CN111473777A - Hydrological monitoring system and method - Google Patents

Hydrological monitoring system and method Download PDF

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CN111473777A
CN111473777A CN202010536129.XA CN202010536129A CN111473777A CN 111473777 A CN111473777 A CN 111473777A CN 202010536129 A CN202010536129 A CN 202010536129A CN 111473777 A CN111473777 A CN 111473777A
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李�杰
刘德虎
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Abstract

The invention discloses a hydrologic monitoring system, which comprises a data acquisition module, a data transmission module, a data storage module, a data processing module and a response module, wherein the data acquisition module is used for acquiring hydrologic data; the invention also discloses a hydrologic monitoring method, which comprises the following steps: obtaining an input sample from a data storage module; transmitting the input sample to a data preprocessing block, preprocessing the input sample, and judging whether to transmit the input sample to a training machine after preprocessing; if not, waiting for finishing the pretreatment; if yes, executing the next step; transmitting the input sample and the initial weight of each component to a training machine to obtain a weight, and storing the weight in a weight library; and the predictor acquires the optimal weight in the weight library, predicts the optimal weight to obtain a predicted value and transmits the predicted value to the output block. The invention has the following advantages and effects: the prediction efficiency is optimized, historical hydrological data sharing of data is achieved through communication, and the purposes of achieving quick communication and timely obtaining hydrological prediction information are achieved.

Description

Hydrological monitoring system and method
Technical Field
The invention relates to the field of hydrology, in particular to a hydrology monitoring system and a hydrology monitoring method.
Background
The hydrologic forecast scientifically forecasts future hydrologic situations (such as peak flow), particularly accurately forecasts disastrous hydrologic phenomena, so that flood control and disaster reduction are realized, and water resources are reasonably developed and utilized. Improving the accuracy of hydrologic prediction is an important content of hydrologic prediction work, and plays a vital role in flood control and disaster reduction, protecting the life and property safety of people, fully exerting hydraulic engineering benefits, improving ecological environment and the like.
The hydrologic monitoring system at the present stage has the problems of low hydrologic prediction efficiency, poor timeliness, time-consuming manual processing and prediction and incapability of meeting flood prevention requirements.
Disclosure of Invention
The invention aims to provide a hydrological monitoring system and a hydrological monitoring method, which are used for optimizing prediction efficiency, realizing data history hydrological data sharing through communication, achieving the purposes of quick communication and timely acquisition of hydrological prediction information.
In order to achieve the aim, the invention provides a hydrologic monitoring system which comprises a data acquisition module, a data transmission module, a data storage module, a data processing module and a response module, wherein the data acquisition module is used for acquiring data;
the data acquisition module consists of a water level station, a rainfall station and a meteorological station and is used for acquiring hydrological information;
the data transmission module is connected between the data acquisition module and the data storage module and transmits hydrological information acquired by the data acquisition module to the data storage module in a communication mode;
the data storage module comprises hydrological information transmitted from the data transmission module and historical hydrological information, and is used for storing and updating the hydrological information;
the data processing module is connected with the data storage module and is used for analyzing hydrological information so as to carry out hydrological forecast;
the response module is connected with the data processing module and triggers a response action based on the conclusion obtained by the data processing module.
The further setting is that: the data processing module comprises a data preprocessing block, a training machine, a weight database, a prediction machine, an event log database and an output block;
the data preprocessing block is connected with the data storage module and is used for preprocessing the acquired hydrological information, wherein the preprocessing comprises interference information elimination, error information discarding and missing information correction;
the training machine is connected with the data preprocessing block and takes known hydrological information as a training sample to adjust the parameters of the training machine so as to enable the output predicted value to be within a set error range; and the weight is obtained after passing through the training machine;
the weight library is connected with the training machine and used for storing the weight obtained after the training machine;
the prediction machine is connected with the weight database and used for predicting the hydrological information which is actually acquired through a group of weights obtained by the self-training machine, and the result of the prediction information is a natural number which is greater than zero;
the event log library is connected with the prediction machine and used for storing predicted historical information, wherein the predicted historical information comprises acquired hydrological information, predicted data information and historical weight;
the output block is connected with the prediction machine, and the prediction information obtained by the prediction machine is compared with the divided warning threshold value, so that the corresponding warning action is triggered.
The invention also provides a hydrologic monitoring method, which comprises the following steps:
step S1, obtaining input sample X from data storage modulei＝{x1，x2，…，xn}；
Step S2, inputting sample Xi＝{x1，x2，…，xnIs passed to the data pre-processing block while on input sample Xi＝{x1，x2，…，xnChecking the integrity of the training data, preprocessing the training data, and judging whether the training data is transmitted to a training machine or not after the preprocessing is finished; if not, waiting for finishing the pretreatment; if yes, executing the next step;
step S3, inputting sample Xi＝{x1，x2，…，xnAnd initial weight ω of each componenti＝{ω1，ω2，…，ωnTransmitting the data to a training machine, training by the training machine, obtaining a weight after training, and storing the weight in a weight library;
and step S4, the prediction machine obtains the optimal weight in the weight library, predicts the optimal weight to obtain a predicted value, transmits the predicted value to an output block, and triggers the corresponding warning action by comparing the predicted value with the divided warning threshold value.
The further setting is that: the step S4 further includes a prediction opportunity to transmit the weight obtained after training to the event log library for subsequent maintenance and debugging.
The further setting is that: the step S4 further includes comparing the real-time weight with the historical weight by a weight library, so as to select an optimal weight, and the optimal weight in the weight library is obtained by the predictor.
The further setting is that: the preprocessing of the data preprocessing block comprises the following steps:
discarding input samples obviously not conforming to the sample rule;
and supplementing missing data in the sample by correction, wherein the correction method adopts a linear interpolation method:
Figure BDA0002537118290000041
in the above formula, xiAnd xjMeasured hydrological data, x, at times i and j, respectivelytIs the data to be interpolated.
The invention has the beneficial effects that:
1. the hydrologic monitoring system can be integrated and optimized through the invention, the whole system is effective and reliable, and the processes of acquisition, data storage, communication and prediction of hydrologic monitoring from the beginning are continuous, so that the efficiency of hydrologic monitoring is improved, the timeliness is improved, automatic processing is used for replacing partial manual operation, the operation is quick, simple and convenient, the processing time is saved, and the flood prevention requirement can be met through the timely communication of signals.
2. In the invention, error signals are effectively eliminated and missing information is corrected through preprocessing, so that the whole prediction process is more accurate, and the reliability is improved.
3. In the invention, the real-time weight and the historical weight can be compared, so that the optimal weight is selected, the training and processing results are more accurate, and the purpose of the most accurate processing result is realized.
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FIG. 1 is a block diagram showing the overall structure of the embodiment;
fig. 2 is a block diagram of a data processing module in the embodiment.
In the figure: 11. a data acquisition module; 12. a data transmission module; 13. a data storage module; 14. a data processing module; 15. a response module; 21. a data preprocessing block; 22. a training machine; 23. a weight database; 24. a prediction machine; 25. an event log repository; 26. and outputting the block.
Detailed Description
The present invention will be described in further detail with reference to the accompanying drawings.
Referring to fig. 1 and 2, the embodiment discloses a hydrologic monitoring system, which includes a data acquisition module 11, a data transmission module 12, a data storage module 13, a data processing module 14 and a response module 15.
The data acquisition module 11 is composed of a water level station, a rainfall station and a meteorological station and is used for acquiring hydrological information.
The data transmission module 12 is connected between the data acquisition module 11 and the data storage module 13, and transmits hydrological information acquired by the data acquisition module 11 to the data storage module 13 in a communication mode; the communication can be carried out in a wired communication mode or a wireless communication mode, and in practical application, two communication modes can be adopted to carry out communication in a mutual backup mode, so that the timeliness of the communication is guaranteed.
The data storage module 13 comprises hydrologic information transmitted from the data transmission module 12 and historical hydrologic information, and is used for storing and updating the hydrologic information; the historical hydrological information also comprises basin basic data, scheduling files, characteristic value statistical data of the annual month and the ten days of the water station, historical flood marshalling and sorting data and the like.
The data processing module 14 includes a data preprocessing block 21, a training machine 22, a weight database 23, a prediction machine 24, an event log database 25, and an output block 26.
The data preprocessing block 21 is connected to the data storage module 13, and is configured to preprocess the acquired hydrologic information, where the preprocessing includes interference information elimination, error information discarding, and missing information correction.
The training machine 22 is connected with the data preprocessing block 21, and the known hydrologic information is used as a training sample to adjust the parameters of the training machine 22 so as to enable the output predicted value to be in a set error range; and will get the weight after passing through the training engine 22.
The weight database 23 is connected to the training machine 22 and is used for storing the weights obtained by the training machine 22.
The predictor 24 is connected with the weight database 23, and predicts the hydrological information actually acquired through a group of weights obtained from the training machine 22, wherein the result of the prediction information is a natural number larger than zero.
The event log library 25 is connected to the prediction machine 24, and is used for storing the predicted historical information, which includes the collected hydrological information, the predicted data information and the existing optimal weight value.
The output block 26 is connected to the predictor 24 and is arranged to trigger a corresponding alert action based on a comparison of the prediction information obtained by the predictor 24 with a partitioned alert threshold.
In this embodiment, the training machine 22 is an AFSVM training machine, and the prediction machine 24 is an SVM prediction machine. The specific process is as follows: the data processing module 14 is connected to the data storage module 13, and is configured to analyze the hydrologic information, so as to perform hydrologic prediction. The response module 15 is connected to the data processing module 14 and triggers a response action based on the conclusion reached by the data processing module 14. The measured hydrological data in the data acquisition module 11 is uploaded to the database of the hydrological central station through the internet by each hydrological branch central point, and the hydrological data in the database is updated in remote areas through an automatic measurement and reporting system by taking satellites and short waves as communication media. The workstation can extract data samples in the data storage bank, train the SVM prediction machine through the AFSVM training machine, store the obtained weight in the weight database 23 after training, and the SVM prediction machine extracts the weight from the weight database 23, automatically calculates a predicted value, and triggers a corresponding alarm mechanism such as e-mail, short message, fax and the like after comparing with the set warning water level.
The embodiment also discloses a hydrologic monitoring method, which is characterized by comprising the following steps of:
step S1, obtaining input sample X from data storage module 13i＝{x1，x2，…，xn}；
Step S2, inputting sample Xi＝{x1，x2，…，xnIs passed to the data pre-processing block 21 while on input samples Xi＝{x1，x2，…，xnChecking the integrity of the training data and preprocessing the training data, and judging whether the training data is transmitted to the training machine 22 or not after the preprocessing is finished; if not, waiting for finishing the pretreatment; if yes, executing the next step;
step S3, inputting sample Xi＝{x1，x2，…，xnAnd initial weight ω of each componenti＝{ω1，ω2，…，ωnIs transferred to and trained by the trainer 22The machine 22 trains to obtain the weight and stores the weight in the weight library 23;
step S4, the prediction machine 24 obtains the optimal weight in the weight database 23, and performs prediction to obtain a predicted value, and transmits the predicted value to the output block 26, and compares the predicted value with the divided warning threshold value, thereby triggering a corresponding warning action.
Further, step S4 includes that the prediction engine 24 will transfer the trained weights to the event log library 25 for subsequent maintenance and debugging.
Further, step S4 includes comparing the real-time weight with the historical weight by the weight library 23, so as to select the optimal weight, and the predictor 24 obtains the optimal weight in the weight library 23.
Further, the preprocessing of the data preprocessing block 21 includes:
discarding input samples obviously not conforming to the sample rule;
and supplementing missing data in the sample by correction, wherein the correction method adopts a linear interpolation method:
Figure BDA0002537118290000071
in the above formula, xiAnd xjMeasured hydrological data, x, at times i and j, respectivelytIs the data to be interpolated.
The above disclosure is only for the purpose of illustrating the preferred embodiments of the present invention, and it is therefore to be understood that the invention is not limited by the scope of the appended claims.

Claims (6)

1. A hydrologic monitoring system characterized in that: comprises a data acquisition module (11), a data transmission module (12), a data storage module (13), a data processing module (14) and a response module (15);
the data acquisition module (11) consists of a water level station, a rainfall station and a meteorological station and is used for acquiring hydrological information;
the data transmission module (12) is connected between the data acquisition module (11) and the data storage module (13), and transmits hydrological information acquired by the data acquisition module (11) to the data storage module (13) in a communication mode;
the data storage module (13) comprises hydrological information transmitted from the data transmission module (12) and historical hydrological information, and is used for storing and updating the hydrological information;
the data processing module (14) is connected with the data storage module (13) and is used for analyzing hydrological information so as to carry out hydrological forecast;
the response module (15) is connected with the data processing module (14) and triggers a response action based on the conclusion made by the data processing module (14).
2. A hydrologic monitoring system according to claim 1 and wherein: the data processing module (14) comprises a data preprocessing block (21), a training machine (22), a weight library (23), a prediction machine (24), an event log library (25) and an output block (26);
the data preprocessing block (21) is connected with the data storage module (13) and is used for preprocessing the acquired hydrological information, wherein the preprocessing comprises interference information elimination, error information discarding and missing information correction;
the training machine (22) is connected with the data preprocessing block (21) and adjusts the parameters of the training machine (22) by taking the known hydrological information as a training sample so as to enable the output predicted value to be in a set error range; and the weight is obtained after passing through the training machine (22);
the weight library (23) is connected with the training machine (22) and is used for storing the weight obtained after the training machine (22);
the prediction machine (24) is connected with the weight library (23), and predicts the hydrological information which is actually acquired through a group of weights obtained by the self-training machine (22), wherein the result of the prediction information is a natural number which is greater than zero;
the event log library (25) is connected with the prediction machine (24) and is used for storing predicted historical information, wherein the predicted historical information comprises collected hydrological information, predicted data information and historical weight;
the output block (26) is connected with the prediction machine (24) and is used for comparing the prediction information obtained by the prediction machine (24) with the divided warning threshold value so as to trigger the corresponding warning action.
3. A hydrologic monitoring method, comprising the steps of:
step S1, obtaining input sample X from data storage module (13)i＝{x1，x2，…，xn}；
Step S2, inputting sample Xi＝{x1，x2，…，xnIs passed to a data pre-processing block (21) while on input samples Xi＝{x1，x2，…，xnChecking the integrity of the training data and preprocessing the training data, and judging whether the training data is transmitted to a training machine (22) or not after the preprocessing is finished; if not, waiting for finishing the pretreatment; if yes, executing the next step;
step S3, inputting sample Xi＝{x1，x2，…，xnAnd initial weight ω of each componenti＝{ω1，ω2，…，ωnThe data are transmitted to a training machine (22), the training machine (22) is used for training, a weight is obtained after training, and the weight is stored in a weight library (23);
and S4, the prediction machine (24) acquires the optimal weight in the weight library (23), predicts the optimal weight to obtain a predicted value, transmits the predicted value to the output block (26), and triggers the corresponding warning action by comparing the predicted value with the divided warning threshold value.
4. A hydrologic monitoring method according to claim 3, characterized in that: the step S4 further includes that the prediction engine (24) transmits the trained weights to the event log library (25) for subsequent maintenance and debugging.
5. A hydrologic monitoring method according to claim 3, characterized in that: the step S4 further includes a weight database (23) for comparing the real-time weight with the historical weight, so as to select an optimal weight, and the prediction machine (24) obtains the optimal weight in the weight database (23).
6. A hydrologic monitoring method according to claim 3, characterized in that: the preprocessing of the data preprocessing block (21) comprises the following steps:
discarding input samples obviously not conforming to the sample rule;
and supplementing missing data in the sample by correction, wherein the correction method adopts a linear interpolation method:
Figure FDA0002537118280000031
in the above formula, xiAnd xjMeasured hydrological data, x, at times i and j, respectivelytIs the data to be interpolated.
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