable to predict the water quality change trend are solved, and the existing water quality public data is used, through data preprocessing and efficient prediction model training, to achieve accurate warning of future water quality exceeding standard, so as to facilitate the operation and maintenance personnel to take timely countermeasures.

[0048] The third aspect of the present application provides an electronic device, comprising: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement the water quality exceeding standard warning method as described in the above embodiment.

[0049] The fourth aspect of the present application provides a computer-readable storage medium on which a computer program is stored. The program is executed by a processor to implement the water quality exceeding standard warning method as described in the above embodiment.

[0050] Additional aspects and advantages of the present application will be given in part in the description below, and in part will become apparent from the description below, or will be learned through the practice of the present application. BRIEF DESCRIPTION OF THE DRAWINGS

[0051] The above and / or additional aspects and advantages of the present application will become apparent and easily understood from the following description of the embodiments in conjunction with the accompanying drawings, in which:

[0052] Figure 1 A flow chart of a water quality exceeding standard warning method provided according to an embodiment of the present application;

[0053] Figure 2 A schematic block diagram of a water quality exceeding standard warning device according to an embodiment of the present application;

[0054] Figure 3 Schematic diagram of the structure of an electronic device according to an embodiment of the present application. DETAILED DESCRIPTION

[0055] The embodiments of the present application are described in detail below, and examples of the embodiments are shown in the accompanying drawings, wherein the same or similar reference numerals throughout represent the same or similar elements or elements having the same or similar functions. The embodiments described below with reference to the accompanying drawings are exemplary and are intended to be used to explain the present application, and should not be construed as limiting the present application.

[0056] The following describes the water quality exceeding standard warning method, device, electronic device and storage medium according to the embodiment of the present application with reference to the accompanying drawings. In view of the problems mentioned in the above background technology, such as long time consumption, inability to reflect water quality changes in real time and inability to predict water quality change trends, the present application provides a water quality exceeding standard warning method, in which the current water quality index data of the current sewage treatment site is input into the water quality index prediction model to obtain the predicted water quality index data within a preset time in the future, wherein the water quality index prediction model is obtained by training a preset autoregressive integral sliding average model with a public data set of water quality indicators; if the predicted water quality index data exceeds the preset water quality exceeding standard threshold, a warning message is generated according to the predicted water quality index data. Thus, the problems of long time consumption, inability to reflect water quality changes in real time and inability to predict water quality change trends in the related technology are solved, and the existing public water quality data is used to achieve accurate warning of future water quality exceeding standard through data preprocessing and efficient prediction model training, so as to facilitate the operation and maintenance personnel to take timely countermeasures.

[0057] Specifically, Figure 1 A schematic flow chart of a water quality exceeding standard warning method provided in an embodiment of the present application.

[0058] like Figure 1 As shown, the water quality exceeding standard early warning method comprises the following steps:

[0059] In step S101, current water quality index data of the current sewage treatment site is collected.

[0060] In some embodiments, the current water quality index data includes at least one of temperature, pH value, dissolved oxygen, chemical oxygen demand, ammonia nitrogen and total phosphorus.

[0061] Optionally, the embodiment of the present application can use an online water quality monitoring instrument, such as a multi-parameter water quality analyzer, to monitor and record in real time the current water quality indicators such as temperature, pH value, dissolved oxygen, chemical oxygen demand (COD, Chemical Oxygen Demand), ammonia nitrogen (NH3-N) and total phosphorus (TP, Total Phosphorus). In addition, the embodiment of the present application can also deploy water quality sensors (such as electrochemical sensors, optical sensors or biosensors, etc.), each sensor is responsible for monitoring one or several water quality parameters, so as to obtain the current water quality index data.

[0062] It should be noted that the above-mentioned method of collecting the current water quality index data of the current sewage treatment site is only exemplary and is not intended to be a limitation of the present application. Technical personnel in this field may adopt other methods in the prior art to collect the current water quality index data of the current sewage treatment site according to actual conditions. To avoid redundancy, it will not be described in detail here.

[0063] In step S102, the current water quality index data is input into a water quality index prediction model to obtain predicted water quality index data within a preset future time, wherein the water quality index prediction model is obtained by training a preset autoregressive integrated moving average model using a public water quality index data set.

[0064] Among them, the preset autoregressive integrated moving average model is a time series prediction model used to predict future values ​​based on historical data. It is suitable for analyzing and predicting time series data with a certain stability or fluctuations within a certain range. It combines the three main elements of autoregression, difference and moving average to capture trends and seasonal changes in the data.

[0065] Specifically, the embodiment of the present application can convert the format of the current water quality index data and convert the current water quality index data into a format acceptable to the water quality index prediction model. For example, the input current water quality index data can be arranged in chronological order and converted into a feature vector form, and then input into the trained water quality index prediction model.

[0066] Furthermore, the water quality index prediction model predicts the water quality index data within a period of time in the future (such as the next few hours or the next few days) based on the input current water quality index data and the trained and learned parameters.

[0067] Furthermore, in some embodiments, before inputting the current water quality index data into the water quality index prediction model, it also includes: obtaining a public data set of water quality indicators, wherein the public data set of water quality indicators includes historical water quality index data of multiple target sewage treatment sites; preprocessing the public data set of water quality indicators, and dividing the preprocessed public data set of water quality indicators into a training set and a verification set according to a preset division ratio; using the training set to train a preset autoregressive integral moving average model, and using the verification set to verify the preset autoregressive integral moving average model to obtain a verification result; if the verification result meets the preset verification condition, the preset autoregressive integral moving average model is used as the water quality index prediction model, otherwise, after readjusting the preset division ratio, the preset autoregressive integral moving average model is retrained based on the new training set until the new verification result meets the preset verification condition to obtain the water quality index prediction model.

[0068] The historical water quality index data include, but are not limited to, temperature, pH value, dissolved oxygen, chemical oxygen demand, ammonia nitrogen, total phosphorus, etc. The preset division ratio may be 7:3, which is not specifically limited here.

[0069] Specifically, the embodiment of the present application can obtain a public data set containing historical water quality index data of multiple target sewage treatment sites by using a public database or an online data set platform, and preprocess the public data set of water quality indicators, and divide the preprocessed public data set of water quality indicators according to a preset division ratio (for example, 70% as a training set and 30% as a validation set). Among them, the training set is used to train a preset autoregressive integrated moving average model, and the validation set is used to evaluate the effect of the preset autoregressive integrated moving average model.

[0070] Furthermore, the preset autoregressive integrated moving average model is trained using the training set to obtain optimal parameters so that the preset autoregressive integrated moving average model can better fit the data in the training set. During the training process, the hyperparameters of the model (such as the order of the autoregressive term, the order of the difference, the order of the moving average term, etc.) can be adjusted according to actual needs to optimize the performance of the model.

[0071] Furthermore, the trained model is verified using the validation set to evaluate the model's predictive ability and generalization ability. Commonly used evaluation indicators may be mean square error, mean absolute error, etc., and preset validation conditions are set to determine whether the validation results achieve the expected results. For example, if the mean square error of the model on the validation set is lower than a certain threshold, the validation result is determined to meet the preset validation conditions, that is, the preset autoregressive integrated moving average model is trained successfully.

[0072] In addition, if the verification result fails to meet the preset verification conditions, it means that the accuracy of the current model is low. It is necessary to readjust the division ratio of the training set and the verification set, and then train the model again with a new training set. After the model is trained, the performance of the model is verified using a new verification set. Repeat the above steps until the verification result of the model on the new verification set meets the preset verification conditions, thereby obtaining a water quality index prediction model.

[0073] Furthermore, in some embodiments, the water quality index public data set is preprocessed to obtain a preprocessed water quality index public data set, including: screening out data that meets preset screening conditions in the water quality index public data set to obtain a screened water quality index public data set; using a preset linear interpolation method to interpolate the data in the screened water quality index public data set to obtain an interpolated water quality index public data set; and uniformly processing the time resolution of the data in the interpolated water quality index public data set to obtain a preprocessed water quality index public data set.

[0074] It is understandable that in order to ensure the quality of the data in the public water quality indicator dataset and thus improve the accuracy and reliability of model training, it is necessary to preprocess the public water quality indicator dataset and filter out data that does not meet the requirements to reduce the impact of outliers and improve the quality of the public water quality indicator dataset.

[0075] The preset screening conditions may be error values, abnormal values ​​or duplicate data, etc., which are not specifically limited here.

[0076] Specifically, first, the data that meets the preset screening conditions in the public data set of water quality indicators is screened out, for example, data points that exceed a reasonable range are identified and screened out to obtain the public data set of water quality indicators after screening. Secondly, for the missing data at certain time points in the public data set of water quality indicators after screening, a preset linear interpolation method is used for interpolation processing to fill in the missing values ​​to obtain the public data set of water quality indicators after interpolation processing. In addition, in addition to using the preset linear interpolation method for interpolation processing, polynomial interpolation, spline interpolation and other methods can also be used for interpolation processing, which are not specifically limited here.

[0077] Finally, in order to ensure that all data in the public water quality index data set have the same time interval, so as to facilitate time series analysis and model training, the embodiment of the present application also needs to uniformly process the time resolution of the data in the public water quality index data set after interpolation processing, and adjust the time intervals of all data to be consistent, so as to obtain the preprocessed public water quality index data set. For example, if hourly data is required, but some data is recorded in minutes, it is necessary to aggregate these data into an hourly average or sum.

[0078] In step S103, if the predicted water quality index data exceeds the preset water quality exceeding standard threshold, warning information is generated according to the predicted water quality index data.

[0079] Among them, the preset water quality exceeding threshold value can be a threshold value set by technical personnel in this field according to the water quality standards of laws and regulations or industry specifications. For example, the pH value exceeding threshold value can be 5.0 or 9.0, and the dissolved oxygen exceeding threshold value can be 2 mg / L, etc., which is not specifically limited here.

[0080] Specifically, the predicted future water quality index data is compared with the preset water quality exceeding threshold. If any predicted water quality index exceeds the preset exceeding threshold, a warning information is generated based on the exceeding index item in the predicted water quality index data.

[0081] Further, in some embodiments, warning information is generated based on predicted water quality index data, including: determining an expected time when water quality exceeds a standard based on the predicted water quality index data and a preset water quality exceeding threshold; and generating warning information based on the predicted water quality index data and the expected time when water quality exceeds a standard.

[0082] Among them, the expected time when water quality exceeds the standard refers to the specific time or time period when the exceeding of the standard is expected to occur.

[0083] Specifically, the values ​​of each water quality index in the predicted water quality index data are compared with the corresponding exceeding thresholds one by one. If the predicted value of a water quality index exceeds the exceeding threshold of the index, then the time point in the future (i.e., the expected time of exceeding the water quality) at which the index will exceed the standard is recorded. After the expected time of exceeding the standard is determined, one or more warning messages are generated based on the predicted water quality index data and the expected time of exceeding the water quality. Each warning message contains the exceeding index item, the exceeding degree (i.e., the specific value of the exceeding) and the expected time of exceeding the standard.

[0084] Furthermore, in some embodiments, after generating warning information based on predicted water quality index data, it also includes: matching a target emergency response strategy from a preset emergency response strategy library based on the warning information; performing water quality processing based on the target emergency response strategy, and sending the warning information and the target emergency response strategy to a preset terminal at the same time.

[0085] Among them, the preset emergency response strategy library contains a variety of emergency response strategies, such as increasing aeration volume, adjusting the dosage of reagents, starting a backup processing unit, strengthening monitoring frequency, etc., which are not specifically limited here. The preset terminal can be a mobile device with communication function, a computer system or an online platform, etc., which are not specifically limited here.

[0086] Specifically, based on the exceeded index, degree of exceeded index, and estimated time of exceeded index in the generated early warning information, the target emergency response strategy that best suits the current situation is selected from the preset emergency response strategy library. For example, if the ammonia nitrogen index is predicted to exceed the standard and the degree of exceeded index is high, the aeration volume needs to be increased immediately and the sewage treatment system needs to be checked for external pollution sources to improve the water quality as soon as possible.

[0087] Furthermore, according to the selected target emergency response strategy, the corresponding water quality treatment measures are immediately initiated. For example, the aeration volume is increased, the dosage of the reagent is adjusted, and the backup treatment equipment is started. While executing the emergency response measures, the changes in water quality indicators are continuously monitored in real time to evaluate the effectiveness of the measures, and necessary adjustments are made according to the actual situation. The warning information and the target emergency response strategy are sent to the preset terminal, such as "Indicator name: ammonia nitrogen; predicted value: 5.2mg / L; exceeding threshold: 5.0mg / L; expected exceeding time: October 2, 2024 12:00; recommended measures: increase the aeration volume, check whether the water inlet is contaminated, and prepare to start the emergency treatment plan.", so as to ensure that relevant personnel can receive the warning information and the corresponding emergency response strategy in time so as to take relevant actions quickly.

[0088] According to the water quality exceeding standard warning method of the embodiment of the present application, the current water quality index data of the current sewage treatment site is input into the water quality index prediction model to obtain the predicted water quality index data within the preset time in the future, wherein the water quality index prediction model is obtained by training the preset autoregressive integral sliding average model with the water quality index public data set; if the predicted water quality index data exceeds the preset water quality exceeding standard threshold, then the warning information is generated according to the predicted water quality index data. Thus, the problems of the relevant technology being time-consuming, unable to reflect the water quality changes in real time, and unable to predict the water quality change trend are solved, and the existing water quality public data is used, through data preprocessing and efficient prediction model training, to achieve accurate warning of future water quality exceeding standard, so as to facilitate the operation and maintenance personnel to take timely countermeasures.

[0089] Next, the water quality exceeding standard warning device proposed in accordance with the embodiment of the present application is described with reference to the accompanying drawings.

[0090] Figure 2 It is a block diagram of a water quality exceeding standard warning device according to an embodiment of the present application.

[0091] like Figure 2 As shown, the water quality exceeding standard warning device 10 includes: a collection module 100, a model output module 200 and a warning module 300.

[0092] Among them, the collection module 100 is used to collect the current water quality index data of the current sewage treatment site; the model output module 200 is used to input the current water quality index data into the water quality index prediction model to obtain the predicted water quality index data within a preset time in the future, wherein the water quality index prediction model is obtained by training a preset autoregressive integral moving average model with a water quality index public data set; the early warning module 300 is used to generate early warning information based on the predicted water quality index data if the predicted water quality index data exceeds the preset water quality exceeding threshold.

[0093] Furthermore, in some embodiments, before inputting the current water quality index data into the water quality index prediction model, the model output module 200 is also used to: obtain a public data set of water quality indicators, wherein the public data set of water quality indicators includes historical water quality index data of multiple target sewage treatment sites; preprocess the public data set of water quality indicators, and divide the preprocessed public data set of water quality indicators into a training set and a verification set according to a preset division ratio; use the training set to train a preset autoregressive integral moving average model, and use the verification set to verify the preset autoregressive integral moving average model to obtain a verification result; if the verification result meets the preset verification condition, the preset autoregressive integral moving average model is used as the water quality index prediction model, otherwise, after readjusting the preset division ratio, the preset autoregressive integral moving average model is retrained based on the new training set until the new verification result meets the preset verification condition to obtain the water quality index prediction model.

[0094] Furthermore, in some embodiments, the model output module 200 is used to: screen out data in the water quality index public data set that meets preset screening conditions to obtain a screened water quality index public data set; use a preset linear interpolation method to interpolate the data in the screened water quality index public data set to obtain an interpolated water quality index public data set; and uniformly process the time resolution of the data in the interpolated water quality index public data set to obtain a preprocessed water quality index public data set.

[0095] Furthermore, in some embodiments, after generating warning information based on the predicted water quality index data, the warning module 300 is also used to: match the target emergency response strategy from a preset emergency response strategy library based on the warning information; perform water quality treatment based on the target emergency response strategy, and send the warning information and the target emergency response strategy to a preset terminal at the same time.

[0096] Furthermore, in some embodiments, the warning module 300 is used to: determine the expected time when water quality exceeds the standard according to the predicted water quality index data and the preset water quality exceeding threshold; and generate warning information based on the predicted water quality index data and the expected time when water quality exceeds the standard.

[0097] Further, in some embodiments, the current water quality index data includes at least one of temperature, pH value, dissolved oxygen, chemical oxygen demand, ammonia nitrogen and total phosphorus.

[0098] It should be noted that the above explanation of the embodiment of the water quality exceeding standard warning method is also applicable to the water quality exceeding standard warning device of this embodiment, and will not be repeated here.

[0099] According to the water quality exceeding standard warning device of the embodiment of the present application, the current water quality index data of the current sewage treatment site is input into the water quality index prediction model to obtain the predicted water quality index data within the preset time in the future, wherein the water quality index prediction model is obtained by training the preset autoregressive integral sliding average model with the water quality index public data set; if the predicted water quality index data exceeds the preset water quality exceeding standard threshold, the warning information is generated according to the predicted water quality index data. Thus, the problems of the relevant technology being time-consuming, unable to reflect the water quality changes in real time, and unable to predict the water quality change trend are solved, and the existing water quality public data is used, through data preprocessing and efficient prediction model training, to achieve accurate warning of future water quality exceeding standard, so as to facilitate the operation and maintenance personnel to take timely countermeasures.

[0100] Figure 3 A schematic diagram of the structure of an electronic device provided in an embodiment of the present application. The electronic device may include:

[0101] A memory 301 , a processor 302 , and a computer program stored in the memory 301 and executable on the processor 302 .

[0102] When the processor 302 executes the program, the water quality exceeding standard warning method provided in the above embodiment is implemented.

[0103] Furthermore, the electronic device further comprises:

[0104] The communication interface 303 is used for communication between the memory 301 and the processor 302 .

[0105] The memory 301 is used to store computer programs that can be run on the processor 302 .

[0106] The memory 301 may include a high-speed RAM memory, and may also include a non-volatile memory (non-volatile memory), such as at least one disk memory.

[0107] If the memory 301, the processor 302 and the communication interface 303 are implemented independently, the communication interface 303, the memory 301 and the processor 302 can be connected to each other through a bus and communicate with each other. The bus can be an Industry Standard Architecture (ISA) bus, a Peripheral Component Interconnect (PCI) bus or an Extended Industry Standard Architecture (EISA) bus. The bus can be divided into an address bus, a data bus, a control bus, etc. For ease of representation, Figure 3Only one thick line is used in the diagram, but this does not mean that there is only one bus or only one type of bus.

[0108] Optionally, in a specific implementation, if the memory 301, the processor 302 and the communication interface 303 are integrated on a chip, the memory 301, the processor 302 and the communication interface 303 can communicate with each other through an internal interface.

[0109] The processor 302 may be a central processing unit (CPU), or an application specific integrated circuit (ASIC), or one or more integrated circuits configured to implement the embodiments of the present application.

[0110] An embodiment of the present application also provides a computer-readable storage medium on which a computer program is stored. When the program is executed by a processor, the above-mentioned water quality exceeding standard warning method is implemented.

[0111] In the description of this specification, the description with reference to the terms "one embodiment", "some embodiments", "example", "specific example", or "some examples" etc. means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present application. In this specification, the schematic representations of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described may be combined in any one or N embodiments or examples in a suitable manner. In addition, those skilled in the art may combine and combine the different embodiments or examples described in this specification and the features of the different embodiments or examples, without contradiction.

[0112] In addition, the terms "first" and "second" are used for descriptive purposes only and should not be understood as indicating or implying relative importance or implicitly indicating the number of the indicated technical features. Therefore, the features defined as "first" and "second" may explicitly or implicitly include at least one of the features. In the description of this application, the meaning of "plurality" is at least two, such as two, three, etc., unless otherwise clearly and specifically defined.

[0113] Although the embodiments of the present application have been shown and described above, it can be understood that the above embodiments are exemplary and cannot be understood as limitations on the present application. Ordinary technicians in this field can change, modify, replace and modify the above embodiments within the scope of the present application.

Claims

1. A water quality exceeding standard early warning method, characterized in that: The following steps are involved: Collect current water quality index data for current wastewater treatment sites; Input the current water quality index data into a water quality index prediction model to obtain predicted water quality index data within a preset time in the future, wherein the water quality index prediction model is obtained by training a preset autoregressive integrated moving average model using a public data set of water quality indicators; If the predicted water quality index data exceeds a preset water quality exceeding standard threshold, an early warning message is generated according to the predicted water quality index data.

2. The method according to claim 1, characterized in that: Before inputting the current water quality index data into the water quality index prediction model, the method further includes: Acquire the public water quality index data set, wherein the public water quality index data set includes historical water quality index data of multiple target sewage treatment sites; Preprocessing the public water quality index data set, and dividing the preprocessed public water quality index data set into a training set and a validation set according to a preset division ratio; Using the training set to train the preset autoregressive integrated moving average model, and using the verification set to verify the preset autoregressive integrated moving average model to obtain a verification result; If the verification result meets the preset verification conditions, the preset autoregressive integrated moving average model is used as the water quality index prediction model; otherwise, after readjusting the preset division ratio, the preset autoregressive integrated moving average model is retrained based on the new training set until the new verification result meets the preset verification conditions to obtain the water quality index prediction model.

3. The method according to claim 2, characterized in that The preprocessing of the water quality index public data set to obtain the preprocessed water quality index public data set includes: Screening out data that meets a preset screening condition from the public water quality index data set to obtain a screened public water quality index data set; Using a preset linear interpolation method to interpolate the data in the screened public water quality index data set to obtain a public water quality index data set after interpolation; The time resolution of the data in the water quality index public data set after the interpolation processing is uniformly processed to obtain the pre-processed water quality index public data set.

4. The method according to claim 1, characterized in that After generating early warning information according to the predicted water quality index data, the method further includes: Matching a target emergency response strategy from a preset emergency response strategy library according to the warning information; Water quality treatment is performed based on the target emergency response strategy, and the warning information and the target emergency response strategy are sent to a preset terminal.

5. The method according to claim 1, characterized in that The generating of early warning information according to the predicted water quality index data comprises: Determining the estimated time when water quality exceeds the standard according to the predicted water quality index data and the preset water quality exceeding standard threshold; Early warning information is generated based on the predicted water quality index data and the estimated time when the water quality exceeds the standard.

6. The method according to any one of claims 1 to 5, characterized in that The current water quality index data includes at least one of temperature, pH value, dissolved oxygen, chemical oxygen demand, ammonia nitrogen and total phosphorus.

7. A water quality exceeding standard warning device, characterized in that: include: The collection module is used to collect the current water quality index data of the current sewage treatment site; A model output module, used to input the current water quality index data into a water quality index prediction model to obtain predicted water quality index data within a preset time in the future, wherein the water quality index prediction model is obtained by training a preset autoregressive integrated moving average model using a public data set of water quality indicators; The early warning module is used to generate early warning information according to the predicted water quality index data if the predicted water quality index data exceeds a preset water quality exceeding standard threshold.

8. The device according to claim 7, characterized in that Before inputting the current water quality index data into the water quality index prediction model, the model output module is further used to: Acquire the public water quality index data set, wherein the public water quality index data set includes historical water quality index data of multiple target sewage treatment sites; Preprocessing the public water quality index data set, and dividing the preprocessed public water quality index data set into a training set and a validation set according to a preset division ratio; Using the training set to train the preset autoregressive integrated moving average model, and using the verification set to verify the preset autoregressive integrated moving average model to obtain a verification result; If the verification result meets the preset verification conditions, the preset autoregressive integrated moving average model is used as the water quality index prediction model; otherwise, after readjusting the preset division ratio, the preset autoregressive integrated moving average model is retrained based on the new training set until the new verification result meets the preset verification conditions to obtain the water quality index prediction model.

9. An electronic device, characterized in that: include: A memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement the water quality exceeding standard warning method as described in any one of claims 1 to 6.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: The program is executed by a processor to implement the water quality exceeding standard warning method as described in any one of claims 1 to 6.

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